Showing papers in "Journal of Econometrics in 1980"

TL;DR: In this paper, it was shown that the aggregate series may have univariate long-memory models and obey integrated, or infinite length transfer function relationships, and that if series obeying such models occur in practice, from aggregation, then present techniques being used for analysis are not appropriate.

TL;DR: In this article, it has been argued that the disturbances specified in these models, and techniques used to estimate them should account for that fact, and the very recent literature on frontier functions has motivated the recent literature of applied econometrics.

TL;DR: In this paper, the authors investigate random utility models in which the observed binary outcome does not reflect the binary choice of a single decision-maker, but rather the joint unobserved binary choices of two decision-makers.

TL;DR: In this article, the authors consider the case where the non-positive component of the disturbance represents the shortfall of actual output from the frontier, while the frontier contains the normal component of disturbance, and is therefore stochastic.

TL;DR: In this article, a linear regression model is proposed in which the coefficient vector is a weakly stationary multivariate stochastic process and the model provides a convinient representation of a general class of nonstationary processes.

TL;DR: In this paper, a Monte Carlo study of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors is presented. But none of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are.

TL;DR: In this article, the authors derived sufficient conditions under which the maximum likelihood estimator is consistent and asymptotically normal and also provided sufficient conditions for the estimation of regression models with stationary stochastically varying coefficients.

TL;DR: In this article, the properties of three estimators commonly used in the analysis of autoregressive moving average time series models for both non-seasonal and seasonal data are analyzed by simulation.

TL;DR: In this paper, the authors examined the possibilities of moment estimators of regression coefficients in the errors-in-variables problem suggested by Geary (1942) and others [Scott (1950) and Drion (1951)].

TL;DR: In this paper, the authors adapted the two-stage neo-classical model of consumer behavior to the analysis of time-of-use pricing of electricity, with emphasis placed upon the relationship between partial elasticities, which can be accurately estimated from the first stage, and total elasticities that can be estimated only by using less reliable information to estimate the second stage.

TL;DR: In this article, generalized least squares are applied to a transformed model for time series of cross-sections with fixed effects and with intertemporal correlation to estimate the regression coefficients and their standard errors.

TL;DR: Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by making use of several types of prior information in Klein's model I.

TL;DR: In this paper, the authors examined the methodological problems in the economics literature related to the demand for medical care and showed that in both cases estimates contained in the literature are inconsistent, and the direction of the inconsistency is obtained a priori.

TL;DR: This article developed a characterization of seasonal revisions in terms of stationary and non-stationary linear time series models, assuming that such models generate the series itself and the seasonal and seasonal components.

TL;DR: In this paper, the authors developed and estimated a model of a capital using firm that one can implement using observable data, and the consistency of the model with the data is tested by checking whether the estimated parameters satisfy the regularity conditions imposed by the theory.

TL;DR: In this article, exact finite-sample invariance results for the usual estimators and test statistics in the generalized regression model with non-scalar covariance matrix are established, even when there is no explicit solution for the estimator as a function of the data.

TL;DR: In this article, the authors considered forecasting a contemporal linear aggregate yt of a vector time series Z't =(Z1t,...,Zkt). And they first disciss the case where Zt follows a stationary multiple moving average process and propose a measure of the efficiency of aggregation.

TL;DR: It is found that the Newton-Raphson algorithm employing an analytically-computed Hessian is computationally much more efficient in this context than its oft-employed competitors, such as DFP.

TL;DR: Offenbacher and Clements and Nguyen as discussed by the authors argued that the full competitive rate to demand deposits would seem to overstate substantially the non-monetary services of those deposits.

TL;DR: Alternative methods of classifying observations into the two regimes of disequilibrium are discussed and a Monte Carlo assessment of the most widely applicable classification rule is provided.

TL;DR: In this article, an expression for the minimum mean squared error predictor of the single equation ARMAX model when all the parameters are known is given, and a formula is then derived for the asymptotic prediction mean squared errors when the parameters were replaced by their maximum likelihood estimates.

TL;DR: In this article, the authors proposed an estimator that is consistent and asymptotically more efficient than the standard multinomial logit estimator for the choice of automobile ownership.