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Testing static tradeoff against pecking order models of capital structure1This paper has benefited from comments by seminar participants at Boston College, Boston Unsiversity, Dartmouth College, Massachusetts Institute of Technology, University of Massachusetts, Ohio State University, University of California at Los Angeles and the NBER, especially Eugene Fama and Robert Gertner. The usual disclaimers apply. Funding from MIT and the Tuck School at Dartmouth College is gratefuly acknowledged. We also thank two reviewers, Richard S. Ruback and Clifford W. Smith, Jr., for helpful comments.1

Journal of Financial Economics 1999 51(2), 219-244
This paper tests traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater time-series explanatory power than a static tradeoff model, which predicts that each firm adjusts gradually toward an optimal debt ratio. We show that our tests have the power to reject the pecking order against alternative tradeoff hypotheses. The statistical power of some usual tests of the tradeoff model is virtually nil.

Financial contracting under extreme uncertainty: an analysis of Brazilian corporate debentures

Journal of Financial Economics 1999 51(1), 45-84
Economic volatility, high transaction costs, and fragile institutions hinder financial contracting in emerging markets. These conditions characterize the economy of Brazil, yet a nascent corporate bond market thrives. I analyze 50 Brazilian indenture agreements and find that sample debentures are characterized by (i)features that mitigate inflation risk for investors, (ii)contingent-maturity mechanisms that provide periodic opportunities for exit or renegotiation, (iii)a paucity of covenants that restrict the debtor's investment, financing, and dividend decisions, and (iv)self-enforcement mechanisms that avoid reliance on inefficient institutions. Analysis of these features enhances our understanding of contracting in emerging economies.

The Impact of Multiple Component Reporting on Tax Compliance and Audit Strategies

The Accounting Review 1999 74(1), 63-85
Prior studies of the strategic interaction between taxpayers and the tax authority have focused on reported net taxable income and on audit policies designed to discover potential misstatement of that single item. This paper extends the literature by modeling taxpayer compliance behavior and tax authority audit strategies within the context of a multidimensional report of taxable income. Specifically, the study analyzes the impact of component reporting requirements on taxpayer incentives to misstate their tax liability. It also allows the tax authority to tailor its audit policy to consider all tax return information. In particular, the model permits the tax authority to audit return components sequentially: the investigation of a second component is conditional on the results of the first component's audit. The study finds that partitioning taxable income into a multi-component report reduces overall tax evasion and increases tax authority net revenue collections relative to a singlereport model of net taxable income. However, the impact on predicted evasion is not uniform across taxpayers. While some taxpayers reduce evasion, others with multiple opportunities to evade are more likely to do so when faced with multi-component reporting requirements.

Some Income-Measurement Issues and Their Policy Implications

American Economic Review 1999 89(2), 29-33
This paper discusses some major categories of nonpecuniary income: noncash benefits for lower-income households and for the elderly, and the imputed rent of owner-occupied housing. These are three of the 15 categories in the comprehensive income definition developed by Timothy M. Smeeding and Daniel H. Weinberg (1998). They are certainly important, and their measurement has been controversial. Government outlays on Medicare in 1998 totaled $190 billion; outlays on the three major low-income benefit programs (Medicaid, food stamps, and housing subsidies) were $145 billion. The rental value of owneroccupied housing is harder to measure, but larger; as of 1995 the market sales value of the stock may have been over $10 trillion (Arthur B. Kennickell and R. Louise Woodburn, 1997), and conventional rules of thumb in the housing industry yield an annual rental value of at least $1 trillion. The paper considers both conceptual issues and their policy significance. Economists and policymakers are most interested in three statistics of income: the well-being of the average American, the well-being of those at the bottom of the income distribution, and the overall distribution of income, usually measured as median household or family income, the poverty rate, and the Gini ratio. As many economists have noted, we as a society are most interested in how these measures change over time and differ between groups. Such comparisons provide the context for the current numbers. When the data are announced, the media immediately compare the current income and poverty figures to last year, the last cyclical peak or trough, or the all-time best or worst; and also compare households by race, ethnicity, and gender of household head. (The Gini ratio attracts less attention because it has no intuitive explanation for the layman.) In this paper, I focus on how the measurement issues affect these statistics.

The effect of reporting restructuring charges on analysts’ forecast revisions and errors

Journal of Accounting and Economics 1999 27(3), 261-284
The frequency and magnitude of restructuring charges have drawn the attention of various groups of users of accounting information. Prior studies on restructuring charges have focused on the market's response to the announcement of the charge. In contrast, we examine the charges from the perspective of financial analysts. We provide evidence that analysts expect declining performance for restructuring firms in the short run but possible improvement over the longer term. When we examine forecast errors in the year following the charge, we find evidence that the analysts’ accuracy has declined and, despite the downward revision, analysts are still optimistically biased.

On Portfolio Optimization: Forecasting Covariances and Choosing the Risk Model

Review of Financial Studies 1999 12(5), 937-974
[We evaluate the performance of models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. We compare the models' forecasts of future covariances and the optimized portfolios' out-of-sample performance. A few factors capture the general covariance structure. Portfolio optimization helps for risk control, and a three-factor model is adequate for selecting the minimum-variance portfolio. Under a tracking error volatility criterion, which is widely used in practice, larger differences emerge across the models. In general more factors are necessary when the objective is to minimize tracking error volatility.]