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Estimation and testing for partially linear single-index models

部分线性单指标模型的估计与检验

In partially linear single-index models, we obtain the semiparametrically efficient profile least-squares estimators of regression coefficients. We also employ the smoothly clipped absolute deviation penalty (SCAD) approach to simultaneously select variables and estimate regression coefficients. We show that the resulting SCAD estimators are consistent and possess the oracle property. Subsequently, we demonstrate that a proposed tuning parameter selector, BIC, identifies the…

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Identifying the finite dimensionality of curve time series

曲线时间序列有限维数的识别

The curve time series framework provides a convenient vehicle to accommodate some nonstationary features into a stationary setup. We propose a new method to identify the dimensionality of curve time series based on the dynamical dependence across different curves. The practical implementation of our method boils down to an eigenanalysis of a finite-dimensional matrix. Furthermore, the determination of the dimensionality is equivalent to the identification of the nonzero…

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Penalized high-dimensional empirical likelihood

惩罚化高维经验似然

We propose penalized empirical likelihood for parameter estimation and variable selection for problems with diverging numbers of parameters. Our results are demonstrated for estimating the mean vector in multivariate analysis and regression coefficients in linear models. By using an appropriate penalty function, we showthat penalized empirical likelihood has the oracle property. That is, with probability tending to 1, penalized empirical likelihood identifies the true model…

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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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LOCAL IDENTIFICATION IN EMPIRICAL GAMES OF INCOMPLETE INFORMATION

不完全信息经验博弈的局部识别

This paper studies identification for a broad class of empirical games in a general functional setting. Global identification results are known for some specific models, e.g., in some standard auction models. We use functional formulations to obtain general criteria for local identification. These criteria can be applied to both parametric and nonparametric models, and also to models with asymmetry among players and affiliated private information. A benchmark model is…

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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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Partial identification of spread parameters

分布离散程度参数的部分识别

This paper analyzes partial identification of parameters that measure a distribution's spread, for example, the variance, Gini coefficient, entropy, or interquartile range. The core results are tight, two-dimensional identification regions for the expectation and variance, the median and interquartile ratio, and many other combinations of parameters. They are developed for numerous identification settings, including but not limited to cases where one can bound either 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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Inference in limited dependent variable models robust to weak identification

有限因变量模型中对弱识别稳健的推断

We propose tests for structural parameters in limited dependent variable models with endogenous explanatory variables. These tests are based upon the generalized minimum distance principle. They are of the correct size regardless of whether the structural parameters are identified and are especially appropriate for models whose moment conditions are non-linear in the parameters. Moreover, they are computationally simple, allowing them to be implemented using a large number…

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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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Some identification problems in the cointegrated vector autoregressive model

协整向量自回归模型中的若干识别问题

The paper analyses some identification problems in the cointegrated vector autoregressive model. A criteria for identification by linear restrictions on individual relations is given. The asymptotic distribution of the estimators of [alpha] and [beta] is derived when they are identified by linear restrictions on [beta], and when they are identified by linear restrictions on [alpha]. It it shown that, in the latter case, a component of is asymptotically Gaussian. Finally we…

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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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Optimal Sparse Segment Identification With Application in Copy Number Variation Analysis

稀疏信号段的最优识别及其拷贝数变异应用

Motivated by DNA copy number variation (CNV) analysis based on high-density single nucleotide polymorphism (SNP) data, we consider the problem of detecting and identifying sparse short segments in a long one-dimensional sequence of data with additive Gaussian white noise, where the number, length and location of the segments are unknown. We present a statistical characterization of the identifiable region of a segment where it is possible to reliably separate the segment…

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Informative Retesting

基于个体信息的复检

In situations where individuals are screened for an infectious disease or other binary characteristic and where resources for testing are limited, group testing can offer substantial benefits. Group testing, where subjects are tested in groups (pools) initially, has been successfully applied to problems in blood bank screening, public health, drug discovery, genetics, and many other areas. In these applications, often the goal is to identify each individual as positive or…

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Causal Effects of Treatments for Informative Missing Data due to Progression/Death

疾病进展或死亡导致信息性缺失时的治疗因果效应

In longitudinal clinical trials, when outcome variables at later time points are only defined for patients who survive to those times, the evaluation of the causal effect of treatment is complicated. In this paper, we describe an approach that can be used to obtain the causal effect of three treatment arms with ordinal outcomes in the presence of death using a principal stratification approach. We introduce a set of flexible assumptions to identify the causal effect and…

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Exploiting Regional Treatment Intensity for the Evaluation of Labor Market Policies

利用地区干预强度评估劳动力市场政策

We estimate the effects of active labor market policies (ALMPs) on subsequent employment and earnings by nonparametric instrumental variable estimators. Very informative administrative Swiss data with detailed regional information are combined with exogenous regional variation in program participation probabilities to generate an instrument within well-defined local labor markets. We find that implementation of an ALMP increased individual employment probabilities by about…

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Accurate and robust tests for indirect inference

间接推断的高精度与稳健检验

In this paper we propose accurate parameter and over-identification tests for indirect inference. Under the null hypothesis the new tests are asymptotically χ2-distributed with a relative error of order n−1. They exhibit better finite sample accuracy than classical tests for indirect inference, which have the same asymptotic distribution but an absolute error of order n−1/2. Robust versions of the tests are also provided. We illustrate their accuracy in nonlinear regression,…

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Testing for co-integration in vector autoregressions with non-stationary volatility

非平稳波动率向量自回归中的协整检验

Many key macroeconomic and financial variables are characterized by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special cases. We show that the conventional rank statistics computed as in (Johansen, 1988) and (Johansen, 1991) are potentially unreliable. In particular, their large sample distributions…

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