Does the WTO Trade Facilitation Agreement Actually Promote International Trade? A Structural Gravity Analysis

ABSTRACT

Trade theories implicitly explain the significance of trade facilitation (TF) in increasing trade. Identifying the methodological gaps in the literature, this study assesses the effects of TF on international trade relative to internal trade under a theoretically consistent structural gravity model. The results suggest that countries’ improved TF performance increases their agriculture and manufacturing trade. However, the ratification of the trade facilitation agreement (TFA) does not affect trade. The study observes differential effects of various dimensions of TF. Moreover, heterogeneity in the TF effects is found across different industries. These findings encourage countries to implement TF measures more seriously.

KEYWORDS:

• International trade
• intranational trade
• structural gravity model
• trade facilitation
• WTO

Acknowledgments

I would like to express my deepest thanks to the anonymous reviewer for his/her valuable time and effort. The reviewer’s constructive comments and suggestions helped to largely improve this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author.

Data availability statement

The data that support the findings of this study were derived from the following resources available in the public domain:

1. USITC-Gravity Portal: https://www.usitc.gov/data/gravity/index.htm.

2. Gravity Portal – Dynamic Gravity Dataset of the USITC: https://www.usitc.gov/data/gravity/dgd.htm.

3. World Bank Logistics Performance Index: https://lpi.worldbank.org/.

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/08853908.2024.2310036.

Notes

¹ See more information at https://www.oecd-ilibrary.org/docserver/9789264277571-en.pdf?expires=1598256927&id=id&accname=guest&checksum=411EE12A4C6A2986D55E43FA0AC886F3.

² The exclusion of country-pair fixed effects will lead to overstated estimates of the impact of TF. Country pairs that trade more have an incentive to boost trade facilitation, so there is a positive correlation between omitted country-pair variables and the variable of interest, which is itself correlated with the outcome variable.

³ https://tfadatabase.org/en/ratifications.

⁴ For details, refer to https://www.usitc.gov/data/gravity/itpde.htm.

⁵ Kindly refer to Gurevich and Herman (2018) for more details of the dataset.

⁶ Provided by Silvia Sorescu, Policy Analyst, Trade and Agriculture Directorate. For a detailed explanation of all the 11 TFIs, go to http://www.oecd.org/trade/topics/trade-facilitation.

⁷ The Trade Facilitation Indicators 2022 edition is also available; however, due to the availability of trade data through 2019, this edition cannot be added.

⁸ The list of 128 countries is presented in the online Appendix, Table A2.

⁹ For a detailed explanation of all the components of LPI, please visit LPI methodology, available at lpi.worldbank.org.

¹⁰ An interesting fact that is worth noting is that I have tried to see to what extent results differ if the globalization effect (captured by industry-specific time varying international border dummies) is eliminated from the specification. In the case of the elimination of the globalization effect, the coefficient for TFA turns out to be significant. This indicates that the effect of the trade policy variable is supposed to capture the common globalization effect, in case the variables to capture globalization are not included in the specification. Therefore, this result complements the findings by Bergstrand, Larch, and Yotov (2015).

¹¹ Food, textile, wood, publishing, chemical, mineral, metal, machinery and equipment, and other manufacturing correspond to ITPD industry codes 36–53, 54–58, 59–69, 70–78, 79–89, 90–101, 102–108, 109–147, and 148–153, respectively.

¹² The dataset used in the study also adds the fishery and forestry sector; however, due to limited observations for these two sectors, their estimations with current structural gravity specifications would not be possible. Agricultural crops, live stocks, and agricultural products correspond to industry codes 1–16, 17–20, and 21–26, respectively.

¹³ LPI data is sourced from the World Bank. Kindly see https://lpi.worldbank.org/international for more information. The study employs the LPI overall score, as the score is preferred over rank.

¹⁴ Based on the availability of LPI and trade data, the sample period for consideration of LPI as a measure of TF is 2012 to 2018.

¹⁵ Although, it is pointed out by Beverelli et al. (2018) that their method (as applied in this article) to identify the relative impact of any country-specific variable on international relative to intra-national trade is effective in dealing with the endogeneity concern of any regressor included in the model specification.