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Re-Considering Aggregated Data Bias by Extending "Koyck Model" of Advertising Effect
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  • Re-Considering Aggregated Data Bias by Extending "Koyck Model" of Advertising Effect
  • Re-Considering Aggregated Data Bias by Extending "Koyck Model" of Advertising Effect
저자명
송태호,김지윤,Song. Tea-Ho,Yuan. Xina,Kim. Ji-Yoon
간행물명
韓國經營科學會誌
권/호정보
2009년|34권 2호|pp.91-100 (10 pages)
발행정보
한국경영과학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

"How does advertising affect sales?" is the fundamental issue of modern advertising research. There is an interesting issue for estimating carryover effects of advertising on sales, and the aggregated data biases exist in the duration of advertising effect. This research suggests an extended model of Koyck Model which is employed for micro-data (Koyck 1954) to estimate aggregated advertising data, and empirically shows the aggregated data bias. Our developed model with the aggregated level of actual advertising data is more appropriate than the basic Koyck model for micro-data. The result figures out that it is important to consider the disaggregated data level in the analysis of dynamic effects of adverting such as carryover effects.