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计量经济学史的视角：评介埃普斯坦《计量经济学史》AI 解读

Only in the last few years has the history of econometrics become established as an accepted field of research, with its own doctoral students and sessions at professional meetings. Yet, the first written histories of econometrics appeared as far back as the 1950s, when Carl Christ [4] reviewed the first 20 years' econometric work of the Cowles Commission and George Stigler [37] surveyed the early econometric analyses of consumer demand. Contributions in the intervening…

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回归系数对单调变换的敏感性AI 解读

This note presents a procedure which enables the user to check whether a monotonic transformation can change the sign of a regression coefficient. One possible use of this procedure is to examine the robustness of key regression coefficients.

删失线性回归半参数估计中的带宽选择AI 解读

Quantile and semiparametric M estimation are methods for estimating a censored linear regression model without assuming that the distribution of the random component of the model belongs to a known parametric family. Both methods require estimating derivatives of the unknown cumulative distribution function of the random component. The derivatives can be estimated consistently using kernel estimators in the case of quantile estimation and finite difference quotients in the…

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比较估计量分布函数图形的解释AI 解读

In this paper I examine graphical comparisons of one-dimensional (or marginal) distribution functions of alternative estimators. It is shown that areas under the c.d.f. (cumulative distribution function) curve can be given a decision-theoretic interpretation as risk under a bounded absolute-error loss function. I also show that by a simple rescaling of the graph's axes, graphical areas are created which can be interpreted as risk under bounded squared-error loss. The bounded…

多元时间序列谱密度矩阵相关统计量的分布渐近展开及应用AI 解读

Let { X ( t )} be a multivariate Gaussian stationary process with the spectral density matrix f 0 (ω), where θ is an unknown parameter vector. Using a quasi-maximum likelihood estimator θ̂ of θ, we estimate the spectral density matrix f 0 (ω) by f θ̂ (ω). Then we derive asymptotic expansions of the distributions of functions of f θ̂ (ω). Also asymptotic expansions for the distributions of functions of the eigenvalues of f θ̂ (ω) are given. These results can be applied to…

Stein 规则估计量均方误差矩阵的无偏估计、置信椭球与假设检验AI 解读

We first present an unbiased estimator of the MSE matrix of the Stein-rule estimator of the coefficient vector in a normal linear regression model. The Steinrule estimator can be used with both its estimated MSE matrix and with the least-squares MSE matrix to form confidence ellipsoids. We derive the approximate expected squared volumes and coverage probabilities of these confidence sets and discuss their ranking. These results can be applied to the conditional prediction of…

具有单位根和无限方差误差的时间序列回归AI 解读

In [4] Chan and Tran give the limit theory for the least-squares coefficient in a random walk with i.i.d. (identically and independently distributed) errors that are in the domain of attraction of a stable law. This paper discusses their results and provides generalizations to the case of I (1) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. General unit root tests are also studied. It is shown that the…

稳健回归型模型设定检验的统一方法AI 解读

This paper develops a general approach to robust, regression-based specification tests for (possibly) dynamic econometric models. A useful feature of the proposed tests is that, in addition to estimation under the null hypothesis, computation requires only a matrix linear least-squares regression and then an ordinary least-squares regression similar to those employed in popular nonrobust tests. For the leading cases of conditional mean and/or conditional variance tests, the…

全球计量经济学研究活动排名更新：1980—1988 年AI 解读

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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