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The Double Power Law in Consumption and Implications for Testing Euler Equations

消费中的双侧幂律及其对欧拉方程检验的影响

We provide evidence suggesting that the cross-sectional distributions of US consumption and its growth rate obey the power law in both the upper and lower tails, with exponents approximately equal to four. Consequently, high-order moments are unlikely to exist, and the generalized method of moments estimation of Euler equations that employs cross-sectional moments may be inconsistent. Through bootstrap studies, we find that the power law appears to generate spurious…

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A Matching Estimator Based on a Bilevel Optimization Problem

基于双层优化问题的匹配估计量

This paper proposes a novel matching estimator where neighbors used and weights are endogenously determined by optimizing a covariate balancing criterion. The estimator is based on finding, for each unit that needs to be matched, sets of observations such that a convex combination of them has the same covariate values as the unit needing matching or with minimized distance between them. We implement the proposed estimator with data from the National Supported Work…

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U.S. Multinationals and Preferential Market Access

美国跨国企业与优惠市场准入

We combine firm-level panel data on U.S. foreign affiliate activity with detailed measures of U.S. trade policy to study the relationship between offshoring and preferential market access. Consistent with theory, we find that trade preferences and offshoring activity are positively and significantly correlated. Using instrumental variables, we estimate that a 10% increase in U.S. foreign affiliate exports to the United States is associated with a 4 percentage point increase…

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TESTING FOR TREATMENT DEPENDENCE OF EFFECTS OF A CONTINUOUS TREATMENT

连续处理效应是否随处理水平变化的检验

This paper provides nonparametric tests for hypotheses about the effects of a continuous treatment variable in a nonseparable structural equation. Specifically, we consider local average responses and average partial effects and test whether these effects are identical across different levels of treatment, including testing whether they are zero for all treatment levels as a special case. Our tests are based on consistent procedures of Bierens (1982, Journal of Econometrics…

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WHAT DO QUANTILE REGRESSIONS IDENTIFY FOR GENERAL STRUCTURAL FUNCTIONS?

分位数回归对一般结构函数识别了什么?

This paper shows what quantile regressions identify for general structural functions. Under fairly mild conditions, the quantile partial derivative identifies a weighted average of heterogeneous structural partial effects among the subpopulation of individuals at the conditional quantile of interest. This result justifies the use of quantile regressions as means of measuring heterogeneous causal effects for a general class of structural functions with multiple unobservables.

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Nonparametric tests of conditional treatment effects with an application to single-sex schooling on academic achievements

条件处理效应的非参数检验:单性别学校学业表现的应用

We develop a general class of nonparametric tests for treatment effects conditional on covariates. We consider a wide spectrum of null hypotheses regarding conditional treatment effects, including the following: (a) the null hypothesis of the conditional stochastic dominance between treatment and control groups; (b) the null hypothesis that the conditional average treatment effect is nonpositive for each value of covariates; (c) the null hypothesis of no distributional (or…

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Semiparametric causal inference in matched cohort studies

匹配队列研究中的半参数因果推断

Odds ratios can be estimated in case-control studies using standard logistic regression, ignoring the outcome-dependent sampling. In this paper we discuss an analogous result for treatment effects on the treated in matched cohort studies. Specifically, in studies where a sample of treated subjects is observed along with a separate sample of possibly matched controls, we show that efficient and doubly robust estimators of effects on the treated are computationally equivalent…

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Regression Analysis of Sparse Asynchronous Longitudinal Data

稀疏异步纵向数据的回归分析

Summary We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or…

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Causal Inference from 2K Factorial Designs by Using Potential Outcomes

两水平析因设计的潜在结果因果推断

Summary A framework for causal inference from two-level factorial designs is proposed, which uses potential outcomes to define causal effects. The paper explores the effect of non-additivity of unit level treatment effects on Neyman's repeated sampling approach for estimation of causal effects and on Fisher's randomization tests on sharp null hypotheses in these designs. The framework allows for statistical inference from a finite population, permits definition and…

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Semiparametric single-index panel data models with cross-sectional dependence

存在截面依赖的半参数单指标面板模型

In this paper, we consider a semiparametric single-index panel data model with cross-sectional dependence and stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the link function for the case where both cross-sectional dimension (N) and temporal dimension (T) go…

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Maximum likelihood estimation of a spatial autoregressive Tobit model

空间自回归Tobit模型的最大似然估计

This paper examines a Tobit model with spatial autoregressive interactions. We consider the maximum likelihood estimation for this model and analyze asymptotic properties of the estimator based on the spatial near-epoch dependence of the dependent variable process generated from the model structure. We show that the maximum likelihood estimator is consistent and asymptotically normally distributed. Monte Carlo experiments are performed to verify finite sample properties of…

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Quantile cointegration in the autoregressive distributed-lag modeling framework

自回归分布滞后框架中的分位数协整

Xiao (2009) develops a novel estimation technique for quantile cointegrated time series by extending Phillips and Hansen’s (1990) semiparametric approach and Saikkonen’s (1991) parametrically augmented approach. This paper extends Pesaran and Shin’s (1998) autoregressive distributed-lag approach into quantile regression by jointly analyzing short-run dynamics and long-run cointegrating relationships across a range of quantiles. We derive the asymptotic theory and provide a…

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Two-step estimation of network-formation models with incomplete information

不完全信息网络形成模型的两步估计

We model network formation as a simultaneous game of incomplete information, allowing linking decisions to depend on the structure of the network as well as the attributes of agents. When the data is rationalized by a symmetric equilibrium, meaning observationally equivalent agents choose the same ex-ante strategies, the model can be estimated using a computationally simple two-step estimator. We derive its asymptotic properties under a sequence of models sending the number…

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Heterogeneity and selection in dynamic panel data

动态面板数据中的异质性与选择

The data generating process (DGP) for generic dynamic panel data consists of a law of state dynamics g, a selection or attrition rule h, and an initial condition F. I study nonparametric identifiability of this complete DGP (g,h,F) using short unbalanced panel data, allowing for nonseparability between observed states and unobserved heterogeneity in each of g, h and F. For T⩾3, the DGP is identified by using a proxy variable. For T⩾6, the three additional periods construct a…

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Estimation of heterogeneous autoregressive parameters with short panel data

利用短面板估计异质自回归参数的截面分布

This paper presents a maximum likelihood approach to estimation of cross sectional distributions of heterogeneous autoregressive (AR) parameters with short panel data. We construct a panel likelihood by integrating the unknown cross sectional density of heterogeneous AR parameters with respect to a known time-series data generating kernel. The solution to this extremal criterion recovers the unknown density of heterogeneous AR parameters. Applying our method to a model of…

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Identification and estimation in a correlated random coefficients binary response model

相关随机系数二元响应模型的识别与估计

We study a linear index binary response model with random coefficients B allowed to be correlated with regressors X. We identify the mean of the distribution of B and show how the mean can be interpreted as a vector of expected relative effects. We use instruments and a control vector V to make X independent of B given V. This leads to a localize-then-average approach to both identification and estimation. We develop a n-consistent and asymptotically normal estimator of a…

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Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity

横截面异方差下动态面板变换似然估计的稳健标准误

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao et al. (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem and its implications for estimation and inference. We approach the problem by working with a mis-specified homoskedastic model, and then show that the transformed maximum likelihood estimator continues to be…

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Jackknife model averaging for quantile regressions

分位数回归的刀切法模型平均

In this paper we consider model averaging for quantile regressions (QR) when all models under investigation are potentially misspecified and the number of parameters is diverging with the sample size. To allow for the dependence between the error terms and regressors in the QR models, we propose a jackknife model averaging (JMA) estimator which selects the weights by minimizing a leave-one-out cross-validation criterion function and demonstrate its asymptotic optimality in…

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Large sample properties of the matrix exponential spatial specification with an application to FDI

矩阵指数空间模型的大样本性质及其外国直接投资应用

This paper studies large sample properties of the matrix exponential spatial specification (MESS). We find that the quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the QMLE of the SAR model. For the general model that has MESS in both the dependent variable and disturbances, labeled MESS(1,1), the QMLE can be consistent under unknown heteroskedasticity when the spatial weights matrices in the two MESS…

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Efficient estimation of nonparametric genetic risk function with censored data

删失数据下非参数遗传风险函数的有效估计

With an increasing number of causal genes discovered for complex human disorders, it is crucial to assess the genetic risk of disease onset for individuals who are carriers of these causal mutations and compare the distribution of age-at-onset with that in non-carriers. In many genetic epidemiological studies aiming at estimating causal gene effect on disease, the age-at-onset of disease is subject to censoring. In addition, some individuals' mutation carrier or non-carrier…

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Semiparametric GEE analysis in partially linear single-index models for longitudinal data

纵向数据部分线性单指标模型的半参数 GEE 分析

In this article, we study a partially linear single-index model for longitudinal data under a general framework which includes both the sparse and dense longitudinal data cases. A semiparametric estimation method based on a combination of the local linear smoothing and generalized estimation equations (GEE) is introduced to estimate the two parameter vectors as well as the unknown link function. Under some mild conditions, we derive the asymptotic properties of the proposed…

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Combining Matching and Nonparametric Instrumental Variable Estimation: Theory and An Application to the Evaluation of Active Labour Market Policies

结合匹配与非参数工具变量估计:理论及积极劳动力市场政策评估

Summary We show how instrumental variable and matching estimators can be combined in order to identify a broader array of treatment effects. Instrumental variable (IV) estimators are known to estimate effects only for the compliers, representing a subset of the entire population. By combining IV with matching, we can estimate the treatment effects for the always‐ and never‐takers as well. Since in many cases these groups are the (endogenous) outcome of some assignment…

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A New Utility‐Consistent Econometric Approach to Multivariate Count Data Modeling

多元计数数据建模的效用一致计量方法

Summary In the current paper, we propose a new utility‐consistent modeling framework to explicitly link a count data model with an event‐type multinomial‐choice model. The proposed framework uses a multinomial probit kernel for the event‐type choice model and introduces unobserved heterogeneity in both the count and discrete‐choice components. Additionally, this paper establishes important new results regarding the distribution of the maximum of multivariate normally…

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When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions

何时能成为就业跳板?经济条件变化下的固定期限合同与劳务派遣

Summary This paper emphasizes differences among short‐term contracts in terms of career prospects. Using French data over the 2002–2010 period, we rely on a dynamic model with fixed effects to disentangle state dependence from unobserved heterogeneity. Although fixed‐term contracts may provide a ‘stepping‐stone’ to permanent positions, temporary agency work is hardly better than unemployment in this regard. The Great Recession of 2008 has changed the dynamics on the labor…

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