Feasible Estimation in Cointegrated Panels
AbstractIn this paper we propose a simple procedure for data dependent determination of the number of lags and leads to use in feasible estimation of cointegrated panel regressions. Results from Monte Carlo simulations suggests that the feasible estimators considered enjoys excellent precision in terms of root mean squared error and reasonable power with effective size hovering close to the nominal level. The good performance of the feasible estimators is verified empirically through an application to the long run money demand.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Lund University, Department of Economics in its series Working Papers with number 2003:12.
Length: 8 pages
Date of creation: 16 Aug 2003
Date of revision: 10 Nov 2003
Publication status: Published in Oxford Bulletin of Economics and Statistics, 2005, pages 691-705.
Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/en
More information through EDIRC
Panel Cointegration Estimation; Monte Carlo Simulation;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
This paper has been announced in the following NEP Reports:
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.:
- Peter C.B. Phillips & Chi-Young Choi & Donggyu Sul, 2004.
"Prewhitening Bias in HAC Estimation,"
Yale School of Management Working Papers
ysm426, Yale School of Management.
- Nelson C. Mark & Donggyu Sul, 2003.
"Cointegration Vector Estimation by Panel DOLS and Long-run Money Demand,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 65(5), pages 655-680, December.
- Nelson C. Mark & Donggyu Sul, 2002. "Cointegration Vector Estimation by Panel DOLS and Long-Run Money Demand," NBER Technical Working Papers 0287, National Bureau of Economic Research, Inc.
- Tom Doan, . "RATS programs to replicate Mark-Sul(2003) panel DOLS," Statistical Software Components RTZ00112, Boston College Department of Economics.
- Campbell, J.Y. & Perron, P., 1991.
"Pitfalls and Opportunities: What Macroeconomics should know about unit roots,"
360, Princeton, Department of Economics - Econometric Research Program.
- John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
- John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Technical Working Papers 0100, National Bureau of Economic Research, Inc.
- Campbell, John & Perron, Pierre, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," Scholarly Articles 3374863, Harvard University Department of Economics.
- Donald W.K. Andrews & Christopher J. Monahan, 1990.
"An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator,"
Cowles Foundation Discussion Papers
942, Cowles Foundation for Research in Economics, Yale University.
- Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
- repec:cup:etheor:v:10:y:1994:i:1:p:95-115 is not listed on IDEAS
- Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2005.
"Dynamic Seemingly Unrelated Cointegrating Regressions,"
Review of Economic Studies,
Oxford University Press, vol. 72(3), pages 797-820.
- Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2003. "Dynamic Seemingly Unrelated Cointegrating Regression," NBER Technical Working Papers 0292, National Bureau of Economic Research, Inc.
- Masao Ogaki & Nelson Mark & Donggyu Sul, 2004. "Dynamic Seemingly Unrelated Cointegrating Regression," Working Papers 04-02, Ohio State University, Department of Economics.
- Shin, Yongcheol, 1994. "A Residual-Based Test of the Null of Cointegration Against the Alternative of No Cointegration," Econometric Theory, Cambridge University Press, vol. 10(01), pages 91-115, March.
- Dreger, Christian & Reimers, Hans-Eggert & Roffia, Barbara, 2006.
"Long-run money demand in the new EU Member States with exchange rate effects,"
Working Paper Series
0628, European Central Bank.
- Christian Dreger & Hans-Eggert Reimers & Barbara Roffia, 2007. "Long-Run Money Demand in the New EU Member States with Exchange Rate Effects," Eastern European Economics, M.E. Sharpe, Inc., vol. 45(2), pages 75-94, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (David Edgerton).
If references are entirely missing, you can add them using this form.