Identifying and addressing the factors influencing the within-firm pay gaps has become a pressing issue amidst the widening global income inequality. This study investigates the impact of corporate ESG ratings on employee income and pay gaps using data from Chinese-listed companies between 2017 and 2021. The results suggest that ESG ratings significantly increase employee income. Further research indicates that ESG ratings exacerbate the within-firm pay gaps and income inequality due to the varying bargaining power among employees. This effect is particularly pronounced in non-state-owned and large-scale companies. This is also true for all kinds of companies in traditional and highly competitive industries. However, reducing agency costs and improving information transparency can help vulnerable employees with weaker bargaining power in income distribution to narrow their pay gaps. The research findings offer important insights to promote fair income distribution within companies and address global income inequality.

Using official information published by Central Commission for Discipline Inspection (CCDI) of the CPC, we construct a database of officials who have been found guilty of corruption in China in the period 2012-21 with their personal characteristics and the amount of embezzled funds. We use it to investigate the correlates of corruption, estimate the effects of corruption on inequality, and find the expected increase in officials’ income due to corruption and the gain in income distribution ranking. We find that the amount of corruption is positively associated with education, administrative (hierarchical) level of the official, and years of membership in the Communist Party. The sample of corrupt officials belongs to the upper income ranges of Chinese income distribution even without corruption. But corruption is a significant engine of upward mobility. While only one-half of the corrupt official would be in the top 5 percent of urban distribution without illegal incomes, practically all are in the top 5 percent when corrupt income is included.

Using an extended overlapping generations (OLG) model, we theoretically prove that functional inequality resulting from weak labor bargaining power can be a key driver of high saving rates, as observed in China and other labor- abundant Asian emerging markets. Income distribution that favors capital over labor may attract excess capital investments and hence lead to high saving rates. The link between inequality and saving is especially prominent for the household sector because excess return on capital motivates the working-age population to increase their retirement savings. We also find empirical support for our theoretical predictions using China’s sectoral-level data.

We study the income inequality among streamers using the administrative data of a leading Chinese live-streaming platform. The live-streaming technology enables a superstar to produce new entertainment products matched with demand and occupies a larger market share. Imagine an extreme case; the best streamer hosts live for 24 hours, earns all possible income, and leaves zero time for other streamers. Our data show that the income distribution of the highest-paid streamers follows Zipf’s Law and appears to be even more concentrated than any offline business: NBA top players, Forbes celebrities, and billionaires. Income inequality increased rapidly as the platform expanded from 2018 to 2020 — for example, the income share of the platform’s top 10 streamers increased from 14.82% to 45.15% as its revenue grew by 142%. To estimate inequality elasticity to the market size, we study four quasi-experimental shocks: potential market size proxied by economic development and Fintech coverage, quarter-end revenue spikes induced by the seasonal incentive regime, user surge induced by capital raising, and the Covid-19 lockdown in Wuhan. Gini coefficient elasticity ranges fromm1.3% to 10.6% estimated from the cross-city variations (local economic development and Covid-19 Wuhan lockdown); the time-series variations (quarter-end and user surge before capital raising) imply an elasticity ranging from 3.6% to 25.5%.