We examine an unusual sample of firms within the life insurance industry: 30 firms which switched from a common-stock to a mutual-ownership structure. Our evidence indicates that the rate of growth of premium income from policyholders remains unchanged, stockholders receive a premium for their stock, and management turnover declines; thus, no group of claimholders systematically loses in the sample of firms which choose to go through the mutualization process. We therefore conclude that for this sample of firms, changing from a stock to a mutual-ownership structure is on average efficiency-enhancing.

Abstrac-t-The profits of leading firms in concentrated markets may be due to market share related cost efficiencies or market power. One way to identify the separate effect of market power is to analyze the relationship of market concentration and market share to the prices charged by firms in local geographic markets. This study analyzes the prices charged by supermarkets in local Vermont markets. Prices are significantly higher in more concentrated markets. The Herfindahl index, as a concentration measure, out-performs the four-firm or one-firm concentration ratio. Herfindahl marginally out-performs a firm's market share as a predictor of its price level.

Research Methodology, Market reaction, Sequential events, Contemporaneous returns

THIS PAPER INVESTIGATES a property of estimators called stability. The stability exponent of an estimator is a measure of the magnitude of the effect of any single observation in the sample on the realized value of the estimator. A number of reasons related to robustness suggest that often it is desirable for an estimator to be relatively insensitive to any particular observation in the sample, i.e., to have high stability. In addition, it is useful for diagnostic purposes to have knowledge of the stability exponents of different estimators, in order to know which estimators are likely to rely more heavily on some single observation. The paper is organized as follows: Section 1 introduces the basic idea contained in the paper, motivates it, and summarizes the results in an informal manner. Section 2 presents definitions, assumptions, and the general results. For purposes of illustration, the linear regression model with the least squares estimator is used as a running example throughout this section. Section 3 discusses numerous additional applications of the general results. An Appendix contains proofs of

Donald W. K. Andrews, A Note on the Unbiasedness of Feasible GLS, Quasi-Maximum Likelihood, Robust, Adaptive, and Spectral Estimators of the Linear Model, Econometrica, Vol. 54, No. 3 (May, 1986), pp. 687-698

A new methodology for statistically testing contingent-claims asset-pricing models based on asymptotic statistical theory is proposed. It is introduced in the context of the Black-Scholes option-pricing model, for which some illustrative estimation, inference, and simulation results are also presented. The proposed methodology is then extended to arbitrary contingent claims by first considering the estimation problem for general Itô processes and then deriving the asymptotic distribution of a general contingent claim which depends upon such Itô processes.