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Nowcasting from disaggregates in the face of location shifts

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  • Jennifer L. Castle

    (Department of Economics, Oxford University, Oxford, UK)

  • David F. Hendry

    (Department of Economics, Oxford University, Oxford, UK)

Abstract

Given a need for nowcasting, we consider how nowcasts can best be achieved, the use and timing of information, including disaggregation over variables and common features, and the role of automatic model selection for nowcasting missing disaggregates. We focus on the impact of location shifts on nowcast failure and nowcasting during breaks, using impulse saturation, its relation to intercept correction, and to robust methods to avoid systematic nowcast failure. We propose a nowcasting strategy, building models of all N disaggregate series by automatic methods, forecasting every variable each period, then testing for shifts in available measures, switching to robust forecasts of missing series when breaks are detected. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.
  • Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:200-214
    DOI: 10.1002/for.1140
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    File URL: http://hdl.handle.net/10.1002/for.1140
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    References listed on IDEAS

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    1. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
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    6. Michael P. Clements & David F. Hendry, 2005. "Guest Editors' Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
    7. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    8. Jennifer L. Castle & Nicholas W.P. Fawcett & David F. Hendry, 2009. "Nowcasting Is Not Just Contemporaneous Forecasting," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 71-89, October.
    9. Clements Michael P. & Hendry David F., 2008. "Economic Forecasting in a Changing World," Capitalism and Society, De Gruyter, vol. 3(2), pages 1-20, October.
    10. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    11. Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
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    Citations

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    Cited by:

    1. Cai, Charlie X. & Kyaw, Khine & Zhang, Qi, 2012. "Stock index return forecasting: The information of the constituents," Economics Letters, Elsevier, vol. 116(1), pages 72-74.
    2. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    3. Espasa, Antoni & Carlomagno, Guillermo, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. repec:spr:jbuscr:v:12:y:2016:i:1:d:10.1007_s41549-016-0005-2 is not listed on IDEAS
    5. Neil Ericsson & Erica Reisman, 2012. "Evaluating a Global Vector Autoregression for Forecasting," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 18(3), pages 247-258, August.
    6. Brüggemann, Ralf & Lütkepohl, Helmut, 2013. "Forecasting contemporaneous aggregates with stochastic aggregation weights," International Journal of Forecasting, Elsevier, vol. 29(1), pages 60-68.
    7. repec:kap:iaecre:v:18:y:2012:i:3:p:247-258 is not listed on IDEAS
    8. Espasa, Antoni & Carlomagno, Guillermo, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    10. Jennifer Castle & David Hendry, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    11. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo Group Munich.
    12. Espasa, Antoni & Carlomagno Real, Guillermo, 2017. "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS 25392, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, Department of Economics, Research Program on Forecasting.
    14. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.

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