We examine the methods commonly employed to estimate Tobin's q ratios and find them to be flawed in design and arbitrary in implementation. We propose an alternative procedure which is both simpler and more accurate. The key to the procedure is an improved measure of fixed asset replacement costs, through the proper identification of the vintages of fixed assets that are in place for a firm. Application of this procedure to a large sample of nonfinancial corporations indicates that existing methods generally produce downward-biased measures of q and can result in errors in the ordering of firms by their q's.

ing, for the moment, from potential statistical and measurement problems, and in the absence of theoretical reasons to specify an alternative form of functional relationship, we may begin by postulating that a top executive's compensation is related in linear fashion to both the profits and sales of the firm he manages. The structural form of the relationship can be written: (1) Cit = ao + a,-rxi + a2Sij + ui, Where, C, r, and S represent executive compensation, corporate profits, and corporate sales, respectively, and u is a random disturbance term. Subscript i denotes the firm and subscript t the period to which the measure applies. By supplying a basis for observing the magnitude of the coefficients a, and a2 and the levels of statistical significance attaching thereto, the above specification provides a natural vehicle for inferring the relative influence of the two independent variables upon compensation, and thereby testing the alternative hypotheses. The emergence of a positive value for the constant term ao would imply, in effect, that executive rewards rise less than in proportion to company sales and/or profits. Thus, it seems probable that a $50 thousand difference in annual profits between two firms in the $100 million profit range would result in a smaller difference in the pay of their respective chief executives than would the same dollar profit difference in the case of two firms whose yearly earnings were in the $100 thousand range. Represented graphically, the compensation vs. profits or compensation vs. sales relationship would therefore be expected to be concave downward for a sample of enterprises differing widely in size, and the linear approximation to any segment of such an underlying relationship would necessarily include a positive intercept value. It follows, then, that a, and a2 must be interpreted in marginal-although constant for the sample range-terms throughout. Statistical Problems Unfortunately, direct application of equation (1) to any generalized sample of crosssectional data can be expected to encounter several possible sources of statistical bias. For one thing, the efficiency of least square estimates depends upon the variances of the disturbance terms being constant. Examination of scatter diagrams of pilot regression runs using equation (1) revealed, as anticipated, that the error terms were not constant but were approximately in proportion to the dependent variable. Moreover, and as one might also suspect, those firms relatively large by virtually any scale criterion were also characterized by relatively high sales and profits levels. This scale-associated linkage between the independent variables poses the threat of serious collinearity,4 with re4The high degrees of correlation between the independent variables in their natural form were indicated by the presence of simple correlation coefficients which in most cases, exceeded .9. This high degree of observed This content downloaded from 157.55.39.104 on Mon, 20 Jun 2016 05:40:33 UTC All use subject to http://about.jstor.org/terms

Research has shown that managers display self-serving behavior in a variety of discretionary information production decisions. We test whether such behavior is also manifest in discretionary information disclosure decisions — in particular, in the common stock return performance comparisons now required in corporate proxy statements. We find evidence that the industry and peer-company stock return benchmarks, and broader market indices, chosen by management for those comparisons are downward biased, thereby overstating relative reporting-firm performance. Cross-sectionally, the extent of the bias varies with key reporting-firm attributes, including firm performance and the character of firm ownership structure.

ABSTRACT Tax‐loss selling by investors in common stocks near the end of calendar years has been proposed as an explanation for the turn‐of‐the‐year effect in stock returns. Past analyses of this hypothesis have relied on inferential data. We provide here some direct data from a compilation of over 80,000 actual common stock investment round trips by a sample of 3000 individual investors. We find strong evidence of a concentration of loss‐taking trades late in the year and milder evidence of a concentration just prior to the dates when investments become eligible for long‐term tax treatment.

Tax-loss selling by investors in common stocks near the end of calendar years has been proposed as an explanation for the turn-of-the-year effect in stock returns. Past analyses of this hypothesis have relied on inferential data. We provide here some direct data from a compilation of over 80,000 actual common stock investment round trips by a sample of 3000 individual investors. We find strong evidence of a concentration of loss-taking trades late in the year and milder evidence of a concentration just prior to the dates when investments become eligible for long-term tax treatment.

Tax-loss selling by investors in common stocks near the end of calendar years has been proposed as an explanation for the turn-of-the-year effect in stock returns. Past analyses of this hypothesis have relied on inferential data. The authors provide here some direct data from a compilation of over 80,000 actual common stock investment round trips by a sample of 3,000 individual investors. The authors find strong evidence of a concentration of loss-taking trades late in the year and milder evidence of a concentration just prior to the dates when investments become eligible for long-term tax treatment.