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误差成分模型的工具变量估计AI 解读

On propose des estimateurs efficaces en considerant des hypotheses alternatives sur les sources d'endogeneite et les proprietes de variance-covariance des perturbations

单变量时间序列模型识别的贝叶斯程序AI 解读

This paper is concerned with model selection in time series analysis. An identification criterion is presented that is asymptotically equivalent to a Bayes decision rule. The discussion is conducted in the context of a general class of parametric time series models and consideration is given to the special case of order determination in autoregressive moving-average representations. Consistency of the criterion is proved.

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利用 Kalman 滤波估计不可观测的月度预期通胀AI 解读

Hamilton developed a technique for estimating financial market expectations of inflation based on the observed time-series properties of interest rates and inflation. The technique is based on a state-space representation derived from an underlying vector autoregressive process of the expected real interest rate and the expected inflation rate on lagged expectations and lagged values of the observed Treasury bill rate and the actual inflation rate. This article extends this…

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非正态误差与 OLS、2SLS 结构方程估计量的分布AI 解读

This paper examines the sensitivity of the distributions of OLS and 2SLS estimators to the assumption of normality of disturbances in a structural equation with two included endogenous variables. The approach taken is that ofimposing Edgeworth distributed errors on the reduced form equations and deriving the pdf of the estimators via the technique of Davis [11]. The sensitivity of the pdf s to changes in the non-normality parameters, i.e., skewness and kurtosis i s examined…

联立方程系统中单方程估计量的比较AI 解读

Comparisons of estimators are made on the basis of their mean squared errors and their concentrations of probability computed by means of asymptotic expansions of their distributions when the disturbance variance tends to zero and alternatively when the sample size increases indefinitely. The estimators include k -class estimators (limited information maximum likelihood, two-stage least squares, and ordinary least squares) and linear combinations of them as well as…

变量含误差模型中测量误差信息的组合AI 解读

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…

过度参数化结构模型的渐近理论AI 解读

A theory of overparameterized structural models is presented. In such a model some “redundant” parameters are involved; the parameter vector is not identified, and the information matrix is not nonsingular. The minimum discrepancy function (MDF) test statistic is shown to have an asymptotic chi-squared distribution almost everywhere for a wide class of discrepancy functions. Asymptotic distribution properties of the MDF estimators are investigated. The factor analysis model…

存在异常值时的时间序列模型设定AI 解读

Outliers are commonplace in data analysis. Time series analysis is no exception. Noting that the effect of outliers on model identification statistics could be serious, this article is concerned with the problem of time series model specification in the presence of outliers. An iterative procedure is proposed to identify the outliers, to remove their effects, and to specify a tentative model for the underlying process. The procedure is essentially based on the iterative…

变量测量误差模型中测量误差信息的结合AI 解读

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…

过度参数化结构模型的渐近理论AI 解读

A theory of overparameterized structural models is presented. In such a model some “redundant” parameters are involved; the parameter vector is not identified, and the information matrix is not nonsingular. The minimum discrepancy function (MDF) test statistic is shown to have an asymptotic chi-squared distribution almost everywhere for a wide class of discrepancy functions. Asymptotic distribution properties of the MDF estimators are investigated. The factor analysis model…

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面板数据中的变量测量误差AI 解读

Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in…

具有ARMA误差的动态联立系统的工具变量估计AI 解读

This paper develops the instrumental variables estimator for a possibly incomplete, dynamic economic system with vector autoregressive moving average disturbances. Its asymptotic distribution is derived and, under fairly weak conditions, it is shown that lagged endogenous variables may be validly included in the set of instruments. Statistics are proposed for testing the order of the error process and the validity of the instruments.

ARCH 与双线性时间序列模型：比较与结合AI 解读

Two extensions to the ARMA model, bilinearity and ARCH errors are compared, and their combination is considered. Starting with the ARMA model, tests for each extension are discussed, along with various least squares and maximum likelihood estimates of the parameters and tests of the estimated models based on these. The effects each may have on the identification, estimation, and testing of the other are given, and it is seen that to distinguish between the two properly, it…

部分状态聚合面板数据中潜在马尔可夫结构的检验AI 解读

SUMMARY For dichotomous longitudinal panel data assumed to have been generated by a Markov chain but with only one of its states identifiable, the likelihood ratio and related tests for underlying Markovian structure are studied. It is shown that the likelihood ratio may be written as a product of conditionally independent likelihood ratios for testing independence in certain contingency tables, given margins. The tests are illustrated on data from malaria and…

关于逻辑回归最大似然估计存在条件的补充说明AI 解读

This note expands the paper by Albert & Anderson (1984) on the existence and uniqueness of maximum likelihood estimates in logistic regression models. Their three possible mutually exclusive data patterns: (i) overlap, (ii) complete separation, and (iii) quasiseparation are considered. The maximum likelihood estimate exists only in (i). Modifications of the statement and proofs of Albert & Anderson's results are given for (ii) and (iii) The identifiability for a more general…

检验误差：有限总体中整数参数的极大似然估计AI 解读

In a probability model for possible errors in the inspection of a finite lot containing defective items, it is shown how maximum likelihood estimation is affected by whether the sampling is carried out with or without replacement. These changes are examined by developing a method for simultaneous maximization over an integer and a scalar parameter. A new method for the bounding of the integer solution is introduced. The results show that the parameter estimates in the…

变点风险率模型似然中的一个奇异性问题AI 解读

A singularity identified by Nguyen, Rogers & Walker (1984) in the log likelihood function for a change-point hazard rate model is eliminated if the likelihood function is appropriately defined.

使用加权工具变量的联立方程模型稳健估计AI 解读

IN THIS PAPER we present a weighted-instrumental-variables estimator that is resistant2 to heavy-tailed errors, aberrant data in either the endogenous or exogenous variables, and certain other model failures. The estimator is analogous to the weighted-least-squares approach to robustness proposed by Krasker and Welsch [21] for ordinary regression. We will discuss the theory that motivated this estimator, derive some of its properties, describe our computational algorithm,…

非线性预算集的计量经济学AI 解读

This article surveys the development of nonparametric models and methods for estimation of choice models with nonlinear budget sets.The discussion focuses on the budget set regression, that is, the conditional expectation of a choice variable given the budget set.Utility maximization in a nonparametric model with general heterogeneity reduces the curse of dimensionality in this regression.Empirical results using this regression are different from maximum likelihood and give…

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