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A perfect storm: COVID-19 in emerging economies

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A perfect storm: COVID-19 in emerging economies

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Emerging economies must navigate the COVID-19 pandemic amid collapsing exports, dwindling remittances and tightening international credit conditions that call for austerity. To contain the pandemic, the necessary limits on economic activity fall more heavily on these economies than in the advanced countries. 

Those of us who have been staying at home for several weeks understand the economic costs of universal social distancing policies (Baldwin 2020). Simple back-of-the-envelope calculations tell us that these costs can be substantial (Hevia and Neumeyer 2020). For example, if half of the economy works at one half of its capacity, the loss of output would be 25%. This is consistent with estimates by Leibovici et al. (2020) for the US.1 If restrictions on the labour supply reduce effective hours worked by 30%, the impact on output would be of the order of 20% (Miguel Faria-e-Castro 2020). Data from the US2 reveal that between the week of 8-14 March and the week of 29 March-4 April, the employment rate decreased from 72.7% to 60.7%, implying 24 million jobs lost, and that the unemployment rate increased from 4.5% to 20.2%.  Hours worked per working age adult declined by 25% where half of this decline is due to lower hours per employee as opposed to lower employment. Over 60% of work hours were from home, compared with a total of roughly 10% in 2017-2018. Recent data from the IMF show that most developed countries are expecting severe contractions in employment and GDP in the first half of 2020.

To put things in perspective, the maximum unemployment rate since 1948 in the US was 10.8% in 1982 and the highest value ever recorded was 24.9% in 1933. An optimistic hypothetical exercise is to assume that output is 20% below ‘normal’ for one quarter and then returns to normal for the rest of the year. This scenario yields a year-on-year average growth rate for 2020 of -5%. Such a drop would be twice the size of the largest drop in US GDP since WWII. If the quarter-on-quarter drop in the order of 20-25% persists for more than one quarter, we would be facing a global recession of the proportion of the Great Depression. In 1929, it took three years for GDP to drop by 26.7%. Today we are facing a drop in GDP of this magnitude in one quarter. 

The persistence of social distancing and other mitigation policies, and the uncertainty about their duration have additional indirect effects that amplify the initial economic downturn and may slow the recovery.  These indirect effects include the following:

  • The reshaping of supply chains and new forms of working, telecommuting and a lower scale of operation reduce efficiency. 
  • Rising unemployment implies a slow recovery. We know from previous recessions that after spikes in unemployment, matching workers and vacancies in the recovery is a slow process. 
  • Many firms with little working capital and limited credit lines are likely to go out of business, especially in contact-intensive industries such as travel and entertainment.3 Restarting these businesses may be a long and costly process (Buera et al. 2020).
  • Financial stability is threatened as households and businesses experiencing income shocks may have problems servicing their debts, reducing bank capital. 
  • Aggregate demand may fall beyond the original supply shock. Investment is likely to fall, agents with a stable income will increase their precautionary savings (due to the uncertainty about the pandemics duration) and the demand for goods in ongoing activities may fall due to complementarities with the demand for shut-down goods.4

All these factors that will severely slow down developed economies are also operating, sometimes more strongly, in emerging markets.  Moreover, as we will show below, the typical tools that developed economies will use to fight the recession and to reduce its economic costs will be much less effective in many emerging economies.

In emerging economies, a large share of the labour force is employed in very small firms and workers have a relatively low level of education.5 These features of developing countries increase the direct cost of social distancing because the share of jobs that can be done at home is much smaller (Figure 1). 

Figure 1 Share of jobs that can be done at home, by GDP (PPP) per capita

A perfect storm: COVID-19 in emerging economies 2

Source: Dingel and Neiman (2020).

Many of the above indirect effects occur because some firms and households have less or no income while they still face fixed costs. Firms must cover the cost of labour and capital that they still employ, and households must pay rent, food, health insurance, and so on. Governments face revenue losses and an increased demand for expenditures and transfers. In an economy with perfect insurance this would not happen; agents that generate income would transfer resources to those that transitorily don’t. Each agent’s consumption would be independent of their idiosyncratic income shock and would move with aggregate consumption. 

Of course, there is no perfect insurance, especially against the risk of pandemics. One way of partially achieving this risk-sharing in the absence of perfect insurance is for the interest rate to rise such that agents with revenues have incentives to consume less and lend money to those who lose income.  This is unlikely to happen for two reasons. It is uncertain that borrowers will be willing and able to repay these debts. Potential lenders, uncertain about their future income, may prefer to stay liquid. Governments with fiscal space use the credibility of their future ability to tax to address this problem: the US, Denmark, Perú, and Chile, for example, announced fiscal packages to cushion the effect of social distancing of over 10% of GDP. These programmes transfer resources from future taxpayers to those who lost income. Central banks provide the liquidity demanded by precautionary savers. 

In many emerging economies, sovereign borrowing to smooth the COVID-19 shock is not feasible. To a large extent, this is because they find it more difficult to credibly commit future tax revenues to pay for a fiscal expansion today. The negative correlation between income per capita and the ability to tax (Figure 2) may explain why poor countries have less access to financial markets.  

Figure 2 Government revenue excluding grants and income per capita

A perfect storm: COVID-19 in emerging economies 3

Source: World Development Indicators, The World Bank.

The previous hypotheses are supported by data on portfolio flows. Between 24 February and 30 March, institutional and retail money funds in the US increased their assets by 19%.6 Figure 3 shows how this flight to quality resulted in sudden capital outflows from emerging economies. The speed and magnitude of portfolio outflows from emerging economies signals that it will be very hard for their governments and corporations to issue debt to finance their transitory fall in income due to COVID-19. Credit spreads for selected sovereigns in Latin America tell the same story. 

The IMF and the World Bank have jointly pledged $1,160 billion to help emerging economies deal with COVID-19. This is a staggering number, which corresponds to 4% of the aggregate GDP of low- and middle-income countries. However, assuming that taxes in emerging economies are proportional to income, this valued help is lower than the expected loss of tax revenue due to the recession. 

Figure 3 Portfolio flows to emerging economies Source: IIF daily portfolio tracker

A perfect storm: COVID-19 in emerging economies 4

Emerging economies face additional sources of hardship.  Commodity exporters are facing a sharp drop in the price of their exports. Bloomberg’s index of commodity prices7 fell by 20% since the pandemic broke out in China, mainly driven by oil prices. For many countries, rich and poor, tourism accounts for more than 20% of exports (Figure 4 plots the share of tourism receipts in exports against per capita income). As social distancing and restrictions on international travel remain in place for several quarters, these countries will have to reduce imports or find other sources of foreign currency.  

Figure 4 Per capita income and tourism exports

A perfect storm: COVID-19 in emerging economies 5

Unemployment in advanced economies will reduce immigrant remittances to their home countries.  Figure 5 shows that, for many poor countries, remittances received from abroad account for more than 10% of GDP. Early data from Central American countries indicate that remittances fell by 40% in the latter part of March. Dwindling remittances and social distance restrictions at home may rapidly deplete the recipients’ liquid assets.

Figure 5 Per capita income and remittances

A perfect storm: COVID-19 in emerging economies 6

Policymakers in less developed countries face a very difficult policy dilemma. They have to protect their societies from the pandemic with a weak health infrastructure.8 At the same time, prolonged social distancing policies in economies already hit by large negative global shocks could be devastating,9 and all the more so because they will have a hard time financing the social insurance policies that palliate the cost of social distancing. A policymaker that decides to contain the epidemic must consider that social distancing policies are likely to be with us until herd immunity is attained through a vaccine, probably in a year or a year and a half.

How much consumption should a society forgo to avoid the deaths associated with COVID-19? Economists have developed frameworks to answer this question. Jones et al. (2020) compute the trade-off between the forgone utility of consumption lost due to the increased probability of dying and the utility of current consumption. Their baseline estimate with US parameters is that the cost of letting the epidemic run with no intervention is about 25% of one year’s consumption. The cost of a one-year lockdown in a less developed country is probably higher.10

Targeted social distancing policies that isolate a smaller subset of the population can moderate the economic cost of containing the pandemic. One often proposed targeted intervention strategy is to isolate only persons that are infectious. This has proven elusive even in advanced countries with efficient bureaucracies, high-quality health infrastructure and ample fiscal space. 

Another policy that has been advocated is the targeted isolation of more at risk individuals such as older people (Ray et al. 2020, World Bank 2020). This strategy might be of interest to emerging market economies with a younger population, but it might be challenging to implement in a context where there is extensive cohabitation of multiple generations. 

Concluding remarks

To sum up, the COVID-19 pandemic has the potential to be the largest macroeconomic shock faced by developed and developing economies over the past 100 years. Moreover, it is going to hit certain sectors of the population which are subject to lockdown particularly hard. Many developed economies will be able to mitigate its impact by redistributing resources from safe workers to the hardest hit (Heathcote et al. 2020). However, such policies are unlikely to be available in emerging economies, making the trade-off for policymakers between health and wealth even more pronounced.     

Given this, it is of vital importance that economists and epidemiologists work together in designing coordinated health and policy responses to COVID-19 that are appropriate for developing countries. 

References

Alvarez, F,  D Argente and F Lippi (2020), “A Simple Planning Problem for COVID-19 Lockdown”, University of Chicago Becker Friedman Institute for Economics Working Paper No. 2020-34, 6 April.

Baldwin, R (2020), “COVID, remobilisation and the ‘stringency possibility corridor’: Creating wealth while protecting health”, VoxEU.org, 10 April.

Bartik, A W, M Bertrand, Z B Cullen, E L Glaeser, M Luca and C T Stanton (2020). “How Are Small Businesses Adjusting to COVID-19? Early Evidence from a Survey”, NBER Working Paper 26989.

Bick, A and A Blandin (2020), “Real Time Labor Market Estimates During the 2020 Coronavirus Outbreak”, manuscript 15 April.

Buera, F, R Fattal-Jaef, H Hopenhayn, P A Neumeyer and Y Shin (2020), “The Economic Ripple Effects of COVID-19”, manuscript World Bank.

Busso, M, M Spector and P A Neumeyer (2012), “Skills, Informality and the Size Distribution of Firms”, manuscript.

Dingel, J and B Neiman (2020), “How Many Jobs Can be Done at Home?”, COVID Economics: Vetted and Real-Time Papers 1:16-24.

Ebsim, M, M Faria-e-Castro and J Kozlowski (2020), “Corporate Bond Spreads and the Effects of Unconventional Monetary Policy during the Pandemic”, On The Economy Blog, Federal Reserve Bank of St Louis, 6 April.

Eichenbaum, M S, S Rebelo and M Trabandt (2020), “The Macroeconomics of Epidemics”, NBER Working Paper No. 26882.

Faria-e-Castro, M (2020) “Back-of-the-Envelope Estimates of Next Quarter’s Unemployment Rate”, On The Economy Blog, Federal Reserve Bank of St Louis, 24 March.

Glover, A, J Heathcote, D Krueger and V Rios Rull (2020), “Health versus Wealth: On the Distributional Effects of Controlling a Pandemic“, in COVID Economics: Vetted and Real-Time Papers 6, 17 April.

Greenstone, M and N Vishan (2020), “Does Social Distancing Matter?”,University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2020-26. 

Guerrieri V, G Lorenzoni, L Straub and I Werning (2020), “Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?”, NBER Working Paper No. 26918.

Hevia, C and P A Neumeyer (2020), “A Conceptual Framework for Analyzing the Economic Impact of COVID-19 and its Policy Implication”,  UNDP LAC COVID-19 Policy Documents Series 1, 29 March. 

Hevia, C, P A Neumeyer and F Perri (2020), “The COVID-19 business cycle in emerging economies”, manuscript. 

Klenow, P, R E Hall and C I Jones (2020), “Trading Off Consumption and COVID-19 Deaths”, April.

Leibovici, F, A M Santacreu and M Famiglietti (2020), “How the Impact of Social Distancing Ripples through the Economy”, On The Economy Blog, Federal Reserve Bank of St Louis, 7 April.

Meidan, D, R Cohen, S Haber and B Barzel (2020), “An alternating lock-down strategy for sustainable mitigation of COVID-19”, Quantitative Biology, Populations and Evolution, 3 April.

Ray, D, S Subramanian and L Vandewalle (2020), “India’s lockdown”, Voxeu.org, 8 April.

Ribakova, E, B Hilgenstock and J Fortun (2020), “Macro Notes – 2020 Capital Flows Outlook for Emerging Markets”, Institute for International Finance, 8 April.

Tiftik, E and K Mahmood (2020), “Global Debt Monitor COVID-19 Lights a Fuse”, Institute for International Finance, 6 April.

The World Bank (2020), Africa’s Pulse, Volume 21, April.

Endnotes

1 Leibovici et al. (2020) find that in the US “a 51% drop in the final demand for goods and services from contact-intensive industries implies a 13% decline in the gross output of low contact-intensive industries in the same supply network and a 24% drop in aggregate gross output.”

2 Bick and Blandin (2020) report data from a new project that conducts an online labor market survey closely following the CPS every other week to get real time labor market estimates of labour market conditions. The data reported above were published on 15 April 2020. 

3 The median small business in the US has more than $10,000 in monthly expenses and less than one month of cash on hand (Bartik et al. 2020).

4 Guerrieri et al. (2020) show that when agents with negative income shocks are unable to borrow and there are strong complementarities between the demand of goods in essential and non-essential activities aggregate demand may fall more than aggregate supply, amplifying the initial shock. 

5 In Latin America, for example, 53% of employment is in firms of five workers or less with about eight years of formal education. This firms are typically informal and in non-essential sectors (Busso et al. 2012).

6 https://fred.stlouisfed.org/graph/fredgraph.png?g=qHGq

7 https://www.bloomberg.com/quote/BCOM:IND

8 See https://data.worldbank.org/share/widget?indicators=SH.MED.BEDS.ZS&type=shaded&view=map&year=2010

9 The combined effect of social distancing polices, exogenous drops in foreign income and financial tightening on economic activity and employment is hard to estimate. Hevia et al. (2020) simulate how a combination of these shocks impacts the economy in a laboratory setup where agents understand the health consequences of their economic choices and have heterogenous access to financial markets. Results are still too unreliable for publication. 

10 Alvarez et. al. (2020), Eichenbaum et. al (2020) and Greenstone and Nigam (2020) evaluate this trade-off using the US governments value of statistical life. The first two find that early protracted interventions containing the epidemic are optimal despite their economic cost. The latter estimate the value of saved lives due to social distancing at $8 trillion (around 60% of yearly consumption).

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