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Functional cointegration: definition and nonparametric estimation

Author

Listed:
  • Banerjee Anurag

    (Durham University Business School, Mill Hill Lane, Durham, DH1 3LB, UK)

  • Pitarakis Jean-Yves

    () (University of Southampton, School of Social Sciences, Division of Economics, Highfield, Southampton, SO17 1BJ, UK)

Abstract

We formally define a concept of functional cointegration linking the dynamics of two time series via a functional coefficient. This is achieved through the use of a concept of summability as an alternative to I(1)’ness which is no longer suitable under nonlinear dynamics. We subsequently introduce a nonparametric approach for estimating the unknown functional coefficients. Our method is based on a piecewise local least squares principle and is computationally simple to implement. We establish its consistency properties and evaluate its performance in finite samples. We subsequently illustrate its usefulness through an application that explores linkages between stock prices and dividends via a sentiment indicator.

Suggested Citation

  • Banerjee Anurag & Pitarakis Jean-Yves, 2014. "Functional cointegration: definition and nonparametric estimation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 1-14, December.
  • Handle: RePEc:bpj:sndecm:v:18:y:2014:i:5:p:14:n:5
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    References listed on IDEAS

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    1. Hansen, Bruce E., 2008. "Uniform Convergence Rates For Kernel Estimation With Dependent Data," Econometric Theory, Cambridge University Press, vol. 24(03), pages 726-748, June.
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    7. Berenguer Rico, Vanessa & Gonzalo, Jesús, 2011. "Summability of stochastic processes: a generalization of integration and co-integration valid for non-linear processes," UC3M Working papers. Economics we1115, Universidad Carlos III de Madrid. Departamento de Economía.
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    Cited by:

    1. Guo-Liang Fan & Hong-Xia Xu & Zhen-Sheng Huang, 2016. "Empirical likelihood for semivarying coefficient model with measurement error in the nonparametric part," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(1), pages 21-41, January.

    More about this item

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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