We analyze the potential competitive effects of the proposed Basel II capital regulations on US bank credit card lending. We find that bank issuers operating under Basel II will face higher regulatory capital minimums than Basel I banks, with differences due to the way the two regulations treat reserves and gain-on-sale of securitized assets. During periods of normal economic conditions, this is not likely to have a competitive effect; however, during periods of substantial stress in credit card portfolios, Basel II banks could face a significant competitive disadvantage relative to Basel I banks and nonbank issuers.

The article contributes to the literature on financial fragility, studying how macroeconomic shocks affect supply and demand in the corporate debt market. We take into account the effect of the competitive environment, as well as the risk level, measured by companies’ default rate. The model is estimated using data from the Harmonised BACH database of corporate accounts for large euro area countries on the 1993–2005 period, in order to carry out an illustrative stress testing exercise. We measure the impact of large macroeconomic shocks (a severe recession and a sharp increase in oil prices) on the equilibrium in the debt market.

[Using a sample of municipal bond offerings, I find that "local" investment banks have substantial comparative and absolute advantages over nonlocal counterparts--locals charge lower fees and sell bonds at lower yields. Local investment banks' strongest comparative advantage is at underwriting bonds with higher credit risk and bonds not rated by rating agencies. These findings suggest that high-risk bonds and nonrated bonds are more difficult to evaluate and market, and that investment banks with a local presence are better able to assess "soft" information and place difficult bond issues.]

Using a sample of municipal bond offerings, I find that "local" investment banks have substantial comparative and absolute advantages over nonlocal counterparts---locals charge lower fees and sell bonds at lower yields. Local investment banks' strongest comparative advantage is at underwriting bonds with higher credit risk and bonds not rated by rating agencies. These findings suggest that high-risk bonds and nonrated bonds are more difficult to evaluate and market, and that investment banks with a local presence are better able to assess "soft" information and place difficult bond issues. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected], Oxford University Press.

We develop a model in which investment banks and institutional investors collaborate in smoothing an initial public offering's (IPOs) transition to secondary market trading. Their intervention promotes welfare under the assumption that significant new information arrives in the market in the immediate aftermath of the IPO. Under this assumption, it is optimal to stage the offering and suboptimal to commit to selling shares at a uniform price. The optimal strategy yields an economic rationale for secondary market price stabilization for IPOs carried out via a well-coordinated network of repeat institutional investors.

This paper examines the motivations for public equity offers, using a sample of 17,226 initial public offerings and 13,142 seasoned equity offerings from 38 countries between 1990 and 2003. We estimate the uses of funds raised in both initial and seasoned offerings. Firms appear to spend incremental dollars on both R&D and capital expenditures, consistent with the investment financing explanation of equity issues. However, consistent with the mispricing explanation, high market to book firms tend to save more cash and offer a higher fraction of secondary shares in SEOs than low market to book firms.

We develop a framework to assess how successfully standard time series models explain low-frequency variability of a data series. The low-frequency information is extracted by computing a finite number of weighted averages of the original data, where the weights are low-frequency trigonometric series. The properties of these weighted averages are then compared to the asymptotic implications of a number of common time series models. We apply the framework to twenty U.S. macroeconomic and financial time series using frequencies lower than the business cycle. Copyright 2008 The Econometric Society.

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator is root-N consistent and asymptotically normally distributed with zero asymptotic bias. Valid inferential methods in this setting are the analytic asymptotic variance estimator of Abadie and Imbens (2006a) as well as certain modifications of the standard bootstrap, like the subsampling methods in Politis and Romano (1994).