Web scraping based online consumer price index: The “IPC Online” case

Article type: Research Article

Authors: Uriarte, Juan I.^{a; d} | Ramírez Muñoz de Toro, Gonzalo R.^{a; d} | Larrosa, Juan M.C.^{b; c; *}

Affiliations: [a] Departamento de Derecho, Universidad Nacional del Sur, Argentina | [b] Departamento de Economía, Universidad Nacional del Sur, Argentina | [c] Instituto de Investigaciones Económicas y Sociales del Sur, Argentina | [d] Hyperia Limited, Victoria Island, Lagos, Nigeria

Correspondence: [*] Corresponding author: Juan M.C. Larrosa, Instituto de Investigaciones Económicas y Sociales del Sur (IIESS), Argentina. E-mail: jlarrosa@uns.edu.ar.

Abstract: We describe a case of web scraping data-based price indices implemented in a mid-size city in a moderate inflationary country. Full consumer price (CPI) and construction cost (CCI) indices were implemented for an entire city obtaining efficient results compared to statistics using traditional data collection methods. We state that web scraping combined with big data techniques will allow estimating more individualized and efficient metrics comparable in quality to official statistics. Web scraping technologies empower civil society and small research groups alike by allowing them gather and interpret socioeconomic data. It also helps to create new dimensions of analysis by allowing changes in frequency and focus on specific groups of products and services.

Keywords: Big data applications, heterogeneous data sources, web scrapping, inflation, Argentina

DOI: 10.3233/JEM-190464

Journal: Journal of Economic and Social Measurement, vol. 44, no. 2-3, pp. 141-159, 2019