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Jackknife 工具变量估计：对 Angrist、Imbens 与 Krueger（1999）的复现与扩展AI 解读

Abstract I replicate most of the results in Angrist, Imbens, and Krueger ( Journal of Applied Econometrics 1999; 14: 57–67), point to a possible error in and re‐estimate Model 3, and analyze some simple extensions. The programming code, data, and results are available at http://sites.google.com/site/antonnakov/software . Copyright © 2010 John Wiley & Sons, Ltd.

指数与威布尔持续时间模型中的不可观测异质性检验AI 解读

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chi-square, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter…

非可分模型中的结构性测量误差AI 解读

This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly. We explore the consequences of limited recall for the identification of marginal effects. Our identification approach is entirely nonparametric, using Matzkin-type nonseparable models that nest a large class of potential structural models. We show that measurement error due to limited recall…

不完全信息同时行动博弈的半参数估计AI 解读

This paper studies the problem of estimating the normal-form payoff parameters of a simultaneous, discrete game where the realization of such payoffs is not common knowledge. The paper contributes to the existing literature in two ways. First, by making a comparison with the complete information case it formally describes a set of conditions under which allowing for private information in payoffs facilitates the identification of various features of the game. Second,…

高斯时间序列的贝叶斯非参数信号提取AI 解读

We consider the problem of unobserved components in time series from a Bayesian non-parametric perspective. The identification conditions are treated as unknown and analyzed in a probabilistic framework. In particular, informative prior distributions force the spectral decomposition to be in an identifiable region. Then, the likelihood function adapts the prior decompositions to the data. A full Bayesian analysis of unobserved components will be presented for financial high…

存在内生性与样本选择时的面板模型估计AI 解读

We consider estimation of panel data models with sample selection when the equation of interest contains endogenous explanatory variables as well as unobserved heterogeneity. Assuming that appropriate instruments are available, we propose several tests for selection bias and two estimation procedures that correct for selection in the presence of endogenous regressors. The tests are based on the fixed effects two-stage least squares estimator, thereby permitting arbitrary…

潜在竞标人数未知时的一价拍卖估计：误分类方法AI 解读

In this paper, we consider nonparametric identification and estimation of first-price auction models when N*, the number of potential bidders, is unknown to the researcher, but observed by bidders. Exploiting results from the recent econometric literature on models with misclassification error, we develop a nonparametric procedure for recovering the distribution of bids conditional on the unknown N*. Monte Carlo results illustrate that the procedure works well in practice.…

参数比值的识别稳健置信集及其离散选择应用AI 解读

We study the problem of building confidence sets for ratios of parameters, from an identification robust perspective. In particular, we address the simultaneous confidence set estimation of a finite number of ratios. Results apply to a wide class of models suitable for estimation by consistent asymptotically normal procedures. Conventional methods (e.g. the delta method) derived by excluding the parameter discontinuity regions entailed by the ratio functions and which…

弱工具变量下的稳健置信集合AI 解读

This paper considers instrumental variable regression with a single endogenous variable and the potential presence of weak instruments. I construct confidence sets for the coefficient on the single endogenous regressor by inverting tests robust to weak instruments. I suggest a numerically simple algorithm for finding the Conditional Likelihood Ratio (CLR) confidence sets. Full descriptions of possible forms of the CLR, Anderson-Rubin (AR) and Lagrange Multiplier (LM)…

工具变量可能众多时 LIML 估计量的渐近最优性AI 解读

We consider the estimation of the coefficients of a linear structural equation in a simultaneous equation system when there are many instrumental variables. We derive some asymptotic properties of the limited information maximum likelihood (LIML) estimator when the number of instruments is large; some of these results are new as well as old, and we relate them to results in some recent studies. We have found that the variance of the limiting distribution of the LIML…

更便宜意味着更好吗？兼职教师对学生结果的影响AI 解读

Higher education has increasingly relied on part-time, adjunct instructors. Critics argue that adjuncts reduce educational quality because they often have less education than full-time professors. On the other hand, by specializing in teaching or being concurrently employed, adjuncts could enhance learning experiences. This paper quantifies how adjuncts affect subsequent student interest and course performance relative to full-time faculty using an instrumental variable…

两样本工具变量估计量AI 解读

Following an influential article by Angrist and Krueger (1992) on two-sample instrumental variables (TSIV) estimation, numerous empirical researchers have applied a computationally convenient two-sample two-stage least squares (TS2SLS) variant of Angrist and Krueger's estimator. In the two-sample context, unlike the single-sample situation, the IV and 2SLS estimators are numerically distinct. We derive and compare the asymptotic distributions of the two estimators and find…

一般非线性 AR(1) 模型的线性性上确界检验AI 解读

We consider linearity testing in a general class of nonlinear time series models of order one, involving a nonnegative nuisance parameter that (a) is not identified under the null hypothesis and (b) gives the linear model when equal to zero. This paper studies the asymptotic distribution of the likelihood ratio test and asymptotically equivalent supremum tests. The asymptotic distribution is described as a functional of chi-square processes and is obtained without imposing a…

未知异方差下空间自回归模型的 GMM 估计AI 解读

In the presence of heteroskedastic disturbances, the MLE for the SAR models without taking into account the heteroskedasticity is generally inconsistent. The 2SLS estimates can have large variances and biases for cases where regressors do not have strong effects. In contrast, GMM estimators obtained from certain moment conditions can be robust. Asymptotically valid inferences can be drawn with consistently estimated covariance matrices. Efficiency can be improved by…

允许截面依赖的面板数据广义非线性工具变量单位根检验AI 解读

This paper proposes a unit root test for panel data with cross-sectional dependence. The test generalizes the nonlinear IV unit root test of Chang (2002) to the case where there exist some common factors in panels. The main idea is to eliminate the cross-sectional dependence through the method of principal components as in Bai and Ng (2004) and then apply Chang's test to the treated data. Under certain conditions, the proposed test is consistent and has a standard normal…

含自回归与异方差扰动的空间自回归模型：设定与估计AI 解读

This study develops a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first generalize the GMM estimator suggested in (Kelejian and Prucha, 1998) and (Kelejian and Prucha, 1999) for the spatial autoregressive parameter in the disturbance process. We also define IV estimators for the…

结构计量模型中的间接推断AI 解读

This paper considers parametric inference in a wide range of structural econometric models. It illustrates how the indirect inference principle can be used in the inference of these models. Specifically, we show that an ordinary least squares (OLS) estimation can be used as an auxiliary model, which leads to a method that is similar in spirit to a two-stage least squares (2SLS) estimator. Monte Carlo studies and an empirical analysis of timber sale auctions held in Oregon…

一类新的金融传染检验及其应用AI 解读

A new class of tests of contagion is proposed identifying transmission channels of financial market crises through changes in higher order moments of the distribution of returns such as coskewness. Applying the framework to test for contagion in real estate and equity markets following the Hong Kong crisis in 1997–1998 and the U.S. subprime crisis in 2007 shows that the coskewness-based tests of contagion detect additional channels not identified by the correlation-based…

具有网络结构的社会互动模型：设定与估计AI 解读

This paper considers the specification and estimation of social interaction models with network structures and the presence of endogenous, contextual and correlated effects. With macro group settings, group-specific fixed effects are also incorporated in the model. The network structure provides information on the identification of the various interaction effects. We propose a quasi-maximum likelihood approach for the estimation of the model. We derive the asymptotic…

部分识别模型的经验似然推断：大偏差最优性与自助法有效性AI 解读

This paper addresses the issue of optimal inference for parameters that are partially identified in models with moment inequalities. There currently exists a variety of inferential methods for use in this setting. However, the question of choosing optimally among contending procedures is unresolved. In this paper, I first consider a canonical large deviations criterion for optimality and show that inference based on the empirical likelihood ratio statistic is optimal.…

变换加性可分模型的识别与非参数估计AI 解读

Let r(x,z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses the identification and consistent estimation of the unknown functions H, M, G and F, where r(x,z)=H[M(x,z)], M(x,z)=G(x)+F(z), and H is strictly monotonic. An estimation algorithm is proposed for each of the model's unknown components when r(x,z) represents a conditional mean function. The resulting estimators use marginal integration to separate…

序贯教育决策中的异质回报AI 解读

This paper presents a method for estimating returns to multiple schooling levels taking into account that returns may be heterogeneous among agents and that educational decisions are made sequentially. A sequential decision model explicitly considers that the level of education is the result of previous schooling choices and so, the variation of supply-side instruments over time will emerge as a source of identification of the desired parameters. A test for heterogeneity in…

部分识别结构方程中 LIML 估计量的渐近分布AI 解读

We derive a closed-form expression for the asymptotic distribution of the LIML estimator for the coefficients of both endogenous and exogenous variables in a partially identified linear structural equation. We extend previous results of Phillips (1989) and Choi and Phillips (1992), where the focus was on IV estimators. We show that partial failure of identification affects the LIML in that its moments do not exist even asymptotically.

处理效应分布的尖锐界及其统计推断AI 解读

In this paper, we propose nonparametric estimators of sharp bounds on the distribution of treatment effects of a binary treatment and establish their asymptotic distributions. We note the possible failure of the standard bootstrap with the same sample size and apply the fewer-than- n bootstrap to making inferences on these bounds. The finite sample performances of the confidence intervals for the bounds based on normal critical values, the standard bootstrap, and the…