A semiparametric approach to estimating reference price effects in sales response models
Philipp Aschersleben () and
Winfried J. Steiner
Additional contact information
Philipp Aschersleben: Clausthal University of Technology
Winfried J. Steiner: Clausthal University of Technology
Journal of Business Economics, 2022, vol. 92, issue 4, No 4, 643 pages
Abstract:
Abstract It is well known that store-level brand sales may not only depend on contemporaneous influencing factors like current own and competitive prices or other marketing activities, but also on past prices representing customer response to price dynamics. On the other hand, non- or semiparametric regression models have been proposed in order to accommodate potential nonlinearities in price response, and related empirical findings for frequently purchased consumer goods indicate that price effects may show complex nonlinearities, which are difficult to capture with parametric models. In this contribution, we combine nonparametric price response modeling and behavioral pricing theory. In particular, we propose a semiparametric approach to flexibly estimating price-change or reference price effects based on store-level sales data. We compare different representations for capturing symmetric vs. asymmetric and proportional vs. disproportionate price-change effects following adaptation-level and prospect theory, and further compare our flexible autoregressive model specifications to parametric benchmark models. Functional flexibility is accommodated via P-splines, and all models are estimated within a fully Bayesian framework. In an empirical study, we demonstrate that our semiparametric dynamic models provide more accurate sales forecasts for most brands considered compared to competing benchmark models that either ignore price dynamics or just include them in a parametric way.
Keywords: Sales and price response modeling; Functional flexibility; Bayesian P-splines; Behavioral pricing; Prospect theory; Reference price (search for similar items in EconPapers)
JEL-codes: M31 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s11573-022-01083-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:jbecon:v:92:y:2022:i:4:d:10.1007_s11573-022-01083-y
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/11573
DOI: 10.1007/s11573-022-01083-y
Access Statistics for this article
Journal of Business Economics is currently edited by Günter Fandel
More articles in Journal of Business Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().