Investment Themes in 2019

INVESTMENT THEMES IN 2019

Citi GPS: Global Perspectives & Solutions January 2019

Citi is one of the world’s largest financial institutions, operating in all major established and emerging markets. Across these world markets, our employees conduct an ongoing multi-disciplinary conversation – accessing information, analyzing data, developing insights, and formulating advice. As our premier thought leadership product, Citi GPS is designed to help our readers navigate the global economy’s most demanding challenges and to anticipate future themes and trends in a fast-changing and interconnected world. Citi GPS accesses the best elements of our global conversation and harvests the thought leadership of a wide range of senior professionals across our firm. This is not a research report and does not constitute advice on investments or a solicitations to buy or sell any financial instruments. For more information on Citi GPS, please visit our website at www.citi.com/citigps. Citi GPS: Global Perspectives & Solutions January 2019

Jason B Bazinet Robert Buckland U.S. Entertainment, Cable & Satellite Chief Global Equity Strategist Analyst +44-20-7986-3947 | [email protected] +1-212-816-6395 | [email protected]

Aakash Doshi Amit B Harchandani Senior Commodities Strategist Head of EMEA Technology Research

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Pernille B Henneberg Andrew Howell, CFA Global Economist CEEMEA & Frontier Markets Equity Strategy

+44-20-7986-4170 | [email protected] +1-212-816-1388 | [email protected]

Maximilian J Layton Tracy Xian Liao Head of Commodities Research EMEA Global Commodities Strategist

+44-20-7986-4556 | [email protected] +852-2501-2799 | [email protected]

David Lubin Catherine L Mann Head of Emerging Markets Economics Chief Global Economist

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Mark May Edward L Morse U.S. Internet Analyst Global Head of Commodities Research

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Michel Nies Dana M Peterson Emerging Markets Economics Global Economist

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Arthur Pineda Cesar Rojas Co-Head of Pan Asian Telecommunications Global Economist Research +1-212-816-1426 | [email protected] +65-6657-1174 | [email protected]

Xiangrong Yu Senior China Economist

+852-2501-2754 | [email protected]

January 2019 Citi GPS: Global Perspectives & Solutions 3

INVESTMENT THEMES IN 2019

Kathleen Boyle, CFA Our Investment Themes report in 2018 was titled ‘How Much Longer Can the Cycle Managing Editor, Citi GPS Run?’ and with the full year behind us, we are none the wiser. Last year we suspected upside risk to global growth was limited and that expansion may peak in 2018 and noted that we were moving into an increasingly mature phase of the business cycle. At the end of 2018, what we do know is that there is a widening divergence of views on the prospect of the coming year. Our global economics team writes that real economy data on labor market conditions remain robust as a foundation for investment, growth, and inflation. But financial market turbulence suggests deteriorating economic conditions going forward.

Trade tensions between the U.S. and China has thrown a big wrench into global growth plans, increasing uncertainty across markets and stoking fears of a slowdown in global growth. Our commodities team asks us to ‘Call them in March’ as rarely in history have so many factors for the period ahead depended so significantly on the binary outcome of unfolding events. By the end of the first quarter we should hopefully see a resolution of trade talks between the U. S. and China, whether the U.S. Fed is on a slower path to tightening, the fate of Brexit, politics and policies on Francs, and U.S. sanctions on Iran and Russia. The outlook for Emerging Markets is in limbo as investors wait to see if China will be a help of a hindrance to the region.

Given the volatility in markets in 2018, we again have included and updated our Bear Market Checklist that gives us indications of when the next bear market may have begun. The good news is that our analysis shows it’s still too early to make that call. To that end, we believe Frontier Markets are poised to do well as the economic growth outlook looks reasonably solid in contrast to emerging markets

Although coral has been declared the fashion color of 2019, in terms of what we see from as an overarching theme, the color for 2019 is green. China has made decided steps towards being more environmental friendly and it’s crackdown on pollution is driving a structural upgrade and consolidation of industrial commodity producing sectors. Investors are becoming more interested in ‘green’ investing with large increases of assets under management in ESG-related funds. We look at the top sustainability topics in the technology sector and whether there is a combination where the growth aspects embedded in technology firms can combine with the merits of ethical investing.

Smart cities are a focus and we take a look at the driver of smart cities — the Internet-of-Things — and how IoT will help make life better for residents by helping connected networks be more efficient and empowered through the use of data. Finally, we take a deep dive into the subscriber video on demand market and ask whether there are subscribers out there for a new SVOD service to attract.

We are pleased to present our investment themes for 2019, and we wish all readers of our Citi GPS series successful investing in the year ahead.

Contents Domestic Resilience vs. QE Exit and Trade War 5 Are We Headed for a Global Debt Crisis? 11 Emerging Market’s China Problem 17 Equity Strategy Bear Market Checklist 23 Frontier Markets: Hanging In There 29 Global Commodities: Call Us in March 33 China Goes Green 39 Sustainable Tech: Good and Green Growth is the New Normal 45 Internet-of-Things (IoT) and Its Relevance for Smart Cities 51 The Rise of Subscription Video on Demand (SVOD) Platforms 58

Domestic Resilience vs. QE Exit and Trade War Catherine L Mann The past few months has seen a widening divergence of views on prospects for Chief Global Economist 2019 viewed through the lens of financial market data versus the lens of real economy data. Real economy data on labor market conditions remain robust as a Cesar Rojas foundation for investment, growth, and inflation. But, financial market turbulence Global Economist suggests deteriorating economic conditions going forward. Will disorderly financial conditions on account of both quantitative easing (QE) exit and trade war feedback undermine confidence in the real economy and drag it down?

Prospects for global growth hinge on real economic performance of advanced economies and China, with spillovers to emerging markets. Fiscal policies in the U.S. should bolster growth more now, and China’s panoply of policies should moderate the trajectory of growth there. Some emerging markets could gain from the trade war, in part by focusing on domestic policies and by being a seller of China substitute products.

Financial markets will take their cue from these real data, but also reflect how they absorb the monetary policy normalization paths as the Federal Reserve and European Central Bank (ECB) exit from quantitative easing. Significant uncertainties on the trade front could materially increase financial turbulence and undermine real economic performance. A soft landing in 2019 hinges on the resilience of real-side economic foundations to weather both financial and trade storms.

Real Economy Data (Still) Signal Good Prospects

The most important real-economy signal is the strongest labor market conditions in decades. In the U.S., the employment rate of 61% is above the 1950 to 2018 average and the unemployment rate of 3.7% is the lowest since the late 1960s. For Europe, the unemployment rates are at decade lows (8.1% for the Euro area is the lowest since 2008, and the EU rate at 6.7% is the lowest since data were assembled in 2000) and the employment rates at 72% are the highest ever. Labor market tightness in the U.S. and EU is precipitating labor shortages and is finally filtering through to accelerating wage growth (Figure 1, Figure 2).

Figure 1. Significant Labor Shortages in Advanced Economies Figure 2. Advance Economy Wages Beginning to Accelerate

SD points %YY 4 US - Small Businesses 4 U.S. U.K. Japan Euro area Japan - Industrial Firms 3 Euro zone - Industrial & Services Firms 3 2 2 1 1 0 0 -1

-2 -1

-3 -2 1996 1998 2001 2003 2006 2008 2011 2014 2016 2010 2010 2011 2012 2013 2014 2015 2016 2017 2018 Note: U.S. – NFIB: Business with Few or No Qualified Applications for Job Opening; Japan – TANKAN: Employ Conditions: All Enterprises: All Industry: Actual; Euro Area Note: Euro Area: compensation per employee; Japan: Contractual cash earnings; UK: – EC Survey: Factors Limiting Production: Labor. Average weekly earnings; U.S.: Average hourly earnings Source: NFIB, EC, BoJ, and Citi Research Source: National Statistical Offices, Citi Research

Labor market tightness supports the real economy through two channels. First, Figure 3. Strong AE Consumption and strong employment and rising wages support consumption. But labor market Investment tightness also motivates firms to invest in labor-augmenting and labor-substituting %YY %YY capital. Both consumption and investment data remain strong in advanced 3.5 6 economies. (Figure 3) 5 3 4 Higher frequency data confirm investment intentions that should bolster real- 2.5 economy performance. Attention has been fixed on the manufacturing PMI as a 3 bellwether of concern about trade tensions (to be discussed more below). Although 2 2 the advanced economy (AE) manufacturing Purchasing Managers Index (PMI) has 1 1.5 retreated from exuberant highs, it remains healthy, and the momentum for emerging AE Consumption 0 market (EM) manufacturing PMI has shifted positive to move further into expansion. 1 AE GDP -1 Since consumption in advanced economies is disproportionately in services, strong 0.5 AE Investment (right) -2 demand in own domestic markets is an important signal to promote investment in 0 -3 services-producing industries to satisfy local demand (Figure 5, Figure 6). The 2010 2011 2012 2013 2015 2016 2017 positive feedback loop between strong labor markets to strong investment to satisfy local consumption offers an offset to external headwinds. Source: Citi Research Other data on domestic strength come from more domestically-oriented companies that had remained firm (at least until the most recent escalation of U.S.-China tensions that threatens to envelope whole economies, not just outwardly-oriented large firms). The Russell 2000 was outperforming the S&P500. The smaller firms in the DAX were outperforming the large firms. Credit extension to smaller firms in the U.S. has been stronger than to larger firms. Japan’s survey of manufacturers shows confidence at smaller manufacturers and non-manufacturers just a bit off recent highs.

There are other threats but also supports to domestic demand. In terms of threats, Figure 4. Debt Service Is Contained some wonder whether debt service might claim too many resources, to undermine pp their investment strategies and sap consumer spending. Considering potential 2 increases in the policy rate, private non-financial debt-service remains contained 1.5 (Figure 4). Deleveraging (U.S.) and household saving (Europe) provide a buffer to

1 support consumption. Lower oil prices should also feed through to add to consumers’ pockets. Prospects for 2019 fiscal stance indicate that a number of 0.5 countries plan to deploy fiscal policy to reinforce growth, helping to offset monetary 0 tightening and potential downdrafts coming from trade. All told though, strong labor

-0.5 markets are the key underpinning of the ability of domestically-oriented firms to moderate the downside risks of the trade war and financial turbulence. -1 Rates based on market pricing of policy rates -1.5 Rates based on market pricing of policy Inflation prospects, as indicative of strong underlying growth, remain mixed. On the rates +150bp one hand, higher wages appear in the offing, and would support price inflation -2 Unchanged rates 2000 2003 2006 2009 2012 2015 2018 toward the central bank objectives. Offsetting this upward generalized pressure on costs is the moderation in energy prices. Individual economies have differentiated Note: New interest rates will evolve in line with market pricing of the policy rate in the country, household, pressures from tariffs (positive for U.S. costs) and exchange rates (positive for and NFC debt grows at the average rate over the past European costs). When firm’s margins are squeezed from higher costs, they look to year except in some countries where the page of the strength of domestic demand to determine pricing power and ability to pass- leveraging has generally slowed down recently and private sector nominal income will grow at the rate of through costs into higher prices. Survey data suggest that firms are weighing this nominal GDP growth projected by Citi’s economists option. Source: BIS, National Statistical Offices, Citi Research

Figure 5. Advanced Economy Manufacturing Purchasing Manager Index Figure 6. Non-Manufacturing Purchasing Manager Index (PMIs) Are Well (PMIs) are Robust, Emerging Markets Positive Momentum Into Expansionary Territory

Index (50+=Expansion) Index (50+=Expansion) 58 58 Global Manufacturing PMI (using US ISM) AE EM Global NonMfg PMI AE EM 57 56 56 55 54 54 52 53 52 50 51 50 48 49 46 48 2012 2013 2014 2015 2016 2017 2018 2012 2013 2014 2015 2016 2017 2018 Source: Markit, ISM, Citi Research Source: Markit, ISM, Citi Research

An important determinant for global growth in 2019 is China. Real-side performance Figure 7. China Property Prices Resume in both AEs and EMs has survived China’s slowing during 2018. But a turnaround in Uptick China’s investment and consumption paths is needed to bolster the global economy %YoY in 2019. So far, the growth trajectories for consumption (proxied by retail sales) and 12 investment (proxied by fixed asset investment) continue to slide, but the authorities 10 have put in place a wide variety of policies to turn the momentum. Given the 8 importance of real estate as a wealth investment for households, and the 6 importance of consumption as a foundation for future stable growth, the policies 4 related to real estate prices may be the most important to support a turn in the 2 overall growth path; property prices have arrested their slowdown and resumed a 0 modest increase (Figure 7). -2 70 Cities Property Price by First Hand Homes(%YoY) -4 Financial Markets Signal Poor Global Prospects -6 70 Cities Property Price by Second- Hand Homes(%YoY) -8 Against these positive signals from the real-economy data are financial market Oct-14 Oct-15 Oct-16 Oct-17 Oct-18 signals that paint a very different picture for the global economy. The indicator most commonly cited for the U.S. is the yield curve flattening into inversion as a precursor Source: CEIC, Citi Research to recession, not the strong domestic demand of real-side data (Figure 8). Equity market turbulence, sell-off, and softness (different in different markets) call into question earnings prospects and suggest lower growth and little pricing power in 2019. The lack of term premium in long-duration assets implies continued slack growth and no inflationary pressures.

Figure 8. One Yield Curve Inverted; Will Others (And a Recession) Soon Follow?

bps 400 300 200 100 0 -100 -200 5Y-2Y 10Y-3M 3M/18M3M 10Y-2Y 1984 1986 1989 1992 1995 1997 2000 2003 2006 2008 2011 2014 2017 Source: Bloomberg, Macrobond, Citi Research

But, are financial markets telling a story of growth and inflation prospects, or are they reflecting cumulative pressures from monetary policy normalization by the Fed and the likely withdrawal of monetary policy accommodation by the ECB? Are the financial markets under-pricing the solid labor market foundations for growth? They surely are being buffeted by trade tensions which would tend to.

2018 has been an important year in terms of Fed policy normalization, but the process is not finished. The QE-constellation of asset prices has been predicated on low policy rates and low inflation. Completing the exit from QE (often called QT or quantitative tightening) implies normalization of risk spreads (which QE narrowed), reassessing equity valuations (which QE supported and which were further bolstered in U.S. indexes by U.S. fiscal policy) and durable inflation reflected in longer duration assets (but which the very long period of labor market slack delayed). Only a few of these adjustments are apparent in asset prices so far, and, on balance, financial conditions remain very accommodative (Figure 9).

Figure 9. Financial Conditions Remain Accommodative

SD Banking Sector Commodities Market 6 Credit Market Equity Market FX Market Housing Sector Money Market Sovereign Bond 4 AE FCI Tighter financial conditions

-2 2004 2006 2008 2010 2012 2014 2016 2018

Source: National Statistical Offices, Macrobond, Bloomberg, Citi Research How far have financial markets moved toward the QT-constellation of asset prices? On risk spreads in U.S. financial data, there is some return to pricing in risk although more in some types of assets (low investment grade) than others (collateralized loan obligations). On equity markets, the turbulence in the equity markets is the most important component in the change in financial conditions, and is partly due to a runoff of the tax reform windfall (in the U.S.) and trade tensions (everywhere).

The bellwether of both risk prospects as well as inflation prospects is the 10-year U.S. Treasury yield. Based on market forecasts, the 10-year yield should be above 3 and rising over the projection period. But, the implied forward yield on the 10-year U.S. Treasury currently is below 3, has been flat through the projection period, and lurches up and down based on risk sentiment (Figure 10). So the market is conflicted between what it thinks the 10-year ‘should be’ (maybe based on real- economy data?) and how it collectively positions assets.

So, the adjustment from QE to QT in asset prices has far to go, if exit from quantitative easing is to be achieved. Even so, the small adjustment from the QE- constellation of asset prices to a QT-constellation of asset prices with normal credit risk, term risk, and equity valuation risk has been very bumpy so far.

Figure 10. Market Measures Differ for the 10-Year Yield, And Lurch Up and Down Citi Forecast Yield (%) Median Market Forecast (as of February 8) 3.9 Median Market Forecast (as of June 8) Median Market Forecast (as of September 13) Median Market Forecast (as of Nov 12 and Dec 5) Implied Forward Yield (as of February 8) 3.4

2.9 Current

2.4 Q4-2018 Q1-2019 Q2-2019 Q3-2019 Q4-2019 Q1-2020 Source: Citi Research

Supposing that the trade war de-escalates, can the real-economy weather the QT financial storm? Financial turbulence and a move toward the QT-constellation of asset prices could feed back to arrest the momentum in the real-economy. Consumption could be dampened through an equity shock to wealth. Investment could be dampened by uncertainty, higher cost of capital, and higher debt service. What does empirical evidence suggest about the strengths of these channels?

On consumption, the strong labor market is broad-based whereas wealth is concentrated. Empirical evaluation emphasizes the dominance of the labor market in driving consumption. So QT equity valuations would be painful, but would not collapse consumption. On investment, financial turbulence could play a role in undermining investment, particularly of large firms and particularly when amplified by trade (Figure 12), whereas empirical evidence suggests that the cost of capital is less a factor (and indeed could be a positive support to investment to the extent that higher rates evidence higher returns) (Figure 35). So a QT-constellation could be more of a headwind to real-side growth through the investment channel, relatively more for larger firms than for domestically-oriented firms where labor market strength dominates.

Figure 11. U.S.: Investment, Uncertainty, and Rates Figure 12. Germany: Investment and Uncertainty Response of CapEx qqsaar growth to a 1D shock Response of CapEx qqsaar growth to a 1SD shock in 2.5 3.0 2.0 Policy Rate Uncertainty 2.0 1.5 1.0 1.0 0.5 0.0 0.0 -0.5 -1.0 -1.0 -2.0 G4 Composite (3 + CESI) -1.5 Germany composite (3) -3.0 -2.0 -2.5 -4.0 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 Quarters Quarters Note: the VAR model contains change in equity prices, our uncertainty measures, CPI Note: G4 is the first principal component for G4 measures for equity volatility, policy inflation, unemployment rates and a measure of activity. Uncertainty is the first uncertainty, and dispersion in production expectations, and the absolute value of the principle component of G4 measures of equity volatility, policy uncertainty, and CESI. dispersion in production expectations. Source: Eurostat, PolicyUncertainty.com, CitiQuantFX, Citi Research Source: BLS, IMS, PolicyUncertainty.com, CitiQuantFX, Citi Research

Absent the trade wars, the normalization process could proceed as the strength of the real economy could weather the financial turbulence. But, the trade wars appear to be escalating and spreading more broadly to investment restrictions.

Trade Turbulence Muddles the Signals

2019 is likely to be marked by trade turbulence, which makes it even more difficult to read the signals from the financial markets and from the real economy. GDP and inflation would both be affected by tariffs, and even more deeply by investment restrictions. (Figure 13, Figure 14). The financial market gyrations in late 2018 no doubt reflect these potential risks to global growth and inflation, even more so than any monetary policy path. Even if the trade wars do not develop with the virulence as suggested by the scenarios, trade uncertainty will likely persist into 2019. Already, sentiment has turned negative, and modest declines in trade volumes appear in the data. Even if some emerging markets enjoy second-round benefits as supply-chain buyers search for non-China sources, the overall picture is negative.

Figure 13. GDP Scenarios Under Rising U.S.-China Trade Tensions Figure 14. Inflation Scenarios Under Rising U.S.-China Trade Tensions GDP level, cumulative % from baseline, no policy response CPI Index, cumulative % from baseline 0.0 0.0 0.4 0.4 -0.2 -0.2 0.3 0.3 -0.4 -0.4 0.2 0.2 -0.6 -0.6 0.1 0.1 0.0 0.0 -0.8 -0.8 -0.1 -0.1 -1.0 -1.0 -0.2 -0.2 -1.2 -1.2 25% on $200bn 2019 2020 2021 -0.3 -0.3 -1.4 -1.4 -0.4 -0.4 25% on all imports 25% on $200bn 2019 2020 2021 -1.6 -1.6 -0.5 25% on all imports -0.5 -1.8 -1.8 -0.6 -0.6

Note: Both estimates include the impact from tariffs on the initial $50bn Chinese goods Note: Both estimates include the impact from tariffs on the initial $50bn Chinese goods (and the proportionate retaliation by China,) as well as the impact of the 10% tariff on (and proportionate retaliation by China), as well as the impact of the 10% tariff on the the $200bn of Chinese goods. $200bn of Chinese goods. Source: Oxford Economics, Citi Research Source: Oxford Economics, Citi Research

Conclusion

Three forces will dominate 2019: strong labor markets, monetary policy normalization, and trade wars. If just the first two were in train, the strong labor markets’ support for consumption and investment — particularly by domestically - oriented firms — could weather the financial turbulence associated with monetary policy normalization. Indeed, some financial turbulence is a consequence of re- pricing of assets to the QT-constellation. But, unfortunately, the metastasizing trade war has already hit business sentiment, weakened trade growth, and accentuated financial market disorder. Data-dependent monetary policy authorities need to carefully gauge the feed-through of trade and financial turbulence on the real economy even as their keep their sights on exiting QE.

Are We Headed for a Global Debt Crisis? Dana M Peterson Global debt is now more than three times the level it was 20 years ago. In 1999, Global Economist global debt tallied to $79 trillion but has since swollen to $247 trillion as of the first quarter of 2018 — a more than three-fold increase in level terms or by 211 percent. Pernille B Henneberg Global debt, defined as the sum of all liabilities held by households, financial, and Global Economist non-financial corporations plus governments has expanded rapidly over the last 20 years, but appears to have accelerated since 2015.

The outsized amount of global debt, as well as the seeming pick-up in the pace of debt accumulation, has raised concerns the world is headed for another crisis. The sense of urgency has become more palpable since the U.S. Federal Reserve began its policy normalization process. The limited capacity of economies to address a new crisis with monetary, fiscal, and/or political tools is worrisome, but the answer to the primary question of who would fuel a world debt crisis is complex.

The disturbing global debt headline notwithstanding, it is important to understand the key drivers of debt over the last 20 years, and what likely will influence these figures going forwards

The largest economies hold the greatest The largest economies by shares of both global debt and global GDP hold the amount of debt outstanding…but not debt as greatest amount of debt outstanding but debt as shares of local GDP is more shares of local GDP which we think is more informative. The U.S, China, Japan and the euro area hold the lion’s share of important outstanding global debt. The U.S. and China in particular are the individual economies with the most debt, given the relative sizes of their economies and populations. However, when compared as shares of own GDP, the situations of the U.S. and China appear less dire. Indeed, Japan, the Nordics, Canada, and peripheral Europe have the most troubling metrics by share of local GDP. Among emerging markets Singapore, Hong Kong, South Korea, and Lebanon stand out as economies with large debt shares of own GDP.

The biggest contributors of global debt Our analysis reveals that the contributors to global debt have shifted repeatedly constantly shift over the last 20 years. In the period immediately predating the start of the commodity super-cycle, the world experienced moderate debt accumulation. Ahead of the Great Financial Crisis (GFC), householder and financial corporations swelled global debt in large emerging markets that fueled the commodity super-cycle and advanced economies that supplied the raw materials demanded. During the easy global monetary policy period after the GFC, the driver of global debt switched to non-financial firms in emerging markets and governments in advanced economies. In the current ‘Fed tightening’ era, debt levels appear to be rising with interest rates fairly uniformly across regions and economic actors.

But financing debt across the globe can be We also find that rising interest rates amid slowing global growth is a significant risk hurt by rising interest rates and slowing to the ability of economic actors to finance debt across the globe. Advanced global growth economy households in Norway, Sweden, and Australia top the list of economies that are the most vulnerable to higher rates. Advanced economy non-financial firm debt service ratios are poised to spike in Canada, Sweden, France, and the Netherlands. Emerging market private non-financial actors in China and Hong Kong are highly sensitive to rising rates. The majority of advanced economies have poor financial sector health relative to emerging markets especially Europe.

Most AE and several large EM governments Governments of most advanced economies and several large emerging markets are currently over-indebted and are their are currently overly-indebted and highly vulnerable to future sovereign debt risks sovereign debt is at risk from shocks from shocks. Among most advanced economies, the U.S., Japan, and the euro area periphery are the most sensitive to shocks. Among emerging markets China, India Lebanon, Egypt, Pakistan, and Ukraine are at risk. Economies signaling sovereign default risk are mainly in the emerging markets. Neither the U.S. nor China are flashing strong warning lights, but warrant continued monitoring.

Who Is the Most Indebted?

Global debt outstanding is dominated by the largest economies, but shares of debt- to-national GDP and debt as a share of total global debt by economic actor may be more important metrics.

U.S., China, and the euro area hold two- The largest economies by share of global GDP, unsurprisingly, hold the most thirds of the total amount of current global outstanding global debt. The U.S., China, and the euro area are responsible for debt roughly two-thirds of the total amount of current global debt. Together these three regions sum to just over 60% of global debt held by households, financial firms, and governments, respectively. The trio also represents 70% of non-financial corporate debt. Adding Japan, another major economy, would raise the share for households to 70%, financial and non-financial firms to 75%, and governments to nearly 80%. Within Europe the U.K., Germany, and France stand out as the economies holding sizeable levels of debt a shares of global debt. The U.S. (21%), China (13%), Japan (6%), and the euro area (14%) comprise 54% of world GDP.

Advanced economies outpace emerging markets concerning the level of debt by economic actor, in every category. Non-financial corporations among emerging markets possess a significant amount of debt, with liabilities concentrated in China. However, advanced economy debt for households, financial firms, non-financial corporations, and governments all exceed the share for emerging markets. Among advanced economies, financial firms, followed by governments comprise the greatest share of global debt ownership. The advanced economy bulk of the burden is unevenly shared by the U.S., the EU, Japan, the U.K., Canada, and Australia. By these metrics, one might be the most concerned about rising debt in China and the U.S., but comparisons of shares to local GDP are more informative.

But as a share of local GDP, these countries The debt burden risk analysis changes dramatically if debt is considered as a share aren’t as much of a concern of local GDP. Debt as share of local (i.e., own country or region) GDP for the U.S. (as of 1Q 2018) is notably elevated across economic actors, but far from the greatest among advanced economies. Likewise, with the exception of non-financial corporations, China is far from the greatest holder of debt as a share of its own GDP. Still, by the IMF/World Bank definition of debt sustainability 14 of 25 advanced economies, including the U.S., have debt as a share of GDP above the lower 70 percent threshold with Japan and Greece hovering above the 150 percent upper limit. Among 26 emerging markets tracked by the BIS, 21 are over the 25 percent threshold, and 4 are above the 75 percent limit.

Figure 15. Advanced Economies Hold Most Outstanding Global Debt Figure 16. China Stands Out Among Emerging Market Economic Actors with Debt

AE: Debt as Share of Total Global Debt by Economic Actor (%) EM: Debt as Share of Total Global Debt by Economic Actor (%) 90% 90% 80% 80% Other LATAM 70% Non-EA Europe 70% Other CEEMA 60% Australia 60% Other Asia 50% Canada 50% India 40% United Kingdom 40% Japan Brazil 30% 30% Euro Area Korea 20% 20% United States China 10% 10% 0% 0% HH FF NFF GOV HH FF NFF GOV Note: Non-EA Europe includes Denmark, Israel, Norway, Sweden. Note Other LatAm includes Argentina, Chile, Colombia, Mexico; Other CEEMEA Source: BIS, Citi Research includes Egypt, Ghana, Kenya, Lebanon, Nigeria, Russia, Saudi Arabia, South Africa, Turkey, UAE, Ukraine; Other Asia includes Hong Kong, Indonesia, Malaysia, Pakistan, Philippines, Singapore, Thailand. Source: BIS, Citi Research

The U.S. is not the greatest advanced In a comparison of all advance economy and economic actors, Luxemburg, followed economy debtor by share of local GDP by Japan and the Netherlands appears the most worrisome. By economic actor, households in Australia (124), Denmark (122), the Netherlands (107), and Canada (102) rank among the highest shares of debt-to-local GDP, with shares exceeding 100 percent. Collectively, financial firms in Luxemburg (6501), Ireland (330), the Netherlands (316), and Denmark (246) each have debt shares of GDP exceeding 200 percent. The U.K. (186), Japan (149), and Sweden (144) also have sizable aggregate financial firm debt shares of GDP. Non-financial corporations in Western Europe, the Nordics, and Canada are more likely to have debt shares of local GDP exceeding 100 percent, compared to 70 percent in the U.S. Finally, while the U.S. has engaged in a significant degree of fiscal stimulus of late, its general government debt share of GDP stands at a relatively modest 98 percent, compared to shares for Japan (224), the euro area periphery (Greece 186; Italy 150; Portugal 138; Spain 110), Belgium (119), France (110), and the U.K. (108).

China’s debt shares of GDP are not the Mainland China fades to the background when its debt share of own GDP are highest among emerging markets compared to other large emerging market’ debt to own GDP shares. Singapore, South Korea, Lebanon, and Hong Kong have more outsized shares of debt to own GDP by economic actor than does mainland China. Households in South Korea and Lebanon have shares nearing 100 percent of GDP, while Hong Kong, Malaysia, and Thailand have shares approaching 70 percent of GDP, relative to mainland China with a share of 48 percent. Financial firms in Singapore (189) and Hong Kong (141) have the most outsized shares of debt to local GDP, probably given their international financial market hub status. Singapore (141) and Lebanon (110) are the only economies with government debt to GDP shares exceeding 100 percent. Brazil’s share is also quite elevated at 88 percent. China’s debt shares do appear notably large for non-financial firms at 160 percent. Only the share for Hong Kong, which is part of greater China, is higher at 226 percent.

Figure 17. Advanced Economies: Debt as a Percent of National GDP Figure 18. Emerging Markets: Debt as a Percent of National GDP (%) (%)

Source: BIS, IMF, Citi Research Source: BIS, IMF, Citi Research

Who’s Most Vulnerable to Rising Debt Risk?

Vulnerabilities to assorted shocks are disparate across economic actors, regions, and economies. Nonetheless, several economies by economic actor stand out as being at risk of financial crisis fueled by mounting debt.

Households in Norway, Sweden, and We also find that rising interest rates amid slowing global growth is a significant risk Australia top the list of economies that are to the ability of economic actors to finance debt across the global. Advanced most vulnerable to rates…and non-financial economy households in Norway, Sweden, and Australia top the list of economies debt services ratios are poised to spike in that are the most vulnerable to higher rates. Advanced economy non-financial debt Canada, Sweden, France, and the service ratios are poised to spike in Canada, Sweden, France, and the Netherlands. Netherlands Emerging market private non-financial actors in China and Hong Kong are highly sensitive to rising interest rates. Advanced economy financial sectors appear ill- equipped to handle a crisis relative to emerging markets, especially Europe.

Figure 19. BIS Debt Service Ratios Non-Financial Sector: AE Figure 20. BIS Debt Service Ratios Non-Financial Sector: EM

Debt Service Ratio of Private Nonfinancial Sector: HHs & Non-Financial Firms (%) Debt Service Ratio of Private Nonfinancial Sector: HHs & Non-Financial Firms (%) 45 35 40 30 35 25 30 Latest Reading 25 20 Latest Reading 20-Yr Average 20 20-Yr Average 15 20-Yr Max 15 20-Yr Max 10 20-Yr Min 10 20-Yr Min 5 5 0 0 HK U.K. U.S. India Brazil Spain Italy China Turkey Russia Mexico Korea Japan Sweden Thailand France Poland Malaysia Finland Norway Canada Indonesia Belgium Portugal Hungary Australia Denmark Germany Switzerland South Africa Czech Rep Netherlands Note: The debt service ratio (DSR) is defined as the ratio of interest payments plus Note: The debt service ratio (DSR) is defined as the ratio of interest payments plus amortization to income. amortization to income. Source: Bank of International Settlements, Citi Research Source: Bank of International Settlements, Citi Research

Among emerging markets, governments are Governments of most advanced economies and several large emerging markets sensitive to shocks in China, India, Lebanon, are currently overly-indebted and highly vulnerable to future sovereign debt risks Egypt, Pakistan and Ukraine from shocks. Among advanced economies, the U.S., Japan, and the euro area periphery are the most sensitive to shocks. Among emerging markets, China, India, Lebanon, Egypt, Pakistan and Ukraine are at risk.

Figure 21. Most AE General Government Debt is Over IMF 70% Limit Figure 22. Several Large Ems Have Debt Over IMF 60% of GDP Limit

300 EM - General Government Debt Levels (IMF Article IV Reports) AE - General Government Debt Levels (IMF Article IV Reports) 160 151

250 240 140 120 200 188 100 91 86 150 132 72 121 80 69 68 106 101 97 55 53 52 50 100 96 96 87 60 74 71 66 63 62 60 54 53

GrossDebt (% of GDP) 40 50 28 25

GrossDebt (% of GDP) 20 0 0 Italy U.S. U.K. Israel Spain Japan Ireland France Austria Poland Greece Finland Canada Belgium India Portugal Hungary Egypt Africa Germany China South Turkey Mexico Nigeria Ukraine Netherlands Pakistan Lebanon Malaysia

Argentina

Source: IMF, Citi Research Source: IMF, Citi Research

Concluding Thoughts: It’s Complicated

No one economic actor, region, or economy Our analysis reveals a complex web of contributors to a potential global debt crisis. is solely responsible for the rise in global No on particular economic actor, region, or economy is solely responsible for the debt rise in global debt. Moreover, the reasons for elevated debt levels by category can be quite variable from economy to economy. Four examples: (1) both Denmark and the Netherlands have high personal savings due to their pension systems, potentially providing a cushion for households should interest rates rise aggressively; (2) Ireland’s elevated debt levels may reflect tax and other corporate residence considerations; (3) China’s corporate debt is effectively and largely government debt; and (4) Japanese government debt is largely domestically financed. Additionally, current levels of debt may not be the best predictor of future levels of debt and the risks thereof. For example, the BIS’s Drehmann and Juselius note that non-financial firm over-indebtedness is slightly more common than excess debt for households and trends to be linked more closely to the business cycle (i.e. recessions), while household debt is more closely aligned with banking crises, which tend to be less frequent, but deeper. So debt service ratios are only part of the story.

Continued analysis and monitoring is This cursory analysis does provide useful signposts warranting continued analysis warranted, particularly regarding the and monitoring. We can determine that non-financial firms and governments are financial sector health in advanced holding sizeable amounts of debt, but the rates of increase in debt across economic economies actors appears to be about equal since the Fed began hiking. To this end, it is important to understand which economic actors are most at risk of falling prey to rising interest rates, or other shocks, including slower growth. China and the U.S., which possess the greatest store of total global debt outstanding, are not necessarily the smoking guns regarding current (or very near-term) financial crisis risks. However the private non-financial sector in Greater China (Mainland China, Hong Kong) does raise warning flags regarding financial crisis over the next few years. China and the U.S. also should be watched for sovereign debt default risks, according to a variety of metrics, and due to the sheer size of their combined shares of global GDP growth. Finally, while far from satisfactory, current metrics of financial sector health across the globe suggest advanced economies continue to have more work to do to shore up their financial systems, and render themselves more robust to shocks — whether internal or external in nature.

Emerging Market’s China Problem David Lubin Emerging markets (EM) has been an emphatically ‘China-centric’ asset class for Head of Emerging Markets Economics most of the past 20 years, and things seem to be changing now for the worse. The most obvious way in which EM became China-shaped is the 2001-2011 Michel Nies commodities boom and its aftermath. The boom, which was the longest and largest Emerging Market Economics peacetime boom in real commodity prices for almost 200 years, helped to transform EM — particularly its commodity exporters — and the end of the boom coincided with a long period — 2012-2015, more or less — in which EM became vulnerable to consistent downgrades in growth expectations, shocks from U.S. monetary policy, and a global trade recession which was at least partly explained by the effort that China made during those years to ‘rebalance’ its economy away from its dependence on debt accumulation to generate growth.

China stimulus in global trade growth helped The Chinese stimulus of 2015-2017 was especially supportive for EM. The stimulus EM to ensure a recovery in growth that China introduced in late 2015 had two important consequences for EM: (1) it ended the 4.5-year decline in commodity prices which had set in during the summer of 2011, and which started to recover in January 2016; and (2) it helped to trigger a recovery in global trade volumes around mid-2016. Since trade growth in EM had been particularly badly hit by the global ‘trade recession’ of 2012-2015, the China- induced stimulus to global trade growth gave a respite to EM that helped to ensure a recovery in growth. Indeed, thanks to this, 2017 was the first year in five in which forecasters’ growth expectations didn’t have to be revised down. And, perhaps more important, that Chinese stimulus played a significant role in helping to weaken the dollar in 2017: Figure 24 suggests that China ‘causes’ the German (and by extension, European) manufacturing cycle, and so it is reasonable to think that China’s stimulus helped to encourage the ECB to move towards ‘tapering’, which strengthened the euro and weakened the dollar. That dollar weakness was exceptionally helpful to EM since it helped to push capital towards emerging economies, and was also helpful to China since Chinese corporates once again enjoyed access to external financing.

Figure 23. China’s Late 2015 Stimulus Kick-Started Global Trade Figure 24. That Stimulus Also Helped to Engineer the Dollar’s Growth; Though That Stimulus Has Now Ended… Weakness in 2017, Which Helped to Push Capital to EM. That’s Also Gone YoY % China and German manufacturing Index 16 40 14 35 12 30 25 10 20 8 15 6 10 4 5 2 0 0 -5 2011 2012 2013 2014 2015 2016 2017 2018 2019 Li Keqiang Index (6m fwd), lhs Ifo Manufacturing, rhs

Source: Haver Analytics, Citi Research Source: Bloomberg, Haver Analytics, Citi Research

Declining Chinse stimulus combined with EM’s problems in 2018 resulted from the change in the balance between the waning U.S. stimulus led to problems for EM in 2018 of the Chinese stimulus and the appearance of the U.S. stimulus. The withdrawal of China’s stimulus in early 2018 primarily took the form of a sharp decline in local government bond issuance, together with the lagged effects of the ‘regulatory tightening’ in the financial sector that had been in place during the course of 2017. These two factors help explain the location of the two main sources of weakness in the Chinese data during 2018: sharply declining infrastructure investment growth (due to declining bond issuance); and sharply declining retail sales (which is at least partly thanks to declining risk appetite in the financial sector).

The question for 2019 is whether China can Going into 2019, therefore, a critical question is whether China can once again cast cast a benign shadow over EM a benign shadow over EM. To date, the measures Chinese authorities have delivered since the summer of 2018 to support domestic demand have not worked: economic confidence remains low. That may be because the measures announced in recent months were neither large in scale nor effective in their implementation. One way of interpreting this state of affairs is to be optimistic that even if China needs to do more to meet its growth targets, then China will on balance once again emerge as a supportive influence on EM growth expectations. However, since we think the U.S.-China trade conflict is unlikely to disappear for long, this kind of optimism might be misplaced. Instead, our bias is to consider once again the effect on EM of a slower-growing China.

A slowdown in China is one of the largest China is the largest customer for many emerging markets. This is partly just due to risks to EM growth geographic location — a large market surrounded by other emerging economies. But as we'll see further below, China's importance as an export market goes beyond what simple gravity would explain and a slowdown in China is thus one of the largest risks to EM growth. Figure 26 shows the impact of a sharp, but temporary, shock to Chinese GDP growth.1 Peak growth loss in EM other than China is about two-thirds of that of China itself, with the effect being felt stronger in commodity- exporting countries. This chart, as well as others in this section, does not show Citi forecasts, but simulations using a GVAR model, based on quarterly GDP, inflation, real exchange rates, equity markets, policy rates, bond yields, and credit impulses for 31 developed and emerging markets since 2000.

Figure 25. China Is the Largest Export Market for Many Emerging Figure 26. …But Its Weight Means Countries With Less Direct Exposure Economies, and Has Gained Importance Almost Everywhere… and Developed Markets Would Also be Affected by a Shock to It’s Economy China share in exports pp GDP growth YoY, difference to baseline 40% 0.5 35% 0.0 30% 25% -0.5 20% 15% -1.0 10% -1.5 5% 0% -2.0 TW KR BR MY ID TH RU CO IN HU CZ 18Q4 19Q2 19Q4 20Q2 20Q4 21Q2 21Q4 22Q2 22Q4 2013-2017 2000-2004 EM Mfg ex CN EM Comm DM CN

Source: Haver Analytics, Citi Research Source: Citi Research

1 The simulated shock would lead to a growth loss of 1.6 percentage points in the first year. The standard deviation in Chinese four quarter cumulative GPD growth is about 2% since 2000 and 1.4% since 2010.

A shock to the Chinese economy would also China's weight means that a shock to its economy would affect macro-indicators affect economies across the globe around the globe. China was responsible for more than a third of GDP growth and almost half of investment growth over the last five years. The country might be somewhat less important as an export market for developed than for emerging markets, but a nasty shock to the world's third largest market (second if the euro area is not counted as one) would still affect advanced economies (Figure 26). This is particularly true for nearby Japan and the euro area, but even the U.S. would experience some growth loss. And of course these shocks reinforce each other; the U.S. slowdown is probably as much a result of the slowdown in Europe than the one in China.

It is this ability to move the needle globally that makes a China shock so difficult to handle for EM. The reduced demand from China is already uncomfortable in itself, but the propagation through other channels makes it very hard for EM to find a hedge. A way to see this is to fix certain indicators to the same values as in a baseline scenario without a China shock. The shock commodity exporters experience is only about a third as severe when oil and metal prices are (unrealistically) assumed to remain unaffected. These countries thus suffer more from indirect effects, as not only their exports to China, but any other markets, generate less revenue, often leading to currency depreciation and a contraction in domestic absorption. Similarly, the CE3 countries (Czech Republic, Hungary, and Poland) go fairly unscathed if the Euro Area were to prove resilient to a slowdown in China (Figure 27). Other EMs also fare better in that scenario, probably a result of both the lesser crunch in global demand as well as EUR/USD holding up. And since EUR/USD seems to remain a highly important driver of EM risk appetite, a China shock therefore has the potential to hurt EM both on the current and the capital account.

Figure 27. The Impact Is to a Large Degree Through Indirect Channels Figure 28. …And China Itself Can Amplify or Absorb Shocks to Such as Developed Market Growth, EUR/USD or Commodity Prices… Emerging Markets pp China shock: GPD growth YoY, difference to pp EM ex CN: GDP growth YoY, difference to 0.5 baseline 0.2 baseline 0.1 0.0 0.0 -0.1 -0.5 -0.2 -0.3 -1.0 -0.4 -0.5 -1.5 18Q4 19Q2 19Q4 20Q2 20Q4 21Q2 21Q4 22Q2 22Q4 -0.6 Commodity exp. CE3 18Q4 19Q2 19Q4 20Q2 20Q4 21Q2 21Q4 22Q2 22Q4 US10Y shock US10Y shock, China constant Comm. exp., comm. prices con. CE3, no effect on EA growth Source: Citi Research Source: Citi Research

A current account deficit by China could One unknown is the interaction of such a shock with a Chinese current account mean China competes for EM investor deficit. It could be a sign that Chinese imports hold up better than expected and funding thus cushion the impact on the rest of the world. If the shock were however the consequence of contracting Chinese exports (and thus production), it is difficult see how EM exports to China would not suffer, since they are to large extent intermediate goods. A Chinese current account deficit would also mean that, rather than a being net creditor, China would compete with other EM for investor funding.

And if China no longer accumulates reserves, the yield on U.S. bonds might rise further. All in all though, the point is that the appearance of current account deficits in China — after 25 years of perpetual surpluses — could be an extremely important development in international capital markets, and one which is not necessarily in the interests of broader EM.

A permanent slowdown of 1ppt in China A more protracted slowdown would threaten the relative attractiveness of EM as an would reduce EM long-term growth by asset class. In the analysis above, we modeled a sharp, but temporary, shock 0.8ppt having in mind that Chinese policymakers would try to bring growth back to target. A lengthy economic conflict, though, could result in a more permanent growth reduction. Our simulations suggest that a permanent slowdown by 1% percentage point (relative to baseline) would reduce EM long-term growth by 0.8 percentage points. With DM less affected, the growth premium of EM would be in peril.

As China becomes more consumer-driven, Even without a significant slowdown, China might not be as much of a pull factor for sellers of intermediate goods may suffer EM as over the last years. The Chinese growth model has been a boon for disproportionately emerging economies. EM exports to China are significantly higher than what their share in global (ex-China) GDP might imply (Figure 29). This is partly due to geography, as China is surrounded by many important EM, but there is more to it. Figure 30 shows how EM and DM exports to China compare to what a gravity model would predict. In this approach, bilateral trade flows for 60 markets since 2000 are modeled as a function of distance between the trade partners, their respective market size, economic development, and a number of other characteristics such as common language, common colonial past, or whether the market is a commodity exporter. What Figure 30 shows is that Chinese imports were considerably higher than what would be predicted by the countries’ "gravity", and that this premium was mostly an EM phenomenon. The disappearance of the ‘export premium’ to China that EM enjoyed is probably explained by the changing composition of Chinese growth: as China becomes more consumer-driven, it seems natural that a bloc of countries that has relied on selling intermediate goods to China might suffer disproportionately.

Figure 29. Emerging Market Export Shares to China Have Been Larger Figure 30. …But the Large ‘Premium’ That Emerging Markets Enjoyed Than Variables Like Market Size, Distance, etc. Would Predict… Has Disappeared Over the Last Few Years EM share in China's imports vs EM share in %GDP Exports to China $bn 100% global GDP 35% 4.0 14,000 12,000 80% 30% 3.0 10,000 60% 8,000 25% 2.0 40% 6,000 20% 20% 1.0 4,000 2,000 0% 15% 0.0 0 2000 2002 2004 2006 2008 2010 2012 2014 2016 2000 2002 2004 2006 2008 2010 2012 2014 2016 Consumer goods & cars Intermediate goods Actual EM Actual DM Predicted EM Capital goods GDP (rhs) Predicted DM GDP China (rhs) Note: GDP share in Global GDP ex China Source: Haver Analytics, Citi Research Source: Comtrade, Haver Analytics, Citi Research

The days where EM exports to China The change in China's growth composition might not be an EM-friendly one. enjoyed a higher elasticity to Chinese Consumption has become the dominant driver of growth in recent years, whereas demand than DM exports might be previously, China had the somewhat exceptional situation of investment accounting over…and he premium EM exports have for half of growth (Figure 31). A breakdown of Chinese goods imports into broad enjoyed, has disappeared economic classifications reflects this as well; the share of capital goods in imports has decreased, while consumer goods and passenger cars have captured increasingly larger parts of import growth (Figure 32). Intermediate goods still account for three-quarters of Chinese imports and they represent over 80% of EM exports to China, but it appears that at the margin, additional Chinese import expenditure is mostly allocated to consumer goods, which account for less than 4% of EM exports to China. In other words, the days where EM exports to China enjoyed a higher elasticity to Chinese demand than DM exports might be over, and hence the premium EM exports have enjoyed, has disappeared.2 Another way to see this is that vehicles and pharmaceutical imports, not typical EM export goods, account for 60% of the increase in Chinese consumer goods imports over the last decade.3

Figure 31. Chinese Growth Is Increasingly Driven by Consumer Figure 32. …Which is Changing the Structure of Chinese Imports, and Spending Rather Than Investment… Not in a Way That Emerging Markets Will necessarily Benefit From

contribution Contributions to China's GDP growth Chinese imports by category 25% 100% 75% 90% 20% 80% 70% 70% 15% 60% 65% 50% 40% 10% 60% 30% 20% 5% 55% 10% 0% 0% 50% 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 2000 2002 2004 2006 2008 2010 2012 2014 2016 ytd Consumption Gross Capital Formation Consumer goods & passenger cars Capital goods Intermediate goods (rhs) Source: Haver Analytics, Citi Research Source: Comtrade, Citi Research

The structural change in China’s economy Our China-pessimism raises questions about the long-term outlook for capital flows may bode poorly for FDI flows to EM to emerging markets. We showed that a permanent slowdown could partly erode the EM-DM growth differential, and thus the attractiveness of EM as an investment destination. The structural change in China's economy might have a similar effect. This does not bode well for foreign direct investment (FDI) flows, the most stable (and probably most beneficial) source of capital flows to emerging economies.

2 We estimate the long-run elasticity of exports (to China) to Chinese growth is around 1 for Emerging Markets and 0.75 for Developed Markets. We use an autoregressive distributed lag model, based on quarterly export volume data since 2003. As bilateral trade volume data do usually not exist, we use the same price deflators as for the respective economy’s overall export series. 3 Using the HS trade qualification, we mapped 1,363 product categories at the 6-digit level, which are used to calculate the consumption and passenger cars categories in the BEC trade qualification, into 2-digit HS categories.

Foreign investors might see little reason to increase their exposure to EM. The positive EM-DM growth differential should attract capital to EM. However, the share of EM in global inward FDI has been stagnating for many years (Figure 33) and is still below EM's share in in GDP (Figure 34). This could mean that investors don't believe in higher returns in the future, or ask for risk premia larger than the growth differential. This is possible, but there might be another explanation: their exposure is higher than we think.

Figure 33. The Emerging Market Share in Inward FDI Stocks Has Been Figure 34. …But We Believe Its’ Size Might Be Underestimated Stagnating… Share in global (ex China) stock of inward FDI EM ex China: share in global total (ex China) 88% 30% 30% 86% 25% 25% 84% 82% 20% 20% 80% 15% 15% 78% 76% 10% 10% 74% 5% 72% 5% 70% 0% 0% 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 Inward FDI stock Adjusted inward FDI GDP DM share EM ex China share (rhs) stock Source: Haver Analytics, Citi Research Source: Haver Analytics, Citi Research

EM faces a circularity problem – FDI might EM faces a circularity problem. The low returns on capital deter further investment. not flow unless investors expect a rise in The way to lift returns is to increase the supply of other factors of production. Labor returns…but rising returns require a boost to supply is very difficult to boost significantly, unless an economy is coming out of a productivity….but productivity growth in EM deep recession (although measures to increase participation of certain groups can historically has been FDI increase the labor supply somewhat). Improving returns significantly would thus require a boost to productivity. The problem with this is that one of the most important sources for productivity growth in EM has been FDI — which might not flow unless investors expect a rise in returns. The task therefore once again falls to "structural reforms", a catch-all term for a large variety of measures to improve productivity.

EM goes into 2019 with a number of All in all then, the near-term outlook — which is largely governed by the market’s strengths, but could also be the victim of perception of financial resilience — is rosier than the longer-term, which will be further capital account shocks governed by growth differentials. As we argued at the start of this note, EM goes into 2019 with a number of strengths: an ‘under-owned’ asset-class with cheap currencies, diminishing external financing needs, generally robust external balance sheets and a rising ‘risk premium’ as reflected in the real interest rate differential. Of course that’s not to say that EM won’t be a victim of future capital account shocks, but merely that the asset class seems positioned better than it was this year to absorb those shocks. EM’s greater difficulty, we think, is when it comes to thinking about the future of the EM-DM growth differential. Since that differential was so heavily supported by China, the risk of a China slowdown, together with the consequences of a change in the composition of Chinese growth, means that EM is losing an important source of macroeconomic support that it has enjoyed for the past couple of decades.

Equity Strategy Bear Market Checklist Robert Buckland The MSCI AC World fell 13.7% from its September 2018 highs to the end of Chief Global Equity Strategist December. Many investors worry that this marks the beginning of the next bear market. Our Bear Market Checklist (BMC) suggests it’s too early to make that call.

We created our list a few years ago. It was never intended to be a market timing tool. Instead, it helps us to deal with the inevitable corrections when they come along. If it is only showing a few red flags, then investors should hold their nerve and buy the dip. If it is showing many red flags, then buying the dips is dangerous because the next bear market may have begun.

We include 18 factors that sent warning We include 18 factors that sent warning signs at the peak of previous bull markets. signs at the peak of previous bull markets We shade those that look similar to 2000 and 2007 in red. Those that are nearly there are shaded amber. Those that seem fine are left as white. When adding up the total number of warning signs, red counts as one flag, amber counts as a half. This is not a strict quantitative model. We also cast a qualitative eye over the outputs. We compare the current market indicators to those that, with hindsight, were flashing sell in 2000 and 2007.

Our checklist is telling us to still buy the dip Some of our factors can move quickly (e.g., credit spreads and yield curve), but as this bull market is not finished yet others are longer term and move slowly (e.g., capital expenditures and return on equity). This keeps the BMC relevant, but also stops it over-reacting when the corrections occur. It told us to hold our nerve during sharp global sell-offs in 2011-12 and 2015-16. Both were nasty, but neither marked the beginning of the next major global near market. As for now, we are reassured. Only 3.5 of 18 factors are flashing sell compared with 17.5 of 18 in 2000 and 13 of 18 in 2007. Before the recent market correction, there were 4 of 18 factors sending worrying signals. The checklist is telling us to buy this dip. Sure, returns will be lower and volatility higher, but this bull market is not finished yet.

Perhaps equity markets will follow a similar path to that seen earlier in 2018 — a sharp correction followed by a slower recovery. Indeed, the similarities in performance of the S&P are uncanny.

Of the 18 factors, we believe the shape of We are often asked to pick a couple of factors from our checklist that matter most. the U.S. yield curve and investment grade We would probably choose the shape of the U.S. yield curve and investment grade spreads matter the most spreads. If the curve were flat (+21 basis points end-2018) and spreads widened above 175 basis points (currently 155 basis points) then we would be much more reluctant to buy the dip.

Worrying factors include stretched corporate balance sheets and high profitability. A flat U.S. yield curve and rising credit spreads are of particular concern. On the positive side, equity valuations do not look stretched and the equity risk premium is still quite high. Corporate activity is not excessive and fund inflows have never picked up strongly.

We will be more worried with 7-8 factors are In previous cycles, the BMC red flags have accumulated gradually before rising flagging caution exponentially in the last year of the bull market. We will be more worried when 7-8 factors are flagging caution.

Figure 35. Bear Market Checklist Start of Proper Bear Markets Recent Peak March 2000 October 2007 September Now* Global Equity Valuations Trailing Price/Earnings (P/E) 3.3 17 18 15 Forward P/E 24 14 15 13 Dividend Yield 1.3 2.1 2.4 2.8 Cyclically-Adjusted P/E (CAPE) 48 30 25 22 Global Equity Risk Premium 1.0% 3.30% 3.1% 3.9%

U.S. Yield Curve (10-Yr minus 2-Yr) -0.5 0.0 0.2 0.2

Sentiment Global Analyst Bullishness (Std Dev) 1.7 1.0 1.1 1.2 U.S. Panic Euphoria Model 1.09 0.42 0.35 -0.28 Global Equity Fund Flows (3-Yr as % of Mkt 2.9% 0.7% 0.4% 0.2% Cap)*

Corporate Behavior Global CapEx Growth (YoY) 8% (1999) 11% (2007) 8% (2018E) 1% (2019E) Mergers & Acquisitions 6.1% 4.2% 5.3% 5.2% (Previous 6mo as % of Mkt Cap) Initial Public Offerings (IPOs) 0.70% 0.40% 0.2% 0.2% (Previous 12mo as % of DM Mkt Cap)

Profitability Global Return on Equity (RoE) 12.2% 16.1% 12.8% 13.3% Global Earning per Share (EPS) 35% 117% 10% 13%

Balance Sheets / Credit Markets Asset/Equity (U.S. Financials) 16x 16x 10x 10x Net Debt/EBITDA (U.S. ex-Financials) 1.8x 1.4x 1.6x 1.6x u.S. High Yield Bond Spread 600bp 600bp 350bp 555bp U.S. Investment Grade Bond Spread 175bp 175bp 109bp 155bp

# of Sell Signals 17.5/18 13/18 4/18 3.5/18 Note: Shading color code: Red = worrying, Amber = perhaps, White = note worrying *as of Jan 2 2019 Source: Citi Research

Below we go through each factor, explaining how it currently compares to levels reached at the start of the last two major bear markets. We also look for important factors that were not present at previous market peaks, but are more important in the current cycle. The grey bars mark major global bear markets.

Equity Valuations Figure 36. Price/Earnings (P/E) Figure 37. Cyclically Adjusted PE (CAPE) Global equities have de-rated in 2018, which 40 50 MSCI AC World PE Median 35 45 means none of the valuation measures in the BMC 40 30 look stretched anymore. At the September peak, 35 25 30 price-to-earnings (PE) was an amber flag. The 20 25 MSCI AC World benchmark currently trades on a 15 20 trailing of P/E of 15x, below the long-run median of 10 15 17x, while cyclically-adjusted P/E at 22x is slightly 5 10 MSCI AC World CAPE Median below the historic median of 23x. 0 5 80 85 90 95 00 05 10 15 80 85 90 95 00 05 10 15

Rate hikes mean U.S. cash has become an increasingly competitive asset. It yields more than equities for the first time since 2007. Source: Citi Research, MSCI, Datastream Source: Citi Research, MSCI, Datastream

Equity Valuations Figure 38. Dividend Yield Figure 39. Equity Risk Premium

6.0 7% MSCI AC World DY Median The current global dividend yield (2.8%) looks 5.5 reasonable and near the long-term median of 5.0 6% 4.5 2.4%. 5% 4.0

3.5 4% The global Equity Risk Premium (ERP), although 3.0 2.5 3% falling, is still high (at 3.9%) compared to history 2.0 (3.2% median, 3.3% in 2007 and just 1.0% in 1.5 2% 1.0 2000). We would get more worried if it fell below 1% 80 85 90 95 00 05 10 15 the historical averages. MSCI World ERP Median 0% 96 98 00 02 04 06 08 10 12 14 16 18

Source: Citi Research, MSCI, Datastream Source: Citi Research, MSCI, Haver

Yield Curve Figure 40. U.S. Yield Curve Figure 41. European Yield Curve A flat or downward sloping U.S. yield curve has 3.0 3.0 been a good predictor of previous recessions, 2.5 2.5 earnings per share (EPS) collapse, and global bear 2.0 2.0 1.5 markets. A flat curve indicates that Fed policy is 1.5 1.0 tight and likely to drive a slowdown in the economy. 1.0 0.5 Therefore, we watch the recent flattening of the 0.5 0.0 U.S. curve with concern. It’s amber for now. The 0.0 -0.5 yield curve in Europe is less worrying. 10-year -0.5 -1.0 Bund yields are low, but 2-year bund yields are US Yield Curve (10Y minus 2Y) Bund Yield Curve (10Y minus 2Y) -1.0 -1.5 even lower. That has kept the German yield curve 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 upward-sloping. Source: Citi Research, Datastream Source: Citi Research, Datastream

Sentiment Figure 42. U.S. Panic Euphoria Model Figure 43. Global Analyst Bullishness*

1.8 60 Our U.S. Strategy Team’s Panic/Euphoria model is 12m Forward Return (%, rhs) The Other PE 3.0 1.5 50 comprised of nine factors correlated with future Euphoria 1.2 40 2.0 stock price performance. A euphoria reading 0.9 30 1.0 implies a >50% probability of a down market in the 0.6 20 next 12 months. It hit these levels ahead of the 0.3 10 - recent correction but has fallen to Neutral since 0.0 0 -1.0 then and is no longer flagging caution. (0.3) (10) (0.6) (20) -2.0 (0.9) (30) Overly bullish stock analysts were a useful Panic (1.2) (40) -3.0 96 98 00 02 04 06 08 10 12 14 16 18 contrarian indicator in 2000 and 2007. They’ve 87 92 97 02 07 12 17 increasingly become more bullish through the years. The factor is now at amber. Source: Citi Research, US Equity Strategy Source: Citi Research. *Std Dev. High number means more buy vs. sell recommendations

Sentiment Figure 44. Equity Fund Flows (3Yr % Of Mcap) Figure 45. Equity Flows By Region ($bn) We use flows into global equities as a contrarian indicator. Unsustainably high inflows usually signify unsustainably high stock markets. Reassuringly, three year inflows are still far from previous peaks as a percentage of market capitalization

On a regional basis, 2018 inflows as a percent of assets under management (AUM) have been strongest into emerging markets (3.5%) and Japanese equities (10.7%). There have been outflows from U.S. (-0.6%) and European equity funds (-4.3%). Source: Citi Research, EPFR Source: Citi Research. EPFR

Corporate Behavior Figure 46. Global Capex Growth Figure 47. M&A and IPOs as % Of Mcap

25% 14% 0.9% There are limited few signs of CEO exuberance. Global Capex Growth Global M&A (12m rolling as % of Mkt Cap) 0.8% 12% DM IPO (12m rolling as % of Mkt Cap, RHS) Capital expenditures (capex) has picked up 20% 0.7% substantially in 2018, especially in the U.S. 10% 0.6% (+14%). Globally-listed company capex is expected 15% 8% 0.5% to grow by 8% in 2018. But this is still well behind 10% 0.4% the sustained double-digit capex gains at previous 6% 0.3% market peaks. Corporate actions (M&A and IPOs) 5% 4% 0.2% are picking up but still look subdued when 2% 0% 0.1% compared to previous bull markets. Cautious CEOs 0% 0.0% 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 send a reassuring signal. 2018E 2019E 98 00 02 04 06 08 10 12 14 16 18

Source: Citi Research, Worldscope. Ex-financials Source: Citi Research, Dealogic, MSCI

Profitability Figure 48. Global Return on Equity Figure 49. Global EPS* (% from Previous Peak)

17% 120% Unsustainable market highs are usually ROE 16% 100% Distance from previous EPS peak accompanied by unsustainable profitability. Current 15% 80% global return-on-equity (RoE) levels (13.3%) are 14% 60% starting to look stretched. We recently set this 13% 40% factor to amber. 12% 11% 20% 10% 0% Previous bull market peaks have also been 9% -20% accompanied by unsustainably increases in EPS, 8% -40% which then collapse in the subsequent bear 7% 6% -60% market. Global EPS fell 38% in 2001-03 and 57% 80 85 90 95 00 05 10 15 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 in 2008-10. Currently, global EPS is 13% above its 2007 high which does not suggest overextension. U.S. EPS looks more stretched. Global EPS was 35% above its previous peak in 2000 and 117% above in 2007. Source: Citi Research, MSCI, Datastream Source: Citi Research, MSCI, Datastream. * in US$

Balance Sheets Figure 50. Asset / Equity (U.S. Financials) Figure 51. Net Debt / EBITDA (U.S. x Financials)

18 2.0 Last time round, significant balance sheet US Net Debt/EBITDA 17 expansion in the global banking sector gave a big 1.9 16 1.8 warning sign. This factor is unlikely to turn red in 15 1.7 this cycle given the regulatory constraints. 14 1.6 13 1.5 Corporate balance sheets are looking stretched. 12 1.4 The U.S. Net Debt-to-EBITDA ratio exceeds 2007 11 1.3 10 1.2 levels, despite coming down recently. High US Financials: Assets / Equity 9 1.1 leverage worries us and we set this factor to red, 8 1.0 96 98 00 02 04 06 08 10 12 14 16 18 although low interest rates mean this burden is 96 98 00 02 04 06 08 10 12 14 16 18 sustainable for now. Source: Citi Research, Worldscope Source: Research, Worldscope

Credit Markets Figure 52. U.S. HY Bond Spreads (bp) Figure 53. U.S. IG Bond Spreads (bp)

2000 600 Historically, rising credit spreads have been a US HY Credit Spread US IG Spread 1800 useful indicator of future problems for equities, but 500 1600 they can send false sell signals as they did in 2011- 1400 400 12 and 2015-16. As markets move towards end 1200 cycle, we expect spreads to continue rising. U.S. 1000 300 high yield (HY) spreads, at around 555bps, are 800 200 only slightly below the 600bps reached at the 600 400 beginning of previous bear markets. 100 200 0 0 U.S. investment grade (IG) spreads, at 155bps, are 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 moving closer to the dangerous territory of 175bps+ when the last two equity bear markets began. We color this factor amber. Source: Research, Datastream, BAML U.S. High Yield Source: Citi Research, Datastream, Barclay’s U.S. Index Corporate Investment Grade Index

What Are We Missing? Figure 54. China Non-Fins Corp Debt as % GDP Figure 55. Lower QE Means Lower IG Prices

Maybe we are missing something. Perhaps there is 180 2500 50% China Non-Financial Corporate Debt As % of GDP Total CB purchases 40% a new factor which indicates that the next bear 170 160 2000 30% market is imminent. Here are some that are not in 150 Low In The 20% 140 the BMC, but do look worrying: Previous Cycle Very High Now 1500 10% 130 1) High level of Chinese debt, especially non- 120 0% financial corporate debt. 110 1000 -10% 2) The end of quantitative easing (QE) (Figure 55). 100 -20% 90 500 MSCI World -30% 80 12m chg -40% 0 -50% Mar 06 Mar 07 Mar 08 Mar 09 Mar 10 Mar 11 Mar 12 Mar 13 Mar 14 Mar 15 Mar 16 Mar 17 Sep 06 Sep 07 Sep 08 Sep 09 Sep 10 Sep 11 Sep 12 Sep 13 Sep 14 Sep 15 Sep 16 09 10 11 12 13 14 15 16 17 18 19 Source: Citi Research, Haver, BIS Source: Research, Haver

What Are We Missing? Figure 56. U.S. Buyback Figure 57. Italian Bond Spreads (bp) 3) Buybacks: Since 2011, global non-financial corporates have bought back over $3.4 trillion of their own shares, equivalent to 13% of market capitalization. Buybacks in the U.S. have been especially strong, where we expect a record $800 billion shares repurchased in 2018. This is above 2007 highs but below when adjusted for market capitalization. 2) Italian government bond spreads were

synonymous with the European financial crisis of 2011. They have widened again recently. Source: Citi Research, Factset, Worldscope Source: Citi Research, Datastream

Global BMC Through Time Figure 58. Global Bear Market Checklist Red Flags (out of 18) We have charted our BMC over time. We fill in the gaps between the bull market peaks by using a quantitative model to create a moving history.

In the previous market cycles, the red flags have accumulated gradually before rising exponentially in the last year of the bull market. Traditionally, the last factors to fall into place have been analysts’ bullishness, high yield and investment grade credit spreads. These are starting to look more worrying.

But overall, we have not yet seen this gradual accumulation of red flags, let alone the exponential rise of around 5 that traditionally accompany the last year of a bull market.

There will be volatility along the way, but our Bear Market Checklist tells us to

buy this dip. We will get more worried when 7-8 factors are flagging caution. Source: Citi Research Source: Citi Research, MSCI

Frontier Markets: Hanging In There Andrew Howell, CFA Surveying the wreckage of 2018 as a new year for frontier markets (FM) beckons CEEMEA & Frontier Markets Equity Strategy we see the pieces falling into place for a better 2019, although not without its challenges. On the positive side, stocks look much cheaper than they did a year ago, with aggregate FM valuations back to around average levels. Indeed, two markets — Vietnam and Kuwait — inflate the average valuation level, and stripping these out puts the region’s multiple closer to multi-year lows.

The economic growth outlook also looks reasonably solid in FM, in contrast with EM, with an acceleration in GDP growth for the group, on our forecasts, compared with a growth deceleration among both emerging and advanced economies. The same is true of earnings growth: on consensus forecasts, this should be above 15% in 2019 for FM, much better than the sub-10% forecast for EM.

Against these factors can be set a few negatives. Firstly is the fund flow backdrop which remains challenging. The past year has seen significant outflows from FM funds, a trend that, if it does not reverse, could pose a continued headwind, especially for stocks still widely held by FM funds. We suspect that ongoing changes to the FM index — including the upcoming departure of Argentina and potential departure of Kuwait (MSCI Annual Market Classification Review) — are making for a more difficult fundraising environment for FM funds. Meanwhile, the stubbornly low trading liquidity in many stocks continues to act as a deterrent to many EM and global investors to involvement in FM.

A further concern is over the risks to the economic outlook stemming from higher global interest rates, and the effect that this might have on frontier debt dynamics. Debt has risen substantially in many FMs over this cycle.

Putting that together, we expect frontier markets to log a positive, if not stellar return this year.

Frontier Market Survey

As we did in 2018, we surveyed a group of top frontier investors on their outlook for the year ahead and summarize their responses below. The 30+ respondents collectively manage nearly $20b in dedicated frontier markets funds — 60% of which are global frontier funds, with the remainder representing regional strategies.

1. A tough year for flows

Our respondents confirmed a similar picture to the one seen in the EPFR data: the majority (57%) experienced outflows over the past year, while about a third saw inflows and a smaller number (11%) reported neutral flows (Figure 59).

Turning to the coming year, the majority (61%) are nevertheless of an optimistic frame of mind, expecting inflows, compared with just 7% expecting outflows (slightly higher than last year, when not a single respondent expected outflows) and 32% calling for neither.

We asked what is the “right” size of a frontier fund, given liquidity constraints. The most replies (63%) went for the $500 million-$1 billion range as the maximum healthy size for an FM fund, while for a FM/EM fund the majority split between “$1 billion-$2 billion” (30%) and “>$2 billion” (39%). Interestingly, compared with a year ago, more respondents expressed comfort with a larger target fund size, despite lower trading volumes (Figure 60).

Figure 59. Inflows vs. Outflows Figure 60. Maximum Capacity for a Fund 70% Experienced Over the Past Year 70% Frontier Market 61% Expected in the Coming Year 63% 60% 57% 60% Frontier Emerging Markets

50% 50%

40% 40% 39% 32% 32% 30% 30% 30% 26% 22% 20% 20% 11% 11% 10% 7% 10% 4% 4% 0% 0% Net Neither Inflows nor Net <$500mn $500mn - $1bn- >$2bn Inflows Outflows Ouflows $1bn $2bn

Source: Citi Research Source: Citi Research

2. Calling for market gains, FX weakness in 2019

On the heels of a tough year, most respondents came out bullish on frontier markets for 2019. This is the case in absolute terms, where 76% called for gains between 5 and 25%, slightly lower than a year ago but still a strong majority (Figure 61). Respondents were also bullish on relative performance, with 83% expecting FM to outperform DM (Figure 62), although the view on performance relative to EM was more equivocal, with the highest number (41%) calling for in-line performance, a slightly lower smaller number (39%) calling for outperformance and 21% expecting FM to underperform EM.

There was, however, a lack of a consensus on currencies in FM: 28% expected weakness versus the U.S. dollar, while 17% expect appreciation, with a majority having no clear view (Figure 63).

Figure 61. FM Performance in Coming Year? Figure 62. Outperform or Underperform EM? Figure 63. FM Currencies Relative to US$ 90% 90% 83% 60% A Year 55% 76% Ago 80% 80% Relative Emerging Markets 50% 70% 70% Relative Developed 60% 60% Markets 40% 50% 50% 28% 41% 30% 38% 40% A 40% 30% Year 20% 17% 21% 30% Ago 21% 20% 20% 3% 10% 10% 10% 10% 7% 0% 0% 0% -5% to +5% +5% to +25% > +25% Weaken Appreciate No View Outperform In-line Underperform Source: Citi Research Source: Citi Research Source: Citi Research

3. Favored region: Asia, replacing Africa; Top markets: Egypt, Vietnam, Argentina

As to where to expect the best returns on the frontier in 2019, here we see a big improvement in sentiment towards Asia, which is now the most popular region for the year ahead, replacing Africa where 21% now expect top performance, down from 40% last year (Figure 64).

The top country picks were Egypt, Vietnam, and Argentina, all of which also featured in last year’s more popular markets (Figure 65). The markets expected to underperform include Pakistan, Kuwait, and Bangladesh, the last of which replaces Nigeria, which was widely shunned a year ago, but not this year (Figure 66).

Figure 64. Top Region Picks for 2019 Figure 65. Top Country Picks Figure 66. Least Favored Countries

50% Egypt Pakistan Vietnam Kuwait Bangladesh 40% Argentina Saudi Arabia 34% Pakistan Morocco Saudi Arabia 30% Kenya Nigeria Vietnam UAE 21% Romania 20% 17% Kuwait Qatar 17% Bangladesh Sri Lanka 10% 10% Sri Lanka Nigeria Philippines Kazakhstan 0% Georgia Argentina 0% Asia Africa MENA LatAm Europe No View 0% 5% 10% 15% 20% 25% 30% 0% 5% 10% 15% 20% 25% 30% Source: Citi Research Source: Citi Research Source: Citi Research

4. Sectors / Saudi QFI

We asked about sector preferences for 2019, with the responses led by financials (32%), consumer staples (21%), and health care (14%) (Figure 67).

We also asked investors about investing in Saudi Arabia, and note a big shift from a year ago: half of respondents invest there currently, compared with just 11% a year ago, while a further 21% plan to start investing there in the near future (Figure 68). The number of respondents with “no plans” to invest in Saudi Arabia fell from 74% last year to 29%. Clearly, most frontier investors see Saudi as a natural place to invest, despite the fact that it will leapfrog FM and join MSCI’s EM Index directly this coming May.

Figure 67. Top FM Sectors in 2019? Figure 68. Do You Invest as a QFI in Saudi Arabia? 35% 80% 32% 32% Current 30% 70% A Year Ago 60% 25% 50% 21% 50% 20% 40% 15% 14% 30% 29% 10% 21% 20% 5% 10% 0% 0% Financials Consumer Health No Invest Don't Invest Yet, No Plans To Care View Currently But I Plan To Invest

Source: Citi Research Source: Citi Research

6. MSCI Predictions

Our final questions dealt with predictions for MSCI’s actions in its annual country classification review next June. Just 55% expect Kuwait to receive the go-ahead for a move to EM, while a similar number expect MSCI to launch a consultation on moving Vietnam to EM. Meanwhile, expectations for Georgia to be added to the FM index have been tempered by years of inaction by MSCI, with 52% expecting this to occur in the coming year, versus 74% who expected it a year ago (Figure 69).

Figure 69. Do You Expect Any of the Following? 100% 10% 10% 10% 90% 80% 70% 34% 38% 38% 60% 50% 40% 30% 55% 52% 52% 20% 10% 0% Kuwait to be Vietnam to be Georgia to be Added to Promoted to EM Considered for MSCI Frontier Promotion No View No Yes Source: Citi Research

Other Comments

Finally, respondents shared a variety of views on frontier markets and the outlook, some of which we convey below. Many of these highlight the challenges presented by the evolving frontier markets benchmark and what some perceive as a lack of a viable frontier index:

 Some expressed the view that most FM currencies are now attractively valued, meaning that local currency growth can translate into higher USD growth.

 A number mentioned that a new benchmark is needed, despite a lack of consensus among most investors on the most appropriate frontier index. Some suggested that the existing benchmarks have been improperly constructed, rendering them irrelevant.

 Respondents also suggested that the Frontier markets index was even at risk of “dissolving”, although the return of Pakistan to frontier could halt that process.

 Furthermore, some complain that index weight is overly skewed towards companies that cannot be purchased due to foreign ownership limits.

 There is a view that some small markets are missing from the MSCI Frontier index and should be included, with Tanzania given as an example.

Were People Right About Last Year? ‘Fraid Not

The crystal balls were foggy last year. Our respondents correctly predicted that FM currencies would weaken, and they also presciently flagged two of the worst performing markets — Nigeria and Pakistan. On most other questions, however, respondents proved too bullish on the outlook — as were we — expecting FM to do well in both absolute and relative terms. Neither of the top country picks that were cited (Egypt and Argentina) delivered outperformance, while not a single respondent tagged Kuwait to be the year’s top market. Here’s hoping for better soothsaying in 2019!

Global Commodities: Call Us in March Edward L Morse Rarely in history have so many factors for the period ahead depended so Global Head of Commodities Research significantly on the binary outcomes of unfolding events. More critically, the trigger points for these events are unusually concentrated in policy decisions being made Aakash Doshi by the leaders of the two largest economies in the world, which at this juncture have Senior Commodities Strategist abnormally significant impact on global economic growth and the robustness of trade in the year ahead. Maximillian J Layton Head of Commodities Research EMEA All else equal, the outlook for 2019 should still be fairly positive for global GDP growth and with it the outlook for commodities. To be sure, Citi economists are Tracy Xian Liao seeing a slowdown underway, with global GDP decelerating from earlier 2018’s Global Commodities Strategist 3.4% year-over-year increase to 3.2% in 2019 and 3.0% in 2020. But slowing growth is still positive for commodity demand. What’s more, the last of investment spending in many commodities, but in particular in industrial metals, is being accompanied by a significant reduction in inventories with many if not most base metals moving into negative territory on supply versus demand balances and to higher costs on incentive/cost curves for marginal production increases. The situation is more complicated for bulk commodities, where quality differentials in coal (particularly thermal or steaming coal) should strengthen, while those in iron ore shrink. Row crops remain at the vagaries of weather and U.S.-China trade while oil and natural gas are looking, in turn, weaker and stronger, respectively, than we had thought a couple of months ago.

Global politics is a big factor in the But global politics constitute the major ingredients of not only the basic trend lines commodities sector and for basic trend lines for the rest of the year but also for the timing of decisions, which, in turn, impact the this year commodities sector. These include the status of the U.S.-China trade talks come March where the interim U.S. truce either comes to an end or is turned into a future roadmap for negotiation; the level of inventory builds in the oil market and whether OPEC+ needs to meet again to consider deeper cuts; the level of Iranian exports and whether sentiment is for another round of U.S. waivers in imports of Iranian crude and how tight and binding those waivers might be.

Domestic policy changes in China will also Domestic policy changes, particularly in China, should also look a great deal clearer get clearer later in 2019 post Chinese New Year, when the Year of the Dog comes to an end and the Year of the Pig is ushered in, perhaps an omen for consuming a lot and fattening up. That’s one of the two changes indirectly that would be healthy for China — greater household spending along with higher fixed asset investment. A combination of decreased obstacles to trade and higher growth could well support higher GDP growth for both China and the U.S. and, with ripple effect, higher growth for the rest of the world and higher demand for commodities.

By the end of the first quarter, other critical factors might also help clarify the direction of change impacting commodities, including whether the U.S. dollar is strengthening (and emerging market currencies weakening) — or not; whether the U.S. Fed is on a slower path to tightening; the fate of Brexit; politics and policies in France; and U.S. sanctions on Iran and Russia.

By March the World Might Look Less Binary…But Binary It Is for Now

Trade talks between the U.S. and China will The resumption of trade talks between the U.S. and China is already impacting both continue to impact agricultural commodities agricultural commodities and base metals and we expect these impacts to continue and base metals over the next three months but to be subject to volatility as the vicissitudes of trade discussions are reflected in the press and through actual policy. As Citi has long anticipated, U.S. soybeans immediately bounced with the G-20 agreements, but more broadly an array of U.S. exports on top of soy should respond positively to progress in trade negotiations. These include cotton, ethanol, and live hogs as a direct result of potentially “significantly higher Chinese imports.” But we similarly believe there should be higher investor flows into base metals, including especially copper, with the whole industrial metals sector responding even more positively should Chinese authorities given an extra fillip to demand via an uptick in spending on infrastructure and a prod to consumer spending. We also believe that progress on trade should be accompanied by lower prices for iron ore and a dissipation of the spread between richer and less rich ore.

By the end of the initial 90 day period, it should be clear as to whether trade talks are extended with a more precise roadmap agreed jointly by China and the U.S., or whether the U.S. will raise tariffs on the $200 billion of goods currently impacted by a 10% tariff, to a 25% tariff. That should lead to significantly lower expectations of global growth and even lower expectations for the future of both soybean and corn prices and of base metals, especially copper, prices.

We do not expect a full resolution of frictions Come what may, we do not expect a full resolution of fictions between the U.S. and between the U.S. and China any time soon China any time soon, so markets will likely remain volatile for a long while. – volatility will likely persist Underlying the trade war started by the U.S. are issues of fairness related to intellectual property, mandatory transfer, and theft. Deeper changes are required in China’s policy and behavior to resolve this underlying friction.

By the end of the first quarter of 2019 there should be a better sense of the path of the U.S. dollar through 2019, with prolonged U.S. dollar strength being reflected in emerging market currency weakness in importing countries and headwinds to higher demand and GDP growth in developing countries. In the oil markets alone, prolonged U.S. dollar strength could reduce demand by 100-k b/d with a prematurely lower U.S. dollar facilitating perhaps 100-k b/d additional growth.

Trade Tensions May Trigger Higher Correlations Across Commodities Again

We are likely to see more episodes of The low cross-commodity correlation, which helped keep index volatilities low in volatility/cross-commodity correlation spikes recent years, was challenged in 2018 by the breakout of the U.S.-China trade fight. in 2018 due to ongoing trade tensions and We are likely to see more episodes of such volatility/correlation spikes in 2019, with fears of a global growth slowdown ongoing trade tensions and the increasing likelihood of a slowdown in global growth.

Cross-commodity correlations have come off from the peak in the third quarter of 2018 when U.S.-China trade tensions took center stage. The 3-month realized correlation across Bloomberg Commodity Index (BCOM) constituent commodities, which jumped to a 2-year high of 22% in the third quarter of 2018, fell below 10% in the fourth quarter, keeping a lid on the volatility of the benchmark index despite the massive swings in oil and natural gas prices. As expected, while U.S.-China trade tensions have continued to be a major driver of metals and grains prices, the price effect on the energy sector has been secondary to fundamental factors such as Iranian Sanctions, U.S. and OPEC+ production levels, and winter weather conditions. Indeed, the correlations between the energy sector and other sectors are all weaker than 10% and below their long-term averages.

A demand shock in 2019, which could be triggered by an abrupt slowdown in global growth, may send the cross-commodities correlation and index volatilities higher again. The risk of a meaningful slowdown in global growth is higher in 2019 than in recent years, particularly in China and the broader emerging markets, and the recession risk cannot be ruled out completely. A sustained demand shock could lead to widespread price sell-offs across the board, trigger co-movements across sectors, and send index volatilities sharply higher. To be sure, even at its peak of 33%, the 3-month cross-commodity correlation remains low historically — it reached as high as 465 during the Financial Crisis and averaged 33% during 2008-11.

Figure 70. BCOM 3-Month Realized Vol vs. 3-Month Correlation Figure 71. 3-Month Inter-Sector Correlations

30%

25%

20%

15%

10%

5% BCOM 3M Vol BCOM 3M Corr 0% 2014 2015 2016 2017 2018 2019

Note: The 3M realized correlation is calculated as the weighted average pairwise 63- day correlation between the sub-indices of all BCOM constituents. Note: Levels are as of later November 2018 Source: Bloomberg, Citi Research Source: Bloomberg, Citi Research

U.S.-China Trade War is Impacting Commodity Demand — March 2019 Will Be Key

Possible de-escalation of the U.S.-China Global economic activity and sentiment has been impacted by the escalation of the trade war provides a more pro-risk backdrop U.S.-China trade war. While risks remain elevated, the recent halt in the U.S.-China for commodities over the next 3-6 months trade war and the possibility of de-escalation by March 2018 are set to provide a more pro-risk backdrop for commodities over the next 3-6 months.

The slowdown in global growth in part reflected the escalating trade war between the U.S. and China. This has negatively impacted global growth sentiment, real activity, and demand for cyclically-exposed commodities. Specifically, the recent imposition of a new 10% tariff on $200 billion of Chinese goods is set to lower China’s GDP growth by 0.5 percentage points and global growth by 0.2 percentage points according to our economists. However, our economists see Chinese easing measures offsetting the impact of tariffs imposed to date.

Copper and U.S. soybeans are levered to developments in the U.S.-China trade war. Since mid-June 2018 when President Trump imposed the 25% tariff on the first $34 billion of Chinese goods imports to the U.S., copper and U.S. soybeans have been particularly affected, with the former a bellwether for Chinese and global growth, and the latter a key bilaterally traded commodity.

We see a 30% probability trade tensions last Were U.S.-China trade tensions to be prolonged beyond March 2019, this would past March 2019 and add risks to EM pose further downside risks for emerging markets commodities demand. This is our commodities demand metals bear scenario which we attribute a 30% indicative probability. Potential slowdown of China’s manufacturing sector will likely hurt those emerging market countries that are upstream suppliers to China. Trade tensions may also spur the migration of labor-intensive manufacturing out of China, but there is no evidence of this happening yet.

Figure 72. The Soybean Market Is a Great Proxy for Market Sentiment Figure 73. Copper Also Initially Disconnected on the Trade War, Towards U.S.-China Trade Tensions However This Gap has Narrowed More Recently 25% 11000 Modelled vs Actual using forwards 20% 20% U.S. soy export price premium Copper 15mth 15% (discount) to Brazil 10000 Modelled copper using 12-15mth fwds 15% 10% 5% 9000 10% 0% -5% 8000 5% -10% Implementation of 25% import tariffs -15% on U.S. soybeans (July 2018) with 7000 0% -20% expectations of this escalation priced- -25% in late May 2018/June 2018 6000 -5% -30% 5000 -10% Jun-18 Jun-17 Jun-16 Jun-15 Jun-14 Mar-18 Mar-17 Mar-16 Mar-15 Dec-17 Sep-18 Dec-16 Sep-17 Dec-15 Sep-16 Dec-14 Sep-15 Sep-14 4000 -15% 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Source: Bloomberg, Broker Markets, Citi Research Source: Bloomberg, Broker Markets, Citi Research

Figure 74. Expected Impact of a Clean Bilateral Resolution on Commodities Most Sensitive to U.S.-China Trade Spat Commodity Price Impact Comment Soybeans Positive Prices could surge on a quick trade resolution given sizable fund shorts, tight winter supplies in Brazil and since China imports two-thirds of global soybeans. Corn Positive Knock-on impact from higher soybeans and agri-macro. Global corn balances are already tightening; increases odds of China E10 policy for 2020. Cotton Positive China is the leading global producer, consumer, and sovereign stockpile holder of cotton. Represents up to 40% of U.S. high- quality cotton exports. Gold Positive Lower USD/CNY and potential boost to Asian gold consumption growth. US$ rally likely to slow as overall emerging market sentiment gets a meaningful boost. Copper Positive Copper remains one of the most leveraged assets to an improvement in trade talks. Palladium Positive Fundamental tightness has allowed for outperformance despite trade war escalation and speculative unwinds. Palladium has a strong beta to global/Chinese growth so could benefit further on U.S-China trade deal. Crude Oil Slight Positive U.S.-China trade impacts on oil were already minor so any reversal likely to be muted too. But stronger Chinese economic growth and import potential could boost prices. Iron Ore Negative Underperformance versus base metals and outright Bulk commodities did not take a big hit via U.S.-China trade spat and a lasting deal reduces odds of local stimulus. Steel Negative Underperformance versus base metals and outright Bulk commodities did not take a big hit via U.S.-China trade spat and a lasting deal reduces odds of local stimulus. LNG Neutral LNG prices unlikely to move much independently but may follow crude oil price up and down. China would likely sign more contracts with U.S. suppliers and pursue JV's. Commodities Negative Should reduce energy and agriculture sector volatilities albeit industrial metals volatilities are already very low, so a strong

Volatility rebound in copper prices could lift implied volatilities there. Source: Citi Research

China: Goodbye Deleveraging, Welcome Stimulus

China has experienced a material slowdown in fixed asset investment and retail sales in 2018, reinforcing the urgency of supporting growth amid uncertainty on the trade war with the U.S. and prompting the government to restart stimulus measures after largely abandoning them for the past few quarters.

China’s macro data for September and October suggest a continued slowdown in growth momentum, in particular on household consumption. The question now is how Beijing would deploy stimulus measures and whether these measures would be strong and quick enough to offset the likely simultaneous slowdown of exports and household consumption. The situation of U.S.-China trade tensions remains fluid despite a temporary postponement of 25% tariffs on $250 billion worth of Chinese goods, and the current “trade war truce would further reduce the odds of a major stimulus package from Beijing to offset negative consequences of escalated trade tariffs.

To support the economy, apart from across-the-board cuts in taxes and fees that may revitalize investments and household consumption, other targeted stimulus measures may start with infrastructure — which appears to be an easy fix after a 12-month deceleration in infrastructure fixed-asset investment. In order for infrastructure spending to grow materially, Beijing needs to remove a series of regulatory constraints on banks’ off-balance sheet financing. While it is not our base case, if downward pressure to growth is so severe that further stimuli are needed, Beijing may re-allow property sales to grow by raising cash subsidies to shantytown residents — a key driver behind the 2016-17 Chinese property boom.

Figure 75. Real Infrastructure Fixed-Asset Investment to Pick Up Figure 76. Investment Is Expected to Accelerate to Offset Slowdown in Consumption and Net Exports 1200 30% Consumption Investment Net Exports GDP 20 1100 25%

1000 20% 15

900 15% 10 800 10% %

CNY billion CNY 700 5% 5 600 0% Infrastructure, yoy (rhs) 500 Infrastructure, sa, level -5% 0 Infrastructure, 6mma, sa 400 -10% -5 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Sep-12 Sep-13 Sep-14 Sep-15 Sep-16 Sep-17 Sep-18 May-12 May-13 May-14 May-15 May-16 May-17 May-18 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Source: NBS, Citi Research Source: NBS, Citi Research

China’s Environmental Campaign is Reshaping the Commodity Markets

China’s increasing focus on pollution is driving a structural upgrading and consolidation of the nation’s commodity producing sectors. The past two years of capacity cuts by brute force, combined with more stringent emission standards and rising pollutant charges have boosted the industrial utilization rates and in some cases prompted commodity price spikes. Going forward, targeted environmental overhauls should drive a slow-burn cost inflation process across different industries partly via scrubber installation, use of cleaner energy, and logistics.

China’s winter production curtailments in steel and aluminum have so far appeared weaker-than-expected, but should eventually kick in as local governments in eastern China pledge to reduce PM2.6 concentration by 3-5% year-over-year, and production cuts are the easiest options to clean up the air. More importantly, production cuts are extended across a broader set of regions this year, reducing the potential for regulated production cuts to be offset with rising production in the rest of the country.

Cost inflation, supply disruptions and a shift in the energy mix will likely send prices higher for aluminum LNG, and coke over the next 6-12 months. Prices of petroleum products, copper, thermal coal, steel, zinc, and lead may also find some support. Steel, high-grade iron ore, and coal benefitted from steep Chinese production cuts over the past two years. Prices are expected to stay elevated as a result of stable Chinese demand and persistent limits on supply growth.

Figure 77. Beijing’s PM2.5 Concentration Spiked in November Figure 78. China Reforms and Commodity Matrix

Pollution New 2013-2016 2017 2018 Pollution at Heavy FAI at Demand 250 End-user Debts Dependent Producer Horizon Steel Yes Maybe Maybe Yes Maybe 200 Thermal Coal Yes Yes Maybe Maybe No Coking Coal Yes Yes Maybe Yes No

150 Iron Ore Yes Yes Maybe Yes No Copper Yes Maybe Maybe Maybe Yes

μg/m3 Aluminium Yes Maybe Maybe Maybe Yes 100 Nickel Yes Maybe Maybe Yes Yes Zinc Yes Maybe Maybe Yes Maybe 50 Lead Yes Maybe Maybe Maybe Maybe Crude Oil Yes Yes No Yes No 0 Diesel Yes Yes Maybe Yes No Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Gasoline Yes Maybe Maybe No No Natural Gas Yes No No Maybe Yes Source: Ministry of Ecology and Environment, Wind, Bloomberg Citi Research Source: Ministry of Ecology and Environment, Wind, Bloomberg Citi Research

China Goes Green Tracy Xian Liao China’s crackdowns on pollution are driving a structural upgrading and Global Commodities Strategist consolidation of the industrial commodity producing sectors, a crucial step to match China’s environmental quality with its income level by discouraging investment into Xiangrong Yu energy-and-pollution-intensive industries. Beijing has so far managed to strike a fine Senior China Economist balance between cleaning up the environment and maintaining growth momentum, though we remain cautious that PPI inflation will possibly run ahead of planned fiscal stimuli in the quarters to come, limiting domestic policy’s room to head off external trade pressures.

Chinese environmental policies are evolving After two years of forceful “one size fits all” production cuts which prompted major from ‘one size fits all’ to more targeted price spikes for a number of industrial commodities, environmental policies are overhauls evolving into targeted overhauls, triggering a slow-burn cost inflation process across different industries partly via scrubber installation, use of cleaner energy and logistics. China’s “war on pollution” is also pressing local governments to score high on environment and incentivizing them to continue ordering shutdowns at polluting plants during visits by central government inspection teams and when their jurisdictions rank low in air quality. This should remain China's major policy focus over the next two years.

Cost inflation, supply disruptions, and a shift in the energy mix will likely send prices higher for aluminum, liquefied natural gas (LNG), and coke over the next 6-12 months. Prices of petroleum products, copper, thermal coal, steel, zinc, and lead may also find some support. Steel, high-grade iron ore, and coal benefitted from steep Chinese production cuts over the past two years. Prices are expected to stay elevated as a result of stable Chinese demand and persistent limits on supply growth.

China is emerging as an exporter of inflation China is emerging as an exporter of inflation to the rest of the world. Such spillover to the rest of the world primarily happens via higher export prices of manufacturing goods. China’s appetite for imported raw materials is likely plateauing due to limited investment into new processing capacity, while imports of clean energy such as LNG are set to rise. The environmental crackdowns might also spur migration of manufacturing out of China into countries with higher competitiveness in low-value-added sectors.

China’s environmental campaign is creating investment opportunities across the commodity supply chains. Leaders in the Chinese material sector, Chinese natural gas distributors, the new energy vehicle value chain, and global metals and mining producers that offer high quality ore products are expected to benefit. Ex-China steel, aluminum and alumina producers will also likely benefit from China’s persisting supply discipline.

We must speed up the construction of a system of ecological civilization and ensure that the ecology and environment are fundamentally improved by 2035, and that our goal of building a beautiful China is basically achieved. – XI JINPING

China has cut capacity in polluting sector China has done a remarkable job in cutting capacity in polluting sectors in recent and is set to materially accelerate their years. It has also unveiled a series of aggressive ‘war books’ on pollution, which are environmental clean-ups and upgrade expected to materially accelerate China’s environmental clean-ups and to manufacturing structurally upgrade its manufacturing industry. The same policies, if executed inappropriately, may instead leave China’s growth, inflation, and employment at risk.

Rising public concerns over air quality were a main trigger of government actions. In 2014, Beijing had 193 “bad air” days. Public discontent arose as kids were unable to play outdoors, and face masks and air purifiers became must-buys. In 2015, a central government-led crackdown on pollution was first introduced in the 13th Five Year Plan, which called for a change in reporting systems to reduce the ability of local government officials to impede enforcement of environmental measures. Thereafter, policy execution significantly accelerated, with thousands of industrial plant owners being fined and charged for misconduct and local government officials being punished for dereliction. Air quality in major cities also improved modestly, though most cities are still far from reaching the “healthy” standards set by international organizations.

China’s efforts to rationalize overcapacity industries, more importantly alongside synchronized global growth, spurred a mini bull cycle for industrial commodities during 2016-2017. Looking forward, while global commodity demand remains uncertain with a trade war unfolding between the U.S. and China, a supply-side story driven by Beijing’s continued crackdowns on pollution and overcapacity appears increasingly plausible.

As China starts to charge for environmental compliance, global costs are set to rise for manufacturing goods across-the-board before the emergence of a new “world factory”. A shift in China’s energy mix is also underway, allowing China’s demand for imported LNG natural gas to grow over 20% per year during 2018-2020. A collapse of capital expenditure in metals mining, as well as more expensive investment in a green China, have positioned the country as a key raw material importer over the medium term.

Beautiful China, More than Pandas Environmental Protection Hitting Point of No Return

This time is different: Green development for The Chinese government called for the transformation of its economic growth model a beautiful China two decades ago, but it was for a long time more rhetoric than action. Yet, we believe the move has reached the turning point: The government is now serious, perhaps too serious, about cleaning up the environment and greening the economy:

 Strong political will to win the war on pollution: President Xi personally initiated the idea that “green mountains with blue waters are mountains of gold and silver” and launched the “Beautiful China” campaign. The 19th Party Congress elevated environmental protection to an unusually high level. It pledged to solve prominent environmental problems such as air, water, and soil pollution and promote green development via eco-friendly governments, families, schools, and communities.

 Passing the inflection point of the Environmental Kuznets Curve (EKC): The EKC theory and empirics suggest that environmental degradation tends to worsen as modern economic growth takes off, spurred by industrial production, until average income reaches a certain point over the course of development. After four decades of growth, China’s environmental quality is now significantly lower than that implied by its income level (Figure 79).

As China (with GDP per capita of $8,827 in 2017) continues to grow into a high income economy, both the government and the public become more amenable to paying the price for better environmental standards. Environmental cleanup has become an essential focus of the government’s search for high-quality development. The public’s growing environmental awareness also renders green development irreversible. Empirically, China's carbon emissions seem to have already peaked along the EKC (Figure 80). Air quality, as measured by PM2.5 concentration, has also started to improve, at least for the time being, after a series of policy initiatives

Figure 79. China’s Environmental Performance Index 2018

Source: Yale University and Citi Research

Figure 80. China’s Carbon Emissions Seem to have Already Peaked Figure 81. China’s Air Quality, as measured by PM2.5 Concentration, Along the Environmental Kuznets Curve has Started to Improve on Recent Policy Efforts

mt CO2 Emissions Per Capita: 1978-2014 120 (days) Heavily Polluted (>200 µg/m3) 8 102 Polluted (100-200 µg/m3) 100 98 7 89 89 90 79 6 80 77 5 61 60 4 41 41 40 3 40 35 29 28 29 24 2 22 20 18 1 4 1 0 0 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 2009 2010 2011 2012 2013 2014 2015 2016 2017 8M GDP per capita in 2010 US$ 2018 Source: World Bank and Citi Research Source: MEE and Citi Research

Moreover, the government has started to match its words with actions in the environmental campaign. Over and above high-level guidance, the government has set very specific trackable targets on environmental development in the 13th Five- Year Plan (2016-2020; 5YP) (Figure 82). In August 2017, the government issued its “Beijing-Tianjin-Hebei Autumn and Winter Air Pollution Control Action Plan 2017- 18”, embarking on a campaign to combat air pollution via aggressive industrial production cuts. The State Council further announced a “Three-year Action Plan for Winning the Blue Sky Defense War” with detailed targets and measures in Jun 2018. The government has also introduced new regulations on water and soil pollution. Further, the enforcement of environmental policy has become quite effective due to changing political incentives. The government first upgraded and further empowered the environmental ministry in the recent reshuffling. As in the hard-hitting anti-corruption campaign, the Ministry of Ecology and Environment (MEE) started to send ministerial-level inspection teams to provinces in 2016. The four rounds of initial inspections and the recent round of “look-back” inspections have led to ~1,800 arrests and held ~22,000 people (including local officials, business owners) accountable for environmental damage (Figure 83).

Figure 82. China has Set Trackable Environmental Targets in the 13th Five-Year Plan (2016-2020) 12th Plan Actual 13th Plan Target Reduction in energy consumption per unit of GDP 18.2% 15% Non-fossil energy (% of primary energy consumption) 12% 15% Reduction in CO2 emissions per unit of GDP 20% 18% Reduction in pollutant emissions: Chemical oxygen demand 12.9% 10% Reduction in pollutant emissions: Ammonia nitrogen 13% 15% Reduction in pollutant emissions: Sulfur dioxide 18% 10% Reduction in pollutant emissions: Nitrogen oxide 18.6% 15% Days of good+ air quality in cities at the prefectural+ level (% of year) 76.7% >80% Reduction in PM2.5 intensity in prefectural+ cities missing the target 18% Surface water quality: Grade III or better 66% >70% Surface water quality: Worse than Grade V 9.7% <5% Forest coverage 21.66% 23.04% 3 3

Forest growing stock 15.1bn m 16.5bn m Note: The targets are set for the level by 2020 or for the cumulative change from 2016 to 2020. Source: State Council, Citi Research

Figure 83. China’s Environmental Inspections Have Led to ~1,800 and Held ~22,000 People Accountable for Environmental Damages

Source: MEE, Citi Research

What Does Environmental Protection Mean for China?

We see limited impact of the production cuts Despite uncertainties on the size and timing of production cuts as well as whether on economic growth this winter. more cities will volunteer to cut, it is very clear that the extra production reduction over the output loss materialized last winter should be modest. Even in the worst case, as our commodity strategists analyze, the increase in output loss could be material in aluminum and alumina but not so much in steel and coke. Taking the maximum possible output losses, we estimate that the supply cuts could lower China’s quarterly industrial production up to 0.3ppt and slow its GDP growth by up to 0.1ppt in the fourth quarter of 2018 and first quarter of 2019. Thus, the impact on the full year GDP growth is not very visible.

The supply cuts may be inflationary, but the marginal impact should be minimal this winter. The additional cuts are possibly smaller in size this year, and markets have fairly well anticipated the cuts (with purchases front-end loaded). Instead, demand- side factors might play a larger role in determining the prices of industrial commodities and the broad producer price index (PPI) ahead. As the government moves to stabilize domestic demand and public/private partnership (PPP) investment recovers, we expected that infrastructure investment growth could rebound to around 10% year-on-year toward the year-end, while property investment may remain resilient at 7% year-on-year.

We still expect PPI inflation to moderate in our base case. Meanwhile, we would mainly watch out for potential upside risks. In addition to the supply shocks (industrial production cuts, hog down-cycle reversal, etc.), China has all the macro conditions for inflation to take off: loose monetary policy, expansionary fiscal policy, weak RMB, and import tariff increases. In particular, if expectations were to drive inflation significantly higher and before the policy stimuli boost activities, the economic backdrop would appear like a “stagflation” scenario. Such risks would limit the domestic policy room to counter external trade pressures.

Over the medium term, we believe the environmental strategy will shape China’s economic structures profoundly in various ways:

 Structural upgrading: The government will likely stringently restrict capacity expansion in traditional materials sectors. The market should also discourage capital expenditure investment in sensitive sectors via improved pricing of potential environmental risks. Instead, eco-friendly sectors like advanced manufacturing and modern services, as well as the environmental industry itself, are set to attract more policy support and financial resources. Fixed asset investment (FAI) in ferrous and nonferrous metals and coal mining has all seen negative growth since 2015, while FAI in environmental management has grown above 20% year-on-year for five years in a row (Figure 8).

 Sector consolidation: The lower tolerance of pollution should lead to shutdowns of non-compliant or illegal small-scale factories. The resultant factory inflation and profit boost benefit the survivor players, which tend to be bigger and cleaner. Merging state-owned enterprises SOEs further adds to sector consolidation. Due to the supply-side reform and the anti-pollution drive, the concentration ratio (CR10 or the market share of the 10 largest firms) has increased from 34.2% in 2015 to 36.9% in 2017 in the steel sector and from 49.3% in 2014 to 53.4% in 2016 in the cement sector.

 Cleaner energy structure: Much of China’s pollution is a result of heavy coal use, which still accounts for 60.4% of total energy consumption as of 2017. The government has set binding targets on energy intensity and carbon intensity and pledged to increase consumption from natural gas and non-fossil fuels sources. We expect to see more construction of hydropower and nuclear projects, steady development of wind and solar energy, and better control of new coal production, by giving prominence to more efficient and clean coal facilities. In particular, given the rapid coal-to-gas switching and the resultant domestic natural gas shortage, China has become one of the largest importers of natural gas via LNG and pipeline purchases.

 Cleaner transport structure: China has become the world’s largest auto market since 2009. Its freight traffic also dominantly depends on road networks (76.8% in 2017), much more than on railway (7.7%) and water (13.9%). China will move to contain pollutant emissions from new motor vehicles, a major source of air pollution. On the one hand, for road transport, China may shift to China VI emission standard sooner than expected (to be applied in Beijing, Tianjin, Hebei, Hunan, and Shandong in January 2019) and continue its green overhaul to address issues like overloading and dust-raising. As a matter of industrial policy, electric vehicles (EVs) will continue to grow rapidly, despite the gradual withdrawal of subsidies and the introduction of new regulations. On the other hand, for transportation changes, the government calls for shifting freight from roads to rail and waterway networks. In addition to high-speed rail, China is set to expand its investment to raise its rail freight capacity.

Overall, we think investment opportunities lie in the structural changes brought by environmental protection: (1) growth of eco-friendly advanced manufacturing and modern services; (2) consolidation of traditional materials sectors; (3) investment in clean energy and renewables; (4) expansion of natural gas production and imports; (5) favoring cleaner vehicles; and (6) development of rail freight.

Sustainable Tech: Good and Green Growth is the New Normal Amit Harchandani ESG Interest has grown significantly, and asset under management (AUM) Head of EMEA Technology Research dynamics / fund flows reflect the same. Specific to Technology, we see sustainability credentials being increasingly viewed as an additional material aspect of the investment case by both investors and corporates. Citi's approach to ESG consists of 3 key elements — thematic analysis and the Citi GPS series, ESG quant integration and ESG integration in sector and stock analysis.

Figure 84. Sustainability for the Global Tech Sector, E vs. S vs. G Figure 85. Sustainability for the Global Tech Sector: Most Material SDGs Global

26% 23%

Environmental Social Governance

51%

Source: Citi Research Source: United Nations, Citi Research

 ESG Interest has grown significantly: Interest in Environment, Social and Governance (ESG) investing has grown significantly over the past 10 years, although it has been flagged under various guises historically, such as Ethical Investing, Sustainable Responsible Investing, and Green investing. Much of the principle concepts remain the same in that ESG aims to offer a portfolio umbrella class to cater for a growing investor base looking beyond pure financial considerations but also inclusive of one or more aspects of social, environmental, and governance qualities of firms in their investment universe.

 AUM dynamics / fund flows reflect the same: Asset managers are increasingly adopting UN Principles for Responsible Investing (PRI) to align their practices with broader objectives defined by the UN's 17 sustainable development goals (SDGs). The 2000 or so asset manager signatories to the UN PRI now represent AUM of some $90 trillion — admittedly not all of that will be ESG screened or managed. According to investor flows tracking firm EPFR, global ESG fund assets have grown rapidly over the past decade, from $20 billion to over $200 billion. The split among ESG funds is also interesting: most of the money is actively managed, although there is a significant passive component as well.

Figure 86. UN PRI Signatories and AUM Growth (2006-2018) Figure 87. ESG Funds, By Type ($bn, AUM)

100 2500 120 90 Assets under management (US$ trillion) EM Funds DM Funds 100 80 Number of Signatories (rhs) 2000 70 80 60 1500 50 60 40 1000 40 30 20 500 20 10 0 0 0 Active Country Active Passive Passive

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Regional Country Regional

Source: UN PRI, Citi Research Source: EPFT

 ESG wave has also reached Tech shores: Over the past year, we observe several long-term Tech Investors increasingly looking to ascertain in greater detail not just what the key drivers of growth are, but also how that growth is being delivered. Even in the hedge fund community, we have had sporadic discussions wherein we sense investors are evaluating risks from sustainability / governance factors as opposed to just fundamental reasons. And we see corporates too responding to this change – to illustrate the point, we provide two examples: (1) At ASML’s recent CMD (Nov 8, 2018), CEO Peter Wennink outlined the most relevant SDGs and the firm’s 2025 ambitions for the same as part of his presentation, and (2) At Capgemini’s recent CMD (Oct 30, 2018), there was a dedicated presentation on the topic of CSR wherein management outlined its focus on diversity, digital inclusion and environmental sustainability.

Figure 88. ASML’s SDGs Outlined at 2018 CMD Figure 89. Capgemini CSR Ambition Outlined at 2018 CMD

Source: Company Data, Citi Research Source: Company Data, Citi Research

Tech Sustainability Topics: Governance Top

We combine qualitative insights from 14 region / sub-sector teams to arrive at a list of 10 broad sustainability topics for the sector worldwide. Below we summarize the thoughts of the global tech team on each of these topics.

Figure 90. Sustainability for the Global Tech Sector: Most Material Topics

25%

20%

15%

10%

0% Responsible Consumption & Production Clean Energy Pollution & Waste Management Innovation & Industrialization Employee Welfare & Education Stronger & Sustainable Society Diversity Data Privacy & Protection Business Ethics & Governance Structures Intellectual Property Rights (IPR) & Protection

Source: Citi Research

 Business Ethics & Governance Structures: Business Ethics & Governance Structures represents the most material sustainability topic facing tech firms worldwide today; 12 out of the 14 teams highlighting issues associated with it. In the U.S., we note the increased emphasis on adherence to code of conduct on the back of recent dismissals of CEOs of Intel and Texas Instruments for violations. Meanwhile, Citi's U.S. Software team highlights the importance of financial disclosure, in light of multi-year transitions to cloud-based service delivery models, coupled with adoption of new accounting standards. Finally, in Asia, the team highlights management succession (given the presence of founder-run and family-owned enterprises), along with implementation / adherence of stewardship codes.

 Data Privacy & Protection: While this is already one of the more material topics for the sector, we see its materiality only rising with time, and note that it is already at par with governance in the U.S. Citi's U.S. Internet team notes that data and customer privacy have been top priorities for Internet companies, exacerbated by recent events, including the Facebook & Cambridge Analytica scandal. Meanwhile, under the newly enacted General Data Protection Regulation (GDPR) rules in the European Union, data hacks and breaches can inflict significant monetary fines. For Payments firms, there has been increased focus in areas such as data encryption, customer consent management, and data-sharing.

 Employee Welfare & Education: This in our view represents two broad aspects — the education / talent management aspect which is more unique to the tech industry in our view, given the rapid shifts and emergence of new paradigms, and the labor welfare / human rights aspect which should be a key consideration across all sectors. Specific to talent management, the teams highlight measures needed not only to manage existing employees, but also make investments to support STEM-based education. Meanwhile, labor welfare is seen as more material for firms across Asia — teams highlight programs launched by Apple to help improve the health awareness for women working throughout its supply chain in India and China, while in Korea — Samsung has finally formed its first labor union.

 Stronger & Sustainable Society: Tech corporates (like most others) have a moral responsibility towards helping create stronger and sustainable societies. And in this context, we particularly highlight the role of FinTech firms that are emerging as critical enablers of the financial inclusion of the underbanked, thereby contributing towards reducing inequality in society. Various teams also emphasize the need for corporates to engage with and give back to local communities.

 Innovation & Industrialization: Innovation in our view is the lifeblood of the technology sector. Our EU team sees this as encompassing both internal innovation as well as that across the supply chain. Colleagues in Asia point to innovation as a sustainability topic not only in terms of new products but also product quality and industrialization. Meanwhile, our U.S. IT Services and Internet analysts highlight the need for companies to better manage the wider social impact of innovation, particularly given the continued adoption of automation and artificial intelligence.

 Responsible Consumption & Production: This topic is primarily associated with hardware firms, but in our view is increasingly relevant for software ones too. Our U.S. Hardware team highlights that in 2017, Apple announced "closed-loop supply chain" to make products using recycled and renewable materials only. Meanwhile, our U.S. Semiconductors team flags the semiconductor manufacturing uses a variety of potential conflict materials, and Intel has taken the lead here with its products having been conflict-free since 2014. In this context, our team in Japan notes that electronics firms support one or more global standards (ISO26000, JIS, etc.).

 Clean Energy: Against a backdrop of global warming, we see clean energy as a material sustainability topic for Tech firms, not only from the perspective of own usage, but also as enablers of renewable/reusable energy. In fact, teams across Asia flag clean energy as a sustainability topic at par with responsible consumption and employee welfare. Our team in Taiwan notes that with the upcoming 3nm fab, TSMC’s total power consumption could add up to over 3,000kW, or 10% of Taiwan’s electricity supply. Clean energy is also relevant in case of software/Internet firms given the rise of cloud computing. The environmental impact has been top of mind for many of these companies, with Alphabet achieving its 100% renewable energy goal for global operations in 2017, while Amazon Web Services (AWS) continues to progress towards this same goal (AWS at 50% renewable energy use in January 2018).

 Diversity: Corporates across sectors are increasingly focusing on developing a more inclusive workforce and ensuring equal opportunities for all employees regardless of their gender, ethnicity and nationality, and Tech is no exception. In the U.S., we see a particular emphasis on gender equality, and increasing female representation.

 Intellectual Property Rights (IPR) & Protection: We see an interesting divergence of opinion around this topic with a couple of teams (Taiwan, Korea) seeing it as very material, with some others not even flagging it. Digging further, we see that materiality stems from the recent issue involving FICC in China — note that the U.S. Justice Department unveiled an indictment against FICC and UMC indicating they conspired to steal trade secrets from Micron for its R&D and memory storage devices. According to the Korean National Intelligence Service, there have been 40 instances of illegal trade secret transfers of “key national technology” over the last two years, 70% of which were to China. In the U.S., our software team notes that IP lawsuits are some of most cited risks for companies. We suspect, similar to data privacy, this topic will become a more material and prevalent sustainability topic for tech firms over time.

 Pollution & Waste Management: This is the last topic we call out. While some would argue that pollution could be viewed under the broader definition of 'responsible production', we highlight it as a separate topic as we believe its importance merits the same. Like data privacy and IPR, we believe that waste management (both during production and after consumption) will become a more material sustainability topic for tech firms over time.

Quantitative Analysis: Momentum Matters

Technology firms are primarily growth orientated and as we’ve previously observed, growth is not a feature necessarily associated with highly rated ESG firms. Therefore, the question we attempt to address is whether an option exists to benefit from the growth aspects embedded in technology firms while combining this with the merits of ethnical investing.

We conclude that while long-term performance of investing in top rated ESG tech firms was less than convincing, strategies that focused on improving ratings (momentum strategies) demonstrated outperformance in most cases. Governance momentum strategy in particular stood out with strong outperformance, validating the qualitative thoughts of the tech team outlined in the earlier section

Figure 91. Long-Term Performance: Best (Top Quintile) Tech ESG vs. Figure 92. Long-Term Performance: Tech Firms with Improving E, S, G Worst (Bottom Quintile) Tech ESG vs. Tech Index and Overall ESG Ratings vs. Tech Index 600 600 ESG Worst 500 500 Social Best Governance 400 400 MSCI ACWI IT Environment 300 300 Benchmark

200 200

100 100

0 0 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Sep-16 Sep-17 Sep-18 Sep-09 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Sep-16 Sep-17 Sep-18 Source: MSCI, Sustainalytics, Citi Research Source: MSCI, Sustainalytics, Citi Research

From a risk premia perspective we observe that firms with higher ESG ratings are generally larger, less growth orientated, and slightly cheaper relative to their lower rated peers. The figures below highlight this relationship by comparing the median quintile portfolio scores of our style factors each year for firms within the MSCI ACWI IT universe. For much of the time, the relationship across portfolios appears fairly stable and consistent.

 Empirical performance of Tech ESG Leaders / Highly Rated Firms: Given the lower growth scores of higher rated tech firms, it doesn’t come as a surprise to find that long term performance of investing in top rated ESG tech firms was less than convincing, we would argue that these higher rated firms are more likely to be those which are more mature and have already surpassed their initial growth phase and are lagging behind their peers.

 Empirical performance ESG Momentum: As opposed to using ESG ratings we focused on a strategy that invested in firms with improving ESG ratings, the results from our ESG Edge research publications had highlighted financial outperformance relative to the market once sector and country specific issues were addressed. Within the technology sector similar results were obtained even when country neutralization was removed. We found outperformance in most momentum strategies, with the Governance momentum strategy standing out. Over the past 8 years, a systematic strategy which invested in companies that had made significant improvements in their Governance ratings relative to their peers had an average annualized return of over 20%.

 ESG and Governance Momentum Candidates: Due to the mechanics applied in computing ESG momentum, we would expect firms with lower initial ratings and making positive changes to occur more frequently in the portfolio, however to our surprise this was not the case, it appears that middle tier firms (Quintile 3) firms have historically been the ones exhibiting highest positive momentum scores, these would have been the firms selected for investment by the strategy.

Internet-of-Things (IoT) and Its Relevance for Smart Cities Arthur Pineda The concept of smart cities where technology, connectivity, and services are used Co-Head of Pain Asian Telecommunications extensively to improve the quality of life for its residents and raise efficiencies for Research enterprises is spreading globally. Broadly speaking, the discussion and focus points on smart cities often address five main areas: (1) Transport/Mobility; (2) Health & Living; (3) Security & Safety; (4) Environment; and (5) Services. Solutions and policies are then built around the needs of these five areas.

Figure 93. Smart City Focus Areas

Source: Citi Research

How are the objectives of a better quality of life by addressing the five focus areas achieved? The common framework is the utilization of technologies, connected via networks and empowered and made efficient by the use of data to make life better and more efficient for the residents as well as the environment.

Figure 94. Levers & Components to the Smart City Benefits

Source: Citi Research

IoT Growth Potential for Smart Cities

The Internet of Things (IoT) is the concept of having a multitude of devices connected and talking to each other in order to deliver efficiencies or a service. The concept of IoT spans across multiple sectors and types of devices. Connected devices would expand exponentially beyond traditional phones and PCs/tablets to include, among others, consumer wearables, smart meters, appliances, vehicles, cameras, sensors, trackers, and likely many more. Based on Cisco estimates for instance, IoT devices will exceed 50 billion devices by 2020 whereas GSMA is forecasting a more conservative~25 billion IoT devices by 2025. Considering that there are only 5.9 billion mobile users globally as of end-2017, the potential subscription and revenue opportunities for IoT is massive and arguably yet to be fully imputed into street estimates

Figure 95. IoT Endpoint Unit Shipments by Category – Annual Sales to More than Double From 3 Billion Units in 2017 to Nearly 7 Billion Units by 2020

Source: Gartner, Citi Research

The use and proliferation of such IoT devices will be critical to any smart city roll-out as these devices will drive the multiple touch points which can be analyzed, processed, and drive the efficiencies in the various areas. Improving efficiency and reducing cost/wastage for instance can be achieved with examples for the following five common area focus points for smart cities: (1) Transport/Mobility (2) Health/Living (3) Environment (4) Public Safety (5) Government and private services.

Smart Transport and Mobility

Smart transport in a smart city extends beyond the often discussed autonomous and electric vehicles. IoT opportunities on transport extend to land, sea and air transport and goes well beyond what is visible on the consumer level. We divide the smart transport opportunities into five segments: Cars, Mass transit, Maritime, Traffic Management, and Aircraft. All of these segments can utilize IoT to some degree in order to drive efficiencies to meet their objectives.

Figure 96. Smart Transport Opportunities with IoT

Source: Citi Research

 Autonomous vehicles will emerge and this will raise connectivity needs to a higher level: Vehicles embedded with connectivity mainly for infotainment and telematics services have already commercialized. Tech and car companies are looking beyond to produce fully autonomous vehicles over the next four years (2020-21). This should gain considerable scale over time with favorable economics of autonomous vehicles as a service which grants greater conveniences and flexibility to the riding public. As autonomous vehicles gain more scale, market efficiencies could increase with the concept of a scalable asset across multiple users. The need for greater connectivity also increases dramatically.

 Traffic management and smart transit systems: Smart traffic systems are being formulated, harnessing array of technologies such as IoT, data analytics, and artificial intelligence. Systems are aimed towards increasing traffic efficiency through live traffic predictions and smart traffic lighting. On top of these, smart systems can help in dynamic pricing which not only tracks and bills users based on the distance traveled, but also bills the user differently based on peak/non- peak road use, helping influence demand. IoT systems are expanding in the mass transit systems as well allowing for real-time tracking of buses/trains.

 Aircraft and Maritime IoT: Airlines themselves are increasingly connected with more plans offering WiFi services and wireless-based entertainment systems. Unmanned aerial vehicles/drones can also be used more frequently in the future. Surveillance drones for security and monitoring purposes are also being developed. IoT can extend into shipping and the related supply chain industry. Container ship monitoring for instance can be enhanced with connected containers. These connected containers can then potentially seamlessly integrate with the local networks upon arrival, allowing for seamless point-to-point cargo tracking.

Smart Healthcare & Living

Healthcare is becoming increasingly expensive, with global health care spending already hitting $7.2 trillion in 2015 or 10% of global GDP. Healthcare thus occupies a position of importance in various smart cities/nation initiatives. Technology innovation will be important in helping to deliver holistic health and elder care to an aging population powered by digital technologies such as IoT, mobility, cloud, data analytics, artificial intelligence (AI) to improve continuity of care, as well as encourage active lifestyles and good living. Leveraging technology in creating smart healthcare can materially help to reduce healthcare costs for governments as well as insurers.

Figure 97. Healthcare KPIs, Inhibitors, and IoT Solutions

Source: TCS, Citi Research

Contextualizing Healthcare in a Smart City

 Remote monitoring: Remote monitoring enables doctors to consult and review real-time patient data, reducing emergency admissions and the number of home visits and appointments needed. Patients are empowered to get on with their lives while clinicians can see more patients each day and quickly involve colleagues around the world to consult on challenging cases. Users could be fitted with connected devices and wearables. Implanted pacemakers or wearables such an ECG-capable smartwatch for instance are able to identify potential problem points and direct users to timely assistance.

 Independent living: Smart homes, which incorporate environmental and wearable medical sensors, actuators, and modern communication, and information technologies can enable continuous and remote monitoring of elderly health and wellbeing at a low cost. For example, IoT-powered assisted living solutions bridge the gap transforming services to enable people to live independently in and out of their homes for longer with more peace of mind while reducing costs in end-to-end patient solutions. Patients can be fitted with wearables and areas can be scanned with sensors to ensure patient safety. Predictive analytics aggregate and analyze activity data trends and, when changes in patterns occur, generate actionable insights.

 Clinical trials: Clinical trials are an essential but costly component of drug development. It typically takes pharmaceutical companies ~17 years to get from basic science to clinical product. Technologies such as wearables and biosensors enable real-time clinical trial monitoring and facilitate data-sharing between research groups, clinicians, pharmaceutical companies and clinical research organizations, and the patients themselves. Using analytic feedback that is captured from web-connected medical devices and aggregated clinical results, scientist can create shorter, more effective trials, with results that are valuable and useful to a wide range of stakeholders. As methods of data collection and analysis become more sophisticated, clinical trial sponsors stand to make unprecedented progress when conducting a trial.

Environment and Utilities

Some 4 billion people, representing 54% of the global population currently live in cities; the UN expects this to grow by 1 billion by 2030, and 2 billion by 2050, by which time 66% of us will be living in cities. The effective implementation of smart cities requires an integrated and interdisciplinary approach to sustainable development to ensure a low carbon, low water, and low ecological footprint. A smart city facilitates this by leveraging sensor technology, behavioral economics, and gamification to alter not only physical infrastructure, but to encourage resourcing decisions.

 Smart metering and responsive devices: Powered by sensors and connectivity, smart electricity meters can record consumption in regular intervals and communicate this data to the utility company. This allows utilities to introduce dynamic pricing for instance time of the day and encourages citizens of smart cities to reduce/manage their energy consumption, especially when demand is at peak level.

 Smart electricity grid: Electric utilities are adding IoT technologies such as sensors and automated controls and connection devices. Smart grid integrates sensing, communication, and control technologies with field devices in distribution systems to improve reliability and efficiency. The software monitors distribution system data in real time to automatically locate and isolate faults to reduce outages, and dynamically optimize voltage to reduce transmission losses, with limited human intervention. The grid can “heal” itself through a combination of automated switching, dispatch of distributed energy resources, coordinated demand response and management without intervention by operators in the control room.

Figure 98. Smart Grid Technology

Source: ONCOR, Citi Research

 Smart water management: IoT technologies can be embedded in the water network structures to make it efficient and reduce costs. A grid-based water meter system which monitors the pipeline network in real time allows it to rapidly identify pipeline failures to enable leakage analysis and action. Automatic meter reading can help to reduce user complaints and improve service quality. Data related to water, such as quality, pressure, and temperature, can be managed elaborately and visually to enhance the capabilities of water utilities.

 Smart waste management: The use of sensors that monitor the status of waste bins and transmitting this data to an application server will allow efficient route planning in the collection of waste. This data is used to optimize the number of garbage trucks and their routes, skipping containers that are not yet full and making an early stop at containers that are close to reaching their limit.

Public Safety and Security

Public safety initiatives have to serve to optimize the capacity and response time of emergency services, secure and control mass events, secure public administration transactions and work flow, and provide surveillance of public places. IoT can help cities meet their public safety goals by offering the following features:

 Real-time monitoring: Using microphones, videos, sensors, and other connected devices strategically placed throughout the city, police can readily identify when and where crime is occurring, so that they can successfully track down perpetrators as well as create deterrents. Facial recognition software for instance can be integrated to the video surveillance platforms allowing for enhanced safety.

 Crowdsourcing and emergency apps: IoT can combine massive quantities of relevant data from multiple sources and analyze it in real-time, allowing cities to quickly take action to keep citizens safe. For instance, citizens can access apps that allow them to send an alert or request assistance during emergency situations. The app can automatically detect the person’s location and could trigger audio or video recordings to better track the situation on the ground. The app notifies the nearest safety guards, police officers or stations, and/or medical personnel to provide immediate assistance.

 Predictive policing: IoT solutions also allow cities to take advantage of real-time analytics, which can help them to understand and resolve public safety issues right away – before residents are affected. For example, predictive policing uses a blend of sensors and connected devices to identify potential areas or events of crime before they occur. These insights can be used to focus police officers patrols to areas with high likelihoods of crime.

Public and Private Services

Smart governance widely represents a collection of technologies, people, policies, practices, resources, social norms and information that interact to optimize governance and public services. This in itself may not have to depend on IoT but rather on broader applications and service layers. Online or open governance through IT systems (e-Government) for instance is a big component of smart governance and thus it may be difficult to envisage relevance of sensors and connected appliances to improve governance, but deriving value from information collection and analysis is central to many government missions. The creation of a centralized database for instance would allow multiple government and private agencies to share data, allowing for expedited and more accurate data recall.

Figure 99. Centralized Information Platforms such as MyInfo in Singapore Creates Efficiencies in Data Collection and Processing Across Institutions

Source: Citi Research

Private services can also be optimized with the move towards digitization. Streamlining the financial services sector for instance with the move towards a more efficient, cashless system not only lowers costs for institutions but also greatly enhances convenience for the residents/users with reduced handling and manpower costs. Objectives such as broader financial inclusion for the lower income segments can be met for example with a government supported push towards mobile wallet systems which effectively reduce handling charges. Businesses also benefit from move to digital currency as cash is inefficient. Digitizing cash flow allow for smaller and more frequent transactions with lower cost. This allows companies and financial institutions to reduce frictional fees which could allow for better profits. This also allows for potentially greater convenience and savings on the consumer level.

The Rise of Subscription Video on Demand (SVOD) Platforms Jason B Bazinet Netflix’s streaming video service launched about 12 years ago. For most of that U.S. Entertainment, Cable & Satellite time, traditional media firms didn’t view Netflix as an existential threat to the pay TV Analyst ecosystem. But beginning in 2015 – about 8 years after Netflix streaming launched – incumbent media firms began to wake up to true nature of the threat. As a result, Mark May Netflix spawned M&A – like AT&T / Time Warner or Discovery / Scripps – and U.S. Internet Analyst caused some radical strategic pivots among some media firms into the direct-to- consumer (DTC) market. But, over time, we expect all media firms to pivot to web- based delivery.

The rub, however, is this: today, most media firms can’t profitably make the pivot. The legacy business model is just too lucrative. In effect, it’s better to harvest than pivot. But, as more ads flow to the web and more consumers terminate their pay TV subscription, media incumbents will eventually find the transition to the new (less profitable) SVOD model, well, palatable.

For investors, however, there is a central question: “How many subscribers (subs) can a new SVOD service attract”? To help answer that question, we looked at five years of history among three SVOD services (Netflix, Amazon, and Hulu) and two premium channels (HBO and Showtime).

To be sure, the historical data are fraught with challenges. Here are seven of the most important vagaries:

 Subscribers: Netflix is a global SVOD player. However, Hulu is only available in the U.S. HBO is primarily a U.S. service, but the content is licensed overseas (to Sky, for example). Showtime is available in the U.S. and Canada. For our purposes, we’ve used Netflix’s global subs but used U.S. subs for all other services because these rival services are very U.S.-centric. (We excluded Eros Now from our analysis because it has a unique B2B2C acquisition model, making comparisons to traditional B2C business models challenging.)

 Average Revenue per User (ARPU): Most SVOD or premium channels charge an explicit fee. But, Amazon’s video service is free for Prime members. For our regressions, we apply 100% of the Prime fee to the video service. For premium channels, we use the retail ARPU (versus the reported wholesale ARPU) to harmonize the data with Netflix and Hulu.

 Distribution: Premium channels (HBO and Showtime) are primarily sold through pay TV firms. And, the pay TV firms are typically allotted (during carriage negotiations with the content owner) a specific number of units to give away as a pay TV retention tool. As such, premium channel sub counts are usually not indicative of true sub counts. To account for this, we have created a dummy variable to isolate ‘free’ premium subs from paying premium subs.

 Content Duration: When cash is spent on content, it can stay on the server indefinitely (originals) or for limited periods (licensed). Moreover, the utility of content that’s on the server — for both originals and licensed shows — likely diminishes over time. As such, it is unclear how to compare historical content spend to current subscriber figures. To account for this, we ran three regressions (five year, three year, and one year historical content spending). And, we cross checked the data with longitudinal data from Netflix by comparing sequential changes in content spend to sequential changes in subs.

 Content Utility: Clearly, not all content is created equal. We have made no quantitative adjustment for the type or quality of content that is produced or licensed. In effect, a $100 of content spending is treated as a fungible asset both within and across platforms.

 Content Spending: Given its scale, Netflix’s content spend plays a meaningful role in our analysis. And, two specific factors could skew our analysis: (1) In recent years, Netflix has tilted toward originals (including self-produced originals). These typically require greater upfront investment than licensed content; and (2) More recently, Netflix has increased spending on localized content as it expands into new markets. This new (localized) spending may be less efficient than outlays in more established markets (like the U.S.). As a result, our regressions may imply less efficient content spending than is likely to ultimately occur in a mature, steady-state market.

 Content Disclosures: Some firms (Netflix) disclose content spending. Other firms (Hulu, Amazon) do not. And some firms give the cash outlay and the amortized P&L impact (Netflix). Other firms only disclose the amortization figure (HBO). We have used our best estimates to harmonize this data based on our company models or press reports when actual data isn’t available.

Those seven complexities aren’t trivial. As such, one might expect that the historical data isn’t useful. However, after running many regressions, we actually have some good news. The historical data we’ll review is actually statistically significant. And, it suggests a few things:

 First, it takes $140 of content spending per year to attract (and retain) a SVOD subscriber.

 Second, firms that use pay TV platforms to sell their service typically enjoy a 20 to 30 million lift to their U.S. subscriber count. This, in turn, suggests that pay TV firms may have a future role selling SVOD services (while keeping a portion of the retail ARPU).

 Third, SVOD content spending has been rising faster than subscriber growth over the past five years.

 Fourth, current SVOD (and premium channel) ARPUs are very close to the content spend required to acquire (and retain) a subscriber. As such, ARPUs will need to rise significantly to make this new video business sustainable.

With that, let’s dig into the details.

SVOD Platforms See Rapid Growth

If we include traditional premium networks — like HBO or Showtime — there are five main subscription video-on-demand (SVOD) services. Collectively, they have nearly 300 million users. And, these platforms have grown subs at ~20% per year since 2014.

Figure 100. Subscription VOD Subscribers (millions; percent)

CAGR 2014 2015 2016 2017 2018% '14 to '18E Netflix 57.4 75.0 93.8 117.6 146.4 26% + HBO 46.2 48.8 49.0 53.8 56.3 5% + Showtime 19.5 20.5 215.0 22.5 23.2 4% + Hulu 5.0 11.0 14.0 17.0 23.0 46% + Amazon 15.0 17.5 22.0 30.0 38.0 26% = Total 143.1 172.8 200.3 240.9 286.9 19% Source: Company reports, Citi Research

The robust growth has been fueled, in part, by larger outlays on content spending. Indeed, among these five platforms, content spending has grown from less than $8 billion in 2014 to nearly $24 billion by 2018. Indeed content spending has grown at over 30% per year (far faster than subscriber growth).

Figure 101. Content Outlays for SVOD Services ($ millions, percent)

CAGR 2014 2015 2016 2017 2018% '14 to '18E Netflix 3,773 5,745 8,653 9,806 13,152 37% + HBO 1,967 2,035 2,175 2,213 2,346 5% + Showtime 917 908 808 1,103 983 2% + Hulu 750 1,250 1,750 2,500 3,000 41% + Amazon 500 1,500 2,500 3,500 4,500 73% = Total 7,907 11,438 15,886 19,122 23,981 32% Source: Company reports, Citi Research

The other driver behind robust growth is the relatively low ARPUs for these services. Indeed, they typically cost around $11 per month. HBO has the highest retail price point ($15) and Amazon has the lower price point (which is free for Amazon Prime customers).

Figure 102. ARPU of SVOD Offerings ($ per month per sub) 2018 ARPU Comments Netflix 10.99 Standard package HBO 14.99 Retail ARPU Showtime 10.99 Retail ARPU Hulu 11.99 No commercials Amazon 8.25 Free for Amazon Prime Members Source: Company reports Citi Research

The key question we want to answer is this: “Can we predict SVOD subscriber growth?” We would like to base the regression on a few key variables: (1) content spend; (2) price point; and (3) whether the service is sold directly to customers (like Netflix or Hulu) or primarily uses a pay TV distribution intermediary (like HBO or Showtime)?

Testing Four Regressions

We ran a handful of regressions to see if we could predict subscriber growth for SVOD platforms. We began with a few hypotheses:

– First, SVOD firms that spend more on content will experience faster subscriber growth.

– Second, SVOD firms that charge less for the service will experience faster subscriber growth.

– Third, firms that use third-party distributors — like cable, telecom, or direct broadcast satellite (DBS) —- will experience faster subscriber growth. (In part, this is because distributors often give HBO or Showtime away for free as a tool to retain video customers.)

What is a little unclear, however, is what time horizon we should use for content spending. That is, spending on originals can remain on the service indefinitely (but may have lower utility once the content is viewed by users). Conversely, content that is acquired from third parties will not remain on the platform indefinitely.

As such, we regressed content spending three ways: (1) over the last five years; (2) over the last three years; and (3) over the last year.

Since the quality of the regression inputs is particularly accurate for Netflix, we performed a final (fourth) regression using just Netflix data. This regression is longitudinal. That is, we regressed net additions in a given year versus the incremental change in content outlays between 2014 and 2018.

Figure 103. Four SVOD Regressions

Source: Citi Research

So what did the regression outputs suggest? A few important things:

 First, all four regressions had a robust correlation (R2). Indeed, they varied from 0.99 to 0.89. In effect, over 90% of the variance in subscribers is explained by the content spend, the ARPU, and the method of distribution.

 Second, all four regressions had a low p-value for every regression coefficient. The highest p-value was 9.7%. And the lowest p-value was 0.2%. This is good. Recall, a p-value represents the likelihood that the coefficient is not statistically significant. So, a p-value of zero is great. And, a p-value of 1.0 is bad.

 Third, the coefficient for content spend is positive for all four regressions. This is intuitive. It varies from a low of 0.004 to a high of 0.012. Clearly, as firms spend more on content, subscribers increase (via higher gross adds or lower churn).

 Fourth, unfortunately the ARPU coefficient is positive for all regressions. This is counterintuitive. We would expect as firms charge more for the service, subscriber growth should be lower (akin to a negative coefficient).

 Fifth, the regressions suggest that using third party distributors (like cable, telco, or DBS) tends to help subscriber growth. This is intuitive. Said another way, for firms that market directly to consumers, they tend to see a subscriber headwind that varies from 20 million to 31 million (depending on the regression).

Figure 104. Regression Outputs for Cumulative Content Spend (percent; millions of subs)

Regression Regression Regression Regression #1 #2 #3 #4 5 Year 3 Year 1 Year Net Adds vs. Content Content Content Incremental Spend Spend Spend Spend Average R2 0.999 0.998 0.998 0.887 nm

Coefficients; Content spend 0.004 0.005 0.012 0.007 0.007 ARPU 0.776 1.203 1.530 nm nm SVOD or Premium (20) (27) (31) nm nm

P value: Content spend 0.002 0.002 0.003 0.017 nm ARPU 0.097 0.046 0.036 nm nm SVOD or Premium 0.046 0.03 0.031 nm nm Source: Citi Research

We can recast the regression outputs for content spend to make it a bit more intuitive. To capture one million SVOD subs, the regression suggest you need to spend between $80 million and $260 million a year on content. The average of all four regressions is $140 million in annual content outlays.

At some level, this is a shockingly high number. Indeed, it suggests that the ARPU required to generate gross profits is between $7 and $22 per month (with an average ARPU of $12 a month).

Clearly, prevailing SVOD ARPUs are too low. In addition to content outlays, SVOD platforms need to pay for customer acquisition costs, streaming costs, customer care, and billing.

Figure 105. Cumulative Content Spend for One Million Subs (millions, $ millions, $ per month)

Regression Regression Regression Regression #1 #2 #3 #4 5 Year 3 Year 1 Year Net Adds vs. Content Content Content Incremental Spend Spend Spend Spend Average One million SVOD subs 1.0 1.0 1.0 1.0 1.0 / Content spend coefficient 0.004 0.005 0.012 0.007 0.007 = Content spend 259 196 81 135 139

Content spend per year ($ mil) 259 196 81 135 139 / Months 12 12 12 12 12 = Breakeven ARPU ($ per month) 22 16 7 11 12 Source: Company reports, Citi Research

Content Utility Likely Lasts Two Years

Since there is a wide variance in the required content outlays to acquire and retain a million subscribers ($259 million if we use five-year trailing spend versus $81 million if we use one-year trailing spend), let’s unpack this a bit.

If we look at Netflix’s content amortization and compare it to the unamortized content that sits on the balance sheet, it suggests the average life (across originals and licensed content) has increased from about 1.5 years (in 2016) to nearly 2.0 year (in 2018).

Figure 106. Netflix historical Amortization rate ($ millions; number; percent)

2016A 2017A 2018E 2019E Prior period ending content, net 7,193 10,975 14,669 19,914 / Average life 2 2 2 2 / Annualized ratio 1 1 1 1 = Content amortization expense 4,788 6,798 7,568 8,873 memo:% of Total Streaming Revenue 57.8% 55.1% 48.9% 45.5% Source: Company reports, Citi Research

If we take the average of the three-year content spend ($196 per year) and the one- year content spend ($81 per year), the average is two years (consistent with Netflix’s amortization rate). This implies an annual content spend to acquire a sub of $140 a year. It also suggests content has about two years of utility to consumers. Content that is older than two years likely has limited utility for attracting and retaining subs. Parenthetically, these results closely mirror our fourth regression (which use longitudinal date from Netflix).

Figure 107. Content Likely Has Two-Year Utility ($ per year per sub; $ per month per sub)

Annual Monthly Spend Spend Three year look back on content spend to acquire a sub 196 16 + One year look back on content spend to acquire a sub 81 7 = Sub-total 277 23 / Average 2 2 = Implied two year look back at content spend to acquire a sub 139 12 memo: Regression #4 based on longitudinal Netflix data 135 11 Source: Company reports, Citi Research

Spend Required to Acquire (and Retain) a Sub May be Rising

We can perform one last piece of analysis. By taking the five-year trailing content spending and dividing it by five, we get the average annual content spend for the last five years. Similarly, we can do the same for the three-year trailing content spend. (Of course, the one-year training content spend doesn’t need to be adjusted).

Figure 108. Regression Output for Annual Content Spend (percent; millions of subs)

Regression Regression Regression Regression #1 #2 #3 #4 5 Year 3 Year 1 Year Net Adds vs. Content Content Content Incremental Spend Spend Spend Spend Average R2 0.999 0.998 0.998 0.887 nm

Coefficients; Content spend 0.019 0.015 0.012 0.007 0.014 ARPU 0.776 1.203 1.530 nm nm SVOD or Premium (20) (27) (31) nm nm

P value: Content spend 0.002 0.002 0.003 0.017 nm ARPU 0.097 0.046 0.036 nm nm SVOD or Premium 0.046 0.03 0.031 nm nm Source: Company reports, Citi Research

When we recast the figures in terms of content spend per subscriber (or ARPU to generate gross profits), it suggests there is an arm race, of sorts. That is, over the last five years, it took $52 to acquire a sub. But, based on last year’s data, it was closer to $81. In effect, more money needs to be spent to acquire a subscriber. Since content has two years of utility — consistent with the amortization rate of Netflix’s content — these raw figures should be roughly doubled. That is, based on data over the last five years, it took, on average, $102 of content spending to attract a subscriber ($51x2). Based on last year’s data, the required content spend was closer to $162 ($81x2).

Figure 109. Average Annual Content Spend for One Million Subs (millions; $ millions; $ per month)

Regression Regression Regression Regression #1 #2 #3 #4 5 Year 3 Year 1 Year Net Adds vs. Content Content Content Incremental Spend Spend Spend Spend Average One million SVOD subs 1.0 1.0 1.0 1.0 1.0 / Content spend coefficient 0.019 0.015 0.012 0.007 0.014 = Content spend 52 65 81 135 74

Content spend per year ($ mil) 52 65 81 135 74 / Months 12 12 12 12 12 = Breakeven ARPU ($ per month) 4 5 7 11 6 Source: Citi Research

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All Citi GPS reports are available on our website www.citi.com/citigps

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January 2019 Citi GPS: Global Perspectives & Solutions 67

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