Working Papers
2020
October 21, 2020
Exiting from Lockdowns: Early Evidence from Reopenings in Europe
Description: European authorities introduced stringent lockdown measures in early 2020 to reduce the transmission of COVID-19. As the first wave of infection curves flattened and the outbreak appeared controlled, most countries started to reopen their economies albeit using diverse strategies. This paper introduces a novel daily database of sectoral reopening measures in Europe during the first-wave and documents that country plans differed significantly in terms of timing, pace, and sequencing of sectoral reopening measures. We then show that reopenings led to a recovery in mobility—a proxy for economic activity—but at the cost of somewhat higher infections. However, the experience with reopening reveals some original dimensions of this trade-off. First, the increase in COVID-19 infections after reopening appears less severe in fatality rates. Second, a given reopening step is associated with a worse reinfection outcome in countries that started reopening earlier on the infection curve or that opened all sectors at a fast pace in a relatively short time. Finally, while opening measures tend to have an amplification effect on subsequent cases when a large fraction of the economy is already open, this effect appears heterogenous across sectors.
October 16, 2020
COVID-19 and Inequality in Asia: Breaking the Vicious Cycle
Description: The COVID-19 pandemic risks exacerbating inequality in Asia. High frequency labor surveys show that the pandemic is having particularly adverse effects on younger workers, women and people that are more vulnerable. Pandemics have been shown to increase inequalities. As a result, income inequality, which was already high and rising in Asia before the pandemic, is likely to rise further over the medium term, unless policies succeed in breaking this historical pattern. Many Asian governments have implemented significant fiscal policy measures to mitigate the pandemic’s effect on the most vulnerable, with the impact depending on the initial coverage of safety nets, fiscal space, and degree of informality and digitalization. The paper includes model-based analysis which shows that policies targeted to where needs are greatest are effective in mitigating adverse distributional consequences and underpinning overall economic activity and virus containment.
October 16, 2020
A Vicious Cycle: How Pandemics Lead to Economic Despair and Social Unrest
Description: In this paper we analyze the dynamics among past major pandemics, economic growth, inequality, and social unrest. We provide evidence that past major pandemics, even though much smaller in scale than COVID-19, have led to a significant increase in social unrest by reducing output and increasing inequality. We also find that higher social unrest, in turn, is associated with lower ourput and higher inequality, pointing to a vicious cycle. Our results suggest that without policy measures, the COVID-19 pandemic will likely increase inequality, trigger social unrest, and lower future output in the years to come.
October 13, 2020
Mexico Needs a Fiscal Twist: Response to Covid-19 and Beyond
Description: Mexico’s fiscal response to the pandemic has been modest compared to its peers, reflecting the authorities’ desire to not issue new debt for spending. This approach, however, risks a more severe recession and a weaker economic recovery, with further costs in the future. Balancing the need for stronger near-term fiscal support for the people and the recovery against medium-term discipline, this paper lays out an alternative strategy. We show that credibly announcing a pro-growth and inclusive medium-term fiscal reform upfront—including increased tax capacity, higher public investment and strengthened social safety nets—would open space for larger short-term support and close medium-term fiscal gaps. Model simulations suggest that this package would boost output, limit lasting economic damage from the pandemic, and put debt trajectory on a declining path in the medium term as tax reforms pay off and risk premia decline.
October 13, 2020
A Mexican State-level Perspective on Covid-19 and its Economic Fallout
Description: Mexico has had one of the highest death tolls from Covid-19 and among the largest declines in output compared to peers. This paper utilizes data on Mexico’s thirty-two states to better understand the relationship between health and economic outcomes. For instance, did the states with worse pandemic outcomes suffer more economically? What state-level characteristics impacted health and economic outcomes? Among the findings are: individual traits such as age and certain pre-existing conditions were associated with higher illness and fatality risks. States with higher initial health expenditure and capacity on average had a lower case fatality rate. The economic fallout was widespread well beyond the direct impact of the pandemic. Tourism-heavy states were particularly badly affected, while states with larger exposures to manufacturing exports performed better. These findings support the case for adequate health spending, fiscal lifelines for hard-hit workers and sectors, and further integration into global value chains to bolster economic outcomes and resilience.
September 25, 2020
US Housing Market during COVID-19: Aggregate and Distributional Evidence
Description: Using zip code-level data and nonparametric estimation, I present eight stylized facts on the US housing market in the COVID-19 era. Some aggregate results are: (1) growth rate of median housing price during the four months (April-August 2020) since the Federal Reserve’s unprecedented monetary easing has accelerated faster than any four-month period in the lead-up to the 2007-09 global financial crisis; (2) the increase in housing demand in response to lower mortgage interest rates displays a structural break since March 2020 (housing demand has increased by much more than before). These results indicate either the existence of “fear of missing out” or COVID-induced fundamental changes in household behavior. In terms of distributional evidence, I find that the increase of housing demand seems more pronounced among the two ends of the income distribution, possibly reflecting relaxed liquidity constraints at the lower end and speculative demand at the higher end. I also find that the developments in housing price, demand, and supply since April 2020 are similar across urban, suburban, and rural areas. The paper highlights some potential unintended consequences of COVID-fighting policies and calls for further studies of the driving forces of the empirical findings.
September 25, 2020
Financial Frictions and Firm Informality: A General Equilibrium Perspective
Description: In this paper we build a model of occupational choice with informal production and progressive income taxation. We calibrate the model to the Brazilian economy to evaluate the impact of removing financial frictions on informality. We find that financial deepening leads to a drop in the size of the informal sector (from 37 percent to 22 percent of official GDP), to an increase in measured TFP (by 4 percent), to an increase in official GDP (by 27 percent), to a decrease in tax evasion (by 17 percent) and to an increase in fiscal revenues (by 15 percent). When assessing the response of this policy at different levels of financial development, we find a non-linear relationship between the credit-to-GDP ratio on the one hand, and either the size of the informal economy, or GDP per capita on the other hand. We test these features with cross-country data and find evidence in favor of both types of non-linearity. We also investigate changes in the income tax progressitivity as an alternative policy and find it to be more effective in countries with a medium to high level of financial markets development.
September 25, 2020
Are Bilateral Trade Balances Irrelevant?
Description: Based on an empirical gravity model of sectoral bilateral trade, we uncover three features of bilateral trade balances. First, the difficulty of gravity models in fitting the observed level of bilateral balances is likely due to the presence of unobservable bilateral trade costs. Second, the model fit improves drastically when we focus on changes over time of the balances. Third, using a log linear approximation we show that changes in bilateral trade balances over the past two decades were driven almost entirely by changes in the same macro factors that determine countries’ aggregate balances – changes in bilateral trade costs, including tariffs, played therefore only a negligible role. This conclusion provides new support for the view that bilateral balances are, for practical purposes, not relevant to the conduct of macroeconomic policy.
September 25, 2020
Capital Gaps, Risk Dynamics, and the Macroeconomy
Description: Motivated by the increasing interest in analyzing the links between the financial sector and the real economy, we develop a macro-financial structural model with two novel features. First, we include idiosyncratic and aggregate risk in a tractable general equilibrium model. This allows us to capture sectoral dynamics and the probabilities of default of both firms and financial intermediaries, and the feedback between them. Second, we introduce the concept of sticky (observed) versus flexible (agents’ target) capital. The identified differences between realized and optimal values — the capital gaps of firms and banks — lead financial and business cycles, and cause gaps in credit spreads and asset prices. The model can be used as a signaling device for macroprudential intervention, and to gauge whether macroprudential action was successful ex-post (e.g., whether gaps were closed). For illustration, we show how the analysis of gaps can be applied to the U.S. economy using Bayesian estimation techniques.
September 25, 2020
Fintech Credit Risk Assessment for SMEs: Evidence from China
Description: Promoting credit services to small and medium-size enterprises (SMEs) has been a perennial challenge for policy makers globally due to high information costs. Recent fintech developments may be able to mitigate this problem. By leveraging big data or digital footprints on existing platforms, some big technology (BigTech) firms have extended short-term loans to millions of small firms. By analyzing 1.8 million loan transactions of a leading Chinese online bank, this paper compares the fintech approach to assessing credit risk using big data and machine learning models with the bank approach using traditional financial data and scorecard models. The study shows that the fintech approach yields better prediction of loan defaults during normal times and periods of large exogenous shocks, reflecting information and modeling advantages. BigTech’s proprietary information can complement or, where necessary, substitute credit history in risk assessment, allowing unbanked firms to borrow. Furthermore, the fintech approach benefits SMEs that are smaller and in smaller cities, hence complementing the role of banks by reaching underserved customers. With more effective and balanced policy support, BigTech lenders could help promote financial inclusion worldwide.