This project is funded by National Science Centre of Poland on the basis of the decision Nr DEC-2013/11/B/HS4/02126 US counties and European NUTS 3 regions in 21 st century – wealth of citizens, convergence processes and spatial dependencies Paweł Folfas Warsaw School of Economics

AIM OF RESEARCH answer question whether absolute income (GDP per capita) beta-convergence exists in the case of regions of the United States (US counties) and of the EU-28 (NUTS 3) during period Samples consist of 3130 US regions (counties) and 1352 regions of the EU (NUTS 3) Forthcoming Transatlantic Trade and Investment Partnership may become a crucial element in the post-crisis world economics and politics. Consequently, it is worth to scrutinize economic performance of the United States and the European Union.

METHODOLOGY (1) MODEL OF ABSOLUTE CONVERGENCE average annual change of GDP per capita (static approach)

METHODOLOGY (2) SPATIAL ECONOMETRICS Ordinary or not-linear last squares (OLS or NLS) methods do not include the possible spatial dependencies between regions Spatial estimation techniques: – Spatial lagged model (SLM) and spatial error model (SEM) – Spatial Durbin model

METHODOLOGY (3) SPATIAL LAGGED MODEL

METHODOLOGY (4) SPATIAL ERROR MODEL

DATA Data concerning GDP per capita of NUTS 3 regions are extracted from Eurostat statistical database Data for US counties from BEA Average number of neighbouring regions: – 5,85 for US counties – 5,13 for EU NUTS 3 regions

ESTIMATIONS RESULTS INTRODUCTION In the case of US regions error model is slightly better than lagged model In the case of EU regions spatial model is slightly better than error model The most adequate, both for US and UE regions, is Durbin spatial model including lagged and error model

ESTIMATION RESULTS (1) SPATIAL LAGGED MODELS USEU Intercept *** *** ln y *** *** ρ *** *** *** denotes statistical significance at level Source: Own study based on estimation in R CRAN beta-convergence at the level of 1.54% (annual speed) much stronger spatial dependencies among EU than US regions

ESTIMATION RESULTS (2) SPATIAL ERROR MODELS USEU Intercept *** *** ln y *** *** ρ *** *** *** denotes statistical significance at level Source: Own study based on estimation in R CRAN beta-convergence at the level of 1.90% (annual speed)

ESTIMATION RESULTS (3) DURBIN MODELS USEU Intercept *** *** ln y *** *** lag ln y *** *** ρ *** *** *** denotes statistical significance at level Source: Own study based on estimation in R CRAN beta-convergence at the level of 1.90% (annual speed) beta-convergence at the level of 1.78% (annual speed) much stronger spatial dependencies among EU than US regions

CONCLUSIONS During period average annual speed of convergence among regions in US was faster than between regions of EU-28. US GDP pc/ EU-28 GDP pc EU-28 regions are characterized by stronger spatial dependencies that regions of the United States