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This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.

This research is an attempt to study the empirical relationship between infrastructure and income inequality in Indonesia. It uses regression analysis with panel data set covering 32 provinces in the period of 2007–2013 in order to estimate whether the infrastructure has positive or negative effects on income inequality. We use a conventional income inequality measure, Gini index. The model is estimated by simple pooled OLS, fixed-effect and random-effect models. To overcome the endogeneity problem, infrastructures quantity and quality indicators enter the regressions with one-year lag. We find that road and telecommunication quantities tend to boost income inequality, while electricity quantity, airport quantity, and airport quality have a favorable impact on the distribution of income and help to alleviate income inequality. Whereas, when these different categories of infrastructure are formed as synthetic indices, the relation between these indices and income inequality lends support to the idea that infrastructure increases income inequality.