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预定工具变量下的面板有效估计：矩条件估计量的实证比较AI 解读

The author examines the empirical performance of instrumental variables estimators with predetermined instruments in an application to life-cycle labor supply under uncertainty. The estimators studied are two stage least squares, generalized method-of-moments (GMM), forward filter, independently weighted GMM, and split-sample instrumental variables. The author compares the bias/efficiency trade-off for the estimators using bootstrap algorithms suggested by D. A. Freedman…

摘要暂缺

扩散过程的非参数估计及其在短期利率模型中的应用AI 解读

In this paper, we propose a nonparametric identification and estimation procedure for an ltd diffusion process based on discrete sampling observations. The nonparametric kernel estimator for the diffusion function developed in this paper deals with general ltd diffusion processes and avoids any functional form specification for either the drift function or the diffusion function. It is shown that under certain regularity conditions the nonparametric diffusion function…

基于自回归近似的 ARMA 模型简便估计与识别技术AI 解读

We examine simple estimators for general ARMA models and a corresponding identification method. Both estimation and identification are based on a matrix formed from the coefficients of an autoregressive approximation to the process of interest. We show that a zero determinant of this matrix is necessary and sufficient for the existence of a common factor in autoregressive and moving average lag polynomials, and therefore for redundant parameters in the model. Simulation…

Summary When measurement error is present in covariates, it is well known that naïvely fitting a generalized linear model results in inconsistent inferences. Several methods have been proposed to adjust for measurement error without making undue distributional assumptions about the unobserved true covariates. Stefanski and Carroll focused on an unbiased estimating function rather than a likelihood approach. Their estimating function, known as the conditional score, exists…

含无关数据与核验偏差样本的非参数极大似然估计AI 解读

Suppose that some measurements come from a distribution F that is of interest and others come from another, irrelevant distribution G. Some measurements from F are verified and known to be from F. The other, unverified measurements may be from F or from G. Not all measurements from F are equally likely to be verified, and no measurement from G is ever verified. This model applies to measurements of low concentrations obtained using gas chromatography/mass spectroscopy, for…

含无关数据与核验偏差样本的非参数最大似然估计AI 解读

Suppose that some measurements come from a distribution F that is of interest and others come from another, irrelevant distribution G. Some measurements from F are verified and known to be from F. The other, unverified measurements may be from F or from G. Not all measurements from F are equally likely to be verified, and no measurement from G is ever verified. This model applies to measurements of low concentrations obtained using gas chromatography/mass spectroscopy, for…

回归变量与工具变量可能非平稳时的完全修正 IV、GIVE 与 GMM 估计AI 解读

This paper develops a general theory of instrumental variables (IV) estimation that allows for both I(1) and I(0) regressors and instruments. The main goal of this paper is to develop a theory in which one does not need to know the integration properties of the regressors in order to obtain efficient estimators. The estimation techniques involve an extension of the fully modified (FM) regression procedure that was introduced in earlier work by Phillips and Hansen (1990). FM…

协整下两阶段最小二乘估计量的统计性质AI 解读

We derive the limiting properties of the two-stage least squares estimator of an equation in a dynamic simultaneous model when variables are nonstationary and cointegrated. The implication on hypothesis testing is also discussed. It is shown that in a structural equation approach what one needs to worry about are the classical issues of identification and estimation, not nonstationarity and cointegration. Conventional formulae for computing the asymptotic covariance of the…

过度识别广义矩模型的一步估计量AI 解读

In this paper I discuss alternatives to the GMM estimators proposed by Hansen (1982) and others. These estimators are shown to have a number of advantages. First of all, there is no need to estimate in an initial step a weight matrix as required in the conventional estimation procedure. Second, it is straightforward to derive the distribution of the estimator under general misspecification. Third, some of the alternative estimators have appealing information-theoretic…

长期识别限制何时能够给出可靠结果？AI 解读

Many recent articles have identified behavioral disturbances in vector autoregressions by imposing restrictions on the long-run effects of shocks. This article demonstrates that this approach will be unreliable unless the underlying economy satisfies three types of strong restrictions. Although many aspects of these issues have been raised before, this article draws out and illustrates the implications for inferences under the long-run scheme. Furthermore, it provides…

杂录：样条变换后的线性回归AI 解读

In a transformation model h(Y) = X'β + ε for some smooth and usually monotone function h, we are often interested in the direction of β without knowing the exact form of h. We consider a projection of h onto a linear space of B-spline functions which has the highest correlation with the design variable X. As with the Box-Cox transformation, the transformed response may then be analysed by standard linear regression software. The direction estimate from canonical correlation…

摘要暂缺

This note estimates the long-run demand for skilled and unskilled labor using panel data for Colombian manufacturing plants. Unobserved heterogeneity and measurement error problems that commonly arise in microdata production estimates are examined. Output measurement errors cause OLS estimators to underestimate the output and wage response of employment demand. Time-difference estimators exaggerate the measurement error biases. Instrumental-variable estimates of the output…

条件异方差模型中准极大似然估计量的渐近偏差AI 解读

For conditional heteroskedasticity models, the authors study the identification condition that is required for consistency of a non-Gaussian quasi-maximum-likelihood estimator. They show that, if the conditional mean is zero or if a symmetry condition is satisfied, then the identification condition is satisfied. Without symmetry, an additional parameter, for the location of the innovation density, must be added for identification. For the conditional variance parameters of a…

弱工具变量下的工具变量回归AI 解读

This paper develops asymptotic distribution theory for instrumental variables regression when the partial correlations between the instruments and the endogenous variables are weak, here modeled as local to zero. Asymptotic representation are provided for various statistics, including two-stage least squares and limited information maximum likelihood estimators, Wald statistics, and statistics testing overidentification and endogeneity. The asymptotic distributions provide…

杂论：利用高斯图规则识别单因子模型AI 解读

We state a sufficient condition for the global identification of a single-factor model when some conditional associations among residuals are allowed The condition relies on the structure of the conditional independence graph of the observed variable given the latent factor, and can be derived using graphical rules.

医疗技术的边际成本效果：面板工具变量方法AI 解读

We use panel instrumental variables techniques to estimate incremental mortality and cost effects of intensive procedures for treating heart attacks among the elderly. We identify incremental effects by comparing trends in procedure use, hospital costs, and mortality between hospitals that adopted intensive technologies to corresponding trends at nonadopting hospitals. We formalize the identification assumptions required for ‘difference-in-differences’ estimation and present…

二元数据一般随机效应模型的极大似然一致性AI 解读

We consider a general random effects model for repeated binary measures, assuming a latent linear model with any class of mixing distributions. The latent model is assumed to have the Laird-Ware structure, but the random effects may be from any specified class of multivariate distributions and the error vector may have any specified continuous distribution. Elementwise threshold crossing then gives the observed vector of binary outcomes. Special cases of this model include…

存在不依从的随机实验中因果效应的贝叶斯推断AI 解读

For most of this century, randomization has been a cornerstone of scientific experimentation, especially when dealing with humans as experimental units. In practice, however, noncompliance is relatively common with human subjects, complicating traditional theories of inference that require adherence to the random treatment assignment. In this paper we present Bayesian inferential methods for causal estimands in the presence of noncompliance, when the binary treatment…

协整 I(1) VAR 系统中移动平均影响矩阵的渐近推断AI 解读

This paper addresses the problem of inference on the moving average impact matrix and on its row and column spaces in cointegrated 1(1) VAR processes. The choice of bases (i.e., the identification) of these spaces, which is of interest in the definition of the common trend structure of the system, is discussed. Maximum likelihood estimators and their asymptotic distributions are derived, making use of a relation between properly normalized bases of orthogonal spaces, a…

印度村庄中的风险与保险：评论AI 解读

THE PROTECTION OF POOR HOUSEHOLDS in high-risk agrarian economies from shocks to their incomes has often been seen as a compelling motive for various forms of policy intervention including transfers of cash or food, credit subsidies, and public employment schemes (for a survey see Lipton and Ravallion (1995)). The desirability of such safety net policies clearly depends on how well pre-existing risk-sharing arrangements work. While it is commonly thought that, without…

多变量非参数关系中因子数量的推断AI 解读

This paper considers the problem of determining the number of factors in a multivariate nonparametric relationship. The definition of factors given is broad enough to encompass a number of potential applications in econometrics, including inferring the rank of demand, consistent tests for lack of identification in linear instrumental variable models, and testing arbitrage pricing theory. The paper gives both series and kernel methods for testing hypotheses concerning, and…

区域股票市场的共同可预测成分AI 解读

This paper employs recently developed multivariate methods to study the predictability of international stock market returns. The authors find evidence of significant common predictable components within the Pacific, the European, and the North American stock markets using region-specific instrumental variables. The degree of predictability of these common movements, however, varies across regional markets and across subperiods. Results indicate that only North American…