5. Evaluation of wage subsidy programmes for the unemployed in Greece

Along with training, the wage subsidy programme is one of the main active labour market policies (ALMPs) used to connect unemployed people with jobs in Greece. By providing employers with a financial incentive to hire certain categories of jobseekers, wage subsidies can facilitate their integration into the labour market. This chapter examines how effective Greece’s subsidised employment programmes have been in moving individuals into sustainable employment, how this has affected their career prospects, and how the effects vary across groups of individuals and their characteristics.

The results of the counterfactual impact evaluation (CIE) suggest that wage subsidies have large and statistically significant effects on the probability of individuals being in employment. Compared with the results of other studies of similar programmes in other countries, the estimated effects for Greece are generally much larger over all the time horizons examined (up to 36 months after initial entry into the programme). These large employment effects are observed without negatively effecting occupational mobility over the longer term, although some slightly negative effects on occupational mobility are found for time horizons around 15 months.

The chapter is structured as follows. The next section presents the overall results of wage subsidies in terms of the main outcomes studied: employment probability and duration, occupational mobility and earnings. It also compares the results of the CIE with those of similar studies, both for Greece and for other countries. The next section compares the outcomes observed for wage subsidies across subgroups of workers based on age, gender, skill level and location, comparing these effects with those found in similar studies in other countries. The chapter concludes by examining which features of Greece’s wage subsidy programmes are associated with better employment outcomes.

The next sections describe the aggregate results for wage subsidies on selected labour market outcomes and compare them to the results from other studies. The effects of wage subsidies on labour market outcomes are estimated using the selection-on-observables approach described in Chapter 3 of this report. Details on the wage subsidy programmes and their features are also discussed in Chapter 3, with some specific programme parameters also discussed in Section 5.4.

Before examining the counterfactual effects of wage subsidy participants (that is, the estimated difference between the outcomes they achieved through the programme and those they would have experienced without participating), it is instructive to examine the employment outcomes of participants and comparable control group individuals (individuals with similar characteristics). This can help establish reference values of outcomes that are roughly comparable to those contained in analytical reports used for monitoring purposes, with the notable difference that the control group here only includes a subset of the unemployed. Figure 5.1, Panel A compares the employment rates of individuals entering wage subsidies with comparable individuals who did not enter the programme (at least not within that calendar month). It thus excludes the large majority of registered jobseekers who were not comparable to the wage subsidy entrants as well as a small number of wage subsidy participants for whom similar non-participants could not be identified (the comparison group). The note in Figure 5.1 states how treatment and control groups individuals have been matched while more details and the econometric approach are described in Section 3.5 of Chapter 3 and in the accompanying technical report (OECD, 2024[1]).

Initially, virtually all wage subsidy participants are observed to have employment records in the ERGANI database. By contrast, in the control group, individuals are not employed in the month when they are matched to a wage subsidy participant by construction. The initial decline in the share of employed wage subsidy participants mostly reflects individuals (prematurely) leaving the wage subsidy programme, as all programmes analysed are anticipated to last at least nine months.1 At 12 months, 86% of wage subsidy participants remain in employment and at 36 months the proportion stands at 59%. The share of employed individuals in the control group increases from 0% at the beginning of the observation period to 28% by month 12 and stands at 32% at month 36.

Showing the differences between the outcomes of the wage subsidy participants and those of the control group (that is the difference between the two lines in Figure 5.1, Panel A yields the estimates of the counterfactual impact and shows strongly positive results (Figure 5.1, Panel B). The results show that wage subsidies generate large and statistically significant effects on individuals’ probability of being in employment. After 36 months, wage subsidy participants were 27.3 percentage points more likely to be in employment than their matched controls. Given that the subsidy period lasts for a maximum of 24 months – but that for the large majority participants, the actual duration is considerably shorter – these effects capture unsubsidised employment (although, depending on the programme’s specifications, employers may still have an obligation to retain workers for up to six months).

Paralleling the positive effects on employment probability, the impact evaluation results also show a decrease in registered unemployment and inactivity over the entire 36-month time horizon examined (Figure 5.2). Given that wage subsidies affect registered unemployment and inactivity in the first months of participation by construction, it is worth focusing on the effects at the end of the 36-month time horizon. Wage subsidy programme participants have considerably lower rates of registered unemployment and inactivity compared to similar individuals who were not employed via wage subsidies. The results also show that roughly half of the net increase in employment among wage subsidy participants can be accounted for by individuals who would have otherwise been registered as unemployed. Another way to interpret the effects is to separately compare the outcomes between the wage subsidy participants and their matched controls (Annex Figure 5.A.1) as was done also in Figure 5.1, Panel A for the probability of employment. After 36 months, 59% of individuals participating in wage subsidy programmes are employed, 26% are registered as unemployed and 15% are neither. By contrast, among comparable individuals who did not participate in wage subsidies, 32% of individuals are employed, 40% are registered as unemployed and 28% are neither.

Although wage subsidies contribute to a reduction in the share of individuals in registered unemployment, they also lead to an increase in unemployment benefit recipients. In absolute numbers – i.e. examining simple outcomes of wage subsidy participants – the share of individuals in the treatment group receiving unemployment benefits begins to increase beginning at six months (Annex Figure 5.A.1). This coincides with the point at which some individuals have reached the end of the period for which wage subsidies are paid. While the majority of individuals who were participating in a wage subsidy programme remain employed even after they have exhausted the wage subsidies, the minority who become unemployed are potentially eligible for unemployment benefits.

Consistent with the positive effects of wage subsidies on employment probability, wage subsidy participants were employed for a considerably longer period than jobseekers who did not enter subsidised employment (Figure 5.3, Panel A). Over the three-year time horizon studied, they were employed for 524 days more than individuals who did not participate in the wage subsidies programmes. Note that this period includes days worked which were directly subsidised (at least the first nine months), as well as employment during the subsequent period for which wage subsidies were not paid. Half of the additional days worked in this three-year period are attributable to additional days worked during the period after the initial 12 months, when most individuals have exhausted their subsidies. During the first nine months – a period during which employers were paid wage subsidies for individuals on subsidised employment – they were employed for 208 days more than individuals in the control group.

The additional earnings associated with the additional days worked were sizable (Figure 5.3, Panel B). Three years after entering the wage subsidy programme, wage subsidy participants earned at total of EUR 20 389, which amounts to EUR 13 784 more than their control group peers over that three-year period. The trajectory of the increase over time, with subsequent increases remaining positive but diminishing in magnitude, parallel the trajectory of the employment effects, which also become progressively smaller in magnitude. These effects are quite sizable also when taken in the context of counterfactual earnings: cumulatively, after 36 months, individuals in the control group earned an average of EUR 6 605 over the entire period. Roughly half of the additional earnings attributable to the wage subsidy programme (EUR 6 947) is attributable to additional earnings in the first 12 months of programme participation.

To what extent are the wage subsidy programmes potentially cost effective? Direct comparisons of these additional earnings with the programmes’ costs are not feasible due to insufficient information on programme costs. However, examining the parameters of the largest programme can provide a rough sense of the relative magnitude. In this programme, employers who hired participants through the wage subsidy scheme could receive up to EUR 8 250 per participant for nine months of participation in the programme (the minimum amount received, for a minimum wage recipient, would be EUR 5 861).2 These amount to between 43% and 60% of the additional cumulative earnings associated with participating in all the wage subsidy programmes.

In contrast to the robust boost the wage subsidy programme provides to jobseekers’ employment and earnings, programme participation comes with a slightly negative temporary effect on the occupational mobility of participants. Jobseekers entering subsidised employment experienced a small but statistically significant negative effect to their occupational index for most of the first 21 months after starting the wage subsidies (Figure 5.3, Panel C). While the average effect over this period is negative, it is rather small, amounting to an effect size of up to 0.6 percentage points relative to the average observed wage: wage subsidy participants entered occupations which, on average, paid 0.6 percentage points less than the occupations entered by individuals in the comparison group. This provides some evidence that jobseekers may be taking up slightly lower-paying occupations in exchange for their improved employment prospects, which ultimately include higher total earnings.

In order to examine how the results obtained by the CIE of the programmes in Greece compare with those of similar studies in other countries, this section places them in the context of the results of two meta-analyses. The first, conducted by Card, Kluve and Weber (2017[2]), covers 49 countries in total, and summarises estimates from over 200 impact evaluations of ALMPs. Of these, 15 impact evaluations include point estimates of the employment effects of private employment support programmes comparable to the ones in Greece. The second meta-analysis covers projects funded by the EU’s European Social Fund (ESF) and includes estimates from 17 studies examining employment subsidies as well as 14 classified as mixed interventions, combining e.g. subsidies with training components (European Commission and Ismeri Europa, 2023[3]).

The discussion in this section focuses only on the results for employment. As noted in the discussion of training outcomes in Chapter 4, the meta-analysis by Card, Kluve and Weber (2017[2]) does not provide estimates of the effects of other outcomes analysed for Greece, such as earnings or days worked or occupational mobility. While the meta-analysis of the ESF programmes does contain some estimates on measures such as earnings, the number of estimates is insufficient to make meaningful comparisons by programme type.

Compared with the results of the meta-analysis, the estimated effects for Greece are much larger, particularly over shorter time horizons (Figure 5.4). The estimated short-term effect for Greece, 59 percentage points, is considerably higher than the median of 0 and 10 percentage points found in the 2018 and ESF meta-analyses, respectively. The long-term effect, of 27 percentage points, is also considerably higher than the 23 and 19 percentage point median of the 2018 and ESF meta-analyses, respectively.

In interpreting the results, it is worth noting that, while the point estimates in the comparison studies are generally positive, they are not necessarily statistically significant. Figure 5.4 plots all the point estimates in the studies found in the meta-analysis by regardless of statistical significance. In fact, a small majority (58%) of the studies in the Card, Kluve and Weber (2017[2]) meta-analysis do not find positive and statistically significant results over the long term.

Other evaluations of Greece’s wage subsidy schemes do not offer a clear basis for comparison, although they do suggest the interventions are effective. A recent evaluation by the PES (DYPA, 2023[4]) found high employment rates of participants after the end of their subsidy period but did not account for counterfactual outcomes and is thus not directly comparable. An evaluation by the World Bank (2021[5]) of a pilot programme trialling several interventions, including modified wage subsidy programmes, found the programme decreased the probability that participants remained registered as unemployed. However, although the study accounted for counterfactual outcomes, the number of wage subsidy participants in that study was too small to be evaluated separately from the other interventions.

While the empirical results do suggest that Greece’s wage subsidies are effective, the large magnitude of the results should be interpreted with caution given two factors which could conceivably be play an important role in the evaluation of the wage subsidy:

  • Deadweight effects. These effects related to an unintended effect of the subsides and occur when subsidies unintentionally support hiring that would have otherwise occurred without them. Concerns about such effects are present in all wage subsidy programmes, and empirical research has documented that they are indeed present and often sizable (see Brown and Koettl (2015[7]) for an overview of the empirical evidence). Appropriately targeting such wage subsidies – for example, by limiting eligibility to long-term employed – can help limit such effects: a recent evaluation of Lithuania’s wage subsidies, for example, suggested any such deadweight effects were minimal (OECD, 2022[8]). However, in the case of the Greek wage subsidies, the features included in the wage subsidy schemes particularly prior to July 2020– some of which were intended to prevent fraud or strategic behaviour – arguably served to increase deadweight effects (see Section 3.2.2 of Chapter 3 for details). First, the client selection procedure was amenable to strategic behaviour. Consultations with stakeholders indicate that employers could propose their own candidates they wanted to hire, with PES counsellors verifying the eligibility of candidates and employers. This practice, which was phased out with the wage subsidy schemes beginning in July 2020, facilitated the use of wage subsidies to hire individuals who otherwise would have been hired anyway. Second, the wage subsides prior to July 2020 arguably imposed a considerable administrative burden on participating employers. This increased the likelihood that employers willing to bear these costs by participating in the programme were confident they would like to hire – and retain – a given worker. Third, requirements that employers do not reduce staff while they are receiving wage subsidies increase the opportunity costs, in the form of reduced staffing flexibility, of receiving the subsidies. This again makes it more likely that take-up is higher among employers who were certain they would like to hire a candidate anyway.

  • Mismeasurement of counterfactual outcomes due to undeclared work. The large, estimated effect could be partly attributable to measurement of outcomes for control group individuals, comprised of individuals with otherwise similar observed characteristics but who could conceivably be engaging in undeclared work while registered as unemployed. Such undeclared work has the effect of decreasing the observed employment rate of the control group, artificially inflating the difference in the rates of actual employment – declared or undeclared – between the two groups. While significant progress has been made in addressing the prevalence of undeclared employment in Greece – the European Labour Authority (2020[9]) estimates it decreased by ten percentage points between 2014 and 2018 (from 19.2% to 8.9%) – it arguably remained a relevant feature of the labour market for much of the period when the programmes were analysed. Consultations with stakeholders indicate that a sizable share of individuals register with the Greek public employment service (DYPA) in order to be eligible for a range of associated benefits3 and that a sizable proportion of jobseekers are not actively seeking (formal) employment but there are no data to confirm this.

An additional, complementary interpretation of the results is that the wage subsidies are encouraging people in Greece to transition from undeclared work into formal employment. Wage subsidies provide a financial incentive for entering the formal labour market and serve to counteract the financial disincentives to formal employment imposed by the tax system. This interpretation of the results highlights the potential positive impact of wage subsidies on formalising the labour market in Greece.

This section discusses how the results of the wage subsidies vary across sub-groups of the population. It begins by discussing the detailed results for Greece and concludes by contrasting these results with those of other comparable studies.

Given that the results above have documented the generally positive effects of employment subsidies in aggregate, an interesting additional set of questions concerns their effects across different characteristics of subgroups of unemployed. Paralleling the analysis of training in Section 4.3 of Chapter 4, the subsequent analysis provides separate estimates for the results along several dimensions: (i) gender, (ii) age, (iii) level of education, (iv) region of residence, and (v) long-term unemployment status. While the estimated results do differ slightly across some of these characteristics, it is worth bearing in mind that the positive effects on outcomes such as employment probability are present for all groups examined.

Men tend to experience slightly higher boosts to employment probability than women over the longer term (Figure 5.5). Three years after beginning subsidies, the effect size for men is 2.5 percentage points higher than for women, due partly to the lower effects for women over 50 years of age. The effect for women over 50 is considerably lower and reflects a large decrease towards the latter end of the observation period – while the employment effects for women over 50 are higher than for other age groups up until 24 months after receiving the subsidies, the magnitude of the effects decreases considerably thereafter. This pattern may be attributable to the fact that women over 50 are considerably more likely to have a longer subsidy duration, after which they are less likely to retain their employment: during the period studied, 7.9% of women over 50 had their wage subsidy entitlement period extended, significantly higher than any other demographic group (at the other extreme, only 3.7% of men under 30 had their wage subsidy entitlement extended).

In terms of other participant characteristics, there is a markedly positive effect of participation for participants in the two largest cities, Athens and Thessaloniki. Three years after entering wage subsides, the magnitude of the effects for participants living in these cities is ten percentage points higher than for individuals in other locations. As discussed in Chapter 3 (Section 3.3.1), these two cities also had lower rates of jobseekers exiting unemployment compared to jobseekers in the other two geographic breakdowns shown. One possible interpretation of these factors together is that wage subsidies may have stronger effects in weaker labour markets: wage subsidies help boost the demand for workers more if the demand is not as strong.

Individuals who have been unemployed more than 12 months experience a larger boost to their employment probability compared to those who have been unemployed for less than 12 months. The magnitude of the difference – 2 percentage points – is relatively small given that both groups experience boosts to their employment probability that exceed 30 percentage points. Nevertheless, this finding is important particularly in light of the low uptake of wage subsidies for the long-term unemployed. As noted in Chapter 3, during the period studied, the long-term unemployed accounted for 50% of registered unemployed but only 45% of wage subsidy participants. This finding suggests that shifting the targeting of wage subsidies towards the long-term unemployed could increase the aggregate positive impact of the wage subsidies on employment. It would also arguably result in lower deadweight effects given that the probability of jobseekers becoming employed decreases with unemployment duration.

The effects of wage subsidies on the cumulative earnings of different sub-groups of workers (Annex Figure 5.A.2) largely reflect their employment effects. Groups experiencing relatively larger boosts to their employment probabilities – such as the long-term unemployed – also generally experience a larger effect in terms of increased earnings. The one exception to this trend relates to women over age 50 – the relatively lower employment effect for this group is not reflected in lower cumulative earnings. This can be partly explained by a difference in the trajectory of the employment effect for this group: compared to other groups of workers, wage subsidies are observed to have an especially positive employment effect in the first two years after individuals enter the programme. While the underlying reasons for this finding are unclear, it could possibly be explained by a lower willingness by employers to retain such workers after they are no longer contractually required to do so: women over 50 are more likely to have longer subsidy durations (due to extensions) compared to other groups.

In addition to employment outcomes, another interesting dimension for examining the effects of wage subsidy participation relates to occupational mobility. Empirical evidence for other countries has documented the “scarring” effects of job loss (for example, Lachowska, Mas and Woodbury (2020[10])). Interestingly, in the case of Greece, the occupational indices of individuals becoming re-employed are almost unaffected by job loss. Looking in the individual-level data used in the analysis amongst all individuals who are observed to have been employed both before and after a spell of registered unemployment, roughly half (47%) did not experience any occupational mobility. Of the remaining 53%, roughly equal proportions of individuals experienced positive and negative mobility (although a slightly larger proportion, by a margin of 0.4 percentage points, experienced negative mobility).

The counterfactual impact evaluation results on the effects of wage subsidy participation on occupational mobility show strong differences in the profiles by age group and gender. Figure 5.6 shows the changes in the occupational index over time, taking as the reference point the month in which individuals entered the wage subsidy programme. Unlike the results presented in much of this chapter, the results here show outcomes separately for the treatment and control groups. The vertical axis shows the occupational index, measured in percentage points relative to the average wage, for individuals who became employed. Several interesting findings emerge from these figures:

  • Men under 30 who participate in the wage subsidy programme experience statistically significant increases to their occupational index, with the effect amounting to roughly two percentage points. This means that they enter occupations which, on average, pay 2% more, relative to the average wage, than those who do not. Although the point estimates for other age groups of men suggest there may also be a positive effect, the differences are not as large and the estimated differences are generally not statistically significant.

  • The point estimates for women over 30 suggest a slight negative effect on occupational mobility, although the results are mostly not statistically significant. Regardless of whether they participate in the programme, older groups of women who become employed do so at lower-paid occupations compared to the other demographic groups analysed.

The results for Greece share some interesting similarities as well as contrasts with a related type of analysis conducted of Lithuania’s wage subsidies (OECD, 2022[8]). Employing a similar type of approach as in Greece, the results for Lithuania showed that both men and women under 30 who became employed generally experienced increases in their occupational index, regardless of whether they received wage subsidies. Men and women over 50, on the other hand, were found to experience downward occupational mobility – a trend which, in the case of men, wage subsidies helped mitigate. The latter finding of positive effects on occupational mobility is mirrored in the positive results for men under 30 in Greece. It illustrates the potential for wage subsidies to exert a positive effect on the career trajectories of their participants.

Although the 17 individual wage subsidy programmes collectively analysed in the preceding sections have many similarities, they also have some important differences which could conceivably explain some of the observed results. To shed light on these features, this section examines several of the key features of the programmes analysed. Specifically, it first looks at programmes based on whether they were first implemented before and after July 2020, when some important changes to the programmes’ parameters were implemented. As discussed in detail in Chapter 3, these changes were intended to decrease the administrative burden associated with programme participation and lower deadweight costs. The second set of features examined relate to the generosity of individual programmes – the share of earnings subsidised by the programmes and the duration of the subsidies themselves.

Examining the outcomes of the wage subsidy programmes before and after changes the major changes in July 2020 shows that both sets of programmes have broadly similar outcomes (Figure 5.7). The effects on the employment rates of participants in both sets of programmes are virtually identical in the first six months but diverge slightly thereafter (Panel A). This means that participants in the older programmes have a slightly higher probability of being employed (defined as working at least one day in a given calendar month) from the ninth month after entering the programme. However, these differences in the employment rates are not reflected in more days worked or higher earnings: both of these outcomes are almost identical for both programmes examined (Panels B and C). In aggregate, the more positive employment effects of the earlier programmes are thus counteracted by the greater intensity of work and greater earnings of individuals under the later programmes.

An important question in the design of wage subsidy programmes relates to whether the specific parameters of the programmes, such as their duration or generosity, affect their effectiveness. Unfortunately, the results of the analysis do not provide a clear answer to this question: there are no persistent differences in programme characteristics between specific implementations of wage subsidy programmes (details are provided in the accompanying technical report (OECD, 2024[1])). The programmes in the period analysed had a minimum subsidy duration of mostly either 9 or 12 months (although in a small number of cases the minimum duration was 15 months, with extensions of subsidy receipt possible but only observed in a small proportion of cases). The subsidy payment was also generally either 50% or 75% of participants’ wages, with the higher payments more common in programmes first implemented after June 2020 (when other important changes were also made to programme implementation, such as how candidates were selected). Finally, programmes also had different requirements for employers to retain workers after the subsidy period ended, with some programmes having no requirements and others requiring individuals to be retained for up to three months.

The role of programme characteristics in explaining the wide variation in the estimated effects of wage subsidy programmes is unclear. For example, the two programmes with the largest estimated treatment effect sizes 18 months after individuals entered the programme differ in each of their key attributes. Although both provide similarly large increases in employment rates – 51 and 49 percentage points respectively – they are otherwise as different as any of the programmes implemented during the period analysed. Similar differences can also be seen in the other programmes included in the analysis with sufficiently large numbers of participants. An additional complication in attempting to isolate the effect of programme attributes relates to the fact that certain parametric changes were made to all programmes at the same time: several changes were made to all the programmes in July 2020, making it difficult to distinguish time-specific factors (relating to e.g. the COVID-19 pandemic) and those relating to the programmes themselves.

To examine the effect of programme parameters in the future, such evaluations would ideally be factored into the design of programmes. A sensible option for examining the effects would be through a regression discontinuity design (RDD), where changes in eligibility relate to a continuous variable, such as unemployment duration. Such evaluations are possible in the existing data in principle, but the sample sizes are too small to make meaningful conclusions. For example, two of the larger wage subsidies programmes imposed a condition that employers retain workers for 3 months after the subsidy has been exhausted, but only for jobseekers who had been unemployed for less than 12 months before entering the programme. An RDD would examine the effects for individuals immediately below and above the 12-month threshold. If suitable numbers of individuals were observed in such groups – and the data contained information on precisely which group each individual belonged to – this could be used to examine the differences in the programme’s parameters.

As shown in the impact evaluation results discussed in this chapter, Greece’s wage subsidy programmes for the unemployed are effective in helping jobseekers move into employment, leading to long-lasting and meaningful improvements in other labour market outcomes as well. The increased employment rates of wage subsidy participants are also reflected in increased earnings as well as days worked. Wage subsidies also provide a small boost to the occupational mobility of men under 30, but do not affect the occupational mobility of other groups over the longer-term. While wage subsidy programmes are effective for all groups of jobseekers examined, their effectiveness is particularly high for certain groups of jobseekers, such as the long-term unemployed. These results could be used to better inform the targeting of the programmes.


[7] Brown, A. and J. Koettl (2015), “Active labor market programs - employment gain or fiscal drain?”, IZA Journal of Labor Economics, Vol. 4/1, https://doi.org/10.1186/s40172-015-0025-5.

[2] Card, D., J. Kluve and A. Weber (2017), “What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations”, Journal of the European Economic Association, Vol. 16/3, pp. 894–931, https://doi.org/10.1093/jeea/jvx028.

[4] DYPA (2023), Αξιολογηση Προγραμματων Νεων Θεσεων Απασχολησης [Evaluation of new employment programmes: Labour Status Audit of beneficiaries of the programmes during the period June 2020 - March 2022, Pre-publication of the Key Findings Summary, June 2023], https://www.dypa.gov.gr/storage/statistika-stoikheia/meletes-analyseis/prodimosiefsi-aksiologhsh-programmaton-neon-theseon-ergasias.pdf.

[12] Eurofound (2023), Living and working in Greece: Minimum wages, https://www.eurofound.europa.eu/fr/country/greece#pay (accessed on 14 April 2023).

[6] European Commission (2023), , Meta-analysis of the ESF counterfactual impact evaluations – Final report, Publications Office of the European Union, Directorate-General for Employment, Social Affairs and Inclusion, Pompili, M., Kluve, J., Jessen, J. et al.,, https://data.europa.eu/doi/10.2767/580759.

[3] European Commission and Ismeri Europa (2023), Meta-analysis of the ESF counterfactual impact evaluations – Final report, Publications Office of the European Union, https://doi.org/10.2767/580759.

[9] European Labour Authority (2020), Training labour inspectors to use the new IT tools, https://www.ela.europa.eu/sites/default/files/2021-09/EL-TrainingInspectorsToUseNewITtools.pdf.

[10] Lachowska, M., A. Mas and S. Woodbury (2020), “Sources of Displaced Workers’ Long-Term Earnings Losses”, American Economic Review, Vol. 110/10, pp. 3231-3266, https://doi.org/10.1257/aer.20180652.

[11] Ministry of Digital Governance (2023), Greek Public Employment Service, https://www.gov.gr/en/org/dypa/anergia (accessed on 20 July 2023).

[1] OECD (2024), “Technical report: Impact Evaluation of Training and Wage Subsidies for the Unemployed in Greece”, OECD, Paris, https://www.oecd.org/els/emp/Greece_ALMP_Technical_Report.pdf.

[8] OECD (2022), Impact Evaluation of Vocational Training and Employment Subsidies for the Unemployed in Lithuania, Connecting People with Jobs, OECD Publishing, Paris, https://doi.org/10.1787/c22d68b3-en.

[5] World Bank (2021), Monitoring Report #2: Elefsina pilot program, https://documents1.worldbank.org/curated/en/955371622093970259/text/Monitoring-Report-No-2-Elefsina-Pilot-Program.txt.


← 1. The wage subsidy conditions stipulate that individuals leaving the wage subsidy for acceptable reasons can be replaced with another wage subsidy participant. In this case, the duration of the wage subsidy for the second wage subsidy beneficiary is shortened accordingly.

← 2. This refers to the programme “Programme for 10 000 socially and/or long-term unemployed people aged 30-49 years” (Public call 15/2017), where employers could receive up to received up to EUR 750 per month for nine months. Employers could also be compensated for the mandated additional bonuses (Easter, vacation, Christmas) comprising of two additional monthly salaries. The lower amount is calculated based on minimum wages in effect through January 2019 (Eurofound, 2023[12]) assuming 10 monthly wages are paid.

← 3. These include one-off cash transfers for long-term unemployed and a wide array of vouchers, such as those for theatres, books, prescription glasses, and DYPA campsites (Ministry of Digital Governance, 2023[11]).

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