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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…

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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…

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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…

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…

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…

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…

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…

方程两侧均含支出测量误差时的需求估计AI 解读

Let x be total consumption expenditures. Measurement errors in consumer budget allocation models cause unusual problems because errors in the dependent variables, consumption on individual goods, contribute to errors in the regressor x. Empirically adequate budget share models, like the AIDS, translog, and quadratic AIDS, are linear or quadratic in log x. It is shown that, for these specifications, two stage least squares fails to correct for the measurement error. A simple…

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广义线性测量误差模型中的工具变量估计AI 解读

Instrumental variable estimation in generalized linear measurement error models are studied. For models with canonical link functions, unbiased estimating equations are derived. The maximum likelihood estimator for the normal theory, structural linear instrumental variable model is shown to be a solution to the estimating equations derived herein. Logistic regression is studied in detail. An example is given and a simulation study described for the logistic model based on…

动态线性模型中不同工具变量估计量的比较AI 解读

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, the authors compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). They find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that, in…

宏观计量模型中中位数无偏估计的计算AI 解读

A stochastic simulation model is proposed in this paper for obtaining median unbiased (MU) estimates in macroeconometric models. MU estimates are computed for the lagged dependent variable (LDV) coefficients in 18 equations of a macroeconometric model. The 2SLS bias for a coefficient, defined as the difference between the 2SLS estimate and the MU estimate, is on average smaller in absolute value than would be expected from Andrews' exact results for an equation with only a…

使用工具变量识别因果效应AI 解读

We outline a framework for causal inference in settings where assignment to a binary treatment is ignorable, but compliance with the assignment is not perfect so that the receipt of treatment is nonignorable. To address the problems associated with comparing subjects by the ignorable assignment—an “intention-to-treat analysis”—we make use of instrumental variables, which have long been used by economists in the context of regression models with constant treatment effects. We…

利用工具变量识别因果效应：评论AI 解读

We outline a framework for causal inference in settings where assignment to a binary treatment is ignorable, but compliance with the assignment is not perfect so that the receipt of treatment is nonignorable. To address the problems associated with comparing subjects by the ignorable assignment-an intention-to-treat analysis-we make use of instrumental variables, which have long been used by economists in the context of regression models with constant treatment effects. We…

This paper discusses how randomized social experiments operate as an instrumental variable. For two types of randomization schemes, the fundamental experimental estimation equations are derived from the principle that experiments equate bias in control and experimental samples. Using conventional econometric representations, we derive the orthogonality conditions for the fundamental estimation equations. Randomization is a multiple instrumental variable in the sense that one…

美国对外直接投资的计量分析AI 解读

This paper constructs a theoretical model of foreign direct investment and examines the extent to which the model can explain the level of outward direct investment by U.S. companies over the last two decades. The authors find that market size and factor costs, both labor and capital, are important factors in the investment decision. Instrumental variable estimation is used to demonstrate that the expectation of short-run fluctuations in the dollar also influences the timing…

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持久收入、当期收入与消费：来自两个面板数据集的证据AI 解读

In this paper, the author estimates Euler equations, i.e., the first order conditions of the consumers' maximization problem, using data from two data sets. Consumption data are taken from the Consumer Expenditure Survey. Income data are taken from the Panel Study of Income Dynamics. Since the data for the estimation come from two samples, the author uses a generalization of the instrumental variables estimator: two-sample instrumental variables estimator. She finds evidence…

非平稳回归中的有效工具变量估计AI 解读

A limit theory for instrumental variables (IV) estimation that allows for possibly nonstationary processes was developed in Kitamura and Phillips (1992, Fully Modified IV, GIVE, and GMM Estimation with Possibly Non-stationary Regressors and Instruments, mimeo, Yale University). This theory covers a case that is important for practitioners, where the nonstationarity of the regressors may not be of full rank, and shows that the fully modified (FM) regression procedure of…