The dynamics of perception: modelling subjective wellbeing in a short panel
We consider the issue of the dynamics of perceptions, as expressed in responses to survey questions on subjective wellbeing. We develop a simulated maximum likelihood method for estimation of dynamic linear models, where the dependent variable is partially observed through ordinal scales. This latent auto-regression model is often more appropriate than the usual state dependence model for attitudinal and interval variables. The paper contains an application to a model of households' perceptions of their financial wellbeing, demonstrating the superior fit of the latent auto-regression model to both the usual static model and the state dependence model. Copyright 2008 Royal Statistical Society.
Volume (Year): 171 (2008)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom|
Web page: http://wileyonlinelibrary.com/journal/rssa
More information through EDIRC
|Order Information:||Web: http://ordering.onlinelibrary.wiley.com/subs.asp?ref=1467-985X&doi=10.1111/(ISSN)1467-985X|
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.:
- Olympia Bover & Manuel Arellano, 1997. "Estimating limited dependent variable models from panel data," Investigaciones Economicas, Fundación SEPI, vol. 21(2), pages 141-166, May.
When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:171:y:2008:i:1:p:21-40. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
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.