Denoised least squares estimators: An application to estimating advertising effectiveness
Issue Date
2000-01-01Author
Cai, Zongwu
Naik, Prasad A.
Tsai, Chih-Ling
Publisher
Academia Sinica, Institute of Statistical Science
Type
Article
Article Version
Scholarly/refereed, publisher version
Published Version
http://www3.stat.sinica.edu.tw/statistica/j10n4/j10n412/j10n412.htmMetadata
Show full item recordAbstract
It is known in marketing science that an advertiser under- or overspends millions of dollars on advertising because the estimation of advertising effectiveness is biased. This bias is induced by measurement noise in advertising variables, such as awareness and television rating points, which are provided by commercial market research firms based on small-sample surveys of consumers. In this paper, we propose a denoised regression approach to deal with the problem of noisy variables. We show that denoised least squares estimators are consistent. Simulation results indicate that the denoised regression approach outperforms the classical regression approach. A marketing example is presented to illustrate the use of denoised least squares estimators.
Description
This is the publisher's version, also available electronically from http://www3.stat.sinica.edu.tw/statistica/j10n4/j10n412/j10n412.htm.
ISSN
1017-0405Collections
Citation
Cai, Zongwu; Naik, Prasad A.; Tsai, Chih-Ling. (2000). "Denoised least squares estimators: An application to estimating advertising effectiveness." Statistica Sinica, 10(4):1231-1241. http://www3.stat.sinica.edu.tw/statistica/j10n4/j10n412/j10n412.htm
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