We document that gold mining firms have consistently realized economically significant cash flow gains from their derivatives transactions. We conclude that these cash flows have increased shareholder value since there is no evidence of an offsetting adjustment in firms’ systematic risk. This finding contradicts a central assumption in the risk management literature that derivatives transactions have zero net present value, and highlights an important motive for firms to use derivatives that the literature has hitherto ignored. Although we find considerable evidence of selective hedging in our sample, the cash flow gains from selective hedging appear to be small at best.

We examine the role of cash flow from operations (CFO) in chief executive officer (CEO) cash compensation. We predict that CFO is contract‐relevant in the presence of earnings, and more so when (1) the quality of earnings relative to the quality of CFO as a measure of performance is low and (2) the need for CFO as a financing source is high. Our analysis is motivated principally by normative arguments and anecdotes from financial disclosures linking CFO to managerial effort and contracts, notwithstanding the traditional role of earnings in performance measurement. We find that the weight of CFO in the compensation model is positive and significant in the presence of earnings and stock returns. We also find that the relative quality of CFO compared with that of earnings has a positive (negative) impact on the weight of CFO (earnings). We further find that the relative weight of CFO is enhanced substantially when enterprise activities crucially depend on internally generated cash flow. These findings are unaltered when we include CEO age, firm size, and risk in the model and allow the coefficients to vary across industries.

Comparisons of learning models in repeated games have been a central preoccupation of experimental and behavioral economics over the last decade. Much of this work begins with pooled estimation of the model(s) under scrutiny. I show that in the presence of parameter heterogeneity, pooled estimation can produce a severe bias that tends to unduly favor reinforcement learning relative to belief learning. This occurs when comparisons are based on goodness of fit and when comparisons are based on the relative importance of the two kinds of learning in hybrid structural models. Even misspecified random parameter estimators can greatly reduce the bias relative to pooled estimation.

If investors are myopic mean-variance optimizers, a stock's expected return is linearly related to its beta in the cross-section. The slope of the relation is the cross-sectional price of risk, which should equal the expected equity premium. We use this simple observation to forecast the equity-premium time series with the cross-sectional price of risk. We also introduce novel statistical methods for testing stock-return predictability based on endogenous variables whose shocks are potentially correlated with return shocks. Our empirical tests show that the cross-sectional price of risk (1) is strongly correlated with the market's yield measures and (2) predicts equity-premium realizations, especially in the first half of our 1927–2002 sample.

We develop a comprehensive and parsimonious measure of corporate financing activities and document a negative relation between this measure and both future stock returns and future profitability. The economic and statistical significance of our results is stronger than in previous research focusing on individual categories of corporate financing activities. To discriminate between risk versus misvaluation as explanations for this relation, we analyze the association between our measure of external financing and sell-side analysts’ forecasts. Consistent with the misvaluation explanation, our measure of external financing is positively related to overoptimism in analysts’ forecasts.

This paper provides direct evidence supporting the tax‐loss selling hypothesis as an explanation of the January effect. Examining turn‐of‐the‐year return and volume patterns for municipal bond closed‐end funds, which are held mostly by tax‐sensitive individual investors, we document a January effect for these funds, but not for their underlying assets. We provide evidence that this effect can be largely explained by tax‐loss selling activities at the previous year‐end. Moreover, we find that funds associated with brokerage firms display more tax‐loss selling behavior, suggesting that tax counseling plays a role.

In this article, we provide a novel rationale for credit ratings. The rationale that we propose is that credit ratings serve as a coordinating mechanism in situations where multiple equilibria can obtain. We show that credit ratings provide a “focal point” for firms and their investors, and explore the vital, but previously overlooked implicit contractual relationship between a credit rating agency (CRA) and a firm through its credit watch procedures. Credit ratings can help fix the desired equilibrium and as such play an economically meaningful role. Our model provides several empirical predictions and insights regarding the expected price impact of rating changes.

Matriculation in U.S. Economics Ph.D. Programs: How Many Accepted Americans Do Not Enroll? by T. Aldrich Finegan, Wendy A. Stock and John J. Siegfried. Published in volume 96, issue 2, pages 453-457 of American Economic Review, May 2006

We use U.S. county data (3,058 observations) and 41 conditioning variables to study growth and convergence. Using ordinary least squares (OLS) and three-stage least squares with instrumental variables (3SLS-IV), we report on the full sample and metro, nonmetro, and and regional samples: (1) OLS yields convergence rates around 2%; 3SLS yields 6%–8%; (2) convergence rates vary (for example, the Southern rate is 2.5 times the Northeastern rate); (3) federal, state, and local government negatively correlates with growth; (4) the relationship between educational attainment and growth is nonlinear; and (5) the finance, insurance, and real estate industry and the entertainment industry correlate positively with growth, whereas education employment correlates negatively.