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Forecasting national activity using lots of international predictors: an application to New Zealand

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Abstract

This paper examines the relationship between wages and consumer prices in New Zealand over the last 15 years. Reflecting the open nature of the New Zealand economy, the headline CPI is disaggregated into non-tradable and tradable prices. We find that there is a joint causality between wages and disaggregate inflation. An increase in wage inflation forecasts an increase in non-tradable inflation. However, it is tradable inflation that drives wage inflation. While exogenous shocks to wages do not help to forecast inflation, the leading relationship from wages to non-tradable inflation implies that monitoring wages may prove useful for projecting the impact of other shocks on future inflation.

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File URL: http://rbnz.govt.nz/research_and_publications/discussion_papers/2009/dp09_04.pdf
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Bibliographic Info

Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2009/04.

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Length: 54p
Date of creation: May 2009
Date of revision:
Handle: RePEc:nzb:nzbdps:2009/04

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Citations

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Cited by:
  1. Robert Lehmann & Klaus Wohlrabe, 2012. "Forecasting GDP at the Regional Level with Many Predictors," CESifo Working Paper Series 3956, CESifo Group Munich.
  2. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511.
  3. Halberstadt, Arne & Stapf, Jelena, 2012. "An affine multifactor model with macro factors for the German term structure: Changing results during the recent crises," Discussion Papers 25/2012, Deutsche Bundesbank, Research Centre.
  4. Eickmeier, Sandra & Ng, Tim, 2011. "How Do Credit Supply Shocks Propagate Internationally? A GVAR approach," CEPR Discussion Papers 8720, C.E.P.R. Discussion Papers.
  5. Schumacher, Christian, 2010. "Factor forecasting using international targeted predictors: The case of German GDP," Economics Letters, Elsevier, vol. 107(2), pages 95-98, May.
  6. Gianluca Cubadda & Barbara Guardabascio, 2010. "A Medium-N Approach to Macroeconomic Forecasting," CEIS Research Paper 176, Tor Vergata University, CEIS, revised 09 Dec 2010.
  7. Julieta Fuentes & Pilar Poncela & Julio Rodríguez, 2012. "Sparse partial least squares in time series for macroeconomic forecasting," Statistics and Econometrics Working Papers ws122216, Universidad Carlos III, Departamento de Estadística y Econometría.
  8. Kopoin, Alexandre & Moran, Kevin & Paré, Jean-Pierre, 2013. "Forecasting regional GDP with factor models: How useful are national and international data?," Economics Letters, Elsevier, vol. 121(2), pages 267-270.
  9. Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.

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