Trade Agreements in Arab Countries: what are the effects on their trade?

(A Gravity Modeling Approach)

Mahmoud R. Fath-Allah

Economist

League of Arab States

1

13th International Conference of MEEAManaging the MENA transitional economies31st May- 1st June 2014 – Tlemcen, Algeria

Contents

1. Motivations, Problem Identification, and Question

2. Literature Review.

3. Dataset and Model Setup.

4. Results and Policy implication.

5. Conclusion.

2

Arab Countries’ membership in WTO and selected RTAs

Number of RTAs the

country has membershi

p

EFTA FTA with Singapore FTA with Turkey Agadir

Agreement COMESA US-FTA EU-MED GCC PAFTA WTO Country

3 X X X X Bahrain2 X X X Saudi Arabia2 X X X Qatar2 X X X UAE2 X X X Kuwait3 X X X X Oman5 X X X X X X Tunisia1 X Yemen3 X X X Lebanon7 X X X X X X X X Jordan6 X X X X X X X Egypt6 X X X X X X X Morocco4 X X X X Palestine2 X X Algeria2 X X Syria2 X X Sudan1 X Iraq1 X X Djibouti1 X Comoros0 X Mauritania2 X X Libya0 Somalia

6 1 6 4 5 4 7 6 18 12Arab country

membership in each RTA

Source: UNESCWA,2007,www.ustr.gov/Trade_Agreements ،www.wto.org،www.arableagueonline/org/las/index.jsp

3

Overlapping Trade Agreements in Arab Countries

Source: Prepared by Author

4

The Question is:

“what is the benefit that Arab countries would gain from being members in many trade agreements?”

5

Literature Review

Source: (Urata and Okabe, 2007)

6

The effect of Overlapping RTAs on Trade

7

PositiveHub and Spokes argument:the country acts like a “hub”, linking up severalfree trade areas and trading on preferential termswith every “spoke” partner.

NegativeTransaction Cost argument:In the case of multiple membership in deferentRTAs. Rules of Origins gets complicated,production will be fragmented according tothe requirements of each agreement

Gravity Model

•

8

Possible combinations of dummy variables and respective implication on trade policy

rtain rtaout rtaoverlp

Respective meaning of the dummy variable combination

Trade agreement

exists between i and

j

Country i has

existing trade

agreement with a

country deferent

than j

Country i has at

least one trade

agreement with a

country other than j

0 0 0

Arab country has no existing trade agreement with its respective

trade partner or any other country. Though, no overlap exists in this

case.

1 0 0

Arab country has existing trade agreement with only its respective

trade partner. No agreements with any other countries. Though, no

overlap exists in this case.

0 1 0

Arab country has only one existing trade agreement with a country

other than its respective trade partner. Though, no overlap exists in

this case.

0 1 1

Arab country has trade agreements with more than one countries

other than respective partner. Though, overlap is existing in this

case.

1 1 1 Arab country has trade agreement with its respective trade partner

and with other countries. Though, overlap is existing in this case.

9

The data set

• Use the dataset of Rose (2004) which covers 175 countries from 1948 to 1999.

• expand dataset by adding more observations using UN-COMTRADE, WITS, World Bank’s World Development Indicators databases.

• panel structure consisting of 32886 annual observations clustered by 1134 country pair groups from 1980 to 2010.

• The number of observations varies per year as the dataset is Un-Balanced Panel Data.

10

List of countries included in sample

Arab Countries EU-27 EFTA

1Algeria 1Austria 1Iceland

2Bahrain 2Belgium 2Liechtenstein

3Comoros 3Bulgaria 3Norway

4Djibouti 4Cyprus 4Switzerland

5Egypt 5Check Republic

6Iraq 6Denmark Other Countries

7Jordan 7Estonia 1China

8Kuwait 8Finland 2India

9Lebanon 9France 3Japan

10Libya 10Germany 4Australia

11Mauritania 11Greece 5USA

12Morocco 12Hungary 6Canada

13Oman 13Ireland 7Brazil

14Qatar 14Italy 8Mexico

15Saudi Arabia 15Latvia 9Turkey

16Somalia 16Lithuania 10Singapore

11

Summary Statistics

12

Scatterplots

13

Estimation process

• Estimate Pooled data using OLS.

• Estimate Fixed Effects Model using Least Square Dummy Variable (LSDV).

• Testing Pooled Model Vs. Fixed Effects Model.

• Estimate Random Effects Model.

• Testing Fixed Effect vs. Random Effects models.

14

OLS estimates for Pooled data

(P1)

Standard gravity model

(P2)

(P1) + trade policy

variables without

overlap variable

(P3)

(P2) with overlap

variable

(P4)

(P3) after omitted non-

significant variables

ltrade

Estimated

parameter tStatistics

Estimated

parameter tStatistics

Estimated

parameter tStatistics

Estimated

parameter tStatistics

lrgdp 1.04994 117.76 1.071241 117.75 1.0671 116.06 0.955379 146.23

lrgdppc 0.22367 18.33 0.257506 20.53 0.264093 20.76

ldist -0.86244 -41.5 -0.86135 -40.21 -0.86399 -40.31 -0.97142 -46.28

lareap -0.16469 -25.89 -0.17941 -27.72 -0.17819 -27.49

border 1.091818 12.42 1.091883 12.45 1.096459 12.5

comlang -0.11477 -2.83 0.010194 0.24 0.01324 0.32

rtain -0.30262 -5.28 -0.37143 -6.04 0.200394 3.13

rtaout -0.30944 -10.28 -0.34344 -10.71 0.295374 9.68

rtaoverlp 0.178938 3.07 -0.10918 -1.77

_cons -33.0161 -100.9 -34.1601 -99.62 -34.0728 -99.05 -27.8429 -87.98

Adjusted R2 0.6417 0.6444 0.6446 0.588

RSS 44630.54 44288.32 44262.35 51318.93

F test 4809.05 3649.76 3246.98 4599.32

15

Pooled Data Model

• Model P1: fits the data will, explaining a major part of the variation in bilateral trade flows. the signs of the coefficients meet the economic expectations except (lareap) and (comlang) which both have negative sign. Lee et. al.(2005) has the same results.

• Model P2: fits data better than P2 but with a negative signs for (RTAin), (RTAout) which leads to the result that trade agreements of the Arab countries has trade diversion effect.

• Model P3: (RTAoverlap) has significant positive effect which means that Arab countries with overlapping trade agreement encountered better trade flows than other normal Arab countries.

• Model P4: slightly less fitness of data with significant parameters except those of RTAoverlap.

16

Fixed Effects estimates using within and between units variations

(F1)

FE- within units

(F2)

FE- between units

ltrade

Estimated

parameter tStatistics

Estimated

parameter tStatistics

lrgdp 0.307045 11.44 1.102518 31.32

lrgdppc -0.10957 -3.51 0.210389 3.99

ldist -0.98845 -11.36

lareap -0.18665 -7.71

border 1.133116 3.26

comlang 0.127101 0.8

rtain 0.022933 0.44 -0.99911 -2.77

rtaout -0.23432 -7.14 -0.72786 -4.83

rtaoverlp 0.202156 5.35 4.329017 5.42

_cons -1.41487 -1.42 -33.9836 -25.9

R2 0.0193 0.7259

F test 59.22 303.02

17

FE Model

• Model F1: has low fitness of data, even though the parameters are significant and lead to conclude that overlapping trade agreements have small positive effects on a trade flow of a country.

• Model F2: fits data better than Model F1and also F2 has significant parameters except for the variable common language which has negative sign which is anticipated as the majority of trade for Arab countries existing with non-Arab speaking countries

18

Pooled Vs. FE Models

Test Statistics

F(1039, 15064) =45.09

According to this test, the specification of FE model is better fits the data.

19

Random Effects estimates of the Gravity Model

RE estimates

ltrade Estimated Parameters z-test

lrgdp 0.636634 29.48

lrgdppc -0.12116 -4.61

ldist -0.93785 -10.86

lareap -0.01063 -0.53

border 0.896302 2.53

comlang -0.51451 -3.33

rtain -0.01447 -0.28

rtaout -0.2629 -8.26

rtaoverlp 0.038094 1

_cons -10.3674 -11.19

R2

within 0.0168

between 0.6241

overall 0.5192

sigma_u 1.557954

sigma_e 0.930076

rho 0.73725

Wald chi2 1884.28

20

RE Model

• The results indicate low value of overall coefficient of determination with higher respective value for between estimates.

• the importance of variations across units (cross sections).

• Trade agreements of Arab countries are not having the same effects across all Arab countries because each of which have deferent aspects and scope in terms of inclusive sectors and goods.

21

Testing FE Vs. RE Models

• Hausman specification test :

The resulting value of the test is 1099.74 which will lead to reject the null hypothesis. Consequently, Fixed Effects model is the right model to fit the data.

22

Conclusion

• The paper contribute in the debate of whither membership in multiple trade agreements would gain positive or negative results on country trade flow.

• The results of this study indicate that the effects of the overlapping agreements are positive on the trade flows of the respective countries.

• The parameter of trade agreement without overlap showed negative effects as the agreements itself may have trade diversion effects.

• Countries engaged in many and overlapping trade agreement would benefit by countervailing their negative effects in some separate agreements with positive overall gains resulting from being “Trade Hub” that have access to deferent markets with preferential terms.

23

Thank you

24