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Mapping trade to household budget survey: A conversion framework for assessing the distributional impact of trade policies

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  • Nhung Luu
  • Nicolas Woloszko
  • Orsetta Causa
  • Christine Arriola
  • Frank van Tongeren
  • Åsa Johansson

Abstract

Whether gains from trade are equally distributed within countries is the subject of a lively debate. This paper presents a novel framework to analyse the distributional effects of trade policy by linking the OECD’s CGE trade model, METRO, with consumption expenditure data from household budget surveys. Specifically, this paper describes a methodology to produce a concordance and transition matrix linking GTAP sectors to household survey classifications based on the Classification of Individual Consumption According to Purpose (COICOP). A mapping methodology is an important pre-requisite for investigating research questions concerning the influence of household behaviour changes on trade, as well as trade developments and policy on household welfare. The paper provides an illustration of the mapping of trade policy induced price changes onto household expenditures by conducting stylized tariff simulations with METRO and translating those into household expenditures by income decile for selected EU countries.

Suggested Citation

  • Nhung Luu & Nicolas Woloszko & Orsetta Causa & Christine Arriola & Frank van Tongeren & Åsa Johansson, 2020. "Mapping trade to household budget survey: A conversion framework for assessing the distributional impact of trade policies," OECD Trade Policy Papers 244, OECD Publishing.
    • Handle: RePEc:oec:traaab:244-en
    DOI: 10.1787/5fc6181b-en
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    1. David H. Autor & David Dorn & Gordon H. Hanson & Jae Song, 2014. "Trade Adjustment: Worker-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(4), pages 1799-1860.
    2. Janos Ferencz, 2019. "The OECD Digital Services Trade Restrictiveness Index," OECD Trade Policy Papers 221, OECD Publishing.
    3. Pablo D. Fajgelbaum & Amit K. Khandelwal, 2016. "Measuring the Unequal Gains from Trade," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1113-1180.
    4. Colin J. Hottman & Ryan Monarch, 2018. "Estimating Unequal Gains across U.S. Consumers with Supplier Trade Data," International Finance Discussion Papers 1220, Board of Governors of the Federal Reserve System (U.S.).
    5. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    6. Olivier Cadot & Julien Gourdon & Frank van Tongeren, 2018. "Estimating Ad Valorem Equivalents of Non-Tariff Measures: Combining Price-Based and Quantity-Based Approaches," OECD Trade Policy Papers 215, OECD Publishing.
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    Cited by:

    1. Hübler, Michael & Wiese, Malin & Braun, Marius & Damster, Johannes, 2024. "The distributional effects of CO2 pricing at home and at the border on German income groups," Resource and Energy Economics, Elsevier, vol. 77(C).
    2. Orsetta Causa & Emilia Soldani & Nhung Luu, 2023. "A cost-of-living squeeze? Distributional implications of rising inflation," Public Sector Economics, Institute of Public Finance, vol. 47(4), pages 431-460.

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    More about this item

    Keywords

    Household expenditure microdata; Inequality; modelling; Trade policy;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • F13 - International Economics - - Trade - - - Trade Policy; International Trade Organizations
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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