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面板数据:固定效应、动态面板、异质性与潜在分组。
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On the use of a working correlation matrix in using generalised linear models for repeated measures

重复测量广义线性模型中工作相关矩阵的使用问题

In a seminal paper Liang & Zeger (1986) extended the use of generalised linear models to repeated measures data. They based the analysis on specifications for the means and variances of the observations, as usual for generalised linear models, but showed how specifications for the correlations between measurements made on the same unit could be avoided by using a ‘working’ correlation matrix. In some cases the parameters involved in this matrix are subject to an uncertainty…

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Projected partial likelihood and its application to longitudinal data

投影偏似然及其在纵向数据中的应用

An estimating equation, which we call the projected partial score, is introduced for longitudinal data analysis. The estimating equation is obtained by projecting the partial likelihood score function onto the vector space spanned by a class of ‘conditionally linear’ estimating equations. We demonstrate that removing certain terms from the projection of the full likelihood score does not alter important inferential properties of the estimating equation, and doing so is…

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Minimum Distance Estimation in Random Coefficient Regression Models

随机系数回归模型中的最小距离估计

Random coefficient regression models are important in modeling heteroscedastic multivariate linear regression in econometrics. The analysis of panel data is one example. In statistics, the random and mixed effects models of ANOVA, deconvolution models and affine mixture models are all special cases of random coefficient regression. Some inferential problems, such as constructing prediction regions for the modeled response, require a good nonparametric estimator of the…

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Modeling Household Purchase Behavior with Logistic Normal Regression

利用逻辑正态回归建模家庭购买行为

The successful development of marketing strategies requires the accurate measurement of household preferences and their reaction to variables such as price and advertising. Manufacturers, for example, often offer products at a reduced price for a limited period. One reason for this practice is that it induces households to try the promoted product with the hope of retaining them as permanent customers. The successful implementation of this strategy requires knowledge of the…

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The Asymptotic Variance of Semiparametric Estimators

半参数估计量的渐近方差

This paper derives a general formula for the asymptotic variance of semiparametric estimators that accounts for the presence of nonparametric estimators of functions. The general formula is specialized to show invariance of the asymptotic variance to the type of nonparametric estimator and to obtain correction terms for estimation of densities and mean-square projections (including conditional expectations). Regularity conditions for the validity of the formula are also…

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Attrition in longitudinal panel data and the empirical analysis of dynamic labour market behaviour

纵向面板数据中的样本流失与动态劳动力市场行为分析

Abstract In the empirical analysis of unemployment durations and job durations, it is generally assumed that the stochastic processes underlying labour market behaviour and the behaviour concerning participation in a panel survey are independent. However, there are reasons to believe that the probability of dropping out of the panel is related to the rate at which a (different) job is found. If there is such a relation, and if it is ignored, then the estimator of the rate at…

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Efficient Semiparametric Estimation in a Stochastic Frontier Model

随机前沿模型中的有效半参数估计

Abstract This article considers the semiparametric stochastic frontier model with panel data that arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered to be unknown. We construct an efficient estimator of the slope parameters in the frontier function. We also give an estimator of the level…

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A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data

应用于面板数据的随机系数 Logit 品牌选择模型

A random-coefficients logit model that allows for unobserved heterogeneity in brand preferences and in the responses to marketing variables is empirically investigated using household-level panel data. The unknown underlying distribution of unobserved heterogeneity is approximated by a discrete distribution. The results reveal that there is significant unobserved heterogeneity across households and that ignoring its effects results in a downward bias in the parameter…

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Conditional Log-Linear Models for Analyzing Categorical Panel Data

分析分类面板数据的条件对数线性模型

Conditional log-linear models are developed for panel data and used to predict sequences of categorical responses. The class of models considered includes conventional Markov models and independence models as well as distance models in which all previous responses and present and past values of covariates are used to predict the current response. The approach taken in this article has some advantages over the marginal modeling approach that has become popular for…

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Simultaneously Modeling Joint and Marginal Distributions of Multivariate Categorical Responses

多元分类响应的联合分布与边际分布同步建模

We discuss model-fitting methods for analyzing simultaneously the joint and marginal distributions of multivariate categorical responses. The models are members of a broad class of generalized logit and loglinear models. We fit them by improving a maximum likelihood algorithm that uses Lagrange's method of undetermined multipliers and a Newton-Raphson iterative scheme. We also discuss goodness-of-fit tests and adjusted residuals, and give asymptotic distributions of model…

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Conditional Log-Linear Models for Analyzing Categorical Panel Data

用于分类面板数据分析的条件对数线性模型

Conditional log-linear models are developed for panel data and used to predict sequences of categorical responses. The class of models considered includes conventional Markov models and independence models as well as distance models in which all previous responses and present and past values of covariates are used to predict the current response. The approach taken in this article has some advantages over the marginal modeling approach that has become popular for…

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Estimating Error Component Models With General MA( q ) Disturbances

具有一般 MA(q) 扰动的误差成分模型估计

This paper provides a simple estimation method for an error component regression model with general MA( q ) remainder disturbances. The estimation method utilizes the transformation derived by Baltagi and Li [3] for an error component model with autoregressive remainder disturbances, and a standard orthogonalizing algorithm for the general MA( q ) model. This estimation method is computationally simple utilizing only least-squares regressions. This is important for panel…

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Estimating the Economic Model of Crime with Panel Data

使用面板数据估计犯罪经济模型

Previous attempts at estimating the economic model of crime with aggregate data relied heavily on cross-section econometric techniques and, therefore, do not control for unobserved heterogeneity. This is even true of studies that estimated simultaneous equations models. Using a new panel data set of North Carolina counties, the authors exploit both single and simultaneous equations panel data estimators to address two sources of endogeneity: unobserved heterogeneity and…

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A simulation estimation analysis of the external debt crises of developing countries

发展中国家外债危机的模拟估计分析

Abstract In this paper we develop models of the incidence and extent of external financing crises of developing countries, which lead to multiperiod multinomial discrete choice and discrete/continuous econometric specifications with flexible correlation structures in the unobservables. We show that estimation of these models based on simulation methods has attractive statistical properties and is computationally tractable. Three such simulation estimation methods are…

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Estimation of a Panel Data Model in the Presence of Correlation Between Regressors and a Two-Way Error Component

解释变量与双向误差分量相关时的面板模型估计

In this paper, we derive an instrumental variables estimator for the generalized Hausman and Taylor [4] model with a two-way error component. We also extend the work of Breusch, Mizon, and Schmidt [2] to this model and derive two additional instrumental variables estimators. Consistency and asymptotic normality of the parameter estimator is demonstrated, allowing both the number of time periods as well as the number of individuals to increase, their ratio bounded. Consistent…

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A Computationally Practical Simulation Estimator for Panel Data

一种计算上可行的面板数据模拟估计量

The author develops a practical extension of D. McFadden's method of simulated moments estimator for limited dependent variable models to the panel data case. The method is based on factorization of the method of simulated moments first order condition into transition probabilities, along with development of an accurate new method for simulating transition probabilities. Monte Carlo tests indicate that this method of simulated moments estimator performs quite well relative…

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Economic fluctuations, market power, and returns to scale: Evidence from firm‐level data

经济波动、市场势力与规模报酬:企业数据证据

Abstract Recent research on aggregate fluctuations, coupled with ongoing work in industrial organization, has renewed interest in the existence, magnitude, and cyclical pattern of market power and the extent of increasing returns to scale. By exploiting restrictions from dynamic theory and information from financial markets, we present a framework for generating quantitative evidence on market power and returns to scale. Tailoring the econometric model to firm‐level panel…

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Logistic regression for autocorrelated data with application to repeated measures

自相关数据的逻辑回归及其重复测量应用

A stochastic model is proposed for the study of the influence of time-dependent covariates on the marginal distribution of the binary response in serially correlated binary data. Markov chains are expressed in terms of transitional rather than marginal probabilities. We show how to construct the model so that the covariates relate only to the mean value of the process, independently of the association parameter. After formulating the stochastic model for a simple sequence of…

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Consumer Purchase Behavior in a Frequently Bought Product Category: Estimation Issues and Managerial Insights from a Hazard Function Model with Heterogeneity

高频购买品类的消费者行为:含异质性的风险率模型

We apply hazard function models to marketing data on household purchases of disposable diapers to calibrate repeat-purchase and brand-switching behaviors. In the model we allow for household-specific unobserved traits. Hazard function models with fixed-effects heterogeneity specification are computationally feasible. We directly compare the results of fixed- and random-effects heterogeneity specifications in the context of parametric and nonparametric duration-dependence…

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Consumer Purchase Behavior in a Frequently Bought Product Category: Estimation Issues and Managerial Insights from a Hazard Function Model with Heterogeneity

高频购买品类的消费者行为:异质性风险函数模型的估计与管理启示

Abstract We apply hazard function models to marketing data on household purchases of disposable diapers to calibrate repeat-purchase and brand-switching behaviors. In the model we allow for household-specific unobserved traits. Hazard function models with fixed-effects heterogeneity specification are computationally feasible. We directly compare the results of fixed- and random-effects heterogeneity specifications in the context of parametric and nonparametric…

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Engel Functions, Panel Data, and Latent Variables

恩格尔函数、面板数据与潜变量

Systems of consumer expenditure functions are estimated from Norwegian household panel data. Total consumption expenditure is modeled as a latent variable, as indicators of it are purchase expenditures on different goods and two income measures. The usual assumption of no measurement error in total expenditure is clearly rejected while a parsimonious alternative is not. The authors test hypotheses regarding the distribution of measurement errors, the evolution of the…

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Modelling Complexity: Applications of Gibbs Sampling in Medicine

复杂模型建模:Gibbs 抽样在医学中的应用

SUMMARY We review applications of Gibbs sampling in medicine, involving longitudinal, spatial, covariate measurement and survival models. Applications in immunology, pharmacology, transplantation, cancer screening, industrial epidemiology and genetic epidemiology are discussed.

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