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PurposeThe purpose of this paper is to explore the effect of growth in different sectors of the economy of developing countries on income inequality and analyze how inflation, as a proxy for monetary policy, makes a proportionate contribution for setting a binding national target for reducing income inequality. The paper examines the existence of a linear or nonlinear effect of inflation and sectoral economic growth on income inequality using a balanced panel data of 92 developing countries for the period of 1990–2014.Design/methodology/approachMethods section includes several steps as below: first, the functional form of the model using panel data for investigating the contribution of economic sectors in income inequality; second, to estimate the relationship between income inequality and sector growth: testing the Kuznets hypothesis; third, to estimate the relationship between inflation and income inequality base on general functional form of the model proposed by Amornthum (2004); fourth, a panel Granger causality analysis based on a VECM approach.FindingsThe statistically significant finding shows that first agricultural growth and then industrial growth have a dominate impact in reducing income inequality in our sample. But, the service sector growth has positive effects. The results confirm the existence of Kuznets inverted "U" hypothesis for industry growth and Kuznets "U" hypothesis for service sector growth. The findings show that sector growth and inflation affect income inequality in the long-run.Originality/valueThis research is an original paper which analyzes the effect of growth in different sectors of the economy of developing countries (agriculture, manufacturing and services sectors) on income inequality and test the Kuznets hypothesis in terms of sector growth and at the same time, examine the existence of a linear/nonlinear effect of inflation and sectoral economic growth on income inequality and test Granger causality relationship between income inequality and sector growth and inflation.

Purpose
The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of 24 developed countries (DCs) and 66 developing countries (LDCs) observed over the period of 1990–2014.


Design/methodology/approach
This paper explores the short- and long-run Granger causality relationship between inflation and income inequality using the Toda and Yamamoto (1995) procedure and a Vector Error Correction Model (VECM) approach. The existence of a nonlinear relationship between inflation and income inequality is confirmed implying as inflation rises income inequality decreases. Income inequality then reaches a minimum and then starts rising again. The findings of this paper show the existence of Kuznets "U-shaped" hypothesis between income inequality and real GDP per capita in DCs group, and the existence of Kuznets' inverted "U-shaped" hypothesis for LDCs group.


Findings
The results indicate that there is no bi-directional Granger causality between inflation and income inequality in the short-run, but, there is bi-directional Granger causality in the long-run for both the DCs and LDCs group. The results help us to assess the effectiveness of monetary policy in reducing income inequality in both the DCs and LDCs group. As a policy implication, monetary policy is often aimed at controlling the annual rate of inflation in the long-run with a short-run focus on reducing output gaps and creating employment. However, managing inflation may have implications for income inequality.


Originality/value
This is original research paper which analyzes the "U-shaped" and inverted "U-shaped" paths of income inequality and real GDP per capita for large sample of two group countries including developed and developing countries, respectively. Also, this paper analyzes the nonlinear relationship between inflation and income inequality in two groups. Furthermore, this paper investigates the short- and long-run relationship between variables. The results are important for policy makers.

The main objective of this article is to empirically examine the short and long-run relationship between real tax revenue and real local government expenditure as well as investigate the relationship between real sales tax revenue and real individual tax revenue and selective variables in Washington, D.C. for the period ranging from 1984-2015. The study uses the Johansen co-integration techniques as well as the bivariate and multivariate vector error correction model (VECM). The results indicate that there is a unidirectional and one-way causality running from real local government expenditure to the real DC's tax revenue in the short and long-run, but not vice versa. The finding indicates that DC's tax revenue changes local government expenditure. As a result, budget deficits can be avoided by implementing policies that stimulate DC's tax revenue. The Granger-causality test shows that DC resident employment does affect real individual tax in the short and long-run, simultaneously. The Granger-causality test shows that DC resident employment, household's population and stock of housing does affect real sales tax revenue in the short and long-run simultaneously. Furthermore, the results of the impulse response function (IRF) indicate that household's population and stock of housing are the major short-run effect on the real individual income tax and real sales tax revenue.