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On the Existence of Moments of Ratios of Quadratic Forms

二次型比值矩的存在性

We obtain simple and generally applicable conditions for the existence of mixed moments E ([ X ′ AX ]″/[ X ′ BX ] U ) of the ratio of quadratic forms T = X ′ AX / X ′ BX where A and B are n × n symmetric matrices and X is a random n -vector. Our principal theorem is easily stated when X has an elliptically symmetric distribution, which class includes the multivariate normal and t distributions, whether degenerate or not. The result applies to the ratio of multivariate…

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Nonparametric Kernel Estimation for Semiparametric Models

用于半参数模型的非参数核估计

This paper presents a number of consistency results for nonparametric kernel estimators of density and regression functions and their derivatives. These results are particularly useful in semiparametric estimation and testing problems that rely on preliminary nonparametric estimators, as in Andrews (1994, Econometrica 62, 43–72). The results allow for near-epoch dependent, nonidentically distributed random variables, data-dependent bandwidth sequences, preliminary estimation…

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Causality in the Long Run

长期因果关系

The definition of causation, discussed in Granger (1980) and elsewhere, has been widely applied in economics and in other disciplines. For this definition, a series y t is said to cause x t +l if it contains information about the forecastability for x t +l contained nowhere else in some large information set, which includes x t − j , j ≥ 0. However, it would be convenient to think of causality being different in extent or direction at seasonal or low frequencies, say, than…

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Instrumental Variables Estimation in Misspecified Single Equations

误设单方程中的工具变量估计

This paper examines the exact sampling behavior of a family of instrumental variables estimators of the coefficients in a single structural equation when the model has been misspecified by the incorrect inclusion or exclusion of variables. It is found that such specification errors can have implications for the structure of the exact results obtained. A brief numerical examination of the analytical results is also provided.

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Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models

离散选择模型模拟极大似然估计的渐近偏差

In this article, we investigate a bias in an asymptotic expansion of the simulated maximum likelihood estimator introduced by Lerman and Manski (pp. 305–319 in C. Manski and D. McFadden (eds.), Structural Analysis of Discrete Data with Econometric Applications , Cambridge: MIT Press, 1981) for the estimation of discrete choice models. This bias occurs due to the nonlinearity of the derivatives of the log likelihood function and the statistically independent simulation errors…

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