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An Alternative Estimator for the Censored Quantile Regression Model

线性删失分位数回归模型的一种替代估计量

This paper introduces an alternative estimator for the linear censored quantile regression model. The estimator also applies to cases where the censoring point is unknown. Since the objective function is globally convex and the estimator is a solution to a linear programming problem, a global minimizer is obtained in a finite number of simplex iterations. The estimator has a square root of n-convergence rate and is asymptotically normal. A Monte Carlo study performed shows…

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Instrumental Models and Indirect Encompassing

工具模型与间接涵盖

We introduce nonnested hypotheses tests using indirect, simulation-based estimation procedures. We propose different test statistics and carefully examine the corresponding implicit mi hypotheses. A notion of indirect encompassing comes up naturally, which may be compared to the usual encompassing conditions. Then we show how these methods extend standard specification and overidentification tests.

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High Breakdown Point Conditional Dispersion Estimation with Application to S & P 500 Daily Returns Volatility

高崩溃点条件离散度估计:应用于标普500日收益波动率

The authors show that quasimaximum likelihood (QML) estimators for conditional dispersion models can be severely affected by a small number of outliers such as market crashes and rallies, and they propose new estimation strategies (the two-stage Hampel estimators and two-stage S-estimators) resistant to the effects of outliers and study the properties of these estimators. They apply their methods to estimate models of the conditional volatility of the daily returns of the…

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Subject Evaluation in Social Experiments

社会实验中的受试者评价

This paper concerns inferring how self-interested subjects, as opposed to altruistic investigators, evaluate treatments in social experiments. The authors argue that the attrition behavior of subjects reveals their evaluation and discuss the usefulness of using such data in performing subject-based evaluation. The authors study the causes of disagreements between investigators and subjects in evaluating treatments and empirically assess the degree to which they disagree. The…

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Large Sample Properties of Posterior Densities, Bayesian Information Criterion and the Likelihood Principle in Nonstationary Time Series Models

非平稳时间序列模型中后验密度的大样本性质、贝叶斯信息准则与似然原则

Asymptotic normality of posterior is a well understood result for dynamic as well as non-dynamic models based on sets of abstract conditions that are hard to verify especially for the case of nonstationarity. In this paper the authors provide a set of conditions by which they can relatively easily prove the asymptotic posterior normality under quite general situations of possible nonstationarity. This result reinforces and generalizes the validity of inference based on the…

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Sieve Extremum Estimates for Weakly Dependent Data

弱依赖数据下的筛极值估计

Many non/semiparametric time series estimates may be regarded as different forms of sieve extremum estimates. For stationary absolute regular mixing observations, the authors obtain convergence rates of sieve extremurn estimates and root-n asymptotic normality of 'plug-in' sieve extremum estimates of smooth functionals. As applications to time series models, they give convergence rates for nonparametric ARX(p,q) regression via neural networks, splines, wavelets; root-n…

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Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants

利用参军申请者的社会保障数据估计志愿兵役的劳动力市场影响

Effects of military service on veterans' earnings are estimated using Social Security administrative records to fit models with heterogeneous potential outcomes. The first estimation strategy uses matching and regression to compare applicants who enlisted with applicants who did not enlist. The second uses instrumental variables generated by an error in military entrance exams. The empirical results suggest that military service led to higher employment rates for veterans.…

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Information Theoretic Approaches to Inference in Moment Condition Models

矩条件模型推断的信息论方法

This paper develops a variant of one-step efficient GMM based on the KLIC rather than empirical likelihood. As in other one-step methods, the authors introduce M (the number of moments) auxiliary 'tilting' parameters which are used to construct a reweighting of the data so that the reweighted sample obeys all the moment conditions at the parameter estimates. Parameter and overidentification tests can be recast in terms of these tilting parameters; such tests are often…

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On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects

倾向得分在平均处理效应有效半参数估计中的作用

The role of propensity score in the efficient estimation of the average treatment effects is examined. If the treatment is ignorable given some observed characteristics, it is shown that the propensity score is ancillary for estimation of the average treatment effects but not for estimation of average treatment effects on the treated. Efficient semiparametric estimators take the form of relevant sample averages of the data completed by the nonparametric imputation method.…

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Trend Function Hypothesis Testing in the Presence of Serial Correlation

存在序列相关时的趋势函数假设检验

Test statistics are proposed for testing hypotheses about the parameters of the deterministic trend function of a univariate time series. The tests are valid for general forms of serial correlation in the errors and do not require estimates (parametric or nonparametric) of serial correlation parameters. The tests are valid for stationary and unit root errors. Allowable trend functions include linear polynomials of time that may have structural change. Asymptotic results are…

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Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors

含内生或误测解释变量的半参数潜变量模型估计

A simple root n consistent, asymptotically normal semiparametric estimator of the coefficient vector beta in the latent variable specification y = L (beta'x + e) is constructed. The distribution of e is unknown and may be correlated with x or be conditionally heteroscedastic, e.g., x can contain measurement error. The function L can also be unknown. The identification assumption is that e is uncorrelated with instruments u and that the conditional distribution of e given x…

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Exact Inference Methods for First-Order Autoregressive Distributed Lag Models

一阶自回归分布滞后模型的精确推断方法

Exact tests and confidence sets are obtained for general transformations of the coefficients in linear first-order autoregressive models with exogenous variables and i.i.d. disturbances. The tests proposed have known level and are either similar (constant rejection probability under all processes consistent with the null hypothesis) or use bounds which are free of nuisance parameters. Correspondingly, the confidence sets are either similar with known size or conservative.…

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Estimating and Testing Linear Models with Multiple Structural Changes

含多重结构变化的线性模型:估计与检验

This paper develops the statistical theory for testing and estimating multiple change points in regression models. The rate of convergence and limiting distribution for the estimated parameters are obtained. Several test statistics are proposed to determine the existence as well as the number of change points. A partial structural change model is considered. The authors study both fixed and shrinking magnitudes of shifts. In addition, the models allow for serially correlated…

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Statistical Inference for the Measurement of the Incidence of Taxes and Transfers

税收与转移支付归宿测度的统计推断

We establish the asymptotic sampling distribution of general functions of quantile-based estimators computed from samples that are not necessarily independent. The results provide the statistical framework within which to assess the progressivity of taxes and benefits, their horizontal inequity, and the change in the inequality of income which they cause. By the same token, these findings characterise the sampling distribution of a number of popular indices of progressivity,…

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Estimation of a Panel Data Sample Selection Model

面板数据样本选择模型的估计

The author considers the problem of estimation in a panel data sample selection model, where both the selection and the regression equation of interest contain unobservable individual-specific effects. He proposes a two-step estimation procedure, which 'differences out' the sample selection effect and the unobservable individual effect from the equation of interest. In the first step, the unknown coefficients of the 'selection' equation are consistently estimated. The…

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Some Impossibility Theorems in Econometrics With Applications to Structural and Dynamic Models

计量经济学中的若干不可能性定理及其在结构与动态模型中的应用

General characterizations of valid confidence sets and tests in problems involving (locally almost) unidentified (LAU) parameters are presented. In particular, any valid confidence set for an unbounded LAU parameter must be unbounded with positive probability. Consequently, almost surely bounded confidence sets, like Wald-type confidence sets, have zero coverage probability and Wald-type test statistics cannot be pivotal functions. The results are applied to simultaneous…

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Monotone Treatment Response

单调处理响应

This paper investigates what may be learned about treatment response when it is assumed that response functions are monotone, semimonotone, or concave-monotone. Nothing is assumed about the process of treatment selection and cross-individual restrictions on response are not imposed. The idea is to determine, for every member of the population, the response functions that pass through the realized (treatment, outcome) pair and that are consistent with the assumption imposed.…

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The "Devil's Horns" Problem of Inverting Confluent Characteristic Functions

汇合特征函数反演中的“魔鬼之角”问题

WE WARN OF A CLASS of problems that can occur when inverting confluent characteristic functions (CF's). The term confluence is often used in Mathematics in connection with analysis and/or dynamic (difference, differential, and integral) equations; for example, see the classic text by Whittaker and Watson (1927). A confluence (of singularities) is a joint degeneracy that occurs within a function; here, the CF. When one is dealing with the CF of a k-dimensional variate where k…

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Virtual Bayesian Implementation

虚拟贝叶斯实施

Allowing for incomplete information, this paper characterizes the social choice functions that can be approximated by the equilibrium outcomes of a mechanism: incentive compatibility is necessary and almost sufficient for virtual Bayesian implementability. In conjunction with a second condition, Bayesian incentive consistency, incentive compatibility is also sufficient. This new condition is weak--under standard topological and informational assumptions it is satisfied by…

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A Conditional Kolmogorov Test

条件柯尔莫哥洛夫检验

This paper introduces a conditional Kolmogorov test of model specification for parametric models with covariates (regressors). The test is an extension of the Kolmogorov test of goodness-of-fit for distribution functions. The test is shown to have power against 1/[square root of n] local alternatives and all fixed alternatives to the null hypothesis. A parametric bootstrap procedure is used to obtain critical values for the test.

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Constructing Instruments for Regressions With Measurement Error When no Additional Data are Available, with An Application to Patents and R&D

无额外数据时为测量误差回归构造工具变量:专利与研发应用

Arthur Lewbel, Constructing Instruments for Regressions With Measurement Error When no Additional Data are Available, with An Application to Patents and R&D, Econometrica, Vol. 65, No. 5 (Sep., 1997), pp. 1201-1213

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