Deep Integration

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Transcript Deep Integration

Deep Integration: Free trade agreements heterogeneity and its impact on bilateral trade Séminaire DIAL

Jaime Ahcar Olmos Under the supervision of : Jean-Marc Siroën PSL Université Paris-Dauphine Laboratoire LEDa-DIAL 24 avril, 2014


1) Introduction 2) Methodology and Data 3) Results 4) Conclusions 5) References 1


• International trade economists have apparently successfully dealt with the question : does free trade agreements increase trade flows? Rose (2004), Baier & Bergstrand (2007), Martinez et al. (2009) • This has been done neglecting thorny issues like heterogeneity and the concept of deep integration.


Introduction : Questions

• • • • • So we now try to answer new questions : Are all free trade agreements equal? What happens if not ?

Does a deeper free trade agreement really increase trade more than a shallow agreement ?

What would be a good indicator of deep integration like ?

Are other provisions related to trade but out of the traditional WTO framework of negotiation really important to expand trade ? 3

Introduction : Importance

• • • • Preferential Trade Agreements PTA heterogeneity little explored Indicators of heterogeneity Implications for the interpretation of PTA coefficients Implications for our understanding of the limits of trade liberalization 4

Literature review

• • • • Bourgeois, Dawar & Evnenett (2007). A Comparative Analysis of Selected Provisions in Free Trade Agreements.

Magee (2008) controlled for some levels of trade integration.

Vicard (2009) on the depth of the agreements found that their trade creation effect does not statistically differ according to the depth of the RTA.

Vicard, V (2011) By using interactions terms found that large, similar and close countriesn benefit more from RTA. This approach doesn’t care about their dose or their design. 5

Literature Review

• • • Horn, Mavroidis & Sapir (2010) and non traditional WTO provisions in the analysis and explored legal enforcement effects, but ramained on the descriptive approach.

Orefice & Rocha (2013) carried out empirical analysis from Horn et al. observarions and found positive evidence.

Dür, Baccini & Elsig (2014) enlarged the database and introduced latent trade analysis. 6


• Two different classification of agreements databases: 1) WTO (2011) Research division for the World Trade Report 2) Design of Trade Agreements DESTA-WTI (2014) Then, we introduce this information in our gravity model unbalanced panel data set which encompasses 153 countries and 613.030 bilateral trade flows from 1980 to 2012.


Databases and methodology :

• • • • • Following (Horn et al. 2010) approach: 1) WTO+ provisions: topics under the competence of the WTO agreements. 2) WTO-X provisions: topics outside the current mandate of the WTO.” This database is exploited by Orefice & Roche (2013) Their regressions account for 66 PTA from 1980– 2007. We include in our calculations 103 PTA including agreements for Peru & Colombia from 1980-2012.


Database variables WTO+ Policy Areas Negociated in PTAs Anti-dumping Countervailing Measures GATS General Agreement on Trade in Services Public Procurement Sanitary and Phytosanitary Measures State Aid (Subventions) State Trading Enterprises Technical Barriers to Trade Trade Related Aspects of Intellectual Property Rights TRIPs TRIMs Trade-Related Investment Measures Source: Orefice & Rocha (2013), Horn et al. (2010). WTO ( 2011) Research division for the World Trade Report 9

Database variables

WTO-X Provisions Negociated in PTAs

Agriculture Innovation policies Anti-corruption Approximation of Legislation Audiovisual Competition policy Consumer protection Cultural cooperation Data protection Economic policy dialogue Education and training Energy Environmental laws Financial assistance Health Human rights Illegal immigration Illicit drugs Industrial cooperation Information society Investment measures IPR Labour market regulation Mining Money laundering Movement of capital Nuclear safety Political dialogue Public administration Regional cooperation Research and technology SMEs Social matters Statistics Taxation Terrorism Visa and asylum Source: Orefice & Rocha (2013), Horn et al. (2010). WTO ( 2011) Research division for the World Trade Report 10


• • • • • Probit approach We put forward two main kinds of indicators to try to capture deep integration.

They depend on a set of variables (provisions) that characterize PTA texts. 1) Additive indicators 2) Distilled indicators taken from PCA related methodologies. 11

Methodology Contributions : Additive indicators

• • • Does an additive indicator tell us something about the depth of the agreement?

Reasonably yes. One can expect that more comprehensive agreements are deeper.

Isn’t the magnitude of the reduction on tariffs the main indicator of depth? Maybe not, as nontariff barriers can play a major role to block trade.


Methodology Contributions : Distilled indicators

• • We calculate a Multiple Correspondence Analysis MCA indicator for deep integration: MCA is a technique that can be applied to obtain an indicator that summarizes in just one dimension the variability of a set of variables related with the content and design of PTA, and then with the depth of the integration.


Limits of the analysis

• • • • “Europe’s single market is probably the best example globally of successful deep integration” Claar S. & Nölke A. (2010).

Nevertheless, because of methodology consistency requirements, Dür et al. (2014) additive indicator give UE 1992 single market agreement a 5 while Colombia USA receive a 7 Orefice & Rocha gives 6-11 to EU27 but 9-27 to EU Chile.

Enforceability of the agreements. Too subjective, it implies going into the nuances of the language in PTA texts.


Methodological Limits

• • Due to the large size of our data set, we can not completely control for multilateral resistance in all specifications. Anderson and Van Wincoop (2003); Baldwin & Taglioni (2006) We try to minimize this setback by introducing time fixed effects and time invariant fixed effects for importers and exporters countries.


Theoretical Model

x ij

is export from region i to region j, σ is the elasticity of substitution between all goods, t

ij cost factor between i and j; y i and y j

are GDP in region i and region j; y

W is a trade

is world nominal income; k is a constant, (1 – σ) and (1 – σ)ρ are coefficients.


Probit model with single EV for the median rta coeffient on some WTO+ provisions

(1) sps tbt ste ad cvm publicprocurement trims gats trips Constant brtamed brtamed brtamed brtamed brtamed brtamed brtamed brtamed brtamed 0.071

(0.252) 0.206

(0.282) -0.268

(0.248) 0.096

(0.319) 0.077

(0.275) -0.226

(0.250) -0.031

(0.196) -0.140

(0.242) 0.145

(0.174) -0.066

(0.288) -0.043

(0.233) 0.140

(0.187) -0.074

(0.247) 0.050

(0.177) -0.219

(0.273) 0.168

(0.230) -0.132

(0.253) 0.092

(0.196) Observations r2_p Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

103 0.000555

103 0.00375

103 0.00823

103 0.000634

103 0.000552

103 0.00576

103 0.000625

103 0.00454

103 0.00192


Probit model with single EV for the median rta coeffieient on WTO-X provisions

consumerprotection environmentallaws labourmarketregulation Constant brtamed brtamed brtamed -0.599* (0.330) -0.520** (0.252) 0.120

(0.137) 0.244

(0.168) -0.496* (0.276) 0.155

(0.147) Observations r2_p Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

103 0.0238

103 0.0302

103 0.0228



• • • On a probit model regression with single EV. No evidence that the presence of any particular provision under WTO+ would increase trade above the median level, which PTAs are supposed to do.

Only 3 out of 36 WTO-X provisions show significant estimators : environmental laws, labour market regulation and consumer protection. All three show a negative coefficient.

It could open the door to the possibility of PTA that deters trade rather than promote it.



• • • Robustness. Possible bias in the estimation of the individual PTA coefficients and colinearity between provisions.

A better way could be capture the whole variability of the provisions in just one indicator.

This indicator would give us a clue about the depth of the integration.


Specification to estimate with PPML : Control for large zero value flow observations in GM data sets and gives consistent estimates.

(Silva & Tenreyro, 2006; 2011) 21

Deep integration: Latent trait analysis (Rasch) indicator Dur and al (2014) and additive indicator on levels and logs. DESTA.

xij xij xij xij dp_D_ra0 lndp_D_ra00001 deep_DE_ad ln_dp_d_ad lnPIBi lnPIBj lndist 0.129*** (0.006) 0.730*** (0.024) 0.647*** (0.023) -0.803*** (0.009) 0.027*** (0.001) 0.729*** (0.024) 0.645*** (0.023) -0.792*** (0.009) -5.617*** (0.863) 0.085*** (0.003) 0.746*** (0.024) 0.662*** (0.023) -0.775*** (0.009) -6.215*** (0.845) 0.033*** (0.001) 0.729*** (0.024) 0.642*** (0.022) -0.759*** (0.009) -5.424*** (0.850) Constant -6.577*** (0.864) Observations R-squared Exporter FE Importer FE Country-pair FE Time FE 587,654 0.891

YES YES NO YES 587,654 0.892

YES YES NO YES 587,654 0.900

YES YES NO YES Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

587,654 0.900


Deep Integration: Additive indicators and its log from WTO+ and WTO-X. PPML estimator.

xij xij xij xij 0.058*** (0.002) ad_ch1 lnad_ch00001 ad_x1 lnad_x100001 lnPIBi lnPIBj lndist Constant 0.765*** (0.024) 0.679*** (0.023) -0.784*** (0.009) -5.860*** (0.886) 0.036*** (0.001) 0.734*** (0.024) 0.647*** (0.023) -0.746*** (0.009) -5.607*** (0.889) 0.023*** (0.001) 0.756*** (0.024) 0.671*** (0.024) -0.819*** (0.008) -5.810*** (0.904) 0.035*** (0.001) 0.738*** (0.024) 0.650*** (0.023) -0.747*** (0.009) -5.623*** (0.886) Observations R-squared Exporter FE Importer FE Country-pair FE Time FE Time Varying Exporter FE Time Varying Importer FE 572,657 0.900

YES YES NO YES NO NO 572,657 0.903

YES YES NO YES NO NO Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

575,383 0.894

YES YES NO YES NO NO 575,383 0.903



• We are now more aware that not all PTA are equal. This would imply that much of previous estimations on the average effect of PTA on trade could be biased.

• Through different indicators we have confirmed that deeper PTAs increase trade more than shallow ones. However these indicators also present limits to their interpretation. A better definition of deep integration continues to be a challenge.



• • • A better deep integration indicator should show EC model as the deepest. Meanwhile, these imperfect indicators present enough power to give us sufficient clues about the direction of the impact of heterogeneity of the agreements on trade.

Other provisions out of the traditional WTO scope present significant positive impact on trade. Yet, some of them could individually bear a negative impact. More research is needed specially to try to identify which provisions or combination of provisions presents a higher impact.


Data Set : Sources PTA provisionas database :


( 2011) Research division for the World Trade Report.

World Trade Institute

(2014) . The Design of trade agreements database DESTA.

Bilateral Exports: International Monetary Fund


Direction of Trade Statistics Database DOTS (2013). Current GDP and population: World Development Indicators (WDI) database,

World Bank

, (2013) Area, Island and Landlocked, constructed by the author based on the World Factbook from the Central Intelligence Agency of the United States of America (


) Weighted distance, contiguity, col45 and comlang_eth9 :


(2013): Head, K., Mayer, T. & Ries, J. (2010), Gravity dataset, obs. till 2006. Regional Trade Agreements: constructed by the author, based on the Regional Trade Agreements Information System (RTA-IS), World Trade Organization


(2013) GATT membership: constructed by the author based on the World Trade Organization


information (2013).

CEPII: Head, K., Mayer, T. & Ries, J

. (2010), Gravity dataset, obs. Till 2006.


membership: constructed by the author based on the Organisation de coopération et de développement économiques OCDE (2013) information.



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