Abstract

Purpose. Comparable data on distribution of family income provide reference point for determining economic performance of any country, opportunity to assess effects of income inequality and poverty drivers that are either country- or region-specific. This study analysed the effectiveness of composite indices of public spending on family benefits, labour productivity, macroeconomic performance indicators and moderating factors in reducing income inequality and poverty gap in the Group of Seven (G7) countries from 1980 to 2019. Methodology. The study employed fixed effects Least Squares regression model in panel environment within the framework of empirical econometric methodologies. The composite indices comprised public spending on family benefits in cash and kind, unemployment allowance payments, tax on personal income, labour productivity, harmonised unemployment rate, consumer price index, real GDP growth rate, GDP per capita and per hour worked, fertility rate and trade. After graphical analysis of the data, order of integration was via unit root tests. Hausman test was carried out to choose between fixed and random effects models. Subsequently, parameters of the models were estimated and evaluated for significance at the 0.05 critical level. Findings. The results showed that percentage changes in income inequality and poverty gap indices differed for same percentage change in components of the composite indices. Some variable-specific percentage changes in income inequality and poverty gap were statistically significant, while others were not. However, the overall percentage changes was statistically significant. The paper concluded that while some specific effectiveness of the explanatory variables in reducing income inequality and poverty gap was not significant, their joint effectiveness significantly reduced poverty. Therefore, it is pertinent that family-oriented fiscal policy thrusts should be strengthened and sustained so as to continually reduce income inequality and, ultimately, narrow poverty gap in the countries. Limitations. The study considered the G7 countries for a period of 40 years. The limitations were that the variables considered to influence income inequality and poverty gap in the countries were both exhaustive. Also, the results were conditioned to the method used, and different methods can alternatively be used by other researchers and the results compared with this. Originality. The study is original research paper. It has neither been published in any other peer-reviewed journal not under consideration for publication by any other journal.

Highlights

  • Considerable reduction in income inequality and poverty, through peoplecentred fiscal policy thrusts and increased productivity and national output, has been one of the main objectives of governments of most countries all over the world

  • GDP per hour worked and labour productivity are the productivity variables, while harmonised unemployment rate, consumer price index, real GDP growth rate, GDP per capita and trade are relevant macroeconomic variables, and fertility rate and trade moderate the influence of the variables on income inequality and poverty gap

  • Components: Fertility rate (FTR), which indicates the rate at which family size changes, and trade to proxy the influence of trade globalisation on poor family-oriented fiscal policy thrust in the harmonised unemployment rate (HUR): Unemployed family members actively looking for work but cannot find any

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Summary

Limitations

The study considered the G7 countries for a period of 40 years. The limitations were that the variables considered to influence income inequality and poverty gap in the countries were both exhaustive. The results were conditioned to the method used, and different methods can alternatively be used by other researchers and the results compared with this. It has neither been published in any other peer-reviewed journal not under consideration for publication by any other journal

INTRODUCTION
LITERATURE REVIEW
Empirical Studies
METHODOLOGY
Specification of Models for Analysis
Graphical Analysis of the Data Series
Time Series Properties of the Data Sets

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