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New Evidence on Long-Term Effects of Start-Up Subsidies: Matching Estimates and their Robustness

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  • Marco Caliendo

    (University of Potsdam, IZA Bonn, DIW Berlin, IAB Nuremberg)

  • Stefan Tübbicke

    (University of Potsdam)

Abstract

The German start-up subsidy (SUS) program for the unemployed has recently undergone a major make-over, altering its institutional setup, adding an additional layer of selection and leading to ambiguous predictions of the program’s effectiveness. Using propensity score matching (PSM) as our main empirical approach, we provide estimates of long-term effects of the post-reform subsidy on individual employment prospects and labor market earnings up to 40 months after entering the program. Our results suggest large and persistent long-term effects of the subsidy on employment probabilities and net earned income. These effects are larger than what was estimated for the pre-reform program. Extensive sensitivity analyses within the standard PSM framework reveal that the results are robust to different choices regarding the implementation of the weighting procedure and also with respect to deviations from the conditional independence assumption. As a further assessment of the results’ sensitivity, we go beyond the standard selection-on-observables approach and employ an instrumental variable setup using regional variation in the likelihood of receiving treatment. Here, we exploit the fact that the reform increased the discretionary power of local employment agencies in allocating active labor market policy funds, allowing us to obtain a measure of local preferences for SUS as the program of choice. The results based on this approach give rise to similar estimates. Thus, our results indicating that SUS are still an effective active labor market program after the reform do not appear to be driven by “hidden bias”.

Suggested Citation

  • Marco Caliendo & Stefan Tübbicke, 2019. "New Evidence on Long-Term Effects of Start-Up Subsidies: Matching Estimates and their Robustness," CEPA Discussion Papers 06, Center for Economic Policy Analysis.
  • Handle: RePEc:pot:cepadp:06
    DOI: 10.25932/publishup-42679
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    2. Siddhartha Bandyopadhyay & Sanjukta Sarkar & Rudra Sensarma, 2021. "Does Access to Key Household Resources Help in Reducing Violence against Women?," Discussion Papers 21-09, Department of Economics, University of Birmingham.
    3. Melcangi, Davide & Turen, Javier, 2023. "Subsidizing startups under imperfect information," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 93-109.
    4. Remya Tressa Jacob & Rudra Sensarma, 2022. "Does knowledge empower? A story of debt literacy and credit usage in rural consumer finance," Working papers 529, Indian Institute of Management Kozhikode.
    5. Francesco Manaresi & Carlo Menon & Pietro Santoleri, 2021. "Supporting innovative entrepreneurship: an evaluation of the Italian “Start-up Act” [The effects of entry on incumbent innovation and productivity]," Industrial and Corporate Change, Oxford University Press, vol. 30(6), pages 1591-1614.
    6. Caliendo, Marco & Tübbicke, Stefan, 2021. "Design and effectiveness of start-up subsidies: Evidence from a policy reform in Germany," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 333-340.
    7. Gabrikova Barbora & Svabova Lucia, 2022. "Allowance for Self-Employed Gainful Activity in Slovakia: A Closer look into the Factors Involved," Folia Oeconomica Stetinensia, Sciendo, vol. 22(2), pages 55-77, December.

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    More about this item

    Keywords

    Start-Up Subsidies; Policy Reform; Matching; Instrumental Variables;
    All these keywords.

    JEL classification:

    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship

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