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Qatar's LNG Economy: From Price-Driven Dependency to Supply Shock Risk

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  • Ansar, Muhammad Uzair

Abstract

This research covers Qatar's LNG-driven export economy from 2010 to 2025, with a scenario analysis for a supply shock in 2026. The dataset draws on GDP figures from the World Bank national accounts¹, total export values from World Bank trade indicators², LNG production volumes from the Energy Institute Statistical Review³, and LNG price series from Macrotrends Asia LNG (JKM) data⁴. The full compiled dataset is in Appendix A. The defining pattern across the sixteen years is a stark contrast: LNG export volumes were broadly stable — rising gradually from around 2,746 MMBtu million in 2010 to roughly 3,700–3,900 MMBtu million by the mid2010s and holding there — while revenues swung from $16.42 billion in 2020 to $129.88 billion in 2022. The LNG Export-to-GDP ratio mirrored this: up from 20.77% in 2010 to 55.03% in 2022, then back to ~20% by 2024–2025 — tracking the global LNG price cycle almost exactly. At its peak, more than half of Qatar's entire GDP was effectively attributable to a single commodity whose price it does not control. The 2026 attack on Ras Laffan introduces a different kind of problem. A 17% capacity reduction means annual LNG revenue losses of around $20 billion — not because prices have fallen, but because the infrastructure to produce and liquefy the gas is no longer fully operational. The LNG/GDP ratio will remain suppressed until capacity is rebuilt, which could take three to five years.

Suggested Citation

  • Ansar, Muhammad Uzair, 2026. "Qatar's LNG Economy: From Price-Driven Dependency to Supply Shock Risk," MPRA Paper 129324, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:129324
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    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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