-time dynamic panel relationship between growth rates and initial levels of income as well as endowments of physical, knowledge and … step uses the club assignments in a dynamic space-time panel data model to assess long-run dynamic direct and spillover …

This paper considers a linear panel data model with time varying heterogeneity. Bayesian inference techniques organized …

Recent advances in empirical finance has shown that the adoption of network theory is critical to understand contagion … review networks, however, they do not focus on the econometrics aspects. This paper presents a state-of-the-art review on the … interface between statistics and econometrics in the inference and application of Bayesian graphical models. We specifically …

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our …

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a …

We apply a heterogenous coefficient spatial autoregressive panel model from Aquaro, Bailey and Pesaran (2015) to … likelihood estimation method set forth by Aquaro, Bailey and Pesaran (2015), we rely on a Markov Chain Monte Carlo (MCMC …) estimation methodology. MCMC estimates as applied here with non-informative priors will produce estimates equal to those from …

relationships involving spatial data samples is the broad topic covered by spatial econometrics. Like any sub-discipline, spatial … econometrics has its quirks, many of which reflect influential past literature that has gained attention in both theoretical and …

estimation can be achieved by controlling for both phenomena. -- Spatial econometrics ; Bayesian spatial econometrics ; Spatial … for spatial heterogeneity. In particular, Bayesian and Maximum-Likelihood (ML) estimation methods are employed for model …

leverage. For parameter estimation, we develop efficient Markov chain Monte Carlo algorithms and illustrate our methods, using …