Trade similarity across the Mediterranean Basin

Bridging the gap: the role of trade and FDI in the Mediterranean

Naples, 9 June 2006

Luca De Benedictis and Lucia Tajoli

Politecnico di MilanoUniversità di Macerata

Research questions

General IssuesGeneral Issues

Is economic integrationeconomic integration affecting trade structures making countries more similar or more diversified in terms of production and trade patters?

Which are the implications of a given specialization?Is the trade structure trade structure relevant? theory vs. empiricsstatic vs. dynamic

Which is the role of export compositionrole of export composition in determining income convergence within a group of countries (catching-up)?

Luca De Benedictis:

Trade and other openness indicators often positively associated to growth, but criticisms on criticisms on the the robustness of robustness of the evidencethe evidence, on the indicators used, and on the lack of a clear underlying mechanism linking the two variables.

Luca De Benedictis:

Trade and other openness indicators often positively associated to growth, but criticisms on criticisms on the the robustness of robustness of the evidencethe evidence, on the indicators used, and on the lack of a clear underlying mechanism linking the two variables.

Research questions

Does it make a difference to change the export pattern?

Does it matter to become more or less similar to a given country or group of countries?

Does it matter in which way (in terms of forms of integration and in terms of sectoral composition) a country is open (and not only how much it is open)?

Relatively high GDP growth rates for the MED

countries, but little or no catching-up in terms of GDP

per capita

Many political and institutional problems Many political and institutional problems

hampering growth and integrationhampering growth and integration

Difficulties in running acceptable growth

regressions for these countries

Relevance of these issues for the Mediterranean countries

Are trade and export composition related to these

problems ? Can an export-led growth model be

achieved?

• Aim of this work:Aim of this work:

-verify if export structures in the process of economic integration with the EU has become more similar to the EU export structure

- verify if the change in the export structure is associated with other forms (non-traditional trade) of economic integration

- verify if export structures capture characteristics of the development process

Research questions

A group of countries with very strong ties with the EU

Initial agreements very early, in the late 1978

EU is the main trade partner for the MED group, but EU is the main trade partner for the MED group, but

not for allnot for all

Barcellona Agreement Barcellona Agreement as a compensation for the as a compensation for the

trade diversion?trade diversion?

Growth of Med economic integration with the EU -

and growth of their trade in general - somehow

disappointing

The EU - Med partnership

EU trade with the CEECs and with the MEDA group

EU total imports from CEECs and MEDA

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

Tot MEDA

Tot CEECS

Algeria

Egypt

Israel

JordanLebanon

Morocco

Tunisia

Palestinean Terr. Syria

Turkey

Export Share to EU - 1990

Algeria

EgyptIsrael

JordanLebanon

Morocco

Tunisia

Palestinean Terr.

Syria

Turkey

Export Share to EU - 2003

Data and sources for this empirical analysis

Countries: Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian territories, Syria, Tunisia, Turkey

Benchmark: EU15

Trade data: exports toward the EU market in 97 sectors from Comext, Eurostat database

Time period: 1990-2003

Three groups of countries in this sample:

Mono-export (fuel) countries: Algeria and SyriaMono-export (fuel) countries: Algeria and Syria

Diversified but not changingDiversified but not changing

Characteristics of the export composition of the MED

Diversified and changingDiversified and changing

Algeria 1990

Gini = 0.983

exp

ort

sh

are

02

04

06

08

0

Algeria 2003

Gini = 0.931

exp

ort

sh

are

02

04

06

08

0

Egypt 1990

Gini = 0.858

exp

ort

sh

are

01

02

03

04

05

06

0

Egypt 2003

Gini = 0.775

exp

ort

sh

are

01

02

03

0

Israel 1990

Gini = 0.801

exp

ort

sh

are

02

46

81

01

2

Israel 2003

Gini = 0.897

exp

ort

sh

are

05

10

15

Jordan 1990

Gini = 0.887

exp

ort

sh

are

05

10

15

20

Jordan 2003

Gini = 0.802

exp

ort

sh

are

05

10

15

20

25

Lebanon 1990

Gini = 0.786

exp

ort

sh

are

02

46

81

0

Lebanon 2003

Gini = 0.855

exp

ort

sh

are

02

46

81

01

2

Morocco 1990

Gini = 0.860

exp

ort

sh

are

05

10

15

20

25

Morocco 2003

Gini = 0.860

exp

ort

sh

are

05

10

15

20

25

Tunisia 1990

Gini = 0.898

exp

ort

sh

are

01

02

03

0

Tunisia 2003

Gini = 0.882

exp

ort

sh

are

05

10

15

20

25

30

Palestinian Territories 1990

Gini = 0.989

exp

ort

sh

are

02

04

06

08

01

00

Palestinian Territories 2003

Gini = 0.955

exp

ort

sh

are

05

10

15

20

25

30

Syria 1990

Gini = 0.980

exp

ort

sh

are

02

04

06

08

0

Syria 2003

Gini = 0.972

exp

ort

sh

are

02

04

06

08

0

Turkey 1990

Gini = 0.814

exp

ort

sh

are

05

10

15

Turkey 2003

Gini = 0.815

exp

ort

sh

are

05

10

15

EU 1990

Gini = 0.675

exp

ort

sh

are

02

46

81

01

2

EU 2003

Gini = 0.718

exp

ort

sh

are

02

46

81

01

21

4

Measuring export structure and similarity

Export structure: the vector of shares of each sector on

total exports, x1j, ……xnj.

Self-similarity: taking a base year, we observe how a

country export structure changed in time. The change is

measured by the variation of the correlation or distance

indices.

EU-Similarity: we compare a country’s export structure with the one of the EU, using different indices.

We compare country’s export structure to the EU benchmark over time to observe whether differences narrow or widen.

ProductivityProductivitySelection (Melitz, 2003)Knowledge spillovers (Keller, 2002)Factor composition (Slaughter, 1997; Ventura, 1997)=> proxy used: high-tech intensity

InvestmentsInvestmentsFDIOutward Processing Trade => proxy used: FDI + OPT

Adaptation to international demandAdaptation to international demandThe Linder hypothesis (Linder, 1961; Markusen, 1986)=> proxy used: growth in demand

StabilityStabilityInternational risk sharing (Acemoglu and Zilibotti, 1997)Optimal currency area arguments=> proxy used: efficiency of financial system and institutions

Why similarity in trade structure should matter? Some possible channels:

Methodological points

SimilaritySimilarity => (1 – Distance)

Distance: Bray-Curtis index

Measuring similaritysimilarity in trade structures through a synthetic metric based on distance (De Benedictis-Tajoli, 2004)

Measuring similarity in trade structures both with respect to itself at the beginning of the period (SELF-SIMILARITYSELF-SIMILARITY), and with respect to the EU15 (EU-SIMILARITYEU-SIMILARITY)

countries

Export sectoral sharessectors

j = countryk = benchmarkx = sectoral export sharei = sector

Strong similarity 1Weak similarity 0

Similarity in Trade StructuresSimilarity in Trade Structures

Methodological points

Advantages of such a similaritysimilarity index with respect to other alternatives:

- no need of a normal distribution of observations, it is is appropriate in presence of skewed distributions (unlike correlation)

- change of weight of sectors is taken into account (not based on pure ranking) =>it capture changes due to specific sectors

- this particular index is immune from the double-zero paradox, it has the advantage of not increasing in the number of sectors considered, n; of being invariant to proportional sub-classifications of the n sectors considered; of considering both large and small differences

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

MEDA EU-Similarity (Bray-Curtis)

ME

DA

Se

lf-s

imila

rity

(B

ray-C

urt

is)

AlgeriaEgyptIsraelJordaniaLebanonMoroccoTunisiaPalestinian territoriesSyriaTurkey

A comparison with another group: The EU- and SELF- similarity Plot for the CEECs

How can economic integration influence the observed changes?

On the supply side: through FDI and other forms of delocalization of production, production sharing agreements between the EU and the MEDA can affect the share of exports in important sectors

Previous result for the CEECs confirm the relevance of these effects: changes in the export structure of all CEECs is driven by changes in a few sectors highly involved in processing trade, and growth in EU demand also plays a role. But for the CEECs international fragmentation of production can foster both convergence and divergence of trade structures

On the demand side: opening of the EU market can influence the export structure of the MEDA to accomodate the European demand

Are these effects at work for the Mediterranean Are these effects at work for the Mediterranean countries? Has integration gone far enough to countries? Has integration gone far enough to produce them?produce them?

0 20 40 60 80 100

0.0

00

.05

0.1

00

.15

Algeria - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Wood

Autovehicles

0 20 40 60 80 100

0.0

00

.01

0.0

20

.03

0.0

40

.05

0.0

6

Egypt - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Apparel

Autovehicles

0 20 40 60 80 100

0.0

00

.05

0.1

00

.15

0.2

0

Israel - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Aircraft

Clocks

0 20 40 60 80 100

0.0

00

.05

0.1

00

.15

Jordan - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Cutlery and tools

0 20 40 60 80 100

0.0

00

.05

0.1

00

.15

0.2

00

.25

Lebanon - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Photog. Products

0 20 40 60 80 100

0.0

0.2

0.4

0.6

0.8

1.0

Morocco - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Other animal prods.

Cereal preparations

Hats

Clocks

0 20 40 60 80 100

0.0

0.2

0.4

0.6

0.8

Tunisia - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Sugar

Photog. Products

CementJewellery

0 20 40 60 80 100

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Syria - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Jewellery

Art pieces

0 20 40 60 80 100

0.0

00

.05

0.1

00

.15

0.2

00

.25

0.3

0

Turkey - Opt in 2003

sectors

sect

ora

l sh

are

of o

pt

Pharmaceut. Jewellery

Art pieces

Exports toward the EU market: total and OPT tradeCorrelation for Tunisia: 0.95

Tunisia composition of OPT and total exports

0

10

20

30

40

50

60

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97

CN sectors

%

OPT

Total exports

Exports toward the EU market: total and OPT tradeCorrelation for Israel: 0.39

Israel: composition of total and OPT trade

0

5

10

15

20

25

30

35

40

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97

CN sectors

%

OPT

Total export

Exports toward the EU market: total and OPT tradeCorrelation for Turkey: 0.40

Turkey composition of OPT and total trade

0

5

10

15

20

25

30

35

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97

CN sectors

%

OPT

Total exports

Export structure correlated to export volumesExport structure correlated to export volumes

Changes in export composition correlated with Changes in export composition correlated with

increase in EU similarityincrease in EU similarity

Changes in export composition correlated with Changes in export composition correlated with

inward FDIinward FDI

Some regression results

Changes in export composition correlated with OPTChanges in export composition correlated with OPT

Similarity in export composition and trade

Dependent Variable: TOTEXPEU?Method: Pooled Least SquaresDate: 05/22/06 Time: 15:42Sample: 1990 2003Included observations: 14Number of cross-sections used: 8Total panel (balanced) observations: 112Cross sections without valid observations dropped

Variable CoefficientStd. Error t-Statistic Prob.

EUSIM? 32261372 5333587 6.048719 0SELFSIM? -6626375 1890934 -3.50429 0.0007Fixed EffectsALG--C 13089913EGY--C -401063ISR--C -6014709LEB--C -7187733MOR--C -2184132SYR--C 5554367JOR--C -7857860TUR--C 4284490

R-squared 0.795012 Mean dependent var4711510Adjusted R-squared0.776925 S.D. dependent var 4.98E+06S.E. of regression2350038 Sum squared resid 5.63E+14Log likelihood -1796.72 F-statistic 395.5902

Similarity in export composition and trade

Dependent Variable: TOTEXPEU?Method: Pooled Least SquaresDate: 06/08/06 Time: 19:38Sample: 1990 2003Included observations: 14Number of cross-sections used: 9Total panel (unbalanced) observations: 115

Variable CoefficientStd. Error t-Statistic Prob.

GDP? 107.9112 11.94513 9.033907 0EUSIM? 13369352 5118070 2.612186 0.0103Fixed EffectsEGY--C -8310466ISR--C -9957794LEB--C -6248052MOR--C -2268398TUN--C -1709597TUR--C -1E+07ALG--C 3113890SYR--C -471313JOR--C -5363180

R-squared 0.867569 Mean dependent var5013036Adjusted R-squared0.854836 S.D. dependent var 4.76E+06S.E. of regression 1813994 Sum squared resid 3.42E+14Log likelihood -1814.67 F-statistic 681.3174