The New Evidence on the Gender Wage Gap in Indonesia report from the Asian Development Bank explores how Indonesia’s economic growth and rapid urbanisation in recent years is contributing to the gender income gap. The study examines how monthly wages are distributed between male and female workers and tests whether a wage gap exists between them.
The report highlights the implications of income growth on the distribution of income among male and female workers and on improvements in living standards, particularly in urban areas. The livelihood and welfare of workers depend on labour income, especially in urban residents. From the social equality and egalitarian’s points of view, wages should match marginal productivity of labour as well as skill level. If the gender wage gap exists in Indonesia, the government has obligations to narrow such gap through labour policy reforms from both views.
By focusing on gender wage gap in Indonesia and extending the analysis to examine its relationship with urbanisation, this study contributes to the literature on urbanisation and the gender wage gap, which remains limited, and its implications, which are yet to be analysed.
- Regression results reveal that urbanisation tends to benefit male workers more favourably, in terms of monthly wages, than female workers.
- While the average wage is higher in urban areas, the benefits of urbanisation, in terms of monthly wages, also tend to flow more to male workers rather than female workers.
- The wage gap tends to be wider among younger workers, particularly among those who are underemployed and severely underemployed. It is also greater among public sector workers than those in the private sector.
- A woman’s wage is consistently and significantly lower than a man’s wage in Indonesia due to non-market reasons. On average, a woman’s real wage is 30.8% lower than a man’s — and the gap exists for any age cohort.
- Gender wage gap in Indonesia is mainly due to gender discrimination. An act to equalise opportunity and wages among workers, especially in the public sector, is proposed.
- Tables and figures
- Literature review
- Data and stylised facts
- Distribution of real wages and hours worked in urban and rural areas
- Distribution of hours worked by urban and rural workers
- Full employment, underemployment, and severe underemployment
- Predictive margins of real wages
- Empirical model and results
- Labour force participation selection bias
- Selection bias correction based on the multinomial logit model
- Oaxaca-blinder decomposition
- Empirical results
- Summary findings and policy recommendation