Estimating sales and sales market share from sales rank data for consumer appliances

Samir Touzani and Robert Van Buskirk

Physica A: Statistical Mechanics and its Applications, 2016, vol. 451, issue C, 266-276

Abstract: Our motivation in this work is to find an adequate probability distribution to fit sales volumes of different appliances. This distribution allows for the translation of sales rank into sales volume. This paper shows that the log-normal distribution and specifically the truncated version are well suited for this purpose. We demonstrate that using sales proxies derived from a calibrated truncated log-normal distribution function can be used to produce realistic estimates of market average product prices, and product attributes. We show that the market averages calculated with the sales proxies derived from the calibrated, truncated log-normal distribution provide better market average estimates than sales proxies estimated with simpler distribution functions.

Keywords: Sales rank; Log-normal distribution; Market average quantities; Price indices; Statistical model (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:451:y:2016:i:c:p:266-276

DOI: 10.1016/j.physa.2016.01.030

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