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Analysing shock transmission in a data-rich environment: a large BVAR for New Zealand

  • Chris Bloor
  • Troy Matheson

    ()

We analyse a large Bayesian Vector Autoregression (BVAR) containing almost one hundred New Zealand macroeconomic time series. Methods for allowing multiple blocks of equations with block-specific Bayesian priors are described, and forecasting results show that our model compares favourably to a range of other time series models. Examining the impulse responses to a monetary policy shock and to two less conventional shocks – net migration and the climate – we highlight the usefulness of the large BVAR in analysing shock transmission.

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File URL: http://hdl.handle.net/10.1007/s00181-009-0317-3
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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 39 (2010)
Issue (Month): 2 (October)
Pages: 537-558

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Handle: RePEc:spr:empeco:v:39:y:2010:i:2:p:537-558
DOI: 10.1007/s00181-009-0317-3
Contact details of provider: Web page: http://www.springer.com

Order Information: Web: http://www.springer.com/economics/econometrics/journal/181/PS2

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