Arnulf Grubler studies patterns and drivers of technological change and how they affect the environment. His research comprises four main analytical areas: 1) empirical case studies on past and present technological transitions, with emphasis on energy, transport, and communication systems; 2) development of experimental mathematical models that attempt to capture the main “stylized facts” derived from the empirical case studies; 3) integrated assessment modeling of long-term greenhouse gas emissions and analysis of technology portfolios that could lead to climate stabilization from a multi-gas, multi-sector perspective; and 4) spatially explicit modeling of demographic and economic change as input to technology diffusion and climate impact assessment studies.
Empirical Case Studies of Technological Change
The empirical work tries to answer three main questions: How is innovation uncertainty on feasibility, costs, and impacts of new technologies overcome; What is the relationship between supply push and demand pull factors in the diffusion of new technologies; What are characteristic rates of change and how these differ across different technologies and diffusion contexts. Case studies include historical as well as existing and emerging new technologies.
Modeling Technological Change
New experimental, stylized models are developed that aim at gaining a better understanding of the dynamics of technological change as arising from three main, interrelated features: uncertainty, increasing returns to adoption, and changes in the knowledge stock underlying new technologies (resulting from both directed R&D activities, knowledge spillover effects, as well as user-supplier interactions). Mathematically, the resulting models deal with stochastic, non-convex optimization problems. Recent research also aims at replacing the traditional social planner perspective by a multi-agent approach in models of technological change.
Long-term Greenhouse Gas Emissions and Climate Stabilization Scenarios
In a larger collaborative framework integrated assessment models are used to explore uncertainties in future greenhouse gas emissions through a scenario approach and to analyze technology portfolios that could ultimately lead to climate stabilization. The research emphasis is on exploration of key uncertainties, analysis of optimal technology portfolios that enable hedging against a variety of climate and mitigation risks, and on inter-sectorial linkages and feedbacks between the energy, agriculture and forestry sectors.
Spatially Explicit Scenarios
This research addresses the issue of how to represent spatial heterogeneity in long-term demographic and economic change scenarios that are key determinants framing climate change vulnerabilities as well as technology adoption potentials. Ongoing research combines both demographic, economic, as well as urbanization scenarios with stochastic gravity-models of spatial interactions and location to produce spatially explicit maps of future human activities.