Students of the innovative process in American manufacturing have emphasized the scarcity of labor and the consequent need for labor-saving machines. In the late nineteenth century one of the country's largest manufacturing industries was the production of carriages, which, in its most important center, Cincinnati, was organized on a mass production basis. But Professor Duggan finds that problems of the quantity and quality of labor were secondary in carriage factories, compared to other factors such as fuel costs, factory space, and the need to stabilize the quality and price of vehicles marketed by the industry as a whole.

Whatever the shortcomings of “no-fault” employee compensation laws, such as the one passed in Massachusetts in 1911, Professor Gersuny shows that such laws were a great improvement over what had prevailed. Working with formerly confidential files, he shows that an “adversary relationship” had existed between the employer and his insurance company, on the one hand, and often pitifully maimed employees on the other. With few exceptions, all of the advantages were on the side of the employer, and the rights of employees to more than token compensation were routinely trampled upon.

Define Rt as the ratio of the value of an asset at the end of the tthperiod to its value at the end of the previous period. Rt is then a one-period relative equal to unity plus the interest rate. Assume that Rt is an independent, normally distributed random variable with mean μ and nonzero variance σ2. Rt is then observed as

where the disturbance term ∈t t is independently and normally distributed with mean zero and variance σ2. To assess the long-term expected rate of return of the asset, it is desirable to estimate its expected increment in value of the one-period relative raised to the Nth power, i.e., μN.

In this study two alternative techniques to analyze pooled time-series and cross-section data are used to test the importance of firm effect and time effect in the financial analysis. These techniques are also integrated with the functional form parameter estimation method to show the importance of appropriate functional form in handling a pooled time-series and cross-section type econometric model. The data on the electric industry show that both the time effect and cross-section effect are of importance in explaining stock price variation. It is also found that linear form (and/or) log-linear form is not always appropriate in testing the importance of both time effect and firm effect in financial analyses.

The API metric, as initially formulated by Ball and Brown [1], has been used to examine the relationship between stock prices and accounting numbers. Its use in this manner has raised at least three difficulties: (1) the metric does not utilize all of the information portentially available from accounting numbers, (2) the statistical significance of the API metric and of differences between API's has not always been satisfactorily considered, and (3) the meaning of the metric has been questioned. This paper will attempt to resolve these difficulties by reformulating the API approach. Two nonparametric statistical procedures are considered, both of which provide a test of the statistical significance of the relationship between accounting income numbers and stock prices. The first procedure is particularly appropriate when alternative accounting income numbers are considered. Both procedures provide a conventional unambiguous interpretation of the results.

The purpose of this paper has been to empirically test Stone's Two-Index Model. The results are mixed, but generally favor the model. Adding a bond index term for the bank sample only marginally improves the model's explanatory power although the index is more important than the equity index. The lack of importance of the bond index for banks is not surprising upon further consideration, however. Banks and their earnings should be more sensitive to short-term rather than long-term rates, and the index reflects primarily long-term rates. To the extent that short- and long-term rates moved in different directions during the sample period, negative correlation is introduced between bank's returns and the index.

The bond index improves in performance for the 30 Dow Jones firms and contributes to the explanatory power of the model in 80 percent of the cases. There is some instability in signs and, contrary to Stone's speculations, omission of the bond index does not bias the equity beta estimates.

Finally, we caution the reader against generalizing about the long-run value of the two-index model. The short time period used here does not allow us to say anything about the relationship between interest rate movements and the stability of beta. Moreover, during the 1969–1972 period the returns on the bond and equity indexes did not behave as Capital Market Theory would predict. The average monthly return on the bond portfolio was .5 percent and the average return on the equity portfolio was .2 percent. Our findings must, therefore, be interpreted with care, but overall the introduction of interest rate effects into the single-index model looks promising.

A student of financial theory must always assume that managers will follow a course of action that will lead to a higher value of the firm rather than a lower value, given a choice between two courses of action. Yet, Lewellen and Racette (hereafter LR) in a recent paper [1] comparing the sale of convertible debentures with the sale of straight debt assumed that managers will behave in a way that will lead to submaximal firm value. The purpose of this paper is to correct the LR error.