This study investigates the impact of analysts' information source diversity on forecast bias and investment returns. We combine the GPT-4o model and text similarity, to extract the names of information sources from the text of analyst in-depth reports. Using 349,200 sources, we calculate information diversity scores based on the variety of data sources to measure analysts’ ability of selecting relevant information. The findings reveal that higher information diversity significantly reduces forecast bias and enhances portfolio returns. The effect is particularly pronounced for large companies, state-owned enterprises, those with low analyst coverage, low firm-specific experience, and reports with positive forecast revisions. Institutional investors recognize the value of this skill, while retail investors remain largely unaware, which contributes to financial inequality. This study highlights the critical role of information diversity in analyst performance.

In this paper, we use a unique dataset of the List of Dishonest Judgment Debtors to explore the impact on the social credit environment of the increasing housing prices in China. We find that housing price has a negative impact on the local credit environment. Dominance analysis suggests that housing price contributes to the model R-squared (R2) by an overwhelming majority, suppressing any other economic or social factors in explaining the deteriorating credit environment. Heterogeneity analysis shows that the rule of law and moral standards mitigate the negative influence of high housing prices, while income inequality exacerbates the influence.

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.

This paper explores the factors that influence redistributive preferences in the context of significant economic transformation, focusing on the transition premium and growth. Using an online survey experiment with a nationally representative sample from China, we find that priming getting rich via relatively less meritocratic, yet representative ways under market transition in post-reform China reduces redistributive support, specifically for policies that aim to take from the rich and the belief in the government’s duty to redistribute, indicating the presence of a set of fairness views in China that deviate from the conventional meritocratic paradigm. Heterogeneous treatment effects analyses reveal that such non-meritocratic fairness views are a general phenomenon, and self-interest in the form of subjective economic pressure only serves as a secondary concern. While people feel that the rich are more deserving and demand less redistribution regardless of subjective economic pressure, only those under less economic pressure exhibit decreased support for policies that aim to help the poor. These representative ways of getting rich under market transition are similarly fair compared to winning a lottery, far less fair than a self-made entrepreneur, but much more legitimate than acquiring wealth through corruption. Priming China’s growth story does not result in statistically significant changes in redistributive support. Additionally, we rule out the influence of three relevant confounders: low tax salience, preference falsification under authoritarianism, and misperceptions about relative income positions and intergenerational occupational mobility. We argue that such non-meritocratic fairness views are particularly salient in societies that break away from a centrally-planned economic system in the past and transition towards a high-growth market economy, where economic opportunities are becoming more inclusive.

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.

This paper studies a novel channel through which climate risks affect households’ choices of risky asset allocation: a stringent climate change regulation elevates labor income risk for households employed by high-emission industries which in turn discourages households' financial risk-taking. Using staggered adoptions of climate change action plans across states, we find that climate change action plans lead to a reduction in the share of risky assets by 15% for households in high-emission industries. We also find a reduction in risky asset holdings after the stringent EPA regulation. These results are stronger with experiences of climate change-related disasters. Our study implies an unintended consequence of climate regulations for wealth inequality by discouraging low-wealth households' financial risk-taking.

Does large-scale privatization increase income inequality? To answer this question, we analyze the impact of China’s reform of state-owned enterprises on labor market outcomes in urban areas from 1992 to 2004, exploiting cross-prefecture variation in reform exposure stemming from initial differences in the employment shares of urban collective enterprises and state-owned enterprises. Our analysis reveals that workers in prefectures with higher exposure to the reform experienced a more rapid decline in employment and a slower increase in income, compared to those in less exposed areas. Further analysis shows that individuals with lower income and those with lower educational attainment experienced greater losses. A backof-the-envelope analysis indicates that the reform contributed to more than 40% of the study period’s increase in income inequality.

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.

This paper comprehensively examines how subjective well-being (SWB) is influenced by various aspects of housing — tenure, living conditions, and housing values — based on an individual panel from the China Household Finance Survey. We employ a two-way fixed effects model to reduce the endogeneity problems of housing choices. Our findings suggest that housing plays a comparable role to income and wealth in SWB and that housing inequality and living experience both matter a great deal. Moreover, the positive impacts of home ownership on SWB reported by prior research are likely quality of life effects masked in home ownership. Results are robust to ordered logistic estimation with individual fixed effects. What we document carries important implications for housing policies, and these are generalizable to other countries.

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%.