We evaluate the costs and benefits of restrictive covenants in bonds issued in 1989 and 1996. Our results indicate that firms with growth opportunities are more likely to seek to preserve flexibility in future financing activities by not including dividend or debt issuance restrictions in their bond contracts. We do not find, however, that the use of other restrictive covenants is significantly lower for firms with high investment opportunities. Instead, the use of these other covenants is primarily driven by the issuing firm's likelihood of financial distress. Our results emphasize that contractual relations between firms and bondholders reflect the specific needs of the contracting parties.

Swedish bankruptcy filing automatically terminates the employment of the chief executive officer (CEO) and triggers an auction of the firm. Critics of this system warn of excessive shareholder risk-shifting incentives prior to filing. We argue that private benefits of control induce managerial conservatism that may override shareholder risk-shifting incentives. By investing conservatively, the CEO increases the joint probability that the auction results in a going-concern sale and that the CEO is rehired. This uniquely implies that the rehiring probability is increasing in private control benefits, which our empirical results support. We also find that buyers in the auction screen on CEO quality. Overall, labor market discipline is dramatic, as filing CEOs suffer large income losses relative to CEOs of matched, non-bankrupt firms. Firms emerging from auction bankruptcy appear healthy as they typically go on to perform at par with industry rivals.

Comparing the Risks of Social Security with and without Individual Accounts by Sita Nataraj and John B. Shoven. Published in volume 93, issue 2, pages 348-353 of American Economic Review, May 2003

We develop an algorithm for detecting teacher cheating that combines information on unexpected test score fluctuations and suspicious patterns of answers for students in a classroom. Using data from the Chicago public schools, we estimate that serious cases of teacher or administrator cheating on standardized tests occur in a minimum of 4–5 percent of elementary school classrooms annually. The observed frequency of cheating appears to respond strongly to relatively minor changes in incentives. Our results highlight the fact that high-powered incentive systems, especially those with bright line rules, may induce unexpected behavioral distortions such as cheating. Statistical analysis, however, may provide a means of detecting illicit acts, despite the best attempts of perpetrators to keep them clandestine.

This paper characterizes empirically achievable limits for time series econometric modeling and forecasting. The approach involves the concept of minimal information loss in time series regression and the paper shows how to derive bounds that delimit the proximity of empirical measures to the true probability measure (the DGP) in models that are of econometric interest. The approach utilizes joint probability measures over the combined space of parameters and observables and the results apply for models with stationary, integrated, and cointegrated data. A theorem due to Rissanen is extended so that it applies directly to probabilities about the relative likelihood (rather than averages), a new way of proving results of the Rissanen type is demonstrated, and the Rissanen theory is extended to nonstationary time series with unit roots, near unit roots, and cointegration of unknown order. The corresponding bound for the minimal information loss in empirical work is shown not to be a constant, in general, but to be proportional to the logarithm of the determinant of the (possibility stochastic) Fisher–information matrix. In fact, the bound that determines proximity to the DGP is generally path dependent, and it depends specifically on the type as well as the number of regressors. For practical purposes, the proximity bound has the asymptotic form (K/2)log n, where K is a new dimensionality factor that depends on the nature of the data as well as the number of parameters in the model. When ‘good’ model selection principles are employed in modeling time series data, we are able to show that our proximity bound quantifies empirical limits even in situations where the models may be incorrectly specified. One of the main implications of the new result is that time trends are more costly than stochastic trends, which are more costly in turn than stationary regressors in achieving proximity to the true density. Thus, in a very real sense and quantifiable manner, the DGP is more elusive when there is nonstationarity in the data. The implications for prediction are explored and a second proximity theorem is given, which provides a bound that measures how close feasible predictors can come to the optimal predictor. Again, the bound has the asymptotic form (K/2)log n, showing that forecasting trends is fundamentally more difficult than forecasting stationary time series, even when the correct form of the model for the trends is known.

Measured by the ratio of trade to output, the period 1870–1913 marked the birth of the first era of trade globalization and the period 1914–1939 its death. What caused the boom and bust? We use an augmented gravity model to examine the gold standard, tariffs, and transport costs as determinants of trade. Until 1913 the rise of the gold standard and the fall in transport costs were the main trade-creating forces. As of 1929 the reversal was driven by higher transport costs. In the 1930s the final collapse of the gold standard drove trade volumes even lower.

We examine ex‐dividend date trading of American Depositary Receipts (ADRs) using a sample of 1,043 dividends over the period 1988 to 1995. ADR dividends are often subject to foreign withholding taxes, creating incentives for certain investors to avoid the distribution. ADRs exhibit negative abnormal ex‐dividend day returns, and their prices behave consistently with their related withholding taxes. Abnormal trading volume for taxable issues exceeds 130 percent and 300 percent of normal volume on the cum‐ and ex‐dates, respectively. Abnormal volume is an increasing function of foreign withholding tax rates and decreasing function of transactions costs. This abnormal ex‐date trading activity is consistent with tax‐motivated trading.

We decompose the cross‐sectional variance of firms' book‐to‐market ratios using both a long U.S. panel and a shorter international panel. In contrast to typical aggregate time‐series results, transitory cross‐sectional variation in expected 15‐year stock returns causes only a relatively small fraction (20 to 25 percent) of the total cross‐sectional variance. The remaining dispersion can be explained by expected 15‐year profitability and persistence of valuation levels. Furthermore, this fraction appears stable across time and across types of stocks. We also show that the expected return on value‐minus‐growth strategies is atypically high at times when their spread in book‐to‐market ratios is wide.

Prior research suggests that investors' response to analyst forecast revisions increases with the analyst's forecast accuracy. We extend this research by examining whether investors appear to extract all of the information that analyst characteristics provide about forecast accuracy. We find that only some of the analyst characteristics that are associated with future forecast accuracy are also associated with return responses to forecast revisions. This suggests that investors fail to extract some of the information that analyst characteristics can provide about future forecast accuracy. In addition, forecast properties other than expected accuracy appear to be value-relevant. For example, investors respond more strongly to forecasts released earlier in the year and to forecasts by analysts employed by large brokerages than appears warranted by the ability of forecast timeliness and broker size to predict forecast accuracy. We conclude that investors respond to analysts' forecast revisions as if forecast accuracy is not all that matters.