Abstract: Individuals tend to overweight positive signals relative to negative ones when updating beliefs in the ego-relevant domain, including their own intelligence, beauty, and skills. One’s kindness to others can also be thought of as ego-relevant. Indeed, it has been documented that people have motivated memories regarding their generosity to others. However, motivated belief updating in the social domain has not been studied. In particular, this paper studies both types of motivated reasoning, i.e., asymmetric updating and motivated memory, in a consistent framework, replicates previous experimental paradigms in related ego-relevant domains, and documents interesting patterns in motivated reasoning about one’s altruism. In particular, participants in our experiment exhibit significant asymmetric updating, relatively overweighting positive signals in the social domain, which can be attenuated by the removal of ego-relevance or the prospect of obtaining objective feedback (uncertainty resolution). We also document patterns that have not been found in other domains. For instance, participants have more severe underweighting of negative signals when they are asked to update beliefs about themselves being the least selfish, rather than the most altruistic, within a group. Moreover, information suggesting that altruism is costly also attenuates asymmetric updating. In terms of motivated memory, we do find that participants were more likely to over-remember the amount allocated to others when they chose the more selfish option in a binary dictator game.

Abstract: Payment markets are two-sided. Networks like Visa and Mastercard charge merchant fees to fund consumer rewards. I study how regulation, private entry, and public entry in this market affect prices, distribution, and welfare in equilibrium. I model two-sided multi- homing, retail price-setting, and network competition. I estimate the model by matching data on consumers’ card holdings, merchant acceptance, network pricing, and the effects of debit reward reductions. The estimated model matches external evidence on networks’ costs, merchants’ margins, and the effects of AmEx’s 2016–2019 cuts in merchant fees. Using the estimated model, I compare the effects of capping credit card merchant fees, increasing entry of private credit card networks, and introducing a low-fee public option like FedNow. Capping credit card merchant fees is progressive and increases annual welfare by reducing rewards, retail prices, and credit card use. However, because consumer adoption is ten times more price-sensitive than merchant acceptance, competition from private networks like Discover or Buy Now Pay Later services like Affirm raises rewards without lowering fees, lowering welfare. A public option struggles to gain consumer adoption without rewards, limiting welfare gains.

Abstract: Exploiting variations in flood timing from the United States as a quasi-natural experiment, we show that floods cause population replacement in affected regions with a 1.9% increase in inflow and a 2.7% increase in outflow migration, respectively. They trigger younger, highly-educated, and employed residents out of, and attract older, less-educated, and unemployed ones into affected zones. Such patterns are significantly amplified by media information provision on flood risks. Moreover, we find that the selective migration induces a 5.3% decrease in housing price growth rates but a 7.4% increase in housing rent growth rates, suggesting a structural change in the housing markets of flood prone regions. A back-of-envelope calculation shows that flood-induced selective migration conditional on education and age profiles leads to net annual losses of $9.3 million and $1.98 million, respectively, in the flooded counties. Our results shed light on how information provision interacts with migration incentives in wake of natural disasters.

Abstract: We study how monetary policy affects financial risk premia. Unlike existing studies, we focus on the Federal Open Market Committee’s (FOMC’s) forward-looking policy stance, beyond the current announcement and macroeconomic forecasts, which we derive from the policymakers’ private deliberations. A more hawkish policymakers’ stance in the FOMC meeting predicts lower risk premia during the intermeeting period. This effect is not explained by the content of the FOMC statement and unfolds gradually after the announcement. We document the importance of intermeeting communication via speeches and minutes to show how communicating forward-looking stance is vital in managing policy-induced risk perceptions.

Abstract: Although the One Child Policy is widely considered to be one of the most stringent public policies in modern global history (Scharping 2003), China’s total fertility rate declined very little following its implementation in 1979/1980.  By contrast, China’s total rate fertility fell abruptly by about 50% during the early 1990s.  In this paper, we propose that strengthening bureaucratic incentives (under the “One Vote Veto” (OVV) policy during the early 1990s) was necessary for effective implementation of the One Child Policy – and was also responsible for its delayed impact on fertility more than a decade later.  Although One Child Policy targets had been part of China’s cadre evaluation system, creating promotion and professional advancement incentives for target adherence among Chinese bureaucrats, the OVV policy greatly strengthened these incentives, strictly prohibited career promotion for adherence failure.  We use provincial variation in OVV implementation to estimate its impact on birth hazards among Chinese women, and we then use event-study regressions to estimate inputs needed to build demographic life tables (with and without the policy), finding that the policy explains roughly half of China’s fertility decline during the 1990s.  We also show that the policy increased intrauterine device (IUD) use “recommended” by party officials by nearly 400% (but that voluntary use of IUDs, other forms of contraception, and abortion did not change). More generally, our paper highlights the central role of aligning bureaucratic incentives with public policy goals, even in a centrally-planned environment like China.

Abstract: Overconfidence is considered a prominent behavioral bias studied across students, executives, and investors using confidence interval production tasks. Overprecision on these tasks has been deemed the 'most robust form of overconfidence'. We provide comprehensive new evidence with nearly 2,000 participants, varying confidence interval widths and paradigms. Our results show that far from being robust, overprecision disappears, and even reverses, once we consider narrower interval widths and avoid tricky or difficult knowledge questions. Moreover, we find evidence that overprecision is more commonly associated with being uncertain, rather than being confident, raising concerns about the appropriateness of this standard confidence interval paradigm for measuring overconfidence. After considering this new evidence, we cannot definitively conclude that individuals are on average overconfident.

Abstract: This paper investigates the impact of various labor market integration policies on the migration decisions of entrepreneurs and the performance of their firms, in the context of China's Hukou policies. We first present suggestive evidence that various Hukou policies have significant and heterogeneous effects on the migration decisions of both workers and entrepreneurs. We then present a spatial general equilibrium framework that takes into account the key features of the Chinese migration restriction system to explain how workers' and firms' location choices interact in response to heterogeneous labor mobility restrictions by skill type. The model highlights the co-sorting of firm and labor. We compile a unique dataset of prefectural-level Hukou reforms between 1995 and 2019, and combine together with data on labor migration flows, entrepreneurs' migration flows, and the registration records of close to 90 million firms, to identify the effect of reductions of labor mobility restriction on the regional redistribution of entrepreneurship. The removal of Hukou restrictions facilitates the sorting of entrepreneurs, with those in high-skill intensity industries moving from smaller cities to larger cities. Additionally, we demonstrate that skill-biased relaxation of mobility restriction attracts high-skill labor and migrant entrepreneurs, at the expense of local entrepreneurs. In contrast, nonrestrictive Hukou relaxation stimulates overall economic activities through abundant labor supply, firm agglomeration, and, more importantly, the simultaneous movement of labor and entrepreneurs.

Abstract: The idea that monetary policy is, in most modern economies, 98% talk and 2% action comes from Ben Bernanke in his first blog for the Brookings Institution after stepping down as Chair of the Federal Reserve. In this talk, I will explain the key role of communication in the conduct of monetary policy. I will discuss what we understand from research on the topic including across different methodological dimensions including theoretical macro models, asset-price event studies, analysis of the textual content of communication and information provision experiments.

Abstract: In this project is to study how men/women form teams to work on a task with gender stereotypes when there is (no) information on the previous performance of men/women. We first look at expected performance in four different tasks. Then we consider two treatments (INFO vs NO INFO), the same four tasks (face-recognition, verbal, mathematical and rotation), and three possible payments schemes (max, min, median) in a between-subject experiment. For the expectations experiment, in Text and Emotions, women are expected to perform better than men, but there are no differences for Math and Rotation. For the team formation experiment, on average, participants select more team members when payment depends on the best member they have in their team. Participants change team composition after being exposed to information. We do not find evidence that preferences are driving our results. Gender Homophily is important (especially in the NO info group), but participants react to information. With INFO: they increase the proportion of females in ‘emotions’ task, and decrease it in ‘rotation’ tasks, as expected.

Abstract: Although the One Child Policy is widely considered to be one of the most stringent public policies in modern global history (Scharping 2003), China’s total fertility rate declined very little following its implementation in 1979/1980.  By contrast, China’s total rate fertility fell abruptly by about 50% during the early 1990s.  In this paper, we propose that strengthening bureaucratic incentives (under the “One Vote Veto” (OVV) policy during the early 1990s) was necessary for effective implementation of the One Child Policy – and was also responsible for its delayed impact on fertility more than a decade later.  Although One Child Policy targets had been part of China’s cadre evaluation system, creating promotion and professional advancement incentives for target adherence among Chinese bureaucrats, the OVV policy greatly strengthened these incentives, strictly prohibited career promotion for adherence failure.  We use provincial variation in OVV implementation to estimate its impact on birth hazards among Chinese women, and we then use event-study regressions to estimate inputs needed to build demographic life tables (with and without the policy), finding that the policy explains roughly half of China’s fertility decline during the 1990s.  We also show that the policy increased intrauterine device (IUD) use “recommended” by party officials by nearly 400% (but that voluntary use of IUDs, other forms of contraception, and abortion did not change). More generally, our paper highlights the central role of aligning bureaucratic incentives with public policy goals, even in a centrally-planned environment like China.

Abstract: Although the One Child Policy is widely considered to be one of the most stringent public policies in modern global history (Scharping 2003), China’s total fertility rate declined very little following its implementation in 1979/1980.  By contrast, China’s total rate fertility fell abruptly by about 50% during the early 1990s.  In this paper, we propose that strengthening bureaucratic incentives (under the “One Vote Veto” (OVV) policy during the early 1990s) was necessary for effective implementation of the One Child Policy – and was also responsible for its delayed impact on fertility more than a decade later.  Although One Child Policy targets had been part of China’s cadre evaluation system, creating promotion and professional advancement incentives for target adherence among Chinese bureaucrats, the OVV policy greatly strengthened these incentives, strictly prohibited career promotion for adherence failure.  We use provincial variation in OVV implementation to estimate its impact on birth hazards among Chinese women, and we then use event-study regressions to estimate inputs needed to build demographic life tables (with and without the policy), finding that the policy explains roughly half of China’s fertility decline during the 1990s.  We also show that the policy increased intrauterine device (IUD) use “recommended” by party officials by nearly 400% (but that voluntary use of IUDs, other forms of contraception, and abortion did not change). More generally, our paper highlights the central role of aligning bureaucratic incentives with public policy goals, even in a centrally-planned environment like China.

Abstract: This paper considers predictive regressions in which a structural break is allowed on an unknown date. We establish novel testing procedures for asset return predictability using empirical likelihood methods based on weighted-score equations. The theoretical results are useful in practice because our unified framework does not require distinguishing whether the predictor variables are stationary or nonstationary. Simulations show that the empirical likelihood-based tests perform well in terms of size and power in finite samples. As an empirical analysis, we test asset returns predictability using various predictor variables.

Abstract: We build a general equilibrium model of endogenous communication, quality control and trade. We derive a structural gravity equation from the model and show that exogenous communication costs raise the costs of quality control and have a larger impact on products with a lower elasticity of substitution. In our empirical application, we estimate the impact of direct flight connectedness on communication costs using the gravity equation. We overcome the identification challenge using an instrumental variable constructed based on the discontinuity of direct flights at around 6,000-mile distance due to air travel regulations. We find that air connectedness increases trade, especially for products with a low elasticity. We combine the empirical estimates and our equilibrium model to analyze the aggregate impact of air connectedness and air travel regulations.

Abstract: We develop a spatial model of endogenous growth via frictional knowledge diffusion to examine the effect of technological waves—defined as long-term shifts in the importance of specific knowledge fields—on local population dynamics. We calibrate the model using a new dataset of historical geolocated patents spanning over one hundred years. We find that frictions to idea diffusion across locations and technological fields account for more than half of the empirical relationship between exposure to technological waves and local growth in the United States during the twentieth century. Counterfactual experiments suggest that future technological scenarios may have large geographical effects. 

Abstract: Spurious factor behaviors arise in large random matrices with high-rank signal components and heavy-tailed spectral distributions. This paper establishes analytical probabilistic limits and distribution theory of these spurious behaviors for high-dimensional non-stationary integrated systems, and stationary systems with near-unit-root spatial processes across cross sections. We transform scree plots into Hill plots to detect spectral patterns in these spurious factor models and develop multiple t-tests to distinguish between spurious and genuine factor models. Numerical analysis indicates that the existing spurious factor models fit some, but not all, economic datasets. In particular, the term structure of interest rates adheres to genuine factor models rather than the local correlation model.

Abstract: This paper investigates the impact of globalization on intergenerational income mobility. First, we show evidence that stronger trade exposure in the commuting zone of residence when aged 16-20 lowers the intergenerational income mobility of U.S. workers. In particular, rising exposure to Chinese import competition between 1991 and 2007 lowers the income mobility of the cohort of U.S. workers born in 1980-1982, as evaluated based on their income in 2012. This evidence is robust to controlling for the initial inequality in parents' income, measured in 1996-2000, and to considering imports from different foreign countries. We then provide a general equilibrium theory to understand how globalization impacts intergenerational income mobility. In theory, path dependence in sector choice of individuals over generations and mobility frictions determine the dynamics of industrial compositions across locations in a country. Exposure to import competition reduces intergenerational income mobility of workers through the interaction of lower wage growth and less opportunities to change job and location in a country. The numerical solutions of the theory show the reduction of intergenerational income mobility of workers from locations with relatively high exposure to a trade shock, which is consistent with our empirical findings for the U.S.

Abstract: The sales of fashion products are influenced by uncertain and heterogeneous demands, necessitating predictive analytics to consider multiple explanatory variables and address the challenge of model uncertainty, which has been overlooked in prior research. To illustrate our solution, we first propose a novel forecasting estimator, which is characterized by provable optimal weighted forecasts and a collection of sub-model forecasts with various model specifications. We then validate our method empirically with store-level sales observations of a well-known international footwear brand, as an example of how a retailer can enhance its sales forecasts and improve promotion decisions after controlling model uncertainty. In a predictive analysis, the results show that controlling for model uncertainty between various predictors and store sales can produce more accurate forecasts of sales. With our proposed estimator, we also demonstrate the heterogeneity of promotion strategy importance for store with high and low previous sales. The additional analysis reveals that combo promotions have the most significant impact, and suggests adjusting the frequencies of gift and combo promotions to boost store sales. However, caution is advised when implementing both gift and combo promotions together to mitigate cannibalization effects.

Abstract: Consider firms that operate platforms matching buyers and sellers while selling goods themselves. By guiding consumers towards their own products through algorithmic recommendations, these firms could influence market outcomes – a regulatory concern. To investigate, we combine novel data about sales and recommendations on Amazon with a structural model that captures seller entry. Recommendations are highly price-elastic (-20), and many consumers (34%) only consider recommended offers. Hence, algorithmic recommendations raise the demand elasticity (from -8 to -11), intensify price competition, and increase the purchase rate. However, increased competition reduces entry (but the missing merchants are the least efficient). Focusing on self-preferencing: recommendations favor Amazon (equivalent to a 6% price discount), but this skew does not act as a barrier to entry or otherwise harm consumers. Indeed, since consumers prefer Amazon’s offers, “self-preferencing” slightly raises consumer surplus by $9 per product per month (assuming Amazon’s prices remain constant.)

Abstract: In theory, individuals’ higher order risk attitudes of prudence and temperance influence saving and investment decisions. Prudent individuals save more when their future income becomes more uncertain, and temperate individuals prefer less risky investments in the presence of greater background risks. In a controlled experiment, we measure individuals’ higher order risk attitudes directly, using two different elicitation methods. Participants then make saving and investment decisions under varying levels of background risk. We find strong evidence for background risk effects on saving and investment. Moreover, individual prudence measures correlate with the strength of precautionary saving, while individual temperance measures do not do so with investment. The risk attitudes acquired with the two elicitation methods are strongly correlated with each other. The representative individual is risk averse and prudent, and neutral towards temperance.

Abstract: In light of the experience of the last few years, the object of this paper is to re-examine the role of supply shocks, labour market tightness and expectation formation in explaining bouts of inflation.  We begin by showing that a quasi-flat Phillips curve,  which was popular prior to the pandemic, still fits the post-2020 US data well with the implication that (i)  labour market tightness likely played a limited role in generating recent inflation and (ii) changes in short term inflation expectations induced by supply shocks likely played a major role.  We then explore how best to capture the joint dynamics of inflation and inflation expectations in response to supply shocks.  Given the difficulty of capturing these dynamics under rational expectations, we propose and evaluate a model with bounded rationality.  In our model,  supply shocks that affect the common component of inflation across many goods drive persistent inflation dynamics through their effect of expectations, while supply shocks that are concentrated in a sector lead to much more temporary changes in both inflation and inflation expectations. Although our departure from full rationality is minor, it allows perceived broad-based supply shocks to be amplified and propagated over time in a manner consistent with observation. 

Abstract: Although maps encode essential information that could affect decision making, some maps suffer from certain levels of distortion. This paper quantifies the economic implications of map distortion by examining the impact of London transit map distortions on the housing market. To contain the sprawling London rail network within a single map resulted in a highly distorted map that draws stations further from one another when they are in fact closely packed with one another, and vice versa. Our estimates reveal that these distance distortions influence our perception of proximity. Every 1 km increase in distortion that portrays the nearest station to be further (closer) from (to) the economic node attributed to an 8.70% reduction (3.10% increase) in housing values. Additional quasi-experimental evidence from the launch of Google Maps on mobile devices suggests that there are house price corrections to these distance distortions. A simple back-of-an-envelope analysis suggests that these distortions attribute to substantial mispricing in the housing market that amounts to around  £10.71 billion (in 2023 values).

Abstract: How do expectation biases causally affect households’ financial decisions? We exploit a unique setting and study the repayment decision in solar loans, in which households borrow to purchase and install solar photovoltaic (PV) systems. Electricity production – the benefit that solar panels generate – primarily depends on sunshine duration. This creates exogenous within-person across-period variation in recent signals that borrowers observe and thereby expectations of future electricity production. We find that a one-standard-deviation decrease in sunshine duration in the week right before the repayment date leads to a 22% increase of delinquency, even though deviated past sunshine duration does not predict that in the future. Survey evidence shows that agents make more positive forecasts of future electricity production after experiencing longer sunshine duration in the past week. We examine a battery of alternative explanations and rule out mechanisms based on liquidity constraints and wealth effects.

Abstract: Estimation and inference of the treatment effects in panel data with only one treated unit have become popular in applied work. This paper studies robust inference procedure for treatment effects in panel data with flexible relationship across units. We exploit the information of the joint distribution of the cross-sectional units to construct counterfactuals and propose a direct construction of confidence intervals for the treatment effect via quantile regression. In particular, we propose a Quantile Control Method (QCM) using Quantile Random Forest (QRF) to accommodate flexible cross-sectional structures as well as high dimensionality. We proceed to establish the asymptotic consistency of QRF under the panel/time-series setup with high dimensionality, which is of theoretical interest on its own right. Monte Carlo simulations show that confidence intervals via the QCM have excellent coverage probability for the treatment effects even in small samples, and are robust to heteroskedasticity, autocorrelation, and various types of model misspecifications. An empirical application to study the effect of the economic integration between Hong Kong and mainland China on Hong Kong's economy is conducted to highlight the potential of the proposed method. 

Abstract: This paper investigates how cashless payment affects credit access for the underprivileged using Alipay, a BigTech platform that offers various financial services to over 1 billion users. Leveraging a natural experiment and a representative Alipay user sample, I find that cashless payment adoption increases credit access by 56.3% and a 1% rise in payment flow increases credit line by 0.41%. These effects are stronger for the less educated and the older. Counterfactual analysis shows that cashless payment data increase credit lines by 57.7%, consumer surplus by 0.5% of median income, and lender profit by 41.3% of consumer surplus.

Abstract: This paper develops a two-step semiparametric methodology for portfolio weight selection for characteristics-based factor-tilt and factor-timing investment strategies. We build upon the expected utility maximization framework of Brandt (1999) and Aït-sahalia and Brandt (2001). We assume that asset returns obey a characteristics-based factor model with time-varying factor risk premia as in Ge et al. (2020). We prove under our return-generating assumptions that an approximately optimal portfolio can be established using a two-step procedure in a market with a large number of assets. The first step finds optimal factor-mimicking sub-portfolios using a linear combination of characteristics-based factor loadings. The second step dynamically combines these factor-mimicking sub-portfolios based on a time-varying signal, using the investor’s expected utility as the objective function. We develop and implement a two-stage semiparametric estimator. We apply it to CRSP (Center for Research in Security Prices) and FRED (Federal Reserve Economic Data) data and find excellent in-sample and out-sample performance consistent with investors’ risk aversion levels.

Abstract: We consider the problem of optimal contest design in an environment where contestants choose not only their effort, but also the distribution of shocks affecting their output. We show that the presence of such strategic risk taking has a stark effect on contest design: The winner-take-all contest, whereby the entire prize budget is allocated to the top performer, maximizes the expected effort (or output) of the agents regardless of the shape of their cost of effort.

Abstract: Robo-advisors are novel tools in financial markets that provide investors with low--cost financial advice, usually based on individual characteristics like risk attitudes. We study the benefits of robo-advice in a portfolio choice experiment running over ten weeks. Depending on treatment, investors either receive robo-advice, have a robo-advisor implementing recommendations by default, or have to invest on their own. While we observe no effect of robo-advice on initial market participation, we do find positive effects on continued market participation. Robos also help investors avoid mistakes, make rebalancing more frequent, and overall yield portfolios much closer to the utility maximizing ones. Robo-advisors that implement the recommendations by default do significantly better than those that just give advice.

Abstract: This study examines the impact of personal data management on firm competition in the data collection and application markets, as well as welfare outcomes. Consumers purchase products from differentiated firms in the two markets. Firms compete to collect consumer data first to predict their preferences in the data application market, in which each firm offers personalized prices to its targeted consumers and a uniform price to untargeted consumers. Before firms offer prices, targeted consumers can erase their data and become untargeted at fixed costs. We show that personal data management mitigates price competition, reduces firm profits, and harms consumer surplus and social welfare in the data application market. Specifically, opt-out consumers bring negative externalities to opt-in consumers by increasing prices. By contrast, personal data management intensifies competition and improves consumer surplus in the data collection market. By combining these two markets, firm profits and social welfare decline. The change in consumers' two-market surplus depends on their foresight regarding the data application market outcomes, with only forward-looking consumers experiencing a higher surplus. We extend the model in several directions, including heterogeneous costs for data tracking, data portability, data-enabled personalized products, data ownership, and market tipping, and discuss policy and managerial implications.

Abstract: Educational resources are distributed unevenly across space and could contribute to spatial inequality. We develop a dynamic spatial model with life-cycle elements to study the impacts of location-specific educational resources. In the model, individuals determine whether and where to attend college, weighing on the distance to home, the expected option value of education, and the educational resources in the destination. Locations with more colleges attract more students. Moreover, as mobility costs increase with age, many college graduates stay in the city of their alma mater, leading to long-term changes in skill composition. We quantify the model to the context of China and structurally estimate the cost of obtaining a college degree in each location. We show that the college expansion between 2005 and 2015 had minimal impacts on welfare and skill composition, as it diverts resources towards the locations already well-endowed with colleges. More evenly distributed colleges could improve aggregate welfare and reduce spatial inequality at the same time.