The Dynamics of Carbon and Energy Intensity in a Model of Endogenous Technical Change

Abstract

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Negishi welfare weights in integrated assessment models: the mathematics of global inequality

“…They accomplish this by choosing how much to abate emissions in each time period, where abatement costs reduce production and consumption. Examples of welfare-optimizing IAMs include both global (single-region) models- DICE-2007(Nordhaus 2008, ENTICE-BR (Popp 2006), DEMETER-1CCS (Gerlagh 2006), and MIND (Edenhofer et al 2006)-and regionally disaggregated models- RICE-2004 (Yang andNordhaus 2006), FEEM-RICE (Bosetti et al 2006), FUND (Tol 1999), MERGE (Manne and Richels 2004), CETA-M (Peck and Teisberg 1999), GRAPE (Kurosawa 2004), and AIM/Dynamic Global (Masui et al 2006). 3 2.1 Global welfare-optimizing IAMs Some of the IAMs that are solved by optimizing welfare treat the world as one homogenous region.…”

Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model

“…The main idea underlying the present piece of research is to assess and discuss the effect of endogenizing this uncertainty on optimal R&D investment trajectories and carbon emission abatement strategies. In order to do so, we use an implicit stochastic programming version of the FEEM-RICE model, first described in Bosetti, Carraro and Galeotti, (2005). The comparative advantage of taking a stochastic programming approach is estimated using as benchmarks the expected-value approach and the worst-case scenario approach.…”

“…In particular, the central value of parameters is chosen in order to approximate baseline emissions of the SRES B2 scenario and following a set of assumptions on carbon and energy intensity trends described in Bosetti, Carraro and Galeotti (2005). We investigate the sensitivity of crucial variables to different uncertain parameters.…”

“…Pure chance is thus assigned a place in the fate of cultures, but not the talents of the individuals who make them up." Squaring the Circle by Michael Levin, a review of Jared Diamond, Guns, Germs, and Steel: The Fates of Human Societies, W. W. Norton, 1997 3 For a detailed discussion of the model calibration procedure the reader is referred to Bosetti, Carraro and Galeotti [2005].…”

“…Moreover, as discussed in greater detail in Bosetti, Carraro and Galeotti (2005), the model has been extended in order to account for both learning-by-researching and learning-by-doing; the former vector of endogenous technical change is modelled through an R&D investment decision variable which cumulates deterministically through time; the latter is modelled as the stock of cumulated emissions reduction. The two inputs are aggregated to compose an index of technical progress which in turn affects both carbon and energy intensities.…”