Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries

TL;DR

This paper introduces a structural econometric method to accurately estimate Covid-19's basic reproduction number across regions, accounting for mitigation effects, with applications to U.S. states and countries.

Contribution

It presents a novel, easy-to-implement econometric approach that isolates the true reproduction number by filtering out mitigation influences.

Findings

Average R0 estimate of 4.5 across regions

Significant underestimation of R0 without mitigation adjustments

Method successfully applied to diverse datasets

Abstract

This paper proposes a structural econometric approach to estimating the basic reproduction number ($\mathcal{R}_{0}$) of Covid-19. This approach identifies $\mathcal{R}_{0}$ in a panel regression model by filtering out the effects of mitigating factors on disease diffusion and is easy to implement. We apply the method to data from 48 contiguous U.S. states and a diverse set of countries. Our results reveal a notable concentration of $\mathcal{R}_{0}$ estimates with an average value of 4.5. Through a counterfactual analysis, we highlight a significant underestimation of the $\mathcal{R}_{0}$ when mitigating factors are not appropriately accounted for.