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Published in: Quality & Quantity 1/2020

27-09-2019

Comparing time series characteristics of official and web job vacancy data

Authors: Pietro Giorgio Lovaglio, Mario Mezzanzanica, Emilio Colombo

Published in: Quality & Quantity | Issue 1/2020

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Abstract

This paper studies the relationship between a job vacancy population obtained from an international project based on web scraping of online job vacancies and job vacancies derived by the Eurostat job vacancy rate referred to Italian national statistics survey. We compare the time series properties of both time series between 2013 and 2018, globally and in each specific sector of economic activity. Using time series decomposition and cointegration analyses, we find that, apart some specific sector, the web and national statistics office vacancies data present similar time series properties, suggesting that both time series represent the same underlying phenomenon, namely the real number of new vacancies in the Italian economy. The study confirms promising frontiers to measure in real time aggregate demand in the labour market based on web data.

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Literature
go back to reference Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., & Picariello, A.: Challenge: processing web texts for classifying job offers. In: Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015), pp. 460–463. IEEE. (2015) Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., & Picariello, A.: Challenge: processing web texts for classifying job offers. In: Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015), pp. 460–463. IEEE. (2015)
go back to reference Antenucci, D., Cafarella, M., Levenstein, M.C., Ré, C., Shapito, M.D.: Using social media to measure labor market flows. NBER Working Papers Series No. 20010 (2014) Antenucci, D., Cafarella, M., Levenstein, M.C., Ré, C., Shapito, M.D.: Using social media to measure labor market flows. NBER Working Papers Series No. 20010 (2014)
go back to reference Artola, C., Galan, E.: Tracking the future of the web: construction of leading indicators using internet searches. Banco de España, Documentos Ocasionales No. 1203 (2012) Artola, C., Galan, E.: Tracking the future of the web: construction of leading indicators using internet searches. Banco de España, Documentos Ocasionales No. 1203 (2012)
go back to reference Artola, C., Pinto, F., de Pedraza, P.: Can Internet searches forecast tourism inflows? Int. J. Manpow. 36(1), 103–116 (2015)CrossRef Artola, C., Pinto, F., de Pedraza, P.: Can Internet searches forecast tourism inflows? Int. J. Manpow. 36(1), 103–116 (2015)CrossRef
go back to reference Askitas, N., Zimmermann, K.F.: Google econometrics and unemployment forecasting. IZA Discussion Paper No. 4201 (2009) Askitas, N., Zimmermann, K.F.: Google econometrics and unemployment forecasting. IZA Discussion Paper No. 4201 (2009)
go back to reference Askitas, N., Zimmermann, K.F.: The internet as a data source for advancement in social sciences. Int. J. Manpow. 36(1), 2–12 (2015)CrossRef Askitas, N., Zimmermann, K.F.: The internet as a data source for advancement in social sciences. Int. J. Manpow. 36(1), 2–12 (2015)CrossRef
go back to reference Bergamaschi, S., Carlini, E., Ceci, M., Furletti, B., Giannotti, F., Malerba, D., Mezzanzanica, M., Monreale, A., Pasi, G., Pedreschi, D., Perego, R.: Big data research in Italy: a perspective. Engineering 2(2), 163–170 (2016)CrossRef Bergamaschi, S., Carlini, E., Ceci, M., Furletti, B., Giannotti, F., Malerba, D., Mezzanzanica, M., Monreale, A., Pasi, G., Pedreschi, D., Perego, R.: Big data research in Italy: a perspective. Engineering 2(2), 163–170 (2016)CrossRef
go back to reference Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Planning meets data cleansing. In: Twenty-Fourth International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press (2014) Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Planning meets data cleansing. In: Twenty-Fourth International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press (2014)
go back to reference Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Using machine learning for labor market intelligence. In: Altun, Y., Das, K. (eds.) Machine Learning and Knowledge Discovery in Databases, pp. 1–13. Springer, Cham (2017a) Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Using machine learning for labor market intelligence. In: Altun, Y., Das, K. (eds.) Machine Learning and Knowledge Discovery in Databases, pp. 1–13. Springer, Cham (2017a)
go back to reference Boselli, R., Cesarini, M., Marrara, S., Mercorio, F., Mezzanzanica, M., Pasi, G., Viviani, M.: WoLMIS: a labor market intelligence system for classifying web job vacancies. J. Intell. Inf. Syst. 51, 1–26 (2017b) Boselli, R., Cesarini, M., Marrara, S., Mercorio, F., Mezzanzanica, M., Pasi, G., Viviani, M.: WoLMIS: a labor market intelligence system for classifying web job vacancies. J. Intell. Inf. Syst. 51, 1–26 (2017b)
go back to reference Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Classifying online job advertisements through machine learning. Future Gener. Comput. Syst. 86, 319–328 (2018)CrossRef Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Classifying online job advertisements through machine learning. Future Gener. Comput. Syst. 86, 319–328 (2018)CrossRef
go back to reference Choi, H., Variant, H.: Predicting the present with Google trends. Econ. Rec. 88, 2–9 (2012)CrossRef Choi, H., Variant, H.: Predicting the present with Google trends. Econ. Rec. 88, 2–9 (2012)CrossRef
go back to reference Cleveland, R.B., Cleveland, W.S., McRae, J.E., Terpenning, I.J.: STL: a seasonal-trend decomposition procedure based on loess. J. Off. Stat. 6(1), 3–73 (1990) Cleveland, R.B., Cleveland, W.S., McRae, J.E., Terpenning, I.J.: STL: a seasonal-trend decomposition procedure based on loess. J. Off. Stat. 6(1), 3–73 (1990)
go back to reference D’amuri, F., Marcucci, J.: Google it! Forecasting the US unemployment rate with a Google job search index. ISER Working Paper Series 2009-32. Institute for Social and Economic Research (2009) D’amuri, F., Marcucci, J.: Google it! Forecasting the US unemployment rate with a Google job search index. ISER Working Paper Series 2009-32. Institute for Social and Economic Research (2009)
go back to reference de Pedraza, P., Visintin, S., Tijdens, K., Kismihók, G.: Survey vs scraped data: comparing time series properties of web and survey vacancy data. AIAS Working Paper 175, Universiteit van Amsterdam (2017) de Pedraza, P., Visintin, S., Tijdens, K., Kismihók, G.: Survey vs scraped data: comparing time series properties of web and survey vacancy data. AIAS Working Paper 175, Universiteit van Amsterdam (2017)
go back to reference Enders, W.: Applied Econometric Time Series, 3rd edn. Wiley, New York (2010) Enders, W.: Applied Econometric Time Series, 3rd edn. Wiley, New York (2010)
go back to reference Engle, R.F., Granger, C.W.J.: Co-integration and error correction: representation, estimation, and testing. Econometrica 55, 251–276 (1987)CrossRef Engle, R.F., Granger, C.W.J.: Co-integration and error correction: representation, estimation, and testing. Econometrica 55, 251–276 (1987)CrossRef
go back to reference Excelsior: La domanda di professioni e di formazione delle imprese italiane nel 2018. Unioncamere Press, Roma (2019) Excelsior: La domanda di professioni e di formazione delle imprese italiane nel 2018. Unioncamere Press, Roma (2019)
go back to reference Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: The KDD process for extracting useful knowledge from volumes of data. Commun. ACM 39(11), 27–34 (1996)CrossRef Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: The KDD process for extracting useful knowledge from volumes of data. Commun. ACM 39(11), 27–34 (1996)CrossRef
go back to reference Fondeur, Y., Karame, F.: Can Google data help now or forecasting French unemployment? Econ. Model. 30, 117–125 (2013)CrossRef Fondeur, Y., Karame, F.: Can Google data help now or forecasting French unemployment? Econ. Model. 30, 117–125 (2013)CrossRef
go back to reference Hafen, R.P., Anderson, D.E., Cleveland, W.S., Maciejewski, R., Ebert, D.S., Abusalah, A., Yakout, M., Ouzzani, M., Grannis, S.: Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts. BMC Med. Inform. Decis. Mak. 9(21), 1–11 (2009) Hafen, R.P., Anderson, D.E., Cleveland, W.S., Maciejewski, R., Ebert, D.S., Abusalah, A., Yakout, M., Ouzzani, M., Grannis, S.: Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts. BMC Med. Inform. Decis. Mak. 9(21), 1–11 (2009)
go back to reference Hernández, M.A., Stolfo, S.J.: Real-world data is dirty: data cleansing and the merge/purge problem. Data Min. Knowl. Discov. 2(1), 9–37 (1998)CrossRef Hernández, M.A., Stolfo, S.J.: Real-world data is dirty: data cleansing and the merge/purge problem. Data Min. Knowl. Discov. 2(1), 9–37 (1998)CrossRef
go back to reference Hyndman, R.J., Athanasopoulos, G.: Forecasting: Principles and Practice, 2nd edn. OTexts.org, Melbourne (2017) Hyndman, R.J., Athanasopoulos, G.: Forecasting: Principles and Practice, 2nd edn. OTexts.org, Melbourne (2017)
go back to reference Hyndman, R.J., Khandakar, Y.: Automatic time series forecasting: the forecast package for R. J. Stat. Softw. 27, 1–22 (2008)CrossRef Hyndman, R.J., Khandakar, Y.: Automatic time series forecasting: the forecast package for R. J. Stat. Softw. 27, 1–22 (2008)CrossRef
go back to reference Kureková, L.M., Beblavý, M., Thum-Thysen, A.: Using online vacancies and web surveys to analyse the labor market: a methodological inquiry. IZA J. Labor Econ. 4, 18 (2015)CrossRef Kureková, L.M., Beblavý, M., Thum-Thysen, A.: Using online vacancies and web surveys to analyse the labor market: a methodological inquiry. IZA J. Labor Econ. 4, 18 (2015)CrossRef
go back to reference Lee, I.: Modeling the benefit of e-recruiting process integration. Decis. Support Syst. 51(1), 230–239 (2011)CrossRef Lee, I.: Modeling the benefit of e-recruiting process integration. Decis. Support Syst. 51(1), 230–239 (2011)CrossRef
go back to reference Lenaerts, K., Miroslav Beblavý, M., Fabo, B.: Prospects for utilisation of non-vacancy internet data in labour market analysis—an overview. IZA J. Labor Econ. 5, 1 (2016)CrossRef Lenaerts, K., Miroslav Beblavý, M., Fabo, B.: Prospects for utilisation of non-vacancy internet data in labour market analysis—an overview. IZA J. Labor Econ. 5, 1 (2016)CrossRef
go back to reference Lovaglio, P.G., Mezzanzanica, M.: Classification of longitudinal career paths. Qual. Quant. 47(2), 989–1008 (2013)CrossRef Lovaglio, P.G., Mezzanzanica, M.: Classification of longitudinal career paths. Qual. Quant. 47(2), 989–1008 (2013)CrossRef
go back to reference Lovaglio, P.G., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Skills in demand for ICT and statistical occupations: evidences from web vacancies. Stat. Anal. Data Min. 2(11), 78–91 (2018)CrossRef Lovaglio, P.G., Cesarini, M., Mercorio, F., Mezzanzanica, M.: Skills in demand for ICT and statistical occupations: evidences from web vacancies. Stat. Anal. Data Min. 2(11), 78–91 (2018)CrossRef
go back to reference Mezzanzanica, M., Boselli, R., Cesarini, M., Mercorio, F.: A model-based evaluation of data quality activities in KDD. Inf. Process. Manag. 51(2), 144–166 (2015)CrossRef Mezzanzanica, M., Boselli, R., Cesarini, M., Mercorio, F.: A model-based evaluation of data quality activities in KDD. Inf. Process. Manag. 51(2), 144–166 (2015)CrossRef
go back to reference Preis, T., Moat, H.S., Stanley, H.E.: Quantifying trading behavior in financial markets using Google Trends. Nat. Sci. Rep. 3, 1684 (2013)CrossRef Preis, T., Moat, H.S., Stanley, H.E.: Quantifying trading behavior in financial markets using Google Trends. Nat. Sci. Rep. 3, 1684 (2013)CrossRef
go back to reference Schmidt, T., Vossen, S.: Using internet data to account for special events in economic forecasting. Ruhr Economic Papers, No. 382 (2012) Schmidt, T., Vossen, S.: Using internet data to account for special events in economic forecasting. Ruhr Economic Papers, No. 382 (2012)
go back to reference Štefánik, M.: Internet job search data as a possible source of information on skills demand (with results for Slovak University graduates). In: CEDEFOP (ed.) Building on Skills Forecasts—Comparing Methods and Applications. Publications Office of the European Union, Luxembourg (2012) Štefánik, M.: Internet job search data as a possible source of information on skills demand (with results for Slovak University graduates). In: CEDEFOP (ed.) Building on Skills Forecasts—Comparing Methods and Applications. Publications Office of the European Union, Luxembourg (2012)
go back to reference Steinmetz, S., Tijdens, K., de Pedraza, P.: WP 76-comparing different weighting procedures for volunteer Web surveys. AIAS Working Paper 09/76, Universiteit van Amsterdam (2009) Steinmetz, S., Tijdens, K., de Pedraza, P.: WP 76-comparing different weighting procedures for volunteer Web surveys. AIAS Working Paper 09/76, Universiteit van Amsterdam (2009)
go back to reference Stewart, C.: A note on spurious significance in regressions involving I(0) and I(1) variables. Empir. Econ. 41(3), 565–571 (2011)CrossRef Stewart, C.: A note on spurious significance in regressions involving I(0) and I(1) variables. Empir. Econ. 41(3), 565–571 (2011)CrossRef
Metadata
Title
Comparing time series characteristics of official and web job vacancy data
Authors
Pietro Giorgio Lovaglio
Mario Mezzanzanica
Emilio Colombo
Publication date
27-09-2019
Publisher
Springer Netherlands
Published in
Quality & Quantity / Issue 1/2020
Print ISSN: 0033-5177
Electronic ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-019-00940-3

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