In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^dr, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^dr, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^dr. These results show that the bias of ^dr goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^dr attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.

Using a unique set of banking data containing both originally reported and subsequently revised financial variables, we find adverse revisions to accounting statements are associated with downgrades in supervisory ratings. To assess the financial significance of the revisions, we compare the ability of the original and revised data to map into exam ratings. The relationship between accounting data and exam results is significantly stronger for revised data than for real-time data. Our findings document significant differences between real-time and revised banking data, highlight the auditing role of bank exams, and provide a more realistic assessment of early warning model accuracy.

We examine theories of leverage and debt maturity, focusing on the impact of firms' investment opportunity sets and regulatory environments in determining these policies. Using results on strategic complementarities, we identify sufficient conditions for the theory to have testable implications for reduced-form and structural-equation regression coefficients. Obtaining testable implications for structural equations requires less from the theory but more from the data than the reduced-form specification because it requires an instrumental-variables approach. We examine this trade-off between theory and statistical methods and provide tests using two decades of data for over 5000 industrial firms.

Agency theory implies that asset ownership and decision authority are complements. Using 1998 data from Texas commercial banks, we test whether the likelihood of local ownership of bank offices increases with the importance of granting local managers greater decision authority (for example, due to location or customer base). Our empirical evidence is consistent with this hypothesis. It suggests that complementarities between strategy and organizational structure can foster differentiation among firms in terms of location, customers, and products. It also supports the growing view that small locally-owned banks have a comparative advantage over large banks within specific environments.

We present a model of mergers and acquisitions based on stock market misvaluations of the combining firms. The key ingredients of the model are the relative valuations of the merging firms and the market's perception of the synergies from the combination. The model explains who acquires whom, the choice of the medium of payment, the valuation consequences of mergers, and merger waves. The model is consistent with available empirical findings about characteristics and returns of merging firms, and yields new predictions as well.

In sharp contrast to results in the United States, the average stock price response to an announcement of a seasoned equity issue in Japan is positive. Offer prices in Japan, unlike the United States, are announced several days before the beginning of the subscription period and incorporate a substantial discount. We suggest that the positive announcement effects in Japan are consistent with the underwriter's certification of the issuing firm's value. We characterize the underwriter's risk as a put option and find a positive association between the underwriter's risk and the announcement returns, as well as other results consistent with underwriter certification.

Although institutional investors have a preference for large capitalization stocks, over time they have shifted their preferences toward smaller, riskier securities. These changes in aggregate preferences have arisen primarily from changes in the preferences of each class of institution, rather than changes in the importance of different classes. Evidence also suggests that recent growth in institutional investment combined with this shift in preferences helps explain why markets in general, and smaller stocks in particular, have exhibited greater firm-specific risk and liquidity in recent years. Additional analyses suggest that institutional investors moved toward smaller securities because such securities offer "greener pastures."

abstract Researchers and practitioners in accounting and finance often investigate or advocate particular disciplined trading strategies, but little work investigates the determinants of individual investors' trading‐strategy reliance. We report two experiments, which provide evidence that the dual‐source model of overconfidence (Sniezek and Buckley [1991]) predicts the circumstances in which investors are more likely to rely on disciplined trading strategies. Our results indicate that reliance is more likely when investors trade portfolios of securities rather than trading on a case‐by‐case basis, particularly when investors have received feedback that their previous (unaided) trading decisions have been unprofitable. These results are driven by the number of shares that investors transact rather than by investors' directional agreement with the recommendations of the trading strategy, suggesting that the effects of a portfolio approach and trading experience occur by mitigating investors' overconfidence. The effects violate an aspect of economic rationality because our experiments ensure that investors in all conditions trade the same set of securities based on the same set of information.

Abstract This paper reports an experiment demonstrating that MBA students overrely on old earnings performance when predicting future earnings performance in a laboratory setting. In the experiment, MBA students relied too heavily on old annual ROE information to predict future annual ROE. The experiment shows how a common cognitive error (overreliance on unreliable information) interacts with the structure of the earnings time series to create particular patterns of prediction errors. The results also suggest directions for research on two well‐known anomalies, long‐run overreactions (De Bondt and Thaler 1985, 1987) and post‐earnings‐announcement drift (Bernard and Thomas 1990).

A fundamentals based monetary policy rule, which would be the optimal monetary policy without commitment when private agents have perfectly rational expectations, is unstable if in fact these agents follow standard adaptive learning rules. This problem can be overcome if private expectations are observed and suitably incorporated into the policy maker's optimal rule. These strong results extend to the case in which there is simultaneous learning by the policy maker and the private agents. Our findings show the importance of conditioning policy appropriately, not just on fundamentals, but also directly on observed household and firm expectations.