Datos mexicanos de COVID-19 en sus etapas iniciales ¿estratégicamente distorsionados?

Abstract

Objective: To identify states that make more changes in measurements related to COVID-19 in Mexico and the cofactors that contribute to explain the magnitudes of these distortions.

Methodology: Hierarchical cluster analysis and cointegration tests are used to identify the states that distort the information the most. Regression analysis relates the magnitude of the distortions with information on state competitiveness.

Results: At least six states under-register deaths, cases or both. Moreover, states distort information on cases to avoid a negative impact on certain economic sectors.

Limitations: The number of observations is subject to the number of states. Cofactors are time invariant. On the other hand, the real magnitude of the distortions in COVID-19 measurements could be greater as the Secretaría de Salud has recognized an underreporting in its information.

Originality: It is the first research that analyzes the distortions in the measurements of COVID-19 in our country.

Conclusions: This paper shows evidence of possible strategic actions carried out by states with respect to the flow of information from COVID-19.