Publication Type
Journal Article
Version
acceptedVersion
Publication Date
2-2023
Abstract
Multicointegration is traditionally defined as a particular long run relationship among variables in a parametric vector autoregressive model that introduces additional cointegrating links between these variables and partial sums of the equilibrium errors. This paper departs from the parametric model, using a semiparametric formulation that reveals the explicit role that singularity of the long run conditional covariance matrix plays in determining multicointegration. The semiparametric framework has the advantage that short run dynamics do not need to be modeled and estimation by standard techniques such as fully modified least squares (FM-OLS) on the original system is straightforward. The paper derives FM-OLS limit theory in the multicointegrated setting, showing how faster rates of convergence are achieved in the direction of singularity and that the limit distribution depends on the distribution of the conditional one-sided long run covariance estimator used in FM-OLS estimation. Wald tests of restrictions on the regression coefficients have nonstandard limit theory which depends on nuisance parameters in general. The usual tests are shown to be conservative when the restrictions are isolated to the directions of singularity and, under certain conditions, are invariant to singularity otherwise. Simulations show that approximations derived in the paper work well in finite samples. The findings are illustrated empirically in an analysis of fiscal sustainability of the US government over the post-war period.
Keywords
cointegration, multicointegration, fully modified regression, singular long run variance matrix, degenerate Wald test, fiscal sustainability
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
232
Issue
2
First Page
300
Last Page
319
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2021.07.002
Publisher
Elsevier
Embargo Period
10-27-2023
Citation
KHEIFETS, Igor L. and PHILLIPS, Peter C. B..
Fully modified least squares cointegrating parameter estimation in multicointegrated systems. (2023). Journal of Econometrics. 232, (2), 300-319.
Available at: https://ink.library.smu.edu.sg/soe_research/2691
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2021.07.002