We show that fraudulent firms allocate resources differently than honest companies. Resources obtained through fraudulent means are likely to be viewed as unearned gains and are less likely to be invested in productive activities, such as recruiting talent. We posit that honest and fraudulent companies also invest in different types of innovation: honest firms pursue technically significant innovations, while fraudulent companies are likely to make smaller investments in less challenging inventive opportunities that contribute to the appearance rather than the substance of innovation. We test these predictions in a longitudinal dataset tracking the personnel recruitment and patenting activities of 467 Chinese high technology firms, all of which applied for state-funded innovation grants. We identify fraud by comparing two sets of financial books prepared by each company in the data in the same fiscal year, which are legally required to be identical but are discrepant in over 50 percent of cases, in a direction that benefits the firm. We find that relative to honest companies, fraudulent firms are more likely to receive state grants and are less likely to recruit new employees or produce important inventions in the post-grant period.

There is often considerable anxiety and conflicting advice concerning the benefits of presenting/being evaluated first. We thus investigate how expert evaluators vary in their evaluations of entrepreneurial proposals based upon the order in which they are evaluated. Our research setting is a premiere innovation fund competition in Beijing, China, where the prize money at stake is economically meaningful, and evaluators are quasi-randomly assigned to evaluate written grant proposals without the possibility of peer influence. This enables us to credibly recover a causal position effect. We also theorize and test how heterogeneity in evaluators’ prior (context-specific) judging experience moderates position effects. Overall, we find that a proposal evaluated first requires total assets in the top 10th percentile to merely equal the evaluation of a proposal in the bottom 10th percentile that is not evaluated first. Firm and evaluator fixed-effects models yield consistent findings. We consider evaluation design elements that may mollify these position effects in the discussion section. This paper was accepted by Sridhar Tayur, entrepreneurship and innovation.

In this study, we examined China’s Young Thousand Talents (YTT) program and evaluated its effectiveness in recruiting elite expatriate scientists and in nurturing the returnee scientists’ productivity. We find that YTT scientists are generally of high caliber in research but, as a group, fall below the top category in pre-return productivity. We further find that YTT scientists are associated with a post-return publication gain across journal-quality tiers. However, this gain mainly takes place in last-authored publications and for high-caliber (albeit not top-caliber) recruits and can be explained by YTT scientists’ access to greater funding and larger research teams. This paper has policy implications for the mobility of scientific talent, especially as early-career scientists face growing challenges in accessing research funding in the United States and European Union