Asymptotic convergence of weighted random matrices: nonparametric cointegration analysis for I(2) processes
AbstractThe aim of this paper is to provide a new perspective on the nonparametric co-integration analysis for integrated processes of the second order. Our analysis focus on a pair of random matrices related to such integrated process. Such matrices are constructed by introducing some weight functions. Under asymptotic conditions on such weights, convergence results in distribution are obtained. Therefore, a generalized eigenvalue problem is solved. Differential equations and stochastic calculus theory are used.
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Bibliographic InfoPaper provided by University of Molise, Dept. SEGeS in its series Economics & Statistics Discussion Papers with number esdp05027.
Length: 17 pages
Date of creation: 09 Sep 2005
Date of revision:
Co-integration; Nonparametric; Differential equations; Asymptotic properties.;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-09-29 (All new papers)
- NEP-ECM-2005-09-29 (Econometrics)
- NEP-ETS-2005-09-29 (Econometric Time Series)
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