We analyze a model in which traders have different trading opportunities and learn information from prices. The difference in trading opportunities implies that different traders may have different trading motives when trading in the same market—some trade for speculation and others for hedging—and thus they may respond to the same information in opposite directions. This implies that adding more informed traders may reduce price informativeness and therefore provides a source for learning complementarities leading to multiple equilibria and price jumps. Our model is relevant to various realistic settings and helps to understand a variety of modern financial markets.

Causal estimates of the benefits of increased schooling using US state schooling laws as instruments typically rely on specifications which assume common trends across states in the factors affecting different birth cohorts. Differential changes across states during this period, such as relative school quality improvements, suggest that this assumption may fail to hold. Across a number of outcomes including wages, unemployment, and divorce, we find that statistically significant causal estimates become insignificant and, in many instances, wrong-signed when allowing year of birth effects to vary across regions. (JEL H75, I21, I28, J24, N31, N32)

This paper studies an optimal renegotiation protocol designed by a benevolent planner when two countries renegotiate with the same lender. The solution calls for recoveries that induce each country to default or repay, trading off the deadweight costs and the redistribution benefits of default independently of the other country. This outcome contrasts with a decentralized bargaining solution where default in one country increases the likelihood of default in the second country because recoveries are lower when both countries renegotiate. The paper suggests that policies geared at designing renegotiation processes that treat countries in isolation can prevent contagion of debt crises.

We examine how financial market development affects technological innovation. Using a large data set that includes 32 developed and emerging countries and a fixed effects identification strategy, we identify economic mechanisms through which the development of equity markets and credit markets affects technological innovation. We show that industries that are more dependent on external finance and that are more high-tech intensive exhibit a disproportionally higher innovation level in countries with better developed equity markets. However, the development of credit markets appears to discourage innovation in industries with these characteristics. Our paper provides new insights into the real effects of financial market development on the economy.

This paper provides new evidence concerning the probability of informed trading (PIN) and the PIN-return relationship. We take measures to overcome known estimation biases and improve the quality of quarterly PIN estimates. We use the average of a firm’s PIN estimates in four consecutive quarters to smooth out the effect of seasonal variation in trading activities. We find that when high-quality PIN estimates are used, the Fama–MacBeth cross-sectional regressions show stronger evidence for the positive PIN-return relationship than documented in the prior literature. This finding is robust to controls for the January, liquidity, and momentum effects.

Collateral frictions have a profound effect on our economic landscape, ranging from the design of financial securities, laws, and institutions, to various rules and regulations. We analyze a model with disagreement, where securities and collateral requirements are endogenous. It shows that the security that isolates the variable with disagreement is “optimal” in the sense that alternative securities cannot generate any trading. In an economy with N states, investors may introduce more than N securities, and markets are still incomplete. The model has several novel predictions on the behavior of basis—the spread between the prices of an asset and its replicating portfolio.

China launched a pilot scheme in March 2010 to lift the ban on short-selling and margin-trading for stocks on a designated list. We find that stocks experience negative returns when added to the list. After the ban is lifted, price efficiency increases while stock return volatility decreases. Panel data regressions reveal that intensified short-selling activities are associated with improved price efficiency. Short-sellers trade to eliminate overpricing by selling stocks with higher contemporaneous returns following a downward trend, and their trades predict future returns. In contrast, we find intensified margin-trading activities for stocks with lower contemporaneous returns, and these trades have no return predictive power.

We analyze a model in which traders have different trading opportunities and learn information from prices. The difference in trading opportunities implies that different traders may have different trading motives when trading in the same market—some trade for speculation and others for hedging—and thus they may respond to the same information in opposite directions. This implies that adding more informed traders may reduce price informativeness and therefore provides a source for learning complementarities leading to multiple equilibria and price jumps. Our model is relevant to various realistic settings and helps to understand a variety of modern financial markets.

We investigate whether voluntary corporate restrictions on insider trading effectively prevent insiders from exploiting their private information. Our results show that insiders of firms with seeming restrictions on insider trading continue to take advantage of positive private information while being more cautious when exploiting negative private information. The results suggest that insiders continue to exploit their informational advantages in a way that minimizes their legal risk. We also find that the degree of information asymmetry is significantly lower in firms with restriction policies and that corporate governance significantly affects firms' decisions to adopt these policies.

Using a large proprietary database of institutional trades, we investigate whether institutional investors drive the turn-of-the-year (TOY) effect. Institutions that engage in window dressing, tax-loss selling, or risk shifting will contribute to the TOY effect by selling small, poorly performing stocks at the end of December and/or buying those same stocks at the beginning of January. We find abnormal pension fund selling in small stocks with poor past performance during the final trading days in December, providing some support for the window dressing hypothesis. However, we find little evidence that institutional tax-loss selling or risk-shifting trading strategies contribute to TOY returns. Furthermore, stocks with no institutional trading around the year-end exhibit considerably stronger TOY return patterns than stocks in which institutions trade. Taken together, our results suggest that institutions play a limited role in driving the TOY effect.