Poverty and Inequality Analysis
Although in general less prevalent than other developing countries at similar stage of development, the problem of child labor in Indonesia is significant. Like in other countries, this study finds that there is a strong link between the child labor phenomenon and poverty. The profile of child labor largely mirrors the profile of poverty. Furthermore, poverty is found as an important determinant of working for children.
Although consumption expenditure data is crucial for assessing the level of people’s welfare and calculating important welfare measures such as the poverty headcount rate, collecting such data requires significant time and effort. In this study, we experiment with three approaches to predict consumption expenditure and poverty at household and aggregate level as simpler alternatives to using consumption expenditure.
This study investigates regional and ethnic inequality in Indonesia from five dimensions: access to education and health facilities, education outcome, health outcome, voice, as well as income and consumption. We believe this is the first comprehensive study that looks at ethnic inequality in Indonesia. We find systematic inequality between urban and rural areas, but not between ethnic groups.
This study extends the literature on the relationship between economic growth and poverty reduction by differentiating growth and poverty into their sectoral compositions and locations. We find that growth in the rural services sector reduces poverty in all sectors and locations. However, in terms of elasticity of poverty, urban services growth has the largest for all sectors except urban agriculture.
Most of the unemployed in Indonesia are young and inexperienced, still live with their parents, and have at least 12 years of education. Starting with the premise that efforts to reduce unemployment should take into account the characteristics of the unemployed, we develop a model to look at the impact of different sectors and locations of economic growth on urban, rural, and national employment using a provincial level panel dataset.
