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Measuring openness to trade

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  • Waugh, Michael E.
  • Ravikumar, B.

Abstract

In this paper we derive a new measure of openness—trade potential index—that quantifies the potential gains from trade as a simple function of data. Using a standard multicountry trade model, we measure openness by a country׳s potential welfare gain from moving to a world with frictionless trade. In this model, a country׳s trade potential depends on only the trade elasticity and two observable statistics: the country׳s home trade share and its income level. Quantitatively, poor countries have greater potential gains from trade relative to rich countries, while their welfare costs of autarky are similar. This leads us to infer that rich countries are more open to trade. Our trade potential index correlates strongly with estimates of trade costs, while both the welfare cost of autarky and the volume of trade correlate weakly with trade costs. Thus, our measure of openness is informative about the underlying trade frictions.

Suggested Citation

  • Waugh, Michael E. & Ravikumar, B., 2016. "Measuring openness to trade," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 29-41.
  • Handle: RePEc:eee:dyncon:v:72:y:2016:i:c:p:29-41
    DOI: 10.1016/j.jedc.2016.03.009
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    Citations

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    Cited by:

    1. Jean Imbs & Laurent L. Pauwels, 2020. "High Order Openness," Working Papers 20200047, New York University Abu Dhabi, Department of Social Science, revised Jun 2020.
    2. Taosheng Wang & Hongyan Zuo & C. H. Wu & B. Hu, 2021. "Combined soft measurement on key indicator parameters of new competitive advantages for China's export," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    3. Ravikumar, B. & Santacreu, Ana Maria & Sposi, Michael, 2019. "Capital accumulation and dynamic gains from trade," Journal of International Economics, Elsevier, vol. 119(C), pages 93-110.
    4. Claudius Gräbner & Philipp Heimberger & Jakob Kapeller & Florian Springholz, 2018. "Measuring Economic Openness," wiiw Working Papers 157, The Vienna Institute for International Economic Studies, wiiw.
    5. Jiang, Yufan & Wang, Hongyan & Liu, Zuankuo, 2021. "The impact of the free trade zone on green total factor productivity ——evidence from the shanghai pilot free trade zone," Energy Policy, Elsevier, vol. 148(PB).
    6. Luca Salvatici & Silvia Nenci, 2017. "New features, forgotten costs and counterfactual gains of the international trading system," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 44(4), pages 592-633.
    7. Ajayi, Patricia & Ogunrinola, Adedeji, 2020. "Growth, Trade Openness and Environmental Degradation in Nigeria," MPRA Paper 100713, University Library of Munich, Germany.
    8. Ibhagui, Oyakhilome & Olarewaju, Favour, 2020. "Broad Dollar Shocks and Economic Activity in Trade-Heavy Countries: The Role of Government Size," MPRA Paper 100944, University Library of Munich, Germany.
    9. Claudius Gräbner & Philipp Heimberger & Jakob Kapeller & Florian Springholz, 2021. "Understanding economic openness: a review of existing measures," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(1), pages 87-120, February.
    10. Auer, Raphael A., 2016. "Comments on “Measuring openness to trade” by M.E. Waugh and B. Ravikumar," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 42-44.

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    More about this item

    Keywords

    Measurement; Openness; Trade potential; Sufficient statistics; Gains from trade; Volume of trade;
    All these keywords.

    JEL classification:

    • F11 - International Economics - - Trade - - - Neoclassical Models of Trade
    • F62 - International Economics - - Economic Impacts of Globalization - - - Macroeconomic Impacts
    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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