The Effects Of Economic Growth On Income Inequality In Middle Income Countries History Assignment Help Ireland

Introduction

Research in the relationship between economic growth and income inequality is an especially important topic in development economics. This topic matters even more as evidenced by being part of the Sustainable Development Goals (SDGs). SDGs are global development goals that were developed to address global development challenges, these goals were then adopted by United Nations members in 2015 building on from the Millennium Development Goals. In total, there are seventeen (17) goals and hundred and sixty-nine (169) targets which member states aim to achieve by 2030. Overall SDG goal 10 aims to reduce inequalities and while target 3 aspires to achieve sustainable income growth of the bottom 40% of the population, within countries. (United Nations, 2015) However, widening income disparities are a concern and have heightened awareness of the need to advocate for economic growth while also ensuring that the benefits of increased wealth are distributed more equally. The United Nations Department of Economic and Social Affairs Sustainable Development Outlook (2021) reports that COVID19 has had drastic impact on global workers’ income, increased global unemployment and thus increased income inequality. Today more than ever the need to address widened income inequality is important. Thus, research and policy solutions that addresses the issue are needed.

Easterly (2007) linked reduced income inequality to periods of sustained economic growth However, research over the years on the topic has remained controversial in that some research have also found out that on the contrary economic growth and the increasing affluence that comes with it have not always resulted in inclusive prosperity, economic opportunity, or improved social indicators for all in developing countries thus income inequality remains a problem (Cingano & Frederico, 2014). Although the relationship between economic growth and income-inequality has remained a subject of interest for years and is still a topic has no clear resolution, the classical Kuznet inverted U-hypothesis remains the yard stick in development economics. Kuznets (1955) claimed that economic growth (GDP) has an impact on the level of income inequality in a country and that the relationship between the two variables is quadratic or U-shaped. This implies that is economic growth increases income inequality and then reduces income inequality as a country achieves high economic growth.

Opponents of this theory claimed amongst others that there was a sample size bias and that the study was based on agricultural economies industrializing. (Barro, 2000) Recently Riveros et., al (2022) have also claimed that Kuznet’s classical inverted U-shaped relationship between income inequality and economic growth may not hold for some regions and have reiterated the need for region, economy, and country specific studies. Subsequent studies claimed that the relationship between economic growth and income inequality in poor countries is negative while the relationship in rich countries is positive (Barro, 2000; 2008). This therefore implies that as the economy grows in poor countries, income inequality reduces and vice versa while in rich countries economic growth results in increased inequalities.

Previous research has taken different forms of approach, methodology and analysis, however the constant amongst these is that the measure of income inequality employed has historically been the GINI Index, while the measure of economic growth was commonly the Gross Domestic Product (GDP) per Capita.

The World Bank (2022) defines GDP per Capita as:

the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars. (GDP Per Capita)

Additionally, the GINI index is defined by the World Bank (2022) as:

Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus, a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality (Gini Index)

Over the years this measure of income inequality though generally accepted as the standard has been criticized as a measure that is not robust enough nor responsive to changes in the top and bottom percentiles of income distribution in an economy thus may incorrectly measure inequality. (Palma, 2011, 2014; Cobham et al., 2015) Palma further suggested that changes in income usually take place in the top and bottom percentiles while the middle percentiles tend to yield little to no response to income changes i.e., changes in GDP per capita. Given that this bracket of income distribution is not sensitive, the GINI Index thus potentially provides biased measure of inequality and thus flawed analysis of the relationship between economic growth and income inequality thus Palma developed the Palma Ratio as a measure of income inequality.

The Organisation for Economic Cooperation and Development (2022, Income Inequality), defines the Palma ratio as “The share of all income received by the 10% people with highest disposable income divided by the share of all income received by the 40% people with the lowest disposable income. Cobham et al. (2015) support Palma’s assertions suggesting that the Gini Index can mask the true extent of inequality since it is increasingly less sensitive at higher levels of inequality as well as being less sensitive to the top and bottom tails of the income distribution. As such, a research space exists where the use of other measures of income inequality other than the Gini Index can be employed.

Although the relationship between economic growth and income inequality has been a subject of research interests for years, it is a topic that still has no clear resolution and therefore holds mixed views. This study does not seek to take away from these previous findings but attempts to add to the body of literature. The study will not use the standard measure of income inequality GINI Index but will use the Palma Ratio as it is potentially responsive to changes that occur in the top and bottom extremes of the income distribution and thus attempt to address the existing research gap. The study will also utilize Real GDP per Capita as a measure of economic growth. It will use the two variables; Palma Ratio as the outcome variable and the Real GDP per capita as the treatment variable to conduct a regression analysis using cross sectional data in a panel of countries to determine the effects of economic growth on income inequality. Additionally, the study focuses on middle income countries as a specific subset of the world economy. Previous studies on middle income countries are limited and some have lumped middle income countries together with the least developed countries and studied them as a single unit “developing countries’’ (Barro, 2000) however middle-income countries are arguably neither rich nor poor and thus research specific to this subset can provide more insight and appropriate policy recommendations.

The study hypothesizes that there is a positive relationship between economic growth and income inequality in middle income countries, thus when the economy grows income inequality increases creating the need for appropriate policy measures which can ensure inclusive growth and propel middle income countries towards attainment of SDG 10.

The rest of the paper includes a review of existing literature which will provide more information on the theoretical and methodological frameworks, this will be followed by the methodology which will indicate data used, variables and estimation. Then I will present the results of the data analysis and provide, conclusion and policy recommendations.

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