學術論文

We study the effect of financial market frictions on managerial compensation. We embed a market microstructure model into an otherwise standard contracting framework, and analyze optimal pay-for-performance when managers use information they learn from the market in their investment decisions. In a less frictional market, the improved information content of stock prices helps guide managerial decisions and thereby necessitates lower-powered compensation. Exploiting a randomized experiment, we document evidence that pay-for-performance is lowered in response to reduced market frictions. Firm investment also becomes more sensitive to stock prices during the experiment, consistent with increased managerial learning from the market.

Motivated by the recent antitrust cases in which Japanese auto parts suppliers colluded to raise supply prices against their long‐term collaborators, the Japanese carmakers, we study the conditions under which an upstream collusion is profitable even after compensating downstream direct purchasers. Oligopoly competition in successive industries is shown to give rise to a vertical externality and a horizontal externality. If a collusive price of intermediate goods better balances the two externalities, the collusion will raise the joint profit of all firms in the two industries and is therefore profitable for the upstream after compensation of downstream firms.

We hypothesize that when investors pay less attention to financial markets, they rationally allocate relatively more attention to market-level information than to firm-specific information, leading to increases in stock return co-movements. Using large jackpot lotteries as exogenous shocks that attract investors’ attention away from the stock market, we find supportive evidence that stock returns co-move more with the market on large jackpot days. This effect is stronger for stocks preferred by retail investors and is not driven by gambling sentiment. We also find that stock returns are less sensitive to earnings surprises and co-move more with industries on large jackpot days.

Drawing on the political theory of judicial decision making, our paper proposes a new and parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics. Firms in liberal circuits (the third quartile in ideology) are 33.5% more likely to be sued in securities class action lawsuits than those in conservative circuits (the first quartile in ideology). This result is stronger after the U.S. Supreme Court's ruling in the Tellabs case. We next show that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and with higher expected litigation costs. Furthermore, judicial appointments affect litigation risk and the value of firms in the circuit, highlighting the economic consequences of political appointments of judges. Finally, using our new measure, we document that litigation risk deters managers from providing long‐term earnings guidance, a result that existing measures of litigation risk cannot show.

We develop a game-theoretic model to explore why retail clusters are so popular in developing economies and when governments should facilitate the formation of retail clusters to improve social welfare. First, we find two determinants of retailer clusters: the valuation-cost ratio (consumers’ maximum valuation over retailers’ production cost) and retailer density (the number of retailers over unit transportation cost). The valuation-cost ratio and retailer density indicate retailers’ profit potential and competition intensity, respectively. Second, the equilibrium cluster size increases in the valuation-cost ratio. This finding explains the phenomenon that clusters are usually larger in developing economies (where numerous retailers sell unrecognized brands with low profit potential) than in developed economies. Third, when the retailer density of a product market exceeds a certain threshold, the market coverages of clusters overlap with each other (i.e., the overlapping case). Furthermore, when compared with the nonoverlapping case, the equilibrium cluster size in the overlapping case is larger for low-profit-potential products but smaller for high-profit-potential products. Together, valuation-cost ratio and retailer density define four types of clusters: overlapping massive clusters, nonoverlapping large clusters, nonoverlapping small clusters, and overlapping mini-clusters. Finally, the socially optimal cluster size is larger than the equilibrium cluster size, and the gap between these two cluster sizes decreases in the valuation-cost ratio.

We offer a new anchoring explanation for the ex-day abnormal returns of stock distributions, including stock dividend distributions, splits, and reverse splits. We propose that investors tend to anchor on cum-day prices in valuating ex-distribution stocks, resulting in a positive association between ex-day returns and adjustment factors. We find that this positive return-factor relation exists for all three types of stock distributions and in both the pre- and post-decimalization periods. Furthermore, we find that this positive return-factor relation is more pronounced among events that are more subject to investors’ anchoring propensity, featured by less investor attention, greater arbitrage difficulty, greater valuation uncertainty, less investor sophistication, and higher market sentiment. Last, using brokerage account data, we show that stocks that are traded by investors with more investment experience demonstrate a weaker return-factor relation.

With the rapid growth of online social network sites (SNSs), it has become imperative for platform owners and online marketers to quantify what factors drive content production on these platforms. Previous research identified challenges in modeling these factors statistically using observational data, where the key difficulty is the inability of conventional methods to disentangle the effects of network formation and network influence on content generation from the subsequent feedback effect of newly generated content on network structure. In this paper, we adopt and enhance an actor-oriented continuous-time statistical model that enables the joint estimation of the coevolution of the users’ social network structure and of the amount of content they produce, using a Markov chain Monte Carlo–based simulation approach. Specifically, we offer a method to analyze nonstationary and continuous-time behavioral data, typically recorded in social media ecosystems, in the presence of network effects and other observable and unobservable user-specific covariates. The proposed method can help disentangle network effects of interest from feedback effects on the network. We apply our model to social network and public posting data over six months to find that (1) users tend to connect with others that have similar posting behavior; (2) however, after doing so, these users tend to diverge in their posting behavior, and (3) peer influence effects are sensitive to the strength of the posting behavior. More broadly, the proposed method provides researchers and practitioners with a statistically rigorous approach to analyze network effects in observational data. Our results lead to insights and recommendations for SNS platform owners on how to sustain an active and viable community.

This paper analyses the effects of the European Union's anti-dumping tariffs against Chinese imports on all affected firms: “the good” European import-competing firms, “the bad” Chinese exporters and “the ugly” European importers of dumped products. The results show that temporary import tariffs are beneficial to the least productive “good” EU producers, but harms the most productive “ugly” EU importers. Overall, the net effects of anti-dumping policy on European employment and exports are largely negative. Also tariffs enhance the productivity of surviving “bad” Chinese exporters and widens the productivity gap with European competitors.

We study a corporate board tasked with monitoring a firm’s CEO and providing incrementally decision relevant information. The board has both compensation and non-pecuniary incentives—we label the latter board bias. Friendly boards have muted information gathering incentives, but can more effectively engage in cheap talk communication with management. As a result, the direction of the optimal board bias is determined by the CEO’s initial information advantage: the board should be weakly friendly if the CEO is endowed with precise information, and weakly antagonistic (to the CEO) otherwise. Aside from assembling a friendly board, another way for shareholders to foster CEO/board communication is by granting the CEO more equity. In general, we find board friendliness and CEO equity grants to be positively associated, in equilibrium. This provides an optimal contracting rationale for an empirical regularity often interpreted as friendly boards facilitating rent extraction.