IDEAS home Printed from https://ideas.repec.org/a/vrs/izajle/v8y2019i1p103-116n4.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

  • Tijdens Kea

    () (University of Amsterdam/AIAS, Postbus 94025, 1090 GAAmsterdam, The Netherlands)

  • Kismihók Gábor

    () (Leibniz Information Centre for Science and Technology, Welfengarten 1 B, 30167Hannover, Germany)

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.

Suggested Citation

  • Pedraza Pablo de & Visintin Stefano & Tijdens Kea & Kismihók Gábor, 2019. "Survey vs Scraped Data: Comparing Time Series Properties of Web and Survey Vacancy Data," IZA Journal of Labor Economics, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 103-116, June.
  • Handle: RePEc:vrs:izajle:v:8:y:2019:i:1:p:103-116:n:4
    as

    Download full text from publisher

    File URL: https://www.degruyter.com/view/j/izajole.2019.8.issue-1/izajole-2019-0004/izajole-2019-0004.xml?format=INT
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    2. Pablo de Pedraza & Martin Guzi & Kea Tijdens, 2020. "Life Satisfaction of Employees, Labour Market Tightness and Matching Efficiency," MUNI ECON Working Papers 2020-02, Masaryk University.

    More about this item

    Keywords

    web crawling; statistical inference; time series; vacancies; Labor demand; data collection;

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:izajle:v:8:y:2019:i:1:p:103-116:n:4. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla). General contact details of provider: https://www.sciendo.com/services/journals .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.