# **2. Data and Descriptive Statistics**

This paper uses data for year 2006 from the national Labor Force Survey (LFS) conducted by the Macedonian State Statistical Office (SSO). The Survey includes a rotational panel, whereby households are interviewed more than one time during a year. The sampling frame, based on the 2002 Census, is stratified, rotational, two stage random and nationally representative. The data contains basic information on demographics, education, and labor market outcomes for individuals 15 years old and plus. Our sample includes approximately 6,536 working men and 4,445 employees between 15 and 64 years old. Due to the nature of the study, unpaid and self-employed workers are not included in the sample. About 77% of the sample is made of low-skilled workers, as defined as those with less than complete tertiary education. Most workers in the sample work in manufacturing (28%), wholesale (12%), public administrations (10%), and education/health/social services (16%); which constitute the largest industries providing employment in Macedonia. More detailed descriptive statistics by gender, age-group, region, education, and industry of employment are presented in Table 1.

An interesting feature of the labor market in Macedonia is the existence of a large wage gap between men and women. Figure 1 plots the cumulative density function (CDF) of hourly wages for both men and women. The figure illustrates that the men’s CDF stochastically dominates that of women, suggesting that at all points of the wage distribution males earn higher wage rates than their female counterparts. On average, unconditional estimates indicate than men earn wages that are 25% higher than women.<sup>2</sup> Table 2 provides descriptive statistics on population shares and wage rates by gender and education for all employees. An interesting result is that gender wage differentials between men and women are large, especially among low-skilled workers in the private sector. A simple Oaxaca decomposition (Oaxaca, 1973) indicates that only 17.4% of the gender gap among low-skilled workers is explained by differences in endowments between men and women while the remaining 82.6% of the gap is unexplained; which is generally attributed to the existence of discrimination (and/or other unobservable factors) in the labor market.

Large gender wage gaps among less skilled workers could be explained by labor market segregation (Becker, 1971; Bergman, 1974; Johnson and Stafford, 1998) to the extent that women are more likely to work in low-pay sectors than men. Table 3 provides simple descriptive statistics on wage differentials and gender segregation by industry of employment. Results in Table 3 indicate that while there is some gender segregation in Macedonia – with men (women) being more segregated in the manufacturing and construction (education/heath/and social services) – overall segregation is not high. Indeed, the index of dissimilarity (one of the most used statistic for segmentation) by

> 2 Similar results using a standard Mincer equation on the natural logarithm hourly wages – controlling for gender, age, age squared, education, region, and industry of employment and other interaction terms between a gender dummy and education categories – indicate that the gender gender wage gap for employees is about 27.3%. These results are available upon request. Also refer to Angel-Urdinola and Macias (2008) for similar estimates.

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