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含 Tobin 型解释变量的集合识别与敏感性分析AI 解读

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…

分布离散程度参数的部分识别AI 解读

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…

非线性 LATE 模型中的半参数效率AI 解读

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…

加性分位数模型的回拟合与平滑回拟合AI 解读

In this paper, we study the ordinary backfitting and smooth backfitting as methods of fitting additive quantile models. We show that these backfitting quantile estimators are asymptotically equivalent to the corresponding backfitting estimators of the additive components in a specially-designed additive mean regression model. This implies that the theoretical properties of the backfitting quantile estimators are not unlike those of backfitting mean regression estimators. We…

结构微观计量经济学的近期发展AI 解读

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…

有限因变量模型中对弱识别稳健的推断AI 解读

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…

价格内生时精确消费者剩余的非参数估计AI 解读

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…

理解总量犯罪回归AI 解读

This paper provides a general description of the relationship between individual decision problems and aggregate crime regressions. The analysis is designed to elucidate the behavioral and statistical assumptions that are implicit in the use of aggregate crime regressions for both the analysis of crime determinants as well in counterfactual policy evaluation. We apply our general arguments to the question of the deterrent effect of capital punishment and show how alternative…

相关随机系数模型的检验AI 解读

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…

可分物品拍卖中的机制选择与策略性竞价：土耳其国债拍卖实证AI 解读

We propose an estimation method to bound bidders' marginal valuations in discriminatory auctions using individual bid-level data and apply the method to data from the Turkish Treasury auction market. Using estimated bounds on marginal values, we compute an upper bound on the inefficiency of realized allocations as well as bounds on how much additional revenue could have been realized in a counterfactual uniform price or Vickrey auction. We conclude that switching from a…

利用合成残差估计跨期配置参数AI 解读

We present a novel structural estimation procedure for models of intertemporal allocation. This is based on modelling expectations errors directly; we refer to it as synthetic residual estimation (SRE). The flexibility of SRE allows us to account for measurement error in consumption and for heterogeneity in intertemporal allocation parameters. An investigation of the small sample properties of the SRE estimator indicates that it dominates generalized method of moments (GMM)…

策略互动静态模型的估计AI 解读

We study the estimation of static games of incomplete information with multiple equilibria. A static game is a generalization of a discrete choice model, such as a multinomial logit or probit, which allows the actions of a group of agents to be interdependent. While the estimator we study is quite flexible, in most cases it can be easily implemented using standard statistical packages such as STATA. We also propose an algorithm for simulating the model which finds all…

带变量选择的时间序列二元选择风险最小化AI 解读

This paper considers the problem of predicting binary choices by selecting from a possibly large set of candidate explanatory variables, which can include both exogenous variables and lagged dependent variables. We consider risk minimization with the risk function being the predictive classification error. We study the convergence rates of empirical risk minimization in both the frequentist and Bayesian approaches. The Bayesian treatment uses a Gibbs posterior constructed…

单位根空间动态面板数据模型的估计AI 解读

This paper examines the asymptotics of the QMLE for unit root dynamic panel data models with spatial effect and fixed effects. We consider a unit root dynamic panel data model with spatially correlated disturbances and a unit root spatial dynamic panel data model. For both models the estimate of the dynamic coefficient is $\root \of {nT^3 }$ consistent and the estimates of other parameters are $\root \of {nT}$ consistent, and all of them are asymptotically normal. For the…

长面板数据中自协方差与自相关的渐近无偏估计AI 解读

An important reason for analyzing panel data is to observe the dynamic nature of an economic variable separately from its time-invariant unobserved heterogeneity. This paper examines how to estimate the autocovariances of a variable separately from its time-invariant unobserved heterogeneity. When both cross-sectional and time series sample sizes tend to infinity, we show that the within-group autocovariances are consistent, although they are severely biased when the time…

线性混合效应模型的最优划分：识别安慰剂响应者AI 解读

A long-standing problem in clinical research is distinguishing drug treated subjects that respond due to specific effects of the drug from those that respond to non-specific (or placebo) effects of the treatment. Linear mixed effect models are commonly used to model longitudinal clinical trial data. In this paper we present a solution to the problem of identifying placebo responders using an optimal partitioning methodology for linear mixed effects models. Since individual…

纵向数据的函数型变系数模型AI 解读

The proposed functional varying coefficient model provides a versatile and flexible analysis tool for relating longitudinal responses to longitudinal predictors. Specifically, this approach provides a novel representation of varying coefficient functions through suitable auto and cross-covariances of the underlying stochastic processes, which is particularly advantageous for sparse and irregular designs, as often encountered in longitudinal studies. Existing methodology for…

疾病进展或死亡导致信息性缺失时的治疗因果效应AI 解读

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…

基于新型有序回归模型的老年人功能状态预测AI 解读

The functional mobility of the elderly is a very important factor in aging research, and prognostic information is valuable in making clinical and health care policy decisions. We develop a predictive model for the functional status of the elderly based on data from the Second Longitudinal Study of Aging (LSOA II). The functional status is an ordinal response variable. The ordered probit model has been moderately successful in analyzing such data; however, its reliance on…

利用地区干预强度评估劳动力市场政策AI 解读

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…

基于逆概率加权的有界、高效与双重稳健估计AI 解读

Consider estimating the mean of an outcome in the presence of missing data or estimating population average treatment effects in causal inference. A doubly robust estimator remains consistent if an outcome regression model or a propensity score model is correctly specified. We build on a previous nonparametric likelihood approach and propose new doubly robust estimators, which have desirable properties in efficiency if the propensity score model is correctly specified, and…

稀疏高维有向无环图估计的惩罚似然方法AI 解读

Directed acyclic graphs are commonly used to represent causal relationships among random variables in graphical models. Applications of these models arise in the study of physical and biological systems where directed edges between nodes represent the influence of components of the system on each other. Estimation of directed graphs from observational data is computationally NP-hard. In addition, directed graphs with the same structure may be indistinguishable based on…

删失事件时间的归因分数函数AI 解读

Attributable fractions are commonly used to measure the impact of risk factors on disease incidence in the population. These static measures can be extended to functions of time when the time to disease occurrence or event time is of interest. The present paper deals with nonparametric and semiparametric estimation of attributable fraction functions for cohort studies with potentially censored event time data. The semiparametric models include the familiar proportional…

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.