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When trade drives markup divergence: An application to auto markets

Author

Listed:
  • Agnes Norris Keiller
  • Tim Obermeier
  • Andreas Teichgraeber
  • John Van Reenen

Abstract

When firms sell in multiple markets, estimates of markups from the demand-side will generally diverge from estimates based on the supply-side (e.g. via production functions). The empirical examination of the importance of this fact has been hampered by the absence of market-specific cost data. To overcome this, we show production markups can be expressed as the revenue-weighted average of demand-based markups across markets (and products). This highlights that a divergence in demand-based and production-based markups is due to the revenue shares and markups across foreign and domestic markets, factors that can be assessed with readily available trade data. Using data from auto firms producing in the UK, we show production-based markups increased between 1998 and 2018 whereas demand-based markups decreased. These trends can be reconciled by an increase in the markup that UK-based producers gained on their exports, which we corroborate using administrative trade data. We find that increases in production-based markups have been driven by exports, particularly to China where foreign brands command high markups. Data Disclaimer: parts of this work were produced using statistical data from the UK Office for National Statistics ("ONS"). The use of ONS data does not imply the endorsement of the ONS in relation to its interpretation or analysis. Analysis using ONS research datasets may not exactly reproduce ONS aggregates and was carried out in the Secure Research Service, part of the Office for National Statistics.

Suggested Citation

  • Agnes Norris Keiller & Tim Obermeier & Andreas Teichgraeber & John Van Reenen, 2024. "When trade drives markup divergence: An application to auto markets," CEP Discussion Papers dp2022, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp2022
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    File URL: https://cep.lse.ac.uk/pubs/download/dp2022.pdf
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