This paper investigates the relation between the value of a firm and employee attitudes on the firm's workplace quality—workplace attitudes. Workplace attitude refers to recognition of those organizational characteristics that enhance employee work experiences and assist employees in balancing their jobs and personal lives. Using inclusion on Fortune's annual list of “The 100 Best Companies to Work for in America” as a proxy for successful efforts in creating high workplace attitudes, we compare the market values of listed firms to the market values of nonlisted firms in the same industry matched on earnings. After controlling for book value, past operational performance, and research and development expense, we find that market values of listed firms exceed those of matched firms. We also provide evidence that firms ranked high on the Fortune list receive higher market values than those ranked lower on the list. Finally, the two-year forward market returns for listed firms exceed the returns for the matched sample while the two-year prior returns are not significantly different between the two groups. This result suggests that market performance does not determine inclusion on the Fortune list.

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The first objective of this study is to describe the substantial differences across property-liability insurers in accounting classification decisions for fixed maturity securities during 1991–1995. This period includes the years before adoption, upon initial adoption, and after adoption of Statement of Financial Accounting Standards No. 115 (FAS 115, “Accounting for Certain Investments in Debt and Equity Securities”). The second and more important objective of this study is to test two risk-based explanations for differences in investment classification decisions under FAS 115. Under this new standard, firms are required to classify fixed maturity investment securities into trading portfolios, available-for-sale portfolios, or held-to-maturity portfolios. These classification decisions determine whether these securities are recognized at fair value or historical cost. On one hand, the decision to classify securities as available-for-sale rather than held-to-maturity (and thus apply fair value accounting) increases the time-series volatility of key accounting numbers such as owners' equity and total assets, which may be costly for insurers with low tolerance for accounting volatility. On the other hand, the choice to classify securities as available-for-sale (and thus apply fair value accounting) reduces liquidity risk because the accounting standards (and SEC enforcement practices) limit management's ability to sell securities that are not recognized at fair value. The empirical analyses examine whether the security classification decisions of the sample property-liability insurers are associated with firm specific characteristics that reflect liquidity risk and the tolerance for accounting volatility. The findings show that managers of property-liability insurers make tradeoffs between liquidity risk and concerns about accounting volatility when making investment classification decisions under FAS 115.

This study utilizes the National Collegiate Athletic Association basketball point spread betting market to investigate whether differences in information availability across markets result in different relative efficiencies of price formation within those markets. Using intra-conference games of various conferences as clearly defined markets, we show that these markets are efficient given the information available in those markets. However, we also show that regression error variances are significantly smaller (greater) for those conferences with greater (lesser) information availability. This evidence supports previous stock market research suggesting that differential fundamental information availability across stock markets results in differential departures from equilibrium values. Copyright Blackwell Publishers Ltd 2001.

Several authors have recently explored the estimation of binary choice models based on asymmetric error structures. One such family of skewed models is based on the exponential generalized beta type 2 (EGB2). One model in this family is the skewed logit. Recently, McDonald (1996, 2000) extended the work on the EGB2 family of skewed models to permit heterogeneity in the scale parameter. The aim of this paper is to extend the skewed logit model to allow for heterogeneity in the skewness parameter. By this we mean that, in the model developed, here the skewness parameter is permitted to vary from observation to observation by making it a function of exogenous variables. To demonstrate the usefulness of our model, we examine the issue of the predictive ability of sports seedings. We find that we are able to obtain better probability predictions using the skewed logit model with heterogeneous skewness than can be obtained with logit, probit, or skewed logit.