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Deconstructing Informality: Evidence from South American Household Surveys

Morales Curiel, Ana Maria Teresa LU (2021) EKHS42 20211
Department of Economic History
Abstract
The persistence and growth of the informal economy in South America is considered one of the most relevant problems in the region. However, studying informality across countries can be a complicated task due to the lack of homogeneous concepts and measurements. In this study, a database is constructed and harmonized with household survey data from 9 South American countries for 2019. This research’s empirical strategy goes from the broadest to the most specific categorization of informality using probit and multi-logit models, to study how individual, household, and employment characteristics affect the probability of informality, based on the legalistic definition. First, it was found that the independent - informal salaried distinction... (More)
The persistence and growth of the informal economy in South America is considered one of the most relevant problems in the region. However, studying informality across countries can be a complicated task due to the lack of homogeneous concepts and measurements. In this study, a database is constructed and harmonized with household survey data from 9 South American countries for 2019. This research’s empirical strategy goes from the broadest to the most specific categorization of informality using probit and multi-logit models, to study how individual, household, and employment characteristics affect the probability of informality, based on the legalistic definition. First, it was found that the independent - informal salaried distinction is not appropriate for studying differences in types of informality. Instead, I consider that differentiating between informal employers, self-employed, salaried, unpaid family workers and formal employment is more accurate. In addition, evidence was found that supports the main theories established in the literature, but this research contributes with new specific findings thanks to the deconstructive analysis of informality across countries. The results support the life-cycle theory, as well as the human capital theory, although I find different effects of education on being an informal employer than on the other types of informality, and that higher education reduces the probability of informality more for women than for men. It was also found that being a woman increases the probability of informality, except for Ecuador, Paraguay, and Uruguay. But when deconstructing, the results show that being a woman has a negative relationship with the probability of being an informal employer and a positive one with being an informal salaried, informal self-employed, and unpaid family worker, and this effect increases in that order. Also, that the number of children is more significant in increasing the probabilities of informality for women than for men. Finally, that informals at the bottom of the distribution are more likely to be unpaid family workers or self-employed, women, young and with no education; while those at the top are more likely to be employers, men, old and with superior education, among other findings. (Less)
Please use this url to cite or link to this publication:
author
Morales Curiel, Ana Maria Teresa LU
supervisor
organization
course
EKHS42 20211
year
type
H2 - Master's Degree (Two Years)
subject
keywords
labor informality, social security, socio-economic characteristics, household surveys, South America
language
English
id
9055761
date added to LUP
2021-06-24 13:23:49
date last changed
2021-06-24 13:23:49
@misc{9055761,
  abstract     = {{The persistence and growth of the informal economy in South America is considered one of the most relevant problems in the region. However, studying informality across countries can be a complicated task due to the lack of homogeneous concepts and measurements. In this study, a database is constructed and harmonized with household survey data from 9 South American countries for 2019. This research’s empirical strategy goes from the broadest to the most specific categorization of informality using probit and multi-logit models, to study how individual, household, and employment characteristics affect the probability of informality, based on the legalistic definition. First, it was found that the independent - informal salaried distinction is not appropriate for studying differences in types of informality. Instead, I consider that differentiating between informal employers, self-employed, salaried, unpaid family workers and formal employment is more accurate. In addition, evidence was found that supports the main theories established in the literature, but this research contributes with new specific findings thanks to the deconstructive analysis of informality across countries. The results support the life-cycle theory, as well as the human capital theory, although I find different effects of education on being an informal employer than on the other types of informality, and that higher education reduces the probability of informality more for women than for men. It was also found that being a woman increases the probability of informality, except for Ecuador, Paraguay, and Uruguay. But when deconstructing, the results show that being a woman has a negative relationship with the probability of being an informal employer and a positive one with being an informal salaried, informal self-employed, and unpaid family worker, and this effect increases in that order. Also, that the number of children is more significant in increasing the probabilities of informality for women than for men. Finally, that informals at the bottom of the distribution are more likely to be unpaid family workers or self-employed, women, young and with no education; while those at the top are more likely to be employers, men, old and with superior education, among other findings.}},
  author       = {{Morales Curiel, Ana Maria Teresa}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Deconstructing Informality: Evidence from South American Household Surveys}},
  year         = {{2021}},
}