Bradford Cornell, J. Kimball Dietrich, Mean-Absolute-Deviation Versus Least-Squares Regression Estimation of Beta Coefficients, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 1 (Mar., 1978), pp. 123-131

The commercial banking industry has been buffeted by a variety of forces in recent years. Alternating periods of intense monetary restraint and the severity of the 1973–74 economic contraction (especially as it affected the real estate industry), huge losses on loan portfolios, a heavy commitment of funds to less developed countries on the part of a few major banks, and the failures of a number of individual banks have created considerable discussion about the stability of the banking system. Questions have been raised about the risk involved in committing funds to the securities of banking organizations. Moreover, the importance of these questions has been underscored for bank management by the necessity for many banking organizations to raise substantial amounts of external funds to prevent further depletion of existing capital ratios.

Glenn H. Petry, Russell J. Fuller, The Geographic Distribution of Papers at the Seven Academic Finance Associations in the United States, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 4, Proceedings of Thirteenth Annual Conference of the Western Finance Association, June 20-26, 1978 (Nov., 1978), pp. 785-794

to prepare and allow a large number of options. The program can be run in batch mode or interactively at a computer terminal. Computer core storage is dynamically allocated so that large problems are only limited by the size of the machine. SHAZAM is designed to grow so that new algorithms and procedures can easily be added by any programmer familiar with the internal structure of the program. Features of SHAZAM include ordinary least squares, two-stage least squares, seemingly unrelated regressions and iterative estimation of seemingly unrelated regressions, threestage least squares and iterative three-stage least squares, models with first and second order autocorrelated disturbances, estimation of Box-Cox [1] type nonlinear functional forms, principal components and factor analysis, regression on principal components, ridge regression, regressions by matrix decompositions, random number generatign for Monte Carlo samples, forecasting, and plotting. Any set of linear restrictions or hypothesis tests can be used in the estimation. A wide variety of output statistics are available with each procedure. The autocorrelation section of SHAZAM is rather extensive and includes maximum likelihood or least squares estimation by a grid search or iterative Cochrane-Orcutt [2] procedure and inclusion or deletion of initial observations, exact and higher-order DurbinWatson [4] type tests, tests based on Golub's [6] uncorrelated residuals, Dhrymes [3, p. 199] corrections for lagged dependent variables, Savin-White [7] corrections for missing observations in a time series, Savin-White [8] type simultaneous testing for functional form and autocorrelation, and forecasting using Goldberger's [5] best linear unbiased predictor. A SHAZAM user's manual [9], which is also machine readable, is available from the author on request.

[A gap is filled in a proof of a central limit theorem, for regression in a time series context, which has been used in some econometric theory.]

Using the result that under the null hypothesis of no misspecification an asymptotically efficient estimator must have zero asymptotic covariance with its difference from a consistent but asymptotically inefficient estimator, specification tests are devised for a number of model specifications in econometrics. Local power is calculated for small departures from the null hypothesis. An instrumental variable test as well as tests for a time series cross section model and the simultaneous equation model are presented. An empirical model provides evidence that unobserved individual factors are present which are not orthogonal to the included right-hand-side variable in a common econometric specification of an individual wage equation.

T HIS is a study of interrelated demand for capital and labor. In a purely static model capital and labor demand functions will usually contain common production function parameters and prices and thus may be viewed as a system of interrelated equations. There are two additional reasons why the interrelated characteristic may be important in a dynamic disequilibrium model. First, if one input is less than a desired or long-run equilibrium value, demand for other inputs may be dependent on the shortage of the first input. Second, the actual process of adjustment may influence demand for other inputs via costs of adjustment. In this article we develop and estimate parameters of labor and capital demand functions where both the deviation of capital from a target value (KK*) and costs of adjustment influence labor demand. Nadiri and Rosen (1969) is a well-known study of interrelated factor demand arising for the first reason noted above. They develop a multivariate flexible accelerator relationship