Agro-Food Export Competitiveness of the European Union Countries on the World Markets Imre Fertő and Štefan Bojnec.

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Presentation transcript:

Agro-Food Export Competitiveness of the European Union Countries on the World Markets Imre Fertő and Štefan Bojnec

Department of Agricultural Economics Outline  Motivation  Theoretical background  Methodological issues  Data and methodology  Results  Conclusions

Department of Agricultural Economics Motivation  COMPETE FP7 Project  Declining competitveness of the EU agriculture –e.g. Ball et al. 2010, EC 2007, FoodDrinkEurope 2011  Investigate the export performance using standard empirical trade analysis tools

Department of Agricultural Economics Dynamics of trade specialisation  HOS model –Trade pattern is stable over time except random shock in relative factor endowments  New trade theory 1. –Grossman and Helpman ( ): long run trade pattern only depends on the relative factors endowments  New trade theory 2 –Krugman (1987) and Lucas (1988): international trade patterns tend to be more specialised  Implications (Proudman –Redding (2000): –The dynamics of trade specialization is an empirical question

Department of Agricultural Economics Previous research  Fertő 2008  Bojnec and Fertő (2008, 2009, 2010, 2011, 2012)  Török and Jámbor (2013)

Department of Agricultural Economics Measuring comparative advantage  Balassa index  B = (Xij / Xit) / (Xnj / Xnt) –X export – i product –j country – total export – n set of countries: world market –B>1. revealed comparative advantage

Department of Agricultural Economics Methodology  Descriptive statistics  Impact of the EU enlargement in 2004 –Chow tests  Convergency: –Panel unit root tests  Stability of B indices at product level –Markov matrices plus mobility indices –Survival analysis

Department of Agricultural Economics Data  Country coverage: EU27  Period:  Trade data –Comtrade-WITS. HS6. –Agri-food trade defined by the WTO –789 product groups

Department of Agricultural Economics

Descriptive Statistics of the B Indices NMeanSt. Dev.minmaxmedian Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxemburg Netherlands Portugal Spain Sweden UK

Department of Agricultural Economics Descriptive Statistics of the B Indices NMeanSt. Dev.minmaxmedian Bulgaria Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Romania Slovakia Slovenia EU EU EU

Department of Agricultural Economics Changes B indices between 2000 and 2011 MeanMedianShare B> Austria %22.8% Belgium %38.9% Denmark %30.9% Finland %12.3% France %43.5% Germany %27.9% Greece %28.4% Ireland %22.9% Italy %30.2% Luxemburg %13.8% Netherlands %55.7% Portugal %28.2% Spain %44.8% Sweden %11.9% UK %22.8%

Department of Agricultural Economics Changes B indices between 2000 and 2011 MeanMedianShare B> Bulgaria %31.3% Cyprus %34.4% Czech Republic %16.0% Estonia %23.2% Hungary %29.5% Latvia %34.6% Lithuania %38.5% Malta %9.2% Poland %33.9% Romania %13.9% Slovakia %18.2% Slovenia %12.0% EU %27.0% EU %29.0% EU %24.6%

Department of Agricultural Economics The impact of the EU enlargement in 2004 Chow test 1Chow test 2Chow test 3 Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxemburg Netherlands Portugal Spain Sweden UK

Department of Agricultural Economics The impact of the EU enlargement in 2004 Chow test 1Chow test 2Chow test 3 Bulgaria Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Romania Slovakia Slovenia

Department of Agricultural Economics Panel unit root tests without trendwith trend IPSADFPPIPSADFPP Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxemburg Netherlands Portugal Spain Sweden UK

Department of Agricultural Economics Panel unit root tests without trendwith trend IPSADFPPIPSADFPP Bulgaria Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Romania Slovakia Slovenia

Department of Agricultural Economics Markov matrix of the EU27 B<1 B>1Total B< B> Total

Department of Agricultural Economics Mobility of B indices M1 Austria0.1502Bulgaria Belgium0.1276Cyprus Denmark0.1232Czech Republic Finland0.0987Estonia France0.1138Hungary Germany0.1099Latvia Greece0.2216Lithuania Ireland0.182Malta Italy0.1201Poland Luxemburg0.1617Romania Netherlands0.1607Slovakia Portugal0.1798Slovenia Spain0.1396EU Sweden0.1682EU UK0.1517EU

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Duration of revealed comparative advantages

Department of Agricultural Economics Histogram of spells

Department of Agricultural Economics Spells of the B>1 1 spells2 spells3 spells4 spells5 spells6 spellstotal spellsmultiple spellsmeanmedian Austria Belgium Bulgaria Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxemburg Malta Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden United Kingdom

Department of Agricultural Economics Kaplan-Meier survival rates 1 year4 year8 year12 year Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxemburg Netherlands Portugal Spain Sweden UK

Department of Agricultural Economics Kaplan-Meier survival rates 1 year4 year8 year12 year Bulgaria Cyprus Czech Republic Estonia Hungary Latvia Lithuania Malta Poland Romania Slovakia Slovenia EU EU EU

Department of Agricultural Economics Conclusions  Mean export growth rate is higher in NMS than OMS  Impact of EU enlargement is restricted to only 5 of 27 countries  Convergency in comparative advantage  Trade pattern is more mobile in NMS than OMS  Duration of comparative advantage is higher in NMS than OMS