Measuring Output Gap: Is It Worth Your Time?
IMF Working Papers, February 7, 2020
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Bibliographic details
- Authors: Jiaqian Chen, Lucyna Gornicka
- Published: February 7, 2020
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781513527864.001
Summary
- Authors: Jiaqian Chen, Lucyna Gornicka
- Publication date: February 7, 2020
- Core finding: A structural VAR with an appropriate identification strategy provides improved estimates of the output gap with better real time properties and lower sensitivity to temporary shocks than usual filtering techniques.
- Additional outcome: The structural VAR produces smaller out-of-sample forecast errors for inflation.
- Cautionary note: Results suggest caution in basing policy decisions on output gap estimates.
Methods and Technical Findings
- Models applied: A range of models to U.K. data, including a structural vector autoregression (structural VAR) and usual filtering techniques.
- Advantages of structural VAR reported:
- Improved estimates of the output gap.
- Better real time properties.
- Lower sensitivity to temporary shocks.
- Smaller out-of-sample forecast errors for inflation compared with filtering techniques.
Policy Implications and Recommendations
- Primary policy implication: Exercise caution when using output gap estimates as the basis for policy decisions.
- Rationale: Even with improved estimation from structural VARs, uncertainty and sensitivity considerations warrant cautious interpretation for policy use.
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