Earnings Distribution of Cuban Immigrants in the United States: Evidence from Quantile Regression.

Friday, 3 July 2015: 2:15 PM-3:45 PM
TW1.2.02 (Tower One)
Aleida Cobas Valdes, Universidad del País Vasco, Bilbao, Spain
Ana Fernández-Sainz, Universidad del País Vasco, Bilbao, Spain
Abstract. This paper uses quantile regressions to describe the conditional earnings distribution of Cuban immigrants in the US. Quantile regression is a method for estimating the relationship between a response variable and a set of predictor variables for all the conditional probability distribution of the response variable. The data used in the study came from the 2011 Census of Population and Housing in the US provided by IPUMS (2011). The results show that increments in earnings associated with the different socio-economics characteristics such as gender, marital status, ethnicity, English proficiency, age at entering in U.S and years of education, vary across the earnings distribution and in this way, we can determine the differences in the impact of these socio-economics characteristics in the wages of the workers who earn less and those who earn more.

Keywords: Earnings distribution, Cuba, Migration, Education, Quantile regression