The Effects of Hiring Subsidies for Older Workers

The Effects of Hiring Subsidies for Older Workers on Unemployment Durations in Germany Andreas Ammermüller Bernhard Boockmann Michael Meier Thomas Zwick Centre for European Economic Research (ZEW), Mannheim 1

Outline (1) Introduction (2) Description of hiring subsidies (3) The data (4) Estimation approach and implementation (5) Results (6) Conclusions 2

Introduction Two questions should be distinguished: 1. Do hiring subsidy programmes causally lead to earlier exit from unemployment to employment in the group of eligible persons as compared to the situation in which no subsidies are available? 2. Do subsidised hirings causally lead to more unsubsidised employment? Forslund et al. (2004), Sianesi (2003), and Hujer et al. (2002) In this paper, the focus is on the first question 3

Conditions for the effectiveness of hiring subsidies • Static model with perfect competition on the labour market: hiring subsidy lowers net wages paid by the employer and increases demand for subsidised employees • Reaction depends on wage elasticity: dln. L/ds = /( + ) , where L is subsidised employment • If elasticity is low, deadweight effects (Buslei and Steiner, 1999; Hujer and Caliendo, 2003; Meyer, 1995 a) occur • Empirically, wage elasticities differ between male/female and single/married and East/West Germany 4

More reasons why hiring subsidies may fail to affect the number of hirings • Hiring subsidies may provide too low an incentive and / or may not be known among eligible firms and workers implementation study • In addition to deadweight effects, hiring subsidies may be ineffective due to substitution or a displacement effect • Since our approach is based on individual-level data, we concentrate on deadweight effects. The particular interest in the deadweight effect is whether the programme is effective for the targeted group 5

Estimating deadweight effects • Deadweight effects involve a counterfactual that must be estimated • In this paper we use changes to the eligibility rules as „natural“ variation • Before 2002, the Integration Supplement for older workers was only available for hiring long-term unemployed workers. Taking effect on January 1 st, 2002, this condition was dropped • Taking effect on January 1 st, 2004, the EGZ subsidy for older workers was integrated into the framework of the general EGZ, so that workers aged 50+ lost preferential treatment 6

Description of hiring subsidies (EGZ) in Germany • One of the major instruments of German active labour market policy • Legal basis: German Social Code (SGB), Volume III • EGZ are paid to the employer as a percentage of standardised labour costs (maximum 50 per cent) for up to 24 months (other limits for workers with specific disadvantages) • If the employment relationship is terminated before a minimum period after the expiration of the subsidy, the employer is legally obliged to refund parts of the subsidy • No legal claim to EGZ either by the worker or the employer 7

Employment contracts subsidised by Integration Supplements 8

Implementation of the programme • EGZ is regarded as an important instrument by employment agencies • There is substantial scope for decision-making concerning the allocation of the subsidy • In the majority of cases, an initial contact between a worker and an employer already existed • It will often be difficult for placement officers to decide whether the company would refrain from hiring without EGZ • The implementation study strongly confirms the notion that deadweight effects are a major issue 9

The data • Evaluation is based on the Integrated Employment Biographies (IEB) • The IEB are composed of four separate data bases: • Employment Register (Be. H) • Benefit Claimants Register (Le. H) • Programme-Participants Comprehensive Data Base (MTG) • Job Applicant Files (ASU) 10

Estimation approach and implementation The paper uses two legal changes in eligibility as natural variation • First, before 1 -1 -2002 eligibility was limited to individuals aged 50+ who were either long-term unemployed (in the legal definition) or had been unemployed for more than 6 consecutive months; this criterion was dropped in 2002 • Hence, workers 50+ and not fulfilling the criterion are used as the treatment group • Second, on 1 -1 -2004 EGZ subsidies for older workers were integrated into the general EGZ framework; workers 50+ lost preferential status • Hence, workers 50+ are used as the treatment group 11

Estimation approach and implementation Definition of age groups: o workers aged 50 to 50+6 months at the time of entering unemployment (treatment group) o workers aged between 49 and 49+6 months (control group) • Treatment and control group are observed before and after the legal changes • We observe individuals belonging to a 3 -months entry cohort during a period of 180 days after entry in unemployment 12

Time frame for the difference-in-differences analysis Policy change 13

Three difference-in-difference estimators (1) time varying unconditional effect obtained from Kaplan-Meier. Survivor functions (DD 1): (2) estimation of a PH model and calculation of the treatment effect on the survivor function (DD 2): 14

Three difference-in-difference estimators (3) time varying conditional effect calculated from the difference-indifferences of the baseline hazard rate of the Cox partial likelihood model (DD 3) 15

Validity of the DD estimators • The most important assumption underlying the difference-indifferences estimator is that all differences in the changes of the outcome variable between the treatment and the control group are due to the treatment • A number of reasons why this could by invalid: 1. Other programmes affecting treatment or control group differently 2. Other influences on particular age groups 3. Anticipation effects 16

Exits into subsidised employment 2001 2002 2003 2004 Treatment Group (Age 50 to 50+6 months) 1. 16 (6209) 3. 72 (7320) 3. 03 (14406) 0. 94 (16389) Control Group (Age 49 to 49+6 months) 0. 82 (6453) 1. 14 (6947) 1. 25 (14374) 0. 52 (17181) Note: Number of individuals in parentheses, t-statistics estimated robustly. 17

DD 1 -effect on employment, 2002 18

DD 1 -effect on employment, 2002 Men, West Men, East Women, West Women, East 19

DD 1 -effect on employment, 2004 20

DD 1 -effect on employment, 2004 Men, West Men, East Women, West Women, East 21

Conditional DD Results (DD 2 -Effect), 2002 All workers Men West Men East Women West Women East 1, 00 0, 98 1, 01 1, 07 0, 88 (-0, 01) (-0, 28) (0, 07) (0, 9) (-0, 87) 0, 95 1, 06 0, 92 0, 94 0, 64 (-1, 15) (0, 93) (-1, 01) (-0, 91) (-2, 94) Interaction term 1, 03 (0, 6) 0, 98 (-0, 22) 1, 05 (0, 41) 0, 99 (-0, 15) 1, 64 (2, 32) PH test, p-level 0, 57 0, 90 0, 92 0, 31 0, 99 DD 2 Number of obs. 0. 68 23760 -0, 43 8870 1, 25 3895 -0, 26 8440 6, 88 2555 LR chi 2 367, 75 131, 82 87, 81 84, 29 31, 72 After treatment (2002) Treatment group (age 50 to 50+6) 22

Conditional DD Results (DD 2 -Effect), 2004 All Men West Men East Women West Women East After treatment (2004) 0, 99 (-0, 51) 0, 88 (-2, 7) 0, 97 (-0, 48) 1, 06 (1, 07) 1, 18 (2, 02) Treatment group (age 50 to 50+6) 0, 97 (-1, 12) 0, 89 (-2, 39) 0, 99 (-0, 17) 1, 02 (0, 36) 1, 04 (0, 46) Interaction term 0, 95 (-1, 23) 1, 10 (1, 39) 0, 99 (-0, 06) 0, 80 (-2, 88) 0, 85 (-1, 43) PH test, p-level 0, 24 0, 13 0, 96 0, 13 0, 04 DD 2 Number of obs. -0, 74 57449 1, 48 20490 -0, 10 10154 -2, 84 18253 -1, 92 8552 LR chi 2 954, 51 333, 36 363, 27 139, 51 80, 05 23

Conditional DD Results (DD 3 -Effect), 2002 24

Conditional DD Results (DD 3 -Effect), 2004 25

Conditional DD Results (DD 3 -Effect), 2002 West East Men Women 26

Conditional DD Results (DD 3 -Effect), 2004 West East Men Women 27

Evidence on deadweight effects • How does the number of jobs created with the help of hirings subsidies compare to the number of subsidies disbursed? • Compare number of exits into subsidised and unsubsidised jobs – if the latter declines by as much as the first increases, crowding out is complete • Competing risks framework using differences of differences to the cumulative incidence functions of exit into subsidised and unsubsidised jobs • All results are unconditional on covariates 28

DD of the Cumulative Incidence Function, 2002 29

DD of the Cumulative Incidence Function, 2004 30

Conditional DD Results (DD 3 -Effect), 2002 West East Men Women 31

Conditional DD Results (DD 3 -Effect), 2002 West East Men Women 32

Conclusions • We have used a natural experiment design to answer the question whether hiring subsidy programmes are effective • Two changes were compared: extension of eligibility for workers aged 50+ in 2002 and abolishment of preferential treatment for the same group in 2004 • Application of three Di. D estimators shows that employment effects for workers as a whole are insignificant and small compared to the number of subsidised hirings • Competing risks framework suggests that the EGZ is not very effective in the group of treated individuals and deadweight effects are important • However, for East German Women (in 2002) and Women in both parts of Germany (in 2004), some effects are significant and large 33 relative to subsidised hirings deadweight effects much smaller here