The association of income inequality with economic growth was brought to attention with the research work of modern economist Simon Kuznets. He proposed that economic growth initially increases inequality in the early stages of development. However, in the later stages of development the effect inverts and any further increase in economic growth decreases income inequality bringing an equalizing effect. This gave rise to the famous inverted-U hypothesis. (Kuznets, 1955) Following Kuznets, Kaldor proposed a reverse relationship suggesting that unequal distribution of income can result into economic growth. He emphasized the role of income distribution of a society that is divided into different classes each having its own propensity to save and invest, highlighting the role of saving-income ratio and the investment-income ratio in the economic development of a country. As greater savings leads to greater investments and capital accumulation, a necessary condition for long-term economic growth. (Kaldor, 1955-56) (Kaldor, 1957)
Both Kaldor and Kuznets’s work established a trade-off between reducing inequality and promoting economic growth. (Forbes, 2000) Simultaneously, Solow’s income growth theory of convergence influenced international policy on income distribution and growth. At the heart of the theory was the assumption of diminishing returns to capital investment. He argued that with low initial capital and labor productivity, growth in less developed countries (LDCs) would be much faster than developed nations; as LDCs progress towards optimum utilization. Hence, leading to convergence. (Solow, 1956)
It is important to note that much of these policies were influenced highly by political and ideological factors. As Kuznets’ work promoted industrialization and capitalism within a country. Solow’s work promoted liberalization on international scale, where it was proposed that free-trade and foreign investment would lead to convergence in income. Along with, the comparative advantage theory, it became the theoretical underpinning of globalization. (Stiglitz, 2002) The final outcome of this Kaldor–Kuznets–Solow consensus was a policy mind-set that advocated that inequality induced growth, further growth reduced inequality, and by pursuing growth all nations would converge to the same economic development path. The powerful influence of this consensus has created something analogous to a multi-pronged approach for neoclassical growth theory and its application. This laid the foundation for several upcoming studies in the academic world.
The next six decades saw flourishing research on inequality, income distribution and its effect on growth. However, the results were ambiguous, contradictory, and inconclusive. Some studies support positive overall impact of inequality on growth while others predict a negative impact of inequality on growth. For instance, Ahluwalia in his 60 countries (of which 40 were developing) cross-sectional study proves that the Inverted-U Hypothesis proposed by Kuznets holds true. The income inequality and growth had non-monotonic relationship as the coefficients of logarithm of GNI per capita of the multivariate regression were significant and the projected opposite signs necessary for forming an inverted-U shape. (Ahluwalia, 1976)
The empirical works were mostly cross-sectional due to the lack of availability of time-series data at the time. Studies found that up to 1970s, not only US but most of OECD countries experienced an inverted-U curve. Inequality fostered growth; this growth then translated into reduced income inequality. However, the validation of the inverted-U hypothesis was less clear-cut in the less developed countries. Moreover, it was found that capital market imperfections had negative impact on growth and redistribution of income had a positive impact on growth. (Aghion, Caroli, & Garcia-Penalosa, 1999)
The studies supporting positive relationship were based on 1) higher savings rate (Kaldor, 1955-56) and 2) growth-inducing incentives based on inequality, wherein the gap between the rich and poor promotes risk-taking, hard work and entrepreneurial spirit; increasing labor productivity. (Mirrlees, 1971)
However, several scholars have observed various transmission channels through which inequality can have a negative and a rather limiting effect on the economic growth of a country. It was observed that countries with greater income per capita have more equal distribution of income and smaller wage differentials. Countries with more equitable distribution of wealth grow more rapidly and have higher income level in the long run. The wealth distribution affects economic growth especially considering the capital market imperfections (short run impact) and indivisibility in investment on human capital (long-run impact). Thus, the economic growth of a country is a function of the initial distribution of wealth, more specifically, the percentage of people in a country who have enough wealth to invest in human capital. Investment in human capital seemed to have proven to be an important factor in both growth and income distribution of a country. This highlights the importance of a huge cohort of middle-class in economic growth as they can enable the economy to transition from the agricultural to industrial or service-sector dominated economies. (Galor & Zeira, 1993)
Several studies have used a political economy approach to define a channel that shows a negative relationship between inequality and growth. Factor ownership of median individual and tax rates, redistribution policies, etc., play a crucial role as a channel. These studies suggest that increased inequality in income and land distribution are negatively associated with subsequent growth. This can be due to redistributive pressures and higher taxation. (Alesina & Rodrik, 1994) (Persson & Tabellini, 1994) A study on 70 countries over the time span of 1960-85 found that income inequality is closely associated with socio-political instability. With the latter, leading to uncertainty in the market and resultant lesser investment. Investment is the fuel of growth in an economy and thus, this study recognizes a channel of inverse relationship between income inequality and economic growth. (Alesina & Perotti, 1996)
Other authors indicated the role of middle-class in generation of adequate demand to sustain economic growth as crucial. Industrialization does not suffice alone, the benefits of such a boom should be distributed evenly to generate domestic demand and create large markets. This way through the channel of distribution, large middle-class can have a positive impact on growth. (Murphy, Shleifer, & Vishny, 1989) (Todaro, 1997)
With greater availability of data and increasingly better models, several studies adopted panel data analysis that simultaneously included the features of time series and cross-sectional studies. With panel estimation, Forbes (2000) found that in short and medium-term the income inequality has a positive effect on economic growth. This relationship was perceived to be robust across samples, model specifications and variable definition with one exception that they might not apply to very poor countries. (Forbes, 2000) Another panel study, reported little overall relation between income inequality and rates of growth and investment. There is however, an indication that inequality retards economic growth in poor countries but encourages growth in richer countries. The study points out to the existence and relevance of Kuznets curve though it is a relatively poor fit as it does not explain the wide range of variability. (Barro, 2000)
Evidently, the Kuznets curve was increasingly tested and not a pre-determined relationship between the two variables of income inequality and growth. Various studies failed to conclusively confirm Kuznets hypothesis in the late 90s and early 2000s. (Deininger & Squire, 1998) (Higgins & Williamson, 1999) (Savvides & Stengos, 2000) As supported by Barro, it was observed that inequality reduces income growth for poor people but not for rich and there is little support of Kuznets hypothesis. (Deininger & Squire, 1998) Cohort sizes were found to be significant factor in inequality. Larger working-class cohort size was coherent with less inequality and bigger youth cohort size indicated greater inequality. (Higgins & Williamson, 1999)
More recently, Thomas Piketty has extensively criticized Kuznets works in his book, “Capital in the 21st Century”. He showed that there is no automatic decrease in inequality in the later stages of development. He gathered the most extensive datasets on inequality from 1910 to 2010 and observed that the fall in income inequality was due to two world wars and other shocks rather than market operations or economic growth alone. He proposed an S-shaped curve rather than an inverted-U shape curve. (Piketty, 2014) This hypothesis was supported by Milanovic (2016), who proposed a sinusoidal curve however, arguing that it was the ‘second Kuznets Curve’ that rose owing to technological changes, globalization, etc. (Milanovic, 2016)
Thus, we can summarize that while there is yet to be a common consensus about the relationship of income inequality and economic growth, it is however, undeniable that income inequality and growth affect each other through transmission channels.
2.1 HDI, Transmission Channels and Income Inequality
From the above discussion, the role of transmission channels and hence, income inequality’s effect on broader spectrum of development other than GDP is quite evident. Schooling and institutions serve as a primary channel by which inequality lowers per capita income as suggested by previous literature. (Acemoglu, Johnson, & Robinson, 2001) on institution, (Schultz, 1963) (Easterlin, 1981) (Mankiw, Phelps, & Romer, 1995) on schooling, and (Easterly, 2007) (Sokoloff & Engerman, 2000) on both schooling and institutions. Thus, it is apparent that income inequality had adverse effects on several aspects of human capital and not just income.
This makes it imperative to analyze the impact of income inequality on a more broader and holistic welfare measure such as Human Development Index (HDI). This will enable us to look at the effects of inequality on people of that nation. This section deals and develops the argument on the same through a very small body of existing literature.
HDI originated from the “Capability Approach” as advocated by Amartya Sen in 1989. It is a geometric mean of three indices covering health, education and living standards of an economy. A few studies have shown a negative relationship between income inequality and human development.
Using data from 147 countries over the time span of 1992-2007, it was found that HDI had an inverse relationship with income inequality as measured by Gini Coefficient. It was observed that the non-GDP components of HDI i.e., education and health projects an S-curve while the GDP component held the traditional Kuznets Hypothesis of an inverted-U curve. It was also observed that when measured against HDI the curve was less steep as compared to GNI or GDP per capita. At low levels of development, there was a shallower rise in income inequality, followed by a significant fall at higher levels of development. As noted in the earlier section, this study also advocates that increase in access to education can have a higher impact on ‘equalizing’ the income than growth. Aforementioned insight throws light at the fact that studying the impact and effects of income inequality through broader measures such as HDI can provide a more nuanced insight on the relationship between development and inequality. (Theyson & Heller, 2015)
Fabien Thiel (2016) using a panel estimation of 117 countries spanning from 1970 to 2010 found that there is a negative long-run effect of income inequality on human development. A different short-run impact on different dimensions of human development was evident. Similar to the previous study by Barro (2000), he found that there exists a positive short-run effect of inequality on economic development. However, a negative short-run effect was detected on education outcome, this again signals at a specific transmission channel. This explains why studies have shown a positive as well as negative impact of inequality on economic development of nations, which seems to largely depend on which of the component of HDI i.e., GDP/ Living standard or health or education component dominates the dynamics in the country. Thus, measuring the effect of inequality on HDI is not redundant as it can give important insights on the transmission channels. (Fabian Thiel, 2016)
Another study, following Easterly’s instrumental variable approach showed that inequality was negative correlated with all the development measures i.e., per capita income, secondary school enrollment rate and institutional performance. Along with, per capita income growth it was detected that HDI growth is also negatively affected by inequality, using both OLS and IV analysis. In conclusion, the paper suggested that income inequality does cause underdevelopment. (Easterly, 2007) (You, 2013)
Thus, from the existing literature one can expect a negative association between human development as measured by Human Development Index (HDI) and income inequality as measured by Gini Coefficient.