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Worldwide Rankings of Research Activity in Econometrics: An Update: 1980–1988

全球计量经济学研究活动排名更新:1980—1988 年

Fourteen leading international journals that publish econometrics articles are used to provide data on institutional activity in econometrics over the period 1980–1988. From this data base, institutional rankings are constructed separately for theoretical econometrics and all econometrics publications, according to standardized page counts of articles published in these journals. Some indication is given as to how institutional rankings have changed over this period.

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A Monte Carlo Study of Some Tests of Model Adequacy in Time Series Analysis

时间序列模型适切性检验的蒙特卡洛研究

In this article, we conduct a Monte Carlo experiment of several computationally attractive tests of model adequacy in time series analysis. The experiment is designed to examine the small-sample properties of tests of fitted autoregressive and moving average models, to compare the performances of asymptotically equivalent procedures, to consider the effects on estimated significance levels and powers of testing against both appropriate and inappropriate alternatives, to…

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Worldwide Rankings of Research Activity in Econometrics: 1980–1985

1980—1985 年全球计量经济学研究活动排名

We provide rankings of academic institutions according to the publication record of their faculty members in the specialization of econometrics. The rankings are based on standardized page counts of articles published by faculty members in 14 journals over the period 1980 to 1985. Separate rankings of the 200 leading institutions are provided for their theoretical contributions, as well as their contributions in theory and applied work. The rankings are compared with a…

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The exact likelihood function of multivariate autoregressive-moving average models

多元自回归移动平均模型的精确似然函数

By making use of the properties of tensor products, this paper describes the derivation of an expression for the exact likelihood function of a stationary process generated by a vector autoregressive-moving average model using concentrated maximum likelihood techniques. Furthermore, in the process of deriving the likelihood function, a closed form expression for the covariance function of the process in terms of the coefficients of the model is derived.

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