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面板数据模型中的反馈AI 解读

Much of the analysis of panel data has been based on an assumption of strict exogeneity. Distributions are specified for outcome variables conditional on a latent individual effect and conditional on observed predictor variables at all dates, with the future values of the predictor variables assumed to have no effect on the conditional distribution. The paper relaxes this assumption in order to allow for lagged dependent variables and, more generally, for feedback from…

决策理论在工具变量模型中的应用AI 解读

This paper applies some general concepts in decision theory to a simple instrumental variables model. There are two endogenous variables linked by a single structural equation; k of the exogenous variables are excluded from this structural equation and provide the instrumental variables (IV). The reduced-form distribution of the endogenous variables conditional on the exogenous variables corresponds to independent draws from a bivariate normal distribution with linear…

多工具变量下的随机效应估计量AI 解读

In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the endogenous regressor. Our proposed estimator puts a random coefficients structure on the relation between the endogenous regressor and the instruments. The variance of the random…

贝叶斯推断的非参数应用AI 解读

Bayesian inference by presenting two applications. Our first application considers an educational choice problem. We focus on obtaining a predictive distribution for earnings corresponding to various levels of schooling. This predictive distribution incorporates the parameter uncertainty, so that it is relevant for decision making under uncertainty in the expected utility framework of microeconomics. The second application is to quantile regression. Our point here is to…

最大最小期望效用的计量经济学应用AI 解读

Abstract Gilboa and Schmeidler (1989) develop a set of axioms for decision making under uncertainty. The axioms imply a utility function and a set of distributions such that the preference ordering is obtained by calculating expected utility with respect to each distribution in the set, and then taking the minimum of expected utility over the set. In a portfolio choice problem, the distributions are joint distributions for the data that will be available when the choice is…

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半参数回归的效率界AI 解读

Efficiency bounds for conditional moment restrictions with a nonparametric component are derived. There is a given function of the data (a random sample from a distribution F) and a parameter. The restriction is that a conditional expectation of this function is zero at some point in the parameter space. The parameter has two parts: a finite-dimensional component and a general function evaluated at a subset of the conditioning variables. An example is a regression function…

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面板数据的多元回归模型AI 解读

Under stationarity, the heterogeneous stoahastic processes are the non-ergodic ones. We show that if a distributed lag is of finite order, then its coefficients are unconditional means of the underlying random coefficients. This result is applied to linear transformations of the process. The estimation framework is a multivariate wide-sense regression function. The identification analysis requires certain restrictions on the coefficients. The actual regression function is…

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矩阵加权平均与后验界AI 解读

Summary Bounds for matrix weighted averages of pairs of vectors are presented. The weight matrices are constrained to certain classes suggested by the Bayesian analysis of the linear regression model and the multivariate normal model. The bounds identify the region within which the posterior location vector must lie if the prior comes from a certain class of priors.