Abstract

An important aspect of the current COVID-19 crisis is that not all age groups are equally affected by the pandemic. To account for the generational impact of COVID- 19, a dynamic overlapping generations model with realistic demography, human capital and NTAs is constructed. The COVID-19 crisis is modelled through two unexpected and temporary negative shocks: an economic shock that reduces labour income, and a demographic shock that increases the mortality hazard rates of those infected. The model is applied to 12 countries for which full NTA data are available. Results are presented for two extreme fiscal policies: one in which governments compensate workers for 0% (without fiscal support) of their total labour income losses due to the pandemic, and another in which governments compensate workers for 100% (with fiscal support) of these losses. In addition, I analyse the impact of these policies on public debt. The results show that COVID-19 is affecting the financial situations of people aged 25 to 64 and their children more than those of older people. By compensating workers for their income losses, the economic impact of COVID-19 has been more evenly distributed across cohorts, reducing the burden on people aged zero to 64, and increasing the burden on people aged 65 and older. Moreover, the simulation results show that a 1% decline in labour income leads to an average increase in the debt-to-total labour income ratio of between 1.2% (without fiscal policy) and 1.6% (with fiscal policy).

Highlights

  • The COVID-19 pandemic has affected all aspects of economic and social life

  • Assuming that the debt-to-GDP ratio is reduced by 10% per year from 2022 onwards, a 1% decrease in labour income leads to an average increase in the total tax revenue during the 2020s of 0.074% if the government does not compensate workers for their labour income losses, and of 0.104% if the government fully compensates workers for their labour income losses

  • Given that most countries have chosen to implement expansionary fiscal policies to reduce the economic burden of the COVID-19 pandemic, the OLGNTA model assumes that the per capita public transfer inflows remain unchanged during the economic crisis caused by the COVID-19 pandemic, and that only the public transfer outflows are adjusted downwards because of labour income losses

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Summary

Introduction

The COVID-19 pandemic has affected all aspects of economic and social life. From a demographic perspective, the COVID-19 pandemic has caused many deaths, an increase in morbidity among those infected, the postponement of many planned migration flows and an unequal fertility response based on socioeconomic conditions (Aassve et al, 2020). From an economic perspective, the COVID-19 pandemic has caused disruptions to both the supply and the demand side. To complement the recent literature on this topic, models should be developed that use economic information by age, and by the extent to which different age groups are supported through familial and public transfers, such as the information provided by the National Transfer Accounts (NTA) project, to assess the impact of the COVID-19 crisis on the generational economy. While this policy option will improve the chances of an economic recovery and offset workers’ pandemic-related labour income losses in 2021 and 2022, it will raise public debt levels and increase the burden on future taxpayers These two extreme policies provide information on the minimum and maximum impact that a pandemic such as COVID-19 may have on fiscal revenues and on public debt. The article has an Appendix in which we explain the formulas needed to construct the OLG-NTA model, and that allow for the replication of this analysis in other countries with current NTA data

Constructing an OLG-NTA model
Per capita profiles
Aggregate profiles
Impact of the COVID-19 pandemic on NTA profiles
Impact on debt
Impact on taxes
Impact of the COVID-19 pandemic on the generational economy
Impact on consumption
Impact on public and private transfers
Discussion
A Demography
Survival probabilities
Population projections
Raw NTA profiles
Exogenously constructed NTA profiles
Interhousehold transfers
Government
Findings
Exogenous parameters
Full Text
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