We analyze the effects of exposure to industrial robots on labor markets and household behaviors,exploring longitudinal household data from China. We find that a one standard deviation increase in robot exposure led to a decline in labor force participation (-1%), employment (-7.5%), and hourly wages (-9%) of Chinese workers. At the same time, among those who kept working, robot exposure increased the number of hours worked by 14%. These effects were concentrated among the less educated and larger among men, prime-age, and older workers. We then explore how individuals and families responded to increased exposure to robots. We find that more exposed workers increased their participation in technical training and were significantly more likely to retire earlier. Despite the negative impact on wages and employment, we find no evidence of an effect on consumption or savings, which is explained by an increase in borrowing (+10%). While there is no evidence of an effect on marital behavior, we document that robot exposure led to a small decline in the number of children (-1%). Finally, we find that robot exposure increased family time investment in the education of children (+10%) as well as the investment in children’s after-school academic and extra-curricular activities (+24%).

Rising concern over the impact of Chinese industrial policy has led to severe trade tensions between China and some of its major trading partners. In recent years, foreign criticism has increasingly focused on the so-called "Made in China 2025" initiative. In this paper, we use information extracted from Chinese listed firms' financial reports and a difference-in-differences approach to examine how the "Made in China 2025" policy initiative has impacted firms' receipt of subsidies, R&D expenditure, patenting, productivity, and profitability. We find that while more innovation promotion subsidies seem to flow into the listed firms targeted by the policy, we see little statistical evidence of productivity improvement or increases in R&D expenditure, patenting and profitability. This paper suggests that the “Made in China 2025” initiative may have not yet achieved its target goals.

快速扩张的加密货币市场引起我们对加密货币价格决定性因素的思考：究竟是什么因素在决定加密货币价格？ 我们以 Google 搜索作为投资者对加密货币的关注度度量指标，检验了加密货币市场的“网络炒作效应”，并进一步提出了由加密货币市场因子、规模因子和网络关注度因子组成的加密货币市场三因子定价模型。我们的实证结果表明：(1) 加密货币市场存在显著的网络炒作效应，网络炒作是加密货币价格上升的推手；(2) 加密货币的平均超额收益率与规模呈负相关关系，与 Google 搜索关注度因子呈显著的正相关关系；(3) 我们提出的三因子模型对加密货币的截面超额收益率具有很强的解释能力，并能够很好地解释加密货币市场中的动量因子、反转因子和流动性因子。

理论上是否需要由政府来制定产业政策仍存在极大争议。本文基于 2008 年 开始实施的《高新技术企业认定管理办法》这一具体的产业政策，研究产业政策实施中的激励效应与迎合效应。研究发现，公司获得高新技术企业认定后，其专利申请数量会显著增加，专利申请质量也会显著提升，但通过虚增研发投入而获得高新技术企业认定的公司，其专利申请数量和专利申请质量却提升较少。这表明产业政策既可能会激励公司创新，也可能导致公司仅仅为表面迎合政策要求，而无意于真正从事创新。机制分析结果还发现，产业政策的减税优惠和政府补助会促进真正的高新技术企业增加创新，但对于伪高新技术企业，税收减免和政府补助的创新激励作用却显著减弱。最后，本文还利用事件研究法发现，真正的高新技术企业在宣告获得高新技术企业认定时公司价值会显著提升，但通过虚增研发投入而获得高新技术企业认定的公司其价值却并未增加。本文研究结论不仅协调了“产业政策之争”交战双方所持的不同理论观点，也为政府如何实施产业政策提供了理论参考。

This paper examines the impact and mechanism of digital finance on financial fraud by constructing a theoretical framework of digital finance affecting corporate financial fraud. We use panel data of Chinese A-share listed companies from 2011 to 2018. The results that digital finance can significantly inhibit corporate financial fraud and improve the ability of financial institutions to identify financial statements. Thus, the incentive and opportunity for corporations to engage in financial fraud is directly reduced. The internal mechanism shows that digital finance can restrain corporate financial fraud by alleviating the financing constraints faced by enterprises, as well as reducing corporate financial fraud by reducing corporate leverage. These effects will reduce debt pressure, thus easing the motivation of corporate financial fraud. The results of heterogeneity analysis that digital finance has a significant inhibitory effect on financial fraud of enterprises with different scales and different property rights.

This paper examines return spillovers within and between different DeFi, cryptocurrency, stock and safe-haven assets. The results show that DeFi and cryptocurrency asset markets exhibit strong within-market and between-market return spillovers, that stock and safe-haven markets show weak connectedness, and that safe-haven assets are minor receivers and transmitters of between-market spillover effects. The connectedness between markets is time varying and reveals structural changes in early 2020. Furthermore, we document that financial conditions shape the dynamics of return spillover effects between markets.

We explore whether Management Discussion and Analysis (MD&A) can provide incremental information to peers. Using Chinese stock market data, we find that positive peers' MD&A tone encourages firms to hold more cash, particularly for industries with fewer institutional investors' site visits. Moreover, this association is moderated by predation risk and decision-making environment. Specifically, this effect is more pronounced for firms which are market followers or financial constrained, and it is also stronger for firms operating under higher economic policy uncertainty or solely in domestic market. Overall, our findings enrich the information channels of peer effects in cash policy.

Regional carbon emission efficiency has differentiated characteristics under different economic development stages and patterns, and it is significant to identify such characteristics and formulate corresponding policies for high-quality regional development. Based on input-output data related to economic development and energy consumption, a comprehensive evaluation model of Super-SBM and Malmquist-Luenberger (ML) index was constructed to evaluate the spatial and temporal changes and driving forces of CEE, on the basis of which a proposal for collaborative carbon emission reduction zoning is proposed. The results indicated that the carbon emission efficiency (CEE) of the YRD shows a fluctuating upward trend with obvious spatial agglomeration characteristics, and the changes in CEE were closely related to the stage of economic development. The annual average CEE value during each period exhibited positive changes, indicating that economic development gradually shifted toward low carbonization. Moreover, the improvement of CEE gradually shifted from being driven by efficiency change to being driven by technological change. Finally, based on the carbon emissions and CEE characteristics of different cities, a carbon-neutral synergistic path is proposed in terms of industrial transformation, green development and technological support.

We explore the relationship between fintech, macroprudential policies, and commercial bank risk-taking. Based on system generalized method of moment modeling on a panel data of 114 commercial banks in China from 2013 to 2020, results show that there are functional differences in the impact of fintech on bank risk-taking. Payment and settlement technology (PST), capital raising technology (CRT) and investment management technology (IMT) are positively correlated with bank risk-taking. In contrast, market facility technology (MFT) negatively correlates with bank risk-taking. We also find that macroprudential policies weaken the promotion effect of CRT on bank risk-taking and strengthen the inhibition effect of MFT on bank risk-taking while having no significant moderating effect on PST and bank risk, IMT and bank risk. Further, the micro characteristics of banks (capital adequacy ratio, asset scale, liquidity level) affects the moderating strength of macroprudential policies. Various robustness tests confirm our conclusions.

Referring to the newspaper textual analysis method by Baker et al. (2016), this study constructs a monthly Chinese Real Estate Policy Uncertainty (REPU) index from 2001 to 2018. The index increases significantly near the promulgation of major policies. We also conduct evaluation of the index with the vector autoregression (VAR) model, which reveals that the rise of REPU indicates the decline in the growth rate of commodity housing development investment, sales area, and real estate industry added value. The REPU index is helpful to expand the understanding of policy uncertainty, and the accurate measurement of REPU is the basis for further research of its impact on China's real estate market.