Zeyi Qian (钱则一)

Coming soon.

A significant body of literature has discussed the crucial role that government and officials' behavior play in alleviating regional poverty. However, existing research often overlooks the potential trade-offs that officials may face regarding whether to improve ("leave from the bottom") or maintain ("race to the bottom") the poverty status of the regions they oversee. Newly appointed officials may choose to maintain regional poverty and slow development in the short term to secure more resources and policy support from the central government, which could be advantageous for long-term development. Conversely, if the officials prioritize their political performance, they may strive to promote development in poverty-stricken areas during their tenure to achieve short-term accomplishments. In this paper, we empirically investigate the effects of political turnover on poverty levels by examining county-level data. We explore how newly appointed officials decide between focusing on short-term versus long-term development outcomes and their decisions on economic outcomes and equity. Our findings indicate that the turnover of local officials is not conducive to short-term economic improvement in the region. It does not significantly increase personal savings or incomes for urban and rural residents and has a negative impact on GDP. Moreover, our analysis of the mechanisms behind these effects reveals that official turnover can exacerbate unemployment issues and social investment in the short run, with less pronounced effects on consumption levels, loan situations, and innovation strength. Additionally, we discover that the development of poverty-stricken areas is more significantly affected by official turnover compared to non-poverty-stricken areas. This ultimately manifests in a development pattern where regions alternate between "leaving from the bottom" and "racing to the bottom", and vice versa.

Technology-based startups are the main force in emerging industries and the source of disruptive technologies, but they face information barriers when acquiring knowledge, technology, and other resources necessary for innovation. As an important platform for connecting resources such as knowledge, technology, and capital, 'how' and 'through what channels' venture capital influences corporate technological innovation are still lacking reliable evidence and direct mechanisms in theory. Based on a matched database constructed from China's tax survey data, venture capital data, and granted invention patent data, this paper empirically tests the impact, mechanism, and source of venture capital on the technological innovation of technology-based startups, and verifies the role of venture capital in corporate innovation resource acquisition based on firm-pair level data. The study finds: (1) Venture capital enhances the quantity but not the quality of technological innovation in technology-based startups, and the results are more significant when venture capitalists with diversified information channels; (2) The embedding of technology-based startups in venture capital networks is beneficial for them to obtain innovation resources from formal channels such as technology transfer and R&D cooperation; (3) In the acquisition of innovation resources in technology-based startups, venture capital mainly plays the role of an “information broker” rather than a “reputation endorser”. The research in this paper will provide good theoretical insights and policy implications for accurately understanding the information barriers encountered in the innovation of technology-based startups, as well as for understanding the role and mechanism of venture capital in technological innovation.

Against the backdrop of the era of the "talent competition", this paper devises a quantitative standard for China's urban talent policies that covers 14 categories of policy objects and 39 specific measures. By collecting and quantifying 3308 talent policies at the prefecture-level city, it has sorted out the comprehensive scores and the scores of various sub-indicators of China's urban talent policies from 2012 to 2021. Then, combined with the micro data of listed companies, it has examined the impact of urban talent policies on the breakthrough of key core technologies of enterprises. The findings reveal that: First, talent policies significantly promote the breakthrough of key core technologies of enterprises, and this conclusion is still valid after considering the potential endogenous problems and a series of robustness tests. Second, from the perspective of enterprise characteristics, talent policies effectively promote the breakthrough of key core technologies of enterprises in growth and mature period, while showing limited effects on companies in decline period. Specifically, companies in growth period benefit more from safeguard measures (e.g., spouse employment and children's education) and development measures (e.g., research funding and innovation infrastructure), whereas companies in mature period respond better to development measures including talent evaluation and performance-based rewards. Third, from the perspective of industry characteristics, the policy effects concentrate in technology-intensive industries, where development measures like research funding allocation and achievement transformation mechanisms demonstrate particularly prominent contributions. Fourth, from the perspective of regional characteristics, the policies exert stronger effects in areas with substantial R&D investment, abundant higher education resources, and advanced marketization levels. Fifth, mechanism analysis indicates that talent policies facilitate technological breakthroughs primarily through enhancing R&D intensity, increasing proportions of highly skilled employees and R&D personnel, and improving overseas director representation, with supplementary evidence from corporate recruitment data. This research provides valuable insights for local governments to optimize talent policies through enterprise-specific approaches, while offering micro-level empirical support for constructing a multi-tiered and differentiated national talent policy system. The findings hold significant practical implications for enhancing core technological innovation capabilities and breaking through the "bottleneck" dilemma.

Large-scale government procurement has a significant impact on both firm performance and macroeconomic development. This paper constructs a comprehensive Chinese government procurement database and, based on matched data with the Chinese tax survey database, reveals the following key findings: Government procurement shows a notable preference for "selecting the best," favoring high-performing firms as contract awardees. Additionally, government procurement has a "nurturing" effect, as firms' performance continues to grow after winning contracts, a result further analyzed through mechanism analysis. Further investigation shows that government procurement can help small firms, startups, and emerging industries grow rapidly. Based on these findings, we designed and calibrated a model to create a virtual economy for counterfactual simulation. This simulation shows that the "selecting" and "nurturing" mechanisms in government procurement enhance overall productivity by 9.15% and increase GDP by 8.29%. We also simulated alternative policy scenarios, such as government procurement aimed at supporting small and medium-sized enterprises (SMEs). Our findings suggest that while this policy promotes SME expansion, it also lowers overall productivity.