JSM 2005 Online Program

Abstract #303369

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	360
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Business and Economics Statistics Section
Abstract - #303369
Title:	Yield Analysis Approach and Problems of Return on Investment Estimation
Author(s):	Igor Mandel and David Hauser*+
Companies:	Media Planning Group and Media Planning Group
Address:	195 Broadway MPG, New York, NY, 10005, USA
Keywords:	random regression coefficients ; Hildretch-Houck regression ; adstock ; return on investment
Abstract:	A commonly understood definition of return on investment (ROI) is the ratio of an output attributed to a specific input. In statistical modeling, however, this straightforward definition can be problematic. Specifically, there are two seemingly equivalent popular notions we will demonstrate can actually lead to different estimates of ROI: a stimulus applied to a system today should influence the future and a response today may have been influenced by historical stimuli. A new method of estimating ROI for time-series data is presented based on two concepts: yield analysis, a methodology to determine object/time varying coefficients of influence, and a distributed lag paradigm, a system of estimated prolonged effects (a form of adstock). This approach adds another dimension to the process of modeling, thus allowing the estimate of ROI in economics and marketing. The principal difference between the two ways of ROI calculation---forward and backward---is analyzed and theoretical and practical results are presented.

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