Sequential Innovation, Patents, and Imitation - Research on Innovation
Direct and indirect effects of Innovation Policies · • Evaluation of these impacts are...
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DIRECT AND INDIRECT EFFECTS OF S&T
POLICIES: QUESTIONS AND CHALLENGES FOR
EVALUATION
Coloquio sobre evaluación de políticas de CTI, 19 de junio 2014
Camino Real Pedregal
Chiara Criscuolo
Structural Policy Division
Science, Technology and Industry Directorate, OECD
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The rationale for public support for R&D
Public support to R&D addresses the less-than-socially-optimal private investment stemming from projects with large expected social benefits but inadequate expected private returns (Arrow, 1962).
Government support to business R&D aims to address market failures, and in particular to:
• Align private and social return, and mitigate the “incomplete private appropriability” characterising the production of scientific and technical knowledge (Nelson, 1959; Arrow, 1962);
• Correct for information asymmetries, characterising R&D and innovation activities, which may lead to difficulties in finding external finance.
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Supporting R&D: policy tools
Two broad R&D policy instruments exist:
1) Direct procurement and public funding of knowledge-based innovative activities carried out by public entities (universities, research centres, etc.);
2) Public support to commercial R&D, i.e. incentives for a greater amount of private investment, in the form of:
Tax credits: based on firm-level R&D activity. Market based tool.
Directly reduce marginal cost of R&D activities.
Allow private firms to choose projects.
Direct R&D subsidies: project-specific tools.
Allow public bodies to target projects with perceived high marginal social rates of return.
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• R&D grants
– Directed at specific projects (government/government agency chooses)
– Often targeted to national needs
– Sometimes targeted to collaborative research (with universities; government; other firms)
– Certification effect ;
• Tax incentives for R&D
– Market based method, affect price of R&D
• Expenditure based
– Accelerated depreciation - usually 100%, i.e., expensing
– Allowances – amounts that can be deducted from income for tax purposes (>100%)
– Credits – amounts deducted from tax liability
– Payroll withholding tax credit for R&D wages
• Income based: tax KBC income at preferential rate
R&D grants vs fiscal incentives
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• Close gap between private and social return to R&D by lowering its cost
• Can also be used to target specific areas (more generous):
– Basic research
– Small & medium-sized firms; young firms
– Collaborative research
– Energy
• Widely used in OECD countries (26 out of 34):
• Differences in the R&D support policy mix
More on R&D tax incentives
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As a percentage of GDP, 2011
Source: OECD Science, Technology and Industry Scoreboard 2013.
http://dx.doi.org/10.1787/888932891112
Direct funding of business R&D and R&D
tax incentives, 2011
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Correlation between total support – R&D intensity, but not necessarily causal
OECD estimates: an additional instrument to test impacts of support policies
Source: OECD Science, Technology and Industry Scoreboard 2013.
http://dx.doi.org/10.1787/888932890143
Business R&D intensity and government
support to business R&D, 2011
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…and differences their design
• Differences in generosity; design; target of areas and firms; expenditure vs income based; tax credits Incremental vs. Volume base;
• R&D definition: not always based on OECD Frascati Manual definition
• Qualified R&D expenditure: e.g only wages related to R&D or total current R&D expenditures (wages + consumables); or include current and capital R&D expenditure
• Carry-over provisions and cash refunds:
• Generosity of the scheme, ceilings
• Temporary vs. permanent nature
• Presence of sub-national tax incentive programs
• Implementation: Complexity, administration and compliance costs,
uncertainty on covered expenses, etc
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Differences in design
Design of the R&D tax incentive scheme
Volume base R&D tax credit Australia, Austria, Belgium (capital), Canada, Chile, Denmark, France, Norway.
Incremental R&D tax credit United States (mostly)*.
Hybrid system of a volume and an incremental credit Ireland, Italy, Japan, Korea, Portugal, Spain.
R&D tax allowance Belgium (capital), Brazil, China, Chile, Columbia, Czech Republic, Finland, Hungary, India, Netherlands, Russian Federation, Singapore, Slovenia, South Africa, Turkey, United Kingdom.
Payroll withholding tax credit for R&D wages Belgium, Hungary, Netherlands, Spain, Turkey.
More generous R&D tax incentives for SMEs Australia, Canada, France, Hungary, Japan, Korea, Netherlands, Norway, Portugal, United Kingdom.
Targeting
Special for energy United States (volume-based).
Special for collaboration Hungary, Italy, Japan, Norway.
Special for new claimants France.
Special for young firms and start-ups Belgium, France, Netherlands, Portugal.
Ceilings on amounts that can be claimed
Austria, Denmark, France, Ireland, Italy, Japan, Netherlands, Norway, Portugal, Singapore, Spain, United Kingdom, United States.
R&D Income-based R&D tax incentives Austria (individuals), Belgium, China, France, Hungary, Luxembourg, Netherlands, Spain, Switzerland, Turkey, United Kingdom.
Special treatment of technology acquisitions (capital cost)
Poland
No R&D tax incentives Estonia, Germany, Israel, Mexico (repealed), New Zealand (repealed), Sweden.
Table 2. Details of differences in R&D tax incentives schemes across selected countries (2013), source Andrews and Criscuolo, 2013
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Source: OECD Science, Technology and Industry Scoreboard 2013.
http://dx.doi.org/10.1787/888932891150
Implied tax subsidy on R&D expenditures, 2013
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Source: OECD Science, Technology and Industry Scoreboard 2013.
http://dx.doi.org/10.1787/888932891150
Implied tax subsidy on R&D expenditures, 2013
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Evaluation of the effect of R&D support
Since Griliches (1958) and Blank & Stigler (1957), many investigated:
• Input additionality, i.e. the complementarity or substitutability of public and private R&D funds (especially additionality VS crowding out) (David et al,
2000 and Hall and Van Reenen, 2000 for a survey);
• Output additionality, (Klette et al, 2000, for a survey; Moen et al., 2007, Bloom,
Schankerman and Van Reenen, 2013)
• Behavioural additionality
Not many have investigated indirect effects of R&D fiscal incentives on:
• Scientists wages (see Goolsbee, 1998 and Lokshin and Mohnen, 2008)
• Location of R&D activities (Bloom and Griffith, 2001 and Wilson, 2008)
• R&D start-up decisions (Norway Skattefunne programme evaluation)
• Resource Reallocation (Acemoglu et al., 2013)
• Efficiency of allocation in terms of R&D type (Akcigit et al., 2014)
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How to assess the effect of R&D support
• Input additionality; deadweight loss; intensive vs extensive margin
• Second-order effects: output additionality; patents; new products
• Third-order effects: productivity growth; survival; employment growth; location of mobile investment
• Full Cost benefit analysis: Spillovers; Administration costs; Compliance costs; Opportunity costs
• General equilibrium analysis: Wage effects; reallocation of resources
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Effect of R&D fiscal incentives: input
additionality
•Does the fiscal incentive increase the total amount of R&D investment in the economy, or it crowds out private R&D investment? (e.g., additionality vs. crowding out). •Two metrics:
•R&D price elasticity: Measures the percentage change in R&D investment resulting from tax relief for every percentage change in its after-tax price (also called the user cost of R&D) •Incrementality ratio (bang for the buck): Measures the change in R&D investment per dollar of foregone tax revenue that is spent on R&D fiscal incentives.
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• Long-run elasticity of R&D with respect to price is around 1 (but wide range.
• R&D elasticity higher in the long than in the short run (probably due to the adjustment cost associated with R&D investments)
• Smaller firms more responsive to R&D tax incentives than larger firms, consistent with small firms being more credit constrained , since they are less likely to have collateral.
• The incrementality ratio affected by policy design with estimates for incremental R&D tax credits generally above 1, and below 1 for volume-based R&D tax credits.
• Importance of stability (Guellec and van Pottelsberghe de la Potterie, 2003 and Westmore, 2013)
Evidence on input additionality
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• If problem is on number of firms performing R&D rather than how much R&D they perform
• new R&D performers to cover sunk entry costs
• effects might be long-lasting because of persistence
• moral hazard problem (start and stop or overinvestment
• Effective? Scarce evidence but all in the same direction (Corchuelo, 2009; Haegeland and Moen, 2007; Arqué-Castells
and Mohnen, 2012)
• Young startups: refundability might be key (Busom et al.,
2012)
Support to new R&D performers
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• Not all firms apply for R&D tax credits because of compliance costs and opportunity costs of applying; monitoring risks; knowledge/information (Corchuelo and Martinez-Ros, 2008)
• Firms with higher human and financial capital; a stable financial position and that have been supported before are more likely to apply
• SMEs and in particular startups incur additional obstacles in applying for R&D tax Credits (Busom et al., 2012)
Compliance and opportunity costs
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Effect of R&D tax incentives: output
additionality
• R&D investment only an input: R&D fiscal incentives could increase amount of reported R&D without increase in innovative outputs and Productivity growth
– Relabeling: relatively small in the long term (e.g., Hall 1995).
– Scientists wages: in the short term higher wages of scientists and engineers, if supply inelastic, lowering the increase in the volume of R&D performed (even if in the long term it induces an increase in the supply of qualified workers).
– Lower marginal private returns: If there are decreasing marginal returns, the additional R&D induced by an R&D tax incentive might be less productive (evidence on Skattefunn programme).
– Lower marginal social returns (Bloom et al., 2013)
– More development than research (Akcigit et al., 2014)
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Evidence on output additionality
• Thus far, the evidence remains scattered.
• Evaluation of these impacts are difficult:
– imperfect measure of innovation output – e.g. patents and available measures of product and process innovations –
– variable time lags between R&D investments in various types of R&D (research versus development, projects, technology areas, etc.) and the resulting innovation output.
• The available evidence suggests a positive effect of R&D tax incentives on innovative sales or the number of new products (e.g. Czarnitzki, Hanel
and Rosa, 2005; de Jong and Verhoeven, 2007).
• However, innovations brought about by R&D tax incentives might not be the same as those funded privately by the firm or by government grants(Cappelen, Raknerud and Rybalka, 2008).
• The assessment of the impact of R&D tax incentives on innovation outcomes is difficult (spillovers also beyond frontiers)
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Evidence on impact on productivity growth
and welfare
• The evidence on the effectiveness of R&D tax incentives on productivity growth is scarce and mixed
• Some positive correlation between R&D tax incentives and productivity (Brouwer et al., 2005 and Lokshin and Mohnen, 2007).
• Estimates of the effectiveness of R&D fiscal incentives on welfare require a full cost-benefit analysis (i.e. consider full direct
and indirect effects of the policy, implementation and compliance costs, and impact of distortionary taxes needed to finance the incentives).
• some studies have attempted to provide such estimates and indicate positive net welfare gain from R&D tax incentives, they depend heavily on the assumptions made (Russo, 2004;Parsons and
Phillips, 2007 and Lokshin and Mohnen, 2009).
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Role of R&D tax incentives for productivity
and employment growth and reallocation
• If the firms that benefit most from R&D fiscal incentives are actually those for which R&D is less likely to generate large spillovers because they focus on niche markets, R&D fiscal incentives might not be associated with increases in aggregate productivity growth (Bloom et al., 2010).
• R&D tax credit might reduce growth and welfare if it subsidizes the R&D of incumbents, unless the R&D of new entrants (new R&D performers) is also subsidized and exit of inefficient incumbent is allowed (Acemoglu et al., 2014)
• R&D tax incentives have the unintended consequence of protecting incumbents at the detriment of potential entrants, thus slowing down the reallocation process (Bravo-Biosca , Criscuolo and Menon, 2013).
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• Fiscal incentives for R&D aim at increasing the volume of R&D investment, but part of these incentives might lead to an increase in the wages of - or the cost to firms of hiring - R&D scientists and engineers. (Gooslbee, 1999)
• Because of inelastic supply of scientists and/or search costs for
scientists and engineers, bargaining power between firms and R&D workers
• Studies that have looked at this issue remain scarce and are strongly constrained by the availability of suitable data (aggregate vs micro; firm vs individual level).
• The available studies tend to find: – increase in R&D wages does not correspond to a change in quality of
researchers, (e.g.Hægeland and Moen, 2007 and Lokshin and Mohnen, 2008).
Effects of R&D tax credits on wages
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Effects of R&D tax incentives: attract
internationally mobile R&D investment
– R&D activity increasingly mobile and internationalized.
– Multinational firms account for a substantial fraction of R&D expenditure
– even if R&D support might affect location of MNEs R&D investment, other key fundamentals are more important.
• for basic research: access to local science and technology, proximity to university frontier research, availability of a skilled workforce, scientists and strong IPRs. (Thursby and Thursby, 2006)
• for development: access to local markets and proximity to other corporate activities, such as production sites, and proximity to local customers (Defever, 2006)
– Distortion from affecting location fo R&D activity (Griffith et al., 2004)
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• Bloom and Griffith (2001)
– Use country-level data over 19 years to show that R&D in one country responds to changes in tax price of R&D in other “competitor” countries.
– Relate R&D expenditure to the domestic user cost of R&D and foreign user cost of R&D.
– R&D increases with a decrease in the domestic user cost and with an increase in the foreign user cost
• Wilson (2009)
– Very similar exercise using data on US states over time
– Nearer states are considered closer competitors
– Evidence of a zero-sum game among US states competing for mobile R&D
– Estimates long-run elasticity of in-state R&D with respect to in-state user cost of -2.5 and long-run elasticity of in-state R&D with respect to out-of-state user cost of 2.5
Findings: effects of R&D tax credits on location
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• difficulties in measuring effective tax rates on R&D, details of design, data availability, and estimation problems:
– Self-selection
– endogeneity
– time lags
– indirect effects on firms that did not apply/receive the fiscal incentives.
– Heterogeneous effects
– General equilibrium effects
Challenges in evaluating impact of R&D
fiscal incentives
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• Finding a counterfactual.
• Policy makers and econometricians cannot observe what firms that received support would have invested had they not received the support.
• Firms that get into the program are not random draws
• Additional problem: impact on non-treated-firms (difficult to find a control group amongst non-treated firms)
Identification and selection: the problem
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• The question of interest:
– What would the performance of firms that participated to the programme if they had not participated?
– Problem: we cannot observe the outcome of not participating for treated firm
• Solution: we need to find a valid counterfactual: what would have happened “but for” the policy
What do we want to estimate?
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Solutions to evaluation concerns
Main microeconometric programme evaluation approaches used:
1) Matching of treated and untreated: requires no assumption on functional forms, but strongly relies on the “conditional independence” assumption and on the existence of a common support.
2) Difference-in-Difference
3) Instrumental variables: account for selection on unobservables, but require instrumental variables, i.e. variables correlated with the likelihood / intensity of treatment, but not with individual firm performance.
4) Regression discontinuity design ( SKATTEFUNN evaluation)
5) (Parametric and semiparametric) sample selection models: account for selection on observables and unobservables. More parametric than IV. Require instrumental variables when applied.
6) (General equilibrium) structural models: economic theory guides the construction of the model and suggests included and excluded variables, but functional form, exogeneity assumptions invoked, and sources of parameter identification may be controversial.
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• Structural econometric models estimating firm R&D investment demand function useful when trying to do ex-ante policy evaluation:
– Characterize firm R&D investment behaviour
– Support policy scenarios and simulations
• Mairesse and Mulkay, 2013 on the 2008 French Reform
– estimate Error Correction specification of dynamic R&D investment demand regression with SYS-GMM
• Assumptions: 1)consistent estimates of structural parameters
2)coeffs apply after the 2008 reform
• need to complement with ex-post assessment. Also to look at impact on extensive margin
Structural econometric approach and
ex-ante policy evaluation
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• Impact of R&D tax credit on R&D expenditure; but not only...think of general equilibrium effects and unintended consequences. Design is key.
• Ex-post assessment of impact difficult but needed:
– Access to data (administrative and design)
• Complemented with ex-ante evaluation based on structural model when data non available
• Importance of including an evaluation phase in the design of the policy (data collection; outcomes of interest; lags; randomization?)
• Importance of making evaluation results open and accessible and use it for future policy design
Summary
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• Important of design and level playing field:
– Refundability; carry forward/backward rules; payroll withholding tax credits for R&D wages
– …but size contingent policies problems
• Importance of:
– innovation policy mix (Supply push policies; innovation demand policies; etc.)
• framework conditions:
– Competition; openness; for experimentation: EPL; bankruptcy; access to finance; entrepreneurship policies etc.
• predictability and stability beyond political mandates
Policy discussion