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Extra tax credit, extra R&D?

Extra tax credit, extra R&D?. Maarten Cornet (m.f.cornet@cpb.nl) & Björn Vroomen (b.l.k.vroomen@cpb.nl) CPB Netherlands Bureau of Economic Policy Analysis New Frontiers in Evaluation Vienna, 24 April 2006 (Work in Progress). Outline. Introduction Methodology Cases starter programme

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Extra tax credit, extra R&D?

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  1. Extra tax credit, extra R&D? Maarten Cornet (m.f.cornet@cpb.nl) & Björn Vroomen (b.l.k.vroomen@cpb.nl) CPB Netherlands Bureau of Economic Policy Analysis New Frontiers in Evaluation Vienna, 24 April 2006 (Work in Progress)

  2. Outline • Introduction • Methodology • Cases • starter programme • extension first tax-credit bracket • Added value • Discussion

  3. Introduction • R&D tax-credit programme • ‘simple’ tool • reference point for more complex programmes • Are R&D-support programmes effective? • identification causal relation • literature not convincing • Analysis of (changes in) policy with social experiment framework • We present two examples

  4. The ‘WBSO’ • WBSO: Dutch R&D tax credit programme • ‘Simple’ tool • Reduction of total wage costs (including R&D) • Credit is only based on R&D-employment (total R&D-wage costs) • 40% tax credit for the first € 68k, 13% for the remaining 40 % 13 % € 68K R&D-wage costs € 0

  5. Effective? • Effectiveness of innovation support programmes in general unclear • Causality or correlation? • WBSO↑→ S&O↑ or S&O↑ → WBSO↑? • Identifying a causal relation between instrument and outcome is far from trivial • We use social experiment

  6. Social experiment • Identify two groups; experimental & control • similar participants in that manner that the difference in outcome can only be explained by the treatment • Participants are not randomly assigned and aware of being treated! • Use characteristics of ‘experiment’ (policy) to identify both groups

  7. Data • Data provided by • Dutch Tax and Customs Administration • SenterNovem (Ministry of Economic Affairs, programme administrator) • Data provided on participants in the WBSO-programme • total yearly R&D wages • firm characteristics (branch, turnover, total wages) • period 1994-2003 (focus on 2000-2001) • 28000+ records

  8. Estimators • Difference-in-Difference estimator (DD): compare group averages over time • corrects time specific effects • corrects group specific effects • First-Difference estimator (FD): compare growth/change of individual participants over time • corrects time specific effects • corrects firm specific effects

  9. Changes WBSO 2001 • Starter programme • additional support for new R&D-firms (starters) • ‘goal directed’ programme • Extension of the first tax-credit bracket • €68K -> €90K • ‘general’ programme • Starters benefit from both programs

  10. Credit starter 60 % - 40 % - no starter - 13 % - 90.756 R&D-wage costs Starter programme • Extra 20% credit for R&D-wage costs till 90K

  11. Identification starters • ‘younger’ than 5 years • max three years of starter funding

  12. Ideal case? • Nearly ideal • Difference in age may influence reaction of firms • Difference in experience with the WBSO program (that is, experience with R&D) may influence reaction of firms • Include control variables • age and WBSO experience • firm characteristics

  13. Effect ? • Effect of policy on R&D wage expenditures is estimated between 10% and 20% • Starter vs near-starter • difference-in-difference estimator: 18% (p=0.00) • first-difference estimator: 14% (p=0.00) • Starter vs ‘hidden’ starter • FD-estimator: 11% (p=0.01)

  14. Credit 40 % - 2001 till 2000 13 % - - - 68.067 90.756 R&D-wage costs Extension first tax-credit bracket • Increase upper bound from € 68k to € 90k

  15. Control & Experimental group • Control group 1, firms below € 68k: • no change, credit remains 40% • Experimental group, firms between € 68k and € 90k: • increase credit of 13% to 40% • Control group 2, firms above € 90k: • no change, remains 40% & 13%, however lump sum subsidy

  16. Methodological issues • Firms in ‘control’ group can also be influenced by treatment • difference in effect is estimated • Choice of group sizes can influence results • Group membership is not constant over time •  No convincing causal relation! • Let’s ignore problems for now

  17. Effect ?(ignoring methodological issues) • Compare 50k-68k with 68k-90k • DD-estimator: 2.6% increase (p=0.01) • FD-estimator: 0% (1.7 ns) • Compare 90k-120k with 68k-90k • DD-estimator: 2.9% increase (p=0.01) • FD-estimator: 0% (0.6 ns) • DD +, FD ?  group composition effect? • entrants cause effect?

  18. Value for money • Bang-for-the-buck (BFTB) • Ratio between extra R&D and extra public funding • BFTB defined in wage costs not total R&D • Possible other definitions • total R&D expenditures • number of innovations • number of innovation hours • turnover • social benefits

  19. BFTB • Starter programme • Effect estimated between 10% and 20% • BFTB between 0.5 and 0.9 • Extension first tax-credit bracket • Effect estimated ? between 0% and 3% • BFTB between 0 and 0.15 • Extra funding firms above 90k is quite costly • lump sum (€ 6000)  minimal effect expected • in 2000: 1932 firms near € 12 million

  20. Summary • Starter programme: • successful, clear causal relation • effect 10% - 20% increase R&D wage costs • BFTB 0.5 - 0.9 • Extension first tax-credit bracket: • unclear, methodological issues that hinder identification causal relation • effect ? 3% increase R&D wage costs • BFTB 0 - 0.15 • lump sum is costly

  21. Concluding remarks • Simple tool, however evaluation not trivial • changes in policy useful for evaluation • Starter programme more cost-effective than extension bracket • extensive cost-benefit analysis necessary • Literature: on average BFTB 1 • total WBSO: 1.02 • starter: BFTB 0.5 - 0.9 • extension bracket: BFTB 0 - 0.15

  22. WBSO 1994-2003

  23. WBSO entry 1994-2003

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