Much of the comparative economic history of the nineteenth century focuses on the spread of the Industrial Revolution from Britain. Incomes converged, in this view, as the transfer of superior technology raised incomes in the periphery. In Globalization and History, Kevin O'Rourke and Jeffrey Williamson challenge this technological approach, arguing that neoclassical effects of trade and factor supply changes provide more insight. Increased trade, stimulated by falling transportation costs, and factor movements caused prices of locally scarce factors to fall and promoted factor price convergence.

My colleagues at Williams, especially Thomas McCoy, James Halstead, Thomas Tietenberg, and Donald Keesing, gave me invaluable criticism on this paper. At an earlier stage, Mark Perlman 's comments were particularly helpful as were those of Roger Bolton, Stephen Lewis, William Gates, Helen Hughes, Earl McFarland and Francisco Thoumi. A Ford Foundation grant (720-0234), the Williams College Center for Development Economics and the World Bank Capital Utilization Research Project made important contributions to this work. Opinions and errors of fact or interpretation are, of course, all mine.

A preliminary draft of this paper was presented at the Decemnber, 1971 meetings of the Econometric Society. This paper has benefited from the perceptive comments of a number of readers; I am particularly indebted to Ronald Bodkin, Stewart Gillmor, Zvi Griliches, Sherwin Rosen and the referees. Assistance in data compilation was provided by Peter Brubaker, Maureen Donahoe, Charles Eckert, Marshall E. Goldman, Stephen Kalos, Lawrence Kenny, Richard LeClair, and Thurman Northcross. Computations were executed on the Wesleyan University IBM 1130 computer. Research support has been provided by Wesleyan University and National Science Foundation Research Grant GS 2903.

I would like to extend my thanks to my colleague, Harry G. Johnson, for hi8 helpful comments, to Daniel Wisecarver, for help extending well beyond the normal call of duty for a research assistant, and to Rudiger Dornbusch and Robert Gordon for valuable suggestions given after the first draft of this paper was completed. Needless to add, they do not bear any responsibility for such flaws or deficiencies as may remain in this paper.

Abstract We examine the role private equity (PE) sponsors play in the resolution of financial distress of portfolio companies. PE-backed firms have higher leverage and default at higher rates than other companies borrowing in leveraged loan markets. But, PE-backed firms restructure more quickly, avoid bankruptcy court more often, and liquidate less often compared to other highly leveraged firms experiencing financial distress. PE owners are also more likely to retain control post-restructuring, often by infusing capital as firms approach distress. While default frequencies are higher among PE-backed firms, PE investors appear to manage financial distress at lower cost compared to other owners. (JEL G23, G32, G33)

We examine the effects of structural change in the U.S. banking industry, as well as key regulatory changes, including recently enacted deposit insurance reform legislation, on the resiliency of the FDIC-administered bank insurance fund (BIF) by estimating and comparing the probability of BIF insolvency over time. We do this using a Markov-switching model that relies on historical patterns of BIF disbursements to define the probability of switching among three “states” of the banking industry's financial health. Monte Carlo simulations are then performed to project the financial condition of the BIF over a 50-year period. Our results indicate that the insolvency risk to the bank insurance fund has increased significantly due to industry consolidation, and is mainly due to the concentration of deposits in the 10 largest U.S. banking companies. We also find that recent deposit insurance reforms will cause only a marginal reduction in the risk of BIF insolvency. The increased risk associated with a more concentrated industry structure simply dominates the reform effect.

A fair level of provisions on bad and doubtful loans is an essential input in mark-to-market accounting, and in the calculation of bank profitability, capital and solvency. Loan-loss provisioning is directly related to estimates of loan-loss given default (LGD). A literature on LGD on bank loans is developing but, surprisingly, it has not been exploited to address, at the micro level, the issue of provisioning at the time of default, and after the default date. For example, in Portugal, the central bank imposes a mandatory provisioning schedule based on the time period since a loan is declared ‘non-performing’. The dynamic schedule is ‘ad hoc’, not based on empirical studies. The purpose of the paper is to present an empirical methodology to calculate a fair level of loan-loss provisions, at the time of default and after the default date. To illustrate, a dynamic provisioning schedule is estimated with micro-data provided by a Portuguese bank on recoveries on non-performing loans. This schedule is then compared to the regulatory provisioning schedule imposed by the central bank.

Many studies use the book value of debt as a proxy for its market value because most corporate debt does not trade. I call this practice the book value of debt (BVD) approximation, and it appears to be justified by the observation that the average market value of debt is close to its book value. Many corporate bonds, however, trade at values significantly different from their book values, and consequently the BVD approximation can create important biases. I compare the accuracy of the BVD approximation to Merton's option pricing (OPT) model of corporate debt valuation, and find consistent evidence that the Merton model provides more accurate estimates. I also show that this model is an easily estimated alternative to the BVD approximation. In short, the BVD approximation not only creates significant biases, but it is also an unnecessary simplification.