Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/11932
Author(s): Bondonio, D.
Fernandes, T. F.
Mamede, R.
Date: 2016
Title: Does EU Public Support to Firm Investments Boost High Quality Jobs? Evidence from Linked Employer-Employee Microdata and Natural-Experiment Conditions
Collection title and number: Working Papers
DINÂMIA
Keywords: Enterprise support programs
Counterfactual impact evaluation
Job-Quality
EU Cohesion Policy
Abstract: In this paper we estimate the impact on job quality of the direct support to firm- investment projects provided through the EU cohesion policy funds. We use linked employer-employee micro-data, from administrative sources, that cover the universe of Portuguese firms over the years 2000s. The analysis exploits the existence of natural experiment conditions in the form of treatment assignment procedures based on exogenous cut-offs in the ranking of the applicant firms. Our preferred estimation strategy is a dynamic exact matching procedure that is combined with a difference-in-difference scheme to mimic a block-randomised pretest-posttest design. The procedure is adopted separately for each of the successive cohorts of applicants and solves the small sample issues that would be encountered with a multiple-ranking regression discontinuity design. Our results indicate that the firm-level support co-funded by EU structural funds in Portugal has contributed to improving job quality compared to the counterfactual scenario of no public support, with each treated firm creating on average 4.9 additional standard-working-time jobs, 2.9 skilled jobs, and 2.0 permanent contract jobs. We also estimate that the average remuneration per hour in treated firms is €2.2 higher than in similar non-treated applicant firms. These results are adequately robust to a wide range of sensitivity analyses and bear some relevant policy implications for the EU.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:DINÂMIA'CET-WP - Working papers com arbitragem científica

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