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Influence Diagnostics and Outlier Tests for Semiparametric Mixed Models

半参数混合模型的影响诊断与异常值检验

Summary Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric…

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Youth Labor Markets in the United States: Shopping Around vs. Staying Put

美国青年劳动力市场:频繁换工作还是保持稳定

The need for school-to-work programs or other means of increasing early job market stability is predicated on the view that the "chaotic" nature of youth labor markets in the United States is costly because workers drift from one job to another without developing skills, behavior, or other characteristics that in turn lead to higher adult earnings. However, there is also ample evidence that workers receive positive returns to job shopping. This paper asks whether youths in…

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Orthogonal Parameters and Panel Data

正交参数与面板数据

This paper describes a class of consistent estimators for short panels with fixed effects. The method is to find an orthogonal reparametrization of the fixed effects and then to integrate the new effects from the likelihood with respect to an appropriately chosen prior density. The resulting marginal posterior densities of the common parameters have modes that are shown to be consistent in the models examined here. The main result concerns the first-order autoregressive…

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Inference on the Quantile Regression Process

分位数回归过程的统计推断

Abstract. Tests based on the quantile regression process can be formulated like the classical Kolmogorov-Smirnov and Cramer-von-Mises tests of goodness-of-t employing the theory of Bessel processes as in Kiefer (1959). However, it is fre-quently desirable to formulate hypotheses involving unknown nuisance parameters, thereby jeopardizing the distribution free character of these tests. We characterize this situation as \\the Durbin problem " since it was posed in Durbin…

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Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models

交换嵌套不动点算法:离散马尔可夫决策模型的一类估计量

This paper proposes a procedure for the estimation of discrete Markov decision models and studies its statistical and computational properties.Our Nested Pseudo-Likelihood method (NPL) is similar to Rust's Nested Fixed Point algorithm (NFXP), but the order of the two nested algorithms is swapped.First, we prove that NPL produces the Maximum Likelihood Estimator under the same conditions as NFXP.Our procedure requires fewer policy iterations at the expense of more…

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Reanalyzing Ultimatum Bargaining—Comparing Nondecreasing Curves Without Shape Constraints

重新分析最后通牒议价:无形状约束下的非递减曲线比较

We employ a hierarchical Bayesian method with exchangeable prior distributions to estimate and compare similar nondecreasing response curves. A Dirichlet process distribution is assigned to each of the response curves as a first stage prior. A second stage prior is then used to model the hyperparameters. We define parameters which will be used to compare the response curves. A Markov chain Monte Carlo method is applied to compute the resulting Bayesian estimates. To…

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Socio‐economic distance and spatial patterns in unemployment

社会经济距离与失业的空间分布模式

Abstract This paper examines the spatial patterns of unemployment in Chicago between 1980 and 1990. We study unemployment clustering with respect to different social and economic distance metrics that reflect the structure of agents' social networks. Specifically, we use physical distance, travel time, and differences in ethnic and occupational distribution between locations. Our goal is to determine whether our estimates of spatial dependence are consistent with models in…

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Geographic poverty traps? A micro model of consumption growth in rural China

地理贫困陷阱?中国农村消费增长的微观模型

Abstract How important are neighbourhood endowments of physical and human capital in explaining diverging fortunes over time for otherwise identical households in a developing rural economy? To answer this question we develop an estimable micro model of consumption growth allowing for constraints on factor mobility and externalities, whereby geographic capital can influence the productivity of a household's own capital. Our statistical test has considerable power in…

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Alcohol abuse and employment: a second look

酒精滥用与就业:重新考察

Abstract Based on data from the 1988 Alcohol Supplement of the National Health Interview Survey, Mullahy and Sindelar ( 1996 ) (M&S) find, for both men and women, that alcohol abuse results in reduced employment and increased unemployment. The estimates from which they drew these inferences were obtained via the instrumental variables (IV) method, which was implemented in order to account for the potential endogeneity of problem drinking. Though these IV estimates…

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Analysing longitudinal count data with overdispersion

过度离散纵向计数数据的分析

In many biomedical studies, longitudinal count data comprise repeated responses and a set of multidimensional covariates for a large number of individuals. When the response variable in such models is subject to overdispersion, the overdispersion parameter influences the marginal variance. In such cases, the overdispersion parameter plays a significant role in efficient estimation of the regression parameters. This raises the need for joint estimation of the regression…

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Multiple-Output Production With Undesirable Outputs

含非期望产出的多产出生产模型

Many production processes yield both good outputs and undesirable ones (e.g., pollutants). In this article we develop a generalization of a stochastic frontier model that is appropriate for such technologies. We discuss efficiency analysis and, in particular, define technical and environmental efficiency in the context of our model. We develop methods for carrying out Bayesian inference and apply them to a panel data set of Dutch dairy farms, where excess nitrogen production…

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Marginal Longitudinal Nonparametric Regression

纵向边际模型中的非参数回归

We consider nonparametric regression in a longitudinal marginal model of generalized estimating equation (GEE) type with a time-varying covariate in the situation where the number of observations per subject is finite and the number of subjects is large. In such models, the basic shape of the regression function is affected only by the covariate values and not otherwise by the ordering of the observations. Two methods of estimating the nonparametric function can be…

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The Effect of Duration and Delay of Licensure on Risk of Crash

持照时长与延迟取证对交通事故风险的影响

The driving history records of a sample of 13,794 Michigan public school students were followed for up to 13 years from their initial time-of-license to determine the separate effects of duration of licensure and delay of licensure on risk of crash. We propose a subject-specific lognormal accelerated failure time to model the expected time-to-crash as a function of age at time of licensure, duration of licensure, and a set of control covariates. When multiple time-to-crash…

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Spatial Price Competition: A Semiparametric Approach

We investigate the nature of price competition among firms that produce differentiated products and compete in markets that are limited in extent. We propose an instrumental variables series estimator for the matrix of cross price response coefficients, demonstrate that our estimator is consistent, and derive its asymptotic distribution. Our semiparametric approach allows us to discriminate among models of global competition, in which all products compete with all others,…

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Learning and communication in sender‐receiver games: an econometric investigation

发送者—接收者博弈中的学习与沟通:计量研究

Abstract This paper compares stimulus response (SR) and belief‐based learning (BBL) using data from experiments with sender–receiver games. The environment, extensive form games played in a population setting, is novel in the empirical literature on learning in games. Both the SR and BBL models fit the data reasonably well in games where the preferences of senders and receivers are perfectly aligned and where the population history of the senders is known. The test results…

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Estimating Lorenz Curves Using a Dirichlet Distribution

利用 Dirichlet 分布估计洛伦兹曲线

The Lorenz curve relates the cumulative proportion of income to the cumulative proportion of population. When a particular functional form of the Lorenz curve is specified, it is typically estimated by linear or nonlinear least squares estimation techniques that have good properties when the error terms are independently and normally distributed. Observations on cumulative proportions are clearly neither independent nor normally distributed. This article proposes and applies…

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NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA

聚合数据下的非参数估计

We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intrafamily component but require that observations from different families be independent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behavior of the characteristic function at infinity. We investigate the practical…

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CONSISTENCY AND EFFICIENCY OF LEAST SQUARES ESTIMATION FOR MIXED REGRESSIVE, SPATIAL AUTOREGRESSIVE MODELS

混合回归与空间自回归模型中最小二乘的一致性和效率

Least squares estimation has casually been dismissed as an inconsistent estimation method for mixed regressive, spatial autoregressive models with or without spatial correlated disturbances. Although this statement is correct for a wide class of models, we show that, in economic spatial environments where each unit can be influenced aggregately by a significant portion of units in the population, least squares estimators can be consistent. Indeed, they can even be…

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A semiparametric pseudolikelihood estimation method for panel count data

面板计数数据的半参数伪似然估计方法

In this paper, we study panel count data with covariates. A semiparametric pseudolikelihood estimation method is proposed based on the assumption that, given a covariate vector Z, the underlying counting process is a nonhomogeneous Poisson process with the conditional mean function given by E{N (t) |Z} = Λ0 (t) exp (β′0Z). The proposed estimation method is shown to be robust in the sense that the estimator converges to its true value regardless of whether or not N (t) is a…

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Varying-coefficient models and basis function approximations for the analysis of repeated measurements

重复测量分析中的变系数模型与基函数近似

A global smoothing procedure is developed using basis function approximations for estimating the parameters of a varying‐coefficient model with repeated measurements. Inference procedures based on a resampling subject bootstrap are proposed to construct confidence regions and to perform hypothesis testing. Conditional biases and variances of our estimators and their asymptotic consistency are developed explicitly. Finite sample properties of our procedures are investigated…

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