Incentive Effects of Rate-of-Return Regulation in Hong Kong: Reply

Journal of Regulatory Economics -     

COGNITIVE DISSONANCE AND MUTUAL FUND INVESTORS

We present evidence from questionnaire responses of mutual fund investors about recollections of past fund performance. We find that investor memories exhibit a positive bias, consistent with current psychological models. We find that the degree of bias is conditional upon previous investor choice, a phenomenon related to the well-known theory of cognitive dissonance. Psychological and economic frictions in the mutual fund industry are examined via a cross-sectional study of equity mutual funds. We find an unusually high frequency of poorly performing funds, consistent with investor “inertia.” We also examine the differential responses of investment dollars to past performance, controlling for survivorship. These show that the effect is confined to the top quartile. We find little evidence that the response to poor performance is unusual.     

Incentive effects of rate-of-return regulation: The case of Hong Kong electric utilities

A comparison of Hong Kong and United States rate-of-return regulation indicates differences in the definition of the rate base and in the proportion of it permitted a fair rate of return. These differences imply that Hong Kong electric utilities utilize proportionately more fixed (less current) assets, and that these assets are financed proportionately more by equity (less by debt), than their United States counterparts. Our results support both these predictions, providing further evidence that since rate-ofreturn regulation is implemented by reference to reported results, comparatively minor differences in regulatory frameworks can have quite dramatic consequences for utilities' asset structure and financing mix.     

Search for information and portfolio selection

The paper examines the problem of how to allocate scarce resources between increasing the investor's knowledge, that is reducing his uncertainty, and the actual investment—that is a kind of an ex ante decision before the final parameters of the securities are known. Our model provides answers to questions of how the search for knowledge affects portfolio selection, to what extent additional information can improve estimates of securities' statistical parameters and how the benefits and costs of additional search alter the investor's efficient mean-variance portfolio set.     

On measuring serial correlation: Implications for finance and accounting research studies

Accounting and finance studies that measure serial correlation implicitly make two assumptions. One, the studies assume that the sample estimate of the autocorrelation coefficient is unbiased. The assumption is intuitively appealing, but incorrect. This article provides a measure of the size of the bias. Two, the studies assume that the target of the time series is constant over time. However, over a long period target values may change. This article models the general case in which not only do random shocks affect actual values, but also random changes affect target values.