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使用预定但非严格外生工具变量的时间序列模型近有效估计AI 解读

Particularly under the assumption of rational expectations, a model may have serially correlated errors and those errors may be uncorrelated with contemporaneous and lagged values of a predetermined instrument, yet the instruments may not be strictly exogenous. This paper proposes a method for transforming such a model to one without serial correlation, while keeping the instrument predetermined. Standard theory of instrumental variables estimation then applies. Furthermore,…

不等删失下对数秩置换检验的表现AI 解读

This note studies the extent to which the type I error of the permutation test based on the log rank score departs from its nominal value in the presence of unequal right censoring. For the asymptotic case, situations are identified that lead to conservative and to nonconservative behaviour, and the amount of conservatism is computed for some specific constant hazard situations. A small Monte Carlo study is used to support the relevance of the asymptotic results in a finite…

用于非嵌套假设检验的工具变量统计量的渐近性质AI 解读

This paper develops Instrumental Variables statistics for testing non-nested hypotheses when the hypotheses considered are single equations from a system of linear dynamic simultaneous equations. Asymptotic distributions of those statistics and of comparable Maximum Likelihood statistics are derived under the null hypothesis, a local non-nested alternative hypothesis, and a local "comprehensive" alternative hypothesis. The asymptotic powers of the non-nested hypothesis tests…

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仅在变量上非线性的方程系统的识别问题AI 解读

This paper examines the identifiability of the coefficients of a single equation in a simultaneous equation model which is nonlinear only in the variables. The concept of identifiability in this model is motivated and developed using the closely related concept of observational equivalence. This framework is then utilized to develop necessary and sufficient conditions for identifiability when the disturbances are required to be independent of the exogenous variables. The…

多元时间序列建模与扩展样本互相关AI 解读

This article provides an expository account of the multivariate autoregressive moving average models and proposes an extended sample cross-correlation approach for practical model identification. An iterative model building procedure for applying these models to real data is discussed and demonstrated by analyzing the 5-series U.S. Hog Data.

不等删失下对数秩置换检验的表现AI 解读

This note studies the extent to which the type I error of the permutation test based on the log rank score departs from its nominal value in the presence of unequal right censoring. For the asymptotic case, situations are identified that lead to conservative and to nonconservative behaviour, and the amount of conservatism is computed for some specific constant hazard situations. A small Monte Carlo study is used to support the relevance of the asymptotic results in a finite…

多重决策与假设检验中的自适应程序AI 解读

Necessary and sufficient conditions for the existence of adaptive procedures for identification of one of several probability distributions or for testing a simple hypothesis against a simple alternative are obtained. By definition, adaptive procedures are required to exhibit the same asymptotic behavior for several parametric families as do the optimal (minimax) estimators for each of these families. The proofs are based on a multivariate version of Chernoff's theorem,…

The permanent income hypothesis with rational expectation is restated, estimated, and tested by an instrumental variables technique on the postwar U.S. aggregate time-series data. The hypothesis is accepted on a consumption series which includes service flows from consumer durables. If the consumption series is the one in the National Income and Product Accounts, the hypothesis is decisively rejected. An explanation is suggested to reconcile the conflicting test results.

相关与谱分析的工程应用AI 解读

Discusses engineering applications and recent developments based upon correlation and spectral analysis. Illustrations deal with applications to acoustics, mechanical vibrations, system identification, and fluid dynamics problems in aerospace, automotive, industrial noise control, civil engineering and oceanographic fields, as well as similar problems in other fields. Tackles problems and solutions, assuming reader has required hardware and software to compute estimates of…

非线性理性预期模型的广义工具变量估计AI 解读

This paper describes a method for estimating and testing nonlinear rational expectations models directly from stochastic Euler equations. The estimation procedure makes sample counterparts to the population orthogonality conditions implied by the economic model close to zero. An attractive feature of this method is that the parameters of the dynamic objective functions of economic agents can be estimated without explicitly solving for the stochastic equilibrium.

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两阶段最小绝对离差估计量AI 解读

In this paper the method of least absolute deviations is applied to the estimation of the parameters of a structural equation in the simultaneous equations model. A class of estimators called two stage least absolute deviations estimators is defined, their asymptotic properties are derived, and the problem of finding the optimal member of the class is considered. IN THIS PAPER WE APPLY the method of least absolute deviations to the estimation of the parameters of a…

结构特征价格模型的估计AI 解读

MANY COMMODITIES can be viewed as bundles of individual attributes for which no explicit markets exist. It is often of interest to estimate structural demand and supply functions for these attributes, but the absence of directly observable attribute prices poses a problem for such estimation. In an influential paper published several years ago, Rosen [3] proposed an estimation procedure to surmount this problem. This procedure has since been used in a number of applications…

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随机回归模型的最小二乘估计及其在动态系统辨识与控制中的应用AI 解读

Strong consistency and asymptotic normality of least squares estimates in stochastic regression models are established under certain weak assumptions on the stochastic regressors and errors. We discuss applications of these results to interval estimation of the regression parameters and to recursive on-line identification and control schemes for linear dynamic systems.

独立观测下的工具变量回归AI 解读

INTRODUCTION THE METHOD OF INSTRUMENTAL VARIABLES (IV), proposed independently by Reiersol [15] and Geary [4], is one of the most useful classes of estimation techniques available to econometricians. The method is particularly useful in the context of errors-in-variables and simultaneous equation problems, and it ineludes ordinary least squares (OLS), two-stage least squares (2SLS) (Klein [9]), three-stage least squares (3SLS) (Madansky [12]) and certain full-information…

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…

非线性联立模型工具变量估计量的比较研究AI 解读

In the context of single equation approaches to the estimation of nonlinear simultaneous models, three classes of estimators can be established, using different fitted values established by a stage-one regression. The first uses the Fitted values of the nonlinear function in the second-stage regression. The second, called here the naive instrument, substitutes a fitted value inside the nonlinear function. The third uses an estimate of the conditional expectation of the…

非线性联立模型工具变量估计量的比较研究AI 解读

In the context of single equation approaches to the estimation of nonlinear simultaneous models, three classes of estimators can be established, using different fitted values established by a stage-one regression. The first uses the Fitted values of the nonlinear function in the second-stage regression. The second, called here the naive instrument, substitutes a fitted value inside the nonlinear function. The third uses an estimate of the conditional expectation of the…

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面板数据与不可观测个体效应AI 解读

Abstract An important purpose in pooling time-series and cross-section data is to control for individual-specific unobservable effects which may be correlated with other explanatory variables, e.g. latent ability in measuring returns to schooling in earnings equations or managerial ability in measuring returns to scale in firm cost functions. Using instrumental variables and the time-invariant characteristics of the latent variable, we derive: 1. (1) a test for the presence…