This article presents information on evaluating alternative methods of accounting for long-term nonsubsidiary holdings of common stock. Long-term investments by one corporation (investor) in the common stock of another corporation (investee) can be classified in one of two basic categories according to the percentage of the common stock of the investee corporation held by the investor corporation. Holdings of more than 50 percent are classified as subsidiary holdings while holdings of 50 percent or less are classified as nonsubsidiary holdings. Under the cost method, "periodic investor income" consists of dividends received by the investor which are distributed from the investor's proportionate share of undistributed investee earnings accumulated since the acquisition of the investment. The book value of the investment on the investor's books, hereafter referred to as "investment carrying value," is periodically reduced by any dividends received in which distributions in excess of investee earnings since acquisition of the investment. Such dividends are referred to in this paper as "excess dividends." Finally, Opinion 18 states that a senes of operating losses of an investee or other factors may indicate that a decrease in value of the investment has occurred which is other than temporary and should accordingly be recognized.

O. C. Ashenfelter, G. E. Johnson, J. H. Pencavel; Trade Unions and the Rate of Change of Money Wages in United States Manufacturing Industry12, The Review

1. Elementary Aspects of Multivariate Analysis.- 1.1 Preliminaries.- 1.2 Joint, Marginal, and Conditional Distributions.- 1.3 A Mathematical Digression.- 1.4 The Multivariate Normal Distribution.- 1.5 Correlation Coefficients and Related Topics.- 1.6 Estimators of the Mean Vector and Covariance Matrix and their Distribution.- 1.7 Tests of Significance.- 2. Applications of Multivariate Analysis.- 2.1 Canonical Correlations and Canonical Variables.- 2.2 Principal Components.- 2.3 Discriminant Analysis.- 2.4 Factor Analysis.- 3. Probability Limits, Asymptotic Distributions, and Properties of Maximum Likelihood Estimators.- 3.1 Introduction.- 3.2 Estimators and Probability Limits.- 3.3 Convergence to a Random Variable: Convergence in Distribution and Convergence of Moments.- 3.4 Central Limit Theorems and Related Topics.- 3.5 Miscellaneous Useful Convergence Results.- 3.6 Properties of Maximum Likelihood (ML) Estimators.- 3.7 Estimation for Distribution Admitting of Sufficient Statistics.- 3.8 Minimum Variance Estimation and Sufficient Statistics.- 4. Estimation of Simultaneous Equations Systems.- 4.1 Review of Classical Methods.- 4.2 Asymptotic Distribution of Aitken Estimators.- 4.3 Two-Stage Least Squares (2SLS).- 4.4 2SLS as Aitken and as OLS Estimator.- 4.5 Asymptotic Properties of 2SLS Estimators.- 4.6 The General k-Class Estimator.- 4.7 Three-Stage Least Squares (3SLS).- 5. Applications of Classical and Simultaneous Equations Techniques and Related Problems.- 5.1 Estimation of Production and Cost Functions and Specification Error Analysis.- 5.2 An Example of Efficient Estimation of a Set of General Linear (Regression) Models.- 5.3 An Example of 2SLS and 3SLS Estimation.- 5.4 Measures of Goodness of Fit in Multiple Equations Systems: Coeficient of (Vector) Alienation and Correlation.- 5.5 Canonical Correlations and Goodness of Fit in Econometric Systems.- 5.6 Applications of Principal Component Theory in Econometric Systems.- 5.7 Alternative Asymptotic Tests of Significance for 2SLS Estimated Parameters.- 6. Alternative Estimation Methods Recursive Systems.- 6.1 Introduction.- 6.2 Indirect Least Squares (ILS).- 6.3 The Identification Problem.- 6.4 Instrumental Variables Estimation.- 6.5 Recursive Systems.- 7. Maximum Likelihood Methods.- 7.1 Formulation of the Problem and Assumptions.- 7.2 Reduced Form (RF) and Full Information Maximum Likelihood (FIML) Estimation.- 7.3 Limited Information (LIML) Estimation.- 8. Relations Among Estimators . Monte Carlo Methods.- 8.1 Introduction.- 8.2 Relations Among Double k-Class Estimators.- 8.3 I.V., ILS, and Double Ar-Class Estimators.- 8.4 Limited Information Estimators and Just Identification.- 8.5 Relationships Among Full Information Estimators.- 8.6 Monte Carlo Methods.- 9. Spectral Analysis.- 9.1 Stochastic Processes.- 9.2 Spectral Representation of Covariance Stationary Series.- 9.3 Estimation of the Spectrum.- 10. Cross-Spectral Analysis.- 10.1 Introduction.- 10.2 Cross Spectrum: Cospectrum, Quadrature Spectrum, and Coherency.- 10.3 Estimation of the Cross Spectrum.- 10.4 An Empirical Application of Cross-Spectral Analysis.- 11. Approximate Sampling Distributions and Other Statistical Aspects of Spectral Analysis.- 11.1 Aliasing.- 11.2 Prewhitening, Recoloring, and Related Issues.- 11.3 Approximate Asymptotic Distributions Considerations of Design and Analysis.- 12 Applications of Spectral Analysis to Simultaneous Equations Systems.- 12.1 Generalities.- 12.2 Lag Operators.- 12.3 An Operator Representation of the Final Form.- 12.4 Dynamic Multipliers and the Final Form.- 12.5 Spectral Properties of the Final Form.- 12.6 An Empirical Application.- Mathematical Appendix.- A.1 Complex Numbers and Complex-Valued Functions.- A.2 The Riemann-Stieltjes Integral.- A.3 Monotonie Functions and Functions of Bounded Variation.- A.4 Fourier Series.- A.5 Systems of Difference Equations with Constant Coefficients.- A.6 Matrix Algebra.

T HIS study investigates within a comrnon analytical framework the determinants of firm expenditures o;n capital investment, research and development and dividends. Its two basic objectives relative to past work are: first, to probe more deeply into the forces determining these outlays by taking into account the interdependencies among them,' and second, to provide a framework for evaluating alternative assumptions regarding firm motivation. A firm maximizing stockholder objectives will exhibit different behavior in its expenditure decisions from one pursuing managerial goals. Consequently, two main variants of a model of firm expenditures, based on these rival concepts of motivation, are developed and tested.

M ANY cross-section studies exist in the literature attempting to explain variations in per capita state and local expenditures on such services as highways, municipal services, health, and education. Differences in per capita expenditures across states are explained in terms of such factors as differences in population densities, urban-rural distributions, average income levels, age distributions, and numbers of school-age children.' In most of these studies, however, the underlying theory has not been carefully spelled out and, in particular, it is never made clear whether the demographic variables are thought to enter on the demand side or on the supply side of the market for state and local services. In the first part of this paper we look at the theory underlying such regression studies of the determinants of state and local expenditures. We attempt to distinguish between the demand side of the market for such services and the supply (cost) side. In the second part of the paper we obtain empirical estimates of price and income elasticities of demand for state and local services for three broad classifications of services. Finally we discuss a number of interesting applications of our results.

The article reports that the evaluation of the cost control procedures applied to a process is facilitated by viewing the control objective as minimizing a whole set of costs including the efficiency cost incurred in the operation of the process and all of the control procedure costs. Thus, proposed changes in control procedures can be evaluated by determining their net effect on the total of this set of costs. Two approaches to controlling efficiency cost were discussed along with some indication of the types of procedures required by each. The first approach, that of preventive controls, has its primary effect on efficiency cost through the frequency of occurrence of operating problems. The second approach, that of detection-correction controls, has its effect on efficiency cost by influencing the length of time operating problems are allowed to exist in the process. It can be argued that budget performance reporting, a major contribution of the accountant to process cost control, serves both control approaches.