Integration, Regional Specialization and Growth Differentials in EU Acceding Countries
activity and that agglomeration and growth reinforce each other leading to increased
regional disparities.
The theoretical models reviewed above make different predictions with respect
to the impact of economic integration on regional growth differentials. Neo-classical
trade and growth models point to increasing specialization, factor price equalization and
convergence of income per capita in the long term in the integrating countries and
regions. New growth models and new economic geography models emphasize
endogenous processes of factor accumulation, increasing returns to scale, and
agglomeration economies that can foster divergence patterns in the context of economic
integration. Understanding the nature of the relationship between openness and growth
is therefore an empirical question. As pointed out by Solow (2000) and Srinivasan /
Bhagwati (2001) the best approach in this respect is to look at country experiences.
In this paper, we look at the case of Hungary during a period of increased
openness, 1994-2000 and focus on the role of knowledge spillovers - proxy ed with a
measure for regional FDI intensity - and regional manufacturing specialization as
driving forces for regional growth differentials.
3 Data and measurement
We use a unique data set REGSTAT4 containing, regional indicators at the NUTS 3
level over the period 1990-2000. For the purpose of our analysis, we use the following
regional data for 20 NUTS 3 regions in Hungary over the period 1994 - 20005: sectoral
employment (in agriculture, industry and services), regional manufacturing employment
(disaggregated on eight branches6), population data, Gross Domestic Product (GDP),
and the number of firms with foreign capital participation.
In order to capture the role of geography in explaining patterns of disparities and
convergence in regional growth, we use a taxonomy of regions proposed by Resmini
(2002) which takes into account the geographical position of regions. Thus, we group
4 REGSTAT data set was generated in the framework of the project P98-1117-R undertaken with
financial support from the European Community’s PHARE ACE Programme. The data set includes
regional indicators at NUTS 2 and NUTS 3 levels for Bulgaria, Estonia, Hungary, Romania and
Slovenia
5 We decide to focus on this period which coincides with increased market integration with the EU via
the Europe Agreement, entered into force in 1994.
6 The manufacturing branches are: food, beverages, and tobacco; textiles, apparel and leather; wood,
paper and printing; chemicals; no-metallic mineral products; metallurgy and metal products;
machinery and equipment; other manufacturing.