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