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Dear Client, In addition to this Special Report written by my colleague Mark McClellan, we are sending you an abbreviated weekly report, which includes the Tactical Global Asset Allocation Monthly Update. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights A "culture of profound cost reduction" has gripped the business sector since the GFC according to one school of thought, permanently changing the relationship between labor market slack and wages or inflation. If true, it could mean that central banks are almost powerless to reach their inflation targets. Amazon, Airbnb, Uber, robotics, contract workers, artificial intelligence, horizontal drilling and driverless cars are just a few examples of companies and technologies that are cutting costs and depressing prices and wages. In the first of our series on inflation, we will focus on the rise of e-commerce and the related "Amazonification" of the economy. In theory, positive supply shocks should not have more than a temporary impact on inflation if the price level is indeed a monetary phenomenon in the long term. But a series of positive supply shocks could make it appear for quite a while that low inflation is structural in nature. We are keeping an open mind and reserving judgement on the disinflationary impact of robotics, artificial intelligence and the gig economy until we do more research. But in terms of the impact of e-commerce, it is difficult to find supportive evidence at the macro level. The admittedly inadequate measures of online prices available today do not suggest that e-commerce sales are depressing the overall inflation rate by more than 0.1 or 0.2 percentage points. Moreover, it does not appear that the disinflationary impact of competition in the retail sector has intensified over the years. Today's creative destruction in retail may be no more deflationary than the shift to 'big box' stores in the 1990s. Perhaps lower online prices are forcing traditional retailers match the e-commerce vendors, allowing for a larger disinflationary effect than we estimate. However, the fact that retail margins are near secular highs outside of department stores argues against this thesis. The sectors potentially affected by e-commerce make up a small part of the CPI index. The deceleration of inflation since the GFC has been in areas unaffected by online sales. High profit margins for the overall corporate sector and depressed productivity growth also argue against the idea that e-commerce represents a large positive macro supply shock. Perhaps the main way that e-commerce is affecting the macro economy and financial markets is not through inflation, but via the reduction in the economy's capital spending requirement. This would reduce the equilibrium level of interest rates, since the Fed has to stimulate other parts of the economy to offset the loss of demand in capital spending in the retail sector. Feature Anecdotal evidence is all around us. The global economy is evolving and it seems that all of the major changes are deflationary. Amazon, Airbnb, Uber, robotics, contract workers, artificial intelligence, horizontal drilling and driverless cars are just a few examples of companies and technologies that are cutting costs and depressing prices and wages. Central banks in the major advanced economies are having difficulty meeting their inflation targets, even in the U.S. where the labor market is tight by historical standards. Based on the depressed level of bond yields, it appears that the majority of investors believe that inflation headwinds will remain formidable for a long time. One school of thought is that low inflation reflects a lack of demand growth in the post-Great Financial Crisis (GFC) period. Another school points to the supply side of the economy. A recent report by Prudential Financial highlights "...obvious examples of ... new business models and new organizational structures, whereby higher-cost traditional methods of production, transportation, and distribution are displaced by more nontraditional cost-effective ways of conducting business." 1 A "culture of profound cost reduction" has gripped the business sector since the GFC according to this school, permanently changing the relationship between labor market slack and wages or inflation (i.e., the Phillips Curve). Employees are less aggressive in their wage demands in a world where robots are threatening humans in a broadening array of industrial categories. Many feel lucky just to have a job. In a highly sensationalized article called "How The Internet Economy Killed Inflation," Forbes argued that "the internet has reduced many of the traditional barriers to entry that protect companies from competition and created a race to the bottom for prices in a number of categories." Forbes believes that new technologies are placing downward pressure on inflation by depressing wages, increasing productivity and encouraging competition. There are many factors that have the potential to weigh on prices, but analysts are mainly focusing on e-commerce, robotics, artificial intelligence, and the gig economy. In the first of our series on inflation, we will focus on the rise of e-commerce and the related "Amazonification" of the economy. The latter refers to the advent of new business models that cut out layers of middlemen between producers and consumers. Amazonification E-commerce has grown at a compound annual rate of more than 9% over the past 15 years, and now accounts for about 8½% of total U.S. retail sales (Chart 1). Amazon has been leading the charge, accounting for 43% of all online sales in 2016 (Chart 2). Amazon's business model not only cuts costs by eliminating middlemen and (until recently) avoiding expensive showrooms, but it also provides a platform for improved price discovery on an extremely broad array of goods. In 2013, Amazon carried 230 million items for sale in the United States, nearly 30 times the number sold by Walmart, one of the largest retailers in the world. Chart 1E-Commerce: Steady Increase In Market Share Chart 2Amazon Dominates With the use of a smartphone, consumers can check the price of an item on Amazon while shopping in a physical store. Studies show that it does not require a large price gap for shoppers to buy online rather than in-store. Amazon appears to be impacting other retailers' ability to pass though cost increases, leading to a rash of retail outlet closings. Sears alone announced the closure of 300 retail outlets this year. The devastation that Amazon inflicted on the book industry is well known. It is no wonder then, that Amazon's purchase of Whole Foods Market, a grocery chain, sent shivers down the spines of CEOs not only in the food industry, but in the broader retail industry as well. What would prevent Amazon from applying its model to furniture and appliances, electronics or drugstores? It seems that no retail space is safe. A Little Theory Before we turn to the evidence, let's review the macro theory related to positive supply shocks. The internet could be lowering prices by moving product markets toward the "perfect competition" model. The internet trims search costs, improves price transparency and reduces barriers to entry. The internet also allows for shorter supply chains, as layers of wholesalers and other intermediaries are removed and e-commerce companies allow more direct contact between consumers and producers. Fewer inventories and a smaller "brick and mortar" infrastructure take additional costs out of the system. Economic theory suggests that the result of this positive supply shock will be greater product market competition, increased productivity and reduced profitability. In the long run, workers should benefit from the productivity boost via real wage gains (even if nominal wage growth is lackluster). Workers may lower their reservation wage if they feel that increased competitive pressures or technology threaten their jobs. The internet is also likely to improve job matching between the unemployed and available vacancies, which should lead to a fall in the full-employment level of unemployment (NAIRU). Nonetheless, the internet should not have a permanent impact on inflation. The lower level of NAIRU and the direct effects of the internet on consumer prices discussed above allow inflation to fall below the central bank's target. The bank responds by lowering interest rates, stimulating demand and thereby driving unemployment down to the new lower level of NAIRU. Over time, inflation will drift back up toward target. In other words, a greater degree of the competition should boost the supply side of the economy and lower NAIRU, but it should not result in a permanently lower rate of inflation if inflation is indeed a monetary phenomenon and central banks strive to meet their targets. Still, one could imagine a series of supply shocks that are spread out over time, with each having a temporary negative impact on prices such that it appears for a while that inflation has been permanently depressed. This could be an accurate description of the current situation in the U.S. and some of the other major countries. We have sympathy for the view that the internet and new business models are increasing competition, cutting costs and thereby limiting price increases in some areas. But is there any hard evidence? Is the competitive effect that large, and is it any more intense than in the past? There are a number of reasons to be skeptical because most of the evidence does not support Forbes' claim that the internet has killed inflation. 1. E-commerce affects only a small part of the Consumer Price Index As mentioned above, online shopping for goods represents 8.5% of total retail sales in the U.S. E-commerce is concentrated in four kinds of businesses (Table 1): Furniture & Home Furnishings (7% of total retail sales), Electronics & Appliances (20%), Health & Personal Care (15%), and Clothing (10%). Since goods make up 40% of the CPI, then 3.2% (8% times 40%) is a ballpark estimate for the size of goods e-commerce in the CPI. Table 1E-Commerce Market Share Of Goods Sector Table 2 shows the relative size of e-commerce in the service sector. The analysis is complicated by the fact that the data on services includes B-to-B sales in addition to B-to-C.2 However, e-commerce represents almost 4% of total sales for the service categories tracked by the BLS. Services make up 60% of the CPI, but the size drops to 26% if we exclude shelter (which is probably not affected by online shopping). Thus, e-commerce in the service sector likely affects 1% (3.9% times 26%) of the CPI. Table 2E-Commerce Market Share Of Service Sector Adding goods and services, online shopping affects about 4.2% of the CPI index at most. The bottom line is that the relatively small size of e-commerce at the consumer level limits any estimate of the impact of online sales on the broad inflation rate. 2. Most of the deceleration in inflation since 2007 has been in areas unaffected by e-commerce Table 3 compares the average contribution to annual average CPI inflation during 2000-2007 with that of 2007-2016. Average annual inflation fell from 2.9% in the seven years before the Great Recession to 1.8% after, for a total decline of just over 1 percentage point. The deceleration is almost fully explained by Energy, Food and Owners' Equivalent Rent. The bottom part of Table 3 highlights that the sectors with the greatest exposure to e-commerce had a negligible impact on the inflation slowdown. Table 3Comparison Of Pre- And Post-Lehman Inflation Rates 3. The cost advantages for online sellers are overstated Bain & Company, a U.S. consultancy, argues that e-commerce will not grow in importance indefinitely and come to dominate consumer spending.3 E-commerce sales are already slowing. Market share is following a classic S-shaped curve that, Bain estimates, will top out at under 30% by 2030. First, not everyone wants to buy everything online. Products that are well known to consumers and purchased on a regular basis are well suited to online shopping. But for many other products, consumers need to see and feel the product in person before making a purchase. Second, the cost savings of online selling versus traditional brick and mortar stores is not as great as many believe. Bain claims that many e-commerce businesses struggle to make a profit. The information technology, distribution centers, shipping, and returns processing required by e-commerce companies can cost as much as running physical stores in some cases. E-tailers often cannot ship directly from manufacturers to consumers; they need large and expensive fulfillment centers and a very generous returns policy. Moreover, online and offline sales models are becoming blurred. Retailers with physical stores are growing their e-commerce operations, while previously pure e-commerce plays are adding stores or negotiating space in other retailers' stores. Even Amazon now has storefronts. The shift toward an "multichannel" selling model underscores that there are benefits to traditional brick-and-mortar stores that will ensure that they will not completely disappear. 4. E-commerce is not the first revolution in the retail sector The retail sector has changed significantly over the decades and it is not clear that the disinflationary effect of the latest revolution, e-commerce, is any more intense than in the past. Economists at Goldman Sachs point out that the growth of Amazon's market share in recent years still lags that of Walmart and other "big box" stores in the 1990s (Chart 3).4 This fact suggests that "Amazonification" may not be as disinflationary as the previous big-box revolution. 5. Weak productivity growth and high profit margins are inconsistent with a large supply-side benefit from e-commerce As discussed above, economic theory suggests that a positive supply shock that cuts costs and boosts competition should trim profit margins and lift productivity. The problem is that the margins and productivity have moved in the opposite direction that economic theory would suggest (Chart 4). Chart 3Comparison Of Pre- And Post-Lehman Inflation Rates Chart 4Incompatible With A Supply Shock By definition, productivity rises when firms can produce the same output with fewer or cheaper inputs. However, it is well documented that productivity growth has been in a downtrend since the 1990s, and has been dismally low since the Great Recession. A Special Report from BCA's Global Investment Strategy 5 service makes a convincing case that mismeasurement is not behind the low productivity figures. In fact, in many industries it appears that productivity is over-estimated. If e-commerce is big enough to "move the dial" on overall inflation, it should be big enough to see in the aggregate productivity figures. Chart 5Retail Margin Squeeze Only In Department Stores One would also expect to see a margin squeeze across industries if e-commerce is indeed generating a lot of deflationary competitive pressure. Despite dismally depressed productivity, however, corporate profit margins are at the high end of the historical range across most of the sectors of the S&P 500. This is the case even in the retailing sector outside of department stores (Chart 5). These facts argue against the idea that the internet has moved the economy further toward a disinflationary "perfect competition" model. 6. Online price setting is characterized by frictions comparable to traditional retail We would expect to observe a low price dispersion across online vendors since the internet has apparently lowered the cost of monitoring competitors' prices and the cost of searching for the lowest price. We would also expect to see fairly synchronized price adjustments; if one vendor adjusts its price due to changing market conditions, then the rest should quickly follow to avoid suffering a massive loss of market share. However, a recent study of price-setting practices in the U.S. and U.K. found that this is not the case.6 The dataset covered a broad spectrum of consumer goods and sellers over a two-year period, comparing online with offline prices. The researchers found that market pricing "frictions" are surprisingly elevated in the online world. Price dispersion is high in absolute terms and on par with offline pricing. Academics for years have puzzled over high price rigidities and dispersion in retail stores in the context of an apparently stiff competitive environment, and it appears that online pricing is not much better. The study did not cover a long enough period to see if frictions were even worse in the past. Nonetheless, the evidence available suggests that the lower cost of monitoring prices afforded by the internet has not led to significant price convergence across sellers online or offline. Another study compared online and offline prices for multichannel retailers, using the massive database provided by the Billion Prices Project at MIT.7 The database covers prices across 10 countries. The study found that retailers charged the same price online as in-store in 72% of cases. The average discount was 4% for those cases in which there was a markdown online. If the observations with identical prices are included, the average online/offline price difference was just 1%. 7. Some measures of online prices have grown at about the same pace as the CPI index The U.S. Bureau of Labor Statistics does include online sales when constructing the Consumer Price Index. It even includes peer-to-peer sales by companies such as Airbnb and Uber. However, the BLS admits that its sample lags the popularity of such services by a few years. Moreover, while the BLS is trying to capture the rising proportion of sales done via e-commerce, "outlet bias" means that the CPI does not capture the price effect in cases where consumers are finding cheaper prices online. This is because the BLS weights the growth rate of online and offline prices, not the price levels. While there may be level differences, there is no reason to believe that the inflation rates for similar goods sold online and offline differ significantly. If the inflation rates are close, then the growing share of online sales will not affect overall inflation based on the BLS methodology. The BLS argues that any bias in the CPI due to outlet bias is mitigated to the extent that physical stores offer a higher level of service. Thus, price differences may not be that great after quality-adjustment. All this suggests that the actual consumer price inflation rate could be somewhat lower than the official rate. Nonetheless, it does not necessarily mean that inflation, properly measured, is being depressed by e-commerce to a meaningful extent. Indeed, Chart 6 highlights that the U.S. component of the Billion Prices Index rose at a faster pace than the overall CPI between 2009 and 2014. The Online Price Index fell in absolute and relative terms from 2014 to mid-2016, but rose sharply toward the end of 2016. Applying our guesstimate of the weight of e-commerce in the CPI (3.2% for goods), online price inflation added to overall annual CPI inflation by about 0.3 percentage points in 2016 (bottom panel of Chart 6). There is more deflation evident in the BLS' index of prices for Electronic Shopping and Mail Order Houses (Chart 7). Online prices fell relative to the overall CPI for most of the time since the early 1990s, with the relative price decline accelerating since the GFC. However, our estimate of the contribution to overall annual CPI inflation is only about -0.15 percentage points in June 2017, and has never been more than -0.3 percentage points. This could be an underestimate because it does not include the impact of services, although the service e-commerce share of the CPI is very small. Chart 6Online Price Index Chart 7Electronic Shopping Price Index Another way to approach this question is to focus on the parts of the CPI that are most exposed to e-commerce. It is impossible to separate the effect of e-commerce on inflation from other drivers of productivity. Nonetheless, if online shopping is having a significant deflationary impact on overall inflation, we should see large and persistent negative contributions from these parts of the CPI. We combined the components of the CPI that most closely matched the sectors that have high e-commerce exposure according to the BLS' annual Retail Survey (Chart 8). The sectors in our aggregate e-commerce price proxy include hotels/motels, taxicabs, books & magazines, clothing, computer hardware, drugs, health & beauty aids, electronics & appliances, alcoholic beverages, furniture & home furnishings, sporting goods, air transportation, travel arrangement and reservation services, educational services and other merchandise. The sectors are weighted based on their respective weights in the CPI. Our e-commerce price proxy has generally fallen relative to the overall CPI index since 2000. However, while the average contribution of these sectors to the overall annual CPI inflation rate has fallen in the post GFC period relative to the 2000-2007 period, the average difference is only 0.2 percentage points. The contribution has hovered around the zero mark for the past 2½ years. Surprisingly, price indexes have increased by more than the overall CPI since 2000 in some sectors where one would have expected to see significant relative price deflation, such as taxis, hotels, travel arrangement and even books. One could argue that significant measurement error must be a factor. How could the price of books have gone up faster than the CPI? Sectors displaying the most relative price declines are clothing, computers, electronics, furniture, sporting goods, air travel and other goods. We recalculated our e-commerce proxy using only these deflating sectors, but we boosted their weights such that the overall weight of the proxy in the CPI is kept the same as our full e-commerce proxy discussed above. In other words, this approach implicitly assumes that the excluded sectors (taxis, books, hotels and travel arrangement) actually deflated at the average pace of the sectors that remain in the index. Our adjusted e-commerce proxy suggests that online pricing reduced overall CPI inflation by about 0.1-to-0.2 percentage points in recent years (Chart 9). This contribution is below the long-term average of the series, but the drag was even greater several times in the past. Chart 8BCA E-Commerce Proxy Price Index Chart 9BCA E-Commerce Adjusted Proxy Price Index Admittedly, data limitations mean that all of the above estimates of the impact of e-commerce are ballpark figures. Conclusions We are keeping an open mind and reserving judgement on the disinflationary impact of robotics, artificial intelligence and the gig economy until we do more research. But in terms of the impact of e-commerce, it is difficult to find supportive evidence. The available data are admittedly far from ideal for confirming or disproving the "Amazonification" thesis. Perhaps better measures of e-commerce pricing will emerge in the future. Nonetheless, the measures available today do not suggest that online sales are depressing the overall inflation rate by more than 0.1 or 0.2 percentage points, and it does not appear that the disinflationary impact has intensified by much. One could argue that lower online prices are forcing traditional retailers to match the e-commerce vendors, allowing for a larger disinflationary effect than we estimate. Nonetheless, if this were the case, then we would expect to see significant margin compression in the retail sector. The sectors potentially affected by e-commerce make up a small part of the CPI index. The deceleration of inflation since the GFC has been in areas unaffected by online sales. High corporate profit margins and depressed productivity growth also argue against the idea that e-commerce represents a large positive macro supply shock. Finally, today's creative destruction in retail may be no more deflationary than the shift to 'big box' stores in the 1990s. Perhaps the main way that e-commerce is affecting the macro economy and financial markets is not through inflation, but via the reduction in the economy's capital spending requirement. Rising online activity means that we need fewer shopping malls and big box outlets to support a given level of consumer spending. This would reduce the equilibrium level of interest rates, since the Fed has to stimulate other parts of the economy to offset the loss of demand in capital spending in the retail sector. To the extent that central banks were slow to recognize that equilibrium rates had fallen to extremely low levels, then policy was behind the curve and this might have contributed to the current low inflation environment. Mark McClellan, Senior Vice President The Bank Credit Analyst markm@bcaresearch.com 1 Robert F. DeLucia, "Economic Perspective: A Nontraditional Analysis of Inflation," Prudential Capital Group (August 21, 2017). 2 Business to business, and business to consumer. 3 Aaron Cheris, Darrell Rigby and Suzanne Tager, "The Power Of Omnichannel Stores," Bain & Company Insights: Retail Holiday Newsletter 2016-2017 (December 19, 2016) 4 "US Daily: The Internet and Inflation: How Big is the Amazon Effect?" Goldman Sachs Economic Research (August 2, 2017). 5 Please see Global Investment Strategy Weekly Report, "Weak Productivity Growth: Don't Blame the Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 6 Yuriy Gorodnichenko, Viacheslav Sheremirov, and Oleksandr Talavera, "Price Setting In Online Markets: Does IT Click?" Journal of the European Economic Association (July 2016). 7 Alberto Cavallo, "Are Online and Offline Prices Similar? Evidence from Large Multi-Channel Retailers," NBER Working Paper No. 22142 (March 2016).

Bank Credit Analyst

A "culture of profound cost reduction" has gripped the business sector since the GFC according to one school of thought, permanently changing the relationship between labor market slack and wages or inflation. If true, it could mean that central banks are almost powerless to reach their inflation targets. Amazon, Airbnb, Uber, robotics, contract workers, artificial intelligence, horizontal drilling and driverless cars are just a few examples of companies and technologies that are cutting costs and depressing prices and wages. In the first of our series on inflation, we will focus on the rise of e-commerce and the related "Amazonification" of the economy. In theory, positive supply shocks should not have more than a temporary impact on inflation if the price level is indeed a monetary phenomenon in the long term. But a series of positive supply shocks could make it appear for quite a while that low inflation is structural in nature. We are keeping an open mind and reserving judgement on the disinflationary impact of robotics, artificial intelligence and the gig economy until we do more research. But in terms of the impact of e-commerce, it is difficult to find supportive evidence at the macro level. The admittedly inadequate measures of online prices available today do not suggest that e-commerce sales are depressing the overall inflation rate by more than 0.1 or 0.2 percentage points. Moreover, it does not appear that the disinflationary impact of competition in the retail sector has intensified over the years. Today's creative destruction in retail may be no more deflationary than the shift to 'big box' stores in the 1990s. Perhaps lower online prices are forcing traditional retailers to match the e-commerce vendors, allowing for a larger disinflationary effect than we estimate. However, the fact that retail margins are near secular highs outside of department stores argues against this thesis. The sectors potentially affected by e-commerce make up a small part of the CPI index. The deceleration of inflation since the GFC has been in areas unaffected by online sales. High profit margins for the overall corporate sector and depressed productivity growth also argue against the idea that e-commerce represents a large positive macro supply shock. Perhaps the main way that e-commerce is affecting the macro economy and financial markets is not through inflation, but via the reduction in the economy's capital spending requirement. This would reduce the equilibrium level of interest rates, since the Fed has to stimulate other parts of the economy to offset the loss of demand in capital spending in the retail sector. Anecdotal evidence is all around us. The global economy is evolving and it seems that all of the major changes are deflationary. Amazon, Airbnb, Uber, robotics, contract workers, artificial intelligence, horizontal drilling and driverless cars are just a few examples of companies and technologies that are cutting costs and depressing prices and wages. Central banks in the major advanced economies are having difficulty meeting their inflation targets, even in the U.S. where the labor market is tight by historical standards. Based on the depressed level of bond yields, it appears that the majority of investors believe that inflation headwinds will remain formidable for a long time. One school of thought is that low inflation reflects a lack of demand growth in the post-Great Financial Crisis (GFC) period. Another school points to the supply side of the economy. A recent report by Prudential Financial highlights "...obvious examples of ... new business models and new organizational structures, whereby higher-cost traditional methods of production, transportation, and distribution are displaced by more nontraditional cost-effective ways of conducting business."1 A "culture of profound cost reduction" has gripped the business sector since the GFC according to this school, permanently changing the relationship between labor market slack and wages or inflation (i.e., the Phillips Curve). Employees are less aggressive in their wage demands in a world where robots are threatening humans in a broadening array of industrial categories. Many feel lucky just to have a job. In a highly sensationalized article called "How The Internet Economy Killed Inflation," Forbes argued that "the internet has reduced many of the traditional barriers to entry that protect companies from competition and created a race to the bottom for prices in a number of categories." Forbes believes that new technologies are placing downward pressure on inflation by depressing wages, increasing productivity and encouraging competition. There are many factors that have the potential to weigh on prices, but analysts are mainly focusing on e-commerce, robotics, artificial intelligence, and the gig economy. In the first of our series on inflation, we will focus on the rise of e-commerce and the related "Amazonification" of the economy. The latter refers to the advent of new business models that cut out layers of middlemen between producers and consumers. Amazonification E-commerce has grown at a compound annual rate of more than 9% over the past 15 years, and now accounts for about 8½% of total U.S. retail sales (Chart II-1). Amazon has been leading the charge, accounting for 43% of all online sales in 2016 (Chart II-2). Amazon's business model not only cuts costs by eliminating middlemen and (until recently) avoiding expensive showrooms, but it also provides a platform for improved price discovery on an extremely broad array of goods. In 2013, Amazon carried 230 million items for sale in the United States, nearly 30 times the number sold by Walmart, one of the largest retailers in the world. Chart II-1E-Commerce: Steady Increase In Market Share Chart II-2Amazon Dominates With the use of a smartphone, consumers can check the price of an item on Amazon while shopping in a physical store. Studies show that it does not require a large price gap for shoppers to buy online rather than in-store. Amazon appears to be impacting other retailers' ability to pass though cost increases, leading to a rash of retail outlet closings. Sears alone announced the closure of 300 retail outlets this year. The devastation that Amazon inflicted on the book industry is well known. It is no wonder then, that Amazon's purchase of Whole Foods Market, a grocery chain, sent shivers down the spines of CEOs not only in the food industry, but in the broader retail industry as well. What would prevent Amazon from applying its model to furniture and appliances, electronics or drugstores? It seems that no retail space is safe. A Little Theory Before we turn to the evidence, let's review the macro theory related to positive supply shocks. The internet could be lowering prices by moving product markets toward the "perfect competition" model. The internet trims search costs, improves price transparency and reduces barriers to entry. The internet also allows for shorter supply chains, as layers of wholesalers and other intermediaries are removed and e-commerce companies allow more direct contact between consumers and producers. Fewer inventories and a smaller "brick and mortar" infrastructure take additional costs out of the system. Economic theory suggests that the result of this positive supply shock will be greater product market competition, increased productivity and reduced profitability. In the long run, workers should benefit from the productivity boost via real wage gains (even if nominal wage growth is lackluster). Workers may lower their reservation wage if they feel that increased competitive pressures or technology threaten their jobs. The internet is also likely to improve job matching between the unemployed and available vacancies, which should lead to a fall in the full-employment level of unemployment (NAIRU). Nonetheless, the internet should not have a permanent impact on inflation. The lower level of NAIRU and the direct effects of the internet on consumer prices discussed above allow inflation to fall below the central bank's target. The bank responds by lowering interest rates, stimulating demand and thereby driving unemployment down to the new lower level of NAIRU. Over time, inflation will drift back up toward target. In other words, a greater degree of the competition should boost the supply side of the economy and lower NAIRU, but it should not result in a permanently lower rate of inflation if inflation is indeed a monetary phenomenon and central banks strive to meet their targets. Still, one could imagine a series of supply shocks that are spread out over time, with each having a temporary negative impact on prices such that it appears for a while that inflation has been permanently depressed. This could be an accurate description of the current situation in the U.S. and some of the other major countries. We have sympathy for the view that the internet and new business models are increasing competition, cutting costs and thereby limiting price increases in some areas. But is there any hard evidence? Is the competitive effect that large, and is it any more intense than in the past? There are a number of reasons to be skeptical because most of the evidence does not support Forbes' claim that the internet has killed inflation. (1) E-commerce affects only a small part of the Consumer Price Index As mentioned above, online shopping for goods represents 8.5% of total retail sales in the U.S. E-commerce is concentrated in four kinds of businesses (Table II-1): Furniture & Home Furnishings (7% of total retail sales), Electronics & Appliances (20%), Health & Personal Care (15%), and Clothing (10%). Since goods make up 40% of the CPI, then 3.2% (8% times 40%) is a ballpark estimate for the size of goods e-commerce in the CPI. Table II-1E-Commerce Market Share Of Goods Sector (2015) Table II-2 shows the relative size of e-commerce in the service sector. The analysis is complicated by the fact that the data on services includes B-to-B sales in addition to B-to-C.2 However, e-commerce represents almost 4% of total sales for the service categories tracked by the BLS. Services make up 60% of the CPI, but the size drops to 26% if we exclude shelter (which is probably not affected by online shopping). Thus, e-commerce in the service sector likely affects 1% (3.9% times 26%) of the CPI. Table II-2E-Commerce Market Share Of Service Sector (2015) Adding goods and services, online shopping affects about 4.2% of the CPI index at most. The bottom line is that the relatively small size of e-commerce at the consumer level limits any estimate of the impact of online sales on the broad inflation rate. (2) Most of the deceleration in inflation since 2007 has been in areas unaffected by e-commerce Table II-3 compares the average contribution to annual average CPI inflation during 2000-2007 with that of 2007-2016. Average annual inflation fell from 2.9% in the seven years before the Great Recession to 1.8% after, for a total decline of just over 1 percentage point. The deceleration is almost fully explained by Energy, Food and Owners' Equivalent Rent. The bottom part of Table II-3 highlights that the sectors with the greatest exposure to e-commerce had a negligible impact on the inflation slowdown. Table II-3Comparison Of Pre- and Post-Lehman Inflation Rates (3) The cost advantages for online sellers are overstated Bain & Company, a U.S. consultancy, argues that e-commerce will not grow in importance indefinitely and come to dominate consumer spending.3 E-commerce sales are already slowing. Market share is following a classic S-shaped curve that, Bain estimates, will top out at under 30% by 2030. First, not everyone wants to buy everything online. Products that are well known to consumers and purchased on a regular basis are well suited to online shopping. But for many other products, consumers need to see and feel the product in person before making a purchase. Second, the cost savings of online selling versus traditional brick and mortar stores is not as great as many believe. Bain claims that many e-commerce businesses struggle to make a profit. The information technology, distribution centers, shipping, and returns processing required by e-commerce companies can cost as much as running physical stores in some cases. E-tailers often cannot ship directly from manufacturers to consumers; they need large and expensive fulfillment centers and a very generous returns policy. Moreover, online and offline sales models are becoming blurred. Retailers with physical stores are growing their e-commerce operations, while previously pure e-commerce plays are adding stores or negotiating space in other retailers' stores. Even Amazon now has storefronts. The shift toward an "multichannel" selling model underscores that there are benefits to traditional brick-and-mortar stores that will ensure that they will not completely disappear. (4) E-commerce is not the first revolution in the retail sector The retail sector has changed significantly over the decades and it is not clear that the disinflationary effect of the latest revolution, e-commerce, is any more intense than in the past. Economists at Goldman Sachs point out that the growth of Amazon's market share in recent years still lags that of Walmart and other "big box" stores in the 1990s (Chart II-3).4 This fact suggests that "Amazonification" may not be as disinflationary as the previous big-box revolution. (5) Weak productivity growth and high profit margins are inconsistent with a large supply-side benefit from e-commerce As discussed above, economic theory suggests that a positive supply shock that cuts costs and boosts competition should trim profit margins and lift productivity. The problem is that the margins and productivity have moved in the opposite direction that economic theory would suggest (Chart II-4). Chart II-3Amazon Vs. Walmart: ##br##Who's More Deflationary? Chart II-4Incompatible With A Supply Shock By definition, productivity rises when firms can produce the same output with fewer or cheaper inputs. However, it is well documented that productivity growth has been in a downtrend since the 1990s, and has been dismally low since the Great Recession. A Special Report from BCA's Global Investment Strategy5 service makes a convincing case that mismeasurement is not behind the low productivity figures. In fact, in many industries it appears that productivity is over-estimated. If e-commerce is big enough to "move the dial" on overall inflation, it should be big enough to see in the aggregate productivity figures. Chart II-5Retail Margin Squeeze ##br##Only In Department Stores One would also expect to see a margin squeeze across industries if e-commerce is indeed generating a lot of deflationary competitive pressure. Despite dismally depressed productivity, however, corporate profit margins are at the high end of the historical range across most of the sectors of the S&P 500. This is the case even in the retailing sector outside of department stores (Chart II-5). These facts argue against the idea that the internet has moved the economy further toward a disinflationary "perfect competition" model. (6) Online price setting is characterized by frictions comparable to traditional retail We would expect to observe a low price dispersion across online vendors since the internet has apparently lowered the cost of monitoring competitors' prices and the cost of searching for the lowest price. We would also expect to see fairly synchronized price adjustments; if one vendor adjusts its price due to changing market conditions, then the rest should quickly follow to avoid suffering a massive loss of market share. However, a recent study of price-setting practices in the U.S. and U.K. found that this is not the case.6 The dataset covered a broad spectrum of consumer goods and sellers over a two-year period, comparing online with offline prices. The researchers found that market pricing "frictions" are surprisingly elevated in the online world. Price dispersion is high in absolute terms and on par with offline pricing. Academics for years have puzzled over high price rigidities and dispersion in retail stores in the context of an apparently stiff competitive environment, and it appears that online pricing is not much better. The study did not cover a long enough period to see if frictions were even worse in the past. Nonetheless, the evidence available suggests that the lower cost of monitoring prices afforded by the internet has not led to significant price convergence across sellers online or offline. Another study compared online and offline prices for multichannel retailers, using the massive database provided by the Billion Prices Project at MIT.7 The database covers prices across 10 countries. The study found that retailers charged the same price online as in-store in 72% of cases. The average discount was 4% for those cases in which there was a markdown online. If the observations with identical prices are included, the average online/offline price difference was just 1%. (7) Some measures of online prices have grown at about the same pace as the CPI index The U.S. Bureau of Labor Statistics does include online sales when constructing the Consumer Price Index. It even includes peer-to-peer sales by companies such as Airbnb and Uber. However, the BLS admits that its sample lags the popularity of such services by a few years. Moreover, while the BLS is trying to capture the rising proportion of sales done via e-commerce, "outlet bias" means that the CPI does not capture the price effect in cases where consumers are finding cheaper prices online. This is because the BLS weights the growth rate of online and offline prices, not the price levels. While there may be level differences, there is no reason to believe that the inflation rates for similar goods sold online and offline differ significantly. If the inflation rates are close, then the growing share of online sales will not affect overall inflation based on the BLS methodology. The BLS argues that any bias in the CPI due to outlet bias is mitigated to the extent that physical stores offer a higher level of service. Thus, price differences may not be that great after quality-adjustment. All this suggests that the actual consumer price inflation rate could be somewhat lower than the official rate. Nonetheless, it does not necessarily mean that inflation, properly measured, is being depressed by e-commerce to a meaningful extent. Indeed, Chart II-6 highlights that the U.S. component of the Billion Prices Index rose at a faster pace than the overall CPI between 2009 and 2014. The Online Price Index fell in absolute and relative terms from 2014 to mid-2016, but rose sharply toward the end of 2016. Applying our guesstimate of the weight of e-commerce in the CPI (3.2% for goods), online price inflation added to overall annual CPI inflation by about 0.3 percentage points in 2016 (bottom panel of Chart II-6). There is more deflation evident in the BLS' index of prices for Electronic Shopping and Mail Order Houses (Chart II-7). Online prices fell relative to the overall CPI for most of the time since the early 1990s, with the relative price decline accelerating since the GFC. However, our estimate of the contribution to overall annual CPI inflation is only about -0.15 percentage points in June 2017, and has never been more than -0.3 percentage points. This could be an underestimate because it does not include the impact of services, although the service e-commerce share of the CPI is very small. Chart II-6Online Price Index Chart II-7Electronic Shopping Price Index Another way to approach this question is to focus on the parts of the CPI that are most exposed to e-commerce. It is impossible to separate the effect of e-commerce on inflation from other drivers of productivity. Nonetheless, if online shopping is having a significant deflationary impact on overall inflation, we should see large and persistent negative contributions from these parts of the CPI. We combined the components of the CPI that most closely matched the sectors that have high e-commerce exposure according to the BLS' annual Retail Survey (Chart II-8). The sectors in our aggregate e-commerce price proxy include hotels/motels, taxicabs, books & magazines, clothing, computer hardware, drugs, health & beauty aids, electronics & appliances, alcoholic beverages, furniture & home furnishings, sporting goods, air transportation, travel arrangement and reservation services, educational services and other merchandise. The sectors are weighted based on their respective weights in the CPI. Our e-commerce price proxy has generally fallen relative to the overall CPI index since 2000. However, while the average contribution of these sectors to the overall annual CPI inflation rate has fallen in the post GFC period relative to the 2000-2007 period, the average difference is only 0.2 percentage points. The contribution has hovered around the zero mark for the past 2½ years. Surprisingly, price indexes have increased by more than the overall CPI since 2000 in some sectors where one would have expected to see significant relative price deflation, such as taxis, hotels, travel arrangement and even books. One could argue that significant measurement error must be a factor. How could the price of books have gone up faster than the CPI? Sectors displaying the most relative price declines are clothing, computers, electronics, furniture, sporting goods, air travel and other goods. We recalculated our e-commerce proxy using only these deflating sectors, but we boosted their weights such that the overall weight of the proxy in the CPI is kept the same as our full e-commerce proxy discussed above. In other words, this approach implicitly assumes that the excluded sectors (taxis, books, hotels and travel arrangement) actually deflated at the average pace of the sectors that remain in the index. Our adjusted e-commerce proxy suggests that online pricing reduced overall CPI inflation by about 0.1-to-0.2 percentage points in recent years (Chart II-9). This contribution is below the long-term average of the series, but the drag was even greater several times in the past. Chart II-8BCA E-Commerce Proxy Price Index Chart II-9BCA E-Commerce Adjusted Proxy Price Index Admittedly, data limitations mean that all of the above estimates of the impact of e-commerce are ballpark figures. Conclusions We are keeping an open mind and reserving judgement on the disinflationary impact of robotics, artificial intelligence and the gig economy until we do more research. But in terms of the impact of e-commerce, it is difficult to find supportive evidence. The available data are admittedly far from ideal for confirming or disproving the "Amazonification" thesis. Perhaps better measures of e-commerce pricing will emerge in the future. Nonetheless, the measures available today do not suggest that online sales are depressing the overall inflation rate by more than 0.1 or 0.2 percentage points, and it does not appear that the disinflationary impact has intensified by much. One could argue that lower online prices are forcing traditional retailers to match the e-commerce vendors, allowing for a larger disinflationary effect than we estimate. Nonetheless, if this were the case, then we would expect to see significant margin compression in the retail sector. The sectors potentially affected by e-commerce make up a small part of the CPI index. The deceleration of inflation since the GFC has been in areas unaffected by online sales. High corporate profit margins and depressed productivity growth also argue against the idea that e-commerce represents a large positive macro supply shock. Finally, today's creative destruction in retail may be no more deflationary than the shift to 'big box' stores in the 1990s. Perhaps the main way that e-commerce is affecting the macro economy and financial markets is not through inflation, but via the reduction in the economy's capital spending requirement. Rising online activity means that we need fewer shopping malls and big box outlets to support a given level of consumer spending. This would reduce the equilibrium level of interest rates, since the Fed has to stimulate other parts of the economy to offset the loss of demand in capital spending in the retail sector. To the extent that central banks were slow to recognize that equilibrium rates had fallen to extremely low levels, then policy was behind the curve and this might have contributed to the current low inflation environment. Mark McClellan Senior Vice President The Bank Credit Analyst 1 Robert F. DeLucia, "Economic Perspective: A Nontraditional Analysis Of Inflation," Prudential Capital Group (August 21, 2017). 2 Business to business, and business to consumer. 3 Aaron Cheris, Darrell Rigby and Suzanne Tager, "The Power Of Omnichannel Stores," Bain & Company Insights: Retail Holiday Newsletter 2016-2017 (December 19, 2016). 4 "US Daily: The Internet And Inflation: How Big Is The Amazon Effect?" Goldman Sachs Economic Research (August 2, 2017). 5 Please see Global Investment Strategy Weekly Report, "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 6 Yuriy Gorodnichenko, Viacheslav Sheremirov, and Oleksandr Talavera, "Price Setting In Online Markets: Does IT Click?" Journal of the European Economic Association (July 2016). 7 Alberto Cavallo, "Are Online And Offline Prices Similar? Evidence From Large Multi-Channel Retailers," NBER Working Paper No. 22142 (March 2016).

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Dear Client, Over the next three weeks, much of BCA’s Geopolitical Strategy team will be traveling in Australia, New Zealand, and Asia. As such, we are taking this week off from publication and will return to our regular schedule next week. In lieu of our regular missive, we are sending you the following Special Report, penned by our colleagues in the BCA Technology Sector Strategy. The report, originally published on May 16, tackles “The Coming Robotics Revolution” in an innovative way that aligns with our own views. Clients often ask us what will be the political consequences of the revolution in artificial intelligence and robotics. Our answers are controversial because we strongly disagree with the conventional, Terminator-inspired, doom and gloom. Brian Piccioni and Paul Kantorovich agree with us, which is reassuring given that they understand the technology behind robotics far better than we do. I hope you enjoy the enclosed report and encourage you to seek out the insights of our Technology Sector Strategy. Kindest Regards, Marko Papic, Senior Vice President Chief Geopolitical Strategist Feature "The amount of technology coming at us in the next five years is probably more than we've seen in the last 50" Mark Franks, Director Of Global Automation at General Motors, Bloomberg News, April 2017 There is good reason to believe we are at the cusp of a Robot Revolution which will have a dramatic impact on our economy. Robots have been around for decades or centuries, depending on the definition. Past robots were either fixed in place, as in the case of factory robots, or supervised by operators that are near the robot, or connected through telemetry. In contrast, the robots that are coming will not be fixed in place, and will be able to perform their functions without a human operator. This opens up massive markets for robots in industry (cutting lawns, cleaning windows, delivering parcels, etc.) and, most significantly, consumer applications. Part 1: Robots - Industrial Revolution To Early 21st Century The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks,"1 a definition which encompasses a broad range of machines: from the Jacquard Loom,2 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. For much of history, most of the labor force was involved with the production of food: over 50% of the U.S. labor force was involved in agriculture until the late 1800s (Chart 1). Agriculture has benefitted immensely from automation as inventions such as the McCormick Reaper (a wheat cutting machine pulled by horses), the cotton gin, and other mechanical systems displaced human effort. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," accelerated the process, as engines delivered much more power more cost effectively than mechanical devices (Chart 2). This massively improved productivity: within 20 years from 1830 to 1850, the labor to produce 100 bushels of wheat dropped from 250-300 to 75-90 hours, and by 1955 it only took 6 ½ hours of labor for a net reduction of 97.5% in 125 years.3 Chart 1Farm Workers Were Disrupted In The Late 19th Century Chart 2...And So Were Horses In other words there is nothing new about automation displacing workers while improving productivity, nor is a rapid displacement unprecedented. The industrial revolution was about replacing human craft labor with capital (i.e. 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. Automation Frightens People Although automation is nothing new, it has always engendered anxiety among workers. The anxiety boils down to concern for continued employment as well as fear of the technology itself. We discuss below why Artificial Intelligence (AI) does not present the sort of threat to humanity or even employment that seems to be the consensus view at the moment. Will Robots Become Self-Aware? We have covered the topic of Artificial Intelligence/Deep Learning as it relates to sentient/self-aware machines in some detail in our October 18, 2016 Special Report on Artificial Intelligence. In summary, most of the discussion surrounding AI is misinformation. Although AI uses algorithms called "artificial neural networks," which are extremely useful for solving certain classes of problems, these are nothing like biological neural networks. There is no reason whatsoever to believe AI technology in its current form can become sentient, or even meaningfully intelligent, and that will not change with increased computing power. Furthermore, whether or not AI can arise to the level of a threat, there is no current or imagined power source which could keep a rampaging robot active for more than a few hours. The Terminator would have been much less threatening if he required frequent recharging. Will Robots Make Human Workers Irrelevant? Automation in agriculture occurred rapidly enough to be felt by workers at the time - and yet there were no marauding hordes of unemployed hay cutters or cowboys. Improved productivity meant markets were opened which did not previously exist, and unemployed agricultural workers moved to factory work. Media coverage of automation tends to focus on the potential job losses without mentioning the fact that the economy and its workers adapt, and overall living standards generally improve (Chart 3). Technology has displaced entire classes of jobs very rapidly in the recent past, and many products such as smartphones would be extremely difficult to assemble if the work was done by hand. Box 1 provides several other examples. Yet as is usual for many things that have happened multiple times in the past, we are told "this time is different." Chart 3The Industrial Revolution Led To A Vast Improvement In Living Standards Box 1 Automation Displaced Entire Classes Of Jobs In The Recent Past, But Brought Enormous Benefits Before calculators and word processors were available, writing and mathematical calculations were done manually. Machines such as calculators and type writers enhanced productivity, eliminating many such jobs. Software applications such as Microsoft Word and Excel further accelerated this process. Not that long ago, welding was entirely a manual job but now most welding in factories is done by robots: you can usually tell a human weld on a mass produced product by its poor quality. Robots in the modern factory have freed up workers for other roles in the economy just as the massive loss of agricultural jobs in the 20th century did. Many modern electronic products such as smartphones would be extremely difficult to assemble if the work was done by hand, as the components are so small they require microscopes to manipulate. Even if it were possible to hand assemble a smartphone, it would take hours of manual labor to produce, and the quality would be very poor. The use of automation means that smartphones cost a few hundred dollars instead of a few thousand dollars and are affordable enough to be a mass market item. Some of the anxiety around automation-related job losses centers on the possibility that this time, robots will displace workers from the service and white-collar sectors. BCA's European Investment Strategy service has written about the potential for AI to replace jobs involving tasks that require specialized education and training, such as calculating credit scores or insurance premiums, or managing stock portfolios.4 Recent developments in AI (specifically deep learning algorithms) have allowed computers to solve pattern recognition problems that they could not previously solve. However, we do not believe AI in its current form poses a widespread risk to white collar employment for the following reasons: Both service-sector and white collar employees have been subject to replacement through automation already, and the economy has adapted: ATMs are robot bank tellers, self-checkout lanes are robot checkout kiosks, and "smart" gas and electric meters that can be read remotely replace human meter readers. The legal profession has been transformed by Google searches and the accounting business by accounting software. These tools allow certain clients to avoid the use of a lawyer or accountant altogether (for example in setting up a corporation or doing bookkeeping), or allow a firm to employ less skilled workers for the task. We can offer numerous other examples of white collar jobs which have been fully or partially automated over the past couple decades. In addition, recall that AI produces high probability answers which turn out to be wrong, and it requires a lot of subject specific training. Both of these are intrinsic to the implementation of the algorithm. In contrast, humans generally are much better at assigning confidence to decisions and train very rapidly because they have cross-expertise AI lacks. An implementation of AI has to meet BOTH of the following conditions to be successful: There has to be a lot of subject-specific data available A high probability assigned to a wrong answer is either inconsequential or can be easily overruled by a human It is also important to note that although AI may reduce the demand for accountants, insurance agents, credit analysts and other skilled professionals, these are exactly the sort of people that can handle retraining. Part 2: What Makes Upcoming Robots Revolutionary Upcoming robots will be different because they will not be confined to the factory floor. We believe this is a key transition point, and that the next 20 years or so will see as dramatic a change from robotics as was caused by the Internet. Factory robots have improved immensely due to cheaper and more capable control and vision systems. Early robots performed very specific operations under carefully controlled conditions -an assembly robot which encountered a misaligned component would simply install it that way, resulting in a defective product. Eventually vision systems were developed which allowed robots to adjust to varying conditions. As camera and computing costs continue to decline, vision systems are becoming more elaborate and useful, as they gather and process more information to make increasingly complex decisions. 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. Mobile robots will likely rely on AI to make many decisions. In order to be cost effective, for many years AI will likely be hosted in cloud data centers. This is especially the case for consumer robots, which will have to be highly capable and yet cost effective. We discuss the implications for cloud services providers in more detail in Part 3: Investment Implications. We May Be Entering A 'Virtuous Cycle' In Robotics Improvements to one domain of robotic applications can be generally applied to others. Robotics technology is concurrently moving forward on many fronts ranging from the aforementioned vacuum cleaners, lawnmowers, and logistics robots, to medical orderlies,5 farm tractors,6 mining equipment,7 transport trucks,8 and cargo ships.9 Despite enormous differences in cost and value added, all of these applications are solving essentially the same problem. As with any other technological revolution, advances between different fields in robotics will be adapted, borrowed, extended and enhanced. This, in turn, creates opportunities for ever more applications, creating a virtuous cycle (Diagram 1). Diagram 1Robotics Will Enter Into A Virtuous Cycle There are few tasks which cannot be automated, but there is a definite cost-benefit tradeoff for each one. For example, a golf course may consider spending $25,000 for a robotic lawnmower, however costs were closer to $70 - $90,000 in 2015,10 and installed cost is even higher.11 Because the incremental cost of the machines is comprised of electronics, which will drop in price rapidly, it is probably a matter of another 2 or 3 years before the price moves to the point where mass adoption by groundskeepers begins. The same improvements to industrial lawnmowers will lead to more useable, albeit still pricy, consumer models which will probably enter mass market adoption 5 to 10 years from now. The same argument can be made for almost any manual chore ranging from cleaning the carpet to delivering parcels. We predict the virtuous cycle for robots will span several decades. As the cost of automation drops, better solutions will be developed, resulting in 'early retirement' of dated but otherwise fully functional robotic systems. This is the opposite of the Feature Saturation phenomenon currently present in the smartphone and PC industries - though feature saturation will eventually hit robots as well. A Self-Driving Car Is A Robot The most important robotics technology, from a macroeconomic perspective, is the rapidly advancing field of Autonomous Vehicles (AVs). The automobile industry is a significant part of the global economy, so changes in this industry will have profound implications. We covered AVs in detail in our April 8, 2016 Special Report. Due to technical and legal obstacles that must be overcome, a vehicle which can safely travel from point to point on major roads and city streets without driver intervention is probably 20 years away, +/- 5 years. The macro impact, however, will occur much sooner than that, due to the technologies developed on the way to full AVs. Vehicles are already offering features such as forward collision warning, autobrake, lane departure warning, lane departure prevention, adaptive headlights, and blind spot detection.12 Although we have only touched the surface, robotics are being applied across many industries, making even seemingly modest advances significant when measured in aggregate, as small changes in one industry are quickly adapted by other industries. It is noteworthy that this transition will likely occur during a period where demographic shifts, in particular in the most developed economies, signal the potential for labor shortages, or at least increasing cost of labor (Chart 4).13, 14 Robots may be showing up in the nick of time to improve both the economy and quality of life in the developed world. Chart 4Advances In Robotics Will Counter Adverse##br## Demographic Trends Part 3: Investment Implications The semiconductor industry has stagnated as the PC and smartphone markets entered a largely replacement-driven era (Chart 5). Although it may not be evident until the virtuous cycle is fully engaged, robotics represents another up-leg in demand for semiconductors and therefore should result in a significant improvement to industry growth rates. There is little opportunity for startup semiconductor companies nowadays due to the high costs of developing a new chip. Well positioned, established, semiconductor companies will be the primary beneficiaries of the robotics revolution. Large firms that attempt to fit their existing product offering into the industry (e.g. by remaining PC or mobile-phone centric) will fall behind. Winners System on a Chip (SoC) Vendors: Robotics hardware will more likely be implemented as "System on a Chip" (SoC) as this provides the greatest functionality with lowest cost and power consumption. SoCs generally consist of a variety of Intellectual Property (IP) "cores" which may be licensed from third parties. Typically, IP cores consist of a microprocessor and various specialized subsystems, depending on the application. Robotics SoCs are likely to include Digital Signal Processing (DSP) or Image Processing cores to process sensor data. SoC vendors who target or encourage robot development, such as Overweight-rated Texas Instruments, are likely to be favored by early movers in the space.15 We believe it is a matter of time before Graphics Processors (GPUs) currently used in AI/Deep Learning are replaced by processors specifically designed for AI, which will be cheaper and more power efficient.16 This is one of the reasons for our Underweight rating on Nvidia. Semiconductor Foundries, Mixed Signal and Automotive Semiconductor Vendors: This environment will favor the merchant semiconductor foundries which manufacture most SoCs. In addition, firms with "mixed signal" expertise will experience increased demand for motor controls, sensor interfaces, etc. As robotics features are added to automobiles, demand for automotive semiconductors should outpace that in other sectors. A significant degree of commonality in the parts and systems used in advanced automobiles will be used in other mobile robots, so "automotive" semiconductor demand should significantly outpace automobile sales. Sensor Vendors: Robots need a variety of sensors, depending on the application. Unlike factory floor robots which can make do with cameras, mobile robots will require advanced radar, ultrasound, laser scanning and other sensor types in order to provide redundancy and cope with weather and other related issues. Important sensors on prototype AVs are currently made in low volumes and are extremely expensive. Due to the number of sensors involved, we believe there is significant opportunity for companies offering aggressive cost reduction in sensor technology. Wireless Equipment and Service Providers: Most robotic systems will include some degree of wireless connectivity and participate in the "Internet of Things" (IoT). This will present challenges and opportunities for wireless equipment and service providers,17, 18 as networks will have to adapt to increased upload bandwidth (from robot to carrier) as well as novel billing schemes. Coverage will also have to be expanded to accommodate AVs as it is non-existent or spotty in large stretches of North American roadways. Not being able to check Facebook between two cities is one thing, losing your robot driver is much more serious. Our recent downgrade of Cisco to Underweight19 may appear inconsistent with the analysis above. However, the company's valuation is extremely elevated and revenues are declining (Chart 6). Any benefit Cisco will derive from investment into wireless infrastructure is several years out, and open-source hardware initiatives are gaining momentum.20 For that reason, we see the risks as outweighing the opportunities at the moment for the company. Chart 5Long Replacement Cycles Mean Slower ##br##Semiconductor Sales Chart 6Cisco's Stock Price Is Close To Tech Bubble##br## Levels Despite Declining Revenue Cloud Service Providers: Most robots will be on line and some will likely use cloud services to offload computational effort and minimize cost. A relatively "dumb" robotic lawnmower which offloads control to a shared computational resource in the cloud would probably be cheaper than a much more capable fully autonomous system. This will increase demand for cloud services, however the challenge of declining margins (due to increased competition in the space) will offset cloud services revenue growth somewhat in the long term. On balance, Overweight-rated Microsoft and Alphabet/Google, as well as Amazon, stand to benefit. Chart 7Eastman Kodak Tried To Ignore The Shift ##br##To Digital Cameras Losers We believe companies who ignore the robotics revolution will find themselves at a significant competitive disadvantage. This is not unprecedented in the technology sector: Digital Equipment Corporation (DEC) and Kodak vanished because their business models could not accommodate an obvious shift in their core markets (Chart 7). Similarly Intel and Microsoft completely missed the smartphone revolution. As we noted in our April 8, 2016 Special Report on AVs, the frequency and severity of crashes will decrease dramatically which will lead to reduced insurance rates, fewer repairs, and less money spent on accident related healthcare and rehabilitation. The economic losses of automobile crashes were estimated $871 billion in the US in 201021 and even a modest reduction in the frequency and severity of collisions due to partial automation would have a significant economic impact. "Dumb" Auto Parts Manufacturers: Fewer collisions will result in fewer repairs to people or vehicles. Auto parts manufacturers will fall into two camps: those with significant expertise in robotics will prosper, while those without such expertise will fall behind as the demand for replacement components (fenders, bumpers, doors, windshields, etc.) will decline. AVs are also likely to include advanced diagnostic and service reminder systems which will result in more timely service, reducing wear and tear on internal components as well. The Auto Insurance Industry: While it is doubtful robotics will ever eliminate auto accidents, the rate might be reduced to such a level that the auto-insurance industry, worth $157 billion in the US alone,22 will be much smaller in 20 years than it is today. This will be offset to a degree by greater demands for product liability insurance for AVs and robots in general. Brian Piccioni, Vice President Technology Sector Strategy brianp@bcaresearch.com Paul Kantorovich, Research Analyst paulk@bcaresearch.com 1 http://www.merriam-webster.com/dictionary/robot 2 http://www.computersciencelab.com/ComputerHistory/HistoryPt2.htm 3 https://www.agclassroom.org/gan/timeline/farm_tech.htm 4 Please see European Investment Strategy Special Report, "Female Participation: Another Mega-Trend," dated April 6, 2017, available at eis.bcaresearch.com. 5 http://www.tomsguide.com/us/Forth-Valley-Royal-Robots-Serco-Medicine,news-7124.html 6 http://modernfarmer.com/2013/04/this-tractor-drives-itself/ 7 http://www.asirobots.com/mining/ 8 http://www.theaustralian.com.au/business/powering-australia/rio-rolls-out-the-robot-trucks/story-fnnnpqpy-1227090421535 9 http://www.bloomberg.com/news/articles/2014-02-25/rolls-royce-drone-ships-challenge-375-billion-industry-freight 10 http://techon.nikkeibp.co.jp/english/NEWS_EN/20141210/393619/ 11 http://www.golfcourseindustry.com/article/do-robotic-mowers-dream-of-electric-turf/ 12 http://www.iihs.org/iihs/topics/t/crash-avoidance-technologies/topicoverview 13 http://gbr.pepperdine.edu/2010/08/preparing-for-a-future-labor-shortage/ 14 http://www.imf.org/external/pubs/ft/fandd/2013/06/das.htm 15 http://www.ti.com/corp/docs/engineeringChange/robotics.html 16 Please see Technology Sector Strategy Weekly Report, "Google - AI And Cloud Strategy," dated April 25, 2017, available at tech.bcaresearch.com. 17 http://www.fiercemobileit.com/press-releases/gartner-says-internet-things-will-transform-data-center 18 http://www.computerworld.com/article/2886316/mobile-networks-prep-for-the-internet-of-things.html 19 Please see Technology Sector Strategy Weekly Report, "Networking Equipment Update ," dated March 28, 2017, available at tech.bcaresearch.com. 20 http://www.businessinsider.com/att-white-box-test-should-scare-cisco-juniper-2017-4 21 http://www.nhtsa.gov/About+NHTSA/Press+Releases/2014/NHTSA-study-shows-vehicle-crashes-have-$871-billion-impact-on-U.S.-economy,-society 22 http://www.bloomberg.c/bw/articles/2014-09-10/why-self-driving-cars-could-doom-the-auto-insurance-industry

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The self-driving car, or Autonomous Vehicle (AV), will have a profound impact on a variety of industries. However, expectations for the timeframe of commercial AV availability are too optimistic. The greatest near-term impact is likely to be from advanced safety technologies developed on the path to full autonomy. In today's <i>Special Report</i>, we discuss our expectations for the timeframe of AV development, and the effect of advanced safety technologies on the Insurance, Health Care, Semiconductors, and Automotive industries.