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Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT

基于(局部)处理组平均处理效应逆概率加权估计的无混杂检验

We propose inverse probability weighted estimators for the local average treatment effect (LATE) and the local average treatment effect for the treated (LATT) under instrumental variable assumptions with covariates. We show that these estimators are asymptotically normal and efficient. When the (binary) instrument satisfies one-sided noncompliance, we propose a Durbin–Wu–Hausman-type test of whether treatment assignment is unconfounded conditional on some observables. The…

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Asymptotic Efficiency of Semiparametric Two-step GMM

半参数两步 GMM 的渐近效率

Many structural economics models are semiparametric ones in which the unknown nuisance functions are identified via non-parametric conditional moment restrictions with possibly non-nested or overlapping conditioning sets, and the finite dimensional parameters of interest are over-identified via unconditional moment restrictions involving the nuisance functions. In this article we characterize the semiparametric efficiency bound for this class of models. We show that…

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Semiparametric Inference in Dynamic Binary Choice Models

动态二元选择模型中的半参数推断

We introduce an approach for semiparametric inference in dynamic binary choice models that does not impose distributional assumptions on the state variables unobserved by the econometrician. The proposed framework combines Bayesian inference with partial identification results. The method is applicable to models with finite space of observed states. We demonstrate the method on Rust's model of bus engine replacement. The estimation experiments show that the parametric…

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Trade Integration, Market Size, and Industrialization: Evidence from China's National Trunk Highway System

贸易一体化、市场规模与工业化:中国国家干线公路系统的证据

Large-scale transport infrastructure investments connect both large metropolitan centres of production as well as small peripheral regions. Are the resulting trade cost reductions a force for the diffusion of industrial and total economic activity to peripheral regions, or do they reinforce the concentration of production in space? This article exploits China's National Trunk Highway System as a large-scale natural experiment to contribute to our understanding of this…

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Inference in dynamic stochastic general equilibrium models with possible weak identification

可能弱识别的动态随机一般均衡模型推断

This paper considers inference in log-linearized dynamic stochastic general equilibrium (DSGE) models with weakly (including un-) identified parameters. The framework allows for analysis using only part of the spectrum, say at the business cycle frequencies. First, we characterize weak identification from a frequency domain perspective and propose a score test for the structural parameter vector based on the frequency domain approximation to the Gaussian likelihood. The…

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Non-Parametric and Adaptive Modelling of Dynamic Periodicity and Trend with Heteroscedastic and Dependent Errors

异方差相关误差下动态周期与趋势的非参数自适应建模

Summary Periodicity and trend are features describing an observed sequence, and extracting these features is an important issue in many scientific fields. However, it is not an easy task for existing methods to analyse simultaneously the trend and dynamics of the periodicity such as time varying frequency and amplitude, and the adaptivity of the analysis to such dynamics and robustness to heteroscedastic dependent errors are not guaranteed. These tasks become even more…

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Endogeneity in high dimensions

高维模型中的内生性

Most papers on high-dimensional statistics are based on the assumption that none of the regressors are correlated with the regression error, namely, they are exogenous. Yet, endogeneity can arise incidentally from a large pool of regressors in a high-dimensional regression. This causes the inconsistency of the penalized least-squares method and possible false scientific discoveries. A necessary condition for model selection consistency of a general class of penalized…

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Sharp bounds on the variance in randomized experiments

随机实验中方差的锐界

We propose a consistent estimator of sharp bounds on the variance of the difference-in-means estimator in completely randomized experiments. Generalizing Robins [Stat. Med. 7 (1988) 773–785], our results resolve a well-known identification problem in causal inference posed by Neyman [Statist. Sci. 5 (1990) 465–472. Reprint of the original 1923 paper]. A practical implication of our results is that the upper bound estimator facilitates the asymptotically narrowest…

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An instrumental variable random‐coefficients model for binary outcomes

二元结果的工具变量随机系数模型

In this paper, we study a random‐coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be…

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Inference of bidders’ risk attitudes in ascending auctions with endogenous entry

内生进入的升价拍卖中竞标者风险态度的推断

Bidders’ risk attitudes have key implications for the choices of revenue-maximizing auction formats. In ascending auctions, bid distributions do not provide information about risk preference. We infer risk attitudes using distributions of transaction prices and participation decisions in ascending auctions with entry costs. Nonparametric tests are proposed for two distinct scenarios: first, the expected entry cost can be consistently estimated from the data; second, the data…

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Adaptive nonparametric instrumental variables estimation: Empirical choice of the regularization parameter

自适应非参数工具变量估计:正则化参数的经验选择

In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g, is discontinuous and must be regularized to permit consistent estimation. The optimal regularization parameter depends on population characteristics that are unknown in applications. This paper presents a theoretically justified empirical method for choosing the regularization parameter in series estimation. The method adapts to the unknown smoothness of g and other…

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ESTIMATING PERSON‐CENTERED TREATMENT (PeT) EFFECTS USING INSTRUMENTAL VARIABLES: AN APPLICATION TO EVALUATING PROSTATE CANCER TREATMENTS

SUMMARY This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to estimate person‐centered treatment (PeT) effects that are conditioned on the person's observed characteristics and averaged over the potential conditional distribution of unobserved characteristics that lead them to their observed treatment choices. PeT effects are more individualized than conditional treatment effects from a randomized setting…

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Adaptive dynamic Nelson–Siegel term structure model with applications

自适应动态Nelson–Siegel期限结构模型及其应用

We propose an Adaptive Dynamic Nelson–Siegel (ADNS) model to adaptively detect parameter changes and forecast the yield curve. The model is simple yet flexible and can be safely applied to both stationary and nonstationary situations with different sources of parameter changes. For the 3- to 12-months ahead out-of-sample forecasts of the US yield curve from 1998:1 to 2010:9, the ADNS model dominates both the popular reduced-form and affine term structure models; compared to…

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Flexible Marginal Structural Models for Estimating the Cumulative Effect of a Time-Dependent Treatment on the Hazard: Reassessing the Cardiovascular Risks of Didanosine Treatment in the Swiss HIV Cohort Study

时变治疗累积风险效应的灵活边际结构模型:重新评估去羟肌苷的心血管风险

The association between antiretroviral treatment and cardiovascular disease (CVD) risk in HIV-positive persons has been the subject of much debate since the Data collection on Adverse events of Anti-HIV Drugs (D:A:D) study reported that recent use of two antiretroviral drugs, abacavir (ABC) and didanosine (DDI), was associated with increased risk. We focus on the potential impact of DDI use, as this drug has not been as studied intensively as ABC. We propose a flexible…

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EMVS: The EM Approach to Bayesian Variable Selection

EMVS:基于 EM 算法的贝叶斯变量选择

Despite rapid developments in stochastic search algorithms, the practicality of Bayesian variable selection methods has continued to pose challenges. High-dimensional data are now routinely analyzed, typically with many more covariates than observations. To broaden the applicability of Bayesian variable selection for such high-dimensional linear regression contexts, we propose EMVS, a deterministic alternative to stochastic search based on an EM algorithm which exploits a…

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Estimating Mixture of Gaussian Processes by Kernel Smoothing

高斯过程混合模型的核平滑估计

When the functional data are not homogeneous, e.g., there exist multiple classes of functional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimation procedure for the Mixture of Gaussian Processes, to incorporate both functional and inhomogeneous properties of the data. Our method can be viewed as a natural extension of high-dimensional normal mixtures. However, the key difference is that smoothed structures are imposed…

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Quasi-Maximum Likelihood Estimation of GARCH Models With Heavy-Tailed Likelihoods

采用重尾似然的 GARCH 模型拟极大似然估计

The non-Gaussian maximum likelihood estimator is frequently used in GARCH models with the intention of capturing heavy-tailed returns. However, unless the parametric likelihood family contains the true likelihood, the estimator is inconsistent due to density misspecification. To correct this bias, we identify an unknown scale parameter ηf that is critical to the identification for consistency and propose a three-step quasi-maximum likelihood procedure with non-Gaussian…

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Why Do Firms Evade Taxes? The Role of Information Sharing and Financial Sector Outreach

企业为何逃税?信息共享与金融服务覆盖的作用

ABSTRACT Tax evasion is a widespread phenomenon across the globe and even an important factor in the ongoing sovereign debt crisis. We show that firms in countries with better credit information–sharing systems and higher branch penetration evade taxes to a lesser degree. This effect is stronger for smaller firms, firms in smaller cities and towns, firms in industries relying more on external financing, and firms in industries and countries with greater growth potential.…

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POINT DECISIONS FOR INTERVAL–IDENTIFIED PARAMETERS

区间识别参数的点决策

This paper considers a decision maker who prefers to make a point decision when the object of interest is interval-identified with regular bounds. When the bounds are just identified along with known interval length, the local asymptotic minimax decision with respect to a symmetric convex loss function takes an obvious form: an efficient lower bound estimator plus the half of the known interval length. However, when the interval length or any nontrivial upper bound for the…

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GMM ESTIMATION AND UNIFORM SUBVECTOR INFERENCE WITH POSSIBLE IDENTIFICATION FAILURE

可能识别失效下的 GMM 估计与一致有效的子向量推断

This paper determines the properties of standard generalized method of moments (GMM) estimators, tests, and confidence sets (CSs) in moment condition models in which some parameters are unidentified or weakly identified in part of the parameter space. The asymptotic distributions of GMM estimators are established under a full range of drifting sequences of true parameters and distributions. The asymptotic sizes (in a uniform sense) of standard GMM tests and CSs are…

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A NOTE ON ESTIMATING AND TESTING FOR MULTIPLE STRUCTURAL CHANGES IN MODELS WITH ENDOGENOUS REGRESSORS VIA 2SLS

内生解释变量模型中基于两阶段最小二乘的多重结构变化估计与检验:一个注记

This note provides a simple proof for the problem of estimating and testing for multiple breaks in a single equation framework with regressors that are endogenous. We show based on standard assumptions about the regressors, instruments, and errors that the second-stage regression of the instrumental variable procedure involves regressors and errors that satisfy all the assumptions in Perron and Qu (2006, Journal of Econometrics 134, 373–399) so that the results about…

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DISENTANGLING DEMAND AND SUPPLY SHOCKS IN THE CRUDE OIL MARKET: HOW TO CHECK SIGN RESTRICTIONS IN STRUCTURAL VARS

区分原油市场的需求与供给冲击:如何检验结构 VAR 的符号限制

SUMMARY Sign restrictions have become increasingly popular for identifying shocks in structural vector autoregressive (SVAR) models. So far there are no techniques for validating the shocks identified via such restrictions. Although in an ideal setting the sign restrictions specify shocks of interest, sign restrictions may be invalidated by measurement errors, data adjustments or omitted variables. We model changes in the volatility of the shocks via a Markov switching (MS)…

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Retrospective-prospective symmetry in the likelihood and Bayesian analysis of case-control studies

病例对照研究中似然与贝叶斯分析的回顾—前瞻对称性

Prentice & Pyke (1979) established that the maximum likelihood estimate of an odds ratio in a case-control study is the same as would be found by fitting a logistic regression; in other words, for this specific target the incorrect prospective model is inferentially equivalent to the correct retrospective model.Similar results have been obtained for other models, and conditions have also been identified under which the corresponding Bayesian property holds, namely that the…

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Nonparametric inference based on conditional moment inequalities

基于条件矩不等式的非参数推断

This paper develops methods of inference for nonparametric and semiparametric parameters defined by conditional moment inequalities and/or equalities. The parameters need not be identified. Confidence sets and tests are introduced. The correct uniform asymptotic size of these procedures is established. The false coverage probabilities and power of the CS’s and tests are established for fixed alternatives and some local alternatives. Finite-sample simulation results are given…

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