Pokaż uproszczony rekord

dc.contributor.authorWęgrzyn, Grażyna
dc.contributor.authorSalamaga, Marcin
dc.date.accessioned2023-09-29T08:31:58Z
dc.date.available2023-09-29T08:31:58Z
dc.date.issued2023-09-29
dc.identifier.issn1508-2008
dc.identifier.urihttp://hdl.handle.net/11089/48008
dc.description.abstractThe main purpose of the work is to present the results of empirical research on the impact of innovation levels in the economy on the structure of labour market flows. The analysis of the directions and scale of these flows makes it possible to discover important characteristics of the labour market and thus makes it possible to better construct and target policies to reduce unemployment or activate economically inactive people. The study uses data from the Labour Force Survey (LFS) and experimental job‑to‑job statistics for the European Union (EU) countries, covering the 2011–2019 period. We conducted research separately for selected groups of economies classified by their level of innovation, i.e. Innovation Leaders, Strong Innovators, Moderate Innovators, and Emerging Innovators. The results demonstrate that the structure of flows in a labour market depends on the innovation level of the respective economy. The main contribution of the study is that it identifies employee flow patterns in the labour markets of individual EU countries from the perspective of the innovation levels of their respective economies. Panel error correction models (ECM) and panel causality tests were used. In countries that are Innovation Leaders, an increase in participation in lifelong learning leads to a parallel increase in employee flow (EE) and job‑to‑job employee turnover. In countries that are Emerging Innovators, increasing participation in lifelong learning increases turnover, mainly among young people (15–24 age group).en
dc.description.abstractGłównym celem pracy jest przedstawienie wyników badań empirycznych dotyczących wpływu poziomu innowacyjności gospodarki na strukturę przepływów na rynku pracy.Analiza kierunków i skali przepływów umożliwia poznanie ważnych własności rynku pracy, a tym samym pozwala lepiej konstruować i adresować polityki ukierunkowane na ograniczanie skali bezrobocia lub aktywizację osób biernych zawodowo. W opracowaniu wykorzystano dane z badania Labour Force Survey (LFS) oraz statystyk eksperymentalnych job‑to‑job dla państw Unii Europejskiej w latach 2011–2019. Badania przeprowadzono odrębnie dla wyróżnionych grup państw ze względu na poziom innowacyjności, tj. Liderzy innowacji (Innovation leaders), Silni innowatorzy (Strong innovators), Umiarkowani innowatorzy (Moderate innovators), Wschodzący innowatorzy (Emerging innovators). Wskazujemy, że skala i kierunek przepływów osób na rynku pracy zależą od poziomu innowacyjności gospodarki. Głównym wkładem opracowania jest zidentyfikowanie wzorców przepływów na rynku pracy w państwach Unii Europejskiej, warunkowanych poziomem innowacyjności gospodarki. W badaniu wykorzystano panelowe modele korekty błędem ECM oraz panelowy test przyczynowości. W krajach zaliczanych do Liderów innowacyjności kształcenie ustawiczne zwiększa przepływy pracowników (EE) oraz rotację (job‑to‑job) ogółem, natomiast w krajach słabych innowacyjnie wzrasta rotacja jedynie wśród osób młodych (15–24 lata).pl
dc.language.isoen
dc.publisherWydawnictwo Uniwersytetu Łódzkiegopl
dc.relation.ispartofseriesComparative Economic Research. Central and Eastern Europe;3pl
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectlabour market flowen
dc.subjecttransitions in labour market statusen
dc.subjectjob‑to‑joben
dc.subjectinnovation economyen
dc.subjectprzepływy na rynku pracypl
dc.subjectzmiany statusu osób na rynku pracypl
dc.subjectrotacja pracownikówpl
dc.subjectinnowacyjność gospodarkipl
dc.titleAnalysis of the Impact of Innovative Economic Conditions on the Flow of Workers in the Labour Markets of the European Union Countriesen
dc.title.alternativeAnaliza wpływu innowacyjnych uwarunkowań gospodarki na przepływy pracowników na rynku pracy w państwach Unii Europejskiejpl
dc.typeArticle
dc.page.number159-178
dc.contributor.authorAffiliationWęgrzyn, Grażyna - Wroclaw University of Economics and Business, Wrocław, Polanden
dc.contributor.authorAffiliationSalamaga, Marcin - Cracow University of Economics, Kraków, Polanden
dc.identifier.eissn2082-6737
dc.referencesAkbas, Y.E., Senturk, M., Sancar, C. (2013), Testing for causality between the foreign direct investment, current account deficit, GDP and total credit: Evidence from G7, “Panoeconomicus”, 60 (6), pp. 791–812, https://doi.org/10.2298/PAN1306791Aen
dc.referencesBalmaseda, M., Dolado, J., Lopez Salido, J. (2000), The dynamics effects of shocks to labour markets: evidence from OECD countries, “Oxford Economic Papers”, 52 (1), pp. 3–23, https://doi.org/10.1093/oep/52.1.3en
dc.referencesBaltagi, B.H., Kao, C. (2000), Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey, “Syracuse University Center for Policy Research Working Paper”, 16, https://doi.org/10.2139/ssrn.1808022en
dc.referencesBassanini, A., Duval, R. (2006), Employment Patterns in OECD Countries: Reassessing the Role of Policies and Institutions, OECD Social, “Employment and Migration Working Papers”, 35, pp. 7–86, https://doi.org/10.1787/702031136412en
dc.referencesBlanchard, O. (2005), European unemployment: the evolution of facts and ideas, “NBER Working Paper”, 11750, https://doi.org/10.3386/w11750en
dc.referencesBlanchard, O.J., Diamond, P. (1990), The Cyclical Behavior of the Gross Flows of US Workers, “Brookings Papers on Economic Activity”, 2, pp. 85–155, https://doi.org/10.2307/2534505en
dc.referencesBoeri, T., Ours, J. van (2021), The Economics of Imperfect Labor Markets, Princeton University Press, Princeton–Oxford.en
dc.referencesBreitung, J. (2000), The Local Power of Some Unit Root Tests for Panel Data, [in:] B. Baltagi (ed.), Advances in Econometrics, Nonstationary Panels, Panel Cointegration, and Dynamic Panels, JAI Press, Amsterdam, pp. 161–178.en
dc.referencesBreschi, S., Lissoni, F. (2009), Mobility of skilled workers and co-invention networks: an anatomy of localized knowledge flows, “Journal of Economic Geography”, 9 (4), pp. 439–468, https://doi.org/10.1093/jeg/lbp008en
dc.referencesCournède, B., Denk, O., Garda, P. (2016), Effects of Flexibility-Enhancing Reforms on Employment Transitions, “OECD Economics Department Working Papers”, 1350, OECD Publishing, Paris.en
dc.referencesCournède, B., Denk, O., Garda, P., Hoeller, P. (2016), Enhancing Economic Flexibility: What Is in it for Workers?, “OECD Economic Policy Papers”, 19, OECD Publishing, Paris.en
dc.referencesDavis, S., Faberman, R., Haltiwanger, J. (2006), The Flow Approach to Labor Markets: New Data and Micro-Macro Links, “Journal of Economic Perspectives”, 20 (3), pp. 3–26, https://doi.org/10.1257/jep.20.3.3en
dc.referencesElsby, M.W.L., Hobijn, B., Sahin, A. (2011), Unemployment Dynamics in the OECD, “Tinbergen Institute Discussion Paper”, 11–159/3.en
dc.referencesErdala, L., Göçer, I. (2015), The Effects of Foreign Direct Investment on R&D and Innovations: Panel Data Analysis for Developing Asian Countries, “Procedia – Social and Behavioral Sciences”, 195(C), pp. 749–758, https://doi.org/10.1016/j.sbspro.2015.06.469en
dc.referencesEuropean Innovation Scoreboard 2021 (2021), Publications Office of the European Union, Luxembourg, https://ec.europa.eu/docsroom/documents/46013 (accessed: 5.05.2022).en
dc.referencesEurostat (n.d.), Labour market transitions – quarterly data, https://ec.europa.eu/eurostat/databrowser/view/lfsi_long_q/default/table?lang=en (accessed: 10.05.2022).en
dc.referencesFujita, S., Nakajima, M. (2013), Worker Flows and Job Flows: A Quantitative Investigation, “Federal Reserve Bank of Philadelphia Working Paper”, 13–9/R, https://doi.org/10.2139/ssrn.2235857en
dc.referencesGomez, P. (2012), Labour market flows: Facts from the United Kingdom, “Labour Economics”, 19 (2), pp. 165–175, https://doi.org/10.1016/j.labeco.2011.08.002en
dc.referencesHaldane, A.G. (2019), Climbing the Jobs Ladder, https://www.bankofengland.co.uk/-/media/boe/files/speech/2019/climbing-the-jobs-ladder-speech-by-andy-haldane.pdf (accessed: 10.05.2022).en
dc.referencesHaltiwanger, J., Scarpetta, S., Schweiger, H. (2013), Cross country differences in job reallocation: The role of industry, firm size and regulations, “Labour Economics”, 26, pp. 11–25, https://doi.org/10.1016/j.labeco.2013.10.001en
dc.referencesJanoskova, K., Kral, P. (2019), An In-Depth Analysis of the Summary Innovation Index in the V4 Countries, “Journal of Competitiveness”, 11 (2), pp. 68–83, https://doi.org/10.7441/joc.2019.02.05en
dc.referencesKao, C. (1999), Spurious regression and residual-based tests for cointegration in panel data, “Journal of Econometrics”, 90 (1), pp. 1–44, https://doi.org/10.1016/S0304-4076(98)00023-2en
dc.referencesMorandini, M.-Ch., Thum-Thysen, A., Vandeplas, A. (2020), Facing the Digital Transformation: Are Digital Skills Enough?, European Economy – Economic Briefs 054, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.en
dc.referencesMortensen, D.T., Pissarides, C.A. (1994), Job Creation and Job Destruction in the Theory of Unemployment, “Review of Economic Studies”, 61 (3), pp. 397–415, https://doi.org/10.2307/2297896en
dc.referencesMoscarini, G., Postel-Vinay, F. (2017), The Relative Power of Employment-to-Employment Reallocation and Unemployment Exits in Predicting Wage Growth, “American Economic Review”, 107 (5), pp. 364–368, https://doi.org/10.1257/aer.p20171078en
dc.referencesPedroni, P. (1999), Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors, “Oxford Bulletin of Economics and Statistics”, 61 (4), https://web.williams.edu/Economics/wp/pedronicriticalvalues.pdf (accessed: 15.04.2022).en
dc.referencesPieroni, L., Pompei, F. (2008), Evaluating innovation and labour market relationships: the case of Italy, “Cambridge Journal of Economics”, 32, pp. 325–347, https://doi.org/10.1093/cje/bem032en
dc.referencesShimer, R. (2010), Labor Markets and Business Cycles, Princeton University Press, Princeton–Oxford, https://doi.org/10.1515/9781400835232en
dc.referencesSocha, M., Sztanderska, U. (2002), Strukturalne podstawy bezrobocia w Polsce, Wydawnictwo Naukowe PWN, Warszawa.en
dc.contributor.authorEmailWęgrzyn, Grażyna - grazyna.wegrzyn@ue.wroc.pl
dc.contributor.authorEmailSalamaga, Marcin - salamaga@uek.krakow.pl
dc.identifier.doi10.18778/1508-2008.26.26
dc.relation.volume26


Pliki tej pozycji

Thumbnail

Pozycja umieszczona jest w następujących kolekcjach

Pokaż uproszczony rekord

https://creativecommons.org/licenses/by-nc-nd/4.0
Poza zaznaczonymi wyjątkami, licencja tej pozycji opisana jest jako https://creativecommons.org/licenses/by-nc-nd/4.0