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Sequential identification of technological news shocks

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  • Seymen, Atılım

Abstract

In an influential recent paper, Beaudry and Portier (2006) propose a sequential approach for identifying technological news shocks. Thereby, the correlation coefficient between news shocks of a short-run identification scheme and technology shocks of a long-run identification scheme in the VAR framework measures the extent to which news incorporated into forward-looking variables could reflect future technological developments. While structural VARs can potentially provide a useful guide for modelers as well as policy-makers, the ability of such models to recuperate structural shocks in general and news shocks in particular from the data is a contentious issue in the literature. In the current paper, I find by means of Monte Carlo simulations that the sequential approach can be quite successful in recuperating technological news shocks from artificial data.

Suggested Citation

  • Seymen, Atılım, 2013. "Sequential identification of technological news shocks," ZEW Discussion Papers 13-111, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:13111
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    References listed on IDEAS

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    More about this item

    Keywords

    News Shocks; Identification; Structural Vector Autoregressive Model;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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