The impacts of sector growth and monetary policy on income inequality in developing countries

Abstract

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.

The Effects of Monetary Policy Shocks on Income Inequality Across U.S. States

“…In all models, the coefficients of the CPI inflation are positively significant. It means that a rise in the CPI inflation, as an indirect effect of monetary policy shocks, can increase income inequality, which is consistent with the results of previous studies (Shiller, 1996; Easterly & Fischer, 2001; Amornthum, 2004; Siami‐Namini, 2019; Siami‐Namini & Hudson, 2019a,b). No matter what measures are used as an income inequality indicator in the estimated models, the effects of CPI inflation on income inequality are similar for all individual measures.…”

“…The results indicated that there is no bi‐directional Granger causality between inflation and income inequality in the short run, but there is, in the long run, for both groups. In another study, Siami‐Namini and Hudson (2019b) analysed the impacts of sectors’ growth and monetary policy on income inequality in a balanced time series panel data of developing countries for the period of 1990–2014. They found that agricultural and industrial sectors’ growth has a dominant impact in reducing income inequality.…”

“…The time series of income inequality measures are available only on an annual‐based frequency, and therefore, the series of the other variables are considered on the yearly basis. The control variables for the cross‐states panel regressions are determined based on the theory and the previous empirical work on income inequality (Roine et al , 2009; Coibion et al , 2012; Neal, 2013; Villarreal, 2014; Siami‐Namini & Hudson, 2016; Siami‐Namini, 2019; Siami‐Namini & Hudson, 2019a,b). The annual data collected from the Federal Reserve Economic Data (FRED) website and the Bureau of Economic Analysis (BEA) website, which include consumer price index (CPI) inflation for all urban consumers, real gross domestic product (GDP), unemployment rate (UN), S&P 500 stock returns (SP), population as a demographic variable (POP), federal funds rate or interest rate as an indicator for monetary policy (I), and money stock (MS).…”

Inflation and income inequality in developed and developing countries

“…Siami-Namini and Hudson (2019) examined the impacts of sector growth and monetary policy on income inequality by using a cross-country panel of 92 developing countries for the period of 1990–2014. They found that agricultural and industrial growth have a negative effect, while service sector growth has a positive effect on income inequality.…”

Panel Method in Hedging: Evidence from The Indonesian Agricultural Sector

“…The agricultural sector has a vital role in national development, including as a source of foreign exchange for the country, contributing GDP, employment, industrial raw materials, sources of food and nutrition, as well as encouraging the movement of other real economic sectors (Devaux, Torero, Donovan, & Horton, 2018;Siami-Namini & Hudson, 2019). Along with its development, companies engaged in the agricultural industry will expand their business by entering into international markets (Amanor & Chichava, 2016;Graeub et al, 2016;Liu, Hertel, Taheripour, Zhu, & Ringler, 2014).…”