Micro-Level Estimation of Optimal Consumption Choice With Intertemporal Nonseparability in Preferences and Measurement Errors
Wayne-Roy Gayle and
Natalia Khorunzhina
Journal of Business & Economic Statistics, 2018, vol. 36, issue 2, 227-238
Abstract:
This article investigates the presence of habit formation in household consumption, using data from the Panel Study of Income Dynamics. We develop an econometric model of internal habit formation of the multiplicative specification. The restrictions of the model allow for classical measurement errors in consumption without parametric assumptions on the distribution of measurement errors. We estimate the parameters by nonlinear generalized method of moments and find that habit formation is an important determinant of household food-consumption patterns. Using the parameter estimates, we develop bounds for the expectation of the implied heterogenous intertemporal elasticity of substitution and relative risk aversion that account for measurement errors, and compute confidence intervals for these bounds. Supplementary materials for this article are available online.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2016.1149071 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:36:y:2018:i:2:p:227-238
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20
DOI: 10.1080/07350015.2016.1149071
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan
More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().