Globalization and income inequality: A panel data analysis of 37 developing countries in Africa

Introduction

The effects of globalization on income inequality had been a source of debate among researchers and policymakers. The background of the debate on globalization; the gainer or loser within and between countries of the world is of utmost concern for economists (Ogunyomi et al., 2013) [24] . Globalization was generally perceived as a tool for promoting global economic growth, while Stiglitz, (2003) [33] and Mahnoor and Kashif (2016) [19] criticized it for growing income inequality, difficulty in competition, and social and environmental degradation, especially in developing countries like Africa. Globalization is a multidimensional phenomenon that captures all aspects of the social, political, economic, and cultural domains. It is a comprehensive process of economic integration which develops international mobility of national resources and increases the interdependency of the national economy (OECD, 2005). Many scholars in the last decade had reported a positive relationship between globalization and income inequality (Bergh and Nilsson 2010 [1] ; Jaumotte et al., 2013 [14] ; Dabla-Norris et al., 2015 [3] ; Gozgor and Ranjan 2017 [10] ; Dornet al., 2018) [5] , especially in emerging countries. These positive effects of globalization are vividly seen among Asia Tigers like Japan, China, Singapore, and South Korea. There markable growth of these countries of East Asia rose per capita income by eightfold and raised hundreds of millions out of poverty (OECD, 2005). However, most African countries that had embraced globalization had resulted in structural economic divergence by widening income inequality, collapsed infant industries because of the dependency on international theory, and less economic convergence informed by technology transfer, increased market size, and relative employment generation (Ogunyomiet al., 2005). The actual benefit of globalization to African countries faces more uncertainty due to serious data concerns, which are more likely to be subject to measurement errors and lack of data records in the time past (Deaton, 2005 [4] ; Jenkins, 2015) [15] . This lack of economic facts on the effects of globalization and income inequality in Africa has manmade difficult for an effective economic policy response to the problem of inequality in the continent. This calls for a sound understanding of the key factors that drive the inequality trends.

Various factors are likely to play a role, these include globalization, real Gross Domestic Product (GDP), age dependency ratio, human capital, skill-biased technological change, economic reforms such as deregulation in financial markets, rolling back the welfare state, or reforms of the tax system, the growing role of telecommunication and the mass media, growing regional disparities within countries and many more (Dorn et al., 2018) [5] . This research established the relationship between globalization and income inequality in Africa, using expanded and recently updated data. The impact between globalization and its sub-indicators was differentiated on i) market income inequality and ii) net income inequality i.e. income inequality after taxes and transfers Gini indices taken from Solt's (2016) Standardized World Income Inequality Database ((SWIID7_1). Due to the multifaceted nature of globalization, the KOF index of globalization such as the economic, trade, social, and cultural globalization index (Dreher 2006 [6] ; Dreher et al., 2008) [7] , was used to see the effect of each on income inequality in Africa. The rest of the paper is organized as follows: Section two concisely reviews the relevant literature on globalization and income inequality. The third section presents models for estimating the influences of globalization on income inequality along with a description of the data and variables applied in the paper. The results of the models are interpreted in section four. Conclusions and policy considerations are presented in the final section.

Methodology

The baseline panel model was estimated following the characteristic model (Park 2017) [25] had utilized, where countries are described by i and 5-year-periods by t as follows:

Where Gini is the Gini index, an indication of income inequality 𝑙𝑛 𝑌 Is shorthand for the logarithm of income of per capita GDP, which generally represents the level of economic development? 𝑢 𝑖𝑡 is the between-entity error and 𝜀 𝑖𝑡 is the within-entity error. All variables are included as averages in each of the nine periods (t = 1..., 9). A positive sign was assumed for 𝑎 1 while a negative sign is predicted for𝑎 1 .

Other explanatory variables were included in the baseline model along with the income variables to better analyze income inequality. where 𝑙𝑛𝐻𝐶𝐿 represents the logarithm of the Human Capital Index, 𝑙𝑛𝐾𝑂𝐹𝐿 is the logarithm of the KOF globalization index,𝑙𝑛𝑃 is the logarithm of population, 𝑙𝑛 𝐴 is the logarithm of age dependency ratio and EFI is the logarithm of economic freedom index. [8] , PWTv9.0 Real Gross Domestic Product (USD)

Results and Discussions

Human capital index Index based on the rate of return to education and average years of schooling Population World Development Indicators (WDI, 2017) [35] Total population in millions Age Dependency Ratio World Development Indicators (WDI, 2017) [35] Age Dependency Ratio Economic Freedom Index Gwartneyet al., (2015) Index of economic freedom

Relationship between income level and income inequality (Baseline model)

Table 2 below showed the regression results for estimating the income level and income inequality. The empirical results validate the Kuznets hypothesis (Kuznets 1955) [17] , a pioneered study that claimed that income inequality would first increase within poor countries as their economies grew through urbanization and population growth but after some point, inequality would fall as a result of subsequent political factors and economic policies. An inverse Ushaped curve relationship for Gini Net while Gini Market reveals a U-shaped curve. The entire coefficient for Gini Market was statistically significant at 5%. The finding showed that the relationship between income inequality and income in Africa was of a U-shaped curve relationship. The R 2 tends to be very small as a result of the nature of the panel data used for the study.

Relationship between Globalization and Income inequality

Table 3 below showed the relationship between Gini income inequality and globalization index with other covariate variables. The result showed an improvement in the R2 statistic, especially in the Gini Market. The result of the Gini market confirmed the finding of previous studies (Ogunyomiet al., 2013 [24] , Ogbeide and Agu 2015 [23] ) indicating a positive relationship between globalization and income inequality while the result of the Gini net was negative and statistically insignificant. The only significant variable in the Gini net is the age dependency ratio, which indicates a negative relationship between the age, dependency ratio, and income inequality but was not significant in the Gini market. The globalization index was found to be positively significant in the Gini market while the population was found to be negatively significant in the Gini market. This finding is in line with Dorn et al., (2018) [5] , who discovered that the coefficient of the globalization index is larger when the Gini market index (before taxation and transfers) was used than when the Gini net inequality index (after taxes and transfers) was used as the dependent variable. 4 below showed the results of Random Effects and OLS regression for the individual globalization indicators using economic, trade, social, political, and cultural dimensions of the KOF globalization index. The coefficient of economic globalization was positive and statistically significant at the 5% in both forms of Gini income inequality used. The coefficient of the trade globalization index was positive and statistically significant in the Gini market but not statistical significance in the Gini net income inequality. The coefficient of social globalization was negatively related to income inequality in both Gini measures but not statistically significant in both Gini income inequality measures. Political globalization was negative and statistically significant at 5% related to both income inequality measures. Also, cultural globalization was negative in both Gini measures but statistically significant in the Gini market income inequality measure. In the overall model, the coefficients of the Gini market are more robust than that of the Gini net.

Sensitivity Tests

The sensitivity (Hausman) test was carried out on the Fixed and Random Effects Model for the study. The probability of the chi (2) was 0.923 and 0.766 for the Gini net and market respectively, (< 0.005) i.e. not significant, hence random effect. The Breusch and Pagan Lagrangian multiplier test for random effects for all the models was significant; hence we accept the null and conclude that random effects were appropriate.

Conclusion and Recommendations

This study examined the relationship between globalization and income inequality in 37developing countries in Africa. Globalization was generally perceived as a tool for promoting global economic growth and social progress, but this view has been criticized by some prominent scholars for escalating income inequality. Though, globalization is a multidimensional phenomenon that captures all the aspects of social, political, economic, and cultural domains.

Findings from the study validate the Kuznets' U hypothesis for the relationship between income level and income inequality in Africa. The study also showed a negative relationship between the total globalization index and income inequality after taxes and transfer for the Ordinary Regression System (OLS). The result for the globalization sub-indicator showed a positive significant relationship between economic globalization with both measures of income inequality measure (Gini net and Gini market), while political globalization indicated a negative relationship. The results of trade and cultural globalization were mixed based on the type of Gini income inequality used, while social globalization did not indicate any statistically significant relationship to income inequality regardless of the Gini income inequality measure used.

Based on the findings from this study, African countries should demonstrate good governance levels in terms of fiscal policy, protectionist domestic policy, political stability, and sound qualitative education to help in human capital development and sustainable economic globalization. Also, they should strengthen their institutions to promote policy frameworks that will increase income levels while steps should be taken to control the ever-increasing population and age dependency ratio. There are many issues to be addressed regarding globalization and income inequality. Hence, further study should focus on other measures of inequality since this study used the Gini coefficient. Also, the area of information communication technology (ICT) and mobile phone data that are not available will be a good area of research interest as they reduce income inequality.

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