Start-up Subsidies for the Unemployed The German Experience

Start-up Subsidies for the Unemployed The German Experience Steffen Künn Institute for the Study of Labor (IZA), Bonn www.iza.org Research Seminar on Self-employment May 21, 2015, Brussels

Key References Caliendo, M., and S. Künn (2011): Start-Up Subsidies for the Unemployed: Long- Term Evidence and Effect Heterogeneity. Journal of Public Economics, 95 (3-4), 311-331. Caliendo, M., and S. Künn (2014): Regional Effect Heterogeneity of Start-Up Subsidies for the Unemployed. Regional Studies, 48 (6), 1108-1134. Caliendo, M., and S. Künn (2015): Getting Back into the Labor Market: The Effects of Start-Up Subsidies for Unemployed Females. forthcoming in: Journal of Population Economics, DOI: 10.1007/s00148-015-0540-5. Caliendo, M., J. Hogenacker, S. Künn and F. Wiessner (2015): Subsidized Start-Ups out of Unemployment: A Comparison to Regular Business Start-Ups. Small Business Economics, 45(1), 165-190. Policy Paper Caliendo, M. (2015): Start-up Subsidies for the Unemployed: Opportunities and Limitations, forthcoming in: IZA World of Labor.

Active Labor market Policies to Fight Unemployment Active labor market policies (ALMP) are common tools to reintegrate unemployed into the labor market (OECD: 0.6% GDP, 2008). ALMP usually consist of traditional measures such as job creation schemes, training programs, job search assistance, or wage subsidies. Goal: Remove severe disadvantages in education, work experience or productivity.

Active Labor market Policies to Fight Unemployment Active labor market policies (ALMP) are common tools to reintegrate unemployed into the labor market (OECD: 0.6% GDP, 2008). ALMP usually consist of traditional measures such as job creation schemes, training programs, job search assistance, or wage subsidies. Goal: Remove severe disadvantages in education, work experience or productivity. Evaluation studies show that labor market effects associated with traditional programs of ALMP are rather mixed (Card et al., 2010): Job creation schemes: Overall ineffective to improve participants labor market perspective (Caliendo et al., 2008). Training programs: Evidence is mixed in medium-run. Modest effects in the (very) long-run (Kluve/Schmidt, 2002; Martin/Grubb, 2001). Wage subsidies: Mixed evidence (Betcherman et al., 2004; Lechner/Wunsch, 2008).

Start-up Subsidies for the Unemployed Start-up subsidies have become a promising alternative Main idea: Unemployed receive a subsidy to start their own business in order to escape unemployment. Goal: Removing disadvantages faced by the unemployed: Capital constraints (Start-up specific) Human capital etc.

Start-up Subsidies for the Unemployed: Pros and Cons Promising alternative to traditional ALMP programs Attractive for individuals whose work is under-valued in paid employment (e.g. with low formal skills) or who face discrimination (e.g. migrants) Alternative to limited job offers in dep. employment for subgroups (e.g. part-time for women) or due to structural changes in regions/industries Potentially, subsidy could not only fight unemployment by reintegrating unemployed...but also lead to a double dividend if there is additional job creation Positive macroeconomic effects: Increased competition leads to efficient markets/technology diffusion and probably to economic growth Concerns Adverse selection: Low-ability ind. might enter self-employment Moral hazard due to no/low risk of income loss Deadweight effects: Outcome would be achieved also without subsidy Crowding-out of incumbent or non-subsidized firms

Resulting Questions: What is of Interest? ALMP perspective: Can these programs deliver? Do they sustainably escape unemployment? What are the long-term effects (employment, income)? Higher effects for different sub-groups? Comparison group: Other unemployed individuals! Economic growth perspective: Do they found successful businesses? Are unemployed individuals qualified enough to start an own business? Old dogma: Necessity start-ups are doomed to fail! How do they perform over time (survival, growth, innovation)? Comparison group: Regular start-ups!

Start-up Subsidies in Germany: Institutional Settings For a certain period individuals could choose between two programs. Main difference: Amount and length of the transfer payments! Bridging Allowance (BA), introduced in 1986, unemployment benefits plus 70% (for SSL), maximum duration: six months. Start-up Subsidy (SUS), introduced in 2003, fixed sum of e600 per month in the first year, e360/e240 in the second/third year. Participants differ: BA recipients are on average better qualified with higher earnings in the past! Both programs were combined to one single subsidy in August 2006. New Start-up Subsidy (New SUS), unemployment benefits plus e300 (for SSL) for nine months; e300 might be extended for further six months. Abolishment of the legal claim in Dec 2011.

Evaluation from an ALMP perspective! Are these programs effective in......avoiding unemployment?...integrating individuals in regular employment or self-employment?...increasing the personal income of individuals?...and if so, for whom do they work best (effect heterogeneity)? Data and Methodology Entries into SUS/BA in the third quarter of 2003 Administrative data enriched by survey information Observation period: 56 months after start-up Control group: Other unemployed individuals in third quarter of 2003 who did not participate in SUS/BA Methodology: PS Matching Details

60% are still self-employed after 56 months! Table: Labor market status of participants Men Women SUS BA SUS BA Self-employed 59.7 67.9 59.6 66.6 Unemployed 11.7 6.7 7.8 3.0 Employed 20.9 21.1 16.7 23.5 Labor market integration 80.6 89.0 76.3 90.1 Note: Results are in percent.

High labor market integration of participants! Causal Effects: Start-up Subsidy vs. Non-Participation Men Women τ 56 (in%-points) = 22.1 τ 56 (in%-points) = 25.5 56 t=1 τ i (in months) = 23.5 56 t=1 τ i (in months) = 26.9 Note: Matching estimates are based on kernel matching. Bootstrapped standard errors with 200 replications; 5% confidence interval is depicted by dashed lines.

High labor market integration of participants! Causal Effects: Bridging Allowance vs. Non-Participation Men Women τ 56 (in%-points) = 14.5 τ 56 (in%-points) = 10.6 56 t=1 τ i (in months) = 14.6 56 t=1 τ i (in months) = 12.7 Note: Matching estimates are based on kernel matching. Bootstrapped standard errors with 200 replications; 5% confidence interval is depicted by dashed lines.

Income is considerably higher than in the control group! Table: Monthly net earnings (in Euro) after 56 months Men Women SUS BA SUS BA Total Income 2092.5 2600.3 1486.8 1767.0 Working Income 2027.5 2501.4 1391.9 1687.8 Causal effects: Participants vs. Non-Participants Total income 270 485 138 225 (121) (110) (84) (137) Working income 435 618 98 189 (135) (110) (80) (134) Note: Results are in Euro per month.

Effect heterogeneity Who benefits most? Groups with bad labor market perspectives, i.e. low educated and low qualified workers Disadvantaged regions in terms of UE rate and GDP Higher effects for women Programs seem to be an alternative to dependent employment overcome labor demand side restrictions!

Evaluation from a business perspective! Questions to explore Are unemployed individuals qualified enough to start an own business? Old dogma: Necessity start-ups are doomed to fail! How do they perform over time (survival, growth, innovation)? Double dividend: Do they create additional jobs? Data and Methodology Entries into the New SUS in the first quarter of 2009 Administrative data enriched by survey information Observation period: 19 months after start-up Control group: Regular start-ups, i.e., non-subsidized out of non-unemployment, in the first quarter of 2009 Methodology: Decomposition based on PS Matching

A detailed look at the business performance Table: Measured 19 months after start-up Subsidized founders Regular founders Business survival 80.7 74.4 Monthly income (in Euro, net) 3,389 3,073 Business growth At least one employee 36.1 56.5 Number of full-time equivalents (FTE) 3.1 6.2 Self-employed 80.7 74.4 At least one employee 36.1 56.5 = FTE per start-up 0.90 2.61 Innovation Filed patent application 2.0 2.6 Protection of corporate identity 6.8 16.0 Higher survival but lag behind in terms of income, innovation and business growth after 1.5 years! Double dividend: 100,000 New SUS start-ups generated 90,000 FTE.

Conclusion Programs are effective from an ALMP perspective Escaping unemployment Improving labor market prospects Alternative to limited job offers for/in disadvantaged groups/regions However, programs induce a negative bias in terms of business performance (long-term evidence needed)!

Conclusion Programs are effective from an ALMP perspective Escaping unemployment Improving labor market prospects Alternative to limited job offers for/in disadvantaged groups/regions However, programs induce a negative bias in terms of business performance (long-term evidence needed)! Policy Conclusions: Start-up subsidies for the unemployed: An interesting alternative (from am ALMP perspective), but not for everyone (from a business perspective)! More commitment and stronger entry controls might help to increase the efficiency. Additional support needed? Business coaching or mentoring? Open Questions Macroeconomic effects? Deadweight losses? Displacement effects?

Dr. Steffen Künn Senior Research Associate IZA - Institute for the Study of Labor Schaumburg-Lippe-Str. 5-9 53113 Bonn, Germany Email: kuenn@iza.org