Browsing by Author "Babaran, Angela Mae B."

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    A cross-sectional analysis on the gender income gap: the case of the Philippine public and private sector
    (2026-01-06) Babaran, Angela Mae B.; Palanca, Julian Andre E.
    "This study investigates the gender income gap in the public and private sectors in the Philippines. Using demographic data from the merged APIS-LFS dataset (2019), we first estimate the conditional income equations for both sexes and find persistent gaps of -0.093 and -0.149 in the public and private sectors, respectively. Furthermore, biased estimations may arise when estimating for the income equations. This may be due to the non-random selection of both sexes into the labor market (Hoddinott 1996; Chzhen 2012). To account for this, we employed the Heckman two-step selection correction where we find significant and negative inverse Mills ratios for both sexes. We then employed the Blinder-Oaxaca (BO) decomposition on the uncorrected and corrected equations and found that, after correcting for selection bias, the discrimination effect in the public sector increased from 0.074 to 0.098; while the unexplained component in the private sector rose substantially from 0.119 to 0.204. The results indicate that women possess better observable characteristics hinting on the higher educational attainment and concentration in professional occupations. However, women workers still receive lower returns to these endowments. After investigating the decomposition of the income gaps in the mean, we extended the analysis to the distribution of the private and public sector income. The quantile decomposition reveals that the public sector exhibits a reverse glass ceiling for women workers inferring that the barriers to advancement described by Cotter et al. (2001) may be less prevalent because of the legislation (i.e., the Salary Standardization Law) that sets and updates wage schedules in government. In contrast, the private sector income distribution exhibits a pronounced sticky floor effect which primarily is driven by the unexplained gap at the 10th (0.0838) and 50th (0.1224) percentiles. This unexplained gap in the private sector income distribution outweighs their corresponding explained and interaction gaps provided in Table 8."