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Guidotti R., Michele C., Pedreschi D., Pennachioli D. Going beyond GDP to nowcast well-being using retail market data. In: NetSci-X 2016 - Advances in Network Science. 12th International Conference and School (Wroclaw, Poland, 11-13 January 2016). Proceedings, pp. 29 - 42. Adam Wierzbicki, Ulrik Brandes, Frank Schweitzer, Dino Pedreschi. (Lecture Notes in Computer Science, vol. 9564). Springer, 2016.
 
 
Abstract
(English)
One of the most used measures of the economic health of a nation is the Gross Domestic Product (GDP): the market value of all officially recognized final goods and services produced within a country in a given period of time. GDP, prosperity and well-being of the citizens of a country have been shown to be highly correlated. However, GDP is an imperfect measure in many respects. GDP usually takes a lot of time to be estimated and arguably the well-being of the people is not quantifiable simply by the market value of the products available to them. In this paper we use a quantification of the average sophistication of satisfied needs of a population as an alternative to GDP. We show that this quantification can be calculated more easily than GDP and it is a very promising predictor of the GDP value, anticipating its estimation by six months. The measure is arguably a more multifaceted evaluation of the well-being of the population, as it tells us more about how people are satisfying their needs. Our study is based on a large dataset of retail micro transactions happening across the Italian territory.
URL: http://link.springer.com/chapter/10.1007/978-3-319-28361-6_3
DOI: 10.1007/978-3-319-28361-6_3
Subject Shopping behavior
Economic sophistication
Complex network analysis
H.2.8 Database Applications. Data Mining
68W01


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