Introduction: Economic Inequality and Growth
In recent years, the increase in economic inequality in both advanced and emerging economies has garnered significant attention, sparking numerous debates in economic and political circles. At the heart of social science inquiries is the critical question of whether economic inequality acts as a catalyst or an obstacle to economic growth. Today, we will explore the impact of wealth inequality on economic growth, considering the hybridism and heterogeneity of countries.
Especially after the 1980s, there has been a significant escalation in wealth inequality globally, affecting about 70 percent of the world’s population. Moreover, over the past few decades, wealth has become increasingly concentrated in the hands of a few global elites. Billionaires such as Microsoft founder Bill Gates, Elon Musk, and investment phenomenon Warren Buffett play a substantial role in the global economy.
Theoretical Review
Numerous transmission mechanisms connecting economic inequality to economic growth have been uncovered by theoretical investigations. Proponents of inequality’s growth-promoting effects, such as Kalecki and Kaldor, argue that inequality stimulates capital accumulation, thereby encouraging economic growth. Additionally, this line of reasoning is supported by the notion that income disparity incentivizes individuals to enhance their productivity through education, financial risk-taking, and migration to more productive sectors.
Empirical Review
Empirical investigations into the inequality-growth nexus present a spectrum of findings, reflecting the theoretical debate’s inconclusiveness. Generally, studies in this area fall into four main categories: those finding positive, negative, no significant, and non-linear connections between inequality and economic growth, highlighting the disparate conclusions drawn from empirical data.
Several researchers have found a positive link between economic growth and income inequality. Li and Zou (1998) expanded on Alesina and Rodrik’s (1994) work by analyzing how public policy affects this relationship, using fixed- and random-effects models to show a positive impact of inequality on growth.
In contrast, Alesina and Rodrik (1994) identified a negative relationship between inequality and growth. They later found that higher inequality can hinder growth by reducing social cohesion and increasing political instability, both of which disrupt economic performance. On the other hand, Benos and Karagiannis (2018), using 2SLS and GMM with U.S. data from 1929 to 2013, found that growth is unaffected by changes in inequality. Castello-Climent (2010) noted that inequality impacts growth positively in developed countries but negatively in less developed ones.
Surrogate Model
Although economic theory often suggests that the relationship between variables such as inequality and growth is inherently nonlinear, using a linear surrogate model enables us to derive a quantitative coefficient that elucidates the relationship between these variables in a more straightforward manner. Therefore, to further enhance the interpretability of the results produced by the XGBoost model, a surrogate model is employed. The primary purpose of this approach is to approximate the complex, non-linear relationships learned by the XGBoost model with a simpler, more interpretable linear model, while still benefiting to some extent from XGBoost’s advantages.
Validity of Politically Connected Wealth Inequality
To assess whether politically connected billionaire wealth is a reasonable proxy for the importance of political connections and cronyism in a country, one must examine the extent to which this measure aligns with other proxies, such as the prevalence of corruption in a society. One source of data on corruption is the aforementioned ICRG dataset.
Regarding government corruption, data are available annually for 100 to 140 countries from 1984 through 2009. By examining the relationship between politically connected wealth inequality and the ICRG corruption score for all countries with billionaires, using specifications for each individual year, one can observe that politically connected wealth inequality and the ICRG index of corruption are strongly and positively correlated. Countries that are more corrupt tend to have a higher fraction of society’s resources controlled by politically connected billionaires. In contrast, politically unconnected billionaire wealth, normalized by GDP and total billionaire wealth, is not correlated in the same manner.
Concluding Remarks
A central question in the social sciences is whether inequality in control over a society’s resources facilitates or hinders economic growth. The issue has been intensively studied but remains unresolved, partly because theoretical arguments have largely focused on the distribution of wealth, while empirical studies have often relied on the distribution of income as a proxy. This gap can be bridged by deriving the first global measure of wealth inequality, focusing on the concentration of wealth at the very top of the pyramid and estimating its effect on economic growth.
Finally, the policy debate about sources of economic growth should focus on the distribution of wealth rather than the distribution of income. Particular attention should be paid to politically connected concentrations of wealth as a potential cause of slower economic growth. Further research in this area is needed.
