Szervezeti egység The Impact of the Eastern European Enlargement on the Prosperity of the Old...

Szervezeti egység

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 2013

Weinbrenner TimoSupervisor: Prof. Dr. Fertő Imre

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Presentation Outline

1. Motivation of the study and research question

2. Research objectives and indicators

3. Analytical method

4. Descriptive and analytical results

5. Summary and Conclusion

22013.08.08.Weinbrenner Timo

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(1) Motivation and research question


Literature 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.M

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What 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:

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(2) Research Objectives and Indicators


No. Objective Indicator

1 Changes in quantitative trade dynamics Disaggregated exports in value from OMS towards NMS

2 NMS’s significance as export markets Share of exports towards the NMS in the OMS’ total exports.

3 Change in trade pattern

•Exports 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) position

•Normalized Revealed Comparative Advantage Index. (NRCA Index)•Annual mean deviation of NRCA Index (distributional divergence analysis

5 Greatest beneficiary among the OMS Comparative analysis of the individual reporter’s results.

Data specification of basis for all indicators

Data and data source Exports in value; OECD iLibrary data base

Representatives for OMS(Reporters)

France, Germany and Italy

NMS in eastern Europe Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Slovenia, Hungary, Romania, and Bulgaria

Assessment period 1999 to 2011

Analyzed trade items 543 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)

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(2) Explanation of indicators; Lawrence and Krugman Indices


Interpretation

Lawrence Index Krugman Index

Range 0 – 1 0 – 1

Behavior Increasing with structural transformation Increasing with structural dissimilarity

Index Assessment Objective

Lawrence Structural transformation in the trade pattern of the reporter within a predefined period.

Krugman Trade pattern similarity of the reporter’s trade towards a predefined trading partner compared to the reporter’s world export pattern at one point in time.

Formulas: Lawrence Krugman

Where and r represent the reporter’s share of product j in it’s exports towards a predefined trading partner i and towards the world at time t respectively and β is assumed to equal 0.5

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Where Eij

denotes the export value of country i for commodity j

Ei denotes total export value (of all ‘j’) of country i

EREFj

denotes the export value of commodity j of the group of reference countries

EREF denotes the total export value (of all ‘j’) of the group of reference countries

(2) Explanation of indicators; NRCA Index


Interpretation:

NRCA value Interpretation

= 0 Country i exports product j at the comparative-neutral level

> 0 Country i exhibits a comparative (export) advantage in product j

< 0 Country i exhibits a comparative (export) disadvantage in product j

Range -2500 to 2500 (after multiplication of all index values by 10,000 for a more convenient presentation)

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(3) Analytical Method to analyze the indicators


1

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Descriptive analysis

Time series regression model to test for structural breaks:Change in mean value after 2004

Change in trade growth rate after 2004

Panel 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 period

Wald test for joint probability: c(3) = 0; c(4) = 0

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(4) Results 1. Trade Quantities

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 -

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12 Evolvement from 1999 to 2011 (bn USD)

France Germany Italy


c(1) c(2) c(3) c(4) c(1) c(2) c(3) c(4) c(1) c(2) c(3) c(4)

Regression results

607,539 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 test Significant Significant Significantc(3)/c(1) 1.7% 3.0% 1.2%

Total agricultural exports from the OMS towards the CEEC country aggregate:

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Regression results:

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(4) Results 2. NMS as export markets

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Proportion of the reporters’ world exports directed towards the CEEC region (export shares):

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110%

2%

4%

6%

8%

10%

12%

14%

Evolvement from 1999 to 2011



c(1) c(2) c(3) c(4) c(1) c(2) c(3) c(4) c(1) c(2) c(3) c(4)

Regression results

1.3E-05 0.54 9.9E-08 0.17 4.0E-05 0.73 8.8E-07 0.10 3.7E-05 0.54 3.3E-07 0.18 (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 test Significant Significant Significant

c(3)/c(1) 0.8% 2.2% 0.9%

Regression results:

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(4) Results 3. Trade Pattern

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Trade pattern = the composition of the export flow of a reporting country

Distributional DivergenceKrugman average annual changeLawrence

1999-2008

1999-2003

2004-2008

France 0.37 0.31 0.25Germany 0.42 0.23 0.27Italy 0.29 0.22 0.22

Above-average transformation rate;No EU-enlargement effect detectable

2000-2004

2005-2009

France -0.005 -0.010Germany -0.018 -0.008Italy -0.006 -0.011

Continuous adaptation;Difference apparent, but inconsistent

Annual Mean Deviations:Unit Root is accepted for

France, Germany and Italy at 1% level

Divergence in export flows confirmed

Chen 1

Chen 2

Chen 3

Chen 4

Chen 1

Chen 2

Chen 3

Chen 4

Chen 1

Chen 2

Chen 3

Chen 4


- 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000

199920042011

Initial ranking of Chen categories systematically reinforced (in absolute and relative terms):1. Consumer-ready food2. Processed intermediate goods3. Raw commodities4. Horticultural products

But: for Italy Horticultural products is the second most important category.

Agri-exports towards the NMS, in million USD

Chen categories as division key:

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(4) Results 4. RCA position

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Reference country group is the OECD family

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

-60-50-40-30-20-10

010203040


NRCA evolvements from 1999 to 2011

Germany

c(1) c(2) c(3) c(4)NRCA Index

for entire Agri-sector

-0.024892 0.703081 0.000443 -0.03463 (0.0000) (0.0000) (0.0001) (0.0000)

Wald test (improving) significant

c(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 Index

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(4) Results 5. Greatest Beneficiary

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Decisive is the general involvements of the OMS in the sales markets of the NMS

Rank Country c(3)1 Germany 58,5502 Italy 10,7873 France 10,348

Rank Country c(3)/c(1)1 Germany 3.0%2 France 1.7%3 Italy 1.2%

heterogeneous

Relatively equal

In concordance with the level of involvement in the CEECs’ sales markets:Rank Country Export share towards NMS 2011

1 Germany 13%2 Italy 7%3 France 3%

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(5) Summary and Conclusion (i)

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Positive effect proven for:

1. Trade quantities towards NMS

2. Export shares towards NMS

3. Support of RCA position

EU-Enlargement effect on French, German and Italian agricultural sectors

Trade creation

Business Boost for OMS

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•The 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-differences•NMS 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)

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Other Revealments

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