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Evidence on a Real Business Cycle model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging

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  • Rodney W. Strachan

    ()

  • Herman K. van Dijk

    ()

Abstract

The empirical support for a real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure. This procedure makes use of a finite mixture of many models within the class of vector autoregressive (VAR) processes. The linear VAR model is extended to permit cointegration, a range of deterministic processes, equilibrium restrictions and restrictions on long-run responses to technology shocks. We find support for a number of the features implied by the real business cycle model. For example, restricting long run responses to identify technology shocks has reasonable support and important implications for the short run responses to these shocks. Further, there is evidence that savings and investment ratios form stable relationships, but technology shocks do not account for all stochastic trends in our system. There is uncertainty as to the most appropriate model for our data, with thirteen models receiving similar support, and the model or model set used has significant implications for the results obtained.

Suggested Citation

  • Rodney W. Strachan & Herman K. van Dijk, 2010. "Evidence on a Real Business Cycle model with Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging," ANU Working Papers in Economics and Econometrics 2010-522, Australian National University, College of Business and Economics, School of Economics.
  • Handle: RePEc:acb:cbeeco:2010-522
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    File URL: https://www.cbe.anu.edu.au/researchpapers/econ/wp522.pdf
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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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

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