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Bayesian modelling of panel data with individual effects applied to simulated data

TLDR
It is concluded that bayesian panel data analysis is of interest if data do not provide enough information and if adequate extraneous information is available.
Abstract
To understand the potentials of bayesian panel data analysis, simulated data are used to estimate a random effects model. Prior Gaussian distributions of various precision are used to understand the influence of the prior information on continuous, discrete, time varying and time constant variables. It is demonstrated that parameters of dummy variables are far more sensitive to priors than parameters of continuous variables. Time varying variables are less sensitive than their time constant counterparts. It is concluded that bayesian panel data analysis is of interest if data do not provide enough information and if adequate extraneous information is available.

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A Bayesian analysis of the impact of post-crash care on road mortality in Sub-Saharan African countries

TL;DR: A negative correlation between the road mortality rate and the estimated share of seriously injured transported by ambulance, the emergency access telephone services and the emergency training for doctors and nurses is suggested.
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Bayesian Inference for Censored Panel Regression Model

TL;DR: In this article, the authors examined the behavior of the maximum likelihood and Bayesian estimators of disturbance variance in a censored panel regression model with a limited dependent variable, which is known to have the incidental parameter problem.
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Designing of research coalitions in promoting GEOSS. A brief overview of the literature

TL;DR: In this paper, the authors apply a game theoretical approach to analyze the Global Earth Observation System of Systems (GEOSS) as a research coalition with varying spillover rates, in order to figure out whether a coalition with full participation can exist in equilibrium.
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The Relationship between Infant Mortality Rate and Health Expenditure in India: A Bayesian Approach

TL;DR: In this paper, a Bayesian approach is used to fit a linear regression analysis to panel data to investigate the relationship between state health expenditure and Infant Mortality Rate in Indian states.
References
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Book

Bayesian Data Analysis

TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Journal ArticleDOI

Bayesian measures of model complexity and fit

TL;DR: In this paper, the authors consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined and derive a measure pD for the effective number in a model as the difference between the posterior mean of the deviances and the deviance at the posterior means of the parameters of interest, which is related to other information criteria and has an approximate decision theoretic justification.
Book

Econometric Analysis of Panel Data

TL;DR: In this article, the authors proposed a two-way error component regression model for estimating the likelihood of a particular item in a set of data points in a single-dimensional graph.
Journal ArticleDOI

Panel data and unobservable individual effects

TL;DR: In this article, the authors derived a test for the presence of this effect and for the over-identifying restriction they use; necessary and sufficient conditions for identification of all the parameters in the model; and the asymptotically efficient instrumental variables estimator and conditions under which it differs from the within-groups estimator.
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