Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors FEEM Venice, 21 May 2009 Carlo Carraro Emanuele Massetti.

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Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors FEEM Venice, 21 May 2009 Carlo Carraro Emanuele Massetti Lea Nicita IEW 2009, Venice

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 1 Motivation of the analysis Even if the description of technical change in integrated models for climate policy analysis has greatly improved, current approaches rarely include a full description of knowledge externalities Few attempts to incorporate R&D spillovers in integrated models for the study of climate policy have been confined to the inclusion of international spillovers only (e.g. Bosetti et al, 2008) Without spillovers, models unrealistically assume that advance of technological frontiers of different sectors and of different countries are mutually independent and omit to consider the interactions among different drivers of technical change.

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 2 Spillovers: empirical evidence The majority of empirical works find that R&D spillovers are significant and positive (Coe and Helpman, 1995; Griliches, 1992) Both domestic and International knowledge spillovers have a significant impact on innovations and productivity (Bottazzi and Peri, 2007; Keller, 2002; Frantzen, 2002) Spillovers are mainly domestic: more national than international in scope (Weiser, 2007) Inter-sectoral spillovers are extremely significant (Australian Industry Commission, 1995; Weiser, 2007)

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 3 Aim of the work We introduce inter-sectoral spillovers in the WITCH model with directed technical change (Carraro, Massetti and Nicita, 2009) R&D expenditures are factor specific and can be directed towards increasing energy-efficiency or towards rising productivity of non-energy inputs The directed technical change approach allows to explicitly modeling spillovers across the two R&D capital stocks We can thus study the effect that modeling inter-sectoral knowledge spillovers has on the advances of the technological frontier and on the costs of climate policy

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 4 WITCH: a “TOP DOWN” optimization framework, with a “BOTTOM UP” energy sector description as a downward expansion of the energy input. “TOP DOWN “ perspective: strategic optimal investment strategy both on a time dimension (inter-temporality) and a regional dimension (non-cooperative game) “BOTTOM UP” component: enables a strategic assessment of the optimal investment in different energy technologies  Electric and non electric energy use  6 Fuels types (Oil, Gas, Coal, Uranium, Biofuels, Traditional biomass)  7 Technologies for electricity generation Optimal intertemporal investment strategies are determined as a dynamic Nash equilibrium of the game among the 12 regions (non- cooperative decision on CO 2 emissions, fuel prices, LbD, emission permits market) WITCH model: main features

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 5 WITCH with Directed Technical Change Output is produced combining capital-labour services (KLS) and energy services (ES) and is reduced by climate damage: KLS is produced combining the capital-labour (KL) aggregate and the stock of capital-labor knowledge (HKL): (1) (2) (3) ES is produced aggregating the energy (EN) and the stock of energy knowledge (HE): (4)

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 6 R&D Sectors with inter-sectoral spillovers Production of new ideas follows an “innovation possibility frontier” specification with intra-sectoral and inter-sectoral spillovers and diminishing returns: (7) (8) (6) (5) Knowledge stocks are increased by the flow of new ideas and are subject to depreciation

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 7 BaU scenario GWP increases over the whole century at a declining rate Population grows at a diminishing rate and start declining at the end of the century Energy Intensity declines Carbon Intensity is constant …..overall carbon emission increases due to economic growth

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 8 BaU Investments in final good capital, as a share of GWP, decline Capital formation in energy sector also declines R&D expenditures, as share of GWP, slightly increase because of increasing path of Non-Energy R&D investments Energy R&D expenditures, as share of GWP and as share of total Investments in R&D, decline

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 9 Stabilization policy Optimal investment and R&D strategies to stabilise GHG concentrations at 550 ppm CO2e Optimal emission time profiles are the solution of the fully cooperative version of the WITCH model It is assumed that regions can trade emissions allowance in an international carbon market Permits are allocated according to the equal per capita scheme, i.e. evenly balanced emissions per person

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 10 Gross World Product and Consumption both decline wrt Bau Stabilization policy

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 11 Stabilization: R&D sector R&D investment in energy sector sharply increases R&D investment in Non-energy sector declines

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 12 Stabilization: R&D sector Overall Total R&D investment declines This result is explained by a contraction of economic activity and by the fact that capital-labor augmenting technical change is energy- biased (Carraro, Massetti and Nicita, 2009)

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 13 Internalization of R&D externalities and Stabilization policy -R&D in Energy sector increases sharply -Non-Energy R&D increases -Total R&D increases

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 14 Costs of policy When the stabilization policy and the policy for the internalization of the externalities are jointly implemented GWP increases wrt Bau

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 15 Policy for the internalization of R&D externalities Policy for the internalization of externalities in the Energy sector affects deeply R&D investments in both sectors, while the effect of internalizing externalities in the Non-Energy sector is very modest

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 16 Policy that only internalizes R&D externalities always increases output and emissions Policy for the internalization of R&D externalities

Optimal R&D Investments and the Cost of GHG Stabilization when Knowledge Spills across Sectors 17 Concluding remarks Even in a model embodying inter-sectoral spillovers, Non-energy R&D investments decrease when a stabilization policy is implemented A joint implementation of R&D policy and stabilization policy reduces the costs of the stabilization policy Implementing only an R&D policy aimed at internalizing externalities increases emissions