A solution method and an estimation method for nonlinear rational expectations models are presented in this paper.The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates.When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models.It is, however, more flexible and general than these methods.The estimation method is based on the maximum likelihood principal.It is, as far as we know, the only method available for obtaining maximum likelihood estimates for nonlinear rational expectations models.The method has the advantage of being applicable to a wide range of models, including, as a special case, linear models.The method can also handle different assumptions about the expectations of the exogenous variables, something which is not true of currently available approaches to linear models.

A ‘tax-loss selling’ hypothesis has frequently been advanced to explain the ‘January effect’ reported in this issue by Keim. This paper concludes that U.S. tax laws do not unambiguously predict such an effect. Since Australia has similar tax laws but a July–June tax year, the hypothesis predicts a small-firm July premium. Australian returns show pronounced December–January and July–August seasonals, and a premium for the smallest-firm decile of about four percent per month across all months. This contrasts with the U.S. data in which the small-firm premium is concentrated in January. We conclude that the relation between the U.S. tax year and the January seasonal may be more correlation than causation.

Over the last ten years, large corporations, have significantly increased their voluntary disclosures of socially-oriented information in annual reports. External organizations such as the Council on Economic Priorities (CEP) also have been active in producing information bearing on firms' social performances--particularly with respect to pollution control. This study investigates whether security price movements are associated with the release of externally produced information about companies' performances in the pollution-control area--information which has attributes of consistency and comparability not typically found in voluntarily reported, socially-oriented data. Specifically, the study investigates security price movements associated with the release of eight major studies conducted by the CEP of firms' environmental performances in four industries. The observed price movements are consistent with changes in investors' perceptions of the probability distributions of future cash flows of the sample firms at the times of release of the CEP studies. The reported results also are consistent with investors using the information released by the CEP to discriminate between companies with different pollution-control performance records.

A capital budgeting procedure is applied in developing a real price index for life insurance over three decades. Individual life policies of three types are analyzed. The analysis reveals that although the cost of whole life insurance, measured in nominal values, has decreased over the past thirty years, when properly measured in present value or constant dollar terms, the cost has risen substantially. Term life insurance has been characterized by decreasing costs in both nominal and real terms. The amounts of the cost variations attributable to improving survival rates, changing policy terms, varying discount rates and differing tax status are identified.