Mega Themes

Highlights The odds of a significant reversal in the current structural downtrend of China's manufacturing productivity growth are low. Meanwhile, the country's manufacturing sector remains highly competitive in the global goods markets. The extent of China's manufacturing productivity growth will largely rely on the scale of its research and development (R&D) investment. China's high-tech sector will likely experience higher productivity growth than other traditional manufacturing sectors, including textiles and metals manufacturing. Feature By definition, increases in productivity1 allow a country to produce greater output for the same level of input, which boosts profits and ultimately improves economic growth and household living standards. In the context of the post-1990 "economic miracle" in China, persistently positive productivity growth has indeed drastically improved the nation's wealth and living standards. Over the past 10 years, however, China's productivity growth has actually decelerated significantly, which carries worrying implications for the future (Chart I-1). Given that productivity is a country's key source of economic growth and competitiveness, two important questions arise: 1. Will there be meaningful improvement in China's productivity growth over the next five years (Chart I-2)? Chart I-1China: Decelerating Productivity Growth China: Decelerating Productivity Growth China: Decelerating Productivity Growth Chart I-2Any Possibility Of A Productivity Boom Ahead? Any Possibility Of A Productivity Boom Ahead? Any Possibility Of A Productivity Boom Ahead? 2. Is China's competitiveness on a declining trajectory (Chart I-3)? In this report we focus on answering these questions as they pertain to China's manufacturing sector, which is still a very important part of the country's economic engine. We conclude that while the odds of a meaningful reversal of the downtrend in China's manufacturing productivity growth are low, Chinese manufacturers are unlikely to experience major losses in global market share. Yet, this underscores the importance of re-orienting China away from the "old economy" model and the difficulty policymakers continue to face in doing so. A long-term shift away from the country's investment-intensive economic sectors is a clear negative for traditional "China plays" such as industrial commodities and emerging market stocks. China's Productivity Growth Downtrend: A Meaningful Reversal Ahead? When examining trends in productivity, measurement issues frequently come into play. For China, we have presented three measures of labor productivity growth (Chart I-1 on the first page). All three exhibit a similar pattern since the early 1990s. However, in the past two years, some divergences have occurred among the three, with the National Bureau Of Statistics (NBS) and Conference Board data showing slight improvement, as opposed to the World Bank data, which declined sharply in 2017. We tend to rely on the Conference Board data over the World Bank, and the recent rebound in the former seems to better reflect both improved manufacturing output and a significant reduction in the number of employees since late 2015 (Chart I-4). Chart I-3Will China's Competitiveness Decline? Will China's Competitiveness Decline? Will China's Competitiveness Decline? Chart I-4Significant Reduction In Manufacturing Workers Significant Reduction In Manufacturing Workers Significant Reduction In Manufacturing Workers In order to understand the outlook for labor productivity, it is first and foremost important to understand what has already occurred. Chart I-1 on page 1 shows that the Conference Board's estimate of Chinese labor productivity growth decelerated significantly from 2008 to 2015, which in our judgement was caused by strong growth in employment, falling manufacturing output growth due to weaker global demand for goods following the 2008 global financial crisis, and, finally, diminishing returns from global technological innovation in the past 30 years. Looking forward over the next five years, several factors point to the conclusion that productivity growth will stay positive but that the odds of a meaningful reversal of the downtrend is low: First, further declines in the number of manufacturing-sector workers are likely to be limited. The manufacturing sector accounts for nearly 90% of total jobs in the industrial sector. Since December 2015, China's supply side reform efforts as well as the increased adoption of automation and technology have already resulted in a 15% decline in the number of manufacturing sector jobs, with employee cuts occurring across all 30 manufacturing sub-sectors covered by the NBS. As such, the lion's share of productivity gains from job cuts has probably occurred already. In fact, since the beginning of this year, the number of employees in the manufacturing sector has actually increased by 0.5%, with positive growth in two-thirds of the 30 manufacturing sub-sectors. Second, overall improvement in manufacturing output volume has been moderate in the past two years, a period when global import volumes have accelerated. Production volumes in nearly half of the 90 major manufacturing product categories contracted during the economic downturn period of 2014-2015. In comparison, about 40% still had negative output growth over the recovery period of 2015-2017 (Chart I-5). Chart I-5Manufacturing Output: Moderate Improvement China's Manufacturing Sector: Don't Bet On A Productivity Boom China's Manufacturing Sector: Don't Bet On A Productivity Boom The likelihood of continued de-leveraging and restructuring will constrain domestic demand growth, while escalating trade wars may even cut external demand for Chinese products. This will create tough headwinds for the Chinese manufacturing sector over the next several years. Third, we examined productivity growth of a sample of nine manufacturing sub-sectors (out of 30) by using key product output volumes divided by the number of employees in each respective sector. The results show that productivity growth for nearly all of the sub-sectors is currently running below 5%, while in some sectors it is actually contracting. The "computers, communication and other electronic equipment" sector is the biggest export sector for China, accounting for over 40% of total export value in U.S. dollars. This is one of the most important high-tech sectors the country is aiming to develop. However, even within this sector, different products show diverging productivity growth. For example, semiconductor integrated circuits are growing at a strong 15% rate, while mobile handsets are contracting at a 13% rate (Chart I-6). Chart I-7 and Chart I-8 drive home the point: productivity growth was positive in four high-value-added manufacturing sectors and four low-value-added commodity process sectors, but most of these sectors' productivity growth was less than 5%. Chart I-6Diverging Productivity Growth Diverging Productivity Growth Diverging Productivity Growth Chart I-7Low Productivity Growth In High-Value-Added ##br##Manufacturing Sectors... Low Productivity Growth In High-Value-Added Manufacturing Sectors... Low Productivity Growth In High-Value-Added Manufacturing Sectors... Chart I-8...And In Low-Value-Added Sectors As Well ...And In Low-Value-Added Sectors As Well ...And In Low-Value-Added Sectors As Well Fourth, we expect Chinese R&D expenditure growth to strengthen, given the government's goal of turning the country into a global leader in digital technology and innovation (Chart I-9, top and middle panels). Chart I-9Rebounding R&D Expenditures Vs. Falling FAIs Rebounding R&D Expenditures Vs. Falling FAIs Rebounding R&D Expenditures Vs. Falling FAIs However, in terms of fixed asset investment (FAI) in the manufacturing sector, which is a much broader investment measure than the R&D investment, its growth already dropped to 3% last year, significantly lower than the compound annual growth rate of 24% over the 2004-2014 period (Chart I-9, bottom panel). Manufacturing FAI growth will likely stay within the range of 0-5% and to some extent will counteract any increases in productivity growth from increased R&D spending. Bottom Line: The recent improvement in China's labor productivity reflects - at least in part - short-term factors that appear to have run their course. China's manufacturing productivity growth will stay low over the coming years, and a meaningful reversal of this downtrend is unlikely. Sustaining Competitiveness Faltering productivity growth, however, does not mean fading competitiveness. For instance, while China's productivity growth plunged from 14.3% in 2007 to 7% in 2017, the country's contribution to global exports climbed from 7.3% to 10.5% during the same period (Chart I-3 on page 2). Meanwhile, Chinese high-tech exports have also gained global market share (Chart I-10). More recently, however, China's exports have lost some global market share both in overall terms and in the high-tech sector over the past two years. Does this herald a declining trajectory in China's manufacturing competitiveness? In our view, the answer is no. We believe China's manufacturing sector will remain highly competitive in the global marketplace: While clearly trending lower, China's productivity growth was the highest among major developed and emerging economies last year (Chart I-11, top panel). It also has always been well above the global average (Chart I-11, bottom panel). Chart I-10Competitive Chinese High-Tech Products Competitive Chinese High-Tech Products Competitive Chinese High-Tech Products Chart I-11China's Productivity Growth: Higher ##br##Than Most Major Economies China's Productivity Growth: Higher Than Most Major Economies China's Productivity Growth: Higher Than Most Major Economies China's manufacturing labor costs are also much lower than many other major exporters (Chart I-12, top panel). In addition, growth of average annual nominal wages in the Chinese manufacturing sector has declined to the lowest since 1997 (Chart I-12, bottom panel). China's R&D investment as a share of GDP is relatively high among major emerging economies (Chart I-13, top panel). With the country allocating more R&D investment into high-tech manufacturing, the pace of technology innovation is set to increase (Chart I-13, middle and bottom panels). Currently, China is already the biggest producer in several high-tech industries, including new energy vehicles, smart phones, communication equipment, solar cells and wind turbines. Chart I-12China's Manufacturing Labor Costs: ##br##Lower Than Most Major Economies China's Manufacturing Labor Costs: Lower Than Most Major Economies China's Manufacturing Labor Costs: Lower Than Most Major Economies Chart I-13China's R&D Spending: ##br##Higher Than Most EM Economies China's R&D Spending: Higher Than Most EM Economies China's R&D Spending: Higher Than Most EM Economies Even in low-value-added export sectors like textiles and metals, China's competitiveness is still strong. This has likely occurred in part due to supply side reforms - which have accelerated the consolidation of domestic industries - reducing costs and increasing production efficiencies. The 8% depreciation in China's currency versus the U.S. dollar over the past three months will also help improve the country's competitiveness. Bottom Line: China's manufacturing sector will remain highly competitive in the global goods market, despite faltering productivity growth. Investment Conclusions BCA's China Investment Strategy service has previously written about how China's export-enabled, catch-up growth phase in the early-2000s came to an abrupt end after the global financial crisis, and how policymakers were subsequently faced with a hard choice: China could either replace exports as a growth driver with debt-fueled domestic demand in order to buy the economy time to move up the value-added chain and transition to a services-led economy, or it could allow the labor market to suffer the consequences of a sharp slowdown in export growth while preserving fiscal and state-owned firepower for some uncertain future opportunity.2 This report highlights the difficulty experienced by China's manufacturing sector at reversing a downtrend in its productivity growth, which can be viewed as a microcosm of China's struggle to reorient itself and move away from its "old economy" towards one that is led by services. For investors, there are two key implications from this: First, the inherent difficulty of transitioning China's economy suggests that it will continue to experience economic mini-cycles around an uncertain primary growth trend, as policymakers periodically shift between aggressive supply-side reforms and demand-side countercyclical policies. In fact, some investors have come to believe that China is about to enter another mini-cycle upswing in response to recent stimulus announcements, but we have noted that the stimulus proposed so far falls short of a "big bang" response that would not only reverse the underlying slowdown and any trade shock but also reaccelerate the growth rate above trend.3 Second, to us the prospect of a potentially long, grinding shift away from China's investment-intensive economic sectors does not present an attractive risk-reward trade-off for traditional "China plays", such as industrial commodities and emerging market equities, over the coming few years. While it is true that periodic mini-cycle upswings may provide tactical opportunities for investors to go long these assets, the China "transition" theme suggests that an investors' strategic allocation to traditional China plays should be below benchmark. Chart I-14Prominence Of Investable ##br##Tech Ex-Internet Stocks Will Rise Prominence Of Investable Tech Ex-Internet Stocks Will Rise Prominence Of Investable Tech Ex-Internet Stocks Will Rise As a final point, periods of economic transition typically create both winners and losers, and China's continued focus on R&D spending suggests that the overlooked elements of China's tech sector may be winners. Chart I-14 highlights that over 90% of China's investable technology sector market capitalization is made up of companies in the internet software and services (ISS) industry, suggesting that investable tech ex-ISS may rise in prominence over time. More generally, identifying potential winners from increased Chinese R&D spending is an area of ongoing research at BCA, and is a theme that we hope to revisit in the future. Stay tuned! Ellen JingYuan He, Associate Vice President Emerging Markets Strategy ellenj@bcaresearch.com 1 The most common productivity measure is labor productivity, typically calculated as a ratio of real gross domestic product (GDP) to hours worked or employed persons. 2 Please see BCA China Investment Strategy Weekly Report, "Legacies Of 2017," dated December 21, 2017, available at cis.bcaresearch.com. 3 Please see BCA China Investment Strategy Weekly Report, "China Is Easing Up On The Brake, Not Pressing The Accelerator," dated July 26, 2018, available at cis.bcaresearch.com. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Congress is conducting a major economic experiment that has never been attempted in the U.S. outside of wartime; substantial fiscal stimulus when the economy is already at full employment. The budget deficit is on track to surpass 6% of GDP in a few years. It would likely peak above 8% in the case of a recession. The alarming long-term U.S. fiscal outlook is well known, but it has just become far worse. The combination of rising life expectancy and a decline in the ratio of taxpayers to retirees will place growing financial strains on the Social Security and Medicare systems. The federal government will be spilling far more red ink over the next decade than during any economic expansion phase since the 1940s. The debt/GDP ratio could surpass the previous peak set during WWII within 12 years. Shockingly large budget deficits in the past have sparked some attempt in Congress to limit the damage. Unfortunately, there will be little appetite to tighten the fiscal purse strings for the next decade. Voters have shifted to the left and politicians are following along. Factors that explain the political shift include disappointing income growth, income inequality, and rising political clout for Millennials, Hispanics and the elderly. Fiscal conservatism is out of fashion and this is unlikely to change over the next decade, no matter which party is in power. This means that a market riot will be required to shake voters and the political establishment into making the tough decisions necessary. While the U.S. is not at imminent risk of a market riot over the deteriorating fiscal trends, there are costs: in the long-term, the dollar will be weaker, borrowing rates will be higher and living standards will be lower than otherwise would be the case. Profligacy: (Noun) Unconstrained by convention or morality. Congress is conducting a major economic experiment that has never been attempted before in the U.S. outside of wartime; substantial fiscal stimulus at a time when the economy is already at full employment. Investors are celebrating the growth-positive aspects of the new fiscal tailwind at the moment, but it may wind up generating a party that is followed by a hangover as the Fed is forced to lean hard against the resulting inflationary pressures. Moreover, even in the absence of a recession, the federal government will likely be spilling far more red ink than during any economic expansion since the 1940s (Chart II-1). What are the long-term implications of this macro experiment? Will the U.S. continue to easily fund large and sustained budget deficits? Chart II-1U.S. Deficits Will Be Extremely Large For A Non-Recessionary Period U.S. Deficits Will Be Extremely Large For A Non-Recessionary Period U.S. Deficits Will Be Extremely Large For A Non-Recessionary Period Historically, shockingly large budget deficits sparked some attempt by Congress to limit the damage. Unfortunately, we argue in this Special Report that there will be little appetite to tighten the fiscal purse strings for the next decade. Voters have shifted to the left and politicians are following along. While the U.S. is not at imminent risk of a market riot over the deteriorating fiscal trends, the dollar will be weaker, borrowing rates will be higher and living standards will be lower than otherwise would be the case. On The Bright Side The Trump tax cuts, the immediate expensing of capital spending and a lighter regulatory touch have stirred animal spirits in the U.S. The Administration's trade policies are a source of concern, but CEO confidence is generally high. The NFIB survey highlights that small business owners are almost euphoric regarding the outlook. The IMF estimates that the tax cuts and less restrictive spending caps will provide a direct fiscal thrust of 0.8% in 2018 and 0.9% in 2019 (Chart II-2). The overall impact on the economy over the next 12-18 months could be larger to the extent that business leaders follow through on their newfound bullishness and ramp up capital spending. Chart II-2Lots Of Fiscal Stimulus In 2018 And 2019 July 2018 July 2018 Fiscal policy is a clear positive for stocks and other risk assets in the near term, as long as inflation is slow to respond. In addition to the near-term boost, there will be longer-term benefits from the 2017 tax act. Various provisions of the act affect the long-run productive potential of the U.S. economy, by promoting increases in investment and labor supply. Corporate tax cuts and the full expensing of business capital outlays should permanently increase the nation's capital stock relative to what it otherwise would be, leading to a slightly faster trend pace of productivity growth. Similarly, lower income taxes are projected to encourage more people to enter the workforce or to work longer hours. The CBO estimates that the tax act will boost the level of potential real GDP by 0.9% by the middle of the next decade. This may not sound like much, but it translates into almost a million extra jobs. The supply-side benefits of the 2017 tax act are therefore meaningful. Unfortunately, given the lack of offsetting spending cuts, it comes at the cost of a dramatically worse medium- and long-term outlook for government debt. The CBO estimates that the recent changes in fiscal policy will cumulatively add $1.7 trillion to the federal government's debt pile, relative to the previous baseline (Chart II-3). The annual deficit is projected to surpass $1 trillion in 2020, and peak as a share of GDP at 5.4% in 2022. Federal government debt held by the private sector will rise from 76% this year to 96% in 2028 in this scenario. Chart II-3Comparing To The Reagan Era Comparing To The Reagan Era Comparing To The Reagan Era The budget situation begins to look better after 2020 in the CBO's baseline forecast because a raft of "temporary provisions" are assumed to sunset as per current law, including some of the personal tax cuts and deductions included in the 2017 tax package. As is usually the case, the vast majority of these provisions are likely to be extended. The CBO performed an alternative scenario in which it extends the temporary provisions and grows the spending caps at the rate of inflation after 2020. In this more realistic scenario, the deficit reaches 7% of GDP by 2028 and the federal debt-to-GDP ratio hits 105% (Chart II-3). Moreover, there will undoubtedly be a recession sometime in the next five years. Even a mild downturn, on par with the early 1990s, could inflate the budget deficit to 8% or more of GDP. The Demographic Time Bomb Chart II-4The Withering Support Ratio The Withering Support Ratio The Withering Support Ratio The pressure that the aging population will place on federal coffers over the medium term is well known, but it is worth reviewing in light of Washington's new attitude toward deficit financing. The combination of rising life expectancy and a decline in the ratio of taxpayers to retirees will place growing financial strains on the Social Security and Medicare systems. In 1970, there were 5.4 people between the ages of 20 and 64 for every person 65 or older. That ratio has since dropped to 4 and will be down to 2.6 within the next 20 years (Chart II-4). Spending on entitlements (Social Security, Medicare, Medicaid, Income Security and government pensions) is on an unsustainable trajectory (Charts II-5 and II-6). In fiscal 2017, these programs absorbed 76% of federal revenues and the CBO estimates that this will rise to almost 100% by 2028, absent any change in law. If we also include net interest costs, total mandatory spending1 is projected to exceed total federal government revenues as early as next year, meaning that deficit financing will be required for all discretionary spending. Chart II-5Entitlements Will Explode ##br##Mandatory Spending Entitlements Will Explode Mandatory Spending Entitlements Will Explode Mandatory Spending Chart II-6All Discretionary Spending ##br##To Be Deficit Financed? All Discretionary Spending To Be Deficit Financed? All Discretionary Spending To Be Deficit Financed? The CBO last published a multi-decade outlook in 2017 (Chart II-7). The Federal debt/GDP ratio was projected to reach 150% by 2047. If we adjust this for the new (higher) starting point in 2028 provided by the CBO's alternative scenario, the debt/GDP ratio would top 164% in 2047. Chart II-7An Unsustainable Debt Accumulation An Unsustainable Debt Accumulation An Unsustainable Debt Accumulation To put this into perspective, the demands of WWII swelled the federal debt/GDP ratio to 106% in 1946, the highest on record going back to the early 1700s (Chart II-8). The debt ratio could rocket past that level before 2030, even in the absence of a recession. Chart II-8U.S. Debt In Historical Context U.S. Debt In Historical Context U.S. Debt In Historical Context These extremely long-term projections are only meant to be suggestive. A lot of things can happen in the coming years that could make the trajectory better or even worse. But the point is that current levels of taxation are insufficient to fund entitlements in their current form in the long run. Chart II-9 shows that outlays as a share of GDP have persistently exceeded revenues since the mid-1970s, except for a brief period during the Clinton Administration. The gap is set to widen over the coming decade. Something will have to give. Chart II-9U.S. Outlays And Revenues U.S. Outlays And Revenues U.S. Outlays And Revenues Forget Starving The Beast "Starve the Beast" refers to the idea that the size of government can be restrained through a low-tax regime that spurs growth and pressures Congress to cut spending and control the budget deficit. It has been the mantra of Republicans since the Reagan era. The 1981 Reagan tax cuts included an across-the-board reduction in marginal tax rates, taking the top rate down from 70% to 50%. Corporate taxes were slashed by $150 billion over a 5-year period and tax rates were indexed for inflation, among other changes. It was not surprising that the budget deficit subsequently ballooned. Outrage grew among fiscal conservatives, but Congress spent the next few years passing laws to reverse the loss of revenues, rather than aggressively attacking the spending side. Today, Congressional fiscal hawks are in retreat and the Republican Party under President Donald Trump is not as fiscally conservative as it once was. This trend reflects the pull toward the center of the economic policy spectrum in response to a shift to the left among voters. BCA's political strategists have highlighted that this is the "median voter theory" (MVT) in action.2 The MVT posits that parties and politicians will approximate the policy choices of the median voter in order to win an election or stay in power. Every U.S. presidential election involves candidates making a mad dash to the most popularly appealing positions. President Trump exhibited this process when he ran in the Republican primary on a platform of increased infrastructure spending and zero cuts to "entitlement" spending. The Great Financial Crisis, disappointingly slow growth, stagnating middle class incomes and the widening income distribution have resulted in a leftward shift among voters on economic issues. Adding to the shift is the rising political clout of the Millennial generation, which generally favors more government involvement in the economy and will become the major voting block as it ages in the 2020s. There also are important changes underway in the ethnic composition of the electorate. The rising proportion of Hispanic voters will on balance favor the Democrats, according to voting trends (Chart II-10). A previous Special Report by Peter Berezin, BCA's Chief Global Strategist, predicted that Texas will become a swing state in as little as a decade and a solid Democrat state by 2030.3 Chart II-10The Proportion Of Minority Voters Set To Grow The Proportion Of Minority Voters Set To Grow The Proportion Of Minority Voters Set To Grow President Trump's shift to the left on economic policy helped him to out-flank Clinton in the election, particularly in the Rust Belt, where his protectionist and anti-austerity message resonated. Even his anti-immigration appeal is mostly based on economic reasoning - i.e. jobs, rather than cultural factors. Trump has admitted that he is not all that concerned about taking the country deeper into hock. The Republican rank-and-file has generally gone along with Trump's agenda because he has delivered traditional Republican tax cuts and continues to rate highly among his supporters (his approval is around 90% among Republicans). Fiscal hawks within the GOP have been forced to the sidelines while Trump and moderate Republicans have passed bipartisan spending increases with Democratic assistance. Where's The Outrage? Chart II-11Entitlements Are Popular* July 2018 July 2018 The implication is that, unlike the Reagan years, we do not expect there will be a strong political force capable of leading a fight against budget deficits. After a decade of disappointing income growth, voters are in no mood for tax hikes. On the spending side, health care and pensions are still politically untouchable. A recent study by the Pew Research Center confirms that only a very small percentage of Americans of either political stripe would agree with cuts to spending on education, Medicare, Social Security, defense, infrastructure, veterans or anti-terrorism efforts (Chart II-11). It is therefore no surprise that a populist such as Trump has promised to defend entitlement programs. Moreover, the graying of America will make it increasingly difficult for politicians to tame the entitlement beast. An aging population might generally favor the GOP, but it will also solidify opposition towards cutting Medicare and Social Security. As for defense, U.S. military spending was 3.3% of GDP and almost 15% of total spending in 2017 (Chart II-12). Congress recently lifted the spending cap for defense expenditures, but it is still projected to fall as a share of total government spending and GDP in the coming years. It is conceivable that Congress could eventually trim the defense budget even faster, but spending is already low by historical standards and it is hard to see any future Congress gutting the military at a time when the global challenge from China and Russia is rising. Indeed, given the geopolitical atmosphere of great power competition, defense spending is more likely to rise. Chart II-12What's Left To Cut? What's Left To Cut? What's Left To Cut? So, what is left to cut? If entitlements and defense are off the table, that leaves non-defense discretionary spending as the sacrificial lamb. This category includes spending by the Departments of Agriculture, Education, Energy, Homeland Security, Health and Human Services, Justice, State and Veteran Affairs. Such spending has already declined sharply during the past several decades (Chart II-12). Non-defense discretionary spending amounted to $610 billion in 2017, which is only 15.3% of total federal spending. To put this into perspective, cutting every last cent of non-defense discretionary spending by 2022 would still leave a budget deficit of about 2½% of GDP. And it would be political suicide. The Departments of Education, Health and Human Services, Homeland Security, Justice and Veterans Affairs account for more than half of non-defense discretionary spending. But these programs are very popular among voters. And, at only 1.3% of total spending, eliminating all foreign aid won't make much difference. Either President Trump or Vice-President Mike Pence will be the GOP presidential candidate in 2020. Pence could be more fiscally conservative than Trump, but Congress is unlikely to remain GOP-controlled through 2024. Similarly, it is difficult to see the Democrats making more than a token effort to rein in the deficit if the party is in charge after 2020. Perhaps they will raise taxes on the rich and push the corporate rate back up a bit, but voters will probably not favor a full reversal of the Trump tax cuts. Democrats will not tackle entitlements either. In other words, we can forget about "starving the beast" as a viable option no matter which party is in power. There will be little appetite for fiscal austerity in the U.S. through to the mid-2020s at a minimum. International Comparison This all places the U.S. out of sync with other major industrialized countries, where structural budget deficits have been tamed in most cases and are expected to remain so according to the IMF's latest projections (Chart II-13). The U.S. cyclically-adjusted budget deficit is projected to be almost 7% of GDP in 2019, by far the highest among other industrialized countries except for Norway. Spain and Italy are expected to have relatively small structural deficits of 2½% and 0.8%, respectively, next year. Greece is running a small structural surplus! Including all levels of government, the IMF estimates that the U.S. general government gross debt/GDP ratio is projected to be well above that of the U.K., France, Germany, Spain and Portugal in 2023 (Chart II-14). It is expected to be on par with Italy at that time, although the newly-installed populist government there is likely to negotiate a loosening of the fiscal rules with Brussels, leading to higher debt levels than the IMF currently expects. The implication is that the U.S. government appears destined to become one of the most indebted in the developed world. Chart II-13U.S. Budget Deficit Stands Out July 2018 July 2018 Chart II-14International Debt Comparison July 2018 July 2018 The Fiscal Tipping Point Investors are not yet worried about the path of U.S. fiscal policy; the yield curve is quite flat, CDS spreads on U.S. Treasurys have not moved and the dollar is still overvalued by most traditional measures. The challenge is timing when a fiscally-induced crisis might occur. A warning bell does not ring when government debt or deficits reach certain levels. Fiscal trends generally do not suddenly spiral out of control - it is a gradual and insidious process reflected in multi-year deficits and slowly accumulating debt burdens. Eventually, a tipping point is reached where the only solution is drastic policy shifts or in extreme cases, default. Along the way, there are a number of signs that fiscal trends are entering dangerous territory. The relevance of the various signs will be different for each country, reflecting, among other things, the depth and structure of the financial system, the soundness of the economy, the dependence on foreign capital, and the asset preferences of domestic investors. Some key signs of building fiscal stress are given in Box II-1. None of the factors in Box II-1 appear to be a threat at the moment for the U.S. Moreover, comparisons with other countries that have hit the debt wall in the past are not that helpful because the U.S. is a special case. It has a huge economy and has political and military clout. The dollar is the world's main reserve currency and the country is able to borrow in its own currency. This suggests that the U.S. will be able to "get away with" its borrowing habit for longer than other countries have in the past. At the same time, financial markets are fickle and, even with hindsight, it not always clear why investors switch from acceptance to bearishness about a particular state of affairs. BOX II-1 Traditional Signs Of An Approaching Debt Crisis Government deficits absorb a rising share of net private savings, leaving little for new investment. Interest payments account for an increasingly large share of government revenues, squeezing out discretionary spending and requiring tough budget action merely to stop the deficit from rising. The government exhausts its ability to raise tax burdens. Traditional sources of debt finance dry up, requiring alternative funding strategies. Fears of inflation and/or default lead to a rising risk premium on interest rates and/ or a falling exchange rate. Political shifts occur as governments get blamed for eroding living standards, high taxes, and continued pressure to cut spending. The Costs Of Fiscal Profligacy Even if the U.S. is not near a fiscal tipping point, this does not mean that massive debt accumulation is costless: Interest Costs: Spending 3% of GDP on servicing the federal government's debt load over the next decade is not a disaster. Nonetheless, it does reduce the tax dollars available to fund entitlements or investing in infrastructure. Counter-Cyclical Fiscal Policy: Lawmakers would have less flexibility to use tax and spending policies to respond to unexpected events, such as natural disasters or recessions. As noted above, a recession in 2020 could generate a federal deficit of more than 8% of GDP. In that case, Congress may feel constrained in supporting the economy with even temporary fiscal stimulus. National Savings: Because government borrowing reduces national savings, then either capital spending must assume a smaller share of the economy or the U.S. must borrow more from abroad. Most likely it will be some combination of both. Crowding Out: If global savings are not in plentiful supply, then the additional U.S. debt issuance will place upward pressure on domestic interest rates and thereby "crowd out" business capital spending. This would reduce the nation's capital stock, leading to lower growth in productivity and living standards than would otherwise be the case. The CBO estimates that the positive impact on the capital stock from the changes to the corporate tax structure will overwhelm the negative impact from higher interest rates over the next decade. Nonetheless, the crowding out effect may dominate over a longer-time horizon. Academic studies suggest that every percentage point rise in the government's debt-to-GDP ratio adds 2-3 basis points to the equilibrium level of bond yields. If this is correct, then a rise in the U.S. ratio of 25 percentage points over the next decade in the CBO's baseline would lift equilibrium long-term bond yields by a meaningful 50-75 basis points. Much depends, however, on global savings backdrop at the time. External Trade Gap: If global savings are plentiful, then it may not take much of a rise in U.S. interest rates to attract the necessary foreign inflows to fund both the higher U.S. federal deficit and the private sector's borrowing requirements. Of course, this implies a larger current account deficit and a faster accumulation of foreign IO Us. Twin Deficits The U.S. has run a current account deficit for most of the past 40 years, which has cumulated into a rising stock of foreign-owned debt. The Net International Investment Position (NIIP) is the difference between the stock of foreign assets held by U.S. residents and the stock of U.S. assets held by foreign investors. The NIIP has fallen increasingly into the red over the past few decades, reaching 40% of GDP today (Chart II-15). The current account deficit was 2.4% at the end of 2017, matching the post-Lehman average. Nonetheless, this deficit is set to worsen as increased domestic demand related to the fiscal stimulus is partly satisfied via higher imports. Chart II-15Scenarios For The U.S. Net International Investment Position Scenarios For The U.S. Net International Investment Position Scenarios For The U.S. Net International Investment Position We estimate that a two percentage point rise in the budget deficit relative to the baseline could add a percentage point or more to the current account deficit, taking it up close to 4% of GDP. Upward pressure on the external deficit will also be accentuated in the next few years to the extent that the U.S. business sector ramps up capital spending. The implication is that the NIIP will fall deeper into negative territory at an even faster pace. A 2% current account deficit would be roughly consistent with stabilization in the NIIP/GDP ratio. But a 4% deficit would cause the NIIP to deteriorate to almost 80% of GDP by 2040 (Chart II-15). The sustainability of the U.S. twin deficits has been an area of intense debate among academics and market practitioners for many years. The U.S. has been able to get away with the twin deficits for so long in part because of the dollar's status as the world's premier reserve currency. The critical role of the dollar in international transactions underpins global demand for the currency. This has allowed the U.S. to issue most of its debt obligations in U.S. dollars, forcing the currency risk onto foreign investors. The worry is that foreign investors will at some point begin to question the desirability of an oversized exposure to U.S. assets within their global portfolios. We argued in our April 2018 Special Report 4 that the U.S. situation is not that dire that the U.S. dollar and Treasury bond prices are about to fall off a cliff because of sudden concerns about the unsustainability of the current account deficit. Even though the NIIP/GDP ratio will continue to deteriorate in the coming years, it does not appear that the U.S. is close to the point where foreign investors would begin to seriously question America's ability or willingness to service its debt. That said, the "twin deficits" and the downward trend in U.S. productivity relative to the rest of the world will ensure that the underlying long-term trend in the dollar will remain down (Chart II-16).5 Chart II-16Structural Drivers Of The U.S. Dollar Structural Drivers Of the U.S. Dollar Structural Drivers Of the U.S. Dollar Conclusions The long-term U.S. fiscal outlook was dire even before the Great Recession and the associated shift to the political left in America. Fiscal conservatism is out of fashion and this is unlikely to change before the mid-2020s, no matter which party is in power. This means that a market riot will be required to shake voters and the political establishment into making the tough decisions. Given demographic trends, it appears more likely that taxes will rise than entitlements cut. We do not foresee a crisis occurring in the next few years. Nonetheless, arguing that the U.S. fiscal situation is sustainable for the foreseeable future does not mean that it is desirable. There will be costs associated with current fiscal trends, even on a relatively short 5-10 year horizon. Interest costs will mushroom, potentially crowding out government spending in other areas. U.S. government debt has already been downgraded by S&P to AA+ in 2013, and the other two main rating agencies are likely to follow suit during the next recession as the deficit balloons to 8% or more. Investors may begin to demand a risk premium in order to entice them to continually raise their exposure to U.S. government bonds in their portfolios. Taxes will eventually have to rise to service the government debt, and some capital spending will be crowded out, both of which will undermine the economy's growth potential. Finally, the dollar will also be weaker than it otherwise would be in the long-term, representing an erosion in America's standard of living because everything imported is more expensive. Could Japan offer a roadmap for the U.S.? The Bank of Japan has effectively monetized 43% of the JGB market and has control over yields, at least out to the 10-year maturity. Moreover, Japan has enjoyed a "free lunch" so far because monetization has not resulted in inflation. The reason that Japan has enjoyed a free lunch is that it has suffered from a chronic lack of demand and excess savings in the private sector. The government has persistently run a deficit and fiscally stimulated the economy in order to offset insufficient demand in the private sector. The Bank of Japan purchased bonds and drove short-term interest rates down to zero. These policies have made very slow progress in eradicating lingering deflationary economic forces. However, if animal spirits in the business sector perk up, then inflation could make a comeback unless the policy stimulus is dialed down in a timely manner. In other words, the BoJ-financed fiscal "free lunch" should disappear at some point. The U.S. is in a very different situation. There is no lack of aggregate demand or excessive savings in the private sector. The economy is at full employment, and thus persistent budget deficits should turn into inflation much more quickly than was the case in Japan. In other words, the U.S. is unlikely to enjoy much of a "free lunch", whether the Fed monetizes the debt or not. Mark McClellan Senior Vice President The Bank Credit Analyst 1 Mandatory spending refers to entitlements; that is, government expenditure programs that are required by current law. These include Social Security, Medicare, Medicaid, government pensions and other smaller programs. 2 Please see Geopolitical Strategy Monthly Report, "Introducing The Median Voter Theory," June 8, 2016, available at gps.bcaresearch.com. 3 Please see The Bank Credit Analyst, "America's Fiscal Fortune: Leave Your Wallet On The Way Out," June 2011, available at bca.bcaresearch.com. 4 Please see The Bank Credit Analyst Special Report, "U.S. Twin Deficits: Is The Dollar Doomed?," April, 2018, available at bca.bcaresearch.com. 5 In the near term, fiscal stimulus and increased business capital spending will likely boost the dollar. But this effect on the dollar will reverse in the long-term.

Highlights One of Europe's major success stories is the structural and broad-based increase in female labour participation rates. The trend is set to continue for the next decade. Stay overweight the Personal Products sector as a long-term position. Italy's decade-long stagnation is not a deep-seated structural malaise. It is a protracted cyclical downturn resulting from a banking system that was never repaired after the 2008 financial crisis combined with wholly inappropriate fiscal austerity. We expect Italy's new government to push back against the EU's misguided fiscal rules and correct this decade-long error. Buy exposure to Italian real estate as a new long-term position either directly or through Italy's small real estate equity sector. Feature Some analysts persist on comparing economic performances on the basis of real GDP per head of total population. But the total population includes children and the elderly who cannot contribute to economic output. Therefore, a correct assessment of economic performance should look at real GDP per head of working-age population. Chart I-1AWomen Are Powering The European Economy... Women Are Powering The European Economy... ...Less So In The U.S. Women Are Powering The European Economy... ...Less So In The U.S. Chart I-1B ...Less So In The U.S. Women Are Powering The European Economy... ...Less So In The U.S. Women Are Powering The European Economy... ...Less So In The U.S. Admittedly, as the retirement age rises, the definition of 'working-age' will gradually change, but the general principle still holds: only count in the denominator those who can contribute to economic output. GDP per head of working-age population can grow in several ways. One way is to get more output or better output from each hour worked through improvements in efficiency and/or quality. As this improvement is theoretically limitless, it is the main source of productivity gains in the long run. A second way is for each worker to work more hours. But given the physical and legal constraints on productive working time, there is only limited scope to increase output in this way. How Women Are Powering The European Economy There is one other way to increase GDP per head of working-age population: increase the percentage of the working age population that is in the labour force.1 In other words, structurally increase the labour participation rate. If this participation rate is already high - as it is for men - then there is little scope to increase it much further. But if the participation rate is low - as it is for European women - then there is considerable scope to increase it. This brings us to one of Europe's major, and largely untold, success stories - the structural and broad-based increase in female participation rates (Chart I-1-Chart I-5). Over the past twenty years, the EU28 female participation rate has risen from 57% to 68%, with an especially large contribution from the socially conservative southern countries. In Spain, female participation has surged from 47% to 70%. In Italy, it has shot up from 42% to 56% and has clear scope to rise much further. Chart I-2Italy: Labour Force Participation Rate Italy: Labour Force Participation Rate Italy: Labour Force Participation Rate Chart I-3Spain: Labour Force Participation Rate Spain: Labour Force Participation Rate Spain: Labour Force Participation Rate Chart I-4Germany: Labour Force Participation Rate Germany: Labour Force Participation Rate Germany: Labour Force Participation Rate Chart I-5France: Labour Force Participation Rate France: Labour Force Participation Rate France: Labour Force Participation Rate What is driving this structural trend? Two things. First, the employment sectors that are growing structurally - healthcare, social care, and education - tend to employ more women than men. Second, European countries have legislated a raft of policies encouraging women to join and remain in the labour force: generous paid maternity leave and subsidised childcare. The trend is for further improvements, with the focus now on improving paternity leave. Sharing parental and family responsibilities between mothers and fathers allows more women to enter and stay in the labour force.2 For the ultimate end-point in the trend, look to the Scandinavian countries which started such policies in the early 1970s. In Sweden, labour force participation for women and men is almost identical: 81% versus 84%. If the EU eventually adopts the Scandinavian model, it would mean another 20 million European women in employment and contributing to economic output (Chart I-6). Chart I-6Another 20 Million European Women ##br##Could Join The Labour Force Another 20 Million European Women Could Join The Labour Force Another 20 Million European Women Could Join The Labour Force Dispelling Two Myths: The Euro Area And Italy Having established that economic performances should be compared on the basis of GDP per head of working age population, we can now dispel two common myths. The first myth is that the U.S. generates superior productivity growth than the euro area. It is true that the U.S. has been better at getting more output from each hour worked, so on this measure, the U.S. does win. Against this, the euro area has been much better at getting more of its working-age population - albeit mostly women - into employment. So on this measure, the euro area wins (Chart of the Week). The net result is that, over the past twenty years, the U.S and the euro area have generated exactly the same growth in real GDP per working-age population (Chart I-7). Of course, the euro area's structural improvement in female participation rates cannot continue forever, but it can certainly continue for another decade or so, and this is generally the longest time horizon that most investors care about. Chart I-7The Euro Area And The U.S.: Identical Growth In Real GDP Per Head Of Working-Age Population The Euro Area And The U.S.: Identical Growth In Real GDP Per Head Of Working-Age Population The Euro Area And The U.S.: Identical Growth In Real GDP Per Head Of Working-Age Population The second myth concerns the subject du jour: Italy. Many people claim that Italy's economic stagnation is due to deep-seated structural problems which differentiate it from other major economies. The problem with this narrative is that from the mid-1990s until 2008 the growth in Italy's real GDP per head of working age population was little different to that in Germany, France or the U.S. (Chart I-8). Chart I-8Italy Performed In Line With Other Major Economies Until 2008 Italy Performed In Line With Other Major Economies Until 2008 Italy Performed In Line With Other Major Economies Until 2008 Italy's economic stagnation only started after the 2008 global financial crisis. After a financial crisis which cripples the banking system, there are two golden rules: unleash fiscal stimulus; and repair the banking system as quickly as possible. The U.S. and U.K. followed the golden rules perfectly and immediately; Ireland followed a couple of years later; Spain waited until 2013. But in each case, the economies rebounded very strongly as the fiscal stimulus kicked in and the banks recuperated. Italy neither unleashed fiscal stimulus, nor repaired its banks - so its economy has stagnated for a decade. Moreover, if output stagnates for a decade, it follows arithmetically that productivity growth will also look poor. In a back-to-front argument, critics have pounced on this as evidence of excessive 'red tape' and 'structural problems'. But this is a misdiagnosis of the malaise. To reiterate, Italy's real GDP per working-age population was growing very respectably before 2008. Italy's misfortune is that its indebtedness has an unusual profile: more public debt than private debt. France and Spain (and other major euro area economies) have the usual profile: less public debt than private debt. So the EU's fiscal rules - which can see only public debt and are blind to private debt - have severely and unfairly constrained Italy's ability to respond to financial crises. While every other major economy followed the golden rules to recover from the 2008 crisis, Italy could neither unleash fiscal stimulus to kick start the economy nor recapitalise its dysfunctional banking system. We expect Italy's new government to push back against the EU's misguided fiscal rules and correct this decade-long error. Two Structural Investment Conclusions This week's two investment conclusions are both long term, and require a buy and hold mentality. The first conclusion reiterates a structural position: overweight the Personal Products sector. This is based on our expectation that, in Europe, female participation rates will continue their structural uptrend; while in the U.S. we expect female participation rates to continue outperforming male participation rates. Therefore the sales and profits of the Personal Products sector, in which female spending dominates, will benefit from a multi-year tailwind, at least relative to other sectors. And the extent of this tailwind is not fully discounted in valuations. The second conclusion is a new long-term recommendation: buy exposure to Italian real estate. This is based on our assessment that Italy's decade-long stagnation is not a deep-seated structural malaise. Instead, it is a protracted cyclical downturn resulting from a banking system that was never repaired after the 2008 financial crisis combined with wholly inappropriate fiscal austerity. Removing these shackles will allow a long-term recovery, just as it did for Spain in 2013. If we are right, the best multi-year buy and hold play is Italian real estate which has been in a decade-long bear market (Chart I-9). For those that cannot directly invest in property, Italy has a small real estate equity sector which faithfully tracks the long term profile of real estate prices (Chart I-10), and whose main component is Beni Stabili. The caveat is that the stock has a market cap of just €2 billion; the appeal is that it offers a juicy dividend yield of 4.5%. Chart I-9Italian Real Estate Has Suffered ##br##A Decade-Long Bear Market Italian Real Estate Has Suffered A Decade-Long Bear Market Italian Real Estate Has Suffered A Decade-Long Bear Market Chart I-10Italian Real Estate Equities##br## Track Real Estate Prices Italian Real Estate Equities Track Real Estate Prices Italian Real Estate Equities Track Real Estate Prices Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 And in employment. 2 Please see the European Investment Strategy Special Report "Female Participation: Another Mega-Trend" published on April 6, 2017 and available at eis.bcaresearch.com Fractal Trading Model* This week, we note that the 130-day fractal dimension for platinum versus nickel is close to its lower bound, a level which has consistently predicted a tradeable countertrend move over the following 130 days. Hence, this week's trade is long platinum/short nickel on a 130 horizon before expiry. The profit target is 14% with a symmetric stop-loss. Our two other open trades, long SEK/GBP and long PLN/USD, are both in profit. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment's fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-11 Long Platinum / Short Nickel Long Platinum / Short Nickel The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report "Fractals, Liquidity & A Trading Model," dated December 11, 2014, available at eis.bcaresearch.com Fractal Trading Model Recommendations Equities Bond & Interest Rates Currency & Other Positions Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations

Highlights The scale of "de-capacity" reforms is diminishing considerably - old, inefficient capacity shutdowns are declining. Sizable new technologically advanced and ecologically friendly capacity is coming on stream for both steel and coal in 2018 and 2019. We project this will boost steel and coal output by 5.2% and 4.7% respectively, this year at a time when demand is set to slow. Steel, coal, iron ore and coke prices are all vulnerable to the downside. Share prices of the companies and currencies of countries that supply these commodities to China are most at risk. Feature Last November, our report titled, "China's "De-Capacity" Reforms: Where Steel & Coal Prices Are Headed," painted a negative picture for steel and coal prices over 2018 and 2019.1 Since then, after having peaked in December and February respectively, both steel and thermal coal prices have so far declined by about 20% from their respective tops (Chart 1). In the meantime, iron ore and coking coal have also exhibited meaningful weakness (Chart 2). Chart 1More Downside In Steel And Coal Prices More Downside In Steel And Coal Prices More Downside In Steel And Coal Prices Chart 2Iron Ore And Coking Coal Prices Are Also At Risk Iron Ore And Coking Coal Prices Are Also At Risk Iron Ore And Coking Coal Prices Are Also At Risk In this report, we revisit the topic of de-capacity reforms and examine how Chinese supply side reforms in 2018 will affect steel and coal prices. The key message is as follows: Having implemented aggressive capacity reduction over the past two years, the authorities are shifting the focus of supply side reforms from "de-capacity" to "replacement" of already removed capacity with technologically advanced capacity. This means the scale of "de-capacity" reforms is diminishing considerably - old, inefficient capacity shutdowns are declining. In addition, sizable new technologically advanced and ecologically friendly capacity is coming on stream for both steel and coal in 2018 and 2019. From an investing standpoint, this means both steel and coal prices are still vulnerable to the downside. Both could drop by more than 15% from current levels over the course of 2018. Diminishing Scale Of "De-Capacity" Reforms Reducing capacity (also called "de-capacity") in the oversupplied steel and coal markets has been a key priority within China's structural supply side reforms over the past two years. Steel Table 1 shows that the capacity reduction target for steel in 2018 is 30 million tons, which is much lower than the 45 million tons in 2016 and 50 million tons in 2017. Table 1Capacity Reduction: Target And Actual Achievement Revisiting China's De-Capacity Reforms Revisiting China's De-Capacity Reforms In addition, between May and September 2017, the "Ditiaogang"2 removal policy eliminated about 120 million tons of steel capacity, and sharply reduced steel products production. Most of Ditiaogang capacity was completely dismantled last year. Therefore, there is not much downside to steel production from Ditiaogang output cutbacks going forward. Furthermore, between October and December 2017, environmental policies aimed at fighting against winter smog also cut steel products output substantially, which pushed steel prices to six-year highs in December (Chart 3). Chart 3Policy Actions And Market Dynamics: Steel Sector Policy Actions And Market Dynamics: Steel Sector Policy Actions And Market Dynamics: Steel Sector In particular, in the last quarter of 2017, to ensure fewer smog days around the Beijing area, Tianjin's steel products output was reduced by 50% from a year earlier. The second biggest contribution to total steel output decline occurred in Hebei - the largest steel-producing province in China - where steel output plummeted by 7%. Excluding Tianjin and Hebei, national steel products output fell only by 3.9% from a year ago. As a long-term solution to ameliorate ecology and air quality around Beijing, the government is aiming to reduce the heavy concentration of steel production in Tianjin and Hebei by shifting a considerable portion of steel capacity to other regions in 2018 and following years. These two provinces together accounted for about 30.6% of the nation's steel products output in 2016; their share dipped to 27.6% in 2017. As a result, next winter the required production reduction from these regions to achieve the air quality targets in Beijing will be smaller. In short, the scale of specific policy driven steel output reduction in 2018 will be meaningfully lower than last year. Coal For coal, despite the same target as last year (150 million tons), the actual capacity cut this year will be much less than last year's actual reduction of 250 million tons, which exceeded the 150 million-ton target. Amid still-high coal prices, the authorities will be more tolerant of producers not cutting too much capacity. Plus, with nearly two-thirds of the 2016-2020 target for capacity cuts having already been achieved in the past two years, there is much less outdated capacity in the industry (Table 1 above). In addition, the government's environment-related policies also led to a decline in total national coal output between October-December 2017 (Chart 4), with Hebei posting the biggest cut in coal output among all provinces. Chart 4Policy Actions And Market Dynamics: Coal Sector Policy Actions And Market Dynamics: Coal Sector Policy Actions And Market Dynamics: Coal Sector However, the authorities shortly thereafter relaxed restrictions on coal output, as the country was severely lacking gas supply for heating. In January and February of this year, the authorities reversed course, demanding that producers accelerate new advanced capacity replacement and increase coal production. Bottom Line: The scale of China's "de-capacity" reforms are diminishing, resulting in a lessening production cuts. Installing Technologically Advanced Capacity China's supply side reforms have included two major components - reducing inefficient capacity and low-quality supply that damaged the environment while boosting medium-to-high-quality production that is economically efficient and ecologically friendly. In brief, having removed significant obsolete capacity in the past two years, the policy focus is now shifting to capacity replacement. The latter enables China to upgrade its steel and coal industries to become more efficient and competitive worldwide, as well as ecologically safer. To guard against excessive production capacity of steel and coal, the authorities are reinforcing the following replacement principle: the ratio of newly installed-to-removed capacity should be less or equal to one. Two important points need to be noted: First and most important, the zero or negative growth of total capacity of steel and coal does not necessarily mean zero or negative growth in steel and coal output. For example, while total capacity for crude steel and steel products declined 4.8% and 1.8% year-on-year in 2016 respectively, output actually increased 0.5% and 1%. Despite falling total capacity, rising operational capacity could still contribute to an increase in final output. Total capacity (measured in tons) for steel and coal production includes both operational capacity and non-operational capacity, the latter representing obsolete/non-profitable capacity. As more technologically advanced capacity is installed to replace the already-removed one, both the size of operational capacity and the capacity utilization rate (CUR) will rise. Typically, advanced technologies have a higher CUR - consequently, production will grow. Second, an increase in the CUR of existing operational capacity will also result in rising output. In 2018, odds are that both the steel and coal industries in China will have non-trivial output increases as a result of new advanced capacity coming on stream. Steel Since late 2015, in environmentally sensitive areas of the Beijing-Tianjin-Hebei region and the Yangtze River Delta and the Pearl River Delta, steel plants have been required to add no more than 0.8 tons of new capacity for every 1 ton of outdated capacity removed. For other areas, the same ratio is 1 or less. Electric furnace (EF) steel-producing technology - which is cleaner, more advanced and used to produce high-quality specialized steel products - has become the major type of new capacity addition. This technology is favored by both the government and steel producers. Chinese EF-based steel production accounted for only 6.4% of the nation's total steel output in 2016, far lower than the world average of 25.7% (Chart 5). The EF technology uses scrap steel as raw materials, graphite electrodes and electricity to produce crude steel. Graphite electrodes, which have high levels of electrical conductivity and the capability of sustaining extremely high levels of heat, are consumed primarily in electric furnace steel production. Chart 6 demonstrates that prices of both graphite electrode and scrap steel have surged since mid-2017. This signifies that considerable new EF production capacity has been coming on stream. Chart 5Chinese Electric Furnace Crude Steel ##br##Production Will Go Up Revisiting China's De-Capacity Reforms Revisiting China's De-Capacity Reforms Chart 6Considerable New Addition Of##br## Chinese Electric Furnace Capacity Considerable New Addition Of Chinese Electric Furnace Capacity Considerable New Addition Of Chinese Electric Furnace Capacity Indeed, in 2017 alone, 44 units of EF were installed. In comparison, between 2014 and 2016, only 47 units of EF were installed. As the completion of a new EF installation in general takes eight to 10 months, all of EF capacity installed in 2017 - about 31 million tons of crude steel production capacity - will be operational in 2018. In addition, a report from China's Natural Resource Department indicates that as of mid-December there have been 54 replacement projects with total new steel production capacity of 91 million tons (including new EF capacity, new traditional capacity and recovered capacity). This compares to 120 million tons of capacity removed in 2016-'17. Assuming 60% of this 91 million tons capacity will be operating throughout 2018 at a utilization rate of 80% (the NBS 2017 CUR for the ferrous smelting and pressing industry was 75.8%), this alone will result in 43.6 million tons more output in 2018 from a year ago (5.2% growth from 2017 output) (Table 2). Table 2Strong Profit Margins Will Encourage Steel Production Revisiting China's De-Capacity Reforms Revisiting China's De-Capacity Reforms At the same time, strong profit margins will encourage steel makers to produce as much as possible to maximize profits (Chart 7). This will be especially true if the incumbent companies have to absorb liabilities of firms that were shutdown (please refer to page 14 for the discussion on this point). Facing more debt from shutdowns of other companies, steel incumbent producers would have an incentive to ramp up their production to generate more cash. Yet, we do not assume a rise in CUR for existing steel capacity. Hence, crude steel output growth in 2018 will likely be around 5.2%, higher than the 3% growth in 2017. This is in line with the top 10 Chinese steel producers' projected crude steel output growth in 2018 of 5.5%, based on their published production guidance data. The Ditiaogang and environmental policy caused a significant contraction in steel products growth in 2017, but will have limited impact in 2018 as discussed above. Eventually, increasing crude steel output will translate into strong growth in steel products output3 (Chart 8). Chart 7Strong Profit Margins ##br##Will Encourage Steel Production Strong Profit Margins Will Encourage Steel Production Strong Profit Margins Will Encourage Steel Production Chart 8Steel Products Production ##br##Will Rebound In 2018 Steel Products Production Will Rebound In 2018 Steel Products Production Will Rebound In 2018 Coal China's current coal capacity is about 5310 million tons, with 4780 million tons as operational capacity and the remaining 530 million tons as non-operational capacity, which has not produced coal for some time. As in general it takes roughly three to five years to build a coal mine, it will take a long time to replace the obsolete capacity. Yet there is hidden coal capacity in China. The China Coal Industry Association estimated last year that there was about 700 million tons of new technologically advanced capacity that has already been built and is ready to use, but has not yet received government approval. This is greater than the 530 million tons of coal production removed in the past two years by de-capacity reforms - equivalent to about 20% of China's total 2017 coal output. This hidden capacity originated from the fact that coal producers in China historically began building mines before applying for approval. However, since 2015, all applications for new coal mines have been halted. Consequently, in the past three years a lot of capacity has already been built but has not been put into operation. Some 70% of this hidden capacity includes large-scale coal mines, each with annual capacity of above 5 million tons. In comparison, China has about 126 million tons of small mines with annual capacity of 90,000 tons that will be forced to exit the market this year as they are non-competitive due to their small scale and inferior technology. Why do we expect this hidden capacity to become operational going forward? The authorities now allows trading in the replacement quota for coal across regions. Producers having these ready-to-use high-quality mines can buy the replacement quota from the producers who have eliminated the outdated capacity. The government wants to accelerate the process of allowing the advanced capacity to be in operation as fast as possible. The following policy initiative supports this: A new policy directive released this past February does not even require coal producers with advanced capacity to pay the quota first in order to apply for approval - they can apply for approval to start the replacement process first, and then have one year to pay for it. Economically, quotas trading makes sense. The mines with advanced technology that have lower costs and higher profit margins should be able to pay a reasonably high (attractive) price for quotas to companies with inferior technologies, so that the latter will be better off selling their quotas than continuing operations. The proceeds from the selling quotas will be used to settle termination benefits for employees of low-quality coal mines. Regarding our projections for coal output in 2018, assuming 30% of the 700 million tons of capacity among high-quality mines will be operational this year at a CUR of 78% (the NBS 2017 coal industry CUR was 68.2%), this alone will bring a 164 million-ton increase in coal output (4.7% of the 2017 coal output) (Table 3). Table 3Chinese Coal Output Will Rise By 4.7% In 2018 Revisiting China's De-Capacity Reforms Revisiting China's De-Capacity Reforms In addition, still-high profit margins could encourage existing coal producers to increase their CUR this year (Chart 9). Yet, we do not assume a rise in CUR for existing coal mining capacity. In total, Chinese coal output may increase 4.7% this year, higher than last year's 3.2% growth (Chart 10). Chart 9Strong Profit Margins Will Boost Coal Production Strong Profit Margins Will Boost Coal Production Strong Profit Margins Will Boost Coal Production Chart 10Coal Output Is Already Rising Coal Output Is Already Rising Coal Output Is Already Rising Bottom Line: Sizable technologically advanced new capacity is coming on stream for both steel and coal. This will boost both steel and coal output by about 5.2% and 4.7%, respectively, this year. Impact On Global Steel And Coal Prices In addition to diminishing capacity cuts and new technologically advanced capacity additions, the following factors will also weigh on steel prices: Relatively high steel product inventories (Chart 11, top panel) Weakening steel demand, mainly due to a potential slowdown in the property market4 Declining infrastructure investment growth (Chart 11, bottom panel). Chinese net steel product exports contracted 30% last year as steel producers opted to sell steel products domestically on higher domestic steel prices (Chart 12). Chart 11Elevated Steel Product Inventory##br## And Weakening Demand bca.ems_sr_2018_04_26_c11 bca.ems_sr_2018_04_26_c11 Chart 12China's Steel Product Exports ##br##Will Rebound China's Steel Product Exports Will Rebound China's Steel Product Exports Will Rebound Falling domestic steel prices may lead steel producers to ship their products overseas. In addition, the government has reduced steel products export tariffs starting January 1, 2018, which may also help increase Chinese steel product exports this year. This will pass falling Chinese domestic steel prices on to lower global steel prices. Between 2015 and 2017, about 1.6% of all Chinese steel exports were shipped to the U.S. Even if U.S. tariffs dampen its purchases of steel from China, mainland producers will try to sell their products to other countries. In a nutshell, U.S. tariffs will not prevent the transmission of lower steel prices in China to the global steel market. With respect to coal, in early April the Chinese government placed restrictions on Chinese coal imports at major ports in major imported-coal consuming provinces including Zhejiang, Fujian and Guangdong (Chart 13). The government demanded thermal power plants in those areas to limit their consumption of imported coal and use domestically produced coal. Clearly the government is trying to avoid cheaper imports flooding into the domestic coal market amid still elevated prices. This will help prevent a big drop in domestic coal prices but will be bearish for global coal prices. For example, 40% and 30% of Chinese coal imports are from Indonesia and Australia, respectively (Chart 14). These economies and their currencies are at risk from diminishing Chinese coal imports. Chart 13Chinese Coal Imports Will Decline Chinese Coal Imports Will Decline Chinese Coal Imports Will Decline Chart 14Indonesia and Australia May Face Falling ##br##Coal Demand From China Indonesia and Australia May Face Falling Coal Demand From China Indonesia and Australia May Face Falling Coal Demand From China For the demand side, continuing strong growth in non-thermal power supplies such as nuclear, wind and solar will curb thermal power growth in the long run and thus limit thermal coal consumption growth in China. This may also weigh on domestic coal prices and discourage coal imports. Bottom Line: The downtrend in domestic steel and coal prices will weigh on the global steel and coal markets. What About Iron Ore And Coking Coal? Iron ore and coking coal prices are also at risk: Chart 15Record High Chinese Iron Ore Inventory Record High Chinese Iron Ore Inventory Record High Chinese Iron Ore Inventory Given about 40% of newly installed steel capacity is advanced electric furnace (EF) based - which requires significant amounts of scrap steel rather than iron ore and coke - rising steel output will increase demand for iron ore and coke disproportionally less. As more Chinese steel producers shift to EF technology, mainland demand for iron ore and coke will diminish structurally in the years to come. Despite weakness in both domestic iron ore production and iron ore imports, Chinese iron ore inventories at major ports, expressed in number of months of consumption, have still reached record highs (Chart 15). This suggests rising EF capacity has indeed been constraining demand for iron ore. Increasing coal output will bring more coking coal and a corresponding rise in coke supply, thereby further depressing coke prices. Bottom Line: Global iron ore and coking coal prices are also vulnerable to the downside. Investment Implications From a macro perspective, investors can capitalize on these themes via a number of strategies: Shorting iron ore and coal prices, or these commodities producers' stocks. Chart 16Chinese Steel And Coal Shares:##br## Puzzling Drop Amid High Profit Chinese Steel And Coal Shares: Puzzling Drop Amid High Profits Chinese Steel And Coal Shares: Puzzling Drop Amid High Profits Going short the Indonesian rupiah (and possibly the Australian dollar) versus the U.S. dollar. Australia and Indonesia are large exporters of coal and industrial metals to China - they account for 30% and 40% of Chinese coal imports, respectively, so their currencies are vulnerable. Notably, although steel and coal prices are still well above their 2015 levels and producers' profit margins are very elevated, share prices of Chinese steel makers and coal producers have dropped almost to their 2015 levels (Chart 16). From a top-down standpoint, it is hard to explain such poor share price performance among Chinese steel and coal companies when their profits have been booming. Our hunch is that these companies have been forced by the government to shoulder the debt of the peer companies that were shut down. This is an example of how the government can force shareholders of profitable companies to bear losses from restructuring by merging zombie companies into profitable ones. On a more granular level, rapidly expanding EF steel-making capacity in China will lead to outperformance of stocks related to EF makers, graphite electrode producers and domestic scrap steel collecting companies. First, demand for graphite electrodes continues to rise, as EF steel production expands. Prices of graphite electrodes may stay high for quite some time (Chart 6 above, top panel). Second, scrap steel prices may go higher or stay high to encourage more domestic scrap steel collection. Companies who collect domestic scrap steel may soon have beneficial policy support, which will create huge potential for expansion (Chart 6 above, bottom panel). Third, EF makers will also benefit due to strong sales of electric furnaces. As a final note, equity investors should consider going long thermal power producers versus coal producers as thermal power producers will benefit from falling coal prices. Ellen JingYuan He, Associate Vice President Frontier Markets Strategy EllenJ@bcaresearch.com 1 Please see Emerging Markets Strategy Special Report, "China's 'De-Capacity' Reforms: Where Steel & Coal Prices Are Headed", dated November 22, 2017, available at ems.bcaresearch.com. 2 "Ditiaogang" is low-quality steel made by melting scrap metal in cheap and easy-to-install induction furnaces. These steel products are of poor quality, and also lead to environmental degradation. 3 The big divergence between crude steel production expansion and steel products output contraction last year was due to both the removal of "Ditiaogang" and statistical issues. "Ditiaogang" is often converted into steel products like rebar and wire rods. As steel produced this way is illegal, it is not recorded in official crude steel production data. However, after it is converted into steel products, official steel products production data do include it. 4 Please see Emerging Markets Strategy Special Report, "China Real Estate: A New-Bursting Bubble?", dated April 6, 2018, available at ems.bcaresearch.com. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Highlights Slower nominal GDP growth explains virtually all of the increase in China's debt-to-GDP ratio over the past ten years. The authorities were unwilling to restrain debt growth as it became obvious that nominal income was decelerating because this would have only exacerbated the economic downturn. Excess private-sector savings forced the Chinese government to rely on debt-financed investment by state-owned companies (SOE) and local governments in order to keep aggregate demand elevated. Financial deregulation also encouraged debt accumulation. Debt growth linked to speculative activity can be curbed without endangering the economy, but a lasting solution to the surplus savings problem will require consumers to spend more. This will take a while. At some point over the next few years, the central government will transfer a large fraction of SOE and local government debt onto its own balance sheet. The risk to investors is that this "debt nationalization" happens reactively rather than proactively. Feature If there are too many pro-cyclical factors in the economy, cyclical fluctuations are magnified and there is excessive optimism during the period, accumulating contradictions that could lead to the so-called Minsky Moment. - Zhou Xiaochuan, Former Governor of the People's Bank of China, October 19, 2017 The Calm Before The Storm? Stability begets instability. That is the nature of business cycles, Hyman Minsky famously argued. Rising confidence leads to excessive risk-taking, higher asset prices, and mounting economic imbalances. Eventually the mood sours. Like Wile E. Coyote running off a cliff, investors look down and see that there is nothing but thin air between them and the ground below. Panic ensues. Is China on the verge of its own Minsky Moment? A glance at the evolution of its debt-to-GDP ratio would certainly say so. But before running towards the exit door, consider the following: People have been fretting about spiraling Japanese government debt levels for over twenty years now. And yet, interest rates remain at rock-bottom levels in Japan. China's Savings Glut In many respects, China finds itself facing similar problems to those that have haunted Japan. The simultaneous bust in equity and real estate prices in 1990 sent Japan's private sector into a prolonged deleveraging cycle (Chart 1). In order to prop up demand, the Japanese government was forced to run large budget deficits. In effect, the government had to absorb the excess savings of the private sector with its own dissavings. The abundance of domestic private-sector savings forestalled a financial crisis, but it also led to today's gross government debt-to-GDP ratio of 240%. Like Japan, China suffers from a dearth of spending, or equivalently, an abundance of savings. The IMF estimates that Chinese gross national savings reached 46% of GDP in 2017. While this is down from a peak of 52% of GDP in 2008, it is still abnormally high for any major economy, even by emerging market standards (Chart 2). Chart 1 Japan Relied On Large Fiscal Deficits And Current Account Surpluses To Offset The Rise In Private-Sector Savings Japan Relied On Large Fiscal Deficits And Current Account Surpluses To Offset The Rise In Private-Sector Savings Japan Relied On Large Fiscal Deficits And Current Account Surpluses To Offset The Rise In Private-Sector Savings Chart 2China's Savings Rate Stands Out Even By EM Standards China's Savings Rate Stands Out Even By EM Standards China's Savings Rate Stands Out Even By EM Standards By definition, whatever a country saves must either be invested domestically or channeled abroad via a current account surplus. China's savings rate has edged lower over the past ten years, but its current account surplus has dropped even more, falling from nearly 10% of GDP in 2007 to 1.4% of GDP at present. As a result, investment as a share of GDP has actually risen to 44%, a three-point increase since 2007 (Chart 3). The decline in China's current account surplus was inevitable (Chart 4). In 2007, China accounted for 6% of global GDP in dollar terms. Today it accounts for 15%. Having a massively undervalued currency, as China had in 2007, is just not politically tenable anymore, especially with Donald Trump in the White House. Simply put, China has become too big to continue exporting its way out of its problems. Chart 3Since The Great Financial Crisis, Chinese Savings Have Been Channeled Into Domestic Investment, Not Funneled Abroad Since The Great Financial Crisis, Chinese Savings Have Been Channeled Into Domestic Investment, Not Funneled Abroad Since The Great Financial Crisis, Chinese Savings Have Been Channeled Into Domestic Investment, Not Funneled Abroad Chart 4Undervalued Currency And Massive Current Account Surplus: Modus Operandi Of The Past Undervalued Currency And Massive Current Account Surplus: Modus Operandi Of The Past Undervalued Currency And Massive Current Account Surplus: Modus Operandi Of The Past Debt As The Conduit Between Savings And Investment How does a country transform savings into investment? In an economy like China where the stock market at times appears to be little more than a casino, the answer is that credit markets must play the dominant role. Households or firms with surplus savings park their funds in banks or other financial institutions. These institutions channel the savings to willing borrowers. Debt ends up being the natural byproduct of surplus savings. China is still a relatively poor country with a lot of catch-up potential. Capital-per-worker is a fraction of what it is among advanced economies (Chart 5). Even with its bleak demographics, China would need to grow by around 6% per year over the next few years just to converge with South Korea in output-per-worker by 2050 (Chart 6). All this means that China needs to invest more than most other economies, which is only possible if it saves more than other economies. Chart 5China Has More Catching Up To Do (1) Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Chart 6China Has More Catching Up To Do (2) China Has More Catching Up To Do (2) China Has More Catching Up To Do (2) Unfortunately, one can have too much of a good thing. The fact that China's capital stock-to-output ratio has risen dramatically in recent years means that the economy is already investing too much. And the optimal amount of investment will only fall over time as potential GDP growth continues to decelerate. Unless savings come down, China will find itself increasingly awash in excess capacity. Chart 7If Only GDP Growth Did Not ##br## Decelerate Over The Past Ten Years Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Slower trend growth will also make deleveraging more difficult to achieve. The overall stock of nonfinancial debt grew at an annualized rate of 18.8% between 2008 and 2017. Notably, this growth rate was not much higher than the one of 16.5% between 2003 and 2007 - a period when the debt-to-GDP ratio was broadly stable. The main difference between the two periods lies in the denominator of the debt-to-GDP ratio, not in the numerator: Nominal GDP expanded at an annualized rate of 11.2% between 2008 and 2017, a sizable retreat from the pace of 18.4% between 2003 and 2007. Chart 7 shows that the debt-to-GDP ratio today would be virtually identical to its end-2007 level had nominal GDP continued to grow at its 2003-2007 pace over the past ten years. Financial Deregulation Has Exacerbated The Debt Problem The Chinese government's reluctance to crack down on credit growth was motivated by the desire to support aggregate demand. However, in turning a blind eye to what was happening in credit markets, a lot of debt was generated that was not directly tied to the intermediation of savings into investment. Chart 8Debt And Capital Accumulation Went Hand In Hand Debt And Capital Accumulation Went Hand In Hand Debt And Capital Accumulation Went Hand In Hand Debt can be created when someone borrows money to finance the purchase of goods or services. Debt can also be created when someone borrows money to finance the purchase of pre-existing assets. Crucially, while the former typically requires additional "savings" (i.e., someone needs to reduce their spending relative to their income), the latter does not.1 Granted, savings can still play an indirect role in facilitating debt-financed asset purchases. Financial assets are typically backed by something of value. A mortgage is backed by a piece of property. A corporate bond is backed by both the tangible and intangible capital that a firm possesses. The more a country has been able to save over time, the larger its capital stock will be. China, of course, has been saving like crazy for years. It is thus no surprise that its debt-to-GDP ratio has soared as its capital stock has expanded (Chart 8). Financial deregulation in China has allowed a large share of its capital stock to repeatedly shift hands. Debt has often been created in the process. The problem is that debt-financed asset purchases drive up asset prices, sometimes to unsustainable levels. And the higher the price of the asset, the greater the risk that it will not yield enough income to cover the borrowing costs. When asset prices are rising, borrowers and lenders are apt to disregard this risk, figuring that they can always sell the asset at a high enough price to pay back the loan. But once prices start falling, reality sets in very quickly. Stability begets instability. Consumers Need To Step Up The authorities are keenly aware of the risks discussed above. This is the key reason why they are clamping down on the shadow banking system, which has increasingly become the main source of speculative lending in China. We expect the pressure on shadow banks to persist in 2018. This will continue to weigh on credit growth. The more vexing challenge is how to reduce excessive household savings. The government's current strategy of cramming down the capital stock by taking out excess capacity from sectors such as steel, coal, and solar may be better than nothing, but it still pales in comparison to a strategy of encouraging consumer spending. Higher consumer spending would obviate the need for state-owned companies and local governments to keep people employed in make-work projects. The good news is that there are plenty of ways that China can boost household consumption. Government spending on education, health care, and pensions as a share of GDP is close to half of the OECD average (Chart 9). Increasing social transfer payments would give households the wherewithal to spend more. Unlike in most countries, the poor in China are net savers (Chart 10). Expanding the social safety net would discourage precautionary savings. Chart 9Chinese Social Welfare Spending ##br##Is Lagging The OECD Average Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Chart 10Low Income Households Are Net ##br##Savers In China Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? The Chinese income tax structure is fairly regressive. Poor households face an effective income tax rate exceeding 40%. This is well above OECD norms (Chart 11).2 A more progressive tax system would boost spending among poorer households. It would also curb inequality, which has increased sharply over the past few decades (Chart 12). The saving rate among the richest 10% of Chinese earners is close to 50%. Policies that shift income from the rich to the poor would reduce overall household savings. Chart 11High Tax Burden For ##br##Low Income Households In China Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Chart 12Shifting Income To Poorer Households Would Reduce ##br##China's Household Savings Rate Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Debt Nationalization Is Inevitable Chart 13Ratio Of Workers-To-Consumers Is Peaking,##br## And China Is No Exception Ratio Of Workers-To-Consumers Is Peaking, And China Is No Exception Ratio Of Workers-To-Consumers Is Peaking, And China Is No Exception Realistically, reforms aimed at encouraging consumption will take a while to implement. In the meantime, debt levels are likely to keep rising. Much of China's debt burden remains on the books of state-owned companies and local governments. At some point over the next few years, the central government will transfer a large fraction of this debt onto its own balance sheet. This would ease concerns about a mass wave of defaults. The key question for investors is whether this de facto "debt nationalization" is done proactively or reactively in response to a crisis. If the latter occurs, investors should steer clear of Chinese assets, as well as China-related plays such as commodities and commodity currencies. If the former pans out, global risk assets could rally. While the truth will fall somewhere between those two extremes, our bet is that the proactive view will prove closer to the mark, at least relative to market expectations (keep in mind that Chinese banks are trading below book value, so a lot of bad news has already been priced in). The Chinese authorities talk a lot about the importance of reducing moral hazard, but in practice, they have shown very little tolerance for defaults. Just as they did in the early 2000s, government leaders could commission state-owned asset management companies to purchase distressed debt from banks and other lenders at inflated prices. Chinese financials, which are nearly 70% of the H-share index, will benefit. Will investors balk at the prospect of the Chinese government blowing out the budget deficit in order to rescue insolvent borrowers? There might be some short-term panic, but as has been the case with Japan, as long as there are plenty of excess domestic savings to go around, the risk of a debt crisis will remain minimal. Indeed, the issuance of more government debt would help alleviate what has become a critical problem for Chinese savers: The lack of safe, liquid domestic assets available for purchase. What is true, from a longer-term perspective, is that the combination of higher debt and slower growth will eventually create a strong incentive for the Chinese government to inflate away debt. As in many other countries, China's "support ratio" -- broadly defined as the ratio of workers-to-consumers -- has peaked (Chart 13). As the growth of output and income falls behind consumption growth, China's savings glut will become a thing of the past. Rather than raising rates, the PBOC will just let the economy overheat. Such a day of reckoning is probably still at least five years away, but eventually inflation will return to China. Concluding Thoughts On The Current Market Environment A true "Minsky moment" in China - one where the financial sector seizes up due to spiraling fears of bankruptcies and defaults - is not in the cards. Nevertheless, China's economy is slowing, and growth is likely to decelerate further over the next few quarters as the authorities restrain credit growth and the property market continues to cool. The slowdown in Chinese growth is occurring at the same time as the economic data has been deteriorating around the world. The equity component of our MacroQuant model - which is highly sensitive to changes in the direction of growth - has been in bearish territory for two straight months (Chart 14). Our base case remains that global growth will stabilize over the next few months at an above-trend pace. Global bond yields are still near record-low levels and fiscal policy is moving in a more stimulative direction (Chart 15). It would be odd for the global economy to deteriorate sharply in such an environment. Chart 14MacroQuant Model Suggests Caution Is Warranted Is China Heading For A Minsky Moment? Is China Heading For A Minsky Moment? Trade protectionism is an obvious risk to this sanguine cyclical view. BCA has long argued that globalization is under threat from the combination of rising populism and the end of America's role as the world's sole superpower. However, the retreat from globalization will occur in fits and starts. Just as investors were overly complacent about protectionism a few months ago, they have become overly alarmist now. Both the U.S. and China have a strong incentive to reach a mutually-satisfying agreement over trade. President Trump has been able to shrug off the decline in equities because his approval rating has actually risen during the selloff (Chart 16). However, if the problems on Wall Street begin to show up on Main Street - as is likely to happen if stocks continue to fall - Trump will change his tune. Chart 15Global Economy Buttressed By ##br##Accommodative Fiscal And Monetary Policy Global Economy Buttressed By Accommodative Fiscal And Monetary Policy Global Economy Buttressed By Accommodative Fiscal And Monetary Policy Chart 16Trump's Approval Rating Has ##br##Actually Risen During Equity Selloff Trump's Approval Rating Has Actually Risen During Equity Selloff Trump's Approval Rating Has Actually Risen During Equity Selloff For its part, the Chinese government is also looking to strike a deal. The U.S. exported only $131 billion in goods to China last year. This is already less than the $150 billion in Chinese goods that Trump has targeted for tariffs. China simply cannot win a tit-for-tat trade war with the United States. Bottom Line: The near-term picture for global equities and other risk assets is murky, but the 12-month cyclical outlook is still reasonably upbeat. Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 For instance, if someone buys stock on margin or takes out a second mortgage on their house, new debt is created without anyone having to cut back on spending. In the context of China, imagine a financial institution which funds the purchase of a building by issuing a certificate of deposit or by selling a "wealth management" product. Both the asset and liability side of the financial institution's balance sheet go up (i.e., new debt is created). Suppose further that the company that sold the building puts the proceeds into a certificate of deposit or wealth management product. The entire transaction is self-financing. The example above illustrates that debt can go up in some situations even if everyone's spending habits remain the same. The need to intermediate savings is one source of debt growth, but it does not have to be the only one. 2 Please see "People's Republic Of China: Selected Issues," IMF Country Report, dated August 15, 2017. Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Highlights In China, the central bank and commercial banks conducted outright monetization of real estate inventories, which caused the property markets' recovery post 2015. Despite destocking, aggregate property inventories remain excessive. Elevated inventories, poor affordability, and policy tightening will depress property demand and lead to a contraction in construction activity. Slumping construction, along with a slowdown in infrastructure investment, pose downside risks to China's demand for commodities, materials and industrial goods. This is the main risk to EM stocks and currencies and the primary reason we maintain our negative stance on EM risk assets. Continue shorting Chinese property developers stocks versus U.S. homebuilders. Feature With a flurry of policy tightening directed at the real estate market in the past year, property demand in China has weakened. The latter typically leads property starts and real estate investment, and is coincident with real estate prices (Chart I-1). Is China entering another property downturn, and if so will it be shallow, or severe? Answers to these questions are important not only for Chinese stocks, but also for China-plays throughout the rest of the world. To shed light on this issue, this week we re-examine how large the imbalances in the Chinese real estate market actually are - with respect to both affordability and supply (the stock of housing and inventories). We also discuss policy objectives and investment implications. Proper Measures Of Inventories And Housing Stock Both purchases and prices of Chinese residential properties surged between 2015 and 2017, when the authorities implemented a property de-stocking policy. As a result, housing inventories declined significantly. Does this mean that one of the major imbalances, namely swelling inventories, has been eliminated? If imbalances, namely inventories and prices, in a property market are very minor, one can expect an ensuing adjustment to be benign. Conversely, if imbalances are large, it is reasonable to bet on a meaningful property market downturn. With respect to China's real estate inventory levels, data from the National Bureau of Statistics (NBS) which many analysts follow, indicates inventories of residential buildings have indeed declined, with a significant 33% drop in residential vacant floor space for sale (Chart I-2). The term "vacant" is used by the data provider to denote the floor space completed but not sold. Clearly, China's de-stocking strategy since 2015 has worked well. Chart I-1China: Real Estate Is Slowing Down China: Real Estate Is Slowing Down China: Real Estate Is Slowing Down Chart I-2Property Developers' Inventories: ##br##Completed But Not Sold Property Developers' Inventories: Completed But Not Sold Property Developers' Inventories: Completed But Not Sold However, data from the NBS on vacant space for sale is not all-encompassing. First, it includes only commodity buildings - i.e., those developed by real estate developers - and does not include buildings built by non-real estate developers. For example, companies, universities, organizations and even a group of individuals can construct both residential and non-residential buildings for their own use. Commodity buildings are just a small subset of total constructed buildings in China. According to NBS data, residential buildings by property developers account for only 26% of total constructed residential buildings in terms of floor space area completed. In brief, the inventory data that the majority of analysts use covers only a part of property construction (Figure I-1). Figure I-1The Breakdown Of Residential ##br##Real Estate Inventory China Real Estate: A Never-Bursting Bubble? China Real Estate: A Never-Bursting Bubble? Second, the vacant floor space data - shown in Chart I-2 and used by many analysts - only measures commodity buildings that have been completed but not sold. It does not account for those units that are under construction and have not been sold. The latter should also be counted as inventory because in China both residential and non-residential properties can be sold even when they are in the construction phase. Unlike advanced economies, in China the housing market is by far dominated by new construction. In particular, about 80% of residential commodity floor space sold are properties that are still under construction. This is drastically different from real estate markets in the U.S. and other developed countries, where the secondary housing market is a major source of supply. Given the above,1 we propose several alternative measures that aim to more accurately reflect the real picture of Chinese property inventory. Real Estate Inventory To capture the flow of the entire residential property supply in China, we calculate the difference between cumulative floor space started and cumulative floor space sold over the period of 1995-2017. This produces a new measure of total space not yet sold (i.e., available for sale), which includes areas both under construction and completed. This is a much more comprehensive measure of the total inventory than other commonly used measures. It is important to note that this measure takes into account both types of floor space available for sale: under construction and completed. The top panel of Chart I-3 illustrates that our derived measure of residential inventory - cumulative floor space started minus cumulative floor space sold - currently stands at 2.5 billion square meters or 27 billion square feet. This is about eight times greater than the NBS measure of vacant floor space - completed by property developers but not sold, which presently amounts to only 0.3 billion square meters or 3.23 billion square feet. On the bottom panel of Chart I-3, we estimate how many months of sales it will take to clear this housing inventory. Our findings reveal that even though our new inventory measure for the residential sector has fallen sharply due to the de-stocking policy, it still takes 22 months of last year sales to clear it. This is much higher than the completed by property developers but unsold vacant space, which presently stands at 2.5 months of last year sales. Provided that (1) most housing for sale in China is new construction, and (2) it can be sold at any stage of the construction cycle, we believe our new estimate of residential inventory that is equal to 22 months of last year sales is a more accurate reflection of reality. We computed a similar measure of inventory for non-residential properties that includes malls, offices, and warehouses. The top panel of Chart I-4 shows that the proper inventory levels for the non-residential sector have kept rising to new record highs in absolute terms. Relative to floor space sold last year, inventories still stand at 170 months of sales (Chart I-4, bottom panel). Chart I-3Our Measure Of Residential Inventories: ##br##Floor Space Available For Sale Our Measure Of Residential Inventories: Floor Space Available For Sale Our Measure Of Residential Inventories: Floor Space Available For Sale Chart I-4Our Measure Of Non-Residential Inventories: ##br##Floor Space Available For Sale Our Measure Of Non-Residential Inventories: Floor Space Available For Sale Our Measure Of Non-Residential Inventories: Floor Space Available For Sale Clearly, China's non-residential markets still carry excessive inventories. It would be misleading to use completed but unsold data for the non-residential sector, which accounts for roughly 14 months of sales. Similar to the residential commodity buildings market, about 65% of non-residential commodity buildings sold are those that are still under construction. In short, despite the decline from 2015's exceptionally high levels, inventories for both residential and commercial properties are still extremely elevated. Furthermore, the inventory-to-sales ratio is not a good indicator for the property market outlook because it is heavily influenced by sales. When sales - the denominator of this ratio - are weak, this inventory ratio is high, and vice versa. In particular, this ratio has been a poor indicator for the property market in China, where sales of properties have been deeply influenced by government policies. Whenever sales dropped and this ratio surged, the authorities would begin easing policies, spurring sales to rise and allowing the market - prices, floor space starts and construction - to recover. As a final note, these inventory data show floor space built by property developers only. Stock Of Housing The measure of per-capita living space gauges the existing stock of housing. Hence, it is a structural measure. Still being a low-income country, China is often perceived to offer enormous construction potential. However, some statistics on per-capita living space are revealing. The NBS data show that the 2016 per-capita living space for both urban and rural area has risen to 36.6 square meters and 45.8 square meters, respectively (Chart I-5). By comparison, in Korea and Japan, living space per capita (the entire population average) is only 33 and 22 square meters, respectively. Chart I-5China: Per Capita Living ##br##Has Grown Dramatically China: Per Capita Living Has Grown Dramatically China: Per Capita Living Has Grown Dramatically Our calculation of per-capita urban living space based on the NBS building construction data also show similar results - 38 square meters for 2017. Consequently, these statistics on per-capita living space are supported by historical construction data, and hence are reliable. Both NBS per-capita living space data and our calculated per-capita living space data confirm that there is already massive stock of residential property in China - the nation's current existing residential floor space area already amounts to 30.8 billion square meters (332 billion square feet). Furthermore, the stock of housing is relatively new with 88% of this living space built in the past 20 years. Assuming the floor space area of each house is on average 90 square meters (970 square feet), we infer that on average every urban household already owns 1.3 houses. This is actually in line with the results of several domestic household surveys, which conclude that 20-25% of houses owned by urban residents are neither being used for living nor for renting out. Provided not every household in China owns a house, and that a meaningful share of the population still lives in smaller and older housing, these data suggest there have been considerable speculative/investor purchases of housing over the past 10 years. Many high-income individuals own multiple properties (that are often kept vacant) while a still-considerable number of families live in poor conditions. Bottom Line: China has constructed enormous amounts of real estate since 2002. Furthermore, inventories are vast for residential and non-residential sectors alike. Such an oversupply of properties poses a considerable risk to construction activity going forward. Property Demand Weakness: Cyclical Or Structural? Very poor affordability, slowing rural-to-urban migration, demographic changes, tightening mortgage lending, a successful government-led clampdown on speculative activity and the promotion of the rental housing all point to both a cyclical and structural slippage in housing purchases in China. House Price-Income Ratios and Affordability House prices in China remain extremely high relative to disposable income. By using NBS 70-city residential average price, our calculation shows for an average household (assuming double income earners) it will take 10.5 years of its disposable income to buy a 90-square-meter (equivalent to 970 square feet) house at current prices (Chart I-6). The same ratio for the U.S. is presently 3.4 and at the peak of U.S. housing bubble in 2006 it was 4. In regard to the ability to service mortgage payments, annual interest costs account for 45% of average household disposable income (assuming a double income household) when buying a 90 square meter house and assuming 20% down payment (Table I-1). Chart I-6House Price-Income Ratio: ##br##China & The U.S. House Price-Income Ratio: China & The U.S. House Price-Income Ratio: China & The U.S. Table I-1House Price-To-Income Ratios ##br##And Affordability China Real Estate: A Never-Bursting Bubble? China Real Estate: A Never-Bursting Bubble? If we use another data provider - Choice, covering 100 cities, house price per a square meter is 60% higher than the NBS 70-city residential average price. Using Choice house price data, the house price-to-income ratio is 17, and affordability - the share of interest payments as a percentage of disposable household income - is 72%. Clearly, there is a huge gap between these two aggregate measures of residential property prices. In this report, we use conservative (low) prices from the NBS, which still reveals that house prices and interest payments are exceptionally high relative to disposable income for a double-income family. Table I-1 contains house price-to-income ratios and affordability ratios for 31 provinces using the house prices from NBS. Given the average urban household already owns more than one property, it is reasonable to expect that a considerable proportion of potential future demand for housing will come from rural residents as urbanization continues, or as rural residents seek to buy homes in the city for access to better quality education in the urban areas for their children. However, rural residents' current and potential (when they move to cities) disposable income is much lower than the urban's. Therefore, housing affordability is a bigger challenge for them. Rural-to-Urban Migration Even though urbanization is an ongoing process in China and will continue for many years, the pace is slowing (Chart I-7). The number of individuals moving from rural areas to cities as a percentage of the urban population is decreasing. This will translate into decelerating growth rate in demand for urban residential properties. Chart I-7China: The Pace Of Urbanization Is Slowing China: The Pace Of Urbanization Is Slowing China: The Pace Of Urbanization Is Slowing The second panel of Chart I-7 illustrates that rural-to-urban net migration accelerated in the early 1990s and has been between 15-18 million people per year over the past 20 years. However, as a share of the urban population, net migration has fallen from 4.5% in the late 1990s to 2% today (Chart I-7, third panel). Overall, urban population growth has slowed below 3% (Chart I-7, bottom panel). In brief, the slowdown in net migration and, consequently, decelerating urban population growth will cap structural housing demand that has been booming over the past 20 years. Poor Demographics The Chinese population is aging rapidly. The proportion of citizens who are over the age of 65 has risen from 8% of the population in 2007 to 11.4% as of last year and will continue rising rapidly. Given Chinese life expectancy is currently at about 76 years, senior citizens cohort will leave a large number of houses to their children or grandchildren over the next 10-15 years. The reason behind this is because the former demographic cohort (11.4% of the total population) is larger than the 10-19-year-age group which accounts for only 10.5% of the total population. The latter would have been a major source of property demand over the next 10 years, as Chinese tradition requires them to own a house before marriage. However, this is no longer the case. For this generation - born in the late 1990s and 2000s and by the time they get married (in general at the age of around 25 or a bit later), each newly-formed family could potentially inherit four houses from their parents and grandparents. Tightening mortgage lending As part of the current property related restrictive policies, mortgage interest rates have been on the rise for both first- and second-home buyers. Mortgage rates have risen by 74 basis points in the past 12 months - from 4.52% to 5.26%. Additionally, banks have been tightening credit standards. Given house prices are very high relative to income, a small increase in mortgage rates meaningfully increases the share of disposable income that must be allocated to interest payments on mortgages. For example, with the house price-to-income ratio at 10.5 and down payment of 20% of house price for the average home buyer in China, a 75-basis-point increase in mortgage rates would lift the share of interest payments on a mortgage from 45% to 51% of disposable income. Hence, higher borrowing costs over the past year as well as the ongoing tightening in credit standards will continue to discourage property buyers. Mortgage loan growth has rolled over after booming between 2015 and 2017, yet at a 22% annual growth rate, it remains very high (Chart I-8). Policy-led clamp-down of speculation President Xi Jinping's mantra that "housing is for living in, not for speculation" - proclaimed in December 2016 - is the focal point of the government's current policies. Many regulations implemented by both the central government and local governments over the past 15 months have been aimed at reducing speculative purchases. The promotion of the housing rental market In large cities residential rental yields fluctuate between 1-2.5% (Chart I-9). This compares with mortgage rate of 5.3%. Currently, renting is significantly cheaper than buying. This may encourage renting in the long term. Rising demand for rental housing might be met by the available stock of empty apartments that investors have been accumulating over the years. If this occurs, it will reduce demand for new home purchases. Chart I-8China: Mortgage Lending Has Been Booming China: Mortgage Lending Has Been Booming China: Mortgage Lending Has Been Booming Chart I-9China: Residential Rental Yields Are Very Low China: Residential Rental Yields Are Very Low China: Residential Rental Yields Are Very Low Meanwhile, the central government is determined to develop a rental market by constructing rental housing. If building of rental housing offsets the potential decline in property construction, it will make our negative view on construction volumes widely off the mark. The crucial factor to watch is financing. If credit supply slows meaningfully, there will be less available financing for overall construction, including rental. Any gains by rental construction will be overwhelmed by a decline in the building of residential and commercial real estate. In turn, financing is contingent on the government deleveraging campaign. If the authorities adhere to their pledge of deleveraging, a slowdown in credit growth will dampen overall construction activity. There can be no construction without credit. Furthermore, it takes only a deceleration in credit growth, i.e., a negative credit impulse, to depress construction volumes. That is why we cover China's credit cycle dynamics in such details in our regular reports. Bottom Line: Chinese property demand is facing numerous cyclical and structural headwinds. Policy Driven Market China's central and local government policies have over time and in different combinations substantially influenced the country's housing market on both the supply and demand sides. Over the past two decades, each time the government implemented restrictive policies (for example, raising down-payment ratios, increasing policy or mortgage rates, setting restrictions on mortgage lending, and so on), the real estate market slowed and housing prices softened. The opposite has also held true - each time the government introduced stimulus, housing prices surged as buyers quickly dove into the market. Chart I-10 illustrates the interaction between government property related regulations and the domestic housing market. Chart I-10China: Policy-Driven Property Market China: Policy-Driven Property Market China: Policy-Driven Property Market The biggest problem with such policies in the long run is that the authorities want to control both prices and volume - they want flat prices and moderately rising volumes. However, no government can control both prices and volumes simultaneously in any industry. China's real estate market is not an exception. Even in a completely closed socialist system, controlling prices and volume simultaneously is almost impossible. As the authorities adhere to their policy objectives of controlling financial risks and unwinding financial excesses, thereby focusing on property price control over the next 12 months, we believe property starts and construction activity will shrink. Monetization of Housing Inventories In 2015-'17 Understanding what was behind the housing market's strong recovery since late 2015 is critical to assessing the outlook. Since the summer of 2015, authorities were not only easing purchasing restrictions and lowering mortgage rates, but they were also implementing outright monetization of housing inventories. After inventories of both residential and non-residential properties swelled, the central government commenced a de-stocking strategy in 2015, mainly through a monetized slum reconstruction program and by encouraging migrant workers to buy housing in smaller cities near their hometowns. The de-stocking strategy focused on smaller cities where inventories had mushroomed. Given tier-1 cities account for only 6% of floor space started by property developers, and most construction in recent years has been taking place in tier-2 and smaller cities, these policies had a substantial positive impact on national sales, as well as drawing down inventories - ultimately spurring a construction recovery. 1. The government's slum area reconstruction policy has been the major driver behind de-stocking within the residential property market. The People's Bank of China (PBoC) has provided a significant amount of financing in the form of pledged supplementary lending (PSL) directly to homebuyers that was intermediated by three policy banks (China Development Bank, Agricultural Development Bank of China and Export-Import Bank of China). To shed more detail on the PSL mechanism, the central bank lends credit to the three policy banks at very low interest rates. These policy banks in turn lend directly to local government and regional property developers (mainly in tier-2 and smaller cities). These entities then turn and buy slums from their owners which puts cash in the hands of these sellers. Consequently, a large number of households suddenly receive large cash infusions - essentially disbursed by the central bank - that can be used to purchase new and better properties. The outstanding amount - total financing - via the PSL has risen from RMB 383 billion in 2014 to RMB 971 billion in 2016. The total amount of the PSL disbursed for the slum reconstruction program over 2014-2017 amounted to 3 trillion, or 3.6% of 2017 GDP, as of March 31, 2018. The interest rate on the PSL currently stands at a mere 2.75%. It appears that huge amounts of cheap money have been directly injected into the real estate market by the central bank alone. This slum reconstruction program has had a material impact on construction activity. Chart I-11 portends that slum area reconstruction accounted for about 20% of floor space sold in 2017. Chart I-11China: Slum Reconstruction ##br##Has Had Meaningful Impact China: Slum Reconstruction Has Had Meaningful Impact China: Slum Reconstruction Has Had Meaningful Impact 2. In addition to the PSL financing, Chinese housing mortgages have increased by 85%, or by 11 trillion RMB in the past two and a half years - since the beginning of China's de-stocking policy. The sum of PSL financing and mortgage lending has been RMB 14 trillion (or $2.2 trillion) during the same period. Hence, not only has the PBoC financed the real estate market directly, but it has also allowed banks to flood the system with money to liquidate housing inventories. As we have argued in our series of reports, bank credit does not come from anyone's savings. Commercial banks originate loans out of thin air.2 In short, altogether these actions constitute outright monetization of real estate inventories and that caused the property markets' recovery post 2015. A Downturn Ahead? Since early 2017 and especially in the wake of last October's Party Congress, the authorities have shifted their policy focus from "de-stocking" to "eliminating speculative demand". Recent weakness in both demand and prices are a reflection of the current policy focus. This time, the government seems to have more determination to break popular perception that property prices will rise forever, and that investing in property markets cannot go wrong. Therefore, we sense the government's objective is to achieve flat or mildly declining property prices to prevent the return of speculators. In order to avoid a further ballooning of the real estate bubble, the government will raise the bar for another round of property stimulus. Therefore, if the authorities are successful in persuading speculators that prices will not rise much further in the years to come, speculative demand will wane. At the same time, not many first-time homebuyers can afford to buy at current prices. This will create an air pocket in sales and prices will deflate, at least modestly. Facing shrinking revenues and being overleveraged, real estate developers will reduce new starts, and property construction volumes will likely contract by 10% or so. Notably, floor space started by property developers in aggregate declined by 27% between 2012 and 2016 (Chart I-12). The construction slump in China, in tandem with rising supplies of commodities, led to a collapse in commodities prices in 2012-'15 (Chart 12). Hence, a decline in property construction is not unprecedented, even amid robust national income growth. We believe the acute structural imbalances will likely result in a property market downturn commensurable if not worse than those that occurred in 2011-'12 and 2014-'15. While the government will try to avoid a sudden bust, a 10% decline in both property prices and construction volumes in the next 12-18 months is our baseline scenario. The budding contraction in cement and plate glass production suggests that overall construction activity is already decelerating (Chart I-13). Chart I-12China: Property Cycles ##br##And Commodities Prices China: Property Cycles And Commodities Prices China: Property Cycles And Commodities Prices Chart I-13China: Nascent Contraction In Cement ##br##And Plate Glass Production China: Nascent Contraction In Cement And Plate Glass Production China: Nascent Contraction In Cement And Plate Glass Production Bottom Line: The Chinese authorities will for now maintain their current restrictions on the property market to contain financial excesses and risks in the system. This, amid lingering elevated inventories and price excesses, poses considerable downside risks to the mainland real estate market. Investment Implications Our view remains that construction activity in China is set to slump from a cyclical perspective, at least. At 13.2 billion square-meter (142 billion square-feet) the total 2017 residential and non-residential floor area under construction was immense (Chart I-14). This, along with a slowdown in infrastructure investment due to tighter control on local government finances, pose downside risks to China's demand for commodities, materials and industrial goods. This is the reason why we have been and remain bearish on commodities, Asian trade and EM risk assets. It appears that several commodities prices are finally beginning to roll over which is consistent with a slowdown in the mainland's construction activity (Chart I-15). Chart I-14China's Total Building Construction: ##br##Level And Annual Growth China's Total Building Construction: Level And Annual Growth China's Total Building Construction: Level And Annual Growth Chart I-15A Budding Downtrend In ##br##Commodities Prices A Budding Downtrend In Commodities Prices A Budding Downtrend In Commodities Prices China's construction activity is much larger than exports to the U.S. and EU combined. Hence, overall industrial activity in China is set to decelerate dragging down Asian trade flows and commodities prices despite robust domestic demand in the U.S. and EU. This heralds underweighting/shorting EM stocks, currencies and credit versus their DM counterparts. We also reiterate our long-standing recommendation of shorting Chinese property developers versus U.S. homebuilders. Chart I-16 depicts that the Chinese property developers listed in A-share market have a debt-to-equity ratio of 6 and the cash flow from operations for the median of 76 property developers has begun contracting again. Further relapse in property sales will cause their financial position to deteriorate and limit their ability to launch new or complete existing construction. In regard to U.S. homebuilders, the fundamentals in the U.S. housing market are much better than those in China. While rising U.S. interest rates could be a headwind for U.S. homebuilder share prices, they stand to resume their outperformance versus Chinese property developers (Chart I-17). Chart I-16China: Median Property Developer's ##br##Financial Ratios Are Worsening China: Median Property Developer's Financial Ratios Are Worsening China: Median Property Developer's Financial Ratios Are Worsening Chart I-17Short Chinese Property Developers / ##br##Long U.S. Homebuilders Short Chinese Property Developers / Long U.S. Homebuilders Short Chinese Property Developers / Long U.S. Homebuilders Ellen JingYuan He Senior Editor/Associate Vice President EllenJ@bcaresearch.com Arthur Budaghyan, Senior Vice President Emerging Markets Strategy arthurb@bcaresearch.com 1 Other oft-used measures of inventories are not correct either. Some analysts use floor space under construction data as a proxy for inventory - this is technically not correct as the data includes both the area that has already been sold in advance and the area that has been completed and sold. Others use cumulative floor space started minus cumulative floor space completed - this is also not correct as cumulative floor space completed includes areas that have not yet been sold. 2 Please see Emerging Markets Strategy Weekly Report "Is Investment Constrained By Savings? Tales Of China And Brazil," dated March 22, 2018, the link is available on page 20. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Highlights China and Brazil are two extremes in regard to investment and savings - the former saves and invests a lot, the latter very little. The key difference between Brazil and China is neither the existing amount of deposits nor their propensity to save. Rather, it is their real economies' capacity to produce goods and services. Regardless of how capital expenditures are financed, when inputs for capital spending are procured domestically it is recorded as national "savings," but when they are imported there is no change in the level of national "savings." In China, policymakers are currently being forced to walk a very thin line between inflation and deflation. Brazilian consumers do not need to save more for companies to get financing for their investments. Instead, businesses - along with facilitation from the government - should build the supply side. Banks can finance the latter by originating loans "out of thin air." However, the natural consequence of this adjustment in Brazil will be considerable currency deprecation. Feature The Fallacy This is the fifth report in our series on money, credit, savings and investment. Its objective is to show that financing of investments is not constrained by national and foreign savings. This report argues against a postulate in mainstream economic literature which holds that in order to invest, nations with low savings rates need to either reduce consumption and boost national savings or to borrow foreign savings. Some examples of this economic thesis can be seen here: As Lindner neatly summarizes: "Many economists hold the position that "saving finances investment." They argue that saving - a reduction of consumption relative to income - is necessary for the provision of loans and the financing of investment." (Lindner 2015).1 Linder also provides other examples suggesting that this thesis is well entrenched in the economic theory and analysis. For example, he cites Gregory Mankiw's influential introductory macroeconomics textbook that upholds: "Saving is the supply of loans - individuals lend their saving to investors, or they deposit their saving in a bank that makes the loan for them. [. . . ] At the equilibrium interest rate, saving equals investment, and the supply of loans equals the demand." (1997, p. 63) (Lindner 2015).2 This mainstream economic thesis - that financing is constrained by savings - is intuitive, and not surprisingly many investors take it for granted. Yet this is a false proposition. This thesis is correct for barter economies but is not pertinent to modern economies with their own banking systems and national currencies. Further, Lindner (2015)3 argues: "The fallacies loanable funds theory commits might be explainable by the mis-application of some ideas and concepts of neoclassical growth models - especially the Ramsey (1928), Solow (1956) and Diamond (1965) models - to the sphere of money and finance... The Ramsey and Solow models are models of real investment only. Financial markets, financial assets and financial saving do not play any role in those models. There is only one good which, for simplicity, will be called "corn". Corn has three functions: it can be consumed, invested and used as a means of payment since wages and interest payments are made with it..." Clearly, modern economies with their fiat money systems are much more complicated than a barter economies with no banks and money. The Veracity: Financing Is Different From "Savings" This and previous reports4 clarify and elaborate on the following aspects of banking, money creation and financing as well as savings and investments: 1. Attributing the lack of investment in many emerging market (EM) economies to their low savings is a major fallacy. Borio (2015)5 argues: "Crucially, the provision of financing does not require someone to abstain from consuming. It is purely a financial transaction and hence distinct from saving... The equality of saving and investment is an accounting identity that always holds ex post and reveals nothing about financing patterns. In ex post terms, being simply the outcome of expenditures, saving does not represent a constraint on how much agents are able to spend ex ante. If we step back from comparative statics and consider the underlying dynamics, it is only once expenditures take place that income and investment, and hence saving, are generated." 2. Banks do not need deposits or "savings" to lend. They create money/deposits when they originate loans or buy assets from non-banks. To settle payments with their peers as well as the central bank, they require reserves at the central bank. Reserves at the central bank - not client deposits - constitute true liquidity for banks. For a more detailed discussion on loan origination and money creation in absence of new deposits entering into the banking system, please refer to Appendix 1 and 2 on pages 14 and 18. Certainly, there are several factors such as regulations and shareholder preferences that can curtail banks' ability to expand their balance sheets. However, households' or nations' "savings" do not constrain banks' ability to originate new loans/create deposits. 3. In an economy where banks exist, "savings" and financing are very different things. Many investors use the term "savings" to refer to bank deposits. Yet, in macroeconomics, national and household "savings" are not related to deposits or money in the banking system at all. Chart I-1 demonstrates that there is no relationship between the savings and changes in the amount of money in the banking system. Chart I-1Savings And New Money ##br##Creation Do Not Correlate Savings And New Money Creation Do Not Correlate Savings And New Money Creation Do Not Correlate The confusion between national "savings" and financing creation is dealt with nicely again by Fabian Lindner. Having modelled it, Lindner argues: "... the aggregate economy's saving is equal to the newly produced tangible assets and inventories. That total saving is equal to just the increase in tangible assets ... (because) all changes in net financial assets in the economy add up to zero... Thus, for every economic agent increasing her net financial assets, there is a corresponding decrease in net financial assets of all other economic agents in the economy (Lindner 2015).6 Put in more general terms: An economic agent can only save financially if other agents dis-save financially by the same amount... That is why in the entire economy (that is the world economy or a closed economy) only the increase in tangible assets, thus investment, is saving...." In another paper, Lindner asserts: "Investment is the production of any non-financial asset in an economy and thus is always directly and unambiguously savings: it increases the economy's net worth... The economy as a whole cannot change its net financial wealth since it always equals zero. The aggregate economy can only save in the form of non-financial assets...The only way an economy can save is by increasing its non-financial wealth, i.e., its physical capital stock" (Lindner 2012).7 On the whole, deposits are a monetary concept; they represent money savings. Deposits are created by banks "out of thin air," as illustrated in Appendix 1 on page 14. Meanwhile, "savings" are a net addition to capital stock. Not surprisingly, there is no relationship between "real savings" and money savings, as illustrated in Chart I-1. In a nutshell, "savings" is an addition to the capital stock of a nation, which is the same as investment. Hence, the Savings = Investment identity for a closed economy is nothing other than a tautology as it de-facto means Investment = Investment. That is why in this report we use "savings" in quotations whenever we refer to it in the traditional sense of economic theory. 4. Households' (or businesses') propensity to save alters the velocity of money, not the amount of deposits/money in the banking system. A decision by a household to spend more rather than save does not change the amount of deposits in the banking system and does not affect the banking system's ability to provide more financing. When households or companies decide to spend their deposits, the velocity of money rises. Conversely, when households and companies decide to save (retain) their deposits, the velocity of money drops. The amount of deposits in the banking system stays constant. In turn, the amount of deposits and hence broad money supply in any banking system equals the cumulative net money creation by banks and the central bank over the course of their history. This has nothing to do with household and national "savings," which form the country's capital stock. 5. In a country with its own national currency, the true macro constraint on commercial banks' ability to expand financing infinitely are inflation and currency depreciation - not "savings." This is of course apart from demand for loans, regulations and shareholder preferences that can limit commercial banks' capacity to expand their balance sheets. Bottom Line: In an economy with banks, one does not need to save in the form of a deposit in a bank for the latter to lend money to another entity. Tales Of Brazil And China Chart I-2Two Extremes Of Investment ##br##And Savings: China And Brazil Two Extremes Of Investment And Savings: China And Brazil Two Extremes Of Investment And Savings: China And Brazil We use China and Brazil solely for illustrative purposes. One can use any country with a low savings rate instead of Brazil or a high savings rate economy such as Korea, Taiwan or Singapore in place of China. China has enjoyed a very high national savings rate and has been investing substantially (Chart I-2). In contrast, both the national savings rate and the investment-to-GDP ratio in Brazil have been depressed. It is very tempting to argue that Brazil has been experiencing very low investment because it saves so little. The narrative goes like this: Brazil's national savings rate is low because households save so little and the public sector dis-saves a lot - i.e., the government runs enormous fiscal deficits. This constrains the pool of available "savings" to finance private capital expenditures. This typical analysis concludes that Brazil needs to boost its "savings" - i.e., reduce its spending. This will allegedly enlarge the pool of available "savings" for investment and allow the country to invest, and consequently boost productivity and its potential growth rate. This narrative is misplaced in our view, because as we have shown in the past and in this report, banks do not need households, businesses or the government to save in order to provide financing. Banks can provide financing by simply expanding the money multiplier, among other things (see a more detailed discussion about the money multiplier below). So what is the true difference between Brazil and China? How has the latter achieved such high savings and investment rates, while the former has failed to finance its capital spending? Why have Brazilian banks not expanded their balance sheets more rapidly to finance investment (Chart I-3)? Chart I-3Snapshot Of Bank Assets-To-GDP Ratios Snapshot Of Bank Assets-To-GDP Ratios Snapshot Of Bank Assets-To-GDP Ratios Let's consider a hypothetical example. For simplicity and illustrative purposes, we assume there are two economies of equal size and have the same level of investment: savings and net exports. In short, they have identical starting points. We refer to these economies as Brazil and China. Now, commercial banks in both countries provide new financing of $50 - or equal to 5% of their respective GDP - to businesses for infrastructure building. This is new purchasing power created by commercial banks "out of thin air" in both economies. We assume that the only difference between these two countries is that in China, 100% of inputs for infrastructure (materials, machinery/equipment and so on) are produced/purchased domestically. In contrast, in Brazil, 100% of the inputs for infrastructure construction are imported, because this economy lacks production capacity. Table I-1 illustrates this hypothetical numerical example. As this infrastructure project is implemented, Brazil's imports will surge, and its net exports will deteriorate. Chart I-4 shows that this indeed is the case in Brazil - when capital spending expands, its current accounts deficit widens, entailing that Brazil imports a considerable portion of inputs for its investments. Table I-1A Hypothetical Example Of Investment - Saving Dynamics Is Investment Constrained By Savings? Tales Of China And Brazil Is Investment Constrained By Savings? Tales Of China And Brazil Chart I-4Foreign Content Of Brazil's ##br##Capital Spending Is High Foreign Content Of Brazil's Capital Spending Is High Foreign Content Of Brazil's Capital Spending Is High If there is no matching rise in foreign investor demand for Brazilian assets, the nation's currency will depreciate. Consequently, to support the plunging currency, Brazilian interest rates would have to rise. As a result, higher borrowing costs short-circuit the credit cycle. In China, because inputs for infrastructure are sourced and procured locally, there is no impact on its exchange rate or interest rates. If there is excess capacity in China to produce these inputs for infrastructure building, this new purchasing power will not lift inflation. A caveat is in order: Similar dynamics in trade balance deterioration, currency depreciation and inflation will prevail if there is a rise in consumer spending instead of capital expenditures. Importantly, the outcome will be the same in both economies if investment spending is done using existing money savings (deposits), not new credit. This example illustrates that a similar amount of capital expenditures financing via money creation "out of thin air" in both economies has increased national savings in China from $250 to $300, yet Brazilian savings stayed at $250 (Table I-1). In terms of savings rate, China will record a rise in its national savings rate from 25% to 28.6% of GDP (Table I-1). In Brazil, however, the national savings rate will remain at 25% of GDP, even though its banks, like Chinese ones, originated money "out of thin air" to finance infrastructure spending. The starting-point difference between China and Brazil is neither their banking systems' ability to expand their balance sheets nor the existing amount of deposits and assets. Rather, it is their real economies' capacity to produce goods and services. Therefore, we conclude: Regardless of how capital expenditures are financed - via new borrowing from banks or non-banks or using the investing company's own financial resources - when inputs for capital spending are procured domestically it is recorded as an increase in national "savings" level, but when they are imported there is no change in the level of national "savings." Over the decades, China, Korea, Taiwan, Singapore and Japan have all aggressively expanded their capacity to produce goods and services. They funded this capacity build-up via both money creation "out of thin air" and by attracting foreign capital. In the meantime, their large exports shielded their currencies from abrupt depreciation - as and when local bank financing was used to acquire foreign inputs. In the past decade, in China, loans - which banks have originated to build infrastructure - were largely spent on domestic inputs: cement, steel, chemicals, machinery and equipment all produced in the mainland. Even though some of that money/loans was used to purchase foreign inputs (commodities and equipment), China had large U.S. dollar revenues from exports that acted as an offset in its balance of payments. In short, Brazil and other low "savings" rate nations do not need to raise interest rates to curtail consumption and boost savings in order to release funds for financing capital expenditures. Chart I-5 demonstrates that there has been no positive relationship between real interest rates and the national savings rate in Brazil. Remarkably, real interest rates in this nation were often very high but that still did not lead to high "savings." Chart I-5Real Interest Rates And Savings Are Not Positively Correlated As They Are Supposed To Be Real Interest Rates And Savings Are Not Correlated Real Interest Rates And Savings Are Not Correlated What Brazil and other low "savings" rate economies need is to build efficient and competitive productive capacity - i.e., they need changes in the supply side of their economies. Only then can their banks expand their balance sheets and provide financing similar to how banks in high "savings" countries do. However, to shield the exchange rate from depreciation, these nations need to boost their exports first. This can be done by depreciating the currency and developing their global competitiveness. This is in effect what China has done in the past 25-30 years. Bottom Line: The key difference between Brazil and China is not their propensity to consume versus save, but their ability to produce goods and services domestically. So long as a nation builds and maintains excess productive capacity, its banks can originate loans "out of thin air" and finance capital and consumer expenditures. Money Multiplier Versus "Savings" Redundancy of the mainstream economic view that a pool of "savings" represents a constraint on financing investments becomes apparent when one applies the money multiplier concept, which is in fact accepted by mainstream economic theory. The money multiplier is the ratio of broad money relative to excess reserves. A rise in the money multiplier will lead to more money creation and financing in an economy per one unit of excess reserves (liquidity provided by the central bank), everything else held constant. In brief, money supply/the amount of deposits in the banking system will change regardless of the level of national or household "savings." Let's assume two countries with the same level of income per capita and GDP have identical national savings and investment rates as well as money supply and excess reserves. In short, they have indistinguishable macro parameters. Now suppose their banking systems in the past year had different money multipliers. The monetary authorities in both countries maintain the banking system's excess reserves at 10 units. If the money multiplier were to remain constant, say at 15, the money supply/deposits in both banking systems would remain at 150 units (10x15). Let's assume the money multiplier increased to 20 in Country A while held constant at 15 in Country B. In such a case, broad money supply would have risen to 200 units (10x20) in Country A and would stay at 150 (10x15) units in Country B. This entails that banks in Country A increased their funding yet those in Country B did not. That is despite the fact that the savings rates (and amount of savings) were identical before the change in the money multipliers occurred. This is one way to prove that a nation does not need to cut consumption for its banks to provide financing. The reason why the money multipliers could vary in these two countries with otherwise similar macro-economic parameters is due to animal spirits: In Country A, banks may have felt increasingly confident to lend more per one unit of their excess reserves, and there was demand for credit from borrowers. In the meantime, the money multiplier remained the same in Country B. In China, the money multiplier - the ratio of broad money to excess reserves - has risen dramatically since 2013 (Chart I-6). Interestingly, the amount of excess reserves at the People's Bank of China has been broadly the same over the past five years, yet broad money has grown by an enormous 75% (Chart I-6, middle and bottom panel). The exponential money/credit creation in China since 2009 has to a large extent been due to the rising money multiplier - wild animal spirits among bankers and borrowers - rather than high national "savings." Bottom Line: In any country, banks can provide more financing simply by expanding the money multiplier. This can happen regardless of the country's savings rate. Investment Relevance Why is this analysis pertinent to investors? First, this issue is critical to assess whether China's excessive credit expansion is an outcome of the nation's high savings - like many economists and investors claim - or due to the enormous amount of money/deposits and credit originated by the mainland's banks "out of thin air." If it is the former, investors have no need to worry about China's money and credit dynamics. If it is the latter, we are facing a typical banking and money/credit bubble. This report corroborates that it is the latter. Chart I-7 shows that China's broad money has grown 4-fold since January 2009 and has reached RMB 200 trillion, or the equivalent of $30 trillion. Chart I-6China: Money Multiplier Has Risen A Lot China: Money Multiplier Has Risen A Lot China: Money Multiplier Has Risen A Lot Chart I-7A Money Bubble In China? A Money Bubble In China? A Money Bubble In China? Does this enormous quantity of RMBs pose an inflation and/or currency depreciation risk? Or will the ongoing policy tightening cause another deflationary slump in China? It is clear that Chinese policymakers are currently being forced to walk a very thin line: On the one hand, the immense amount of money created "out of thin air" could stoke inflation or currency depreciation. It may not take much of a rise in the velocity of money for inflation to become a problem. On the other, tightening policy amid high leverage in an economy that is addicted to money and credit could push it into a growth slump and deflation. There is always a chance that policymakers will get it right and manage it perfectly so that neither inflation/currency depreciation nor a growth slump transpire. We would assign a 25-30% probability to this benign outcome. Hence, in our opinion there are 70-75% odds of either inflation or deflation in China in the next 12-24 months. Given these odds, we have been and remain reluctant to chase the rally in EM and China-related plays. In particular, the Chinese authorities have been tightening liquidity and banking/shadow banking regulation as well as projecting the ongoing anti-corruption campaign into the financial industry. This poses a meaningful risk given the existing macro imbalances. Second, this analysis re-shapes how investors should think about economic development and understand how nations with low savings can grow without relying on foreign funding. This provides us with a framework to assess the developmental path and the sustainability of growth in various developing economies. These include but are not limited to nations with low national savings rates such as Brazil, South Africa, Turkey, Russia, Colombia and many others. Finally, this analysis leads us to argue that Brazil does not need to maintain high real interest rates as a way to force consumers to cut spending and boost savings. In fact, this is the wrong prescription for Brazil. The most optimal macro adjustment path for Brazil is to reduce interest rates much further and encourage banks to finance private investment. Brazil needs to build an efficient supply side, and banks can provide funding by originating loans "out of thin air." Brazilian consumers do not need to save more for companies to get financing for their projects and invest. The natural causality of this adjustment will be considerable currency deprecation. However, Brazil is currently suffering from low inflation and high real interest rates (Chart I-8). Hence, reflationary policies are the right policy prescription. Chart I-8Brazil Needs To Reduce ##br##Interest Rates Much Further Brazil Needs To Reduce Interest Rates Much Further Brazil Needs To Reduce Interest Rates Much Further Foreign investors are therefore at risk due to potential currency depreciation. The new leaders to be elected in the October presidential elections may well adopt such a macro policy mix. Markets will front run this by pushing the real down and this will be negative for foreign investors. However, there will be a buying opportunity after the currency finds a floor. Arthur Budaghyan, Senior Vice President Emerging Markets Strategy arthurb@bcaresearch.com Andrija Vesic, Research Analyst andrijav@bcaresearch.com Appendix 1: Loan Origination, Deposits/Money Creation And Settlement The amount of deposits is not a constraint on a banking system's ability to make loans and buy assets from non-banks. Figure I-1 and I-2 present stylized cases of how commercial banks can originate new loans without requiring a new deposit or extra excess reserves entering the banking system. Specifically Figure I-1 illustrates how commercial banks can originate loans with the subsequent net settlements among themselves taking place via inter-bank borrowing/lending. In this stylized example, the banking system is comprised of three commercial banks. These commercial banks hold all deposits in the system. Cash does not exist and all payments are done via wire transfers. Figure I-1Money Creation By Banks With Net Settlement Among Banks Via Inter-Bank Lending/Borrowing Is Investment Constrained By Savings? Tales Of China And Brazil Is Investment Constrained By Savings? Tales Of China And Brazil Figure I-2Money Creation By Banks With Net Settlement Between Banks & Central Bank Is Investment Constrained By Savings? Tales Of China And Brazil Is Investment Constrained By Savings? Tales Of China And Brazil 1. Loan Origination/Money Creation In the morning, Bank 1 originates a new loan worth $100 for Client 1. This transaction creates a new asset and, for the balance sheet to balance, Bank 1 should also increase the liabilities side of its balance sheet. Therefore, it simultaneously credits Client 1's chequing account by $100. Bank 1 does not transfer other depositors' money to Client 1's chequing account; it creates a new $100 deposit. The rest of the bank's depositors still have their full deposits, which they can draw on. In a nutshell, both assets and liabilities of Bank 1 rose by $100 - this was done "out of thin air" by just pressing the enter button on the computer. That also means that a $100 of new money was created by Bank 1 which increases the overall money stock in the banking system. Meanwhile, Bank 2 lends $200 to Client 2 and Bank 3 lends $300 to Client 3. Let's assume these were the only lending transactions during that day. In aggregate, the three banks originated $600 of new loans, and consequent new deposits/money "out of thin air." 2. Money Transfer / Payments Debtors do not borrow money and leave it sitting idle. They borrow money to pay their suppliers and others they owe. Even though Clients 1, 2 and 3 wire their payments to their respective suppliers on the same day, the total amount of deposits in the banking system does not change: Deposits simply move from one bank to another or from one bank client to another. In Figure I-1, Client 1 wires its $100 from Bank 1 to Supplier B that has an account at Bank 2; Client 2 pays its $200 invoice to Supplier C which in turn has an account at Bank 3; and finally Client 3 transfers $300 to Supplier A, who holds an account at Bank 1. The amount of money/deposits in the overall banking system has not changed as a result of these wire transfers. 3. Multilateral Net Settlement At the end of the day, banks should settle with other banks. Many countries employ a multilateral net settlement system typically operated by the central bank. In a multilateral net settlement system, at the end of the day, each bank pays (receives from) the system only the net amount they are due to pay to (receive from) other banks combined. Importantly, banks settle their payments with other banks using their excess reserves (herein called reserves) at the central bank, not the deposits of their clients. This entails that banks do not need deposits to pay their dues to other banks or the central bank. Figure I-1 illustrates the impacts on the banks' reserves under the multilateral net settlement system: Bank 1's reserves at the central bank change as follows: -$100 (Client 1's wire transfer out) + $300 (this is the amount that Supplier A with an account in Bank 1 gets from Client 3) = $200. The impact on Bank 2's reserves is as follows: -$200 (Client 2's wire transfer out) + $100 (this is the amount that Supplier B with an account in Bank 2 gets from Client 1) = -$100. The net change in Bank 3's reserves is: -$300 (Client 3's wire transfer out) + $200 (this is the amount that Supplier C with an account in Bank 3 gets from Client 2) = -$100. If we assume that all banks had no excess reserves before this day, then how do they settle their accounts? There are various alternatives, but we highlight two: Figure I-1 demonstrates the case of interbank lending. As a result of the settlements, Bank 1 has $200 in extra reserves, while Bank 2 and Bank 3 each have a $100 deficit in reserves. As such, Bank 1 lends $100 to each of Bank 2 and Bank 3. Why does it lend to other banks rather than keeping these reserves at the central bank? Because interbank rates are typically slightly above the central bank's rate - the rate Bank 1 would get if it were to lend the $200 to the central bank. Figure I-2 portends the same transactions with the sole difference being the reserves flow. Unlike Figure I-1, here banks do not lend to/borrow from each other. Banks lend excess reserves to the central bank as well as borrow deficient reserves from the central bank. This is done to settle their payments with other banks. Bank 1 lends its free reserves of $200 to the central bank. Bank 2 and Bank 3 each borrow $100 reserves from the central bank to settle with the system at the end of the day. As a result, the aggregate amount of reserves at the central bank does not change. On the whole, banks created $600 of new deposits/money/loans during the day without requiring savings from households, companies, the government or foreigners. Thereby, the money supply was expanded and new financing in the amount of $600 was provided "out of thin air." Appendix 2: Deposits Versus Liquidity Below are additional questions that we seek to answer to provide further elaboration on the issues of banks creating money and the difference between deposits and liquidity: 1. Why would central banks provide reserves to banks? When a central bank targets interest rates, which is nowadays the most common policy framework in both advanced and developing countries, it must provide liquidity to banks: the latter is required to preclude interbank rates from deviating from the policy rate. Under an interest rate targeting regime, the central bank does not have complete control over banks' reserves nor broad money supply. A central bank can control either the quantity of money or the price of money (interest rates), but not both simultaneously. The following two quotes from the New York Federal Reserve Chairman William Dudley and the European Central Bank confirm that central banks nowadays provide banks with reserves on demand - i.e., the amount of reserves is determined by demand from banks. "The Federal Reserve has committed itself to supply sufficient reserves to keep the fed funds rate at its target. If banks want to expand credit and that drives up the demand for reserves, the Fed automatically meets that demand in its conduct of monetary policy. In terms of the ability to expand credit rapidly, it makes no difference whether the banks have lots of excess reserves or not." (Dudley, 2009) European Central Bank (2012), May 2012 Monthly Bulletin: "The Eurosystem ... always provides the banking system with the liquidity required to meet the aggregate reserve requirement. In fact, the ECB's reserve requirements are backward-looking, i.e. they depend on the stock of deposits (and other liabilities of credit institutions) subject to reserve requirements as it stood in the previous period, and thus after banks have extended the credit demanded by their customers." 2. Why do banks compete for deposits if they create deposits themselves? The true reason banks compete for deposits is not that they require more deposits, but because they require more reserves. When a bank attracts a deposit from another bank, the latter must transmit to the former reserves equal to the amount of the deposit transferred. When a bank is experiencing a liquidity shortage, more deposits are of no help. Banks can always create more deposits themselves, but they cannot create reserves at the central bank. The true liquidity for banks is their reserves at the central bank - not deposits. Reserves are solely created by central banks "out of thin air." A central bank may decide not to provide funding to certain banks in some cases when the authorities deem these banks insolvent and/or in breach of regulations. Otherwise, if the central bank wants to keep policy rates stable, it must provide all liquidity (reserves) banks require. 3. Why do banks attract deposits if the central bank provides liquidity on demand? The primary reason why banks seek to attract deposits instead of borrowing from the central bank is due to the cost of funding and duration of liabilities as well as regulatory requirements. Deposits may be cheaper and have longer duration than short-term funding from the central bank. 1 Lindner, F. (2015), "Does Savings Increase the Supply of Credit? A Critique of Loanable Funds Theory", Macroeconomic Policy Institute, World Economic Review 4, 2015. 2 Lindner, F. (2015), "Did Scarce Global Savings Finance the US Real Estate Bubble? The Global Saving Glut thesis from a stock flow Consistent Perspective", Macroeconomic Policy Institute, Working Paper 155, July 2015. 3 Lindner, F. (2015), "Does Savings Increase the Supply of Credit? A Critique of Loanable Funds Theory", Macroeconomic Policy Institute, World Economic Review 4, 2015. 4 Please refer to the Emerging Markets Strategy Special Reports from October 26, 2016, November 23, 2016, January 18, 2017 and December 20, 2017; available on ems.bcaresearch.com 5 Borio, C. and Disyatat, P. (2015), "Capital flows and the current account: Taking financing (more) seriously", BIS Working Papers, No. 525, October 2015. 6 Lindner, F. (2015), "Did Scarce Global Savings Finance the US Real Estate Bubble? The Global Saving Glut thesis from a stock flow Consistent Perspective", Macroeconomic Policy Institute, Working Paper 155, July 2015. 7 Lindner, F. (2012), "Savings does not finance Investment: Accounting as an indispensable guide to economic theory", Macroeconomic Policy Institute, Working Paper 100, October 2012. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Highlights There are many things that central bankers know they don't know. "Known unknowns" include the outlook for growth (both actual and potential), NAIRU, the neutral rate of interest, and the true shape of the Phillips curve. "Unknown unknowns" are, by definition, unknowable, but are often at the heart of economic downturns. Central bankers, like military leaders, tend to fight the last war. They have tirelessly waged a battle against deflation over the past decade, so it is logical to conclude that they will err on the side of keeping monetary policy too loose rather than too tight. This will prolong the recovery, but it also means that economic and financial imbalances will be greater by the time the next downturn rolls around, most likely in 2020. Keep a close eye on credit spreads. Stay overweight risk assets for now, but look to move to neutral later this year and outright underweight in the first half of 2019. Bond yields will fall as the next recession approaches, but they will do so from higher levels than today. Feature Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns - the ones we don't know we don't know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones. - Donald Rumsfeld, former Secretary of Defense under George W. Bush Uncertainty Galore Central bankers know many things. They know that growth is currently strong across most of the world, unemployment is falling and inflation, while still low, has been slowly trending higher. Unfortunately, there are also many things they don't know. These include things they know they don't know, as well as things that are not even on their radar screens - the "unknown unknowns" that Donald Rumsfeld famously warned about. Known Unknowns Let's start with five "known unknowns." 1. Will Growth Stay Strong? Global growth has likely peaked, but should remain comfortably above-trend over the remainder of this year (Chart 1). The OECD's Global Leading Economic Indicator (LEI) has leveled off, while the diffusion index, which tabulates the share of countries with rising LEIs, has dropped below 50 percent. A fall in the diffusion index has often foreshadowed outright declines in the composite LEI. Consistent with this prognosis, the Citi global Economic Surprise Index has swooned, the Chinese Keqiang index has decelerated, and Korean export growth - a leading indicator for global trade - has slowed. Global manufacturing PMIs have also edged off their highs (Chart 2). The one exception is the U.S., where the ISM index continues to power higher. Despite the occasional blip such as this week's retail sales report - which was probably depressed by tax refund delays - recent U.S. economic data have been reasonably upbeat. Goldman Sachs' Current Activity Indicator remains near cycle highs, implying strong momentum going into the second quarter. Chart 1Global Growth Has Peaked ##br##But Will Remain Above Trend Global Growth Has Peaked But Will Remain Above Trend Global Growth Has Peaked But Will Remain Above Trend Chart 2Global Manufacturing PMIs ##br##Are Off Their Highs Global Manufacturing PMIs Are Off Their Highs Global Manufacturing PMIs Are Off Their Highs Changes in financial conditions tend to lead growth by about six-to-nine months. U.S. financial conditions have eased a lot more since the start of 2017 than elsewhere (Chart 3). In addition, U.S. fiscal policy is likely to be much more expansionary over the next two years than in the rest of the world (Chart 4). All this suggests that the composition of global growth will shift in favor of the U.S. over the coming months. Chart 3Composition Of Global ##br##Growth Will Shift To The U.S. ... Composition Of Global Growth Will Shift To The U.S. ... Composition Of Global Growth Will Shift To The U.S. ... Chart 4U.S. Fiscal Policy Will Become More ##br##Expansionary Than In R.O.W. What Central Bankers Don't Know: A Rumsfeldian Taxonomy What Central Bankers Don't Know: A Rumsfeldian Taxonomy 2. Will Potential Growth Accelerate? The U.S. unemployment rate has declined from a high of 10% in 2009 to 4.1% in February 2018, even though real GDP growth has averaged a meager 2.2% over this period. Extremely weak productivity growth explains why the output gap has managed to contract in the face of subdued GDP growth. Sluggish capital spending has exacerbated the productivity downturn, but probably did not cause it. Chart 5 shows that productivity growth began to decelerate well before the financial crisis erupted. The slowdown has been pervasive across countries and sectors. Economists have a poor track record of predicting productivity trends. Not only did they fail to predict the productivity revival in the late 1990s, but because of data lags and subsequent revisions, they did not even know it had happened until the early 2000s. It is too early to say whether robotics and AI will yield the same sort of productivity windfall that the Internet did. My colleagues, Mark McClellan and Brian Piccioni, have cast a skeptical eye on some of the alleged revolutionary breakthroughs in both fields.1 If it turns out that the late 1990s was the exception rather than the rule, and that we are going back to the lackluster productivity performance of the 1970s, this will make life more challenging for central bankers. 3. What Is The True Level Of NAIRU? Spare capacity has diminished in most countries, but questions linger over how much slack remains. No one truly knows where NAIRU - the so-called Non-Accelerating Inflation Rate of Unemployment - really stands. The Fed and the Congressional Budget Office believe that NAIRU has fallen from over 6% in the late 1970s to around 4.5%-to-4.7% today (Chart 6). Chart 5Productivity Growth Slowdown ##br##Has Been Pervasive Productivity Growth Slowdown Has Been Pervasive Productivity Growth Slowdown Has Been Pervasive Chart 6NAIRU Is Low By Historic Standards NAIRU Is Low By Historic Standards NAIRU Is Low By Historic Standards An aging workforce has reduced frictional unemployment because older workers are less likely to switch jobs than younger ones. The internet has also made it easier for employers to find suitably qualified workers. On the flipside, globalization, automation, and the opioid crisis have likely made it difficult for a growing list of workers to hold down a job for long. Our best guess is that the U.S. economy is operating at close to full employment. This is confirmed by various employer surveys, which show that companies are struggling to find qualified workers (Chart 7). The fact that the share of people outside the labor force who want a job has fallen to pre-recession levels also suggests that labor slack is running thin (Chart 8). Chart 7U.S. Economy: Operating At ##br##Close To Full Employment U.S. Economy: Operating At Close To Full Employment U.S. Economy: Operating At Close To Full Employment Chart 8Few People Left Who Are Eager ##br##To Rejoin The Labor Force Few People Left Who Are Eager To Rejoin The Labor Force Few People Left Who Are Eager To Rejoin The Labor Force There is more slack outside the United States. Labor underutilization is still 2.5 percentage points higher in the euro area than it was in 2008. Taking Germany out of the picture, labor underutilization is nearly six points higher (Chart 9). A number of major emerging markets, most notably Brazil and Russia, also have a lot of excess cyclical unemployment. The Japanese labor market has tightened significantly in recent years, but there is probably a fair amount of hidden underemployment left, particularly in the service sector (factoid of the week: there are more police officers in Tokyo than in New York City).2 4. Where Is The Neutral Rate Of Interest? One of the most vexing questions facing central banks is how high interest rates can go before they move into restrictive territory. There are a variety of reasons for thinking that the neutral real rate of interest - the rate consistent with full employment and stable inflation - is lower today than it was in the past. Trend real GDP growth has fallen. This has reduced the need for firms to expand capacity. The shift to a capital-lite economy - where value-added increasingly takes the form of bits and bytes rather than factory output - has further reduced the need for fresh investment. Meanwhile, a reluctance to take on new debt has restrained spending. Rising inequality has shifted more wealth into the hands of people who tend to save a lot. Globally, savings must equal investment. If desired savings go up and desired investment goes down, interest rates must fall to push down the former and push up the latter (Chart 10). Chart 9Euro Area: There Is Still Labor ##br##Market Slack Outside Of Germany Euro Area: There Is Still Labor Market Slack Outside Of Germany Euro Area: There Is Still Labor Market Slack Outside Of Germany Chart 10Interest Rates Must Fall If Desired Savings ##br##Increase And Desired Investment Declines What Central Bankers Don't Know: A Rumsfeldian Taxonomy What Central Bankers Don't Know: A Rumsfeldian Taxonomy None of these forces are immutable, however. Investment demand appears to be picking up, as judged by capex intention surveys (Chart 11). Consumer credit is rising anew. The U.S. personal saving rate is back near an all-time low (Chart 12). A tighter labor market is likely to cause labor's share of income to rise, just like it did in the late 1990s (Chart 13). This should boost aggregate demand. An unprecedented increase in the U.S. budget deficit should help absorb much of the savings from cash-rich corporations (Chart 14). Meanwhile, savings are likely to decline over the long haul as well-paid baby boomers retire en masse. All this is causing the neutral rate to move higher. Chart 11Upswing In Global Capex Is Underway Upswing In Global Capex Is Underway Upswing In Global Capex Is Underway Chart 12U.S. Consumer Credit Revival U.S. Consumer Credit Revival U.S. Consumer Credit Revival Chart 13Tight Labor Market And Rising Labor ##br##Share Of Income: A Replay Of The 1990s? Tight Labor Market And Rising Labor Share Of Income: A Replay Of The 1990s? Tight Labor Market And Rising Labor Share Of Income: A Replay Of The 1990s? Chart 14Now Is The Time For Fiscal Consolidation, Not Profligacy Now Is The Time For Fiscal Consolidation, Not Profligacy Now Is The Time For Fiscal Consolidation, Not Profligacy 5. What Is The Shape Of The Phillips Curve? Central bankers assume that dwindling spare capacity will lead to higher inflation, a relationship immortalized by the so-called Phillips curve. The fact that inflation has barely risen over the past few years is an obvious challenge to this theory. It may simply be that the Phillips curve is "kinked" at very low levels - it only steepens when the economy has gone beyond full employment. The fact that it has taken this long to reach the kink could explain why inflation has not taken off sooner. The success that central banks have enjoyed in anchoring long-term inflation expectations is another reason why the Phillips curve has become flatter. Chart 15An Overheated Economy Led To ##br##Rising Inflation In The 1960s An Overheated Economy Led To Rising Inflation In The 1960s An Overheated Economy Led To Rising Inflation In The 1960s The problem is that there is no God-given reason why inflation expectations should stay well anchored. Core inflation was remarkably low and stable in the first half of the 1960s. However, the combination of low real interest rates and increased fiscal spending associated with Lyndon Johnson's Great Society programs and the Vietnam War led to a surge in inflation starting in 1966 (Chart 15). Inflation kept climbing thereafter, rising to 6% in 1970. This was three years before the first oil shock occurred, suggesting that an overheated economy, rather than OPEC, was the main inflationary culprit. Unknown Unknowns Then there are the things central bankers are not even thinking about, or even worse, the things they think are true but aren't.3 In the lead-up to the Great Recession, U.S. policymakers blithely assumed that house prices could not fall at the nationwide level. This caused them to turn a blind eye to soaring home prices and the deterioration of underwriting standards in the mortgage market. Warren Buffet once said, "Only when the tide goes out do you discover who's been swimming naked." Our guess is that rising rates will expose a lot of things one would rather not see in the corporate debt market. In the latest issue of the Bank Credit Analyst, my colleague Mark McClellan estimated that the interest coverage ratio for U.S. companies would drop from 4 to 2.5 if rates increased by 100 basis points across the corporate curve. Such a move would take the coverage ratio to the lowest level in the 30-year history of our sample (Chart 16A and Chart 16B).4 Consumer staples, tech, and health care would be the most adversely affected. Chart 16AU.S. Interest Coverage Ratio ##br##Breakdown By Sector (I) U.S. Interest Coverage Ratio Breakdown By Sector (I) U.S. Interest Coverage Ratio Breakdown By Sector (I) Chart 16BU.S. Interest Coverage Ratio ##br##Breakdown By Sector (II) U.S. Interest Coverage Ratio Breakdown By Sector (II) U.S. Interest Coverage Ratio Breakdown By Sector (II) Political shocks are also very difficult for policymakers to foresee. President Trump's decision to impose steel and aluminum tariffs spooked the markets. NAFTA negotiations remain stalled and the odds are high that the U.S. will pursue trade sanctions against China for alleged intellectual property theft. That said, as we noted last week, an all-out trade war would cause equities to crater.5 Trump remains focused on the value of the stock market as a gauge of the success of his presidency. This will curb his hawkishness. Unemployment is also very low these days, which limits the attractiveness of protectionist policies. The specter of trade wars will escalate if a recession causes stocks to tumble and unemployment to rise in key midwestern swing states. Other "unknown unknowns" include another flare-up in sovereign debt markets in Europe, a hard landing in China, and a supply-induced spike in oil prices. Investment Conclusions It may be tempting to think that central banks can calibrate monetary policy as events unfold in order to keep economies on an even keel. If only it were so easy. Monetary policy affects the economy with a lag of 12-to-24 months. By the time it is clear that either more or less monetary stimulus is needed, it is often too late to act. Central bankers have to work with incomplete or inaccurate data. One of the reasons that inflation spiraled out of control in the 1970s was because the Federal Reserve systematically overstated the size of the output gap (Chart 17). This led the Fed to falsely conclude that slower growth was the result of inadequate demand rather than a deceleration in the economy's supply-side potential. It is impossible to know what mistakes central banks will make in the future, but it is almost certain that something will go awry. Central bankers, like military leaders, tend to fight the last war. They have tirelessly waged a battle against deflation over the past decade, so it is logical to conclude that they will err on the side of keeping monetary policy too loose rather than too tight. This will prolong the recovery, but it also means that economic and financial imbalances will be greater by the time the next downturn rolls around. As we discussed several weeks ago, the next recession is most likely to arrive in 2020.6 Investors should stay overweight risk assets for now, but look to move to neutral later this year and outright underweight in the first half of 2019. Bond yields will fall as the next recession approaches, but they will do so from higher levels than today. Similar to the 1970s, investors should expect inflation and bond yields to make a series of "higher highs" and "higher lows" with every boom/bust episode (Chart 18). Chart 17The Fed Continuously Overstated The ##br##Magnitude Of Economic Slack In The 1970s The Fed Continuously Overstated The Magnitude Of Economic Slack In The 1970s The Fed Continuously Overstated The Magnitude Of Economic Slack In The 1970s Chart 18A Template For The Next Decade? A Template For The Next Decade? A Template For The Next Decade? Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 Please see Technology Sector Strategy Special Report, "The Coming Robotics Revolution," dated May 16, 2017; The Bank Credit Analyst, "Did Amazon Kill The Phillips Curve?" dated August 31, 2017; and The Bank Credit Analyst, "The Impact Of Robots On Inflation," dated January 25, 2018. 2 "As crime dries up, Japan's police hunt for things to do," The Economist, May 18, 2017. 3 Mark Twain is often credited for saying that "It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so." It's a great quote, but there's only one problem: There is no evidence that he ever said it. 4 Please see The Bank Credit Analyst, "Leverage And Sensitivity To Rising Rates: The U.S. Corporate Sector," dated February 22, 2018. 5 Please see Global Investment Strategy Weekly Report, "Trump's Tariffs: A Q&A," dated March 9, 2018. 6 Please see Global Investment Strategy Weekly Report, "The Next Recession: Later But Deeper," dated February 23, 2018. Tactical Global Asset Allocation Recommendations Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Dear Client, This Special Report is the full transcript and slides of a presentation I recently gave at the London School of Economics symposium: 'Will I Work For AI, Or Will AI Work For Me?' The presentation pulls together several years of research analyzing the impact of current technological advances on work, the economy and society. I hope you find the presentation insightful and provocative, especially the narrative surrounding Slide 12. Dhaval Joshi Slide 2 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Feature Good afternoon Thank you very much for the invitation to speak here at the London School of Economics. The specific question you asked me was: will we be able to work in the future? (Slide 1). To which my answer is yes, an emphatic yes. I'm very optimistic that we will be able to work in the future. And one reason I'm saying this is, imagine that we had this symposium 100 years ago. I suspect we might have had exactly the same fears that we have right now (Slide 2). Slide 1 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 2 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Specifically, at the start of the 20th century, about 35% of all jobs were on farms and another 6% were domestic servants. At the time, you could probably also have said, "Well, these jobs aren't going to exist." More or less half of the jobs that existed at that time were going to disappear - and disappear they did. So we'd have thought there would be mass unemployment. Of course, there wasn't mass unemployment, because just as jobs were destroyed, we had an equivalent job creation (Slide 3). For example, at the start of the 20th century, less than 5% of people worked in professional and technical jobs. But by the end of the century, these jobs employed a quarter of the workforce. I guess what I'm saying is that we're very conscious of job destruction because we can see existing jobs being destroyed. But we're not very conscious of job creation, because in real time, it's difficult to visualize or imagine where these new jobs will be. In essence, what we saw in the 20th century was one major segment of employment basically collapsed from very significant to insignificant. While another segment surged from insignificant to very significant (Slide 4). Slide 3 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 4 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? As you all know, there is an economic thesis that underlies this. It's called Say's Law, derived by French economist Jean-Baptiste Say in 1803. In simple terms, it says that new supply creates new demand. Think about it like this: why would you replace a human with a machine? You would only do that if it increases your productivity, right? Otherwise, it does not make sense to replace a human with any sort of machine, including AI. But because you have increased productivity, you then have extra income to spend on new goods and services. Now if those goods and services are being supplied by a machine, then you can redeploy humans to satiate new desires, desires that do not even exist at the time. In economic terms, the producer of X - as long as his products are demanded - is able to buy Y (Slide 5). The question is, what is Y? Y is the new product or service. Let me give you some examples (Slide 6). In the 19th century, we had the advent of railways. And then someone thought. "Hang on a minute. We have this way of moving things around much faster, and we've got all these people who live hundreds of miles from the coast who might want to eat fresh fish." So this was the birth of the frozen food industry. But you could not have the frozen food industry without railways. What I'm saying is that entrepreneurs will seize the new technology to satiate a desire. Or even create a new desire because maybe the people in the middle of the country never thought they could eat fresh sea fish. Until someone came along and said, "you can eat fresh fish now." Slide 5 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 6 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Another example is, as technology improved the health and longevity of your teeth someone thought. "Well, hang on a minute. Maybe there's a desire to make teeth look beautiful." And we created this whole new industry called the dental cosmetics industry. We know this because prior to the 1960s, there was no job called dental technician or dental hygienist. A third example is, let's say that we have more advanced healthcare and pharmaceuticals, so humans are living longer and healthier lives. Well, then you can sort of ask. "Hang on a minute. Don't you want your dog to live the same long and healthy life that you're living?" And this is behind the explosion of the pet care industry that we're seeing at the moment. So while one segment of the economy will employ less, a new segment will come along to replace it. In the 20th century we saw farm work disappearing but professional work rising. Today, we are seeing manufacturing and driving jobs disappearing but healthcare work rising (Slide 7). Which does raise a pretty obvious question (Slide 8). Is there anything really different this time around? Slide 7 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 8 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Well, the answer is yes, there is a subtle but crucial difference this time around. To see the difference, we have to look more closely at where jobs are being destroyed, and where they are being created. As you can see, the mega-sectors losing a lot of jobs are manufacturing, the auto industry, and finance (Slide 9). While on the other side of the ledger, we have job creation in health, social work and education. But now, let's look in a little more detail. Where, specifically, are the jobs being created? For this we have to look at the United States data which is much more granular than in Europe. Here are the top five subsectors of job creation this decade (Slide 10). At the top of the list is food services and drinking places, which is just a euphemistic way of describing bartenders, waitresses, and pizza delivery boys. We also have a lot of new administrative jobs and care workers. What is the common link in this job creation? Answer: these are predominantly low-income jobs. Slide 9 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 10 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? So it is true that we have an enormous amount of job creation in the last decade or so, and the policymakers keep boasting about it, they say, "Well look, the unemployment rate in the U.S. is at a record low, the unemployment rate in the UK is at a record low, the unemployment rate in Germany is at a record low. We're creating loads and loads of jobs." The trouble is that these are predominantly low-income jobs. Meanwhile the job destruction is in middle-income jobs in manufacturing and finance. This means what we're seeing in the labour market is called a 'negative composition effect' - a hollowing out of middle incomes. So while we're getting loads and loads of job creation, it is not translating into wage inflation at an aggregate level. I think one of the reasons is a concept called Moravec's paradox. Professor Hans Moravec is an expert in robotics and Artificial Intelligence, and he noticed this paradox (Slide 11). He said, "Look. For AI, the things that we think are difficult are actually easy." By easy, he means they're doable. Let me give you some specific examples. Say someone could speak five languages fluently and translate between them at ease. We would think that person is a genius, a real rare specimen, and the economy would value this person extremely highly, probably pay that person hundreds of thousands of pounds at a minimum. But actually, AI can translate across five languages quite easily, and even something like Google Translate, which we all use, does a reasonably good first stab at translating from one language to another. Slide 11 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Or consider something like insurance underwriting. Pricing an insurance premium from lots of data on a risk. AI can do that extremely well, much better than a human can. Or medical diagnosis. Figuring out what's wrong with a patient from very detailed medical data. Again, AI beats humans hands down on that. What I'm saying is, these skills that we thought were difficult transpired not to be that difficult for AI, because they just amount to narrow-frame pattern recognition and repetition of algorithms. Whereas, the second part of Moravec's paradox is that AI finds the easy things very hard. Things that we think are really innate, we don't even give them a second thought like walking up some stairs, cleaning a table, moving objects around, and cleaning around them. Actually, AI finds these things incredibly difficult, almost impossible. We have a false sense of what is difficult and what is easy. The main reason is that the things that we find innate took millions and millions of years of human brain evolution for us to find them innate. And as AI is in essence trying to replicate the human brain, only now are we recognizing that things that we find innate are actually incredibly complex. If it took millions and millions of years to evolve the sensorimotor skills that allow us to walk up some stairs, recognize subtle emotional signals, and respond appropriately, then obviously AI is going to find it very, very difficult to replicate those innate human skills. Conversely, the brain's ability to do calculus, construct a grammatical structure for a language, or play chess only evolved relatively recently. So AI can do them very easily. Which brings me to quite a profound thought. If there's one thing that I want you to remember from this presentation it is this (Slide 12). Might we have completely misvalued the human brain? Might we have grossly overvalued things that are actually quite easy? And might we have undervalued things which are actually very, very difficult? And what AI is now doing is correcting this huge error. In which case, the next decade could be extremely disruptive as AI corrects this economic misvaluation of our skills. Slide 12 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? This might also explain the mystery as to why there is no wage inflation when the Phillips curve says there should be. The Phillips curve makes a simple relationship between the unemployment rate and wage pressures. And the folks at the Federal Reserve and Bank of England, they're sort of getting really perplexed. They're saying, "Look, unemployment is so low. Where is this wage inflation? It's going to kick in any time now." In fact, there's a bit of a paradox going on. For the people who are continuously employed in the same job, there has been pretty good wage inflation - at sort of three, four percent (Slide 13). But when you take the negative composition effect into account, then suddenly there's this big gap because what's happening is that the well-paid jobs are disappearing to be replaced by lower-paid jobs. So even if you give the bartender making thirty thousand a big pay rise to thirty-five thousand. Even if you hire two of them, but you're losing a finance job paying over a hundred thousand, then at the aggregate level, you won't see much wage inflation. And this problem, I think, continues for the next few years, minimum. It means that you will not get the wage pressures that a lot of economists think you're going to get from the low unemployment rate. Because you have to look at the quality of the jobs as well as the quantity. I think there is another disturbing impact from a societal perspective. Look again at where the jobs are being lost and where they're being created, and look at the percentage of male employees (Slide 14). Job destruction is occurring in sectors that are male-dominated, whereas job creation is occurring in sectors that are female-dominated. Slide 13 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 14 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? AI is good at narrow-frame pattern recognition and repetition of algorithms and functions - jobs like driving, which are typically male-dominated. Whereas jobs that require emotional input, emotional understanding, and empathy in the 'caring sectors' are typically female-dominated. So if you're a male, you're in trouble. You're in a lot of trouble. Obviously, there'll be re-training, so all the guys who were driving trucks will have to retrain as nurses, or as essential carers. But if you're a female, things are looking okay. You can see that in the data (Slide 15). Female labour force participation is in a very clear uptrend. Male participation is flat to down. This varies by country by country, and in the U.S., it's catastrophic for males, especially young males. Young male participation in the U.S. is really falling off a cliff at the moment. I think the other thing to say from a societal perspective is that the so-called 'Superstar Economy' is booming - both superstar individuals and superstar firms. One way of seeing this is in this index called 'the cost of living extremely well' calculated every year by Forbes (Slide 16). Whereas the ordinary CPI includes the cost of bread and milk, the CPI index for the extremely rich includes the cost of Petrossian caviar and Dom Perignon champagne. And a Learjet 70, a Sikorsky S-76D helicopter. I think there's a pedigree racehorse in there too. Anyway, we're seeing the CPI for the extremely rich rising at a dramatically faster pace than the CPI for society as a whole. So it would seem that superstar individuals and superstar firms are really thriving. Slide 15 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 16 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Let's explain this dynamic in terms of a superstar we all recognise - Roger Federer. Roger Federer was unknown initially, but as he went up the tennis rankings and became a superstar, his income grew exponentially. The other aspect is, how long can he stay a superstar? Because all superstars are eventually displaced by a new superstar. So there's two aspects to the dynamics of superstar incomes (Slide 17). First, how exponential is your income growth? And second, how long do you stay a superstar? What I'm saying is that the rise of AI, by hollowing out the middle jobs, actually allows a few superstars to have this exponential rise in their income. Let's think about it in terms of the legal profession. The top lawyer will be in huge demand. Technology really boosts him. Not just AI, but things like the internet, the fact that social media will reinforce his position, whereby everyone will know who he is. Even if he can't service you directly, he will have a team with his brand on it. And he can stay there for longer before he is displaced. So this is the mechanism by which technology can increase income inequality by hollowing out the middle. In the legal profession, the assistant lawyer who just checks a document for simple legal principle, well the machine can do that. But the guy who knows all the oddities, who knows all the loopholes that can win you the case, the machine won't be able to do that. Essentially what I'm saying is that the technological revolution - it's not just AI, it's technology in aggregate, including the internet and social media, and so on - it increases the rate of income growth for a few superstar individuals and firms. And it increases their longevity (Slide 18). And these are the two drivers for the Pareto distribution of incomes. You can actually go through the mathematics of this to show that it does increase the polarization of incomes. Slide 17 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Slide 18 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Let's sum up (Slide 19). First of all, yes, we will be able to work in the future. I don't think there's any doubt about that because there will be new jobs created, the nature of which we can only guess because we're going to get new industries to satiate our new desires. However, in the coming years, middle-income work will suffer high disruption because of Moravec's Paradox. Some things that we thought were difficult are actually quite easy for AI. But things like gardening, plumbing, nursing, and childcare are very difficult for machines to replicate. Which means that low-income work will suffer much less disruption and, of course, low-income work will get paid better over time - though the gap is so large at the moment that it's preventing overall wage inflation from kicking in. And that, I think, will persist for the next few years at a minimum. Slide 19 The Impact Of AI: Will We Be Able To Work In The Future? The Impact Of AI: Will We Be Able To Work In The Future? Men are going to suffer much more disruption than women because of the nature of the job destruction versus the job creation. And the final point is that superstars will thrive. All of this has a lot of implications for how we respond as a society, and maybe we will need some support mechanisms in this period of disruption. I think the most intense disruption will be in the next decade. After that we will reach a new equilibrium once we have actually corrected this misvaluation of the brain, this misvaluation of what it is that makes us truly human. Thank you very much. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com

Dear Client, In addition to this Special Report written by my colleagues Mark McClellan and Brian Piccioni, we are sending you an abbreviated weekly report. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Feature Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart 1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart 1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart 2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart 3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart 2Global Robot Usage Global Robot Usage Global Robot Usage Chart 3Global Robot Usage By Industry (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart 4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart 5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart 4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart 5Stock Of Robots By Country (II) (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart 6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 Chart 6U.S. Investment In Robots U.S. Investment In Robots U.S. Investment In Robots The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart 7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart 7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix 1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart 8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart 8U.S.: Productivity Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart 9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart 10). Chart 9GPT Contribution To Productivity The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 10U.S.: Unit Labor Costs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart 11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart 11Inflation Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box 1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart 12). Box 1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart 12U.S. Job Rotation Has Slowed The Impact Of Robots On Inflation The Impact Of Robots On Inflation The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart 13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix 2 for more details. Chart 13Global Manufacturing Jobs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix 1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart 14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart 14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix 2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart 4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart 15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart 16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart 15Japan: Earnings Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017) "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against the Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com. 10 OECD Productivity Working Papers, No. 05 (2016) "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 8.