Using the staggered intercity but within-province deregulation of local banks in China as exogenous variations, we evaluate the effect of banking integration across geographical segmentation on capital misallocation. Based on an administrative data set comprehensively covering Chinese manufacturing firms, we find that for firms with initially high marginal revenue products of capital (MRPK), the integration increases physical capital by 19.3%, and reduces MRPK by 33.1% relative to low MRPK ffrms. Our findings are more pronounced for non-statedowned firms and firms with higher exposure to integrated banks. Integration also significantly increases the responsiveness of firms’ investments to deposit shock on other cities within the same province.

We document a speculation channel through which house market booms negatively affect entrepreneurship. To address endogeneity concerns, we exploit plausibly exogenous variation in house prices generated by staggered and unintended policy spillovers in China. We find house market speculation triggered by house booms crowds out entrepreneurship. Reduced labor supply, reduced capital supply, and heightened entry costs do not appear to explain our main findings. The negative effect exhibits in the OECD countries as well. Our paper complements the well-documented collateral channel by offering novel evidence on a previously under-explored adverse consequence of house market booms – their hindrance to entrepreneurship.

This paper employs a new empirical approach to estimate the impact of subsidies on growth and productivity. Our key innovation is to use local political leader geographic rotation as a source of exogenous variation. By using Chinese Industrial Census data from 1999 to 2013, we find that more subsidies have a positive effect on growth but not on productivity. Further firm-level results suggest that the size expansion of firms to win subsidies might be the mechanism, a new spillover channel, in explaining our main finding.

This paper examines the effect of political favoritism on economic inequality in the short run and political polarization in the long run. We exploit the sudden death of an authoritarian leader – President Chiang Ching-Kuo of Taiwan – in 1988 to generate plausibly exogenous variation in partiality. We find that Chiang’s nationalist regime conducted political favoritism broadly toward political immigrants via cronyism (allocating public sector positions) and also differentially toward specific subgroups of political immigrants via wage discrimination (offering higher wages to these subgroups within the public sector). Favoritism led to a 7.2 percent immigrant wage premium, which accounted for nearly three quarters of the immigrant-native wage gap at the time. This in turn propelled overall income inequality by 4.5 percent. Moreover, political favoritism breeds political polarization in the long run by pulling apart the political views of immigrants and natives. Compared with natives, immigrants who were exposed to favoritism tend to adopt political positions that are aligned with the nationalist party today: they are more likely to support unification with China, and are more inclined to trust the mainland Chinese government and its citizens. Exposed immigrant (native) swing voters are also more (less) likely to vote for the nationalist party today.

We identify negative spillovers exerted by large, successful manufacturing plants on other local production facilities in China. A short-lived alliance between the U.S.S.R. and China led to the construction of 150 "Million-Rouble plants" in the 1950s. Our identification strategy exploits the ephemeral geopolitical context and the relative position of allied and enemy airbases to isolate exogenous variation in plant location decisions. We find a boom-and-bust pattern in hosting counties: treated counties are twice as productive as control counties in 1982, but 30% less productive in 2010. The average other establishment in treated counties is unproductive, does not innovate, and charges high markups. We find that (over)specialization limits technological spillovers. This prevents the emergence of new industrial clusters and leads to a flight of entrepreneurs.

This paper evaluates the impact of mobile cashless payment on credit provision to the underprivileged. Using a representative sample of Alipay users that contained detailed information about their activities in consumption, credit, investment, and digital footprints, I exploit a natural experiment to identify the real effects of cashless payment adoption. In this natural experiment, the staggered placement of Alipay-bundled shared bikes across different Chinese cities brings exogenous variations to the payment flow, allowing me to address the endogeneity issues and establish a causal relationship. I find that the use of in-person payment in a month increases the likelihood of getting access to credit in the same month by 56.3%. Conditional on having credit access, a 1% increase in the in-person payment flow leads to a 0.41% increase in the credit line. Those having higher in-person payment flow also use their credit lines more. Importantly, the positive effect of in-person payment flow on credit provision mainly exists for the less educated and the older, suggesting that cashless payment particularly benefits those who are traditionally underserved.

In geographically segmented credit markets, local real estate booms can divert capital away from manufacturing firms, create capital scarcity, increase local real interest rates, lower real wages, and cause underinvestment and relative decline in the industrial sector. Using exogenous variation in the administrative land supply across 172 Chinese cities, we show that the predicted variation in real estate prices does indeed cause substantially higher capital costs for manufacturing firms, reduce their bank lending, lower their capital intensity and labor productivity, weaken firms' financial performance, and reduce their TFP growth by economically significant magnitudes. This evidence highlights macroeconomic stability concerns associated with real estate booms.

Using a unique FinTech data containing monthly individual-level consumption, investments, and payments, we examine how FinTech can lower investment barriers and improve risk-taking. Seizing on the rapid expansion of offline usages of Alipay in China, we measure individuals’ FinTech adoption by the speed and intensity with which they adopt the new technology. Our hypothesis is that individuals with high FinTech adoption, through repeated usages of the Alipay app, would build familiarity and trust, reducing the psychological barriers against investing in risky assets. Measuring risk-taking by individuals’ mutual-fund investments on the FinTech platform, we find that higher FinTech adoption results in higher participation and more risk-taking. Using the distance to Hangzhou as an instrument variable to capture the exogenous variation in FinTech adoption yields results of similar economic and statistical significance. Focusing on the welfare-improving aspect of FinTech inclusion, we find that individuals with high risk tolerance, hence more risk-taking capacity, and those living in under-banked cities stand to benefit more from the advent of FinTech.