Knowledge that Transforms

At the request of Edwin N. Hurley, then Vice-Chairman and later Chairman of the Federal Trade Commission, the President of the American Association of Public Accountants (predecessor of the American Institute of Accountants), J. Porter Joplin, appointed a special committee to confer with the trade commission on all questions of accounting. Robert H. Montgomery was Chairman of the eight-member committee. The most important accomplishment of the committee was the promulgation of a programme for audit procedure which was prepared at the request of the Federal Trade Commission, approved by the commission and transmitted to the Federal Reserve Board... . The audit program in its final form was unanimously approved by the members of the council.2 The Federal Reserve Board published the text in the Federal Reserve Bulletin (April 1, 1917) and reprinted it in pamphlet form in 1917 and again in 1918 for general distribution. The text also appeared in the Journal

Income smoothing, Chemical industry, Real smoothing, Artificial smoothing

Accounting changes, Depreciation, Inventory valuation

Transfer Pricing, Decentralized firm

The construction of tests of model specification is considered from a general point of view. The results are applied to testing the serial independence of the disturbances in a regression model where some of the regressors are lagged dependent variables. It is shown that the asymptotic distribution of the lag-1 serial correlation coefficient calculated from the least-squares residuals differs from that of the coefficient calculated from the true disturbances. A consequence of this is that tests of serial independence based on the residuals from regression on fixed regressors are invalid when applied to models containing lagged dependent variables even when the null hypothesis of serial independence is true. Tests which are asymptotically valid for the large-sample case are suggested.

FOR VARIOUS REASONS, data availability being not the least of these, empirical studies of production processes can often be carried out more conveniently in terms of cost functions instead of production functions. Assuming cost minimizing behavior by entrepreneurs, cost function studies can, in principle, reveal the same information [23, 26]. Such dual cost functions have an empirical difficulty in common with production functions, however. They must be concave and linear homogeneous in input prices so that, when limitations of known estimation techniques are considered, the choice of appropriate algebraic structure is severely restricted. Even when only economies of scale information is desired, the preferred time-series studies [27, p. 39ff] are placed under this handicap since construction of a proper index to deflate price variation is equivalent to specification and parameter estimation of a production function [16]. For this reason, attention is directed to the sometimes criticized cross-section studies where input price variation may be negligible.

[The parameters of a system of demand equations are estimated subject to the prior information of classical demand theory. The equations are estimated as a system using a variant of generalized least squares, the parametric restrictions being imposed by Lagrange multipliers. Tests of significance are given, both for individual restrictions and for the restrictions applied collectively. The method is applied to Barten's sixteen commodity consumer expenditure data for Holland. The work was done independently of R. H. Court's [6] similar treatment; however, there are significant differences in the method which warrant further discussion and the application is itself of some interest.]

[The problem to be considered in this paper is that in a linear regression model, y = Xβ + ε (where X is n × k of rank r ≤ k), the disturbance vector ε′ = ( extlesstex-math extgreater$ extbackslashvarepsilon _\1\, extbackslashvarepsilon _\2\,..., extbackslashvarepsilon _ $ extless/tex-math extgreater) is distributed according to the null hypothesis, H0, as multivariate normal with mean vector 0 and variance-covariance matrix proportional to extlesstex-math extgreater$ extbackslashSigma _\0$ extless/tex-math extgreater, against the alternative hypothesis, H_1, that it is distributed as multivariate normal with mean vector 0 and variance-covariance matrix proportional to Σ _1. Three test statistics, extlesstex-math extgreaters_\1\,s_\2\ extless/tex-math extgreater, and s_3, all functions of estimated disturbances from the fitted regression are proposed to test the hypothesis H_0. It is shown (in Section 3) that all three tests based on extlesstex-math extgreaters_\1\,s_\2\ extless/tex-math extgreater, and s_3 are unbiased and that the test T(1) based on s_1 is most powerful. In Section 4, ε is assumed to have a special covariance structure, namely, a first order stationary Markov process, uniform covariance structure, and moving average of order one, and the general results obtained in Section 3 are simplified. It is also shown that the hypothesis H_0, in general, cannot be tested and that only an implication of it can be tested. Section 5 contains three numerical illustrations comparing the results proposed in this study with the Durbin-Watson procedure.]