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从 VAR 模型到结构模型：工资—价格螺旋的应用AI 解读

Abstract In this paper a VAR model is considered as a general framework in which a structural model can be tested. We carefully describe the hypotheses defining a structural model; this leads us to discuss various notions such as: predeterminedness, non‐causality, exogeneity, contemporaneous identification, overall identification, weak and strong structural forms. Then we propose a test procedure, based on the asymptotic least‐squares method, which allows successive testing…

指数分布混合假设的检验与混合分布的矩估计AI 解读

This article presents nonparametric methods for testing the hypothesis that duration data can be represented by a mixture of exponential distributions. Both Bayesian and classical tests are developed. A variety of apparently distinct models can be written in mixture of exponentials form. This raises a fundamental identification problem. A consistent estimator for the number of points of support of a discrete mixture is developed. A consistent method-of-moments estimator for…

核分位数估计量AI 解读

For an estimator of quantiles, the efficiency of the sample quantile can be improved by considering linear combinations of order statistics, that is, L estimators. A variety of such methods have appeared in the literature; an important aspect of this article is that asymptotically several of these are shown to be kernel estimators with a Guassian kernel, and the bandwidths are identified. It is seen that some implicit choices of the smoothing parameter are asymptotically…

多朋友选择中的同质性与社会距离：条件对称对数双线性关联模型AI 解读

This article presents an analysis of friendship choice data by focusing on homophily (or inbreeding bias) and social distance revealed in the patterns of both association between subjects' and friends' statuses and association among friends' statuses. These two aspects of inbreeding bias and social distance are simultaneously taken into account in modeling the data of friendship choice from subjects with different numbers of friends. The statuses of friends are expressed in…

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微观数据的披露控制AI 解读

National statistical offices meet an increasing demand for the dissemination of microdata. This trend can be at variance with the care taken not to disclose data about individuals. Therefore, the risk of disclosure of each microdata set to be released should be assessed. If this risk is too high, measures have to be taken to protect the data set. This article describes the disclosure problem, and explains why it is a real problem. Using the concept of uniqueness, some theory…

计量经济建模的统计基础AI 解读

Foreword David Hendry Preface Acknowledgements Part I. Introduction: 1. Econometric modelling, a preliminary view 2. Descriptive study of data Part II. Probability Theory: 3. Probability 4. Random variables and probability distributions 5. Random vectors and their distributions 6. Functions of random variables 7. The general notion of expectation 8. Stochastic processes 9. Limit theorems 10. Introduction to asymptotic theory Part III. Statistical Inferences: 11. The nature…

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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…

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This paper studies the asymptotic properties of instrumental variable (IV) estimates of multivariate cointegrating regressions and allows for deterministic and stochastic regressors as well as quite general deterministic processes in the data-generating mechanism. It is found that IV regressions are consistent even when the instruments are stochastically independent of the regressors. This phenomenon, which contrasts with traditional theory for stationary time series, is a…

非线性时间序列的识别：一阶刻画与阶数确定AI 解读

We study the possibility of identifying nonlinear time series using nonparametric estimates of the conditional mean and conditional variance. It is shown that most nonlinear models satisfy the assumptions needed to apply nonparametric asymptotic theory. Sampling variations of the conditional quantities are studied by simulation and explained by asymptotic arguments for a number of first-order nonlinear autoregressive processes. The conditional mean and variance can be used…

一般层级模型中异常值的识别与处理AI 解读

By their nature, hierarchical models involve a considerable number of structural and distributional assumptions; for example, normality and linearity are common assumptions. Considerations of robustness therefore suggest that some form of model elaboration is necessary. However, it is not clear how to achieve this in the already complex setting of hierarchical models whilst maintaining reasonable tractability in the analysis. We provide a comprehensive account of the way in…

使用二次指数模型的相关二元回归AI 解读

A model of quadratic exponential form is parameterized in terms of marginal means and pairwise correlations for the regression analysis of correlated binary data. Pseudo-maximum likelihood methods using a special case termed the multiplicative model are proposed, but are noted to be computationally unattractive if the ‘blocks’ of correlated responses are at all large. On the other hand score estimating functions for mean and correlation parameters are shown to be of a…

ARMA模型的阶数识别AI 解读

We present a new powerful method for determining the order of ARMA (p, q) models having small sets of observations. The procedure is based on an autoregressive order determination criterion and on linear estimation methods. Simulated data are used to demonstrate the capabilities of the approach.

不规则纵向数据中发生率与诊断误差率的联合估计AI 解读

Longitudinal studies often involve the repeated diagnosis across time of each patient's status with respect to a progressive categorical process. When the occurrence of a change in status is not readily apparent, two factors can make modeling and assessing the incidence rates of progression difficult. First, because diagnoses may be difficult, they may not be performed with the frequency necessary to pinpoint exact times of incidence. Second, uncertainty in the diagnostic…

不规则纵向数据中发生率与诊断错误率的联合估计AI 解读

Longitudinal studies often involve the repeated diagnosis across time of each patient's status with respect to a progressive categorical process. When the occurrence of a change in status is not readily apparent, two factors can make modeling and assessing the incidence rates of progression difficult. First, because diagnoses may be difficult, they may not be performed with the frequency necessary to pinpoint exact times of incidence. Second, uncertainty in the diagnostic…

多重均衡模型的可观测含义AI 解读

Economic models with multiple equilibria are now so common in economics that we need a general framework for statistical inference in such models. This note offers a simple theoretical framework that can be used to organize the debate about the question of whether such a model is identified, and about the question of how much predictive content it retains

指标模型系数的半参数估计AI 解读

This paper gives a solution to the problem of estimating coefficients of index models, through the estimation of the density-weighted average derivative of a general regression function. A normalized version of the density-weighted average derivative can be estimated by certain linear instrumental variables coefficients. The estimators, based on sample analogies of the product moment representation of the average derivative, are constructed using nonparametric kernel…

结构方程中的 t 检验AI 解读

Properties of t ratios associated with the LIML, TSLS, and OLS estimators in a structural form estimation are studied. The existence of moments of these t ratios including the LIML form is proved first. Second, Monte Carlo simulations are performed to find out real sizes of the t test and the likelihood ratio test. Third, asymptotic expansions of the distributions of t ratios are derived under the null hypothesis to find out deviations of real sizes from nominal sizes…

未识别测量误差模型中由非正规先验得到正规后验AI 解读

The problem considered is inference in a simple errors-in-variables model where consistent estimation is impossible without introducing additional exact prior information. The probabilistic prior information required for Bayesian analysis is found to be surprisingly light: despite the model's lack of identification, a proper posterior is guaranteed for any bounded prior density, including those representing improper priors. This result is illustrated with the improper…