Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Zellner, Arnold & Rossi, Peter E., 1984. "Bayesian analysis of dichotomous quantal response models," Journal of Econometrics, Elsevier, vol. 25(3), pages 365-393, July.
- Han C. & Carlin B. P., 2001. "Markov Chain Monte Carlo Methods for Computing Bayes Factors: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1122-1132, September.
- J. Durbin & S. J. Koopman, 2000.
"Time series analysis of non‐Gaussian observations based on state space models from both classical and Bayesian perspectives,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 3-56.
- Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Other publications TiSEM 6338af09-6f2c-46d0-985b-d, Tilburg University, School of Economics and Management.
- Durbin, J. & Koopman, S.J.M., 1998. "Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives," Discussion Paper 1998-142, Tilburg University, Center for Economic Research.
- Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Kadane, Joseph B. & Lazar, Nicole A., 2004. "Methods and Criteria for Model Selection," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 279-290, January.
- Sylvia FrüHwirth-Schnatter & Helga Wagner, 2006. "Auxiliary mixture sampling for parameter-driven models of time series of counts with applications to state space modelling," Biometrika, Biometrika Trust, vol. 93(4), pages 827-841, December.
- Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
- Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
- Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Bauwens, Luc & Rombouts, Jeroen V.K., 2012.
"On marginal likelihood computation in change-point models,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
- Luc Bauwens & Jeroen V.K. Rombouts, 2009. "On Marginal Likelihood Computation in Change-point Models," Cahiers de recherche 0942, CIRPEE.
- BAUWENS, Luc & ROMBOUTS, Jeroen VK, 2012. "On marginal likelihood computation in change-point models," LIDAM Reprints CORE 2403, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & ROMBOUTS, Jeroen, 2009. "On marginal likelihood computation in change-point models," LIDAM Discussion Papers CORE 2009061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Joshua C. C. Chan & Eric Eisenstat, 2015.
"Marginal Likelihood Estimation with the Cross-Entropy Method,"
Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 256-285, March.
- Joshua C C Chan & Eric Eisenstat, 2012. "Marginal Likelihood Estimation with the Cross-Entropy Method," CAMA Working Papers 2012-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chan, Joshua & Eisenstat, Eric, 2012. "Marginal Likelihood Estimation with the Cross-Entropy Method," MPRA Paper 40051, University Library of Munich, Germany.
- Hajargasht, Gholamreza & Rao, D.S. Prasada, 2019.
"Multilateral index number systems for international price comparisons: Properties, existence and uniqueness,"
Journal of Mathematical Economics, Elsevier, vol. 83(C), pages 36-47.
- Gholamreza Hajargasht & Prasada Rao, 2018. "Multilateral Index Number Systems for International Price Comparisons: Properties, Existence and Uniqueness," Papers 1811.04197, arXiv.org, revised Dec 2018.
- Gholamreza Hajargasht & D.S. Prasada Rao, 2019. "Multilateral Index Number Systems for International Price Comparisons: Properties, Existence and Uniqueness," CEPA Working Papers Series WP032019, School of Economics, University of Queensland, Australia.
- Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
- Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
- Bijwaard, Govert E. & Franses, Philip Hans, 2009. "The effect of rounding on payment efficiency," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1449-1461, February.
- Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012.
"A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
- David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
- Reichl Johannes, 2020. "Estimating marginal likelihoods from the posterior draws through a geometric identity," Monte Carlo Methods and Applications, De Gruyter, vol. 26(3), pages 205-221, September.
- Jamie L. Cross & Aubrey Poon, 2020. "On the contribution of international shocks in Australian business cycle fluctuations," Empirical Economics, Springer, vol. 59(6), pages 2613-2637, December.
- Joshua C. C. Chan, 2020.
"Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
- Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2012.
"A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation,"
Journal of Econometrics, Elsevier, vol. 171(2), pages 101-120.
- Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 12-026/4, Tinbergen Institute.
- Koop, Gary & Korobilis, Dimitris, 2010.
"Bayesian Multivariate Time Series Methods for Empirical Macroeconomics,"
Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
- Gary Koop & Dimitris Korobilis, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Working Paper series 47_09, Rimini Centre for Economic Analysis.
- Koop, Gary & Korobilis, Dimitris, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," MPRA Paper 20125, University Library of Munich, Germany.
- Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020.
"Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model,"
OECD Statistics Working Papers
2020/01, OECD Publishing.
- Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
- Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," PSE Working Papers halshs-02443364, HAL.
- Junior A. Ojeda Cunya & Gabriel Rodríguez, 2022. "Time-Varying Effects of External Shocks on Macroeconomic Fluctuations in Peru: An Empirical Application using TVP-VAR- SV Models," Documentos de Trabajo / Working Papers 2022-507, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Chan, Joshua C.C. & Koop, Gary, 2014.
"Modelling breaks and clusters in the steady states of macroeconomic variables,"
Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 186-193.
- Chan, Joshua C.C. & Koop, Gary, 2011. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," SIRE Discussion Papers 2011-22, Scottish Institute for Research in Economics (SIRE).
- Joshua C.C. Chan & Gary Koop, 2013. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," ANU Working Papers in Economics and Econometrics 2013-603, Australian National University, College of Business and Economics, School of Economics.
- Joshua C C Chan & Gary Koop, 2012. "Modelling breaks and clusters in the steady states of macroeconomic variables," CAMA Working Papers 2012-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Gary Koop & Joshua Chan, 2011. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," Working Papers 1111, University of Strathclyde Business School, Department of Economics.
- Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
- Chan, Joshua C.C. & Grant, Angelia L., 2015.
"Pitfalls of estimating the marginal likelihood using the modified harmonic mean,"
Economics Letters, Elsevier, vol. 131(C), pages 29-33.
- Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022.
"An automated prior robustness analysis in Bayesian model comparison,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
- Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Rodriguez, Gabriel & Castillo B., Paul & Calero, Roberto & Salcedo Cisneros, Rodrigo & Ataurima Arellano, Miguel, 2024.
"Evolution of the exchange rate pass-through into prices in Peru: An empirical application using TVP-VAR-SV models,"
Journal of International Money and Finance, Elsevier, vol. 142(C).
- Roberto Calero & Gabriel Rodríguez & Rodrigo Salcedo Cisneros, 2022. "Evolution of the Exchange Rate Pass-Throught into Prices in Peru: An Empirical Application Using TVP-VAR-SV Models," Documentos de Trabajo / Working Papers 2022-510, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Sylvia Frühwirth-Schnatter & Gertraud Malsiner-Walli, 2019. "From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 33-64, March.
- Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
- Pacifico, Antonio, 2020. "Structural Panel Bayesian VAR with Multivariate Time-varying Volatility to jointly deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," MPRA Paper 104292, University Library of Munich, Germany.
- Joshua C. C. Chan, 2018.
"Specification tests for time-varying parameter models with stochastic volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 807-823, September.
- Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan & Eric Eisenstat, 2018.
"Bayesian model comparison for time‐varying parameter VARs with stochastic volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
- Joshua C.C. Chan & Eric Eisenstat, 2015. "Bayesian model comparison for time-varying parameter VARs with stochastic volatility," CAMA Working Papers 2015-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2018. "Does time-variation matter in the stochastic volatility components for G7 stock returns," Working Papers 062, Centre for Econometric and Allied Research, University of Ibadan.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Nakajima, Jouchi & Kunihama, Tsuyoshi & Omori, Yasuhiro & Frühwirth-Schnatter, Sylvia, 2012.
"Generalized extreme value distribution with time-dependence using the AR and MA models in state space form,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3241-3259.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruwirth-Scnatter, 2009. "Generalized Extreme Value Distribution with Time-Dependence Using the AR and MA Models in State Space Form," IMES Discussion Paper Series 09-E-32, Institute for Monetary and Economic Studies, Bank of Japan.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruhwirth-Schnatter, 2011. "Generalized Extreme Value Distribution with Time-Dependence Using the AR and MA Models in State Space Form," CIRJE F-Series CIRJE-F-782, CIRJE, Faculty of Economics, University of Tokyo.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruhwirth-Schnatter, 2009. "Generalized extreme value distribution with time-dependence using the AR and MA models in state space form," CIRJE F-Series CIRJE-F-689, CIRJE, Faculty of Economics, University of Tokyo.
- Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
- Drew Creal, 2012.
"A Survey of Sequential Monte Carlo Methods for Economics and Finance,"
Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 245-296.
- Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- István Barra & Agnieszka Borowska & Siem Jan Koopman, 2018.
"Bayesian Dynamic Modeling of High-Frequency Integer Price Changes,"
Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 384-424.
- Istvan Barra & Siem Jan Koopman & Agnieszka Borowska, 2016. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Tinbergen Institute Discussion Papers 16-028/III, Tinbergen Institute, revised 16 Feb 2018.
- Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
- Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
- McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
- Mesters, G. & Koopman, S.J., 2014.
"Generalized dynamic panel data models with random effects for cross-section and time,"
Journal of Econometrics, Elsevier, vol. 180(2), pages 127-140.
- Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
- Garland Durham, 2004. "Likelihood-based estimation and specification analysis of one- and two-factor SV models with leverage effects," Econometric Society 2004 North American Summer Meetings 294, Econometric Society.
- Deschamps, Philippe J., 2011.
"Bayesian estimation of an extended local scale stochastic volatility model,"
Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
- Deschamps, Philippe J., 2009. "Bayesian estimation of an extended local scale stochastic volatility model," DQE Working Papers 15, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 12 Nov 2011.
- Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
- Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004.
"Stochastic Volatility with Leverage: Fast Likelihood Inference,"
CIRJE F-Series
CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
- Neil Shephard & Yashurio Omori & Faculty of Economics & University of Tokyo & Siddhartha Chib & Olin School of Business & Washington University & Jouchi Nakajima & Faculty of Economics & University of, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Series Working Papers 2004-FE-16, University of Oxford, Department of Economics.
- Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Papers 2004-W19, Economics Group, Nuffield College, University of Oxford.
- Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
- Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2017.
"Bayesian modeling of dynamic extreme values: extension of generalized extreme value distributions with latent stochastic processes,"
Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(7), pages 1248-1268, May.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-952, CIRJE, Faculty of Economics, University of Tokyo.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-952, CIRJE, Faculty of Economics, University of Tokyo.
- Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.
- Nakajima, Jouchi & Omori, Yasuhiro, 2009.
"Leverage, heavy-tails and correlated jumps in stochastic volatility models,"
Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
- Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," CIRJE F-Series CIRJE-F-514, CIRJE, Faculty of Economics, University of Tokyo.
- Siem Jan Koopman & André Lucas & Marcel Scharth, 2015.
"Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 114-127, January.
- Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
- Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2012.
"Efficient estimation and particle filter for max‐stable processes,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 61-80, January.
- Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2011. "Efficient estimation and particle filter for max-stable processes," CIRJE F-Series CIRJE-F-791, CIRJE, Faculty of Economics, University of Tokyo.
- Osman Doğan & Süleyman Taşpınar & Anil K. Bera, 2021. "Bayesian estimation of stochastic tail index from high-frequency financial data," Empirical Economics, Springer, vol. 61(5), pages 2685-2711, November.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:52:y:2008:i:10:p:4608-4624. See general information about how to correct material in RePEc.
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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.