This paper evaluates the effects of events leading to the passage of the Garn-St. Germain Depository Institutions Act of 1982. The evidence suggests that the call for reform by President Reagan's Housing Commission and the Senate passage of the bill produced positive abnormal returns to stockholders of large savings and loans and commercial banks. Stockholders of small S&Ls and banks, on the other hand, generally experienced negative abnormal returns. Furthermore, when hopes of passage of the act faded, significant negative (positive) abnormal returns were experienced by stockholders of large (small) S&Ls and banks.

This study reexamines the earlier finding of Michael J. Alderson and K. C. Chen (1986) that financial markets do not consider excess pension assets in determining share prices and that significant increases in shareholder wealth occur when an overfunded pension plan is terminated. The results document that specific event-time contamination (corporate restructuring announcements) provides the driving force for all the earlier findings.

Using daily and monthly stock returns, the authors find no convincing evidence that Federal Reserve margin requirements have served to dampen stock market volatility. The contrary conclusion, expressed in recent papers by Gikas Hardouvelis (1988), is traced to flows in his test design. The authors do detect the expected negative relation between margin requirements and the amount of margin credit outstanding. They also confirm the recent finding by William Schwert (1988) that changes in margin requirements by the Fed have tended to follow, rather than lead, changes in market volatility.

This paper analyzes the application of liability to large-scale, long-term hazards. The key features distinguishing such hazards are the long temporal separation between exposure to a hazard and disease and the large damages when injuries finally emerge. The large scale of damages creates a strong incentive to avoid liability payments, and the long temporal separation creates numerous avenues through which parties can avoid paying possible damage awards. The analysis focuses on the incentive to avoid paying damages by vertically divesting production tasks associated with serious occupational risks. Such divestiture can lower liability costs if the small firm operating the risky stage goes out of business before latent injuries emerge or has insufficient assets to pay damages and declares bankruptcy when suits are filed. The paper then presents an empirical regression analysis of small-firm entry into the U.S. economy between 1967 and 1980, the period in which liability laws were changing. The point estimate is that, ceteris paribus, liability changes appear to have led to a large increase in small corporations in hazardous sectors. Hence the empirical analysis shows widespread attempts to avoid liability by shielding assets through divestiture.

This paper analyzes the application of liability to large-scale, long-term hazards. The key features distinguishing such hazards are the long temporal separation between exposure to a hazard and disease and the large damages when injuries finally emerge. The large scale of damages creates a strong incentive to avoid liability payments, and the long temporal separation creates numerous avenues through which parties can avoid paying possible damage awards. The analysis focuses on the incentive to avoid paying damages by vertically divesting production tasks associated with serious occupational risks. Such divestiture can lower liability costs if the small firm operating the risky stage goes out of business before latent injuries emerge or has insufficient assets to pay damages and declares bankruptcy when suits are filed. The paper then presents an empirical regression analysis of small-firm entry into the U.S. economy between 1967 and 1980, the period in which liability laws were changing. The point estimate is that, ceteris paribus, liability changes appear to have led to a large increase in small corporations in hazardous sectors. Hence the empirical analysis shows widespread attempts to avoid liability by shielding assets through divestiture.

This paper considers estimation and hypothesis testing in linear time series when some or all of the variables have (possibly multiple) unit roots. The motivating example is a vector autoregression with some unit roots in the companion matrix, which might include polynomials in time as regressors. Parameters that can be written as coefficients on mean zero, nonintegrated regressors have jointly normal asymptotic distribution, converging at the rate of T(superscript "one-half") In general, the other coefficients (including the coefficient on polynomials in time), and associated t and F test statistics, have nonstandard asymptotic distributions.

[Management accountants are often required to construct measures of performance of individual managers by aggregating several accounting numbers (signals). We show that the same method of aggregation will rarely be used for evaluating the performance of different managers. Instead, the method of aggregation will vary with the specific preference functions of individual managers and the corresponding action choices induced by the owner. Such an optimal aggregate always exists but is not, in general, a sufficient statistic for the individual signals with respect to the agent's effort. We further show that, in most cases, using all the information in the sufficient statistic makes the principal strictly worse off. The analysis provides insights into a different statistical approach for evaluating nonsufficient aggregates based on the signal to noise ratio of the individual signals that are aggregated.]

This study finds a bibliometric regularity in the finance literature that the number of authors publishing n papers is about 1/n(superscript "c") of those publishing one paper. The authors find that the finance literature conforms very well to the inverse square law(c = 2) if data are taken from a large collection of journals. When applied to individual finance journals, they find that values of c range from 1.95 to 3.26. They also find that top-rated journals have higher concentrations among their contributors. This implies that the phenomenon "success breeds success" is more common in higher-quality publications.