Calculating and Pivoting a Place-Based Food Price Index with Tapestry Segmentation
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Keywords: Place-based, Food price index, Tapestry, Geographic variation
Abstract Type: Paper Abstract
Authors:
Lan Mu, Department of Geography, University of Georgia
Chen Zhen, Department of Agricultural & Applied Economics, University of Georgia
Brian Payton Duran, Department of Geography, University of Georgia
Chandra Dhakal, Department of Agricultural & Applied Economics, University of Georgia
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Abstract
Food price can be an essential indicator of the balance between agricultural production and market demand and substantially impact food affordability and income. While there are numerous food price indices, there is a lack of high-quality food price measures that have the desired levels of granularity in food categorization and geographical resolution. ESRI’s Tapestry Segmentation system combines lifestyle demography with local neighborhood geography to create 67 distinct behavioral market segments that can be grouped into 14 lifemodes and six urbanization categories. In a multi-year ongoing project, we use InfoScan’s over 40,000 stores data to calculate the food price index at the place level in the US and pivot the index with Tapestry Segmentation, so that we understand the food price variations both temporally and geographically.
This paper presents some preliminary results from the project. We delineated 5,061 geographic units at the place level with three or more stores and used the GEKS (Gini-Éltető-Köves-Szulc) method to calculate the panel food price index for fruit-flavored, caffeine-free soft drinks during the pilot period of 27 quad-weeks. Pivoting these measures with the tapestry segment, lifemode, and urbanization, we found that, in general, the highest food price index happens in the lifemode of Uptown Individuals, and the lowest is in Rustic Outposts. However, when incorporating urbanity, the highest index happens in Ethnic Enclaves at Semirural, and the lowest is in Scholars and Patriots at Suburban Periphery. Geographic variations at the state and region levels are also explored and discussed.
Calculating and Pivoting a Place-Based Food Price Index with Tapestry Segmentation
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Paper Abstract