Abstract
This article evaluates the effect of different aspects of trade facilitation in developed and developing countries on bilateral trade through an augmented gravity model and uses the latter to estimate ad valorem equivalents (AVEs) of administrative barriers to trade. The results show that a multitude of trade facilitation variables including internet, bureaucracy, corruption and geography affect the transaction times to import and to export. However, the time to import has a higher negative impact on trade when compared with the time to export. Another important finding is that both facilitation and liberalization of trade are complements rather than substitutes. Finally, when sectoral characteristics are taken into account, some perishable, seasonal and high-value-added products appear to be more sensitive to transaction time than other products. These results are also confirmed by the values of the AVEs.
Abstract
Cette étude évalue les différents aspects de la facilitation du commerce, en particulier le commerce bilatéral, en pays développés et en voie de développement, utilisant un modèle de gravité augmenté, pour estimer les équivalents ad-valorem (AVEs) des barrières administratives au commerce. Les résultats montrent qu’une multitude de variables qui facilitent le commerce – y inclus internet, la bureaucratie, la corruption, la géographie – ont un effet sur le temps de transaction des importations et exportations. Un autre résultat important est que la facilitation et la libéralisation du commerce sont complémentaires, pas les substituts l’un de l’autre. Pour finir, dès qu’on tient en compte les caractéristiques sectorielles, il y a des produits périssables, saisonniers, ou d’haute valeur-ajoutée, qui sont plus sensibles que d’autres au temps de transactions. Les résultats sont aussi confirmées par les valeurs des AVEs.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
This definition is taken from the World Customs Organization website: http://www.wcoomd.org/en/topics/facilitation/overview/customs-procedures-and-facilitation.aspx.
OECD (2002b) argues that this large range could be explained by three factors: the difference in the reference year of the study, the components of the administrative barriers taken into account and the sample of countries considered.
For instance, in this model, the impact of trade facilitation aspects can be divided into two parts: the impact of trade facilitation itself and the impact of the elasticity of substitution. If this point is not taken into account, the effect of trade facilitation aspects will be underestimated.
This data set contains several sections, the largest being ‘Trading across Borders’ as it brings together seven indicators related to procedures incorporated in trade. These indicators are number of days to export and to import, number of documents required for exports and imports, the cost of imports and exports, and the ease of doing business. Only the time and document aspects are taken into account.
For the purpose of robustness checks, a second way to deal with the multicollinearity issue is to use the factor analysis method. The latter allows us to estimate an index called ‘TF’ for trade facilitation taking into account the previous aspects, namely, the documents to export and to import, the time to export and to import, the internet widespread of the exporter and the importer, corruption, and their geographic situation. The advantage of the first method (two-steps estimation) is that it allows us to estimate the AVEs for administrative barriers. The second way (factor analysis) eliminates the problem of multicollinearity as it summarizes all of the trade facilitation aspects in one index, but it has the usual drawback of the results being difficult to interpret.
A list of countries and sectors taken into account is presented in Tables B1 and B2 in Appendix B. Following the World Bank classification, 28 per cent of the sample are low-income countries, 50 per cent are lower- and upper-middle-income ones and finally 22 per cent are high-income countries, distributed between OECD and non-OECD countries. The difference in country incomes allows the state of trade facilitation in developing and developed countries to be taken into account.
Centre d’Etudes Prospectives et d’Informations Internationales. This data set is available on the CEPII website: http://www.cepii.fr/francgraph/bdd/distances.htm.
In fact, as I am using the CEPII version of Trade and Production, two important aspects of the methodology deserve to be mentioned. According to Mayer et al (2007), the first remark is related to the utilization of mirror flows. When both exporting and importing countries report to COMTRADE, researchers usually consider only imports, or average both values. While in the first case a lot of information is discarded, in the second the CIF component (cost, insurance and freight) is not properly removed. For this reason, BACI (Base pour l’Analyse du Commerce International) developed a methodology to estimate a mean CIF to obtain an estimation of values in FOB, which is applied to every flow. The second consideration is the weighting criteria for mirror values, based on an estimation of the quality of declaration of reporter countries. Thus, the weights can differ from a 50/50 average.
For the purpose of robustness checks, an alternative would have then been to estimate an Anderson and van Wincoop (2004) gravity-type equation and explain the fixed effects with the determinants of the time to export (number of days, corruption, etc …), and then aggregate the impact of all these variables on quantity imported. This is more or less equivalent to inverting steps 1 and 2. Results (presented in Tables C1 and C2) remain relatively robust.
When standard errors are clustered by country pair, common language has a significant and positive effect on trade. When they are clustered by exporter and importer, this effect becomes insignificant. However, for all the other variables, results do not change whether I cluster by country pair or by exporter and importer.
For the purpose of robustness checks, while the standard errors are clustered by country pair in columns 1, 2 and 4, in column 3 they are clustered by exporter (standard errors shown in the first row) and importer (those shown in the second row). It is obvious that the results are robust regardless of the way the standard errors have been clustered.
This graph shows the marginal effect of the estimated time to import on relative imports when tariffs increase. It has been constructed using the grinter utility. It allows the marginal effect of an interacted variable to be graphed. This utility should work with any equation with a linear index. In our case, the index is rel. imp=b1+b2*tariff+b3*time_imp+b4*tariff*time_imp, grinter can graph either b2+b4*time_imp or b3+b4*tariff.The graph includes a vertical line at the mean value of the other constitutive term comprising the interaction (the modifying variable).
For more details on the product assumptions, see Appendix A. It is noteworthy that the results do not change even if the products that are not compatible with Doing Business assumptions are eliminated.
The exports diversification index is measured by the 1-Herfindahl-Hirschman Index (HHI). Therefore, positive variation shows less concentration and more diversification.
Ad valorem tariff equivalents for the whole sample are available upon request.
For a robustness check, I have computed the AVEs using the elasticities of substitution σ that have been estimated from my model. The Spearman’s rank correlation coefficient between the AVEs computed using Kee et al’s (2008) elasticities and those computed using the estimated ones is 0.88 for time to export and 0.86 for time to import. Both versions of AVEs are quite close. Yet, using the estimated elasticities generates, in some cases, slightly higher AVEs since the elasticities values are lower than those of Kee et al (2008). Results are shown in Tables C3 and C4 in Appendix C.
For more details, see Tables C3 and C4 in Appendix C.
This part presents the scope and the description of Doing Business. It is available on www.doingbusiness.org.
They are available on CEPII’s website.
As the available data from ‘Trade and Production’ end in 2004 and the available data from ‘Doing Business’ start in 2006, these two databases have been merged under the following assumption: institutional variables of ‘Doing Business’ would not vary much between 2004 and 2006, making their combination possible.
BACI is the new CEPII world database for international trade analysis at the product level.
Institutional Profiles (2001) is a survey conducted by researchers based at the French Ministry of the Economy, Finance and Industry (MINEFI) and the French Development Agency (AFD) in the countries covered (51 developed and developing countries). Data have been collected through a questionnaire describing the institutional characteristics of these countries and were split into four sections: section A is related to the institutional environment, section B is related to the market for goods and services, section C concerns the financial system and section D concerns the labor market as well as social interactions. Out of the legion of indicators included in the database, only 14 have been chosen based on their appropriateness to trade facilitation.
References
Anderson, J. (1979) A theoretical foundation for the gravity equation. American Economic Review 69 (1): 106–116.
Anderson, J. and van Wincoop, E. (2003) Gravity with gravitas: A solution to the border puzzle. American Economic Review 93 (1): 170–192.
Anderson, J. and van Wincoop, E. (2004) Trade costs. Journal of Economic Literature 70 (1): 197–215.
APEC (2002) APEC Economies: Realising the Benefits of Trade Facilitation, a report prepared for the APEC Ministerial Meeting, Los Cabos, Mexico, October.
Baier, S. and Bergstrand, J. (2001) The growth of world trade: Tariffs, transport costs, and income similarity. Journal of International Economics 53 (1): 1–27.
Bergstrand, J. (1989) The generalized gravity equation, monopolistic competition, and the factor-proportions theory in international trade. The Review of Economics and Statistics 71 (1): 143–153.
Bergstrand, J. (1990) The Heckscher-Ohlin-Samuelson model, the Linder hypothesis and the determinants of bilateral intra-industry trade. Economic Journal 100 (403): 1216–1229.
Cernat, L. (2001) Assessing Regional Trade Arrangements: Are South-South More Trade Diverting? New York and Geneva: UNCTD. Division on International Trade in Goods and Services, and Commodities, Study Series no. 16.
De, P. (2006) Why Trade Costs Matter?, Asia-Pacific Research and Training Network on Trade, Working Paper Series, no. 7, April.
Djankov, S., Freund, C. and Pham, C. (2006) Trading on Time. World Bank. Policy Research Working Paper Series no. 3909, January.
Dutt, P. and Traca, D. (2007) Corruption and Bilateral Trade Flows: Extortion or Evasion?, Working Paper Series, SSRN: http://ssrn.com/abstract=992399.
Feenstra, R. (2002) Border effects and the gravity equation: Consistent methods for estimation. Scottish Journal of Political Economy 49 (5): 491–506.
Fontagné, L., Mayer, T. and Zignago, S. (2004) Trade in the Triad: How Easy Is the Access to Large Markets? CEPII Working Paper, no. 2004-04, April.
Fontagné, L. and Zignago, S. (2007) A re-evaluation of the impact of regional agreements on trade patterns. Integration & Trade 11 (26): 31–51.
Freund, C. and Weinhold, D. (2000) On the Effect of the Internet on International Trade. Board of Governors of the Federal Reserve System. International Finance Discussion Papers, no. 693.
Fujita, M., Krugman, P. and Venables, A. (2000) The spatial economy: Cities, regions, and international trade. Southern Economic Journal 67 (2): 491–493.
Gaulier, G., Martin, J., Méjean, I. and Zignago, S. (2008) International Trade Price Indices. CEPII Working Paper, no. 2008-10, June.
Head, K. and Mayer, T. (2002a) Effet frontière, intégration Economique et Forteresse Europe. Economie et Prévision 152–153 (1–2): 71–92.
Head, K. and Mayer, T. (2002b) Illusory Border Effects: Distance Mismeasurement Inflates Estimates of Home Bias in Trade. CEPII Discussion Paper 2002-01.
Hummels, D. (2001) Time as a trade barrier. Department of Economics, IN: Purdue University (mimeo).
Jean, S. and Mitaritonna, C. (2010) Determinants and pervasiveness of the evasion of custom duties CEPII Working Papers 2010–26, CEPII research center, Paris, France.
Kee, H., Nicita, A. and Olarreaga, M. (2008) Import demand elasticities and trade distortions. The Review of Economics and Statistics 90 (4): 666–682.
Kee, H., Nicita, A. and Olarreaga, M. (2009) Estimating trade restrictiveness indices. Economic Journal 119 (534): 172–199.
Kim, S., Lee, H. and Park, I. (2004) Measuring the impact of APEC trade facilitation: A gravity analysis. Paper presented at the Reunion of the Economic Committee of the APEC, Santiago, Chili.
Limao, N. and Venables, A. (2000) Infrastructure, Geographical Disadvantage and Transport Costs. World Bank. Policy Research Working Paper no. 2257.
Martin, P., Mayer, T. and Thoenig, M. (2008) Make trade not war? Review of Economic Studies 75 (3): 865–900.
Mayer, T., Paillacar, R. and Zignago, S. (2007) CEPII trade, production and bilateral protection database: Explanatory notes, CEPII research center, Paris, France (mimeo).
McCallum, J. (1995) National borders matter: Canada-U.S. Regional trade patterns. The American Economic Review 83 (2): 615–662.
Milner, C., Morrissey, O. and Rudaheranwa, N. (1998) Protection, Trade Policy and Transport Costs: Effective Taxation of Ugandan Exporters. DFID-TERP: CREDIT DISCUSSION PAPER 7 (CDP007).
Minor, P. and Tsigas, M. (2008) Impacts of Better Trade Facilitation in Developing Countries: Analysis with a New GTAP Database for the Value of Time in Trade, mimeo, June.
Nicita, A. and Olarreaga, M. (2001) Trade and Production, 1976-99. World Bank. Policy Research Working Paper Series no. 2701, November.
OECD (2002a) La Relation entre les Accords Commerciaux Régionaux et le Système Commercial Multilatéral: Facilitation des Echanges, prepared by Evokia Mosé, Working Party of the Trade Committee, TD/TC/WP(2002)17/FINAL, June.
OECD (2002b) Avantages pour les Entreprises de la Facilitation des Echanges, prepared by T. Matsudaira and Evokia Mosé, Working Party of the Trade Committee, TD/TC/WP(2001) 21/FINAL, August.
OECD (2003a) Le Programme de Doha pour le développement : Gains de bien-être à attendre de la poursuite de la libéralisation des échanges multilatéraux du point de vue des droits de douane. Document TD/ TC/ WP(2003)10/ FINAL, August, Paris.
OECD (2003b) Trade Facilitation: The Benefits of Simpler, more transparent Border Procedures, Policy Brief, Public Affairs Division, Public Affairs and Communications Directorate, August.
OECD (2003c) Réflexions sur les Méthodes Possibles pour mettre en œuvre les Principes Relatifs à la Facilitation des Echanges Figurant dans les Articles V, VII et X du GATT, prepared by Evokia Mosé, Working Party of the Trade Committee, TD/TC/WP(2003)12/FINAL, October.
Park, S. (2002) Measuring Tariff Equivalents in Cross-Border Trade in Services. Korea Institute for International Economic Policy. Working Paper no. 02-15.
Raballand, G. (2003) Determinants of the negative impact of being landlocked on trade: An empirical investigation through the central asian case. Comparative Economic Studies 45 (4): 520–536.
Schröder, P. (2004) Real versus tariff liberalization: A welfare comparison under monopolistic competition. Open Economies Review 15 (4): 403–418.
Walsh, K. (2006) Trade in Services: Does Gravity Hold? A Gravity Model Approach to Estimating Barriers to Services Trade. Insitute for International Integration Studies. Discussion Paper no. 183.
Wilson, J., Mann, C. and Otsuki, T. (2003) Trade Facilitation and Economic Development: Measuring the Impact. World Bank. World Bank Policy Research Working Paper no. 2988, March.
Wilson, J., Mann, C., Woo, Y., Assanie, N. and Choi, I. (2002) Trade facilitation: A development perspective in the Asia-Pacific region report prepared for the Asia-Pacific Economic Cooperation, The World Bank, Washington DC, October.
Wilson, J., Mann, C. and Otsuki, T. (2004) Assessing the potential benefit of trade facilitation: A global perspective. The World Economy 28 (6): 841–871.
WTO (2001) Ministerial Conference – Fourth Session, Doha adopted on 14 November 2001, WT/MIN(01)/DEC/1, November.
Zaki, C. (2013) Trade facilitation and corruption: A CGE model of Egypt. Journal of North African Studies 18 (1): 70–111.
Zaki, C. (2014) An empirical assessment of the trade facilitation initiative: Econometric evidence and global economic effects. World Trade Review 13 (01): 103–130.
Acknowledgements
I would like to thank Lionel Fontagné, Bernard Hoekman and Marcelo Olarreaga for their useful comments. I am also grateful to Catherine Bros, Fida Karam and Rodrigo Paillacar. I thank participants at the University of Paris 1 Panthéon Sorbonne seminars, Global Trade Analysis Project, European Trade Study Group, Economic Research Forum and Globalization and Economic Policy annual conferences. All the relevant data and computation files are available upon request from the author. Any errors are my own. This work has benefited from financial support from the Economic Research Forum (ERF). It does not reflect the opinions of the ERF.
Author information
Authors and Affiliations
Appendices
Appendix A
Data Description
This appendix presents the definition as well as the source of each variable used in the database. Data have been collected from several sources. Regarding the trade facilitation variables, ‘Doing Business’Footnote 18 has been used. This data set compiles procedural requirements for exporting and importing a standardized cargo of goods by ocean transport. Every official procedure for exporting and importing the goods is recorded, from the contractual agreement between the two parties to the delivery of goods along with the time and cost necessary for completion. All documents required for clearance of the goods across the border are also recorded. For further details, go to www.doingbusiness.org.
First Step: Time Determinants
Dependent Variable
The logarithm of the Time to export and to import has been used in the first step estimation. It is recorded in calendar days. The time calculation for a procedure starts from the moment it is initiated and runs until it is completed. If a procedure can be accelerated for an additional cost, the fastest legal procedure is chosen. It is assumed that neither the exporter nor the importer wastes time and that each commits to completing each remaining procedure without delay. Procedures that can be completed in parallel are measured as simultaneous procedures but with the same time frame for completion.
Independent Variable
For trade bureaucracy, documents to export and to import have been used. ‘Doing Business’ defines these as all documents required to export and import goods. It is assumed that the contract has already been agreed upon and signed by both parties. These documents include bank documents, customs declaration and clearance documents, port filing documents, import licenses and other official documents exchanged between concerned parties. Documents filed simultaneously are considered different documents but with the same time frame for completion.
The number of procedures to start a business is taken from the Doing Business database. It gives all the procedures that an entrepreneur needs to carry out to obtain all the necessary permits, to notify and file with all requisite authorities, and hence to launch a legally operating firm involved in industrial or commercial activity.
The corruption variable comes from the Corruption Perceptions Index (CPI) developed by Transparency International. It is based on 13 independent surveys and indicates the perceived level of public sector corruption in a country. While the CPI is ranked from 0 (most corrupt) to 10 (least corrupt), it is used as a proxy of customs fraud.
The Internet variable comes from the WDI database available on the World Bank website. This variable determines the number of internet users per 1000 people and is the best proxy for technological intensity. Thus, it is used as a proxy for the intensity of e-commerce.
Geographic variables (the fact of being landlocked or an island) are taken from the Distance data set available on the CEPII website.
Second Step: Gravity Model
Dependant Variable
The dependant variable is the ratio between bilateral and internal trade flows as explained below:
Bilateral Flows: The data used is a cross-section in 2004 and come from CEPII’sFootnote 19 ‘Trade and Production’ database.Footnote 20 The mirror flows, available in Nicita and Olarreaga (2001), were used along with the CEPII database on international trade (BACI),Footnote 21 which is also based on COMTRADE data.
Internal Flows: Internal trade flows are in current USD and are calculated as the difference between domestic primary and secondary sector production minus exports. This variable also comes from ‘Trade and Production’.
Explanatory Variables
Tariff and Production Data: First, the original data (Nicita and Olarreaga, 2001) come from the United Nations sources: COMTRADE and UNIDO. Despite wide coverage, the World Bank files contain many missing values for production figures in recent years. This is the reason why the Trade and Production database was largely extended using more recent versions of the UNIDO CD-ROM together with OECD STAN data for OECD members.
Distance Variable: This comes from the distance database developed by the CEPII. The methods used in this database allow many indicators on internal distance, weighted distance, etc to be generated. This allows us to estimate the model derived in the section ‘Results’. In my model, I use the relative distance defined as the ratio between bilateral and internal distance. The former is the distance between two capitals and the latter is a proxy of average distance between producers and consumers in a country. It is computed as follows 
. For further details regarding this measure, see Head and Mayer (2002a).
Other Classical Gravitational Variables: These come from the CEPII data set, namely, dummy variables indicating whether the two countries are contiguous, share a common language, have had a common colonizer after 1945 or have ever had a colonial link. Some other variables are not bilateral but country-specific. They are dummies indicating whether a country is landlocked and an island. The variable of belonging to the same PTA comes from the data set developed by Martin et al (2008), available at http://team.univ-paris1.fr/teamperso/mayer/data/data.htm.
Relative Prices: These come from the data set that has been constructed by Gaulier et al (2008). This data set is built from the unit value given by the BACI database at the product level. In my regressions, the Laspeyres index is used. Other indices (namely, Paasche, Fisher and Tornqvist indices) have been used but the results did not change.
Robustness Check Variables: As mentioned earlier, in order to eliminate multicollinearity issues, the factor analysis method is used. The idea behind this is to calculate one index taking all of the trade facilitation aspects into account. It is quite obvious that the results remain robust because trade facilitation aspects have a highly significant and negative effect on bilateral trade. The coefficients of the other variables remain significant, with the same sign and almost the same values. Moreover, for the purpose of robustness checks and studying the impact of more aspects of trade facilitation, the Institutional Profiles database has been used.Footnote 22 It is worth mentioning that customs efficiency has a positive and significant effect on trade. By contrast, transaction security appears to reduce trade by 11 per cent because after the events of 9-11, developed countries imposed many constraints in order to secure trade. These constraints reduced trade flows coming from developing countries. Fraud has a significant negative effect on trade. The internet widespread remains significant and boosts trade. A very important result is that concerning geographical variables (being landlocked or an island). Once I control for many trade facilitation aspects, these variables become non-significant. Hence, more trade facilitation means overcoming trade barriers induced by geographical impediments. The results using the factor analysis and the Institutional Profiles database are available upon request.
Appendix B
Lists of Countries and Sectors
Appendix C
Robustness Checks
Inverting the Two-step Procedure
Computing the AVEs Using the Estimated σ
Rights and permissions
About this article
Cite this article
Zaki, C. How Does Trade Facilitation Affect International Trade?. Eur J Dev Res 27, 156–185 (2015). https://doi.org/10.1057/ejdr.2014.36
Published:
Issue Date:
DOI: https://doi.org/10.1057/ejdr.2014.36