Measuring Resilience as Asymmetric Mean Reversion

56 Pages Posted: 18 Feb 2021

See all articles by Sonia Zaharia

Sonia Zaharia

Tufts University - Friedman School of Nutrition Science and Policy

William A. Masters

Tufts University - Friedman School of Nutrition Science and Policy; Tufts University - Department of Economics

Gerald Shively

Purdue University

Shibani Ghosh

Tufts University

Patrick Webb

Tufts University

Date Written: January 20, 2021

Abstract

We introduce a new method to measure resilience, defined as the ability of an individual, household or community to recover after a decline in well-being. Our approach measures resilience as the extent to which outcomes recover, against the benchmark of symmetric mean reversion arising from measurement error or random fluctuations. Observing desirable asymmetry in which recovery is larger than would be expected due to mean reversion allows us to measure resilience without having observed the precipitating shocks. We present the method, derive correction factors to account for autocorrelation, and apply the method to data on diet diversity and anthropometry of women and children from Nepal, Bangladesh, and Uganda. Tests introduced in this paper offer a promising approach to identifying groups with statistically significant resilience; observing the presence or need for social insurance, safety nets and other sources of resilience; and assessing the sustained effects of interventions.

Keywords: Panel Data, Autocorrelation, Safety Nets, Vulnerability

JEL Classification: C23, I38, Q01

Suggested Citation

Zaharia, Sonia and Masters, William A. and Shively, Gerald and Ghosh, Shibani and Webb, Patrick, Measuring Resilience as Asymmetric Mean Reversion (January 20, 2021). Available at SSRN: https://ssrn.com/abstract=3766447 or http://dx.doi.org/10.2139/ssrn.3766447

Sonia Zaharia (Contact Author)

Tufts University - Friedman School of Nutrition Science and Policy ( email )

150 Harrison Avenue
Boston, MA 02111
United States

William A. Masters

Tufts University - Friedman School of Nutrition Science and Policy ( email )

150 Harrison Avenue
Boston, MA 02111
United States

HOME PAGE: http://sites.tufts.edu/willmasters

Tufts University - Department of Economics ( email )

Medford, MA 02155
United States

Gerald Shively

Purdue University ( email )

610 Purdue Mall
West Lafayette, IN 47907
United States

Shibani Ghosh

Tufts University ( email )

Medford, MA 02155
United States

Patrick Webb

Tufts University ( email )

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