Sectoral Productivity Growth, COVID-19 Shocks, and Infrastructure

This paper examines sectoral productivity shocks of the COVID-19 pandemic, their aggregate impact, and the possible compensatory effects of improving productivity in infrastructure-related sectors. We employ the KLEMS annual dataset for a group of OECD and Latin America and the Caribbean countries, complemented with high-frequency data for 2020. First, we estimate a panel vector autoregression of growth rates in sector level labor productivity to specify the nature and size of sectoral shocks using the historical data. We then run impulse-response simulations of one standard deviation shocks in the sectors that were most affected by COVID-19. We estimate that the pandemic cut economy-wide labor productivity by 4.9% in Latin America, and by 3.5% for the entire sample. Finally, by modeling the long-run relationship between productivity shocks in the sectors most affected by COVID-19, we find that large productivity improvements in infrastructure-equivalent to at least three times the historical rates of productivity gains-may be needed to fully compensate for the negative productivity losses traceable to COVID-19.

The online version contains supplementary material available at 10.1007/s41885-021-00098-z.