Inequality and public spending worldwide: A study with panel data and methodologies.

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Cecibel Jiménez
Jorge Flores-Chamba

Abstract

In the study of socioeconomic problems such as poverty and inequality, it is inevitable to analyze the role of the public sector; Hence, it is important to mention that, for example, in markedly unequal regions such as Latin America and Sub-Saharan Africa, final consumption by governments has shown an average growth rate of more than 2\% in the 2000-2020 period, according to World Bank data. . In this sense, the objective of this research is to examine the causal link between inequality and public spending for 89 countries during 1980-2016. Using cointegration techniques for panel data, the results found indicate the existence of a long-term equilibrium between the two variables worldwide and by groups of countries. Finally, the results of the causality test show that there is a two-way causality between inequality and public spending in high-income countries. In upper-middle, lower-middle, extremely low, and low-income countries, there is a one-way causality between inequality and public spending. One of the policy suggestions derived from this research is that in most of the countries analyzed, increasing public spending contributes to reducing inequality.

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How to Cite
Jiménez, C., & Flores-Chamba, J. (2022). Inequality and public spending worldwide: A study with panel data and methodologies. Revista Económica, 9(2), 43–54. Retrieved from https://revistas.unl.edu.ec/index.php/economica/article/view/1209
Section
RESEARCH ARTICLES

References

Akaike, H. (1974) A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, 19, pp.716-723.

Banco mundial. (2017). World Bank Open Data | Data. Retrieved March 4, 2020, from https://datos.bancomundial.org/

Blundell, R.& Etheridge, B. (2010). Consumption, income and earnings inequality in Britain. Review of Economic Dynamics, 13, (1), pp. 76-102.

Breitung, J. (2002). Nonparametric tests for unit roots and cointegration. Journal of Econometrics, 108(2), 343-363.

Glomma, G., & Ravikumar, B. (2003). Educación pública y desigualdad de ingresos. European Journal of Political Economy.

Heer , B., & Scharrer , C. (2018). Las cargas específicas por edad de las fluctuaciones a corto plazo en el gasto público. Journal of Economic Dynamics & Control.

Pistoresi, B., Rinaldi, A., & Salsano, F. (2017). El gasto del gobierno y sus componentes en Italia,1862-2009: impulsores e implicaciones políticas. Journal of Policy Modeling.

Cain, S., Hasan, R., & Magsombol, R. (2010). Contabilización de la desigualdad en la India: evidencia de los gastos del hogar. World Development.

Cabrera, M., Lustig, N., & Moran, H. (2015). Política fiscal, desigualdad y la división étnica en Guatemala. World Development.

Charlesa, M., & Lundy, J. (2013). Los habitantes locales: el consumo de los hogares y la desigualdad de ingresos en las grandes áreas metropolitanas. ScienceDirect.

Chatterjee, A., Chakrabarti , A., Ghoshc, A., Chakraborti , A., & Nandie, T. (2016). Características invariables de la desigualdad espacial en el consumo: el caso de la India. Physica A.

Dickey, D., Fuller, W. A., (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49, 1057-1072.

Dickman, S., Himmelstein, D., & Woolhandler, S. (2017). La desigualdad y el sistema de salud en los Estados Unidos. crossmark.

Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450-1460.

Elgin , C., Goksel , T., & Gurd, M. (2013). Religión, desigualdad de ingresos y el tamaño del gobierno. Economic Modelling.

Getachew, Y. Y. (2012). Efectos distributivos de las elecciones de políticas públicas. Economics Letters.

Getachewa, Y., & Turnovsky , S. (2015). El gasto público productivo y sus consecuencias para la desigualdad de crecimiento. Research in Economics.

Gregorini, F. (2015). Geografía Política y Desigualdades de Ingresos. Research in Economics.

Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the Econometric Society, 1251-1271.

Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74.

Jin, Y., Li, H., & Wu, B. (2011). Desigualdad de ingresos, consumo y búsqueda de estatus social. Journal of Comparative Economics.

Justino , P., & Martorano, B. (2018). Gasto en bienestar y conflicto político en América Latina, 1970-2010. World Development.

Kao, C., Chiang, M. (2000). On the estimation and inference of a cointegrated regression in panel data. Advances in Econometrics, 15, pp. 179–222.

Kim, D. (2015). Las asociaciones entre el gasto social estatal y local de EE. UU., La desigualdad de ingresos y la mortalidad individual por todas las causas y causas: el Estudio Nacional de Mortalidad Longitudinal. Preventive Medicine.

Levin, A., Lin, C. & Chu, C. J. (2002). Unit root tests in panel data: Asymptotic and nite-sample properties, Journal of Econometrics, 108, pp. 1-24.

Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and statistics, 61(S1), pp. 631-652.

Martín-Baró, I. (1985). Acción e ideología. San Salvador: UCA.

Modalsli, J. (2017). La dispersión regional de la desigualdad de ingresos en la Noruega del siglo XIX. Explorations in Economic History.

Neal, T. (2014). Panel cointegration analysis with xtpedroni. The Stata Journal, 14(3), pp. 684-692.

Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653-670.

Pedroni, P. (2001). Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics, 83(4), 727-731.

Petrei, A. H. (1987). El gasto público social y sus efectos distributivos: un examen comparativo de cinco países de América Latina. Programa ECIEL.

Phillips, P. C., & Moon, H. R. (1999). Linear regression limit theory for nonstationary panel data. Econometrica, 67(5), 1057-1111.

Phillips, P., Perron, P. (1988). Testing for a unit root in time series regression. Biometrica, 75, 335-346.

Pistoresi, B., Rinaldi, A., & Salsano, F. (2017). El gasto del gobierno y sus componentes en Italia,1862-2009: impulsores e implicaciones políticas. Journal of Policy Modeling.

Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709-748.

Wooldridge, J.M., (2002). Econometric Analysis of Cross Section and Panel Data. MIT Press, Cambridge, MA.

World Bank, 2017. World Development Indicators. Washington D.C. Available on. https://data.worldbank.org/data-catalog/world-development-indicators.

Zoundi, Z. (2017). CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach. Renewable and Sustainable Energy Reviews, 72, pp. 1067-1075.