« Back to Results
Marriott Marquis, Rancho Santa Fe 2
Hosted By:
American Economic Association
across households results in different tariff burdens across consumer groups. We
investigate the distribution of tariff burden among U.S. households of different incomes
and consumers of different genders. As a share of total household consumption expenditure
in 2015, the tariff burden was a nearly constant 0.25 percent across all income
deciles, meaning that tariffs act as a flat consumption tax. Since a flat consumption
tax is a regressive tax on income, tariffs fall disproportionately on the poor. Across
genders, we find large differences in tariff burden. Focusing on apparel products, which
were responsible for about 75% of the total tariff burden on U.S. households, we find
that the majority, 66%, of the tariff burden was from women’s apparel products. In
2015, the tariff burden for U.S. households on women’s apparel was $2.77 billion more
than on men’s clothing. This gender gap grew about 11% in real terms between 2006
and 2016.
Inequality
Paper Session
Friday, Jan. 3, 2020 2:30 PM - 4:30 PM (PDT)
- Chair: Carolyn M. Sloane, University of California-Riverside
Gender and Income Inequality in United States Tariff Burden
Abstract
The combination of different tariff rates across products and different consumption patternsacross households results in different tariff burdens across consumer groups. We
investigate the distribution of tariff burden among U.S. households of different incomes
and consumers of different genders. As a share of total household consumption expenditure
in 2015, the tariff burden was a nearly constant 0.25 percent across all income
deciles, meaning that tariffs act as a flat consumption tax. Since a flat consumption
tax is a regressive tax on income, tariffs fall disproportionately on the poor. Across
genders, we find large differences in tariff burden. Focusing on apparel products, which
were responsible for about 75% of the total tariff burden on U.S. households, we find
that the majority, 66%, of the tariff burden was from women’s apparel products. In
2015, the tariff burden for U.S. households on women’s apparel was $2.77 billion more
than on men’s clothing. This gender gap grew about 11% in real terms between 2006
and 2016.
How Automation that Substitutes for Labor Affects Production Networks, Growth, and Income Inequality
Abstract
We study the impact of technological change on GDP growth, income inequality, and the interconnectedness of the economy. Technological advances in goods that complement labor increase productivity but do not change the interdependencies across sectors nor the relative wages between high-skilled and low-skilled labor. In contrast, technological advances that (directly or indirectly) substitute for labor (e.g., robots, AI) change both and have impacts that depend on the state of the economy. As automation becomes more productive, wages drop for workers employed in automatable tasks to slow their displacement. With less productive alternative opportunities for labor, there is a greater drop in the wages of replaceable workers (raising inequality), and hence less automation, and a lower growth in overall productivity. The growth effects of technological advances in automation emerge gradually, and propagate both downstream and upstream (due to wage effects). In addition, as automation progresses, the production network becomes denser, increasing the centralities of automation good producers and their (direct and indirect) suppliers. Our findings provide additional insights into what makes today’s automation different from the previous ones.Inequality and Inefficiency Due to Networked Job Referrals
Abstract
Most labor markets rely on a combination of referrals and open applications to identify potential candidates. How do these different sources of hiring interact, and do such markets work well? We investigate the inefficiency and inequality that result in such markets as a function of the density of the network of referrals, the homophily in the society, and how common the productivity of a worker is to different firms. In particular, we examine settings in which workers differ in productivity as well as their ethnicity, gender, etc. Workers applying via open applications exhibit a ``lemons'' effect: some of them are applying after being rejected for jobs via their referrals. This lemons effect disadvantages workers who have few or no friends from whom to get a referral, resulting in an inefficiently low threshold for hiring via referrals, thus lowering productivity. It also disadvantages types who have lower employment rates and thus are forced to rely more on open applications; and therefore a higher lemons effect leads to increased inequality and decreased productivity. The lemons effect increases with the commonality of workers' productivity across firms, and thus so does the relative disadvantage of types who have lower initial employment. Increasing the density of the network and/or homophily disproportionately helps types with higher initial employment, and so inequality and its persistence are exacerbated. Similarly, increasing the commonality of the productivity of a worker to different firms increases the lemon effect, reducing productivity and increasing inequality. Inequality across groups persists over time, however, decreases with each generation as referrals do not always result in employment. However, if workers have to make a costly investment in their productivity before seeking employment, then inequality in steady state is possible.The Effect of Self-Employment on Income Inequality
Abstract
It is well known that the self-employed are over-represented at the bottom as well as the top of the income distribution. This paper shifts the focus from the income situation of the self-employed to the distributive effects of a change in self-employment rates. With representative German data and unconditional quantile regression analysis we show that an increase in the proportion of self-employed individuals in the labor force increases income polarization by tearing down floors at the bottom and allowing higher income potentials at the very top of the hourly income distribution. Recentered influence function regression of inequality measures corroborate that self-employment is a source of income inequality in the labor market.JEL Classifications
- D3 - Distribution