Showing papers in "Journal of Econometrics in 1976"

TL;DR: In this paper, the authors rationalize certain functional forms of index numbers with functional forms for the underlying aggregator function, and show that a certain family of index number formulae is exact for the "flexible" quadratic mean of order r aggregator functions.

TL;DR: In this article, a trans-log joint production function based on the US private domestic economy is presented. But the authors consider the problem of numerical instability when the underlying (economic) data are nearly collinear and propose an adaptation of ridge regression concepts to canonical correlations.

TL;DR: In this paper, the authors present a method for computing predictions, prediction error variances, and confidence intervals, which can be implemented with any regression program, and demonstrate that a regression estimated for an augmented data set, obtained by combining n sample points with r forecast points, and including r dummy variables (each equalling one only for the corresponding forecast point), will yield r dummy variable coefficients and variances which equal the corresponding prediction errors and prediction error variance.

TL;DR: In this article, the authors show that all presently known estimators are readily derivable from the FIME formula if they are considered as numerical approximations to its solution, and then they classify the resulting estimators into asymptotically equivalent groups.

TL;DR: In this article, the identification conditions for a simultaneous equation model in which some of the exogenous variables are measured with error are established, assuming that observational information is confined to the covariance matrix of the observed variables and that prior information on the structural coefficients and error variances takes the form of zero restrictions.

TL;DR: In this article, several asymptotically efficient methods are suggested on both the full and the limited information approach to estimate the simultaneous equations model in which the lagged endogenous variables and the autoregressive disturbances coexist.

TL;DR: This paper found that low-income households not only spend a large share of their incomes on food, but exhibit a higher income elasticity of demand for food than does the rest of the population.

TL;DR: In this article, the authors used two sets of U.S. railroad data with two outputs and three inputs, and estimated production function parameters via the system of derived input demand functions, and via the dual cost function.

TL;DR: In this paper, it is proved that the true model from a set of alternative regression specifications involving different transformations of the same dependent variable is the formulation for which population R 2 is highest.

TL;DR: In this paper, the authors examined gains in efficiency from joint estimation of systems of ARMA processes where cross-correlation is due to contemporaneous correlation among disturbances and derived the asymptotic variance of joint estimates.

TL;DR: This article used an orthonormal regression model, a squared error loss measure and Monte Carlo procedures to compare the risk functions of traditional and Stein-rule pre-test estimators under a variety of conditions.

TL;DR: In this article, the product cycle of crude steel production may be observed as a gradual shift in the time trend parameter in the family of the CES production functions Quarterly data from 1957 to 1973 are used for the empirical test Posterior pdf's for the join point as well as for the adjustment parameter are derived.

TL;DR: In this article, the authors deal with specification, prediction and length of interval between the observations in an ARMA model and derive two types of quarterly series and derive the corresponding ARMA models.

TL;DR: In this article, the authors make use of Householder transformations and recursive triangulation solutions in presenting numerical algorithms for the computation of 3SLS and k-class estimates, and the singular value decomposition is valuable in providing additional information in k -class estimation.

TL;DR: In this article, the authors studied the asymptotic properties of least squares estimates of parameters in a stochastic difference equation, where the difference equation is assumed to be linear with constant real coefficients and the roots of the associated characteristic polynomial are all assumed to have absolute value different from one.

TL;DR: In this paper, an instrumental-variable approach similar to the two-stage least-squares method was proposed for estimating the parameters of simultaneous-equations models with missing data.

TL;DR: In this article, it was shown that normalization rules may introduce arbitrary elements into the estimation procedure, whether classical or Bayesian, when estimating the parameters of a single equation, and it was also shown that the normalization rule may introduce new elements in the estimation process.

TL;DR: In this paper, the authors determine whether call option prices can be relied upon to predict future rises in common stock prices, using response surface methodology, and demonstrate that such an advantage would be inconsistent with the efficient market hypothesis.

TL;DR: In this article, a general class of full-information estimators, called K -matrix-class (KMC), is proposed, and conditions under which KMC estimators are consistent (similar to those of the k -class estimators) are given.

TL;DR: In this paper, a Bayesian estimation of CES production functions is presented, which is easier to use than methods so far developed and it allows a direct comparison with the maximum likelihood estimator.

TL;DR: In this paper, the authors measured the lagged stock price and found that it is a combination of the adjustment to stock prices and to the adjustment of other variables, i.e., positive serially correlated disturbance terms.

TL;DR: In this article, the authors developed the Bayesian estimation of the parameters of Solow's distributed lag model with implicit autocorrelation of disturbances in its autoregressive form.

TL;DR: In this article, a Monte Carlo experiment was performed to see which treatment of truncation remainder leads to the most accurate tests of hypotheses, and the results were mixed, but generally it seems better to estimate the truncation rest than to drop it.

TL;DR: In this paper, a methodology based on principal components is developed for the testing and estimation of aggregate income series, which consists in extracting the first principal component from residuals of estimated demand functions which would incorporate the real income effect and other random disturbances.