While the literature shows that perks can affect firm values positively or negatively, we argue that firms with higher perks are more likely to be associated with a lower quality of financial reporting, which, in turn, can affect the informativeness of stock prices. Based on hand-collected data on perks from Chinese listed firms, we find that firms with lower perks are associated with higher informativeness of stock prices (or lower R-square). Moreover, the positive association between perks and R-square is shown to be weaker for firms with higher financial reporting quality through audit and earnings quality measures.

Dale T. Mortensen delivered his Prize Lecture on 8 December 2010 at Aula Magna, Stockholm University.(This abstract was borrowed from another version of this item.)

When agents can learn about their abilities as active investors, they rationally “trade to learn ” even if they expect to lose from active investing. The model used to develop this insight draws conclusions that are consistent with empirical study of household trading behavior: Households ’ portfolios underperform passive investments; their trading inten-sity depends on past performance; and they begin by trading small sums of money. Using household data from Finland, the article estimates a structural model of learning and trad-ing. The estimated model shows that investors trade to learn even if they are pessimistic about their abilities as traders. It also demonstrates that realized returns are significantly downward-biased measures of investors ’ true abilities. (JEL D10, G11) While most households adjust their stock portfolios only infrequently, some trade very actively and underperform passive investments.1 I ask whether a model in which investors rationally learn from experience can explain this be-havior, and, if so, what the model tells us about households ’ beliefs. In my model, investors are uncertain about their abilities and learn as they trade. If the value of observing another signal is high, then an investor trades even if she expects to lose money, thus apparently trading “too much. ” If a trade is successful, the investor infers skill and subsequently trades more. If an investor loses money, she will infer less skill and subsequently trade less. After enough losses, she stops trading altogether. Investors who are especially uncertain about their abilities trade small amounts early in their careers until

[We find that repeated borrowing from the same lender translates into a 10—17 bps lowering of loan spreads and that relationships are especially valuable when borrower transparency is low. These results hold using multiple approaches (propensity score matching, instrumental variables, and treatment effects model) that control for the endogeneity of relationships. We also provide a demarcation line between relationship and transactional lending. Spreads charged for relationship loans and nonrelationship loans are statistically identical if the borrower is in the largest 30% by asset size; has public rated debt; or is part of the S&P 500 index. Past relationships reduce collateral requirements and are also associated with obtaining larger loans. Our results imply that, even for firms that have multiple sources of outside financing, borrowing from a prior lender obtains better loan terms.]

[We propose a new, valuation-based measure of world equity market segmentation. While we observe decreased levels of segmentation in many countries, the level of segmentation remains significant in emerging markets. We characterize the factors that account for variation in market segmentation both through time as well as across countries. Both a country's regulation with respect to foreign capital flows and certain nonregulatory factors are important. In particular, we identify a country's political risk profile and its stock market development as two additional local segmentation factors as well as the U.S. corporate credit spread as a global segmentation factor.]

Estimating the cost of regulation is difficult. Firms sometimes reveal costs indirectly, however, when they exploit loopholes to avoid regulation. We apply this insight to fuel economy standards for automobiles. These standards feature a loophole that gives automakers a bonus when they equip a vehicle with flexible-fuel capacity. Profit-maximizing automakers will equate the marginal cost of compliance using the loophole, which is observable, with the unobservable costs of strategies that genuinely improve fuel economy. Based on this insight, we estimate that tightening standards by one mile per gallon would have cost automakers just 9–27 per vehicle in recent years.

This paper analyzes the predictive power of a new data set of consumer gasoline price forecasts taken from the Michigan Survey of Consumers (MSC). MSC data generally perform as well as a no-change forecast in predicting future gasoline prices, and they substantially out-perform the no-change forecast during the recent economic crisis, during which time they track futures market prices. Finally, the cross-respondent dispersion of the MSC forecasts increases substantially during the economic crisis, paralleling the large increase in price volatility at this time.

We document the cross-sectional properties of corporate dividend-smoothing policies and relate them to extant theories. We find that younger, smaller firms, firms with low dividend yields and more volatile earnings and returns, and firms with fewer and more disperse analyst forecasts smooth less. Firms that are cash cows, with low growth prospects, weaker governance, and greater institutional holdings, smooth more. We also document that dividend smoothing has steadily increased over the past 80 years, even before firms began using share repurchases in the mid-1980s. Taken together, our results suggest that dividend smoothing is most common among firms that are not financially constrained, face low levels of asymmetric information, and are most susceptible to agency conflicts. These findings provide challenges and guidance for the developing theoretical literature.