Volume 44, Number 174,
July-September 2013
Salary Gaps in Uruguay: Gender, Segregation
and Unequal Labor Qualifications
Alma Espino
Salary Differences and Segregation ( ...continuation )

With this in mind, the first salary equation was as follows (1):


Where lwpoij is the logarithm of the hourly salary explained by a dummy variable equal to 1 if the individual p is a woman (0 if it is a man), segM is the percentage of women in occupation o, segrama is the percentage of women by activity sector to one digit i, segtam is the percentage of women by size of the establishment j, X represents a vector of individual variables and ε is a well-behaved error term. βsexo is the difference attributable to gender for individuals after controlling for the proportion of women in the various occupations, sectors of activity and establishment categories. It can be interpreted as a measure of discrimination, but it also captures differences in non-observable features among individuals. When these affect salaries negatively, they are more concentrated among women than men, and this parameter captures this effect. If the sign of the parameter is positive, the interpretation is that there is discrimination against women, whereas a negative sign indicates the opposite situation. The coefficient θ represents remuneration for individual characteristics. If these are valued as positive in the labor market or they imply greater productivity, the higher their value, the more the salary increases, and this translates into a positive value for the parameter. Otherwise, if these characteristics are valued negatively or linked to lower productivity, it will be negative. The parameter γ measures how the proportion of women in different occupations influences perceived salaries. A positive sign in the parameter indicates that a greater weight of women in that occupation would lead to a higher salary. The symbols λ and δ are interpreted analogously.

Equation (1), according to Bayard et al. (2003), can be broken down to express the differences as an average of the logarithms of the salaries between men and women, as shown in (2):


Where the prime in the coefficients indicates estimated values and the subscripts m and h in the variables indicate the average for women and men, respectively.

The average difference of salaries is made up of five terms. The difference XhXm reflects the dissimilarities in individual characteristics. The way in which these characteristics are remunerated in the labor market is defined by the value and the sign of θ. The difference segMhsegMm measures the contribution of occupational segregation to the salary gap. If women are concentrated in few occupations, the difference between these terms will be negative. Moreover, when there is labor segregation, given that occupations with a greater proportion of women receive lower remuneration, this would contribute to the increase in the salary gap (the term is positive). The same interpretation can be used for the third and fourth term.7

Salary Differences and Skill Mismatch

This work estimates three salary equations (Badillo Amador and Vila Llados, 2005; Johansson and Katz, 2007). The first salary equation (Verdugo and Verdugo, 1989) aims to analyze whether educational imbalances with relation to the average of occupied persons can explain the salary differences among workers with similar characteristics, and as such, the same educational level:


Where the dependent variable is the logarithm of the average hourly salary of individual i, sobrecalifi is a dichotomist variable that takes on the value of 1 if employee i is over-educated for the job and 0 if not, subcalifi is a dichotomist variable worth 1 if employee i is under-educated and 0 if not, Xi is an explanatory variable vector that includes the characteristics of individual i and mi is the random disturbance variable. The second and third salary equations analyze whether this labor phenomenon can explain the differences in the return on years of education for employees and, as such, the salary discrepancies among employers in the same job.

7 Analyzing salary differences by gender and controlling for segregation throughout all of these dimensions as well as other features captured by β’ can be thought of as a traditional decomposition from R. Oaxaca (1973), but in this case, the restriction that the coefficients be the same for women and men is imposed. In other words, female segregation would consequently affect both female and male salaries.

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PROBLEMAS DEL DESARROLLO. REVISTA LATINOAMERICANA DE ECONOMÍA, Volume 49, Number 194 July-September 2018 is a quarterly publication by the Universidad Nacional Autónoma de México, Ciudad Universitaria, Coyoacán, CP 04510, México, D.F. by Instituto de Investigaciones Económicas, Circuito Mario de la Cueva, Ciudad Universitaria, Coyoacán,
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