technology-push,demand-pull,andstrategic r&d...
TRANSCRIPT
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INFORMS Annual MeetingNashville, TNNovember 13, 2016
Technology-push, Demand-pull, and StrategicR&D Investment
Benjamin D. LeibowiczAssistant ProfessorGraduate Program in Operations Research and Industrial EngineeringDepartment of Mechanical EngineeringThe University of Texas at Austin
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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Two Types of Technology PolicyI Technology-push
– Reduce the private cost of engaging in innovation– ExamplesI Public R&DI Government funding for private R&DI Support for higher education to enlarge pool of innovators
I Demand-pull– Create or expand markets to increase the payoff tosuccessful innovation– Examples
I Subsidies for consumer purchasesI Direct government procurementI Stronger intellectual property protection
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Retrospective AnalysesI Empirical and case study literatures indicate that eachpolicy type is generally ineffective if used alone.I Technology-push
– Mod program for wind turbines, U.S., 1970sI Loiter and Norberg-Bohm (1999)
– GAVE program for biofuels, Netherlands, 1998–2002I Suurs and Hekkert (2009)
I Demand-pull– Tax credits for wind installations, California, 1980s
I Nemet (2009)– Tax credits for solar installations, California, 1970s–present
I Taylor (2008); Wiser et al. (2007)
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Portfolio ApproachI Technology-push and demand-pull policies arecomplementary, and the ideal technology policy portfolioshould include policies of both types (Gallagher et al., 2012).I The relative importance of technology-push anddemand-pull varies across applications (Pavitt 1984).
In this study, a bilevel optimization model is developed todetermine the optimal balance of technology-push anddemand-pull policies for a given technology policyapplication.
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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Key Model Features 1I Unique features
– Includes a policymaker and firms as separatedecision-making agents– Represents both technology-push and demand-pull– Represents both process and product R&D– Captures uncertainty in R&D outcomesI Three market failures
– Incomplete appropriability of innovation– Imperfect competition– Negative production externality
1 Contrast these to how energy technology R&D is incorporated into IAMs (Bosetti et al., 2009).
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Strategic Innovation in an Oligopoly
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The Model
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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Three Different Motivations for Stimulating InnovationI Case 1: Combat negative externality
– The new good is a close and expensive substitute for theexsiting good, but the latter has a negative productionexternality (e.g. nuclear fission to fusion).I Case 2: Reduce cost
– The new good is a close substitute for the existing good, butcan ultimately be produced at lower cost (e.g. crystallinesilicon to organic PV).I Case 3: Create demand
– Developing the new good is expensive, but it has a largepotential demand that is not being met by the existing good(e.g. new energy-consuming end-use appliance).
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Case 1: Combat Negative Externality
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Case 2: Reduce Cost
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Case 3: Create Demand
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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Product R&D
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Expected Profit
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Expected Welfare
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Optimal Technology-push Policy
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OutlineBackground
Model
Numerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions
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ConclusionsI Process and product R&D are substitutes.I If innovation serves to combat a negative externality,technology policy should emphasize technology-push, butit is difficult to enhance welfare through technology policy.I Firms perform less product R&D under stronger spillovers,but expected welfare is higher.I Each firm performs less product R&D under greatercompetition, but total industry R&D rises.I Expected welfare decreases with competition in theno-policy case, but increases with competition if optimaltechnology policies are imposed.
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AcknowledgmentsI Previous institutions where this work took place
– International Institute for Applied Systems Analysis– Stanford UniversityI Individuals who offered guidance
– Lawrence Goulder– Arnulf Grubler– Charles Kolstad– Volker Krey– James Sweeney– John WeyantI Funding source
– DOE Office of Science PIAMDDI grant
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Thank You for Listening!
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ReferencesBosetti, V., Carraro, C., Massetti, E., Sgobbi, A., Tavoni, M. (2009). Optimal energy investment and R&D strategies tostabilize atmospheric greenhouse gas concentrations. Resource and Energy Economics 31, 123-137.D’Aspremont, C. and Jacquemin, A. (1988). Cooperative and Noncooperative R&D in Duopoly with Spillovers.
American Economic Review 78, 1133-1137.Dasgupta, P. and Stiglitz, J. (1980). Industrial Structure and the Nature of Innovative Activity The Economic Journal 90,266-293.Gallagher, K.S., Grubler, A., Kuhl, L., Nemet, G., Wilson, C. (2012). The Energy Technology Innovation System. Annual
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BackgroundModelNumerical SimulationsMotivations for Stimulating InnovationMarket Failure Sensitivity Analysis
Conclusions