Testing for equality of an increasing number of spectral density functions
Nowadays it is very frequent that a practitioner faces the problem of modelling large data sets. Relevant examples include spatio-temporal or panel data models with large N and T. In these cases deciding a particular dynamic model for each individual/population, which plays a crucial role in prediction and inferences, can be a very onerous and complex task. The aim of this paper is thus to examine a nonparametric test for the equality of the linear dynamic models as the number of individuals increases without bound. The test has two main features: (a) there is no need to choose any bandwidth parameter and (b) the asymptotic distribution of the test is a normal random variable.
|Date of creation:||Jun 2013|
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References listed on IDEAS
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- Peter C.B. Phillips & Hyungsik R. Moon, 1999.
"Linear Regression Limit Theory for Nonstationary Panel Data,"
Cowles Foundation Discussion Papers
1222, Cowles Foundation for Research in Economics, Yale University.
- Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
- Chang, Chung & Todd Ogden, R., 2009. "Bootstrapping sums of independent but not identically distributed continuous processes with applications to functional data," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1291-1303, July.
- Hidalgo, J. & Yajima, Y., 2002. "Prediction And Signal Extraction Of Strongly Dependent Processes In The Frequency Domain," Econometric Theory, Cambridge University Press, vol. 18(03), pages 584-624, June.
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