Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data
نویسندگان
چکیده
منابع مشابه
Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data*
T his article challenges Fixed Effects (FE) modeling as the ‘default’ for time-series-crosssectional and panel data. Understanding different within and between effects is crucial when choosing modeling strategies. The downside of Random Effects (RE) modeling— correlated lower-level covariates and higher-level residuals—is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Conse...
متن کاملSemiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence Jia Chen and Jiti Gao Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence
In this paper, we consider a model selection issue in semiparametric panel data models with fixed effects. The modelling framework under investigation can accommodate both nonlinear deterministic trends and cross-sectional dependence. And we consider the so-called “large panels” where both the time series and cross sectional sizes are very large. A penalised profile least squares method with fi...
متن کاملJoint Modeling of Dynamic and Cross-Sectional Heterogeneity: Introducing Hidden Markov Panel Models
Researchers working with panel data sets often face situations where changes in unobserved factors have produced changes in the cross-sectional heterogeneity across time periods. Unfortunately, conventional statistical methods for panel data are based on the assumption that the unobserved cross-sectional heterogeneity is time constant. In this paper, I introduce statistical methods to diagnose ...
متن کاملModelling discrete valued cross sectional time series with observation driven models
This paper develops computationally feasible methods for estimating random effects models in the context of regression modelling of multiple independent time series of discrete valued counts in which there is serial dependence. Given covariates, random effects and process history, the observed responses at each time in each series are independent and have an exponential family distribution. We ...
متن کاملQML Estimation of Dynamic Panel Data Models with Spatial Errors
We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap met...
متن کامل