This study identifies several interrelated reasons why firms’ depreciation method choice is likely to influence managers’ capital investment decisions. We find that firms that use accelerated depreciation make significantly larger capital investments than firms that use straight-line depreciation. Further, we find that there has been a migration away from accelerated depreciation to straight-line depreciation over the past two decades. Firms that make such accounting changes make smaller capital investments in the post-change periods than in the pre-change periods. These results suggest that a choice made for external financial reporting purposes influences managers’ capital investment decisions.

Thomas Schelling's Strategy of Conflict is a masterpiece that should be recognized as one of the most important and influential books in social theory. This paper reviews some of the important ideas in Strategy of Conflict and considers some of the broader impact that this book has had on game theory, economics, and social theory. By his emphasis on the critical importance of information and commitment in strategic dynamics, Schelling played a vital role in stimulating the development of non-cooperative game theory. More broadly, Schelling's analysis of games with multiple equilibria has redefined the scope of economics and its place in the social sciences. (JEL D74, F51, H56)

I review recent empirical research documenting offer premiums and bidding strategies in corporate takeovers. The discussion ranges from optimal auction bidding to the choice of deal payment form and premium effects of poison pills. The evidence describes the takeover process at a detailed level, from initial premiums to bid jumps, entry of rival bidders, and toehold strategies. Cross-sectional tests illuminate whether bidders properly adjust for winner's curse, whether target stock price runups force offer price markups, and whether auctions of bankrupt firms result in fire-sale discounts. The evidence is suggestive of rational strategic bidding behavior in specific contexts.

We show that acquirer returns are significantly higher in stock-swap acquisitions of difficult-to-value targets, as measured by R&D intensity and idiosyncratic return volatility. This finding contributes to an explanation of the determinants of, and value gains from, using stock as a method of payment. The effects of target-valuation uncertainty on both the method of payment and the market reaction to acquisitions are more likely to be apparent in samples of private acquisitions, as these effects can be masked in samples of acquisitions of publicly held targets. Nevertheless, our results hold for publicly traded targets in multivariate analysis.

[A new methodology is proposed to estimate theoretical prices of financial contingent claims whose values are dependent on some other underlying financial assets. In the literature, the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples. This paper proposes a simulation-based method. When it is used in connection with ML, it can improve the finite-sample performance of the ML estimator while maintaining its good asymptotic properties. The method is implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond and bond option pricing model. It is especially favored when the bias in ML is large due to strong persistence in the data or strong nonlinearity in pricing functions. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims when ML is biased. The bias reductions are sometimes accompanied by reductions in variance. Empirical applications to U. S. Treasury bills highlight the differences between the bond prices implied by the simulation-based approach and those delivered by ML. Some consequences for the statistical testing of contingent-claim pricing models are discussed.]

[Commodity derivatives are becoming an increasingly important part of the global derivatives market. Here we develop a tractable stochastic volatility model for pricing commodity derivatives. The model features unspanned stochastic volatility, quasi-analytical prices of options on futures contracts, and dynamics of the futures curve in terms of a low-dimensional affine state vector. We estimate the model on NYMEX crude oil derivatives using an extensive panel data set of 45,517 futures prices and 233,104 option prices, spanning 4082 business days. We find strong evidence for two predominantly unspanned volatility factors.]

[We develop a tractable and flexible stochastic volatility multifactor model of the term structure of interest rates. It features unspanned stochastic volatility factors, correlation between innovations to forward rates and their volatilities, quasi-analytical prices of zerocoupon bond options, and dynamics of the forward rate curve, under both the actual and risk-neutral measures, in terms of a finite-dimensional affine state vector. The model has a very good fit to an extensive panel dataset of interest rates, swaptions, and caps. In particular, the model matches the implied cap skews and the dynamics of implied volatilities.]

[We investigate whether the geographic dispersion of a firm affects corporate decision making. Our findings suggest that social factors work alongside informational considerations to make geography important to corporate decisions. We show that (i) geographically dispersed firms are less employee friendly; (ii) dismissals of divisional employees are less common in divisions located closer to corporate headquarters; and (iii) firms appear to adopt a "pecking order" and divest out-of-state entities before those in-state. To explain these findings, we consider both information and social factors. We find that firms are more likely to protect proximate employees in soft information industries (i.e., when information is difficult to transfer over long distances). However, employee protection holds only when the headquarters is located in a less populated county, suggesting a role for social factors. Additionally, stock markets respond favorably to divestitures of in-state divisions.]

The importance of cash-flow uncertainty in payout policy has received little attention in empirical studies, while survey studies such as [Lintner, J., 1956. Distribution of incomes of operations among dividends, retained earnings, and taxes. American Economic Review 46, 97–113.] and [Brav, A., Graham, J., Harvey C., Michaely, R., 2005. Payout policy in the 21st century. Journal of Financial Economics 77, 483–527.] indicate its importance. With worldwide firm-level data, we present evidence that cash-flow uncertainty is an important cross-sectional determinant of corporate payout policy. Our results show that across countries, cash-flow uncertainty, as proxied by stock return volatility, has a negative impact on the amount of dividends as well as the probability of paying dividends. The impact of cash-flow uncertainty on dividends is generally stronger than the impact of other potential determinants of payout policy—such as the earned/contributed capital mix, agency conflicts, and investment opportunities. We also find that the effect of cash-flow uncertainty on dividends is distinct from the effect of a firm's financial life-cycle stage.

[We provide experimental evidence that relaxing margin restrictions to allow more short selling can exacerbate overpricing, even though it reduces equilibrium price levels. This is because smart-money traders initially profit more by front-running optimistic investor sentiment than by disciplining prices. When short selling is not possible, competitive pressures among arbitrageurs rapidly drive prices to the equilibrium. However, the risk of margin calls slows the convergence process, because arbitrageurs who sell short too early face substantial losses if they are unable to synchronize their trades with other arbitrageurs (as in Abreu and Brunnermeier. 2002.]