This paper documents that ffrms are increasingly financing innovation using their stock of innovation, measured as patents. We refer to this behavior as financing innovation with innovation. Drawing on patent collateral data from both the US and China, we first show that (1) in both countries, the total number and share of patents pledged as collateral have been rising steadily, (2) Chinese firms employ patents as collateral on a smaller scale and with a lower intensity than US firms, (3) firms increase their borrowing and innovation after they start to use patent collateral. We then construct a heterogeneous firm general equilibrium model featuring idiosyncratic productivity risk, innovation capital investment, and borrowing constrained by patent collateral. The model emphasizes two barriers that hinder the use of patent collateral: high inspection costs and low liquidation values of patent assets. We parameterize the model to firm-level panel data in the US and China and find that both barriers are significantly more severe in China than in the US. Finally, counterfactual analyses show that the gains in innovation, output, and welfare from reducing the inspection costs in China to the US level are substantial, moreso than enhancing the liquidation value of patent assets.

Does the ancient farming culture shape the risk-taking behavior of households today? Using a dataset covering over 130,000 households from a Chinese national survey, our study examines the relationship between the culture of rice cultivation and the financial behavior of modern households. We find that households in regions with a higher rate of historical rice cultivation are more likely to invest in the financial market and buy lottery, but less likely to purchase insurance. We also find that the rice area has more households with risk preferences consistent with prospect theory expectations. To account for omitted variable bias, we use average regional rainfall and downstream distance to ancient irrigation systems as instrumental variables for rice cultivation, and our results remain robust. We find that the rice effect cannot be explained by regional economic development, traditional Confucian values, or ethnic diversity. To explore potential mechanisms, we find that households in rice regions are more likely to borrow money from friends and relatives and have interest waived, and historical commercial development has also been influenced by the rice culture.

We study the income inequality among streamers using the administrative data of a leading Chinese live-streaming platform. The live-streaming technology enables a superstar to produce new entertainment products matched with demand and occupies a larger market share. Imagine an extreme case; the best streamer hosts live for 24 hours, earns all possible income, and leaves zero time for other streamers. Our data show that the income distribution of the highest-paid streamers follows Zipf’s Law and appears to be even more concentrated than any offline business: NBA top players, Forbes celebrities, and billionaires. Income inequality increased rapidly as the platform expanded from 2018 to 2020 — for example, the income share of the platform’s top 10 streamers increased from 14.82% to 45.15% as its revenue grew by 142%. To estimate inequality elasticity to the market size, we study four quasi-experimental shocks: potential market size proxied by economic development and Fintech coverage, quarter-end revenue spikes induced by the seasonal incentive regime, user surge induced by capital raising, and the Covid-19 lockdown in Wuhan. Gini coefficient elasticity ranges fromm1.3% to 10.6% estimated from the cross-city variations (local economic development and Covid-19 Wuhan lockdown); the time-series variations (quarter-end and user surge before capital raising) imply an elasticity ranging from 3.6% to 25.5%.

By using a proprietary real–time daily online sales data collected in China from 10–billion consumer accounts, this paper ffnds that the ffrm–level daily online sales growth (DOSG) can positively predict future one–day to more than three–month cumulative stock returns in the cross section, implying a growth premium in contrast to Lakonishok, Shleifer, and Vishny (1994). A spread portfolio that is long on stocks with high DOSG and short on stocks with low DOSG delivers an abnormal return of around 30 basis points per week. DOSG derives its short–run (e.g., weekly) predictability from investor sentiments, tilting to a behavioral explanation. However, it derives its medium to long–run (e.g., three–month) predictability from fundamentals, voting for a rational explanation. Our further evidence indicates that stocks with high DOSG experience more intensive information acquisition from retail investors and less severe crash risk, implying online sales as a channel for retail investors to get access to daily real–time ffrm fundamentals.

We construct a text-based indicator of US-China tension and examine its economic transmission. Our index closely tracks the share of related discussions in US firms’ earnings conference calls and that it correlates with firm actions in ways that are highly indicative of firm concerns about bilateral tensions. Elevated US-China tension is associated with protracted declines in US corporate investment, especially among firms that are expected to be exposed to the bilateral tensions. We also ffnd adverse effects of US-China tension in the aggregate, even after accounting for a large number of factors traditionally used to explain such effects. Impulse responses from medium-sized VARs show that positive shocks to the US-China tension index lead to protracted output declines, increased credit spreads, and reduced bilateral trade. These effects are milder and less persistent in the Chinese aggregates than those of the US. To examine how USChina tension propagates through the real economy, we isolate a component of our index reflecting the realizations of barriers that disrupt bilateral transactions from the component driven by uncertainty of increased barriers without their materialization. We find data patterns suggesting that the economic transmission of US-China tension primarily operates through uncertainty effects.

Many studies suggest a positive and monotonic relationship between technological progress and wage income inequality since 1980s for industrialized economies. We examine this topic in the context of the Chinese economy where new technologies like automation, AI and digitalization have witnessed worldís most rapid growth in the last decade. Surprsingly, we Önd an inverted U-Shaped relationship - a "Digital Kuznets Curve", using a panel dataset constructed in line with the newly published "2021 Categorization of Core Industries of Digital Economy". We then set out a task-based growth model with heterogenous human capital and occupational choice, and show that this hump-shaped relationship can emerge either by introducing an erosion e§ect of digitalization on worker ability that increasingly counterveils the skill-biasing e§ect, or by directly adding a dynamic learning cost that captures the externality of digitalization. Our study contributes to the understanding of the nature of digitalization in re-shaping labor market structure.

The Chinese earnings yield differential relative to the U.S. switches from negative to positive around 2009, with the aggregate variation masking substantial cross-sector variation. Changes in sectoral composition and (changing) growth expectations are not important determinants of the variation in China-U.S. valuation differentials. Instead, changes in ownership structure, and most importantly cross-sectional and temporal variation in financial openness, are the key contributors. In addition, we show that IPOs in the banking sector and its internationalization played a critical role in the (relative) valuation change.

Unlike equity analysis where analysts follow a small group of firms and exercise discretion in incorporating firm-specific knowledge, ESG ratings that intend to capture firm ESG risk are produced through a largely unified model that incorporates a set of common disclosures decided by each rater. Against this backdrop, we assess the ability of local and global ESG ratings in capturing covered firms’ ESG risk in China. We use firm-level negative ESG incidents that occur within a year of ESG ratings’ release as a proxy for raters’ ESG risk assessment and examine whether local and foreign ratings have differential predictive ability. We find that local ratings better capture ESG risk that relates to social and governance issues on corruption, employment conditions, and regulatory violations, which often require the local context to incorporate. The outperformance is also salient among firms that rely on relationship-based transactions and political connections. Our results suggest that the local rater uses local knowledge to inform its model, which makes the ratings more relevant to ESG risk.

Bank stress tests can be an effective information disclosure policy in persuading stakeholders to avoid “attacking” a bank, thereby decreasing the probability of bank failure during distress. This paper studies stress test design along two dimensions: strength and frequency, assuming stakeholders are privately informed and move sequentially. We characterize all robustly persuasive stress tests that ensure all bank stakeholders disregard private information and coordinate actions perfectly based on test results (“pass” or “fail”). Our ffndings indicate that more frequent stress tests can substitute for increased test strength in making the stress test result robustly persuasive. We then identify the optimal stress test policy and investigate how the optimal frequency and strength depend on macroeconomic conditions, bank idiosyncratic characteristics, and endogenous maturity choices of banks. Finally, we discuss how other regulatory measures may complement the stress test policy.

Using proprietary data of all high-tech incubators in China, we study a new approach by government to implement industrial policy through market intermediaries instead of directly allocating resources. Exploiting a highly localized industrial policy that targets different “strategic emerging industries” across provinces, we find that the incubators in policy-targeted industries receive higher government subsidy after the policy relative to their peers in other industries. Moreover, we find evidence that government subsidy to high-tech incubators increases the incubated startups’ innovation activity. Privately owned incubators in targeted industries, relative to their state-owned peers, receive less government subsidy, although they utilize government subsidy much more efficiently than do their state-owned peers.