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Regression Models with Mixed Sampling Frequencies

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Author Info

  • Elena Andreou
  • Eric Ghysels
  • Andros Kourtellos

Abstract

We study regression models that involve data sampled at different frequencies. We derive the asymptotic properties of the NLS estimators of such regression models and compare them with the LS estimators of a traditional model that involves aggregating or equally weighting data to estimate a model at the same sampling frequency. In addition we provide a new aggregation bias test. We explore the above theoretical aspects and verify them via an extensive Monte Carlo simulation study and an empirical application.

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Bibliographic Info

Paper provided by University of Cyprus Department of Economics in its series University of Cyprus Working Papers in Economics with number 8-2007.

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Length: 43 pages
Date of creation: Apr 2007
Date of revision:
Handle: RePEc:ucy:cypeua:8-2007

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Web page: http://www.econ.ucy.ac.cy

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References

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  1. Granger, C. W. J., 1987. "Implications of Aggregation with Common Factors," Econometric Theory, Cambridge University Press, vol. 3(02), pages 208-222, April.
  2. Peter C.B. Phillips, 1988. "Optimal Inference in Cointegrated Systems," Cowles Foundation Discussion Papers 866R, Cowles Foundation for Research in Economics, Yale University, revised Aug 1989.
  3. Phillips, P C B, 1974. "The Estimation of Some Continuous Time Models," Econometrica, Econometric Society, vol. 42(5), pages 803-23, September.
  4. Geweke, John F, 1978. "Temporal Aggregation in the Multiple Regression Model," Econometrica, Econometric Society, vol. 46(3), pages 643-61, May.
  5. Ben S. Bernanke & Refet S. Gürkaynak, 2002. "Is Growth Exogenous? Taking Mankiw, Romer, and Weil Seriously," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 11-72 National Bureau of Economic Research, Inc.
  6. Ghysels, Eric & Hall, Alastair, 1990. "Are consumption-based intertemporal capital asset pricing models structural?," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 121-139.
  7. Mankiw, N Gregory & Romer, David & Weil, David N, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 407-37, May.
  8. Sims, Christopher A, 1971. "Discrete Approximations to Continuous Time Distributed Lags in Econometrics," Econometrica, Econometric Society, vol. 39(3), pages 545-63, May.
  9. Robert F. Engle & Ta-Chung Liu, 1972. "Effects Of Aggregation Over Time On Dynamic Characteristics Of An Econometric Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Vols. 1 and 2, pages 673-738 National Bureau of Economic Research, Inc.
  10. Phillips, P. C. B., 1973. "The problem of identification in finite parameter continuous time models," Journal of Econometrics, Elsevier, vol. 1(4), pages 351-362, December.
  11. Phillips, P C B, 1972. "The Structural Estimation of a Stochastic Differential Equation System," Econometrica, Econometric Society, vol. 40(6), pages 1021-41, November.
  12. Hsiao, Cheng, 1979. "Linear regression using both temporally aggregated and temporally disaggregated data," Journal of Econometrics, Elsevier, vol. 10(2), pages 243-252, June.
  13. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
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Citations

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Cited by:
  1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  2. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
  3. Winkelried, Diego, 2012. "Predicting quarterly aggregates with monthly indicators," Working Papers 2012-023, Banco Central de Reserva del Perú.
  4. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
  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. Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers 2011-009, Federal Reserve Bank of St. Louis.
  7. Götz Thomas & Hecq Alain & Urbain Jean-Pierre, 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memoranda 012, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
  8. Götz Thomas B. & Hecq Alain & Urbain Jean-Pierre, 2012. "Real-Time Forecast Density Combinations (Forecasting US GDP Growth Using Mixed-Frequency Data)," Research Memoranda 021, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
  9. Ching Wai (Jeremy) Chiu & Bjørn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.
  10. Stefan Dercon & John Hoddinott & Tassew Woldehanna, 2011. "Growth and chronic poverty: Evidence from rural communities in Ethiopia," CSAE Working Paper Series 2011-18, Centre for the Study of African Economies, University of Oxford.
  11. Christian Schumacher, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 231(1), pages 28-49, February.
  12. Chen, Pu, 2009. "A Note on Updating Forecasts When New Information Arrives between Two Periods," Economics Discussion Papers 2009-22, Kiel Institute for the World Economy.
  13. Qian, Hang, 2010. "Linear regression using both temporally aggregated and temporally disaggregated data: Revisited," MPRA Paper 32686, University Library of Munich, Germany.
  14. Asgharian, Hossein & Hou, Ai Jun & Javed, Farrukh, 2013. "Importance of the macroeconomic variables for variance prediction A GARCH-MIDAS approach," Knut Wicksell Working Paper Series 2013/4, Knut Wicksell Centre for Financial Studies, Lund University.
  15. Qian, Hang, 2010. "Vector autoregression with varied frequency data," MPRA Paper 34682, University Library of Munich, Germany.
  16. Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 521-536.

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