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An Unintended Consequence of Using "Errors in Variables Shocks" in DSGE Models?

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  • Adrian Pagan

    (Sydney Uni)

Abstract

This note shows that the common practice of adding on measurement errors or "errors in variables" when estimating DSGE models can imply that there is a lack of co-integration between model and data variables and also between data variables themselves. An analysis is provided of what the nature of the measurement error would be if it was desired to ensure co-integration. It is very unlikely that it would be the white noise shocks that are commonly used.

Suggested Citation

  • Adrian Pagan, 2016. "An Unintended Consequence of Using "Errors in Variables Shocks" in DSGE Models?," NCER Working Paper Series 114, National Centre for Econometric Research.
    • Handle: RePEc:qut:auncer:2016_05
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    File URL: http://www.ncer.edu.au/papers/documents/WP114.pdf
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    References listed on IDEAS

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    1. Daniel M. Rees & Penelope Smith & Jamie Hall, 2016. "A Multi-sector Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 92(298), pages 374-408, September.
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    Cited by:

    1. Fabio Canova & Christian Matthes, 2021. "A Composite Likelihood Approach for Dynamic Structural Models," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2447-2477.

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    Keywords

    DSGE models; shocks;

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