Conference Agenda

In recent years, property tax has been a hot topic in China due to the government's policy to curb soaring housing prices. Although the implementation of property tax has been discussed for a long time, there is still no consensus on how to effectively design and implement it. The government has repeatedly emphasized the importance of listening to the voices of various social groups and conducting scientific research before making any policy decisions. Against this background, studying the opinions of various social groups on property tax has important practical significance. So far, research on property tax in China has mainly focused on the economic and financial aspects, with less attention paid to language analysis of public discourse. This study used the Chinese social media platform Sina Weibo as the data source and natural language processing (NLP) methods as the analysis tool to analyze the discourse on property tax in China from 2010 to 2022, exploring the opinions of different social groups and their changes and developments over time. The results show that the attitudes of different social groups towards property tax vary greatly, which can be attributed to various factors such as ideological differences, economic interests, and regional disparities. We also identified some common themes and trends in the discourse on property tax, such as the necessity of tax reform, the potential impact of property tax on housing affordability, and the role of property tax in promoting social justice and economic development. Our research reveals the complexity and diversity of public discourse on property tax in China and has important implications for policy-making and public discourse on this issue.

This study examines an important yet overlooked perspective in the long-standing debate on industrial policy: the industrial policy making. Specifically, we focus on prefecture-level industrial policies in China, a country with extensive expertise in industrial policy. Using a unique dataset of Reports on the Work of the Government and a novel Natural Language Processing algorithm, we identify industrial policies in Chinese prefectures and explore the determinants of these policies. Our findings reveal that policy compliance with upper-level governments is an important determinant of prefectural industrial policies, in addition to the traditional factor of comparative advantage. However, industrial policies driven by compliance have had negative effects on firms' total factor productivity (TFP) growth. We find that prefectural policies that support the same industry as upper-level policies generate only marginal TFP benefits (0.003 increase) for firms in that industry, while policies that complement upper-level policies generate nearly ten times larger TFP benefits (0.026 increase). Further mechanism analysis shows that the differential effects can be attributed to local government policy concessions, including tax deductions, preferential loans, and land price discounts.

Do punitive decisions made by regulatory authorities vary according to the political and economic status of the offenders? Why do some firms receive harsher punishments than others? Using original firm-level data from the golf course rectification campaign in China, 2014-2017, this paper examines the political and economic considerations of regulatory authorities in making punitive decisions. Results of logit regression and robustness checks suggest that there is no significant association between the seriousness of the violation and punishment outcomes. Rather, golf courses that were located in politically higher-ranking provinces, that have political connections, and that were constructed in earlier years and therefore harsh punishment will incur great economic loss, were more likely to receive lenient penalties. These findings indicate that political and economic considerations of provincial governments play an important role in generating regulatory disparities.

This study examines the relationship between firm leverage and stock price crash risk, where extant literature shows mixed findings on the impact of leverage on stock price crashes. Utilizing the Chinese real estate industry setting with high debt financing, we show that leverage is significantly positively associated with stock price crash risk. We further examine how the relationship between leverage and stock price crash risk is attributed to the unique Chinese institutional and economic environment. We show that the effect of leverage on stock price crash risk is concentrated in regions of low social trust and low marketization, and low economic growth. We next consider China’s new guidance of “three red lines” that governs firms’ debt financing policies, and we find that, among the three red line debt measures, the liability-to-asset ratio is the most significant determinant of crash risk. We also examine the implementation of the guidance in 2020 with a difference-in-difference research design, and we show that the new guidance has significantly reduced stock price crash risk for high-leverage firms. Overall, our results show consistent evidence of stock price crash risk increases for Chinese real estate firms that have shown overreliance on debt financing. Our study highlights the vital role of firm leverage on stock price crash risk that pertains specifically to highly-levered firms.