Instrumental variables and wavelet decompositions
The application of wavelet analysis provides an orthogonal decomposition of a time series by time scale, thereby facilitating the decomposition of a data series into the sum of a structural component and a random error component. The structural components revealed by the wavelet analysis yield nearly ideal instrumental variables for variables observed with error and for co-endogenous variables in simultaneous equation models. Wavelets also provide an efficient way to explore the path of the structural component of the series to be analyzed and can be used to detect some specification errors. The methodology described in this paper is applied to the errors in variables problem and simultaneous equations case using some simulation exercises and to the analysis of a version of the Phillips curve with interesting results.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- James Ramsey, 1999. "Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 163-184.
- Mark Gertler & Jordi Gali & Richard Clarida, 1999.
"The Science of Monetary Policy: A New Keynesian Perspective,"
Journal of Economic Literature,
American Economic Association, vol. 37(4), pages 1661-1707, December.
- Clarida, R. & Gali, J. & Gertler, M., 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Working Papers 99-13, C.V. Starr Center for Applied Economics, New York University.
- Richard Clarida & Jordi Galí & Mark Gertler, 1997. "The science of monetary policy: A new Keynesian perspective," Economics Working Papers 356, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 1999.
- Richard Clarida & Jordi Gali & Mark Gertler, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," NBER Working Papers 7147, National Bureau of Economic Research, Inc.
- Clarida, Richard & Galí, Jordi & Gertler, Mark, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," CEPR Discussion Papers 2139, C.E.P.R. Discussion Papers.
- Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
- Ramsay, James O. & Ramsey, James B., 2002. "Functional data analysis of the dynamics of the monthly index of nondurable goods production," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 327-344, March.
- Jordi Gali & Mark Gertler, 2000.
"Inflation Dynamics: A Structural Econometric Analysis,"
NBER Working Papers
7551, National Bureau of Economic Research, Inc.
- Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
- Jordi Galí & Mark Gertler, 1998. "Inflation dynamics: A structural econometric analysis," Economics Working Papers 341, Department of Economics and Business, Universitat Pompeu Fabra.
- Jinyong Hahn & Jerry Hausman, 2003. "Weak Instruments: Diagnosis and Cures in Empirical Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 118-125, May.
When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:27:y:2010:i:6:p:1498-1513. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.