论文检索

摘要暂缺

相关随机系数与处理效应面板模型的固定效应及相关估计量AI 解读

I derive conditions under which a class of fixed-effects estimators consistently estimates the population-averaged slope coefficients in panel data models with individual-specific slopes, where the slopes are allowed to be correlated with the covariates. In addition to including the usual fixed-effects estimator, the results apply to estimators that eliminate individual-specific trends. I apply the results, and propose alternative estimators, to estimation of average…

结构方程、处理效应与计量经济政策评估AI 解读

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common semiparametric functional form; to organize the literature on alternative estimators; and to explore what policy questions commonly used estimators in the treatment effect literature answer. A…

终身等价尺度的半参数估计AI 解读

Abstract Pashardes ( 1991 ) and Banks et al. ( 1994 ) use parametric methods to estimate lifetime equivalence scales. Their approaches put parametric restrictions on the differences in within‐period expenditure needs across household types, the intertemporal allocation of expenditure, and the shapes of commodity demand equations. This paper puts parametric structure only on the differences in within‐period expenditure needs across household types. This implies structure on…

我没说，也不会说：SIPP中的动态回答误差AI 解读

Abstract Using state administrative records matched to the 1984 Survey of Income and Program Participation , we examine intertemporal relationships in response errors. False negative errors in reporting food stamps are highly correlated across interviews for the same household. Hypotheses that the error process can be explained by learning behaviour are not supported. Bivariate probit of response error in two periods reveals that responses to covariates are stable over time…

利用分位数回归反事实分解工资分布变化AI 解读

Abstract We propose a method to decompose the changes in the wage distribution over a period of time in several factors contributing to those changes. The method is based on the estimation of marginal wage distributions consistent with a conditional distribution estimated by quantile regression as well as with any hypothesized distribution for the covariates. Comparing the marginal distributions implied by different distributions for the covariates, one is then able to…

过街还是等待？行人过街决策的实证分析AI 解读

Abstract We examine the behaviour of pedestrians wishing to cross a stream of traffic at signalized intersections. We model each pedestrian as making a discrete crossing choice by comparing the gaps between vehicles in traffic to an individual‐specific ‘critical gap’ that characterizes the individual's minimal acceptable gap. We propose both parametric and nonparametric approaches to estimate the distribution of critical gaps in the population of pedestrians. To estimate the…

航空网络管理中的离散选择建模AI 解读

Abstract The task of airline network management is to develop new flight schedule variants and evaluate them in terms of expected passenger demand and revenue. Given the industry's trend towards global cooperation, this is especially important when evaluating the potential synergies with alliance partners. From the econometric point of view, this task represents a discrete choice modelling problem in which one has to account for a large number of dependent alternatives. In…

极端分位数回归AI 解读

Quantile regression is an important tool for estimation of conditional quantiles of a response Y given a vector of covariates X. It can be used to measure the effect of covariates not only in the center of a distribution, but also in the upper and lower tails. This paper develops a theory of quantile regression in the tails. Specifically, it obtains the large sample properties of extremal (extreme order and intermediate order) quantile regression estimators for the linear…

纵向数据广义估计方程的渐近结果AI 解读

We consider the marginal models of Liang and Zeger [Biometrika 73 (1986) 13–22] for the analysis of longitudinal data and we develop a theory of statistical inference for such models. We prove the existence, weak consistency and asymptotic normality of a sequence of estimators defined as roots of pseudo-likelihood equations.

相依删失下边际比例风险回归的似然方法AI 解读

In many public health problems, an important goal is to identify the effect of some treatment/intervention on the risk of failure for the whole population. A marginal proportional hazards regression model is often used to analyze such an effect. When dependent censoring is explained by many auxiliary covariates, we utilize two working models to condense high-dimensional covariates to achieve dimension reduction. Then the estimator of the treatment effect is obtained by…

带辅助数据的测量误差模型AI 解读

We study the problem of parameter inference in (possibly non-linear and non-smooth) econometric models when the data are measured with error. We allow for arbitrary correlation between the true variables and the measurement errors. To solve the identification problem, we require the existence of an auxiliary data-set that contains information about the conditional distribution of the true variables given the mismeasured variables. Our main assumption requires that the…

利用企业家努力与财富检验代理理论AI 解读

ABSTRACT We develop a principal‐agent model in an entrepreneurial setting and test the model's predictions using unique data on entrepreneurial effort and wealth in privately held firms. Accounting for unobserved firm heterogeneity using instrumental‐variables techniques, we find that entrepreneurial ownership shares increase with outside wealth and decrease with firm risk; effort increases with ownership; and effort increases firm performance. The magnitude of the effects…

动态面板数据模型中的偏误修正估计AI 解读

This study develops a new bias-corrected estimator for the fixed-effects dynamic panel data model and derives its limiting distribution for finite number of time periods, T, and large number of cross-section units, N. The bias-corrected estimator is derived as a bias correction of the least squares dummy variable (within) estimator. It does not share some of the drawbacks of recently developed instrumental variables and generalized method-of-moments estimators and is…

食品消费截面与时间序列弹性的面板及伪面板估计AI 解读

This article addresses the problem of the bias of income and expenditure elasticities estimated on pseudopanel data caused by measurement error and unobserved heterogeneity. We gauge these biases empirically by comparing cross-sectional, pseudo-panel, and true panel data from both Polish and U.S. expenditure surveys. Our results suggest that unobserved heterogeneity imparts a downward bias to cross-section estimates of income elasticities of at-home food expenditures and an…

含固定效应的非线性面板模型中的时不变解释变量AI 解读

This paper generalizes the intuition of Hausman and Taylor (1981, Econometrica 49, 1377–1398) and develops a method of dealing with a time-invariant regressor in nonlinear panel models with fixed effects. We illustrate the usefulness of our result by discussing the implication for some nonlinear models of social interactions.We are grateful to Dan Ackerberg and Jerry Hausman for helpful comments. The first author gratefully acknowledges financial support from NSF grant…

非对称核密度估计与平滑直方图的一致性及收入数据应用AI 解读

We consider asymmetric kernel density estimators and smoothed histograms when the unknown probability density function f is defined on [0,+∞). Uniform weak consistency on each compact set in [0,+∞) is proved for these estimators when f is continuous on its support. Weak convergence in L1 is also established. We further prove that the asymmetric kernel density estimator and the smoothed histogram converge in probability to infinity at x = 0 when the density is unbounded at x…

非参数前沿估计：基于条件分位数的方法AI 解读

In frontier analysis, most of the nonparametric approaches (free disposal hull [FDH], data envelopment analysis [DEA]) are based on envelopment ideas, and their statistical theory is now mostly available. However, by construction, they are very sensitive to outliers. Recently, a robust nonparametric estimator has been suggested by Cazals, Florens, and Simar (2002, Journal of Econometrics 1, 1–25). In place of estimating the full frontier, they propose rather to estimate an…

总体分位数的校准插值置信区间AI 解读

Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructing nonparametric confidence intervals for population quantiles based on a random sample of size n. We show that the coverage error of the interpolated interval, which is of order O(n−1), can be improved upon by calibrating the nominal coverage level. Three distinct methods of calibration are considered. The analytical and Monte Carlo methods succeed in reducing the order of…

时间维度有限时异质面板数据的平稳性检验AI 解读

and hence makes the test valid for any (T, N) combination. The asymptotic distributions of the tests are derived under the null and are shown to be normally distributed. Their moments for T fixed are derived analytically using Ghazal's (1994, Statistics and Probability letters 20, 313--319) 1 lemma 1. Finite sample size and power are considered in a Monte Carlo experiment. The proposed tests have empirical sizes that are very close to the nominal 5% level. The Monte Carlo…

We propose an estimator for count data regression models where a binary regressor is endogenously determined. This estimator departs from previous approaches by using a flexible form for the conditional probability function of the counts. Using a Monte Carlo experiment we show that our estimator improves the fit and provides a more reliable estimate of the impact of regressors on the count when compared to alternatives which do restrict the mean to be linear‐exponential. In…

摘要暂缺

摘要暂缺

纵向与聚类数据的有效半参数边际估计AI 解读

We consider marginal generalized semiparametric partially linear models for clustered data. Lin and Carroll derived the semiparametric efficient score function for this problem in the multivariate Gaussian case, but they were unable to construct a semiparametric efficient estimator that actually achieved the semiparametric information bound. Here we propose such an estimator and generalize the work to marginal generalized partially linear models. We investigate asymptotic…