We estimate the long-run cointegrating relationship between schooling and income inequality using annual data from 48 contiguous U.S. states between 1946 and 2000. Our study contributes to the literature in several ways in terms of data and empirical methodology. First, we take into account integration and cointegration properties of the data and estimate the cointegrating relationship between schooling and income inequality using Fully Modified OLS (FMOLS) following Pedroni (2000, 2001). Second we investigate the direction of the causality. Using several different measures of income inequality, we find that an increase in the average level of schooling decreases income inequality in the long-run and (Granger) causality runs from schooling to income inequality, not the other way around.
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For a meta analysis of schooling and income inequality see Abdullah et al. (2005).
See Sylwester (2002b) for a theoretical model of public spending on education and income inequality.
CCE does not correct for endogeneity.
Unfortunately, we are unable to control for several independent variables used in studies investigating income inequality such as share of population living in urban areas and share of female headed families in population because of data unavailability. Data used in income inequality studies are mostly from the Current Population Survey (CPS) of the Census Bureau and state level data are available only after 1977.
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Cavusoglu, T., Dincer, O. Schooling and income inequality in the long-run. J Econ Finan 43, 594–606 (2019). https://doi.org/10.1007/s12197-018-9459-5
- Income inequality
- Panel cointegration
- U.S. states