View : 63 Download: 0

Nonparametric Testing for Long-Run Neutrality with Applications to US Money and Output Data

Title
Nonparametric Testing for Long-Run Neutrality with Applications to US Money and Output Data
Authors
Lee J.
Ewha Authors
이진
SCOPUS Author ID
이진scopus
Issue Date
2012
Journal Title
Computational Economics
ISSN
0927-7099JCR Link
Citation
vol. 40, no. 2, pp. 183 - 202
Indexed
SCIE; SSCI; SCOPUS WOS scopus
Abstract
We consider a nonparametric testing procedure for long-run monetary neutrality using spectral approaches. Long-run effects between bivariate integrated series are represented as the spectral density matrix of their first-differences evaluated at the zero frequency. The long-run neutrality, the core issue in this work, reduces to zero power of the cross spectral density function near the origin. We propose a statistic based on a kernel-based cross spectral density estimator. As designed to be consistent against cross correlations of unknown forms, the test differentiates it from tests based on parametric regression models. In implementing the tests, some feasible bandwidth selection procedures are detailed in terms of mean squared error criteria and of type I and type II errors criteria. Our testing procedures can be a complementary approach for neutrality testing. Simulation studies are shown to support theoretical results. Our methods are applied to testing long-run neutrality in the US nominal money and real output quarterly data from the first quarter of 1959 to the third quarter of 2009. Our tests unanimously reject the long-run neutrality for M2 regardless of the choice of bandwidths and of kernels. © 2011 Springer Science+Business Media, LLC.
DOI
10.1007/s10614-011-9270-2
Appears in Collections:
사회과학대학 > 경제학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE