Abstract The literature on international equity holdings distinguishes between home bias (overweighting of home stocks) and foreign bias (relative underweighting for more “distant” countries). The two biases can be integrated into one distance-based model. We define pure home bias as the excess of home bias relative to this model, and find pure home bias only in emerging markets. Countries with high tax rates and low credit standing have higher pure home bias, and more development comes with lower distance aversion. Methodologically, the choice of portfolio bias measure matters. We find the best measure to be a covariance-based measure relative to the world average.

Previous work suggests that the charter value hypothesis is theoretically grounded and empirically supported, but not universally. Accordingly, this paper aims to perform an analysis of the relations between charter value, risk taking, and supervision, taking into account the relations’ complexity. Specifically, using the CAMELS rating system as a general framework for supervision, we study how charter value relates to risk and supervision by means of classification and regression tree analysis. The sample covers the period 2005–2016 and consists of listed banks in countries that were members of the Eurozone when it came into existence, along with Greece. To evaluate the crisis consequences, we also separately analyze four subperiods and countries that required financial aid from third parties and those that did not so, along with large and small banks. Our results reflect the complexity of the relations between charter value, supervision, and risk. Indeed, supervision and charter value seem aligned regarding only some types of risk.

ABSTRACT The literature on the usefulness of analysts’ cash flow forecasts is unsettled, with Call et al. ( ), Mohanram ( ), and Radhakrishnan and Wu ( ) providing evidence in favor of their usefulness, and Givoly et al. ( ), Bilinski ( ), and Ecker and Schipper ( ) questioning this. Target prices provide a good setting to test the usefulness of cash flow forecasts because they are an ultimate output of an analyst's valuation process to which cash flow forecasts are an input. Moreover, studying the effect of cash flow forecasts on target prices is more relevant for assessing their usefulness than is studying their effect on earnings‐forecast accuracy, as the accuracy of target prices requires a comparison with market prices, which are less subject to management influence than reported earnings. By improving an analyst's understanding of unexpected accruals and permanent earnings, a cash flow forecast can increase an analyst's target price accuracy and signal an analyst's superior forecasting ability. We examine whether, conditional on their earnings forecasts, analysts’ cash flow forecasts improve their target price accuracy. We find that when analysts issue cash flow forecasts, their target price accuracy increases. We also find that this accuracy increases with the accuracy of their cash flow forecasts. Finally, we find that this increased target price accuracy is greater for more challenging‐to‐value firms. Our study provides confirmatory evidence of the usefulness of analysts’ cash flow forecasts.

This study documents the fact that large dividend increases are followed by a significant increase in leverage, consistent with management increasing the dividend to use up excess debt capacity. However, the leverage increase is not captured by a standard partial adjustment model of leverage. Nor does it reflect variables known to be related to dividend increases, such as firm maturity, investment, and risk. Instead, the dividend increase signals a complex change in the way firms adjust to their leverage target, but it does not signal a change in the target.

This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change discontinuously at the threshold of the so-called running variable. This contrasts to the common practice of testing the weaker implication of continuity of the means of the covariates at the threshold. When testing our null hypothesis using observations that are “close ” to the threshold, the standard requirement for the finite sample validity of a permutation test does not necessarily hold. We therefore propose an asymptotic framework where there is a fixed number of closest observations to the threshold with the sample size going to infinity, and propose a permutation test based on the so-called induced order statistics that controls the limiting rejection probability under the null hypothesis. In a simulation study, we find that the new test controls size remarkably well in most designs. Finally, we use our test to evaluate the validity of the design in Lee (2008), a well-known application of the RDD to study incumbency advantage.

We develop a measure to capture an audit firm's competitive position in a local audit market based on the transaction costs of changing audit firms included in DeAngelo's (1981) multi-period audit pricing model. Our competition measure reflects the size difference between the largest audit firm in a market specified by client industry at the city level and the other audit firms operating in that market. We find that audit fees of a client decrease as this size difference increases. This result suggests that smaller audit firms charge lower audit fees because of their competitive disadvantage to the local largest firm.

We present new identification results for a class of nonseparable nonparametric simultaneous equations models introduced by Matzkin (2008). These models combine traditional exclusion restrictions with a requirement that each structural error enter through a “residual index.†Our identification results are constructive and encompass a range of special cases with varying demands on the exogenous variation provided by instruments and the shape of the joint density of the structural errors. The most important results demonstrate identification when instruments have only limited variation. Even when instruments vary only over a small open ball, relatively mild conditions on the joint density suffice. We also show that the primary sufficient conditions for identification are verifiable and that the maintained hypotheses of the model are falsifiable.

We describe a symmetric continuous-time model of trading among relatively overconfident, oligopolistic informed traders with exponential utility. Traders agree to disagree about the precisions of their continuous flows of Gaussian private information. The price depends on a trader’s inventory (permanent price impact) and the derivative of a trader’s inventory (temporary price impact). More disagreement makes the market more liquid; without enough disagreement, there is no trade. Target inventories mean-revert at the same rate as private signals. Actual inventories smoothly adjust towards target inventories at an endogenous rate which increases with disagreement. Faster-than-equilibrium trading generates “flash crashes” by increasing temporary price impact. A “Keynesian beauty contest” dampens price fluctuations.

Unprecedented street protests brought down Mubarak's government and ushered in an era of competition between three rival political groups in Egypt. Using daily variation in the number of protesters, we document that more intense protests are associated with lower stock market valuations for firms connected to the group currently in power relative to non-connected firms, but have no impact on the relative valuations of firms connected to rival groups. These results suggest that street protests serve as a partial check on political rent-seeking. General discontent expressed on Twitter predicts protests but has no direct effect on valuations.