Socioeconomic and structural profiles of the informal sector in the COVID-19 pandemics

Abstract

The crisis considered as the "Great Confinement" caused by the outbreak of the COVID-19 disease has had a multidimensional impact on humanity, on a health, social, economic, and political level. One of the main effects has been reflected in an economic crisis unparalleled in human history. In the economic history of the human being, each crisis of a wide magnitude has demonstrated a relationship between sociodemographic and economic factors and the growth of the informal economy, such as the level of earnings, scholarship, search of an extra job sex and levels of inequality and poverty. Method: Database was obtained from harmonized surveys made available by INEGI and SHCP, from where both quantitative and categorical data were identified that correspond to the structuralist and institutionalist dimension of informality. Based on that, we applied a Logit model to determine the probability of a person to belong to the informal sector of the economy, and a Probit model to identify reiterated variables of the model as well. Results: Statistically representative variables to determine the probability to belong to the informal sector, with a global percentage of 72.5 %, are the years of school, age, economic inequality, percentage of poverty in each state, the degree of spending in fiscal obligations, the level of fiscal compensations due to belonging to RIF, the type of occupation, sex and the level of minimal wages earned. Discussion or Conclusion: Considering the findings of the research, it is possible to infer that the people with higher risk of falling in the informality and continuing in it, show a characteristic profile that can be considered as a valid base to design effective public policies to reduce informality. The present research contributes trough the identification of a model that describes the profile of an individual with a higher probability of integrate to the informal sector of the economy, considering both sociodemographic and market structure factors, considering the effect of the pandemics in the current economic conditions.