Revisiting the nested fixed-point algorithm in BLP random coefficients demand estimation

Jinhyuk Lee and Kyoungwon Seo

Economics Letters, 2016, vol. 149, issue C, 67-70

Abstract: This paper examines the numerical properties of the nested fixed-point algorithm (NFP) in the estimation of Berry et al. (1995) random coefficient logit demand model. Dubé et al. (2012) find the bound on the errors of the NFP estimates computed by contraction mappings (NFP/CTR) has the order of the square root of the inner loop tolerance. Under our assumptions, we theoretically derive an upper bound on the numerical bias in the NFP/CTR, which has the same order of the inner loop tolerance. We also discuss that, compared with NFP/CTR, NFP using Newton’s method has a smaller bound on the estimate error.

Keywords: Random coefficients logit demand; Numerical methods; Nested fixed-point algorithm; Newton’s method (search for similar items in EconPapers)
JEL-codes: C1 L1 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176516304141
Full text for ScienceDirect subscribers only

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:eee:ecolet:v:149:y:2016:i:c:p:67-70

DOI: 10.1016/j.econlet.2016.10.019

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().