Tag Archives: Logistic model

“The Political Economy of Early COVID-19 Interventions in US States,” CEPR, 2022

CEPR Discussion Paper 16906, January 2022, with Martin Gonzalez-Eiras. PDF (local copy).

We investigate how politico-economic factors shaped government responses to the spread of COVID-19. Our simple framework uses epidemiological, economic and politico-economic arguments. Confronting the theory with US state level data we find strong evidence for partisanship even when we control for fundamentals including the electorate’s political views. Moreover, we detect an important role for the proximity of elections which we interpret as indicative of career concerns. Finally, we find suggestive evidence for complementarities between voluntary activity reductions and government imposed restrictions.

Forthcoming in the JEDC.

“Optimally Controlling an Epidemic,” CEPR, 2020

CEPR Discussion Paper 15541, December 2020, with Martin Gonzalez-Eiras. PDF (local copy).

We propose a flexible model of infectious dynamics with a single endogenous state variable and economic choices. We characterize equilibrium, optimal outcomes, static and dynamic externalities, and prove the following: (i) A lockdown generically is followed by policies to stimulate activity. (ii) Re-infection risk lowers the activity level chosen by the government early on and, for small static externalities, implies too cautious equilibrium steady-state activity. (iii) When a cure arrives deterministically, optimal policy is dis-continous, featuring a light/strict lockdown when the arrival date exceeds/falls short of a specific value. Calibrated to the ongoing COVID-19 pandemic the baseline model and a battery of robustness checks and extensions imply (iv) lockdowns for 3-4 months, with activity reductions by 25-40 percent, and (v) substantial welfare gains from optimal policy unless the government lacks instruments to stimulate activity after a lockdown.

“Tractable Epidemiological Models for Economic Analysis,” CEPR, 2020

CEPR Discussion Paper 14791, May 2020, with Martin Gonzalez-Eiras. PDF (local copy).

We contrast the canonical epidemiological SIR model due to Kermack and McKendrick (1927) with more tractable alternatives that offer similar degrees of “realism” and flexibility. We provide results connecting the different models which can be exploited for calibration purposes. We use the expected spread of COVID-19 in the United States to exemplify our results.