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Borders, Geography and Oligopoly: Evidence from the Wind Turbine Industry

Author

Listed:
  • Paul Grieco

    (Pennsylvania State University)

  • A. Kerem Cosar

    (University of Chicago)

  • Felix Tintelnot

    (University of Chicago)

Abstract

Using a micro-level dataset of wind turbine installations in Denmark and Germany, we estimate a structural oligopoly model with cross-border trade and heterogeneous firms. Our approach separately identifies border-related from distance-related variable costs and bounds the fixed cost of exporting for each firm. In the data, firms' market shares drop precipitously at the border. We find that 40 to 50 percent of the gap can be attributed to national border costs. Counterfactual analysis indicates that eliminating national border frictions would increase total welfare in the wind turbine industry by 4 percent in Denmark and 6 percent in Germany.

Suggested Citation

  • Paul Grieco & A. Kerem Cosar & Felix Tintelnot, 2014. "Borders, Geography and Oligopoly: Evidence from the Wind Turbine Industry," 2014 Meeting Papers 143, Society for Economic Dynamics.
  • Handle: RePEc:red:sed014:143
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    3. Robert C. Feenstra & Philip Luck & Maurice Obstfeld & Katheryn N. Russ, 2018. "In Search of the Armington Elasticity," The Review of Economics and Statistics, MIT Press, vol. 100(1), pages 135-150, March.
    4. Jerónimo Carballo & Alejandro Graziano & Georg Schaur & Christian Volpe Martincus, 2021. "The Effects of Transit Systems on International Trade," CESifo Working Paper Series 9353, CESifo.
    5. Li, Jianglong & Lin, Boqiang, 2017. "Does energy and CO2 emissions performance of China benefit from regional integration?," Energy Policy, Elsevier, vol. 101(C), pages 366-378.
    6. Lu, Ruichang & Luo, Yao & Xiao, Ruli, 2014. "An MPEC estimator for misclassification models," Economics Letters, Elsevier, vol. 125(2), pages 195-199.
    7. Herz, Benedikt & Varela-Irimia, Xosé-Luís, 2016. "Border Effects in European Public Procurement," MPRA Paper 76401, University Library of Munich, Germany, revised 24 Jan 2017.
    8. John R. Birge & Ali Hortaçsu & J. Michael Pavlin, 2017. "Inverse Optimization for the Recovery of Market Structure from Market Outcomes: An Application to the MISO Electricity Market," Operations Research, INFORMS, vol. 65(4), pages 837-855, August.
    9. Roberto Rigobon & Brent Neiman & Alberto Cavallo, 2013. "Product Introductions, Currency Unions, and the Real Exchange Rate," 2013 Meeting Papers 1357, Society for Economic Dynamics.
    10. Alberto Cavallo & Brent Neiman & Roberto Rigobon, 2014. "Currency Unions, Product Introductions, and the Real Exchange Rate," The Quarterly Journal of Economics, Oxford University Press, vol. 129(2), pages 529-595.
    11. Chatterjee, S., 2019. "Market Power and Spatial Competition in Rural India," Cambridge Working Papers in Economics 1921, Faculty of Economics, University of Cambridge.
    12. Coşar, A. Kerem & Grieco, Paul L.E. & Tintelnot, Felix, 2015. "Bias in estimating border- and distance-related trade costs: Insights from an oligopoly model," Economics Letters, Elsevier, vol. 126(C), pages 147-149.

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    More about this item

    JEL classification:

    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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