Dynamic food demand and habit forming behaviors: Bayesian approach to a Dynamic Tobit panel data model with unobserved heterogeneity
Incorporating dynamics such as habit formation in analysis of demand can make estimation more reliable and help to explain the “stickiness” in consumer demand behavior when consumers receive new information about products, such as a food safety event or recall. Scanner data allow many repeated observations of the same household so are ideal for analyzing the impact of habit on demand. In addition to that, scanner data allow us to easily observe the presence of zero purchases. The presence of zero purchases is an important econometric issue in empirical modeling on food demand in the sense that ignoring the censoring issue could lead to biased estimation results. This paper investigates the impact of state dependence on food demand using Nielsen 2009 and 2010 HomeScan data. In this paper, we take into account the censored nature of food expenditure data and employ a Bayesian procedure to estimate the dynamic demand models on dairy products. By controlling the individual heterogeneity in the model the source of endogeneity for the lagged dependent variable is removed.
|Date of creation:||2013|
|Date of revision:|
|Contact details of provider:|| Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202|
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.org
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ags:aaea13:150698. 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: (AgEcon Search)
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.