Using the data of Chinese industrial enterprises, we examine how the incentive to reach GDP growth targets affects the local firms' capacity utilization. We find that Chinese economic growth targets exhibit a persistent pattern of top-down amplification along different jurisdiction levels, which is associated with a decline in local firms' capacity utilization. Moreover, the effect of amplified targets on overcapacity is more pronounced (1) when officials utilize hard-constraint vocabulary in setting the economic growth target, (2) during the National Congress of Communist Party, and (3) when the age of prefecture-level officials is close to 55. We also find officials intervene local firms' capacity decisions by increasing private communication with local entities and loosening public policies for local firms within their jurisdictions. Further results show that the amplification of economic targets is detrimental to future development of both regional economy and local firms.

We examine the role of an online reputation mechanism in international trade by exploring T-shirt exports on Alibaba. Exploiting rich transaction data and features of search and rating algorithms, we show that exporters displaying a superior reputation perform significantly better than peers with nearly identical true ratings and observables, and the value of reputation rises with the level of information friction and the specificity of information. We develop a dynamic reputation model with heterogeneous cross-country information friction to quantify the effect of the reputation mechanism and find a 20% increase in aggregate exports fueled by a market reallocation towards superstars.

Unlike in standard models, decision makers often narrowly bracket and make each decision in isolation. I develop a new approach, which I term narrow thinking, to systematically model narrow bracketing. The definition of narrow thinking is that different decisions are based on different, non-nested, information. As a result, the narrow thinker makes each decision with imperfect knowledge of other decisions and faces difficulties coordinating her multiple decisions. The narrow thinker effectively cares less about her other decisions when making each decision. The main application of narrow thinking is to provide a smooth model of mental accounting without requiring the decision maker to have explicit budgets. My approach generates unique predictions about how the degree of mental accounting depends on expenditure shares and cognitive limitations. It also illustrates how narrow bracketing and mental accounting can be explained by the same underlying friction.

Using U.S. bank data from 1996 to 2013, this paper studies how liquidity risk affects bank performance in financial crises. It finds that during the subprime crisis of 2007–09, liquidity risk reduced a bank’s survival probability, ROA, and net interest margin, and increased its loan-loss-provision expenses. This adverse effect was more severe for banks with lower capital ratios and higher credit risk. In contrast, there is no strong evidence that liquidity risk hurts bank performance in market crises. The results in this paper imply that liquidity risk is not merely a symptom of banks’ insolvency problems; it has an independent effect on bank performance in banking crises.

Employing a large sample of 7246 firms across 38 economies from 2000 to 2013, we show a positive relation between foreign institutional ownership (FIO) and firms' speed of leverage adjustment. This positive relation is concentrated for over-leveraged firms that need to decrease financial leverage to rebalance their capital structures. We validate our findings using a 2SLS regression and a DiD estimation to exploit the exogenous variations in FIO generated by the inclusion of MSCI membership and the passage of the JGTRRA. These results suggest that foreign institutional investors play an important monitoring role in mitigating agency conflicts between shareholders and managers. Overall, this paper lends support to the dynamic trade-off theory.

Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile regression approach, labeled Quantile Factor Analysis (QFA), to consistently estimate all the quantile‐dependent factors and loadings. Their asymptotic distributions are established using a kernel‐smoothed version of the QFA estimators. Two consistent model selection criteria, based on information criteria and rank minimization, are developed to determine the number of factors at each quantile. QFA estimation remains valid even when the idiosyncratic errors exhibit heavy‐tailed distributions. An empirical application illustrates the usefulness of QFA by highlighting the role of extra factors in the forecasts of U.S. GDP growth and inflation rates using a large set of predictors.

This paper studies whether team members’ past collaboration creates team-specific human capital and influences current team performance. Using administrative Medicare claims for two heart procedures, I find that shared work experience between the doctor who performs the procedure (“proceduralist”) and the doctors who provide care to the patient during the hospital stay for the procedure (“physicians”) reduces patient mortality rates. A one standard deviation increase in proceduralist-physician shared work experience leads to a 10–14 percent reduction in patient 30-day mortality. Patient medical resource use also declines with shared work experience, even as survival improves.

Lack of coordination for prudential regulation hurts developing economies but benefits advanced economies. We consider a two-country macro model in which countries have limited ability to issue state-contingent contracts in international markets, and equilibrium is constrained inefficient. Both countries have incentives to stabilize their economy by using prudential limits, but the emerging economy depends on the advanced economy to bear global risk. Intermediating global risk requires bearing systemic risk, which financially developed economies are unwilling to bear, preferring financial stability over credit flows. Advanced economies prefer tighter prudential limits than would occur with coordination, to the harm of emerging economies.