Is the road to regional integration paved with pollution convergence? Leila Baghdadi a, Inma Martinez-Zarzoso b, Celestino Suárez-Burguet c, Habib Zitouna a a LIM, MES cluster, Tunisia Polytechnic School b University of Göttingen and University Jaume I, Spain c University Jaume I, Spain

Motivation and main aims Theoretical predictions Related literature Empirical strategy – Data – Stylized facts – Main results Conclusions Outline

Motivation –The impact of trade liberalization on environment is a highly controversial debate –Environmentalists fear that poor open economies with low environment standards may act as pollution havens –Scarce attention has been devoted to the effects of regional trade agreements other than NAFTA

Main aims –This paper: –Explores the impact of regional trade agreements on carbon dioxide emissions gap of pairs of countries over the period –Using matching and difference-in-difference techniques

Trade and Environment: Theoretical Predictions –Grossman and Krueger (1993) and Copeland and Taylor (1994): –Trade affects the environment through 3 channels: –scale effect (-) –technique effect (+) –composition effect (?)

Trade and Environment: Theoretical Predictions –The composition effect (?): –Two opposite mechanisms are at work: –Factor Endowments Hypothesis (FEH) : countries that are relatively abundant in factors used intensively in polluting industries will on average get dirtier as trade liberalizes –The Pollution Haven Hypothesis (PHH): countries with relatively weak environmental policy will specialize in dirty industries

Trade and Environment: Theoretical Predictions –PHH: –Trade liberalization will cause pollution intensive industries to migrate from countries with strict environmental regulations to countries with lax environmental regulations –Trade liberalization could lead to a convergence in emissions of the trading partners

Trade and Environment: Empirical Evidence –Trade openness is good for the environment –Levinson and Taylor (2008), Antweiler et al. (1991), Dean (2002), Frankel and Rose (2005) –Trade openness has ambiguous effects on environment –Cole and Elliott (2003), Managi et al (2009), Korves, Voicu and Martinez-Zarzoso (2011)

Trade and Environment: Empirical Evidence –Scarce evidence on the effects of post FTAs on environment –Stern (2007): NAFTA leads to a convergence in pollutant emissions –This paper aims to fill this gap by investigating the effects of FTAs on the pollution emissions gap of pairs of countries during

Empirical Strategy –A simplified version of the determinants of emissions: –Population –Per-capita GDP –Openness ratio –FTA Scale, technique and composition effects

Empirical Strategy i, j: countries; t for time Y ijt : Pollution emissions (Em) gap between a pair of countries i, j in year t Pop: population, GDP is Gross Domestic Product Openness: sum of exports and imports divided by the gross domestic product FTA: equal to 1 if countries are involved in a free trade agreement

Empirical Strategy –Endogeneity of FTAs is an issue –Bergstrand and Baier (2004, 2007): Country pairs involved in FTAs tend to share common characteristics inducing a selection –One possible solution is to use matching techniques (Bergstrand and Baier 2009, Egger et al. 2008)

Empirical Strategy –Matching techniques –The key to successful matching estimates is to generate a credible counterfactual trade flows for an “untreated” matched country pair –A control group of country pairs that are virtually identical to a pair with an FTA (in all other aspects as trade partners)

Empirical Strategy –Matching techniques –The following determinants of FTAs are used to construct the untreated matched pairs: –Incomes –Distances –Contiguity –Common language

Empirical Strategy –Difference-in-difference techniques –The effect of an FTA –Combined with matching techniques –the DID method does not provide valid estimations when the comparison group differs greatly from the treated pairs –Propensity score matching techniques identify a control group without marked differences in characteristics compared to treated pairs of countries

Data –FTA –Jose De Sousa’s website and based on WTO publication –Distance, Common Language and Contiguity –CEPII –Income, Trade and Emissions –World Development Indicators (World Bank)

Stylized Facts Figure 1: Kernel density of log of bilateral distance for pair wise countries without and with FTA

Stylized Facts Figure 1: Kernel density of log of the sum of GDPs pair wise countries without and with FTA

Results –Population and GDP per capita gaps have positive effects on the emissions gap –A convergence in the scale of the economy as well as in the technology will lead to a convergence in CO2 emissions for a pair of countries –Openness ratio has a negative effect –Trade openness does not imply necessarily a reduction in the emissions gap

Results OLSATTOLSATT FTA Effect-0.202*** *-0.210*** * [0.0346][0.0379][0.0347][0.0379] Time fixed effectsNo Yes Number of observations176,04522,423176,04522,423 R-squared Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Results –Taking into account endogeneity by using matching techniques, we find different estimations from traditional OLS estimations: –The effect of FTA seems to be overestimated for all FTA –Countries involved in Free trade agreements converge in terms of pollution emissions

Results for specific agreements AllMatchedAllMatched EUROMED ***-0.204***-0.341***-0.211*** [0.0473][0.0507][0.0591][0.0507] EU ***-0.425***-0.260***-0.409*** [0.0339](0.0424)(0.0340)(0.0424) NAFTA *** *** [0.302][0.21][0.307][0.265] Time fixed effectsNo Yes Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Results –The effects of EU27 and NAFTA appear to be underestimated –Pollutions emissions of EU27 countries and NAFTA converge at a higher rate than EUROMED –Maybe due to a deeper level of economic integration

Conclusion –Pollution emissions of countries involved in FTAs seem to converge –Reasons: It could be that RTAs with environmental harmonization policies embedded affect relative pollution levels Composition effects Dynamic pro-competitive effects

F uture developments –Differences to be also considered: –Levels of economic integration (customs unions, currency unions etc.) –Levels of harmonization in environmental regulations within RTAs –Other pollutants –Bilateral trade gaps –Two countries’ “Polity” measures and in their “Land per capita” measures

Thanks for your attention

Results all FTAs VARIABLES Model 3Model 4 AllMatched FTA ij ***-0.179*** [0.0334][0.0315] After t 0.382***0.194*** [0.0294][0.0343] FTA ij *After t *** * [0.0347][0.0379] Abs Ln population ratio0.734***0.823*** [ ][ ] Abs Ln GDP per capita ratio0.391***0.110*** [ ][0.0148] Abs Ln openness ratio-0.414***-0.137*** [ ][0.0222] Time fixed effectsYes Number of observations176,04522,423 R-squared Robust standard errors in parentheses. Abs denotes absolute value and Ln natural logarithms. *** p<0.01, ** p<0.05, * p<0.1

Speciffic FTAs EUROMED EU-27 NAFTA VARIABLESAllMatchedAllMatchedAllMatched FTA ij ***-0.158***-0.310***-0.155*** [0.0521][0.0439](0.0327)(0.0406)[0.272][0.147] After t 0.108**0.162***0.379***0.546***0.374***1.284*** [0.0523][0.0489](0.0295)(0.0379)[0.0296][0.367] FTA ij *After t ***-0.211***-0.260***-0.409*** *** [0.0591][0.0507](0.0340)(0.0424)[0.307][0.265] Abs Ln population ratio 0.771***0.817***0.733***0.778***0.728*** [0.0125][ ]( )( )[0.0028][0.0853] Abs Ln GDP per capita ratio 0.197***0.118***0.397***0.507***0.407***0.562*** [0.0221][0.018]( )( )[ ][0.191] Abs Ln openness ratio ***-0.156***-0.432***-0.694***-0.439***1.240*** [0.0387][0.0278]( )(0.0153)[ ][0.196] Time fixed effectsYes Observations159,71214,867168,88263,269155, R-squared