The view of labor economists that changes in factor supplies do directly affect factor returns even if commodity prices are set on world markets is justified in this scenario. Table 19 shows the effects of human capital (from column 1 to 2a) and financial development (from column 3 to 4a) on the economic growth for UHC. Empirical evidence shows that proxies used as both human capital and financial development indicators do not significantly affect economic growth. Although the first stage of the credit markets imperfections channel is confirmed in these countries, unlike LLMC, the validity of the channel cannot be proven because these variables do not have a significant effect on economic growth. 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.

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In countries with high fertility rates, economic growth is expected to decline due to diminishing capital per capita. The relationship between income inequality and fertility rate is explained by education level. While low-income families have more children and low investment in education, the opposite will happen for sasol core values affluent families. Therefore, it is stated that in countries with high-income inequality, increasing fertility rates will reduce economic growth (Galor & Weil, 1996; Galor & Zang, 1997; Kremer & Chen, 2002; De La Croix and Doepke, 2003).

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For it to go down, incomes in low-income households need to grow faster than inflation – the higher the growth, the larger the reduction. Put simply, this shows whether or not lower-income households are poorer than in the past. Given incomes are falling in the central https://www.absa.co.za/ and weak scenarios, we would expect rising absolute poverty under both these scenarios, but falling absolute poverty in the very high employment and growth scenario, and the strong economy scenario. Poverty is made up of a higher proportion of pensioners and a lower proportion of working-age individuals in the very high employment and growth scenario compared to the central scenario.

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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 developing countries. The validity of the political economy channel is also examined in many empirical studies (Persson & Tabellini, 1994; Alesina and Rodrick, 1994; Babu et al., 2016; Chletsos & Fatouros, 2016; Castells-Quintana & Royuela, 2017; Gründler & Scheuermeyer, 2018; Le & Nguyen, 2019; Ciegis and Dilius, 2019).

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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. There are few studies in the empirical literature questioning the positive impact of income inequality on economic growth. While income inequality positively affects human capital (Chletsos & Fatouros, 2016), contrary to the theory it can have a negative effect on savings and investments (Nel, 2003) and similarly on patents (Braun et al., 2019). As stated in the positive channel, the fact that the positive effect of income inequality on R&D and innovations cannot be determined is explained by the financial development level of the country, and developed financial systems can reduce the negative effect.

• However, in models where the redistribution is significant (columns 4 and 4a), the coefficient is positive, similar to LLMC.
• Greater inequality might also reduce growth if it leads to political instability and social unrest (Alesina – Perotti 1996; Keefer – Knack 2002).
• The effect of income inequality on growth is significantly negative in most models (except columns 2 and 2a).
• The underdeveloped financial systems in low-income countries may also be the cause of the negative effect (Braun et al., 2019).

Also, in these countries with low financial development, it may not be possible to collect taxes effectively and direct them to economic activities. Although the effect of political instability on economic growth is negative for both country groups, its relation to income distribution is different. When the two group estimates are interpreted together, the results imply that the relationship may not be linear, as Blanco and Grier (2009) stated.

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.

Extensive literature shows that both the level and composition of public expenditures and revenues have implications for economic development. The discussion on the short-term impacts of public finance decisions was especially active after the 2008 global and the subsequent European financial and economic crises, when several countries implemented fiscal consolidation strategies. This literature is frequently referred to as the ‘fiscal multiplier’ discussion (e.g. Auerbach – Gorodnichenko 2012; Blanchard – Leigh 2013).

The results of the credit markets imperfection channel in Table 11 are similar to the results in LLMC. The effect of inequality and credits on education is significantly negative (except column 2) and positive (except columns 6 and 10), respectively. These results provide evidence of the validity of the first stage of the credit markets imperfections channel. On the other hand, the effect of inequality on human capital (columns 1–4) shows that the positive channel stated in theory does not apply here as in LLMC. Furthermore, as in LLMC, the tertiary as the dependent variable is used to examine credit markets defects and human capital channels.

Therefore, examining countries with varying levels of development together may cause misleading results. The analysis is conducted using the System Generalized Moments Method by taking https://satrix.co.za/ the 5-year averages of the data for the period 1980–2017. The fourth section includes the analysis results and growth estimates on the channel variable of inequality. On the other hand, it can be said that the studies suggesting that income inequality is harmful to economic growth are more common.