Gender Discrimination in Job Ads: Theory and Evidence

We study firms' advertised gender preferences in a population of ads on a Chinese internet job board, and interpret these patterns using a simple employer search model. The model allows us to distinguish firms’ underlying gender preferences from firms’ propensities to restrict their search to their preferred gender. The model also predicts that higher job skill requirements should reduce the tendency to gender-target a job ad; this is strongly confirmed in our data. We also find that firms' underlying gender preferences are highly job-specific, with many firms requesting men for some jobs and women for others, and with one third of the variation in gender preferences within firm*occupation cells.discrimination, gender, China, internet, search

Economic Reform, Education Expansion, and Earnings Inequality for Urban Males in China, 1988-2007

In the past 20 years the average real earnings of Chinese urban male workers have increased by 350 per cent. Accompanying this unprecedented growth is a considerable increase in earnings inequality. Between 1988 and 2007 the variance of log earnings increased from 0.27 to 0.48, a 78 per cent increase. Using a unique set of repeated cross-sectional data this paper examines the causes of this increase in earnings inequality. We find that the major changes occurred in the 1990s when the labour market moved from a centrally planned system to a market oriented system. The decomposition exercise conducted in the paper identifies the factor that drives the significant increase in the earnings variance in the 1990s to be an increase in the within-education-experience cell residual variances. Such an increase may be explained mainly by the increase in the price of unobserved skills. When an economy shifts from an administratively determined wage system to a market-oriented one, rewards to both observed and unobserved skills increase. The turn of the century saw a slowing down of the reward to both the observed and unobserved skills, due largely to the college expansion program that occurred at the end of the 1990s.earnings inequality, China

Economic Reform, Education Expansion, and Earnings Inequality for Urban Males in China, 1988-2007

In the past 20 years the average real earnings of Chinese urban male workers have increased by 350 per cent. Accompanying this unprecedented growth is a considerable increase in earnings inequality. Between 1988 and 2007 the variance of log earnings increased from 0.27 to 0.48, a 78 per cent increase. Using a unique set of repeated cross-sectional data this paper examines the causes of this increase in earnings inequality. We find that the major changes occurred in the 1990s when the labour market moved from a centrally planned system to a market oriented system. The decomposition exercise conducted in the paper identifies the factor that drives the significant increase in the earnings variance in the 1990s to be an increase in the within-education-experience cell residual variances. Such an increase may be explained mainly by the increase in the price of unobserved skills. When an economy shifts from an administratively determined wage system to a market-oriented one, rewards to both observed and unobserved skills increase. The turn of the century saw a slowing down of the reward to both the observed and unobserved skills, due largely to the college expansion program that occurred at the end of the 1990s.Earnings inequality, China

Employers’ Preferences for Gender, Age, Height and Beauty: Direct Evidence

We study firms’ advertised preferences for gender, age, height and beauty in a sample of ads from a Chinese internet job board, and interpret these patterns using a simple employer search model. We find that these characteristics are widely and highly valued by Chinese employers, though employers’ valuations are highly specific to detailed jobs and occupations. Consistent with our model, advertised preferences for gender, age, height and beauty all become less prevalent as job skill requirements rise. Cross-sectional patterns suggest some role for customer discrimination, product market competition, and corporate culture. Using the recent collapse of China’s labor market as a natural experiment, we find that firms’ advertised education and experience requirements respond to changing labor market conditions in the direction predicted by our model, while firms’ advertised preferences for age, gender, height and beauty do not.

Gender Discrimination in Job Ads: Theory and Evidence

We study firms' advertised gender preferences in a population of ads on a Chinese internet job board, and interpret these patterns using a simple employer search model. The model allows us to distinguish firms' underlying gender preferences from firms' propensities to restrict their search to their preferred gender. The model also predicts that higher job skill requirements should reduce the tendency to gender-target a job ad; this is strongly confirmed in our data, and suggests that rising skill demands may be a potent deterrent to explicit discrimination of the type we document here. We also find that firms' underlying gender preferences are highly job-specific, with many firms requesting men for some jobs and women for others, and with one third of the variation in gender preferences within firm*occupation cells.

Gender Discrimination in Job Ads: Evidence from China

  We study explicit gender discrimination in a population of ads on a Chinese internet job board. Gender-targeted job ads are commonplace, favor women as often as men, and are much less common in jobs requiring higher levels of skill. Employers’ relative preferences for female versus male workers, on the other hand, are more strongly related to the preferred age, height and beauty of the worker than to job skill levels. Almost two thirds of the variation in advertised gender preferences occurs within firms, and one third occurs within firm*occupation cells. Overall, these patterns are not well explained by a firm-level animus model, by a glass-ceiling model, nor by models in which broad occupational categories are consistently gendered across firms. Instead, the patterns suggest a model in which firms have idiosyncratic preferences for particular job-gender matches, which are overridden in skilled positions by factors such as thinner labor markets or a greater incentive to search broadly for the most qualified candidate.This paper has been accepted by Quarterly Journal of Economics

Do Chinese Employers Avoid Hiring Overqualified Workers? Evidence from an Internet Job Board

Can having more education than a job requires reduce one’s chances of being offered the job?  We study this question in a sample of applications to jobs that are posted on an urban Chinese website.  We find that being overqualified in this way does not reduce the success rates of university-educated jobseekers applying to college-level jobs, but that it does hurt college-educated workers’ chances when applying to jobs requiring technical school, which involves three fewer years of education than college. Our results highlight a difficult situation faced by the recent large cohort of college-educated Chinese workers:  They seem to fare poorly in the competition for jobs, both when pitted against more-educated university graduates, and when pitted against less-educated technical school graduates.This paper has been accepted by Research in Labor Economics

GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences

The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs.National Institutes of Health [P30CA082709 to J.W.]; Walther Cancer Foundation. Funding for open access charge: National Institutes of Health

Genetic Spectrum and Distinct Evolution Patterns of SARS-CoV-2

Four signature groups of frequently occurred single-nucleotide variants (SNVs) were identified in over twenty-eight thousand high-quality and high-coverage SARS-CoV-2 complete genome sequences, representing different viral strains. Some SNVs predominated but were mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguishable evolution patterns over time. A few hundred patients were detected with multiple viral strain-representing mutations simultaneously, which may stand for possible co-infection or potential homogenous recombination of SARS-CoV-2 in environment or within the viral host. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tended to switch between bat RaTG13 coronavirus sequence and Wuhan-Hu-1 genome, indicating the higher genetic instability or tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.This work was partially supported by the National Institutes of Health (Grant Number: P30CA082709) and Walther Cancer Foundation (Grant Number: 4301-80519/0187.01). Funding for open access charge: National Institutes of Health

Updated SARS-CoV-2 Single Nucleotide Variants and Mortality Association

Since its outbreak in December 2019, COVID-19 has caused 100,5844,555 cases and 2,167,313 deaths as of Jan 27, 2021. Comparing our previous study of SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found out that the SNV clustering had changed considerably since June 2020. Apart from that the group SNVs represented by two non-synonymous mutations A23403G (S: D614G) and C14408T (ORF1ab: P4715L) became dominant and carried by over 95% genomes, a few emerging groups of SNVs were recognized with sharply increased monthly occurrence ratios up to 70% in November 2020. Further investigation revealed that several SNVs were strongly associated with the mortality, but they presented distinct distribution in specific countries, e.g., Brazil, USA, Saudi Arabia, India, and Italy. SNVs including G25088T, T25A, G29861T and G29864A were adopted in a regularized logistic regression model to predict the mortality status in Brazil with the AUC of 0.84. Protein structure analysis showed that the emerging subgroups of non-synonymous SNVs and those mortality-related ones in Brazil were located on protein surface area. The clashes in protein structure introduced by these mutations might in turn affect virus pathogenesis through conformation changes, leading to the difference in transmission and virulence. Particularly, we found that SNVs tended to occur in intrinsic disordered regions (IDRs) of Spike (S) and ORF1ab, suggesting a critical role of SNVs in protein IDRs to determine protein folding and immune evasion