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On the long-run neutrality of demand shocks

Author

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  • Chen, Wenjuan
  • Netšunajev, Aleksei

Abstract

We revisit the seminal paper by Blanchard and Quah (1989) and investigate their long-run identification scheme. We use a structural VAR model with smoothly changing covariances for the identification of shocks. Formal testing rejects the long-run neutrality of demand shocks.

Suggested Citation

  • Chen, Wenjuan & Netšunajev, Aleksei, 2016. "On the long-run neutrality of demand shocks," Economics Letters, Elsevier, vol. 139(C), pages 57-60.
    • Handle: RePEc:eee:ecolet:v:139:y:2016:i:c:p:57-60
    DOI: 10.1016/j.econlet.2015.11.039
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    References listed on IDEAS

    as
    1. Markku Lanne & Helmut Lütkepohl, 2008. "Identifying Monetary Policy Shocks via Changes in Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1131-1149, September.
    2. Dornbusch, Rudiger & Frenkel, Jacob A, 1973. "Inflation and Growth: Alternative Approaches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 5(1), pages 141-156, Part I Fe.
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    4. John W. Keating, 2013. "What Do We Learn from Blanchard and Quah Decompositions If Aggregate Demand May Not be Long-Run Neutral?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201302, University of Kansas, Department of Economics.
    5. repec:hum:wpaper:sfb649dp2014-031 is not listed on IDEAS
    6. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    7. Baxter, Marianne & King, Robert G, 1993. "Fiscal Policy in General Equilibrium," American Economic Review, American Economic Association, vol. 83(3), pages 315-334, June.
    8. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    9. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    10. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
    11. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    12. Keating, John W., 2013. "What do we learn from Blanchard and Quah decompositions of output if aggregate demand may not be long-run neutral?," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 203-217.
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    Cited by:

    1. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Martin Bruns & Helmut Lütkepohl, 2024. "Heteroskedastic Structural Vector Autoregressions Identified via Long-run Restrictions," Discussion Papers of DIW Berlin 2103, DIW Berlin, German Institute for Economic Research.
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    5. repec:hum:wpaper:sfb649dp2016-015 is not listed on IDEAS
    6. Ngomba Bodi, Francis Ghislain, 2018. "Contributions relatives des chocs de demande agrégée et d’offre agrégée aux fluctuations de la croissance réelle en zone CEMAC [Relative contributions of aggregate demand and supply shocks to busin," MPRA Paper 116376, University Library of Munich, Germany.

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    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

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