Data and code for: Improving Preferential Market Access Through Rules of Origin: Firm-level Evidence from Bangladesh

Principal Investigator(s): View help for Principal Investigator(s) Tobias Sytsma, RAND Corporation

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In text numbers			01/23/2021 02:26:PM
Tables			01/23/2021 01:16:PM
data			01/23/2021 02:27:PM
Readme.pdf	application/pdf	665.9 KB	07/29/2021 01:42:PM
Requirements.R	text/x-r-syntax	1.7 KB	01/23/2021 08:16:AM
requirements.do	text/x-stata-syntax	1.1 KB	01/23/2021 08:16:AM

Project Citation:

Sytsma, Tobias. Data and code for: Improving Preferential Market Access Through Rules of Origin: Firm-level Evidence from Bangladesh. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-01-28. https://doi.org/10.3886/E130783V1

Project Description

Summary: In countries where there exist limited opportunities to source inputs locally, rules of origin undermine access to preferential trade agreements for final-goods exporters. I analyze the 2011 revision to the rules of origin associated with the EU’s Generalized System of Preferences, which allowed apparel producers in least-developed countries (LDCs) to use internationally-sourced textiles in exported products. Using transaction-level data on Bangladeshi apparel firms, I find the rules of origin effectively cut the preferential margin by three-fourths. Liberalizing the rules of origin resulted in firm-level revenue growth, which was driven by the intensive margin through increased shipment sizes and quality upgrading.

Scope of Project

Subject Terms: rules of origin ; apparel sector; product quality

JEL Classification:
      F13 Trade Policy; International Trade Organizations
      F14 Empirical Studies of Trade
      L25 Firm Performance: Size, Diversification, and Scope
      O19 International Linkages to Development; Role of International Organizations
      O24 Development Planning and Policy: Trade Policy; Factor Movement; Foreign Exchange Policy

Geographic Coverage: Bangladesh

Data Type(s): event/transaction data

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Published Versions

V1 [2022-01-28]

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