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Admission, Tuition, and Financial Aid Policies in the Market for Higher Education

高等教育市场中的招生、学费与经济资助政策

We present an equilibrium model of the market for higher education. Our model simultaneously predicts student selection into institutions of higher education, financial aid, educational expenditures, and educational outcomes. We show that the model gives rise to a strict hierarchy of colleges that differ by the educational quality provided to the students. We also develop a new estimation procedure that exploits the observed variation in prices within colleges.…

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Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure

具有多因子误差结构的大规模异质面板:估计与推断

This paper presents a new approach to estimation and inference in panel data models with a general multifactor error structure. The unobserved factors and the individual-specific errors are allowed to follow arbitrary stationary processes, and the number of unobserved factors need not be estimated. The basic idea is to filter the individual-specific regressors by means of cross-section averages such that asymptotically as the cross-section dimension (N) tends to infinity,…

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The Identification of Fixed Costs From Consumer Behavior

从消费者行为识别固定成本

Some household expenditures, such as those for subsistence or basic needs, are fixed. Using the methodology of equivalence scales, we develop a model in which differences in fixed costs of characteristics across households can be identified from household behavior. Equivalent expenditure for a household is the expenditure needed to bring a reference household, such as a single childless adult, to the level of well-being of household members. The equivalence scale for the…

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Distributional Dominance With Trimmed Data

修剪数据下的分布支配

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We examine a nonparametric approach to refining Lorenz-type comparisons and apply the technique to two important examples from the Luxembourg Income Study database.

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Inference in dynamic stochastic frontier models

动态随机前沿模型中的推断

Abstract An important issue in models of technical efficiency measurement concerns the temporal behaviour of inefficiency. Consideration of dynamic models is necessary but inference in such models is complicated. In this paper we propose a stochastic frontier model that allows for technical inefficiency effects and dynamic technical inefficiency, and use Bayesian inference procedures organized around data augmentation techniques to provide inferences. Also provided are…

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Modelling firm‐size distribution using Box–Cox heteroscedastic regression

利用 Box–Cox 异方差回归建模企业规模分布

Abstract Using the Box–Cox regression model with heteroscedasticity (BCHR), we re‐examine the size distribution of the Portuguese manufacturing firms studied by Machado and Mata ( 2000 ) using the Box–Cox quantile regression (BCQR) method. We show that the BCHR model compares favourably against the BCQR method. In particular, the BCHR model can answer the key questions addressed by the BCQR method, with the advantage that the estimated quantile functions are monotonic.…

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Conditional Inference Methods for Incomplete Poisson Data With Endogenous Time-Varying Covariates

含内生时变协变量的不完整泊松数据的条件推断方法

We investigate the effect of protease inhibitors (PIs) on the rate of emergency room (ER) visits among HIV-infected women from a longitudinal cohort study. One strategy for accounting for serial correlation in longitudinal studies is to assume that observations are independent, conditional on unit-specific nuisance parameters. It is possible to estimate these models using unconditional maximum likelihood, where the nuisance parameters are assigned a parametric distribution…

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How Many People Do You Know in Prison?

你认识多少在监狱中的人?

Networks—sets of objects connected by relationships—are important in a number of fields. The study of networks has long been central to sociology, where researchers have attempted to understand the causes and consequences of the structure of relationships in large groups of people. Using insight from previous network research, Killworth et al. and McCarty et al. have developed and evaluated a method for estimating the sizes of hard-to-count populations using network data…

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Analysis of Failure Time Data Arising From Studies With Alternating Treatment Schedules

交替治疗安排研究中的失效时间数据分析

We develop statistical methods for designing and analyzing studies in which treatments are deliberately interrupted and reinitiated, but where interest lies in making inferences about continuous treatment use. We refer to such designs as alternating designs, because subjects alternate between periods in which they are taking the treatment of interest and periods when they are not. Our goals are to determine how to estimate the distribution of time to an event if the…

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Inference in Semiparametric Dynamic Models for Binary Longitudinal Data

二元纵向数据半参数动态模型的推断

This article deals with the analysis of a hierarchical semiparametric model for dynamic binary longitudinal responses. The main complicating components of the model are an unknown covariate function and serial correlation in the errors. Existing estimation methods for models with these features are of O(N3), where N is the total number of observations in the sample. Therefore, nonparametric estimation is largely infeasible when the sample size is large, as in typical in the…

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Assessing Evidence Inconsistency in Mixed Treatment Comparisons

混合治疗比较中的证据不一致性评估

Randomized comparisons among several treatments give rise to an incomplete-blocks structure known as mixed treatment comparisons (MTCs). To analyze such data structures, it is crucial to assess whether the disparate evidence sources provide consistent information about the treatment contrasts. In this article we propose a general method for assessing evidence inconsistency in the framework of Bayesian hierarchical models. We begin with the distinction between basic…

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Fitting binary regression models with case-augmented samples

病例增补样本下的二元回归模型拟合

In a case-augmented study, measurements on a random sample from a population are augmented by information from an independent sample of cases, that is units with some characteristic of interest. We show that inferences about the effect of the covariates on the probability of being a case can be made by fitting a modified prospective likelihood. We also show that this procedure is fully efficient.

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Estimating the quality-of-life-adjusted gap time distribution of successive events subject to censoring

删失下连续事件生活质量调整间隔时间分布的估计

When treatment effects are studied in the context of successive or recurrent life events, separate analyses of the quality-of-life scores and of the inter-event, gap, times might lead to possibly contradictory conclusions. In an attempt to reconcile this, we propose a unitary and more comprehensive nonparametric analysis that combines the two separate analyses by introducing the quality-of-life-adjusted gap time concept. Inverse probability of censoring estimators of the…

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M-quantile models for small area estimation

用于小区域估计的 M 分位数模型

Small area estimation techniques typically rely on regression models that use both covariates and random effects to explain variation between the areas. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier-robust inference. We describe a new approach to small area estimation that is based on modelling quantilelike parameters of the conditional distribution of…

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Rank-based regression for analysis of repeated measures

重复测量分析中的秩回归

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of…

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Testing for Order-Restricted Hypotheses in Longitudinal Data

纵向数据中次序约束假设的检验

Summary In many biomedical studies, we are interested in comparing treatment effects with an inherent ordering. We propose a quadratic score test (QST) based on a quadratic inference function for detecting an order in treatment effects for correlated data. The quadratic inference function is similar to the negative of a log-likelihood, and it provides test statistics in the spirit of a χ2-test for testing nested hypotheses as well as for assessing the goodness of fit of…

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Properties of principal component methods for functional and longitudinal data analysis

函数型与纵向数据分析中主成分方法的性质

The use of principal component methods to analyze functional data is appropriate in a wide range of different settings. In studies of “functional data analysis,” it has often been assumed that a sample of random functions is observed precisely, in the continuum and without noise. While this has been the traditional setting for functional data analysis, in the context of longitudinal data analysis a random function typically represents a patient, or subject, who is observed…

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The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models

动态反馈对面板模型 LS 与矩估计精度的影响

The finite sample behaviour is analysed of particular least squares (LS) and a range of (generalized) method of moments (MM) estimators in panel data models with individual effects and both a lagged dependent variable regressor and another explanatory variable. The latter may be affected by lagged feedbacks from the de- pendent variable too. Asymptotic expansions indicate how the order of magnitude of bias of MM estimators tends to increase with the number of moment condi-…

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REDUCING BIAS OF MLE IN A DYNAMIC PANEL MODEL

动态面板模型中极大似然估计的偏差削减

This paper investigates a simple dynamic linear panel regression model with both fixed effects and time effects. Using “large n and large T” asymptotics, we approximate the distribution of the fixed effect estimator of the autoregressive parameter in the dynamic linear panel model and derive its asymptotic bias. We find that the same higher order bias correction approach proposed by Hahn and Kuersteiner (2002, Econometrica 70, 1639–1659) can be applied to the dynamic linear…

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Smart Cities: Quality of Life, Productivity, and the Growth Effects of Human Capital

智慧城市:生活质量、生产率与人力资本的增长效应

From 1940 to 1990, a 10% increase in a metropolitan area's concentration of college-educated residents was associated with a 0.8% increase in subsequent employment growth. Instrumental variables estimates support a causal relationship between college graduates and employment growth, but show no evidence of an effect of high school graduates. Using data on growth in wages, rents, and house values, I calibrate a neoclassical city growth model and find that roughly 60% of the…

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Bounds on Parameters in Panel Dynamic Discrete Choice Models

动态面板离散选择模型的参数界

Identification of dynamic nonlinear panel data models is an important and delicate problem in econometrics. In this paper we provide insights that shed light on the identification of parameters of some commonly used models. Using these insights, we are able to show through simple calculations that point identification often fails in these models. On the other hand, these calculations also suggest that the model restricts the parameter to lie in a region that is very small in…

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Estimating an economic model of crime using panel data from North Carolina

利用北卡罗来纳州面板数据估计犯罪经济模型

Abstract This paper replicates the Cornwell and Trumbull ( 1994 ) estimation of a crime model using panel data on 90 counties in North Carolina over the period 1981–1987. While the Between and Within estimates are replicated, the fixed effects 2SLS as well as the 2SLS estimates are not. In fact, the fixed effects 2SLS estimates turn out to be insignificant for all important deterrent variables as well as legal opportunity variables. We argue that the usual Hausman test,…

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Likelihood Inference for a Class of Latent Markov Models under Linear Hypotheses on the Transition Probabilities

潜在马尔可夫模型转移概率线性假设的似然推断

Summary For a class of latent Markov models for discrete variables having a longitudinal structure, we introduce an approach for formulating and testing linear hypotheses on the transition probabilities of the latent process. For the maximum likelihood estimation of a latent Markov model under hypotheses of this type, we outline an EM algorithm that is based on well-known recursions in the hidden Markov literature. We also show that, under certain assumptions, the asymptotic…

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