A meta-regression analysis on the association between income inequality and intergenerational transmission of income Ernesto F. L. Amaral Texas A&M University [email protected] Sharron X. Wang Texas A&M University [email protected] Shih-Keng Yen Texas A&M University [email protected] Francisco Perez-Arce University of Southern California [email protected] Abstract Our overall aim is to understand the association between income inequality and intergenerational transmission of income (degree to which conditions at birth and childhood determine socioeconomic situation later in life). Causality is hard to establish, because both income inequality and inequality in opportunity are results of complex social and economic outcomes. We analyze whether this correlation is observed across countries and time (as well as within countries), in a context of recent increases in income inequality. We investigate Great Gatsby curves and perform meta-regression analyses based on several papers on this topic. Results suggest that countries with high levels of income inequality tend to have higher levels of inequality of opportunity. Intergenerational income elasticity has stronger associations with Gini coefficient, compared to associations with top one percent income share. Once fixed effects are included for each country and study paper, these correlations lose significance. Increases in income inequality not necessarily bring decreases in intergenerational mobility maybe as a result of different drivers of inequality having diverse effects on mobility, as well as a consequence of public policies that might reduce associations between income inequality and inequality of opportunity. Keywords Income inequality. Intergenerational transmission of income. Intergenerational mobility. Inequality of opportunity. Great Gatsby Curve. Meta-regression analysis. Citation Amaral EFL, Wang SX, Yen SK, Perez-Arce F. 2018. “A meta-regression analysis on the association between income inequality and intergenerational transmission of income.” Open Science Framework, July 6. (https://doi.org/10.31219/osf.io/8qmhw) 1 1. Introduction A deeper understanding of the association between inequality and intergenerational mobility across nations is timely. Over the past three decades, income inequality has increased significantly in the United States and most developed countries. Earnings have stagnated except for those at the top end of the income scale, and the distribution of wealth has become more unequal. While stagnant income among low-income individuals is worrisome, an additional concern is that increased inequality may limit mobility and opportunities for their children. The fear is that the bigger the gap between poor and wealthy families, the harder it is for poor children to climb the economic ladder. Some argue that a reduction in intergenerational mobility is a consequence of inequality (OECD, 2011; 2015; Krueger, 2012). The Great Gatsby Curve is used to illustrate the inverse relationship between income inequality and intergenerational mobility: societies with higher level of inequality tend to have lower level of intergenerational mobility (Krueger, 2012; Miles Corak, 2013). However, whether the recent increases in income inequality cause less opportunity for those at the bottom depends on the drivers for greater inequality. The present study employs meta-regression analysis to understand the correlation between societal inequality and intergenerational mobility and whether increase in inequality and inequality in opportunity move together. Intergenerational mobility is defined as the degree to which conditions at birth and childhood determine outcomes later in life. It measures socioeconomic standings pass from one generation to the next. For example, researchers use father-son income correlation to measure intergenerational mobility. Our study hopes to lead us to a better appraisal of the potential of policies to provide greater opportunities for all. A large range of public policies intend to tackle poverty and inequality. However, we know less about the extent to which each of these policies affect inequality of opportunity and related concepts such as the intergenerational transmission of income (IGTI). In addition, our study hopes to contribute to the literature of social inequality and mobility by examining the association between inequality and opportunity across nations using a novel technique. The significant increase in income inequality in developed countries has been driven mostly by a combination of increased wages for highly educated workers and higher incomes for top earners 2 (often managers of large companies and a few other high-paying occupations) (Hout, 2012). Our appraisal of the research literature suggests that the increase in wages for the highly educated is a result of a greater demand for high-skill workers brought about changes in technology that have increased the productivity of skilled workers. The reasons behind the rapid increase in compensation of top earners is not as well understood, but globalization and information technology have played a role by permitting managers and other professionals to control larger operations. To a lesser extent, there is evidence that income inequality has worsened in the United States due to institutional changes such as the decrease in the minimum wage in real terms, the weaker role of trade unions, and lower barriers to international trade. The first two factors have let wages fall for a sector of the working population. Though international trade cannot explain the raise of inequality in the 1980s and early 1990s, it may have had quantitatively larger impacts since the turn of the century, contributing to more low-paid service jobs and well-paid skill-intensive jobs, as well as to fewer middle-class manufacturing jobs (Kalleberg, 2011). We analyze the likely associations of these changes with inequality of opportunity. Highly- skilled workers tend to have higher incomes, which may translate into greater investments in their children and thus greater inequality of investment in children’s skills (Gary Becker and Tomes, 1986). However, the quantitatively most important factor in the increase in inequality— higher incomes at the top of the income distribution—does not reduce the investments that most families can make in their children. Thus, from this point of view, increase in inequality is not likely to affect measures of inequality of opportunity that are based on movements throughout the income distribution. We present empirical evidence regarding the extent to which economic inequality and inequality of opportunity move together across time and geographies, and then attempt to tease out the reasons behind it. We also discuss alternative measures for income inequality, the measures or proxies of inequality of opportunity, and how the use of alternative measures may matter. We describe the results of a meta-regression analysis designed to answer this particular question. Our results indicate that, across countries, there is a correlation between income inequality and the 3 common measures of inequality. However, across time, increases in inequality are not always accompanied by increases in inequality of opportunity. This suggests that the drivers of cross- country differences in income inequality may be different than those that drive. 2. Literature review 2.1. Main concepts of inequality 2.1.1. Income inequality The human capital theory suggests that there is a positive relation between person’s ability and person’s income level (Mincer, 1958; Gary S. Becker, 1962). Each person has their bargaining power in the labor market. The bargaining power is consisted of the human capital, such as education and working experience (Mincer, 1958; Gary S. Becker, 1962; 1993). In the simple framework below, individuals generate income through the use of their assets in the market: mostly labor and capital. Assets are not only physical resources (capital) but also, and most importantly, individual skills (which allow people to work productively). Individuals have a certain level of skills (assets), they decide whether to work and how much (intensity of use), and they make an income depending on the current wage for those skills (return to assets) (Gary S. Becker, 1993). Similarly, individuals may choose to invest their capital and earn income depending on the return rate of type of investment, such as interest rate. Market income inequality arises through: (1) Differences in the amount and type of assets owned by individuals. These assets are partly a result of the accumulation of resources, such as savings and investment in education (i.e. achieved status), as well as of the conditions at birth (i.e. ascribed status) (Parsons, 1940). (2) Differences in the intensity of use of those assets. For example, some individuals work full time while others do not, which generates variations in wage. This intensity of use generates a inequality that is a result of the incentive to use assets (Collins, 1971). (3) Differences in income and rising inequality within occupations (Kim and Sakamoto, 2008; A. Sakamoto and Wang, 2017b). Social scientists have been using occupation as a proxy for person’s social status. Recently, however, some researchers have argued that inequality within occupation could be as high or even higher than inequality across occupations. (4) Differences in income across places of residence for the same activities, related to variations in geographical costs of living. For instance, wages