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Boom or gloom? Examining the Dutch disease in two-speed economies

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  • Hilde C. Bjørnland
  • Leif Anders Thorsrud

Abstract

Traditional studies of the Dutch disease do not account for productivity spillovers between the booming resource sector and other domestic sectors. We put forward a simple theory model that allows for such spillovers. We then identify and quantify these spillovers using a Bayesian Dynamic Factor Model (BDFM). The model allows for resource movements and spending effects through a large panel of variables at the sectoral level, while also identifying disturbances to the commodity price, global demand and non-resource activity. Using Australia and Norway as representative cases studies, we find that a booming resource sector has substantial productivity spillovers on non-resource sectors, effects that have not been captured in previous analysis. That withstanding, there is also evidence of two-speed economies, with non-traded industries growing at a faster pace than traded. Furthermore, com- modity prices also stimulate the economy, but primarily if an increase is caused by higher global demand. Commodity price growth unrelated to global activity is less favourable, and for Australia, there is evidence of a Dutch disease effect with crowding out of the tradable sectors. As such, our results show the importance of distinguishing between windfall gains due to volume and price changes when analysing the Dutch disease hypothesis.

Suggested Citation

  • Hilde C. Bjørnland & Leif Anders Thorsrud, 2014. "Boom or gloom? Examining the Dutch disease in two-speed economies," Working Papers No 6/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Handle: RePEc:bny:wpaper:0024
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    Cited by:

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    2. International Monetary Fund, 2015. "Norway: Financial Sector Assessment Program-Technical Note- Macroprudential Policy," IMF Staff Country Reports 2015/257, International Monetary Fund.
    3. Norbu, Nyingtob, 2017. "Diagnosing the dutch disease: Are the symptoms present in Bhutan?," MPRA Paper 93249, University Library of Munich, Germany.
    4. International Monetary Fund, 2015. "Norway: Financial Sector Assessment Program-Technical Note-Linkages and Interconnectedness in the Norwegian Financial System," IMF Staff Country Reports 2015/256, International Monetary Fund.
    5. Luis N. Lanteri, 2015. "Efectos de la enfermedad holandesa ('Dutch disease'). Alguna evidencia para Argentina," Revista de Economía del Rosario, Universidad del Rosario, vol. 18(2), pages 187-209, December.
    6. Mohn, Klaus, 2015. "Resource revenue management and wealth neutrality," UiS Working Papers in Economics and Finance 2015/2, University of Stavanger.
    7. Marañon, Matias & Kumral, Mustafa, 2021. "Empirical analysis of Chile's copper boom and the Dutch Disease through causality and cointegration tests," Resources Policy, Elsevier, vol. 70(C).
    8. Nam T. Hoang & Bao H. Nguyen, 2018. "Oil and Iron Ore Price Shocks: What Are the Different Economic Effects in Australia?," The Economic Record, The Economic Society of Australia, vol. 94(305), pages 186-203, June.

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    More about this item

    Keywords

    Resource boom; commodity prices; Dutch disease; learning by doing; two-speed economy; Bayesian Dynamic Factor Model (BDFM);
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)

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