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Methods versus substance: Measuring the effects of technology shocks

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  • Ríos-Rull, José-Víctor
  • Schorfheide, Frank
  • Fuentes-Albero, Cristina
  • Kryshko, Maxym
  • Santaeulàlia-Llopis, Raül

Abstract

Calibration and modern (Bayesian) estimation methods for a neoclassical stochastic growth model are applied to make the case that the identification of key parameters, rather than quantitative methodologies per se, is responsible for empirical findings. For concreteness, the model is used to measure the contributions of technology shocks to the business cycle fluctuations of hours worked and output. Along the way, new insights are provided in the parameter identification associated with likelihood-based estimation, the sensitivity of likelihood-based estimation to the choice of structural shocks is assessed, and Bayesian model averaging is used to aggregate findings obtained from different DSGE model specifications.

Suggested Citation

  • Ríos-Rull, José-Víctor & Schorfheide, Frank & Fuentes-Albero, Cristina & Kryshko, Maxym & Santaeulàlia-Llopis, Raül, 2012. "Methods versus substance: Measuring the effects of technology shocks," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 826-846.
  • Handle: RePEc:eee:moneco:v:59:y:2012:i:8:p:826-846
    DOI: 10.1016/j.jmoneco.2012.10.008
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    17. Kociecki, Andrzej, 2013. "Bayesian Approach and Identification," MPRA Paper 46538, University Library of Munich, Germany.
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    21. Dongya Koh & Raül Santaeulàlia-Llopis, 2017. "Countercyclical Elasticity of Substitution," Working Papers 946, Barcelona Graduate School of Economics.

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