Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown
AbstractThe parameters in duration models are usually estimated by a Quasi Maximum Likelihood Estimator [QMLE]. This estimator is efficient if the errors are iid and exponentially distributed. Otherwise, it may not be the most efficient. Motivated by this, a class of estimators has been introduced by Drost and Werker (2004). Their estimator is asymptotically most efficient when the error distribution is unknown. However, the practical relevance of their method remains to be evaluated. Further, although some parameters in several common duration models are known to be nonnegative, this estimator may turn out to be negative. This paper addresses these two issues. We propose a new semiparametric estimator when there are inequality constraints on parameters, and a simulation study evaluates the two semiparametric estimators. The results lead us to conclude the following when the error distribution is unknown: (i) If there are no inequality constraints on parameters then the Drost-Werker estimator is better than the QMLE, and (ii) if there are inequality constraints on parameters then the estimator proposed in this paper is better than the Drost-Werker estimator and the QMLE. In conclusion, this paper recommends estimators that are better than the often used QMLE for estimating duration models.
Download InfoIf 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.
Bibliographic InfoPaper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 1/08.
Length: 29 pages
Date of creation: Jan 2008
Date of revision:
Contact details of provider:
Postal: PO Box 11E, Monash University, Victoria 3800, Australia
Web page: http://www.buseco.monash.edu.au/depts/ebs/
More information through EDIRC
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
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.:
- Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
- BAUWENS, Luc & GIOT, Pierre, .
"The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks,"
CORE Discussion Papers RP
-1497, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc BAUWENS & Pierre GIOT, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annales d'Economie et de Statistique, ENSAE, issue 60, pages 117-149.
- Newey, Whitney K, 1990. "Semiparametric Efficiency Bounds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 99-135, April-Jun.
- Drost, F.C. & Werker, B.J.M., 2004. "Semiparametric duration models," Open Access publications from Tilburg University urn:nbn:nl:ui:12-140875, Tilburg University.
- Drost, Feike C & Werker, Bas J M, 2004.
"Semiparametric Duration Models,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 22(1), pages 40-50, January.
- Shyamal D. Peddada & David B. Dunson & Xiaofeng Tan, 2005. "Estimation of order-restricted means from correlated data," Biometrika, Biometrika Trust, vol. 92(3), pages 703-715, September.
- Fernandes, Marcelo & Grammig, Joachim, 2006.
"A family of autoregressive conditional duration models,"
Journal of Econometrics,
Elsevier, vol. 130(1), pages 1-23, January.
- Fernandes, Marcelo & Grammig, Joachim, 2002. "A Family of Autoregressive Conditional Duration Models," Economics Working Papers (Ensaios Economicos da EPGE) 440, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
- Fernandes, Marcelo & Grammig, Joachim, 2003. "A family of autoregressive conditional duration models," Economics Working Papers (Ensaios Economicos da EPGE) 501, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
- FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," CORE Discussion Papers 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hammou El Barmi & Hari Mukerjee, 2005. "Inferences Under a Stochastic Ordering Constraint: The k-Sample Case," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 252-261, March.
- Shyamal D. Peddada & Joseph K. Haseman & Xiaofeng Tan & Greg Travlos, 2006. "Tests for a simple tree order restriction with application to dose-response studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 493-506.
- BAUWENS, Luc & ROMBOUTS, Jeroen V.K., .
CORE Discussion Papers RP
-1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Simone Grose).
If references are entirely missing, you can add them using this form.