Template-Type: ReDIF-Article 1.0
Author-Name: Rogelio Varela Llamas
Author-Name: Mayra Yesenia Nava Rubio
Title:  Salarios e informalidad laboral en México: una perspectiva regional y empresarial
Abstract: Resumen:Con microdatos de la Encuesta Nacional de Ocupación y Empleo, ENOE, correspondientes al cuarto trimestre de 2016, se estiman regresiones por cuartil para explicar los salarios de trabajadores del sector informal de la economía mexicana. Se instrumenta el método bietápico de Heckman. El modelo Probit indica que la probabilidad de participar en el sector informal aumenta en aquellas regiones socioeconómicas más pobres y en donde la escolaridad es menor. El segmento de los jóvenes, tiende a tener una mayor participación. Los salarios se explican por indicadores de capital humano y por el tipo de empresa en donde se trabaja.Abstract:This paper analyzes the wages of workers in the informal sector of the Mexican economy, according to the size of the company and the socioeconomic characteristics of the worker, such as their schooling, sex and age range. In the econometric estimation, micro-data from the National Occupation and Employment Survey, ENOE, of the National Institute of Statistics and Geography, INEGI, are used for the fourth quarter of the year 2016. In the estimation of the salary equation, the methodology of two stages of Heckman were used to solve the problem of bias by sample self-selection. In the first stage a discrete choice model Probit is estimated, where the dependent variable assumes the value of one if the worker participated in the informal sector and a value of zero otherwise. The probability of participating in the informal sector is explained by variables such as schooling, age of the worker, sex, the economic branch and the socioeconomic region. It is also considered a variable that indicates whether the worker is underemployed and another that informs if he has a job or two. With the exception of the variable schooling and age that are in scale, the rest of the variables are represented by dichotomous variables. The decision equation is estimated using the maximum likelihood method and from it the inverse of the Mills ratio is obtained. In the second stage of the methodology, the interest equation is estimated, in which the dependent variable is the logarithm of the hourly wage, taking into account schooling, sex, age range and company size. The analysis is carried out through the quantile regression approach with the objective of determining if the parameters of the explanatory variables are modified in the different quantiles of the distribution of wages.
Regarding the results of the probit model, it is determined that schooling, sex, age range, the different sizes of the company and the economic branch are variables that help to significantly explain the decision of a worker to participate in the informal sector of the Mexican economy. In the case of the eight socioeconomic regions that are analyzed and that make up the geography of the national economy, it is found that in seven of them, with the exception of the southeast one formed by the states of Campeche, Quintana Roo, Tabasco and Yucatán, it is less likely to participate in the informal sector in relation to the region of reference that is the southwest, which includes the poorest states of Mexico and are Oaxaca, Chiapas and Guerrero. The aforementioned allows us to affirm that it is more likely to participate in the informal sector in those regions that are economically more backward and as more marginalized and poverty. However, it is also observed that in more developed regions such as the Southeast, there is a greater likelihood that informal employment will detonate, even though tourism and industrial activity predominates in these entities and they exhibit less social vulnerability. It is also found that as you have a higher level of schooling, the probability of working in informality decreases. In this sense, the decision that a worker takes when participating in the informal sector is closely related to the stock of human capital, but also to the sex, for the results suggest that men are less likely to participate in the informal economy. It is also found that to the extent that a worker is underemployed and has only one job, is more likely to participate in the informal sector. Regarding the age range, it is noted that those who are above the age of 25, are less likely to participate in the informal sector in contrast to young people who fall within the range of 15 to 24 years.
With respect to the results of the wage equation, it is found that education has a positive and persistent effect. However, its effect is more noticeable in the upper quantiles of the distribution. The coefficient of the variable sex also has a positive sign that suggests that men earn on average more than women, but it is found that in the upper quantiles, the gap tends to close, which means that in the upper part of the distribution men continue to earn more than women but in a smaller proportion. This result is particularly interesting, since it means that women, as they participate in the labor market, also perceive better incomes. With respect to the age ranges, it can be seen that in the highest quantiles of wage distribution, workers who work in the informal sector who are between 45 and 64 years old earn more than young people and those who are 65 years old and older, earn less, but in the higher quantiles the gap tends to narrow. In the case of the vector of dichotomous variables that captures the different sizes of companies, it is found that those who work in small and medium enterprises receive higher income than those who work in microenterprises in the lower quantiles of the distribution, but the differential decreases until it grows in the higher quantiles. As far as large companies are concerned, the differential between these and microenterprises without establishment is positive and systematically growing in favor of large companies in all the quantiles of distribution. In this framework of analysis, it is pointed out that the phenomenon of wage inequality is not exclusively explained by the particular characteristics of each of the heads of households, but also by demand factors such as the type of company. In this sense, it can be concluded that, in the determination of wages, the stock of human capital plays a predominant role, the approximate work experience through age and business structure. It is also found that in most socioeconomic regions it is less likely that a worker participates in the informal sector, with respect to the poorest region of the country, which includes the states of Oaxaca, Chiapas and Guerrero, which means that there is a close relationship between labor informality and poverty, suggesting that those regions more backward economically and socially, should be promoted through regional development strategies that trigger formal employment, productive investment and social welfare.
Classification-JEL: R1
Keywords: Economía Informal, Salarios, Regiones Socioeconómicas, Informal Economy, Wages, Socioeconomic Regions
Pages: 15-46
Volume: 2
Year: 2020
File-URL: http://www.revistaestudiosregionales.com/documentos/articulos/pdf-articulo-2591.pdf
File-Format: Application/pdf
Handle: RePEc:rer:articu:v:2:y:2020:p:15-46