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The Impact of the Eastern European Enlargement on the Prosperity of the Old Member States Agricultural Export Sectors A comparative assessment of the French, German and Italian agricultural export developments towards the new eastern member states and of their effects on the respective revealed comparative advantage positions

Master thesis presentation

at AFEPA summer school 2013Weinbrenner TimoSupervisor: Prof. Dr. Fert ImreSzervezeti egysgPresentation OutlineMotivation of the study and research question

Research objectives and indicators

Analytical method

Descriptive and analytical results

Summary and Conclusion22013.08.08.Weinbrenner TimoSzervezeti egysg2(1)Motivation and research question32013.08.08.Weinbrenner TimoLiterature shows that the Central and Eastern European Countries (CEECs) benefitted from their EU-accessions in the form of welfare gains, while the EU-enlargement implied a moderate welfare decrease for the old member states (OMS).The thesis singles the OMS agricultural sectors out and assesses the impact of the EU-enlargement on them specifically.

Motivation

Research questionEU-enlargement consequencesWhat overall economic effect did the three changes in the business environment have on the OMS agricultural sectors?Consequences for the business environment of the agricultural producers in the OMS:

Szervezeti egysg3(2)Research Objectives and Indicators42013.08.08.Weinbrenner TimoNo.ObjectiveIndicator1Changes in quantitative trade dynamicsDisaggregated exports in value from OMS towards NMS2NMSs significance as export marketsShare of exports towards the NMS in the OMS total exports.3Change in trade patternExports in value by product category (degree of processing)Lawrence Index (trade pattern analysis tool)Krugman Index (trade pattern analysis tool)Annual mean deviation of export data(distribution divergence analysis)4Impact on revealed comparative advantage (RCA) positionNormalized Revealed Comparative Advantage Index. (NRCA Index)Annual mean deviation of NRCA Index (distributional divergence analysis5Greatest beneficiary among the OMSComparative analysis of the individual reporters results.Data specification of basis for all indicatorsData and data sourceExports in value; OECD iLibrary data baseRepresentatives for OMS(Reporters)France, Germany and ItalyNMS in eastern EuropeEstonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Slovenia, Hungary, Romania, and BulgariaAssessment period1999 to 2011Analyzed trade items543 agricultural products (all agricultural entries in SITC-5)Product categories(differentiated by degree of processing and input-intensity)1 raw commodities2 processed intermediate goods3 consumer-ready food4 horticultural products}Chen categories=Data panel with 7059 observations (13 temporal observations for each of the 543 products)

Szervezeti egysg4(2)Explanation of indicators; Lawrence and Krugman Indices52013.08.08.Weinbrenner TimoInterpretationLawrence IndexKrugman IndexRange0 10 1BehaviorIncreasing with structural transformationIncreasing with structural dissimilarity IndexAssessment ObjectiveLawrenceStructural transformation in the trade pattern of the reporter within a predefined period.KrugmanTrade pattern similarity of the reporters trade towards a predefined trading partner compared to the reporters world export pattern at one point in time.

Formulas: Lawrence KrugmanWhere and r represent the reporters share of product j in its exports towards a predefined trading partner i and towards the world at time t respectively and is assumed to equal 0.5

Szervezeti egysg5Where Eijdenotes the export value of country i for commodity jEidenotes total export value (of all j) of country iEREFjdenotes the export value of commodity j of the group of reference countriesEREFdenotes the total export value (of all j) of the group of reference countries(2)Explanation of indicators; NRCA Index62013.08.08.Weinbrenner Timo

Interpretation:NRCA valueInterpretation= 0Country i exports product j at the comparative-neutral level> 0Country i exhibits a comparative (export) advantage in product j< 0Country i exhibits a comparative (export) disadvantage in product jRange-2500 to 2500 (after multiplication of all index values by 10,000 for a more convenient presentation) Szervezeti egysg6(3)Analytical Method to analyze the indicators72013.08.08.Weinbrenner Timo 123Descriptive analysis

Time series regression model to test for structural breaks:Change in mean value after 2004Change in trade growth rate after 2004Panel Unit Root Test for Distributional Divergence:

Panel Unit Root Tests are performed on the mean deviations of the export in value data from the OMS to the NMS.A confirmed Unit Root would indicate distributional divergence over the assessment periodWald test for joint probability: c(3) = 0; c(4) = 0Szervezeti egysg7(4) Results1. Trade QuantitiesFranceGermanyItalyc(1)c(2)c(3)c(4)c(1)c(2)c(3)c(4)c(1)c(2)c(3)c(4)Regression results607,539 0.51 10,348 0.31 1,971,922 0.69 58,550 0.29 872,661 0.51 10,787 0.37 (0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)Wald testSignificantSignificantSignificantc(3)/c(1)1.7%3.0%1.2%Total agricultural exports from the OMS towards the CEEC country aggregate:2013.08.08.8Weinbrenner TimoRegression results:Szervezeti egysgEmphasize absolute and relative changes. Absolute: 1.6, 9.9, 2.6 Relative (multiplier): 6.3, 6.8, 6.2Positive EU-Enlargement effect detected8(4) Results2. NMS as export markets2013.08.08.9Weinbrenner TimoProportion of the reporters world exports directed towards the CEEC region (export shares):FranceGermanyItalyc(1)c(2)c(3)c(4)c(1)c(2)c(3)c(4)c(1)c(2)c(3)c(4)Regression results1.3E-050.549.9E-080.174.0E-050.738.8E-070.103.7E-050.543.3E-070.18 (0.00)(0.00) (0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00)(0.00) (0.00)(0.00)Wald testSignificantSignificantSignificantc(3)/c(1)0.8%2.2%0.9%Regression results:Szervezeti egysgEmphasize absolute and relative changes. Absolute: 1.66%age points, 6.99, 4.24 Relative (multiplier) : 2.84, 2.14, 2.07Extent of EU-enlargement effect noteworthy!!Positive EU-Enlargement effect detected9(4) Results3. Trade Pattern2013.08.08.10Weinbrenner TimoTrade pattern = the composition of the export flow of a reporting countryDistributional DivergenceKrugman average annual changeLawrence1999-20081999-20032004-2008France0.370.310.25Germany0.420.230.27Italy0.290.220.22Above-average transformation rate;No EU-enlargement effect detectable2000-20042005-2009France-0.005-0.010Germany-0.018-0.008Italy-0.006-0.011Continuous adaptation;Difference apparent, but inconsistentAnnual Mean Deviations:

Unit Root is accepted for France, Germany and Italy at 1% levelDivergence in export flows confirmedInitial ranking of Chen categories systematically reinforced (in absolute and relative terms):Consumer-ready foodProcessed intermediate goodsRaw commoditiesHorticultural products

But: for Italy Horticultural products is the second most important category.Agri-exports towards the NMS, in million USDChen categories as division key:Szervezeti egysga trade pattern specifies how the total agricultural exports of a reporter country are distributed over the 543 individual product groups. Which products in what quantityLawrence Index of normal transformation for 8 years: 0.23 According to the unit root test settings it can be inferred that on average the export value for any agricultural product in the trade flow between the OMS and the NMS diverged from the cross-sectional mean. The export increases hence were realized heterogeneously, but all categories experience increases.The heterogeneity in the relative changes that is apparent from table 3.13 argues for the anticipation that the trade patterns changed with a structural determination.10(4) Results4. RCA position2013.08.08.11Weinbrenner TimoReference country group is the OECD familyNRCA evolvements from 1999 to 2011Germanyc(1)c(2)c(3)c(4)NRCA Index for entire Agri-sector-0.0248920.7030810.000443-0.03463 (0.0000) (0.0000) (0.0001) (0.0000)Wald test(improving) significantc(3)/c(1)-1.8%Regression results, exemplarily for Germany:For France, Germany and Italy the c(3) and c(4) coefficients are significant and improving in nature (except FRA c(4)).

But: the NRCA Index developments are not congruent with the export flow developments.

Conclusion: EU-enlargement had a supportive effect on the NRCA IndexSzervezeti egysgMultipliers between 2004 and 2011: 1.02. 1.25 and 1.83 for FRA, GER and ITA.

But because the dynamics of the NRCA data series are not congruent with the EU-enlargement-induced trade pattern alterations, a direct causal relationship cannot be drawn. 11(4) Results5. Greatest Beneficiary2013.08.08.12Weinbrenner Timo123Absolute trade increaseEffect on NRCA positionRelative trade increaseDecisive is the general involvements of the OMS in the sales markets of the NMSRankCountryc(3)1Germany58,5502Italy10,7873France10,348RankCountryc(3)/c(1)1Germany3.0%2France1.7%3Italy1.2%heterogeneousRelatively equalIn concordance with the level of involvement in the CEECs sales markets:RankCountryExport share towards NMS 20111Germany13%2Italy7%3France3%Szervezeti egysg12(5)Summary and Conclusion (i)2013.08.08.13Weinbrenner TimoPositive effect proven for:Trade quantities towards NMSExport shares towards NMSSupport of RCA positionEU-Enlargement effect on French, German and Italian agricultural sectorsTrade creationBusiness Boost for OMS Szervezeti egysg13The agricultural sectors of the OMS are internationally competitive.OMS supply the NMS at different intensity levels (shares of total export). Germany has highest involvement, followed by Italy. France marginally active in NMS.Export patterns continuously transformed and converged to world export pattern.Transformation occurred with structural determination, in favor of highly processed products (while Italy as well is strong in horticulture).Convergence indicates a process of maturing trade linkages.Germany exhibits least Krugman-differencesNMS are heterogeneous sales markets for the OMS. Main trading partners:Absolute quantities: Poland, Czech Republic and Hungary, new comer Romania.Quantity per capita: Baltic states, Czech Republic, Slovenia and Slovakia.Within the agribusiness, the food processing industry might be a major winner, since the greatest share of trade increases was achieved with consumer-ready food products. NRCA Index improvements rely heavily on a small number of competitive products(5)Summary and Conclusion (ii)2013.08.08.14Weinbrenner TimoOther RevealmentsSzervezeti egysg14

2013.08.08.Weinbrenner Timo15Thank You for Your Attention!!

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