Julián Costas-Fernández
Eleonora Patacchini
Jorgen Harris
Marco Battaglini
Ricardo Fernholz
Alberto Bisin
Jess Benhabib
Cian Ruane
Pete Klenow
Mark Bils
Peter Hull
Will Dobbie
David Arnold
Eric Zwick
Owen Zidar
Matt Smith
Ansgar Walther
Tarun Ramadorai
Paul Goldsmith-Pinkham
Andreas Fuster
Ellora Derenoncourt
Golvine de Rochambeau
Vinayak Iyer
Jonas Hjort
Elena Simintzi
Paige Ouimet
Holger Mueller
Pablo Garriga
Gabriel Ulyssea
Costas Meghir
Pinelopi Koujianou Goldberg
Rafael Dix-Carneiro
Alessandro Toppeta
Áureo de Paula
Orazio Attanasio
Seth Zimmerman
Joseph Price
Valerie Michelman
Camille Semelet
Anne Brockmeyer
Pierre Bachas
Santiago Pérez
Elisa Jácome
Leah Boustan
Ran Abramitzky
Jesse Rothstein
Jeffrey T. Denning
Sandra Black
Wei Cui
Mathieu Leduc
Philippe Jehiel
Shivam Gujral
Suraj Sridhar
Attila Lindner
Arindrajit Dube
Pascual Restrepo
Łukasz Rachel
Benjamin Moll
Kirill Borusyak
Michael McMahon
Frederic Malherbe
Gabor Pinter
Angus Foulis
Saleem Bahaj
Stone Centre
Phil Thornton
James Baggaley
Xavier Jaravel
Richard Blundell
Parama Chaudhury
Dani Rodrik
Alan Olivi
Vincent Sterk
Davide Melcangi
Enrico Miglino
Fabian Kosse
Daniel Wilhelm
Azeem M. Shaikh
Joseph Romano
Magne Mogstad
Suresh Naidu
Ilyana Kuziemko
Daniel Herbst
Henry Farber
Lisa Windsteiger
Ruben Durante
Mathias Dolls
Cevat Giray Aksoy
Angel Sánchez
Penélope Hernández
Antonio Cabrales
Wendy Carlin
Suphanit Piyapromdee
Garud Iyengar
Willemien Kets
Rajiv Sethi
Ralph Luetticke
Benjamin Born
Amy Bogaard
Mattia Fochesato

The impact of COVID-19 on formal firms: micro tax data simulations across countries

What is this research about and why did you do it?

When the COVID-19 pandemic hit and triggered lockdowns around the world, it was clear that the effects on firm profits and hence tax payments would be significant. To prepare support policies, governments, aid agencies and NGOs were wondering just how severe the impact would be. The need for well-informed policy design seemed particularly acute in lower-income countries. Yet data on firm activities is typically scarce in these countries. We devised a method to simulate the impact of COVID-19 triggered lockdowns on the profits of formal-sector firms, using available corporate tax records. We applied our approach to data for ten countries.

How did you answer this question?

We simulate a demand shock which induces a drop in firms’ sales for the duration of the lockdown. The severity of the shock is set to differ across economic sectors. We assume that firms produce a unit of output with a Leontief production function which requires capital, labour and material inputs in fixed proportions, with the proportions estimated from each firm’s tax declaration. In our very stylized world, firms can reduce their material costs proportionally to the drop in demand; they reduce labour costs only when making losses because re-contracting workers is costly; and they cannot adjust their fixed costs.

What did you find?

We predicted that less than half of all firms would remain profitable by the end of 2020, about 5–10 percent of the formal aggregate annual wage bill would be lost, and the likelihood that firms exit the formal sector would double. As a result, we expected that tax revenue remitted by the corporate sector would fall by about 1.5 percent of baseline gross domestic product, and aggregate corporate losses would increase by at least 50 percent in all but two countries in our data.

The figure plots the simulated drop in profitable firms (measured in percentage points, on the left-hand side) and the tax loss (measured as a share of GDP, on the right-hand side) induced by a 3-month lockdown, for countries at different income levels. The figure highlights cross-country differences in the predicted effect of COVID-19, where higher GDP per capita levels are correlated with larger negative shocks on profitability and tax revenue. What explains the differences across development levels? First, the formal sector is substantially larger, as a share of GDP, in richer countries, which therefore have more to lose. Second, effective tax rates are on average higher. Third, the industrial composition of middle-income countries implies on average a slightly larger shock, as services (e.g. tourism) are more impacted than agriculture and manufacturing.

What implications does this have for the research on wealth concentration or economic inequality?

This work highlighted cross-country differences in the predicted effect of COVID-19 and in the effectiveness of support policies. Wage subsidies were expected to be less effective in low-income countries and government revenue losses smaller. These findings are driven by differences in sectoral composition and in firms’ cost structures across countries. Firms in low-income countries disproportionately operate in sectors less exposed to the lockdown-triggered shock (e.g. agriculture is less affected) and rely less on formal labour.

What are the next steps in your agenda?

We are currently working on comparing the results of our simulations to the realized impact of COVID-19 on firms, using tax return data for 2020, which is now available for about half of the countries we studied.

Citation and related resources

This paper can be cited as follows: Bachas, P., Brockmeyer, A., and Semelet, C. (2021) 'The Impact of COVID-19 on Formal Firms: Micro Tax Data Simulations Across Countries.' World Bank Policy Research Working Paper 9437.

About the authors

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