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Nowcasting causality in mixed frequency vector autoregressive models

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  • Götz T.B.
  • Hecq A.W.

    (GSBE)

Abstract

This paper introduces the notion of nowcasting causality for mixed-frequency VARs as the mixed-frequency version of instantaneous causality. We analyze the relationship between nowcasting and Granger causality in the mixed-frequency VAR setting of Ghysels 2012 and illustrate that nowcasting causality can have a crucial impact on the significance of contemporaneous or lagged high-frequency variables in standard MIDAS regression models.

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File URL: http://pub.maastrichtuniversity.nl/37088e93-e662-4b4f-ac0c-24ad95566637
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Bibliographic Info

Paper provided by Maastricht University, Graduate School of Business and Economics (GSBE) in its series Research Memorandum with number 050.

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Date of creation: 2013
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Handle: RePEc:unm:umagsb:2013050

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Keywords: Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models;

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  1. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
  2. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March.
  3. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
  4. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  5. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2012. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," CEPR Discussion Papers 8828, C.E.P.R. Discussion Papers.
  6. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
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Cited by:
  1. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," MPRA Paper 53699, University Library of Munich, Germany.
  2. Franco, Ray John Gabriel & Mapa, Dennis S., 2014. "The Dynamics of Inflation and GDP Growth: A Mixed Frequency Model Approach," MPRA Paper 55858, University Library of Munich, Germany.

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