One hesitates to write history as it happens, or to draw policy lessons from current events. The conference took place in May 2008 - after the government-assisted takeover of Bear Stearns but before a capital market downturn fueled a system-wide liquidity crisis, with successive insolvencies at IndyMac, Fannie Mae, Freddie Mac, Lehman, AIG, WaMu, and, as I write, Citigroup. But it would be odd to comment on capital market regulation without mentioning the events of the last three months. I am first to acknowledge that anything I might have written in May would not have foreseen the crisis or linked capital market regulation to financial institutions, which in the US have been conventionally treated as discrete in discourse and institutions (e.g., U.S. Treasury 2008; Leuz and Wysocki 2008).

Abstract Most US credit card holders revolve high-interest debt, often with substantial liquid and retirement assets. We model separation of accounting from shopping allowed by credit cards, in a rational, dynamic game. When the shopper is more impatient than the accountant, selling assets to repay debt is not necessarily optimal, as the shopper can restore debt. Modest relative impatience generates asset-debt co-existence and target utilization rates, matching incidence and median assets of debt revolvers with substantial assets. Empirical evidence is consistent with a role for spending control considerations, after allowing for standard determinants of credit card debt.

Prior evidence that higher-quality financial reporting improves capital investment efficiency leaves unaddressed whether it reduces over- or under-investment. This study provides evidence of both in documenting a conditional negative (positive) association between financial reporting quality and investment for firms operating in settings more prone to over-investment (under-investment). Firms with higher financial reporting quality also are found to deviate less from predicted investment levels and show less sensitivity to macro-economic conditions. These results suggest that one mechanism linking reporting quality and investment efficiency is a reduction of frictions such as moral hazard and adverse selection that hamper efficient investment.

This study examines the effect of firm-level corporate governance on the cost of equity capital in emerging markets and how the effect is influenced by country-level legal protection of investors. We find that firm-level corporate governance has a significantly negative effect on the cost of equity capital in these markets. In addition, this corporate governance effect is more pronounced in countries that provide relatively poor legal protection. Thus, in emerging markets, firm-level corporate governance and country-level shareholder protection seem to be substitutes for each other in reducing the cost of equity. Our results are consistent with the finding from McKinsey's surveys that institutional investors are willing to pay a higher premium for shares in firms with good corporate governance, especially when the firms are in countries where the legal protection of investors is weak.

Extant research suggests that book-tax differences are useful measures in evaluating firm performance. There is little evidence, however, regarding taxable income as an alternative performance measure to book income. We examine firm characteristics that mitigate or enhance the ability of taxable income to inform investors regarding firm performance. We find that the relative and incremental information content of estimated taxable income to book income is lower for high tax planning firms and higher for low earnings quality firms. Our results suggest that tax planning and low earnings quality have contrasting effects on the information content of estimated taxable income. These findings are pertinent to recent research examining book-tax differences as a measure of earnings quality and taxable income as an alternative performance measure.

We study two-sided markets with a finite number of agents on each side, and with two-sided incomplete information. Agents are matched assortatively on the basis of costly signals. Asymmetries in signalling activity between the two sides of the market can be explained by asymmetries either in size or in heterogeneity. Our main results identify general conditions under which the potential increase in expected output due to assortative matching (relative to random matching) is offset by the costs of signalling. Finally, we examine the limit model with a continuum of agents and point out differences and similarities to the finite version. Technically, the paper is based on the elegant theory about stochastic order relations among differences of order statistics, pioneered by Barlow and Proschan in 1966 in the framework of reliability theory.

This paper examines how costly financial contracting and weak investor protection influence the cross-border operational, financing, and investment decisions of firms. We develop a model in which product developers can play a useful role in monitoring the deployment of their technology abroad. The analysis demonstrates that when firms want to exploit technologies abroad, multinational firm (MNC) activity and foreign direct investment (FDI) flows arise endogenously when monitoring is nonverifiable and financial frictions exist. The mechanism generating MNC activity is not the risk of technological expropriation by local partners but the demands of external funders who require MNC participation to ensure value maximization by local entrepreneurs. The model demonstrates that weak investor protections limit the scale of MNC activity, increase the reliance on FDI flows, and alter the decision to deploy technology through FDI as opposed to arm's length technology transfers. Several distinctive predictions for the impact of weak investor protection on MNC activity and FDI flows are tested and confirmed using firm-level data. (c) 2009 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology..

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.

ABSTRACT I identify three option exercise strategies executives engage in, including (i) exercising with cash and immediately selling the shares, (ii) exercising with cash and holding the shares, and (iii) delivering some shares to the company to cover the exercise costs and holding the remaining shares. Stock price patterns suggest executives manipulate option exercises. They use private information to increase the profitability of all three strategies, and likely backdated some exercise dates in the pre‐Sarbanes‐Oxley period to enhance the profitability of the latter two strategies, where the executive's company is the only counterparty. Backdating is associated with reporting of internal control weaknesses.