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Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?

Author

Listed:
  • Markku Lanne
  • Jani Luoto

Abstract

type="main" xml:id="obes12041-abs-0001"> We propose a new methodology for ranking in probability the commonly proposed drivers of inflation in the new Keynesian model. The approach is based on Bayesian model selection among restricted vector autoregressive (VAR) models, each of which embodies only one or none of the candidate variables as the driver. Simulation experiments suggest that our procedure is superior to the previously used conventional pairwise Granger causality tests in detecting the true driver. Empirical results lend little support to labour share, output gap or unemployment rate as the driver of US inflation.

Suggested Citation

  • Markku Lanne & Jani Luoto, 2014. "Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 715-726, October.
    • Handle: RePEc:bla:obuest:v:76:y:2014:i:5:p:715-726
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    File URL: http://hdl.handle.net/10.1111/obes.2014.76.issue-5
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    Cited by:

    1. Narayan, Seema & Cirikisuva, Salote & Naivutu, Revoni, 2023. "A hybrid NKPC inflation model for the small Island state of Fiji," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 873-886.
    2. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    3. Dustin Chambers & Courtney A. Collins & Alan Krause, 2019. "How do federal regulations affect consumer prices? An analysis of the regressive effects of regulation," Public Choice, Springer, vol. 180(1), pages 57-90, July.
    4. Błażej, Mirosław & Górajski, Mariusz & Ulrichs, Magdalena, 2025. "Microdata-based output gap estimation using business tendency surveys," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    5. Narayan, Paresh Kumar & Narayan, Seema & Eki Rahman, R. & Setiawan, Iwan, 2019. "Bitcoin price growth and Indonesia's monetary system," Emerging Markets Review, Elsevier, vol. 38(C), pages 364-376.

    More about this item

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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