How effective are hiring subsidies in reducing long-term unemployment among prime-aged jobseekers? Evidence from Belgium

Notes: The population of short-term unemployed jobseekers consists of all jobseekers who registered at the PES; the population of LTU jobseekers consists of jobseekers who are still unemployed after 6 months. All characteristics, including the jobseekers’ age, are determined at the time of registration at the PES. EU-15: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom. EU-13 (new EU member states): Bulgaria, Croatia, Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, and Slovenia. Low level of education: at the most lower-secondary education; medium level: upper-secondary education or postsecondary nontertiary education; high level: short-cycle tertiary education, bachelor's level, master's level, or doctoral level.

1 This column presents the characteristics of individuals aged 45–48 years hired with the subsidy analyzed in this paper, which is targeted at jobseekers older than 45 years of age and unemployed for at least 6 months, between the second quarter of 2015 and the last quarter of 2016 (pre-reform period). We do not have this information for jobseekers hired before 2015 because we obtained data from Flemish institutions that are in charge of this policy since 2015 and only have data since then. We excluded the first quarter of 2015 because we present the characteristics of the new hires, not of the population of subsidized employees at a given moment in time.

2 This column presents the coefficient of the triple-interaction term of regressing the jobseekers’ characteristics on group dummies (young vs. old; short-term unemployed vs. LTU jobseekers), period dummies (before vs. after the reform), and all the interaction terms. None of these triple-interaction terms is significant at the 10% level.

Notes: Results of estimation of the triple-differences regressions as specified by Eq. (1) are shown. The benchmark specification contrasts the job-finding rate across age groups (40–43 vs. 45–48 years old), unemployment duration (unemployed for 1–5 months vs. unemployed for 6–12 months), and period (before vs. after the reform). The other triple-difference regressions rule out substitution and anticipation effects by, respectively, using jobseekers aged 35–37 years as the control group, using jobseekers unemployed for 1–4 months as the control group, and excluding jobseekers who registered as unemployed in 2016 from the regression. The last triple-difference regression follows the same specification as the benchmark but uses a more stringent definition of “work”, thereby excluding temporary agency work lasting between 10 days and 20 days per month. The following control variables are included in all regressions: unemployment duration (dummies), year of registration at the PES, level of education (low, medium, and high), self-reported proficiency in Dutch, region of origin, and sex. Full results of the benchmark specification are reported in Table A2 in Appendix A. The placebo tests verify whether the parallel trends assumption holds in the post-reform period and whether the abolition of the subsidy did not affect the job-finding rate of jobseekers unemployed for 5 months (see also Table A3 in Appendix A). Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1% and 5% levels, respectively.

Notes: The table shows the triple-interaction term obtained by estimating triple-difference regressions on different subsamples following the benchmark specification as in Table 2. Huber–White standard errors robust for heteroskedasticity are in parentheses.

***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

{ label (or @symbol) needed for fn[@id='j_izajolp-2022-0003_table-fn_005'] } The letter “a” indicates statically significant differences between estimates within the same column under the same heading at the 5% level. For instance, in the first column, the effect on jobseekers without a bachelor's degree is significantly different from the effect on jobseekers with at least a bachelor's degree. The job-finding rate among men, women, and jobseekers without and with a bachelor's degree aged 45–48 years who registered at the public employment service in 2017 and are unemployed for 6 months is, respectively, 10.3%, 7.9%, 9.3%, and 8.9%. This information is used to compute the effect of the reform in relative terms.

[i] Notes: Sector classified based on the NACE three-digit classification. The table shows the share of long-term unemployed jobseekers aged 45–48 years hired on average in each quarter with a subsidy by sector.

Notes: Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1% and 5% levels, respectively.

EU, European Union; PES, public employment service.

Notes: The regressions include the same (control) variables as the benchmark specification (Table A2 in Appendix A). For the sake of conciseness, only the variables relevant for the placebo tests are shown. The post-reform placebo test does not reject the equality of the coefficients printed in bold, indicating that the parallel trend holds after the reform. The placebo test examining the effect of the abolition on the short-term unemployed rejects that the job-finding rate of jobseekers unemployed for <5 months was affected by the reform. We also test whether the parallel trend holds in the pre-reform period. This trend holds, which indicates that the effectiveness of the hiring subsidy does not vary over the business cycle. Huber–White standard errors robust for heteroskedasticity are in parentheses.

* denotes statistical significance at the 10% level.

Notes: The regressions include the same variables as the benchmark specification (Table A2 in Appendix A). The number of observations decreases when considering longer durations of employment because the unemployment spells are censored after February 2019. Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1%, and 5% levels, respectively.

Notes: The regressions include the same variables as the benchmark specification (Table A2 in Appendix A). In the benchmark specification, the population consists of jobseekers who have worked 4 consecutive months prior to becoming unemployed. The population in the second regression (Row 2) includes all jobseekers regardless of the number of months worked prior to becoming unemployed. The population in the third regression (Row 3) excludes jobseekers who did not work 4 consecutive months prior to becoming unemployed but includes jobseekers whose labor market history is not known. Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1% and 5% levels, respectively.

Notes: The regressions include the same variables as the benchmark specification (Table A2 in Appendix A). In the first regression, unemployment spells are censored when jobseekers leave the labor market. In the second regression, jobseekers aged 44.5–45 years at the time of registration at the PES are included in the treatment group. In the baseline specification, jobseekers who registered at the PES after June 1, 2016, are classified in the post-reform period. Regressions 3–6 examine the sensitivity of the results to this cutoff date by the following approaches: (1) using July 1, 2016, as the cutoff; (2) excluding jobseekers registering at the PES in June 2016 from the regression; and (3) excluding jobseekers who registered at the PES in the period April–June 2016. The last regression examines if the effect of the abolition of the subsidy depends on the unemployment duration. Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1% and 5% levels, respectively.

PES, public employment service.

[i] Notes: This table reports the results of the Breusch–Godfrey LM test for autocorrelation of the grouped error terms. We first obtain the individual error terms after estimating Eq. (1) (Table A2 in Appendix A) and compute the average error by group. A group is defined by the combination of the explanatory variables included in the regression: unemployment duration (dummies), year of registration at the PES, level of education (low, medium, and high), self-reported proficiency in Dutch (three levels), country of origin (three levels), and sex. The grouped error term is then regressed on the lagged error grouped error term and the explanatory variables. Observations are weighted by the inverse of the variance of the dependent variables, which equals the number of observations in a group divided by ŷ_mk(1 − ŷ_mk), with ŷ_mk being the predicted probability of resuming work in group k in month m.

[ii] LM, Lagrange multiplier; OLS, ordinary least squares; PES, public employment service.

Notes: The first DiD regression compares the job-finding rate between the short-term unemployed and the LTU among jobseekers aged 45–48 years, before and after the reform. The second DiD regression tests whether the job-finding rate of short-term unemployed and LTU older jobseekers evolved similarly before and after the reform. The third DiD regression compares the job-finding rate between the short-term unemployed and the LTU among jobseekers aged 40–43 years, before and after the reform. All regressions include the unemployment duration (dummies), year of registration at the PES, educational level, proficiency in Dutch, origin, sex, and age. Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and ** denote statistical significance at the 1% and 5% levels, respectively. The post-reform parallel trend test, shown at the bottom of Column 2, tests whether the post-reform interaction terms (printed in bold) are jointly equal, thereby testing the parallel trend in the post-reform period.

Notes: The first DiD regression compares the job-finding rates between younger (40–43 years old) and older (45–48 years old) LTU jobseekers, before and after the reform. The second DiD regression tests whether the job-finding rates of the LTU in both age groups evolved similarly after the reform (i.e., F-test testing whether the coefficients printed in bold are equal). The third DiD regression compares the job-finding rates of short-term unemployed jobseekers in both age groups, before and after the reform. All regressions include the unemployment duration (dummies), year of registration at the PES, educational level, proficiency in Dutch, origin, sex, and age. Huber–White standard errors robust for heteroskedasticity are in parentheses.

*** and * denote statistical significance at the 1% and 10% levels, respectively. The post-reform parallel trend test, shown at the bottom of Column 2, tests whether the post-reform interaction terms (printed in bold) are jointly equal, thereby testing the parallel trend in the post-reform period.

[i] Note: “U” refers to “unpublished”.