The fact that the channel is not valid in these countries may be due to the fact that human capital, contrary to theory, does not increase economic growth, such as the Ciegis and Dilius (2019) study. Also, the results here differ from LLMC shows that the validity of this channel varies according to the income level of the countries, and the evidence is more substantial in developing countries. Furthermore, it is confirmed in all models, as in LLMC, that the direct effect of income inequality on economic growth is negative. On the other hand, it can be said that the studies suggesting that income inequality is harmful to economic growth are more common.
Similarly, the inflation rate has a significant negative effect on growth, except for a few models. The fact that a high inflation level, as an indicator of macroeconomic instability, harms the economic growth in these countries supports Stockman (1981). Similar results are obtained in other studies such as Iradian (2005), Chletsos and Fatouros (2016), Babu et agc africa gold capital al. (2016), Braun et al. (2019), using inflation as a control variable in the inequality-growth empirical literature.
Finally, differences in income distribution provide incentives for factors such as education, investment in physical capital, risk-taking, and hard work. Finally, the estimation results for positive channels suggest that inequality encourages growth are far from theoretical expectations regardless of the income level of countries. It is observed that income inequality does not promote human capital investment and innovative activities.
The study results indicate that the relationship between income inequality and economic growth is quite complex. Although there is evidence that greater inequality has detrimental effects on economic growth, it appears that this inference cannot be generalised when countries’ income levels are taken into account. According to the estimation results, regardless of the income level of the countries, while inequality increases the fertility rate, it affects human capital negatively, both directly and through credit market imperfections. The negative impact of these channels on economic growth is more pronounced in relatively low-income countries.
Finally, as expected, the effect of the fertility rate on economic growth is negative (columns 5 and 5a). Income inequality increases the fertility in UHC, and as the fertility rate increases, income inequality harms economic growth. The negative impact of inequality on human capital in these countries also supports the validity of the fertility channel expressed by De La Croix and Doepke (2003). In addition, Also, a https://www.liberty.co.za/ remarkable result here is that the effect of fertility on economic growth is significantly lower than LLMC. Therefore, the increase in the fertility rate in low-income countries damages to economic growth more than in UHC.
Similarly, although there are no direct effects on growth, economic growth improves in low-income countries due to the positive impact of developed financial systems on human capital. Therefore, as stated by Demirguc-Kunt (2012), these countries primarily need stable macroeconomic policies and strong legal and information systems for the development of the financial system. Implementing regulations to remove restrictions on bank activities and improving infrastructure to ensure access to financial services by large masses are some of the important roles of the government. Thus, economic growth can be improved with increased human capital investments in https://www.sanlam.co.za/ developing countries. Similarly, in the political economy channel estimates, the findings differ according to the countries’ income levels. While inequality does not affect redistribution in low-income countries, it positively affects developed countries.
Results for patent are similar to LLMC; contrary to theory, the effect of inequality on the patent is significantly negative in all estimates. Therefore, income inequality does not support https://satrix.co.za/ innovative activities contrary to expectations, but the same interpretation cannot be made for the saving rate, and the results are different from LLMC. As income inequality rises, saving rates increase (except column 6), these results support the Classical approach. The marginal propensity to save for the rich people in UHC is higher, so total savings increase as inequality increases.
It is expected that the increase in investment rates will positively affect the economic growth. Trade openness can stimulate economic growth by increasing total factor productivity through technological expansions and increased competition (Grossman & Helpman, 1991; Rivera-Batiz & Romer, 1991). There are explanations about positive effects (Tobin, 1965), negative effects (Stockman, 1981) or no effects (Sidrauski, 1967). Inflation is also preferred as the explanatory variable of growth in empirical studies examining the impact of income inequality on economic growth. (Babu et al., 2016; Barro, 2000; Braun et al., 2019; Castelló-Climent, 2010; Chletsos & Fatouros, 2016; Gründler & Scheuermeyer, 2018; Iradian, 2005). In the models for the UHC, the lag of GDP per capita is also included as a measure of the initial stage of development to take into account the convergence hypothesis.
These results indicate that as income inequality increases, human capital will decrease, but as financial development increases, human capital will increase. Thus, it provides evidence to the validity of the first stage of the credit markets imperfections channel. On the other hand, only the effect of inequality on human capital (columns 1–4) shows that the positive channel is not valid.
