Realistic Anchoring and Methodological Advancements: Academic Perspectives on High-Quality Economic Development in China: A Review of Selected Papers

ESG and Product Exports of Firms: Theoretical Model, Empirical Evidence and Quantitative Analysis

We construct a heterogeneous firm trade model with the consideration of firms' ESG ratings. Based on the highly disaggregated data at the firm-destination-country-product level of China's A-share-listed firms in the period of 2009—2015, we then empirically test the impact of firms' ESG ratings on their product export behaviors and the intrinsic mechanisms. Finally, this paper conducts quantitative analyses for structural estimation. First, a firm's ESG rating has a positive effect both on its product export value and export product scope. This core finding is still valid after robustness tests such as replacing the measures of the core explanatory variable, considering sample selection issues, and mitigating endogeneity issues. Second, the foreign demand expansion effect and the export-quality enhancement effect are two important channels through which ESG rating improvement promotes the export of firms' products. Third, our heterogeneity analyses show that for firms exporting to destination countries with higher levels of sustainable development, for non-state-owned firms, as well as for firms exporting non-green and low-carbon products, the contribution of higher ESG ratings to their product exports is more pronounced. Fourth, further expansive analyses show that the positive effect of higher ESG ratings on the export value of firms' products is mainly reflected in an increase in export quantity rather than an increase in export price. Besides, the export-boosting effect of rating advantages is more significant in the “social” dimension, where the public effect is stronger. Finally, our structural estimation and counterfactual analyses reveal that an one-unit increase in a firm's ESG rating will increase its product export quantity, export value, and export product scope by 16.70%, 16.68%, and 18.02%, respectively. This paper systematically reveals, from the level of product markets, how firms can promote high-quality exports with ESG as a key, thus providing new insights for China to cultivate new-quality productive forces and expand high-level opening-up to the outside world.

Understanding China's Business Cycle Fluctuations: Shock Sources Identification, Cause Contribution Decomposition and Policy Efficiency Evaluation

This paper constructs a high-dimensional Bayesian vector autoregressive(BVAR) model and uses a factor-structured sign restriction approach to identify seven major economic shocks, including domestic demand shocks, domestic supply shocks, foreign demand shocks, foreign supply shocks, financial shocks, fiscal policy shocks, and monetary policy shocks. The paper analyzes the intrinsic characteristics, impact scope, and contributions of these shocks to China's economic cycle fluctuations. The findings are as follows: First, domestic demand and supply shocks have direct impacts on GDP and CPI, while foreign demand shocks primarily affect the Chinese economy through trade channels. The effect of foreign supply shocks on the Chinese economy is minimal, whereas fiscal and monetary policy shocks have more significant effects. Second, financial shocks, particularly real estate price shocks, have the largest impact on variables such as GDP, consumption, and investment, making them the main source of China's economic cycle fluctuations. However, domestic supply and demand shocks also make important contributions. Third, from 2010 to 2019, the moderation of China's economic cycle fluctuations is closely related to the weakening of both internal and external economic shocks. Fourth, the effects of fiscal and monetary policies on output exhibit time-varying characteristics, with both policies effectively stabilizing economic growth in response to significant negative shocks. This study provides a new perspective on understanding the complexity of China's economic cycle fluctuations and their dominant drivers, offers a novel explanation for the phenomenon of “great moderation” in China's economy, and emphasizes the importance of fiscal and monetary policies in smoothing economic volatility.

Monetary Policy Uncertainty and New Firm Entry in China: Measuring Monetary Policy Uncertainty with the Stochastic Volatility Regime-Switch Model

Monetary policy uncertainty represents the implicit costs for monetary policy adjustment. With the extensive margin perspective, this study focuses on how monetary policy uncertainty affects new firm entry through the real options and financial friction channels. Using a regime-switch model with stochastic volatility to measure the monetary policy uncertainty in China and using the Chinese Industrial Enterprises Database to measure the new firm entry rate at the city-industry-year level, the empirical results show that the monetary policy uncertainty significantly inhibits the new firm entry, the result is robust to endogeneity test and robustness tests. The real option mechanism and the financial friction mechanism are effective transmission channels that monetary policy uncertainty inhibits the new firm entry. From the real options theory perspective, the inhibitory effect is more pronounced in industries with higher asset irreversibility or lower entry barriers. Further, extending the real options theory from the risk perception perspective, the results show that improvement in the macroeconomic environment weakens the inhibitory effect, and perceived uncertainty magnifies the inhibitory effect. From the financial frictions theory, the results show that the macro credit resources availability and the regional financial development mitigate the inhibitory effect. Further, using the ownership type to proxy for financial constraints, the result shows that the inhibitory effect is stronger among non-state firms. The study enriches the understanding of the extensive marginal effect of monetary policy uncertainty, and has important implications for preventing and resolving risks and optimizing monetary policy operation.

Financial Literacy and Consumer Financial Fraud Prevention

Financial fraud has a non-negligible negative impact on households, society and financial markets. Therefore, it is important to study the factors that influence residents to become potential victims of financial fraud. Using data from China Family Panel Studies(CFPS), this paper empirically examines the relationship between residents' financial literacy and their possibility of becoming victims of potential frauds. Results show that residents with higher levels of financial literacy were less likely to be victims of potential fraudulent projects than those with lower levels of financial literacy. Specifically, a one-standard-deviation increase in financial literacy is associated with 9.9% decrease in the probability of residents becoming victims of a potential fraudulent project, and this effect also holds in those with lower levels of assets. Further tests show that this effect is more pronounced in people who use internets. These results sheds light on the understanding of financial knowledge's role in preventing the risk of financial fraud.

Synergistic Effect of Basic Research Investment and Government R&D Subsidies

Forging synergistic innovation policies and continuously enhancing their effectiveness are crucial to addressing the “chokepoint” issue in core technologies. This paper evaluates the synergistic effect of basic research investment and government R&D subsidies, based on the data of regional innovation practices and the manually-sorted data on R&D subsidies and new technology investments of Chinese listed companies from 2009 to 2020. The results show that combining basic research investment with government R&D subsidies generates a significant innovation effect. By building a high-quality public-knowledge pool, basic research provides enterprises' innovation with foundational inputs, while the R&D subsidies lower the risk and cost of transforming that knowledge into commercial products. Further empirical results show that only firms with strong technology-absorption capacity can effectively identify, assimilate and integrate knowledge spillovers from the public research system, thereby aligning basic research outputs with their own R&D activities and unlocking the synergistic gains of the two policy resources. The conclusions offer significant policy implications for optimizing the allocation of innovation resources, enhancing the efficiency of science-and-technology funding, invigorating innovation actors, and achieving high-level self-reliance and self-strengthening in science and technology.

Intelligent and Unified Market Construction: Artificial Intelligence Applications and Cross-regional Investment of Enterprises

This paper empirically examines the impact of intelligent applications on capital flows. The study finds that artificial intelligence(AI) has facilitated the establishment of subsidiaries by firms across diverse locations. Key mechanisms through which AI drives capital flows include reducing off-site investment management costs, expanding high-skilled employment, optimizing the skill structure of the workforce, enhancing the allocation efficiency of technological and scientific talent, and promoting the diffusion of technical knowledge. The off-site investment effect of AI is particularly significant in non-state-owned enterprises, manufacturing firms, and businesses located in regions with pronounced labor market segmentation and advanced digital infrastructure. Further analysis reveals that AI applications transcend spatial constraints, encouraging firms to invest in more distant cities. Additionally, AI applications contribute to the flow of capital from smaller to larger cities. This paper provides empirical evidence and policy insights on how intelligent transformation can facilitate the smooth flow of capital in the new era.

Gender Composition, Spillover Effects and Students' Outcomes: Evidence from Classmates' Siblings

This paper uses data from the random classroom assignment sample of the China Education Panel Survey to examine the spillover effects of classmates' siblings' gender composition on students' outcomes. We find that a higher proportion of female siblings among classmates is associated with significant improvements in students' academic performance, cognitive skills, and non-cognitive skills. These results remain robust after accounting for potential reflection problems and omitted variable concerns. We further explore the underlying mechanisms and show that students' effort and learning attitudes serve as key mechanisms through which the gender composition of classmates' siblings generates spillover effects, with student diligence playing a particularly central role. In addition, explanatory power analyses indicate that students' effort and learning attitudes account for a substantial share of the observed effects. This study provides a new perspective for understanding the impact of gender composition on human capital accumulation.