1. INMACULADA MARTÍNEZ ZARZOSO Universitat Jaume I and Georg-August Universitaet LAURA MARQUEZ-RAMOS Universitat Jaume I GORDON WILMSMEIER UN-ECLAC Arnold Shain Seminar 26 June 2013, Antwerp

2. The context  Latin American containerised trade  Continued economic expansion and trade  Challenges in trade facilitation  Excessive time delays  Bureaucratic requirements for varying goods traded  Role of institutional trade barriers

3. Research question What are repercussions from maritime transport infrastructure development and trade facilitation in the structure of maritime transport costs, and hence, on bilateral trade?

4. Trade facilitation  WTO definition: “the simplification and harmonization of international trade procedures””  Wilson, Mann and Otsuki (2003, 2005) define four measures  Port efficiency  Customs environment  Regulatory environment  E-business usage

5. Modelling approaches  Gravity model of trade  Mann and Otsuki (2003, 2005) for the Asia-Pacific region  Soloaga, Wilson and Mejía (2006) on Mexican competitiveness  Djankov, Freund and Pham (2006) used the World Bank’s Doing Business Database focusing only on effects of time delays in the exporting country  Nordas, Pinali and Grosso (2006) discuss how time delays affect the probability to export and the export volumes for imports from Japan, Australia and the United Kingdom.  Persson (2007) studied effect of time delays and transaction costs on trade flows using a sample selection approach and focussing on the specific effects for each of the six groups of ACP countries negotiating Economic Partnership agreements with the EU.

6. Modelling approaches  Computable general equilibrium model to estimate the effect of a composite index of trade facilitation on trade flows  UNCTAD, 2001  OECD, 2003  Dennis, 2006  Decreux and Fontagne, 2006

7. Trade facilitation and tariffs  Márquez-Ramos, Martínez-Zarzoso and Suárez-Burguet (2011) compare different types of trade barriers in both developed and developing countries,  Trade facilitation variables and policy trade barriers, as tariff peaks and tariff escalation remain important issues for developing countries, and a “tariff bias” exists against developing countries (Márquez-Ramos et al, 2011).  They show that trade facilitation variables are, in relative terms, more important than tariffs.   increasing trade facilitation would lead to an increase in world trade, although this increase would not be the same in all countries as, by running simulations  The present paper mainly differs from existing trade- facilitation literature in that it focus on imports and analyses the effect of trade facilitation on both transport costs and bilateral trade with Latin America.

8. Data  Data for disaggregated maritime exports from 181 countries to 9 Latin American countries  Time period 2000-2006  LA countries: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Peru, Paraguay and Uruguay.  Each observation corresponds to a given product, k (SITC code 5 digit).

9. Trade Facilitation variables Trading accross bordersN of Documents needed to Export Days needed to Export N of Documents needed to Import Days needed to Export Country2006 Change 2006-132006 Change 2006-132006 Change 2006-132006 Change 2006-13 Argentina 7016-37020-4 Bolivia 8024-57036-13 Brazil 7018-58024-5 Chile 6017-26016-3 Colombia 5034-106048-7 Ecuador 922-2844-15 Paraguay 8035-2100330 Peru 6022-108029-12 Uruguay 7023-78023 Av LA 2006 7-0.1123.44-5.117.56-0.1130.33-6.67 Av OECD 2006 5.4216.706.6219.10 Av OECD 2013 5.28013.70-36.16014.58-4.52

10. Data: Transport cost model  The dependent variable in the transport cost model is the ad- valorem freight rate between the country of origin and the country of destination.  Product value (USD/Kg):  Volume exported:  Total weight in tonnes of the trade flows shipped to each specific country of destination.  Port container throughput: Iportv  Distance: Dist  Number of days (documents) to import and export: ET  from the World Bank’s Doing Business (2006) database

11. Data: Gravity model  Dependent variable in the gravity model is imports between the country of origin and the country of destination.  amount in current dollars that importers have to pay for the products at free on board (fob) prices.  Gross domestic product (GDP) of the importer and exporter countries  Gross domestic product per capita in both countries  Transport costs  Distance.  Dummies:  Common language  Common border

12. Model specification  ln indicate natural logarithms,  uv ijkt denotes the value per weight ratio (USD/ton) of product k in year t,  q ijkt is the volume of transaction between countries i (exporter) and j (importer) of product k in year t,  iportv jt and eportv it denote total port throughput or maritime transport infrastructure in the importing and exporting countries in year t,  dist ij denotes the maritime distance between main ports in country i and j,  T jt and T it the average number of days (documents) needed in the importer and the exporter country to trade a product.  δ kt =sectoral*time dummies at one digit SITC classification, SITC2-SITC8 where:

13. Linking trade costs to a simple gravity equation  where lnM ijkt is the log of the value of imports of product k into country j from country i in period t.  GDP jt is the value of gross domestic product for importer j in period t and GDP it that of exporter i in the same period, dist ij is the distance between each pair of trading partners and T denote trade facilitation variables.  ε ijkt is a composite error term of unobservable effects.  A similar set of country-pair, time and sectoral dummies as in equation (1) is added.

14. Methodology  Estimation of a transport costs model and a gravity equation of trade  Using panel data techniques that allow controlling for country, sectoral and time unobserved heterogeneity.

15. Main results transport costs Lntc(1)(2)(3) b/se lnuv-.753** (.0235) lnq-.108** (.00517) (.00516) i_dayimp.0272* (.00361) e_dayexp.011** (.00067) i_numdocimp-.0568** (.0022) e_numdocexp.0371* (.00316) lnicostimp.128 (.0551) lnecostexp.16** (.00613) R-squared0.678 0.679 N819826 Decrease in TC:Reduc to 2013 i_dayimp-14%with 5 days less e_dayexp-8%with 7 days less Reduc to OECD i_dayimp-27%with 10 days less e_dayexp-16%with 15 days less

16. Main results bilateral aggregated trade data b/se ltgdp-.154*** (.0348) lntc-.751*** (.00089) lnidayimp-2.3*** (.671) lnedayexp-.407*** (.0161) R-squared0.855 N794909 Dyadic FEyes Time&Sector FE yes i_codefobtcavi_dayimpe_dayexp ARG89703.020.0620.0012.46 BOL71129.340.59 BRA116770.70.1424.0011.55 CHL187323.80.3621.0018.92 COL102283.70.1240.8317.80 ECU75085.480.4544.0017.73 PER221833.50.2131.0018.13 PRY59965.951.1133.0013.17 URY49969.270.0923.0013.06 Total106740.40.1723.9612.10

17. Conclusions  Trade facilitation (time and documents required to trade) is considered as determinants of transport costs  Recent institutional trade conflicts among Latin American partners point in evidence the need of empirical research to provide light on the role of institutional trade barriers, or trade facilitation procedures, when trading with Latin America

18. Conclusions (cont’d)  Results show that time delays are a more important trade barrier to trade with Latin American countries than bureaucratic procedures  Natural trade barriers (transport costs) are of higher importance than institutional trade barriers established by Latin American countries (trade facilitation procedures) when trading with this developing region  Further research needed with disaggregated data for a better understanding of the role of trade facilitation procedures

19. INMACULADA MARTÍNEZ ZARZOSO Universitat Jaume I and Georg-August Universitaet LAURA MARQUEZ-RAMOS Universitat Jaume I GORDON WILMSMEIER UN-ECLAC

20. Transport costs disaggregate versus aggregated results (1)(2)(3)(4) Product value-0.693*** -1.419***-1.433*** -32.093-32.065-21.548-22.34 Volume imported-0.110*** -0.785***-0.802*** -9.437-9.433-44.201-46.139 Importer’s port container throughput 0.5160.327 1.1740.734 Exporter’s port container throughput-0.324-0.419 -1.188-1.577 Distance0.1560.14 1.5121.392 Days to import0.012***0.026** 4.0022.43 Days to export0.011*0.010** 1.5862.276 Documents to import0.043-0.083 1.034-1.48 Documents to export0.0390.014 1.570.981 Constant Term-3.920.8343.216***5.084*** -0.5030.1122.9075.133 R-squared0.3590.3170.8720.869 Number of observations1077504 745 RMSE0.7510.7500.5870.589

21. Gravity model for aggregate exports (5)(6) Income0.359***0.321*** 6.3874.827 Distance-0.075-0.063 -0.445-0.365 Transport costs-0.677***-0.699*** -12.823-13.041 Border1.561***1.412*** 3.8223.538 Language0.655**0.754** 2.1192.304 Days to import0.036*** 2.709 Days to export-0.030*** -3.617 Documents to import-0.016 -0.136 Documents to export-0.068*** -3.242 R-squared0.8080.804 Number of observations727 RMSE0.6330.641