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

Belgium is one of the few countries where unemployment insurance (UI) is not time limited, although the benefit level decreases over time. UI amounts to 65% of the (capped) gross wage

The cap decreases with duration of unemployment. In January 2022, it decreased from about €2,900/month during the first 6 months, over €2,700/month during the next 6 months to €2,520/month (€2,470/month for singles living without dependents) when unemployed for >1 year. (www.rva.be/nl/documentatie/infoblad/t67)

Since UI is not time limited, many jobseekers registered at the Vlaamse Dienst voor Arbeidsbemiddeling en Beroepsopleiding (VDAB) (the Flemish PES) are LTU. In 2019, nearly two thirds of the 184,851 jobseekers were unemployed for >6 months, while half of these were unemployed for >1 year (Figure 1). From 2014 until the outbreak of the coronavirus disease-2019 (COVID-19) pandemic in March 2020, the number of jobseekers continuously decreased.

Figure 1

It is well-known that the share of the LTU among the unemployed population increases during economic booms and decreases during economic recessions (Machin and Manning, 1999). This regularity also holds in Flanders. All jobseekers benefited from the economic recovery from 2014 to 2019, but the positive impact was less pronounced for the LTU. In 2019, 65% of the jobseekers were unemployed for >6 months, up from 62% in 2015. Figure A1 in Appendix A shows that a similar pattern emerges when restricting the population to jobseekers aged 40–48 years. As we will explain in section 4, the procyclical behavior of long-term unemployment is the main reason why we opted for a triple-difference evaluation strategy rather than a more standard difference-in-differences (DiD) approach.

The Flemish PES has specific policies, such as training programs and job counseling, tailored to the needs of the LTU (Desiere et al., 2018). Due to a tightening labor market, the PES has renewed and reinforced its attention to the LTU in recent years. In 2017, the PES started to (re)screen jobseekers who were unemployed for >1 year in order to activate them and launched a new tender for the activation of the LTU in 2018.

These programs are unlikely to interfere with the evaluation of the hiring subsidy targeted at jobseekers unemployed for >6 months. First, similar programs have existed before and after the abolition of the subsidy as this aspect of active labor market policies was already a regional competence before the reform. Second, the PES defines a “long-term unemployed jobseeker” as a jobseeker who is unemployed for at least 1 year. Our analysis focuses on jobseekers unemployed for 1–12 months. These jobseekers were not eligible for specific programs aimed at the LTU.

Until a few years ago, the PES applied specific rules when activating and monitoring jobseekers older than 50 years of age. Moreover, this group was eligible for a more generous hiring subsidy until 2014. We restrict the population to jobseekers aged 40–48 years to avoid the possibility that these specific policies for older jobseekers interfere with our evaluation of the hiring subsidy. The PES did not have specific programs in place aimed at jobseekers aged 40–48 years over the entire period considered in the analyses.

Similar to the hiring subsidies, job search monitoring also has become a regional competence and has been subsequently reformed. Since 2016, job search monitoring in Flanders is the competence of the PES and no longer that of a separate federal institution. It is unlikely that the reform of the job search monitoring interferes with the evaluation of the abolition of the hiring subsidy because job search monitoring already occurred before the reform, was not – or, at best, only gradually – intensified after the reform, and did not specifically target jobseekers unemployed for >6 months.

In 2014, wage and hiring subsidies targeted at disadvantaged groups became a regional competence. All four Belgian regions subsequently reformed and simplified the complex existing federal system of wage and hiring subsidies and substantially reduced the number of eligible groups. Flanders opted to abolish all hiring subsidies targeted at the LTU. This paper focuses on the abolition of the hiring subsidy targeted at jobseekers older than 45 years of age who were unemployed for at least 6 months over the past 9 months. After the reform, jobseekers in Flanders aged 25–55 years and unemployed for <12 months were no longer eligible for any hiring subsidy.

The other regions also abolished this specific hiring subsidy, but, in contrast to Flanders, introduced hiring subsidies for jobseekers unemployed for at least 12 months. These hiring subsidies do not depend on the jobseeker's age.

Until January 1, 2017, employers hiring older, LTU jobseekers were entitled to a quarterly Social Security contribution (SSC) reduction of €1,000 during the first five quarters, followed by a quarterly reduction of €400 during the subsequent 16 quarters. Hence, the total maximum hiring subsidy amounted to €11,400 over 21 quarters. The subsidies were reduced (almost proportionally) for employees working part time. In contrast to many other hiring subsidies studied in the literature, no specific conditions were attached to receiving this subsidy: employers were free to offer open-ended or temporary contracts; were not obliged to offer training; did not have to retain the worker for a minimum number of months or offer a nonsubsidized job after the subsidy expired.

The hiring subsidies were not automatically awarded to the employers. Eligible jobseekers had to obtain a certificate from a federal institution proving their eligibility. Employers could then use this certificate to obtain SSC reductions. Eligible individuals (or their employer) could still apply for this certificate after they had been hired, but the subsidies were not granted retrospectively. Given data limitations, the take-up rate of the hiring subsidy is unknown, but the take-up rate of similar SSC reductions is estimated to be approximately 70% (Boucq and Novella, 2018; Desiere et al., 2020).

From January 1, 2017, no new certificates were awarded to Flemish jobseekers, in effect abolishing the hiring subsidy in Flanders. The subsidies granted under the federal rules were gradually phased out. Jobseekers who had obtained a certificate before January 1, 2017, remained eligible for the hiring subsidy until the certificate expired. Employers who had hired an eligible jobseeker continued to receive subsidies until the end of 2018.

In the last quarter of 2016, 2,564 individuals benefited from the hiring subsidy in Flanders, of whom 369 individuals were hired in that quarter. The average, quarterly subsidy amounted to €506, while the total yearly cost of the policy amounted to €5.3 million in 2016.

The median full-time equivalent gross monthly wage (which excludes SSC paid by the employer) of individuals hired with a subsidy is €2,324 and ranges for half of these employees between €1,981 (3rd quartile) and €2,796 (1st quartile). Their income is lower because only one out of four individuals works on a full-time basis. Taking the aforementioned interquartile range as a measure of spread, the abolition of the subsidy increased labor costs by 11%–16% during the first five quarters after being hired and by at most 6% during the 16 subsequent quarters.

These estimates do not take into account the so-called “tax shift”, which gradually reduced employers’ SSC, particularly for low-wage workers (irrespective of their prior unemployment duration or age), from 2016 to 2019. The tax shift partially offsets the negative impact of the abolition of the hiring subsidy on labor costs.

Although the hiring subsidy was not targeted at temporary help agencies, these agencies seem to use this subsidy more intensively for hiring than firms that hire workers directly without the intermediation of such agencies. Between 2015 and 2016, 61% of the LTU aged 45–48 years hired with a subsidy were hired by temporary help agencies (Table A1 in Appendix A). The second most important sector, the cleaning sector, only accounts for 5% of the hires. A representative survey conducted among employers in Flanders in 2016 finds that about 42% of all recruitments are achieved through the mediation of temporary help agencies (Delagrange and Notebaert, 2018, p. 79).

There are two potential reasons why temporary help agencies make more intensive use of the hiring subsidy than firms that directly hire workers. First, as temporary help agencies are specialized in the hiring of workers, they are much better informed about the myriad of hiring subsidies that are available in the Belgian labor market, and therefore, they are more likely to make use of them. For instance, surveys indicate that about 40% of the employers in Flanders are not aware of the existence of hiring subsidies for specific target groups (Boucq and Novella, 2018, p. 10). Second, the Flemish PES announces on its website its partnership with the sector of temporary help agencies and that it regards temporary jobs as “stepping stones” to regular work. This, together with anecdotal evidence that caseworkers of the PES advise unemployed jobseekers to accept temporary jobs (Cockx and Van Belle, 2019), can explain why jobseekers are more likely to be hired by temporary work agencies than by direct hiring firms.

Given the setting, it would be natural to estimate the abolition of the subsidy in a DiD framework, contrasting either short-term unemployed to LTU older jobseekers, or jobseekers younger than to those older than 45 years of age among the LTU.

Figure 3 illustrates the former approach and shows the job-finding rate of jobseekers aged 45–48 years as a function of elapsed unemployment duration before and after the reform. The impact of the abolition of the subsidy appears evident. Due to the improved economic conditions, the job-finding rate is higher for the “control” unemployment durations in 2017 than in 2015, but the job-finding rate abruptly decreases in 2017 at the moment the jobseeker would have become eligible for the subsidy before the reform. Reassuringly, such a “jump” in the job-finding rate is not observed for jobseekers aged 40–43 years (Figure A2 in Appendix A), which suggests that the jump observed here can be attributed to the abolition of the subsidy.

Figure 3

Formal DiD estimates are reported in Appendix B. Contrasting short-term unemployed to LTU older jobseekers, as in Figure 3, suggests that the abolition of the subsidy decreased the job-finding rate by 3.52 pp [95% CI: −4.03 to −3.00]. The DiD model exploiting differences across age groups, rather than across unemployment duration, suggests that the abolition of the subsidy reduced the job-finding rate by 0.14 pp [95% CI: −0.62 to 0.34]. Hence, the abolition of the subsidy has a substantial negative effect (−38%

−38%=−3.52/9.2 (where 9.2% is the job-finding rate of jobseekers aged 45–48 years unemployed for 6 months who registered at the PES in 2017).

Appendix B presents placebo tests that reject the validity of both DiD approaches. The business cycle causes biases in both approaches in opposite directions. Economic upswings have a stronger positive effect on the short-term unemployed than on the LTU, a well-known finding in the literature (Machin and Manning, 1999). Hence, comparing the job-finding rates of short-term unemployed and LTU older jobseekers (as in Figure 3) overestimates the negative effect of abolition of the subsidy since it does not capture the information that, relative to the short-term unemployed, the job-finding rate of the LTU would have deteriorated anyway after the reform due to the improved economic conditions. At the same time, we find evidence that the job prospects of all jobseekers aged 45–48 years, including the short-term unemployed who were not affected by the reform, improved more than those of younger jobseekers after the reform, most likely because the improved economic conditions were more beneficial to older than younger jobseekers. Hence, contrasting the job-finding rate of younger to older LTU jobseekers underestimates the negative effect of the abolition of the subsidy.

The triple-difference approach captures these business cycle effects and avoids wrongly attributing them to the abolition of the subsidy. The weaker identifying assumption of a triple difference, as we show in Section 5.2, is not rejected. The first regression in Table 2 estimates the benchmark specification. The triple-interaction term in the first specification indicates that the abolition of the subsidy reduced the job-finding rate by 1.18 [95% CI: 0.48–1.88 pp]. This is a relatively large effect. Given that the job-finding rate after being unemployed for 6 months is 9.2% after the reform, the hiring subsidy increased the job-finding rate by 13% [95% CI: 5–20%]. We also tested whether the effect on the job-finding rate varied by unemployment duration (Table A6 in Appendix A). While the effect appears to decrease with unemployment duration, a formal F-test rejects the hypothesis that these differences are statistically significant at the 5% level.

Other studies evaluating hiring subsidies targeted at the LTU also report positive effects on the job-finding rate. The results cannot be directly compared since the targeted population, the take-up rate, the subsidy amount, and the subsidy duration differ. Sjögren and Vikström (2015) find that a hiring subsidy in Sweden targeted at jobseekers unemployed or out of the labor force for at least 1 year increased the job-finding rate by 5.8%. This was the finding for the case that the payroll tax (31.4%) was no longer due for a period equal to their time in unemployment or out of the labor force, thereby decreasing labor costs on average by 24% during this period. Doubling the subsidy or doubling the duration of the subsidy increased the job-finding rate by 28% and 65%, respectively. Ciani et al. (2019) and Pasquini et al. (2019) evaluate a subsidy targeted at jobseekers in (Southern) Italy unemployed for at least 2 years using different identification strategies. This hiring subsidy covered 50–100% of the payroll tax of 32.7% for 3 years, thereby reducing labor costs by 12–25%. Ciani et al. (2019) report that the subsidy increased the weekly chance of finding a permanent job by 41%, while, according to Pasquini et al. (2019), the subsidy increased the job-finding rate by 36%.

In order to make the findings of these studies more comparable, we calculate the elasticity of the transition from unemployment to employment with respect to the labor cost. The Belgian hiring subsidy reduced the labor cost by 13% at the median wage level and increased the transition to employment by 13% [95% CI: 5–20%], so that the elasticity equals −1 [95% CI: −1.54 to −0.38]. Similar calculations yield an estimate of this elasticity in Italy of −2.2 and −2.5, respectively, for the studies of Pasquini et al. (2019) and Ciani et al. (2019). By contrast, in Sweden, the elasticities are −0.24 for the single subsidy and −0.59 for the double subsidy. While these are crude estimates that warrant careful interpretation, they nevertheless indicate that our estimates are in-between those for Sweden and Italy, and that hiring subsidies targeted at the LTU are effective, at least in terms of the hiring rate. However, as we discuss in Section 5.3, this effectiveness is transitory.

At the bottom of Table 2, we report the results of two placebo tests. First, we test whether the job-finding rate evolved in parallel in the treatment and control groups in the post-reform period. This approach corresponds to pretending that the reform took place in a “placebo” year after the reform (e.g., in 2017 rather than in 2016) and testing whether the triple-interaction term is insignificant in this case. As explained earlier, the credibility of our DiD approach requires that the parallel trend in the post-reform period – when both treatment and control groups are not treated – holds. This is the case.

The parallel trend also holds in the pre-reform period, which indicates that the effectiveness of the hiring subsidy is not sensitive to the business cycle. This is noteworthy because recent studies have found that wage and hiring subsidies are more effective during downturns (Benzarti and Harju, 2021) and in regions with higher levels of unemployment (Saez et al., 2021).

To rule out bias due to dynamic sorting, we test for autocorrelation based on the Breusch–Godfrey LM test of autocorrelation. To this end, the population is split into groups using all possible combinations of the explanatory variables included in the regression, and the average error in each group is calculated. The grouped error is regressed on the lagged grouped error and the explanatory variables using the inverse of the variance of the dependent variable as weights (Table A7 in Appendix A). We find a small, but significant, positive autocorrelation of 0.053.

In Table 2, we report Huber–White standard errors robust for heteroskedasticity. We could also cluster the standard errors at the individual level to take into account that a minority of the jobseekers have multiple unemployment spells, which could explain the small, positive autocorrelation. In the baseline specification, the clustered standard errors are equal to 0.00361, only slightly larger than the robust standard errors (0.00358).

Finally, we examine whether the results are sensitive to the cutoff date, which determines whether jobseekers are classified in the pre-reform or post-reform period. In the baseline specification, we assume that jobseekers who registered at the PES after June 1, 2016, are not eligible for the hiring subsidy. However, jobseekers who registered at the PES in June 2016 become eligible for the subsidy in December 2016. In practice, these jobseekers do not have much time to obtain the necessary documents proving eligibility. For this reason, we classified these jobseekers in the control group. The results are not sensitive to the choice of the cutoff. The results remain unaltered under the following conditions: (1) using July 1, 2016, as the cutoff date; (2) excluding jobseekers who registered at the PES in June 2016 from the regression; and (3) excluding jobseekers who registered at the PES in the period April–June 2016 (as these jobseekers may not have enough time to apply for the necessary certificates). These sensitivity analyses are presented in Table A6 in Appendix A.

The triple-difference approach exploits differences across unemployment duration, age, and time periods. Substitution and anticipation effects can bias the triple-difference estimates. Regressions 2–4 in Table 2 examine and rule out the possibility that the presence of substitution or anticipation effects bias the findings. This also indicates the absence of general equilibrium effects: the positive effects on the job-finding rate of the target group are not at the expense of ineligible groups.

First, we consider eight age groups to examine whether, prior to the reform, employers hired older jobseekers eligible for the hiring subsidy at the expense of younger jobseekers. Using the triple-difference approach, we evaluate whether the job-finding rates of jobseekers younger than 44.5 years improved after the abolition of the subsidy. To do so, we compare the job-finding rate of jobseekers by age in the age group 38–44 years to the job-finding rate of jobseekers aged 35–37 years. Under the assumption that the substitutability decreases with the age differential, then, if substitution effects do matter, the positive effect of the subsidy on the older eligible unemployed will be at the expense of the job-finding rate of those below the eligibility threshold, and, more so, the closer the age is to the eligibility threshold. For this reason, we also included jobseekers aged 44–44.5 years in the regressions – a group excluded in the baseline specification – because this age group is just below the age eligibility threshold, and, therefore, most likely to be negatively affected by the hiring subsidy. There is no evidence that the job-finding rate of jobseekers just below the eligibility threshold improved after the abolition of the hiring subsidy (Table 2, Regression 2).

Second, we examine whether, prior to the reform, the LTU were hired at the expense of the short-term unemployed. Again, we find no evidence of these substitution effects. The job-finding rate of jobseekers aged 45–48 years and unemployed for 5 months did not improve after the abolition of the subsidy relative to the job-finding rate of jobseekers in the same age group unemployed for <5 months (Table 2, Regression 3).

We also compared the job-finding rate of jobseekers unemployed for 5 months with the job-finding rate of jobseekers unemployed for 1 month, 2 months, 3 months, or 4 months. None of the triple-interaction terms is significant at conventional levels, providing additional evidence that the job-finding rate of jobseekers unemployed for 5 months did not improve after abolition of the subsidy.

Third, we examine anticipation effects. The decision to abolish hiring subsidies for the LTU took time and was not (unexpectedly) announced at a specific point in time. Hence, employers could have anticipated the reform and hired more LTU jobseekers just before the abolition of the subsidy. The reform was, however, barely discussed in the Flemish media

We conducted a search of the Flemish media using GoPress. A few newspaper articles in 2015 mentioned that the existing hiring subsidies would be reformed and suggested that the hiring subsidies for the long-term unemployed might be abolished. In 2016, several newspaper articles discussed the reform in more detail.

While the subsidy increased the job-finding rate of the LTU, the question remains whether the subsidy successfully created stable employment. Descriptive evidence presented earlier indicates that subsidized employment tends to be a short-lived process. Moreover, search and matching models predict that hiring subsidies increase job creation and job destruction, leading to less-stable jobs (Kaas and Kircher, 2015; Mortensen and Pissarides, 2001). Most previous studies have not focused on employment stability, although creating stable jobs is often an explicit objective of hiring subsidies. One notable exception is the study by Sjögren and Vikström (2015), who present evidence that workers holding subsidized jobs are more likely to retain their job even after the subsidy expires. A recent evaluation of a payroll tax cut for young workers in Sweden also finds persistent effects after the workers’ age moves out of eligibility and even after abolition of the policy (Saez et al., 2021).

To test the effect of the subsidy on employment stability, we again rely on the triple-difference approach but use different outcome variables. We first use a more stringent definition of “employment”, which excludes temporary help agency work. Next, we define two related outcome variables that capture employment stability. The first outcome is defined as finding a job and remaining employed for 1–12 consecutive months after being hired, while the second outcome is defined as finding a job and being employed for 1–12 (not necessarily consecutive months) in the next 12 months after being hired. The second indicator allows us to test whether short-lived employment spells created by the subsidy serve as a stepping stone to other (short-lived) employment spells within the next 12 months.

As mentioned earlier, the Flemish PES records different types of “work”. The regressions presented so far consider any type of employment as a positive outcome. The fifth regression in Table 2 uses a more stringent definition of work, which excludes several types of atypical work, most importantly, temporary help agency work that lasted between 10 days and 20 days per month. Excluding atypical work as a positive outcome halves the triple-interaction term to −0.6 pp, but the effect remains statistically significant at the 5% level. This is a first indication that the hiring subsidy mainly created short-lived employment and had a more-limited effect on the creation of more-stable employment.

To further examine employment stability, we redefine the outcome as finding a job and remaining employed for several (consecutive) months in the next 12 months after being hired, again including all types of work. Figure 4 visualizes the results of the triple-difference regressions for both outcomes. The subsidy has a more pronounced effect on finding short-lived employment than on longer-lasting employment. The effect of the abolition of the subsidy converges toward zero with increasing employment duration. While the abolition of the subsidy reduced the likelihood of being employed for at least 1 month by 1.18 pp, the abolition reduced the likelihood of being employed for at least 6 and 12 consecutive months by 0.41 and 0.05 pp, respectively. In relative terms, this implies that the hiring subsidy increased the job-finding rate by 13%, but it only increased the probability of being employed for at least 6 and 12 consecutive months by 6.6% and 1.5%, respectively. This is in line with the graphical evidence presented in Figure 2, which suggests that the employment trajectories of individuals hired with a subsidy were less stable than those of individuals hired without a subsidy.

Figure 4

Abolition of the subsidy has only a slightly larger effect on the number of months worked (not necessarily consecutive) over a 12-month period after being hired (Figure 4, right panel) than on the number of consecutive months worked over the same period (Figure 4, left panel). Hence, the short-lived employment spells created by the subsidy do not serve as stepping stones to other employment spells in the next 12 months.

The results remain qualitatively similar when using the more stringent definition of employment (Figure A3 in Appendix A). While the subsidy's effects on the job-finding rate are more limited when excluding atypical work, the effect of the subsidy on stable employment still tends toward zero for employment spells that last at least 12 (consecutive) months.

In this section, we examine whether certain groups of jobseekers benefited more from the hiring subsidy. We explore effect heterogeneity along two dimensions: gender and level of education. These dimensions are important for three reasons. First, systematic reviews of ALMPs often report estimates along these dimensions. For instance, the review of Card et al. (2018) reports a larger impact for women and for disadvantaged groups. Second, we compare our findings with those of Sjögren and Vikström (2015), who report larger effects for LTU men and LTU individuals without university education. Third, a heterogeneity analysis can shed light on the underlying mechanism explaining the results.

Table 3 examines the effect of abolition of the subsidy on the job-finding rate and on employment stability by gender and level of education. The hiring subsidy is more effective for jobseekers with at least a bachelor's degree. It also appears to be more effective for women (+21.4% in relative terms) than men (+7.8%), but the difference between the effects on men and women is not statistically significant (Table 3, Column 1).

The post-reform placebo tests also hold for each of the subsamples. This observation rules out the possibility that the effect heterogeneity observed here can be attributed to a failure of the parallel trend for specific groups.

For all groups, the effect of the subsidy decreases with employment duration, confirming that the subsidy did not create stable employment (Table 3, Column 3). For the higher educated, the effect is still significantly positive for remaining employed for 6 consecutive months, but it is only 60% of its effect on the job-finding rate, and it further decreases to 35% of this effect (not reported in Table 3) when considering 12 instead of 6 consecutive months. Unfortunately, as the subsidy can last as long as 21 quarters, the data do not allow to check whether the effect for the higher-educated group converges to zero after the subsidy expires, but the pattern of the effect does suggest this.

Our findings are the opposite of those of Sjögren and Vikström (2015), who report larger effects for individuals without a university education and also for men. They interpret these findings as suggestive evidence that the private sector, which tends to employ more men, is more responsive to the policy, and that labor demand is more sensitive at the lower end of the pay distribution, which explains why the hiring subsidy is more beneficial to lower-educated workers. The latter explanation is not relevant in our setting because individuals with a bachelor degree hired with the subsidy have only slightly higher wages than individuals without a bachelor degree (mean monthly gross wage of €2,489 vs. €2,139, respectively), presumably as a consequence of the relatively high minimum wages in Belgium [see, e.g., Rycx and Kampelmann (2013)], and that dismissed workers among the high educated are more negatively selected than among the low educated.

We see the following explanations for our findings. First, our analysis focuses on laid-off “mid-career” individuals. At this stage of the career, job loss usually goes in pair with substantial losses in firm-specific labor market experience and human capital. Consequently, the hiring subsidy and the temporary spells of employment cannot compensate for this loss, making it hard without retraining to materialize an enduring – lasting beyond the subsidization period – labor market reintegration. The finding that higher-educated workers are more likely to be temporarily hired than lower-educated workers owing to the subsidy could be related to their acquisition of more general, transferable skills: this makes them more likely to be hired in different jobs than those from which they were laid-off; the subsidy may compensate for the higher wage costs that are required to make these jobs acceptable or may make up for the productivity gap linked to the reallocation.

Second, we already highlighted that the subsidies were mainly used by temporary help agencies. Out of all hires with a subsidy, roughly 60% were hired by temporary help agencies. It is noteworthy that groups that traditionally rely more on the services of temporary help agencies, namely, (men and) lower-educated jobseekers, are also the groups that benefited less from the subsidy. The subsidies seem to have provided a windfall profit for temporary help agencies, which would anyway have offered temporary jobs to low-educated jobseekers. However, without a subsidy, the hiring of jobseekers with a university degree did not seem profitable for these agencies. By the above argument, the wage subsidy could therefore create additional employment for these workers. However, this employment is not long-lasting or does not seem to be a stepping stone to other, more persistent employment, probably because temporary work is not skill enhancing and may even stigmatize workers (Autor and Houseman, 2010; Givord and Wilner, 2015). This is in line with the findings of Cockx and Van Belle (2019) and Cockx et al. (2020), who report that, in Belgium, temporary work does not cause long-lasting employment for unemployed youth. In addition, it can also explain why, as reported in Section 3, most of the subsidized jobs ended before the subsidy was exhausted. Temporary help agencies offer temporary jobs, which are highly unlikely to exceed the maximum duration of the subsidy (about 5 years).