Survey vs Scraped Data: Comparing Time Series Properties of Web and Survey Vacancy Data

Pedraza Pablo de (), Visintin Stefano (), Kea Tijdens and Kismihók Gábor ()
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Pedraza Pablo de: University of Amsterdam and European Commission, Joint Research Centre (JRC), Unit I.1, Modelling, Indicators & Impact Evaluation, Via E. Fermi 2749, TP 361, Ispra (VA), I-21027, Italy
Visintin Stefano: University of Amsterdam/AIAS and Universidad Camilo José Cela, Facultad de Tecnología y Ciencia, Urb. Villafranca del Castillo, Calle Castillo de Alarcón, 49, 28692, Villanueva de la Cañada, Madrid, Spain
Kismihók Gábor: Leibniz Information Centre for Science and Technology, Welfengarten 1 B, 30167Hannover, Germany

IZA Journal of Labor Economics, 2019, vol. 8, issue 1, 23

Abstract: This paper studies the relationship between a vacancy population obtained from web crawling and vacancies in the economy inferred by a National Statistics Office (NSO) using a traditional method. We compare the time series properties of samples obtained between 2007 and 2014 by Statistics Netherlands and by a web scraping company. We find that the web and NSO vacancy data present similar time series properties, suggesting that both time series are generated by the same underlying phenomenon: the real number of new vacancies in the economy. We conclude that, in our case study, web-sourced data are able to capture aggregate economic activity in the labor market.

Keywords: web crawling; statistical inference; time series; vacancies; Labor demand; data collection (search for similar items in EconPapers)
JEL-codes: C22 C80 J23 J63 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:izajle:v:8:y:2019:i:1:p:103-116:n:4

DOI: 10.2478/izajole-2019-0004

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