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Criteria for Surrogate end Points Based on Causal Distributions

基于因果分布的替代终点判据

Summary When a treatment has a positive average causal effect (ACE) on an intermediate variable or surrogate end point which in turn has a positive ACE on a true end point, the treatment may have a negative ACE on the true end point due to the presence of unobserved confounders, which is called the surrogate paradox. A criterion for surrogate end points based on ACEs has recently been proposed to avoid the surrogate paradox. For a continuous or ordinal discrete end point,…

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Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression

局部复合分位数回归平滑:局部多项式回归的替代方法

Summary Local polynomial regression is a useful non-parametric regression tool to explore fine data structures and has been widely used in practice. We propose a new non-parametric regression technique called local composite quantile regression smoothing to improve local polynomial regression further. Sampling properties of the estimation procedure proposed are studied. We derive the asymptotic bias, variance and normality of the estimate proposed. The asymptotic relative…

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Testing semiparametric conditional moment restrictions using conditional martingale transforms

利用条件鞅变换检验半参数条件矩限制

This paper studies conditional moment restrictions that contain unknown nonparametric functions, and proposes a general method of obtaining asymptotically distribution-free tests via martingale transforms. Examples of such conditional moment restrictions are single index restrictions, partially parametric regressions, and partially parametric quantile regressions. This paper introduces a conditional martingale transform that is conditioned on the variable in the…

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A new instrumental method for dealing with endogenous selection

处理内生选择的一种新工具变量方法

This paper develops a new method for dealing with endogenous selection. The usual instrumental strategy based on the independence between the outcome and the instrument is likely to fail when selection is directly driven by the dependent variable. Instead, we suggest to rely on the independence between the instrument and the selection variable, conditional on the outcome. This approach may be particularly suitable for nonignorable nonresponse, binary models with missing…

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March Madness, Quantile Regression Bracketology, and the Hayek Hypothesis

疯狂三月、分位数回归对阵预测与哈耶克假说

A quantile regression variant of the classical paired comparison model of mean ratings is proposed. The model is estimated using data for the regular 2004–2005 U.S. college basketball season, and evaluated based on predictive performance for the 2005 National Collegiate Athletic Association (NCAA) basketball tournament. Rather than basing predictions entirely on conditional mean estimates produced by classical least-squares paired comparison methods, the proposed methods…

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Model-Based Clustering of Non-Gaussian Panel Data Based on Skew- t Distributions

基于偏斜t分布的非高斯面板数据模型聚类

We propose a model-based method to cluster units within a panel. The underlying model is autoregressive and non-Gaussian, allowing for both skewness and fat tails, and the units are clustered according to their dynamic behavior, equilibrium level, and the effect of covariates. Inference is addressed from a Bayesian perspective, and model comparison is conducted using Bayes factors. Particular attention is paid to prior elicitation and posterior propriety. We suggest priors…

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Testing for Causal Effects in a Generalized Regression Model With Endogenous Regressors

含内生解释变量的广义回归模型中的因果效应检验

A unifying framework to test for causal effects in nonlinear models is proposed. We consider a generalized linear-index regression model with endogenous regressors and no parametric assumptions on the error disturbances. To test the significance of the effect of an endogenous regressor, we propose a statistic that is a kernel-weighted version of the rank correlation statistic (tau) of Kendall (1938). The semiparametric model encompasses previous cases considered in the…

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The Persistent Effects of Peru's Mining Mita

秘鲁矿业米塔制度的持久影响

This study utilizes regression discontinuity to examine the long-run impacts of the mita, an extensive forced mining labor system in effect in Peru and Bolivia between 1573 and 1812. Results indicate that a mita effect lowers household consumption by around 25% and increases the prevalence of stunted growth in children by around 6 percentage points in subjected districts today. Using data from the Spanish Empire and Peruvian Republic to trace channels of institutional…

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Alternative Models for Moment Inequalities

矩不等式的替代模型

Behavioral choice models generate inequalities which, when combined with additional assumptions, can be used as a basis for estimation. This paper considers two sets of such assumptions and uses them in two empirical examples. The second example examines the structure of payments resulting from the upstream interactions in a vertical market. I then mimic the empirical setting for this example in a numerical analysis which computes actual equilibria, examines how their…

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Irregular Identification, Support Conditions, and Inverse Weight Estimation

非正则识别、支持条件与逆权重估计

In weighted moment condition models, we show a subtle link between identification and estimability that limits the practical usefulness of estimators based on these models. In particular, if it is necessary for (point) identification that the weights take arbitrarily large values, then the parameter of interest, though point identified, cannot be estimated at the regular (parametric) rate and is said to be irregularly identified. This rate depends on relative tail conditions…

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Identification and Estimation of a Discrete Game of Complete Information

完全信息离散博弈的识别与估计

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation-based estimators for static, discrete games. We demonstrate that the model is identified under weak functional form…

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Nonparametric Identification and Estimation of Nonadditive Hedonic Models

非加性特征价格模型的非参数识别与估计

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity…

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Quantile and Probability Curves Without Crossing

无交叉的分位数与概率曲线

This paper proposes a method to address the longstanding problem of lack of monotonicity in estimation of conditional and structural quantile functions, also known as the quantile crossing problem (Bassett and Koenker (1982)). The method consists in sorting or monotone rearranging the original estimated non-monotone curve into a monotone rearranged curve. We show that the rearranged curve is closer to the true quantile curve than the original curve in finite samples,…

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Estimating the Technology of Cognitive and Noncognitive Skill Formation

认知与非认知技能形成技术的估计

This paper formulates and estimates multistage production functions for child cognitive and noncognitive skills. Output is determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the benefits of early investment in children compared to later remediation. We establish nonparametric identification of a general class of…

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Sequential Estimation of Dynamic Discrete Games: A Comment

动态离散博弈的序贯估计:评论

Recursive procedures which are based on iterating on the best response mapping have difficulties converging to all equilibria in multi-player games. We illustrate these difficulties by revisiting the asymptotic properties of the iterative nested pseudo maximum likelihood method for estimating dynamic games introduced by Aguirregabiria and Mira (2007). An example shows that the iterative method may not be consistent. Copyright 2010 The Econometric Society.

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Instrumental Variable Models for Discrete Outcomes

离散结果的工具变量模型

Single equation instrumental variable models for discrete outcomes are shown to be set identifying, not point identifying, for the structural functions that deliver the values of the discrete outcome. Bounds on identified sets are derived for a general nonparametric model and sharp set identification is demonstrated in the binary outcome case. Point identification is typically not achieved by imposing parametric restrictions. The extent of an identified set varies with the…

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A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √ n -Consistent Conditional Estimator

允许 √n 一致条件估计的含未观测异质性动态二元面板模型

A model for binary panel data is introduced which allows for state dependence and unobserved heterogeneity beyond the effect of available covariates. The model is of quadratic exponential type and its structure closely resembles that of the dynamic logit model. However, it has the advantage of being easily estimable via conditional likelihood with at least two observations (further to an initial observation) and even in the presence of time dummies among the regressors.…

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Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin

边际政策变化的评估与决策边界人群的平均处理效应

This paper develops methods for evaluating marginal policy changes. We characterize how the effects of marginal policy changes depend on the direction of the policy change, and show that marginal policy effects are fundamentally easier to identify and to estimate than conventional treatment parameters. We develop the connection between marginal policy effects and the average effect of treatment for persons on the margin of indifference between participation in treatment and…

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Binary Response Models for Panel Data: Identification and Information

面板数据二元响应模型:识别与信息

This paper considers a panel data model for predicting a binary outcome. The conditional probability of a positive response is obtained by evaluating a given distribution function (F) at a linear combination of the predictor variables. One of the predictor variables is unobserved. It is a random effect that varies across individuals but is constant over time. The semiparametric aspect is that the conditional distribution of the random effect, given the predictor variables,…

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Effects of school reform on education and labor market performance: Evidence from Chile's universal voucher system

学校改革对教育与劳动力市场表现的影响:智利普遍教育券制度的证据

This paper studies the effects of school reform in Chile, which adopted a nationwide school voucher program along with school decentralization reforms in 1981. Since then, Chile has had a relatively unregulated, competitive market in primary and secondary education. It therefore provides a unique setting in which to study how these reforms affected school attainment and labor market outcomes. This paper develops and estimates a dynamic model of school attendance and work…

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Partial Identification of the Distribution of Treatment Effects in Switching Regime Models and its Confidence Sets

切换机制模型中处理效应分布的部分识别及其置信集

In this paper, we establish sharp bounds on the joint distribution of potential outcomes and the distribution of treatment effects in parametric switching regime models with normal mean-variance mixture errors and in the semi-parametric switching regime models of Heckman (1990). Our results for parametric switching regime models with normal mean-variance mixture errors extend some existing results for the Gaussian switching regime model and our results for semi-parametric…

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A note on the variance of doubly-robust G-estimators

双重稳健 G 估计量方差的一则说明

A recursive variance calculation is derived for doubly-robust G-estimators for dynamic treatment regimes in a multi-interval setting. Treatment decision parameters are not assumed to be shared across treatment intervals; this independence of parameters permits sequential estimation of the G-estimators’ variance when G-estimation is performed in a sequential fashion. The recursive variance calculation is both natural and computationally feasible. This development can easily…

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Quantile regression in partially linear varying coefficient models

部分线性变系数模型中的分位数回归

Semiparametric models are often considered for analyzing longitudinal data for a good balance between flexibility and parsimony. In this paper, we study a class of marginal partially linear quantile models with possibly varying coefficients. The functional coefficients are estimated by basis function approximations. The estimation procedure is easy to implement, and it requires no specification of the error distributions. The asymptotic properties of the proposed estimators…

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A maximum likelihood method for the incidental parameter problem

处理附带参数问题的极大似然方法

This paper uses the invariance principle to solve the incidental parameter problem of [Econometrica 16 (1948) 1–32]. We seek group actions that preserve the structural parameter and yield a maximal invariant in the parameter space with fixed dimension. M-estimation from the likelihood of the maximal invariant statistic yields the maximum invariant likelihood estimator (MILE). Consistency of MILE for cases in which the likelihood of the maximal invariant is the product of…

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