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The effect of aggregation on nonlinearity

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Listed:
  • Clive Granger
  • Tae-Hwy Lee

Abstract

This paper investigates the interaction between aggregation and nonlinearity through a monte carlo study. Various tests for neglected nonlinearity are used to compare the power of the tests for different nonlinear models to different levels of aggregation. Three types of aggregation, namely, cross-sectional aggregation, temporal aggregation and systematic sampling are considered. Aggregation is inclined to simplify nonlinearity. The degree to which nonlinearity is reduced depends on the importance of common factor and extent of the aggregation. The effect is larger when the size of common factor is smaller and when the extent of the aggregation is larger.

Suggested Citation

  • Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 259-269.
  • Handle: RePEc:taf:emetrv:v:18:y:1999:i:3:p:259-269
    DOI: 10.1080/07474939908800445
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    Citations

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    Cited by:

    1. Maria Simona Andreano & Giovanni Savio, 2002. "Further evidence on business cycle asymmetries in G7 countries," Applied Economics, Taylor & Francis Journals, vol. 34(7), pages 895-904.
    2. Pesaran, M. Hashem & Chudik, Alexander, 2014. "Aggregation in large dynamic panels," Journal of Econometrics, Elsevier, vol. 178(P2), pages 273-285.
    3. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," CORE Discussion Papers 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Denny Meyer & Rob J. Hyndman, 2005. "Rating Forecasts for Television Programs," Monash Econometrics and Business Statistics Working Papers 1/05, Monash University, Department of Econometrics and Business Statistics.
    5. Psaradakis Zacharias, 2000. "p-Value Adjustments for Multiple Tests for Nonlinearity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(3), pages 1-8, October.
    6. Sarno, Lucio & Taylor, Mark P. & Chowdhury, Ibrahim, 2004. "Nonlinear dynamics in deviations from the law of one price: a broad-based empirical study," Journal of International Money and Finance, Elsevier, vol. 23(1), pages 1-25, February.
    7. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    8. Lucio Sarno & Giorgio Valente & Hyginus Leon, 2006. "Nonlinearity in Deviations from Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle," Review of Finance, European Finance Association, vol. 10(3), pages 443-482, September.
    9. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
    10. G. Boero & E. Marrocu, 2000. "La performance di modelli non lineari per i tassi di cambio: un'applicazione con dati a diversa frequenza," Working Paper CRENoS 200014, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. Silva Lopes, Artur C. & Florin Zsurkis, Gabriel, 2017. "Are linear models really unuseful to describe business cycle data?," MPRA Paper 79413, University Library of Munich, Germany.
    12. Pavlidis, Efthymios & Martinez-Garcia, Enrique & Grossman, Valerie, 2017. "Detecting Periods of Exuberance: A Look at the Role of Aggregation with an Application to House Prices," Globalization and Monetary Policy Institute Working Paper 325, Federal Reserve Bank of Dallas, revised 01 Jul 2018.
    13. Silva Lopes, Artur C. & Florin Zsurkis, Gabriel, 2015. "Revisiting non-linearities in business cycles around the world," MPRA Paper 65668, University Library of Munich, Germany.
    14. Dramane Coulibaly & Hubert Kempf, 2017. "Inflation Targeting and the Forward Bias Puzzle in Emerging Countries," EconomiX Working Papers 2017-12, University of Paris Nanterre, EconomiX.
    15. Lopes, Artur Silva & Zsurkis, Gabriel Florin, 2017. "Are linear models really unuseful to describe business cycle data?," Economics Discussion Papers 2017-5, Kiel Institute for the World Economy (IfW).

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