We analysed the empirical importance of the capital flows in processes of economic convergence of the CEE region. We depart from reference net measures of capital flow reflecting the level of development of the financial system and focus on gross capital flow. Our econometric model is based on Seemingly Unrelated Regression Equation (SURE) elaborated by Arnold Zellner. This environment seems an alternative to standard panel regression, because it enables cross-country heterogeneity of parameters of interest (like pace of convergence). We tested several restrictions of the unconstrained SURE model, leading to simpler specifications that would allow for regional homogeneity of the role of a particular factor (like capital flows) in growth fluctuations and β-type convergence.

The paper is devoted to discussing consequences of the so-called Frisch-Waugh Theorem to posterior inference and Bayesian model comparison. We adopt a generalised normal linear regression framework and weakenits assumptions in order to cover non-normal, jointly elliptical samplingdistributions, autoregressive specifications, additional nuisance parameters andmulti-equation SURE or VAR models. The main result is that inference basedon the original full Bayesian model can be obtained using transformed dataand reduced parameter spaces, provided the prior density for scale or precisionparameters is appropriately modified.