Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms
This study aims at evaluating the impact of educational mismatch onto firm-level productivity for a large set of Italian firms. In particular, over (under)-education refers to situations where individual’s educational attainment is higher (lower) than the education required by the job, thereby produ...
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| मुख्य लेखकों: | , |
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| स्वरूप: | Online |
| भाषा: | अंग्रेज़ी |
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Firenze University Press, Genova University Press
2023
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| विषय: | |
| ऑनलाइन पहुंच: | ONIX_20230803_9791221501063_120 |
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| _version_ | 1869527557344329728 |
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| author | Bisio, Laura Lucchese, Matteo |
| author_browse | Bisio, Laura Lucchese, Matteo |
| author_facet | Bisio, Laura Lucchese, Matteo |
| author_sort | Bisio, Laura |
| collection | Directory of Open Access Books |
| description | This study aims at evaluating the impact of educational mismatch onto firm-level productivity for a large set of Italian firms. In particular, over (under)-education refers to situations where individual’s educational attainment is higher (lower) than the education required by the job, thereby producing a surplus (deficit) of education. Based on the integration of the LEED (Linked Employer Employee Database) Istat Statistical Register Asia Occupazione – which provides information on workers’ age, professional qualification and educational attainment – and the Istat Frame-SBS Register, we perform an analysis in the spirit of the ORU (Over, Required and Under Education) model proposed by Kampelmann e Rycx (2012). The dataset is based on a large panel of over 55,000 manufacturing and services firms with more than 20 employees, covering the 2014-2019 period. The empirical strategy is based on a two-step procedure: first, ORU indicators are computed at the worker-level; second, we estimate a firm-level productivity (value added per employee) function where the key variables of interest are the ORU indicators collapsed at the firm-level, taking into account both firm and workers characteristics. The productivity function is estimated by GMM-system by Arellano and Bond (1995) e Blundell and Bond (1988). Main results point out that over/under-education affects productivity growth in both manufacturing and services firms: firm’s productivity rises following a one unit increase in mean years of over-education – with spiking results for medium and high-tech manufacturing firms –, whereas a growth in under-education hampers productivity dynamics in high and medium-high tech manufacturing and knowledge-intensive services firms. |
| format | Online |
| id | doab-20.500.12854ir-111719 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Firenze University Press, Genova University Press |
| publisherStr | Firenze University Press, Genova University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1117192025-07-17T10:01:25Z Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms Bisio, Laura Lucchese, Matteo Educational mismatch Productivity Linked Employer-Employee Dataset GMM-System thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences This study aims at evaluating the impact of educational mismatch onto firm-level productivity for a large set of Italian firms. In particular, over (under)-education refers to situations where individual’s educational attainment is higher (lower) than the education required by the job, thereby producing a surplus (deficit) of education. Based on the integration of the LEED (Linked Employer Employee Database) Istat Statistical Register Asia Occupazione – which provides information on workers’ age, professional qualification and educational attainment – and the Istat Frame-SBS Register, we perform an analysis in the spirit of the ORU (Over, Required and Under Education) model proposed by Kampelmann e Rycx (2012). The dataset is based on a large panel of over 55,000 manufacturing and services firms with more than 20 employees, covering the 2014-2019 period. The empirical strategy is based on a two-step procedure: first, ORU indicators are computed at the worker-level; second, we estimate a firm-level productivity (value added per employee) function where the key variables of interest are the ORU indicators collapsed at the firm-level, taking into account both firm and workers characteristics. The productivity function is estimated by GMM-system by Arellano and Bond (1995) e Blundell and Bond (1988). Main results point out that over/under-education affects productivity growth in both manufacturing and services firms: firm’s productivity rises following a one unit increase in mean years of over-education – with spiking results for medium and high-tech manufacturing firms –, whereas a growth in under-education hampers productivity dynamics in high and medium-high tech manufacturing and knowledge-intensive services firms. 2023-08-05T04:06:41Z 2023-08-05T04:06:41Z 2023-08-03T15:07:01Z 2023 chapter ONIX_20230803_9791221501063_120 2704-5846 https://library.oapen.org/handle/20.500.12657/74924 9791221501063 https://directory.doabooks.org/handle/20.500.12854/111719 eng Proceedings e report open access image/png image/jpeg Attribution 4.0 International Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/74924/1/9791221501063-52.pdf https://library.oapen.org/bitstream/20.500.12657/74924/1/9791221501063-52.pdf Firenze University Press, Genova University Press 10.36253/979-12-215-0106-3.52 10.36253/979-12-215-0106-3.52 74113d79-2268-4658-88bb-6e8757c543b0 ASA 2022 Data-Driven Decision Making 9791221501063 6 Florence open access |
| spellingShingle | Educational mismatch Productivity Linked Employer-Employee Dataset GMM-System thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences Bisio, Laura Lucchese, Matteo Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title | Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title_full | Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title_fullStr | Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title_full_unstemmed | Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title_short | Chapter Educational mismatch and productivity: evidence from LEED data on Italian firms |
| title_sort | chapter educational mismatch and productivity evidence from leed data on italian firms |
| topic | Educational mismatch Productivity Linked Employer-Employee Dataset GMM-System thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences |
| topic_facet | Educational mismatch Productivity Linked Employer-Employee Dataset GMM-System thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences |
| url | ONIX_20230803_9791221501063_120 |
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