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工具变量:IV、2SLS 与内生性识别。
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Non-parametric bounds on quantiles under monotonicity assumptions: with an application to the Italian education returns

单调性假设下分位数的非参数界:意大利教育回报应用

Within the inferential context of predicting a distribution of potential outcomes P[y(t)] under a uniform treatment assignment t ∈ T, this paper deals with partial identification of the α-quantile of the distribution of interest Qα[y(t)] under relatively weak and credible monotonicity-type assumptions on the individual response functions and the population selection process. On the theoretical side, the paper adds to the existing results on non-parametric bounds on quantiles…

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The causes and consequences of venture capital stage financing

风险投资分阶段融资的成因与后果

This paper examines the causes and consequences of venture capital (VC) stage financing. Using information about the physical location of an entrepreneurial firm and the geographic distance between the VC investor and the firm, I show that VC investors located farther away from an entrepreneurial firm tend to finance the firm using a larger number of financing rounds, shorter durations between successive rounds, and investing a smaller amount in each round. However, VC…

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Cocaine Dependence Treatment Data: Methods for Measurement Error Problems With Predictors Derived From Stationary Stochastic Processes

平稳随机过程衍生预测变量的测量误差校正:可卡因治疗数据应用

In a cocaine dependence treatment study, we use linear and nonlinear regression models to model posttreatment cocaine craving scores and first cocaine relapse time. A subset of the covariates are summary statistics derived from baseline daily cocaine use trajectories, such as baseline cocaine use frequency and average daily use amount. These summary statistics are subject to estimation error and can therefore cause biased estimators for the regression coefficients. Unlike…

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ESTIMATION OF A SEMIPARAMETRIC IGARCH(1,1) MODEL

半参数 IGARCH(1,1) 模型的估计

We propose a semiparametric IGARCH model that allows for persistence in variance but also allows for more flexible functional form. We assume that the difference of the squared process is weakly stationary. We propose an estimation strategy based on the nonparametric instrumental variable method. We establish the rate of convergence of our estimator.

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IDENTIFICATION AND ESTIMATION BY PENALIZATION IN NONPARAMETRIC INSTRUMENTAL REGRESSION

非参数工具变量回归中的惩罚识别与估计

The nonparametric estimation of a regression function from conditional moment restrictions involving instrumental variables is considered. The rate of convergence of penalized estimators is studied in the case where the regression function is not identified from the conditional moment restriction. We also study the gain of modifying the penalty in the estimation, considering derivatives in the penalty. We analyze the effect of this modification on the identification of the…

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ON RATE OPTIMALITY FOR ILL-POSED INVERSE PROBLEMS IN ECONOMETRICS

计量经济学病态逆问题的收敛率最优性

In this paper we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax risk lower bounds in mean integrated squared error loss for the NPIR and NPIV models under two basic regularity conditions: the approximation number and the link condition. We show that both a simple projection estimator for the NPIR…

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Matching and semi-parametric IV estimation, a distance-based measure of migration, and the wages of young men

匹配与半参数工具变量估计:距离型迁移指标及青年男性工资

Our paper estimates the effect of US internal migration on wage growth for young men between their first and second job. Our analysis of migration extends previous research by: (i) exploiting the distance-based measures of migration in the National Longitudinal Surveys of Youth 1979 (NLSY79); (ii) allowing the effect of migration to differ by schooling level and (iii) using propensity score matching to estimate the average treatment effect on the treated (ATET) for movers…

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Instrumental variable methods for recovering continuous linear functionals

恢复连续线性泛函的工具变量方法

This paper develops methods for estimating continuous linear functionals in nonparametric instrumental variable problems. Examples of such functionals include consumer surplus and weighted average derivatives. The estimation procedure is robust to a setting where the underlying model is not identified but the linear functional is. In order to attain such robustness, it is necessary to employ a partially identified nuisance parameter. We address this problem by consistently…

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The Hausman test in a Cliff and Ord panel model

Cliff–Ord 面板模型中的 Hausman 检验

This paper studies the random effects model and the fixed effects model for spatial panel data. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We discuss instrumental variable estimation under both the fixed and the random effects specifications and propose a spatial Hausman test which compares these two…

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The Hausman test and weak instruments

Hausman 检验与弱工具变量

We consider the following problem. There is a structural equation of interest that contains an explanatory variable that theory predicts is endogenous. There are one or more instrumental variables that credibly are exogenous with regard to this structural equation, but which have limited explanatory power for the endogenous variable. Further, there is one or more potentially 'strong' instruments, which has much more explanatory power but which may not be exogenous. Hausman…

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Estimating Income Poverty in the Presence of Missing Data and Measurement Error

缺失数据与测量误差下的收入贫困估计

Reliable measures of poverty are an essential statistical tool for public policies aimed at reducing poverty. In this article we consider the reliability of income poverty measures based on survey data which are typically plagued by missing data and measurement error. Neglecting these problems can bias the estimated poverty rates. We show how to derive upper and lower bounds for the population poverty rate using the sample evidence, an upper bound on the probability of…

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Applied Nonparametric Instrumental Variables Estimation

应用非参数工具变量估计

Instrumental variables are widely used in applied econometrics to achieve identification and carry out estimation and inference in models that contain endogenous explanatory variables. In most applications, the function of interest (e.g., an Engel curve or demand function) is assumed to be known up to finitely many parameters (e.g., a linear model), and instrumental variables are used identify and estimate these parameters. However, linear and other finite-dimensional…

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Efficient Tests Under a Weak Convergence Assumption

弱收敛假设下的检验效率

The asymptotic validity of tests is usually established by making appropriate primitive assumptions, which imply the weak convergence of a specific function of the data, and an appeal to the continuous mapping theorem. This paper, instead, takes the weak convergence of some function of the data to a limiting random element as the starting point and studies efficiency in the class of tests that remain asymptotically valid for all models that induce the same weak limit. It is…

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Building a Stronger Instrument in an Observational Study of Perinatal Care for Premature Infants

在早产儿围产期护理观察研究中构建更强工具变量

An instrument is a random nudge toward acceptance of a treatment that affects outcomes only to the extent that it affects acceptance of the treatment. Nonetheless, in settings in which treatment assignment is mostly deliberate and not random, there may exist some essentially random nudges to accept treatment, so that use of an instrument might extract bits of random treatment assignment from a setting that is otherwise quite biased in its treatment assignments. An instrument…

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A NEW PROJECTION-TYPE SPLIT-SAMPLE SCORE TEST IN LINEAR INSTRUMENTAL VARIABLES REGRESSION

线性工具变量回归中的新投影型分样本得分检验

In this paper we introduce a new method of projection-type inference and describe it in the context of two stage least squares–based split-sample inference on subsets of structural coefficients in a linear instrumental variables regression model. The use of the new method not only guards against the uncontrolled overrejection of the true value of the parameters of interest but also reduces the conservativeness of the usual method of projection proposed by Dufour and his…

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INSTRUMENTAL VARIABLE ESTIMATION IN A DATA RICH ENVIRONMENT

数据丰富环境中的工具变量估计

We consider estimation of parameters in a regression model with endogenous regressors. The endogenous regressors along with a large number of other endogenous variables are driven by a small number of unobservable exogenous common factors. We show that the estimated common factors can be used as instrumental variables and they are more efficient than the observed variables in our framework. Whereas standard optimal generalized method of moments estimator using a large number…

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GMM estimation of social interaction models with centrality

利用中心性的社会互动模型 GMM 估计

This paper considers the specification and estimation of social interaction models with network structures and the presence of endogenous, contextual, correlated, and group fixed effects. When the network structure in a group is captured by a graph in which the degrees of nodes are not all equal, the different positions of group members as measured by the Bonacich (1987) centrality provide additional information for identification and estimation. In this case, the Bonacich…

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Set identification and sensitivity analysis with Tobin regressors

含 Tobin 型解释变量的集合识别与敏感性分析

We give semiparametric identification and estimation results for econometric models with a regressor that is endogenous, bound censored, and selected; it is called a Tobin regressor. First, we show that the true parameter value is set-identified and characterize the identification sets. Second, we propose novel estimation and inference methods for this true value. These estimation and inference methods are of independent interest and apply to any problem possessing the…

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Semiparametric efficiency in nonlinear LATE models

非线性 LATE 模型中的半参数效率

In this paper we study semiparametric efficiency for the estimation of a finite-dimensional parameter defined by generalized moment conditions under the local instrumental variable assumptions. These parameters identify treatment effects on the set of compliers under the monotonicity assumption. The distributions of covariates, the treatment dummy, and the binary instrument are not specified in a parametric form, making the model semiparametric. We derive the semiparametric…

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Recent developments in structural microeconometrics

结构微观计量经济学的近期发展

The papers in this Special Issue of The Econometrics Journal arose from the 19th meeting of (EC)2 (European Conferences of the Econom(etr)ics Community in Econometrics and Quantitative Economics) held in Rome, Italy, on December 19–20, 2008, at ‘Palazzo Koch’ that houses the Bank of Italy. The focus of the Conference was on ‘Recent Developments in Structural Microeconometrics’. Both theoretical and applied contributions were presented. The Local Organizing Committee…

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The practice of non‐parametric estimation by solving inverse problems: the example of transformation models

通过求解逆问题进行非参数估计:以变换模型为例

This paper considers a semi‐parametric version of the transformation model φ (Y) =β′X+U under exogeneity or instrumental variables assumptions (E(U∣X) = 0 or . This model is used as an example to illustrate the practice of the estimation by solving linear functional equations. This paper is specially focused on the data‐driven selection of the regularization parameter and of the bandwidths. Simulations experiments illustrate the relevance of this approach.

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Non‐parametric estimation of exact consumer surplus with endogeneity in price

价格内生时精确消费者剩余的非参数估计

This paper analyses a structural microeconomic relation describing the exact consumer surplus in a non-parametric setting with endogenous prices. The exact consumer surplus can be characterized as the solution of a differential equation involving the observed demand function. The strategy put forward in this paper involves two steps: first, estimate the demand function with endogeneity using non-parametric IV, second, plug this estimator into the differential equation to…

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Testing the correlated random coefficient model

相关随机系数模型的检验

The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines…

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Applications of subsampling, hybrid, and size-correction methods

子抽样、混合子抽样与尺寸校正方法的应用

This paper analyzes the properties of subsampling, hybrid subsampling, and size-correction methods in two non-regular models. The latter two procedures are introduced in Andrews and Guggenberger (2009a). The models are non-regular in the sense that the test statistics of interest exhibit a discontinuity in their limit distribution as a function of a parameter in the model. The first model is a linear instrumental variables (IV) model with possibly weak IVs estimated using…

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