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Akaike 型准则与推断可靠性：模型选择和统计模型设定AI 解读

Since the 1990s, the Akaike Information Criterion (AIC) and its various modifications/extensions, including BIC, have found wide applicability in econometrics as objective procedures that can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences, primarily because their choice within a prespecified family of models (a) assumes away the problem of model…

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异方差建模：Student t 与椭圆线性回归模型AI 解读

This paper proposes a new approach to modeling heteroskedastidty which enables the modeler to utilize information conveyed by data plots in making informed decisions on the form and structure of heteroskedasticity. It extends the well-known normal/linear/homoskedastic models to a family of non-normal/linear/heteroskedastic models. The non-normality is kept within the bounds of the elliptically symmetric family of multivariate distributions (and in particular the Student's t…

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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…

重读哈维尔莫：计量经济建模的回顾性考察AI 解读

The main aim of the paper is to reevaluate the methodological contributions of Tinbergen and Haavelmo in the context of the current discussions on econometric modeling and propose a reformulation of the Haavelmo methodology. The paper argues that the textbook methodology constitutes a less flexible version of Tinbergen's approach and apart from the probabilistic language, it has little in common with the methodology in Haavelmo's 1944 monograph, commonly acknowledged as…