David Stern is an energy and environmental economist whose research focuses on understanding the relationship between resource use and economic growth and development. He has investigated both the role of energy and resources in economic growth and the determinants of environmental impacts, especially air pollution and climate change. He is also interested in research assessment using meta-analysis and bibliometric techniques.
David is the director of the International and Development Economics program, an associate editor of Ecological Economics, a research associate in CAMA and CCEP, and a participant of the Energy Change Institute.
For more information and a complete publication list please see Prof. Stern’s website: www.sterndavidi.com. David also maintains a blog on energy, economics, and the science of science.
Modelling International Trends in Energy Efficiency
Energy Economics Vol. 34, Issue 6, November 2012
I use a stochastic production frontier to model energy efficiency trends in 85 countries over a 37-year period. Differences in energy effciency across countries are modeled as a stochastic function of explanatory variables and I estimate the model using the cross-section of time-averaged data, so that no structure is imposed on technological change over time. Energy efficiency is measured using a new energy distance function approach. The country using the least energy per unit output, given its mix of outputs and inputs, defines the global production frontier. A country’s relative energy efficiency is given by its distance from the frontier - the ratio of its actual energy use to the minimum required energy use, ceteris paribus. Energy efficiency is higher in countries with, inter alia, higher total factor productivity, undervalued currencies, and smaller fossil fuel reserves and it converges over time across countries. Globally, technological change was the most important factor counteracting the energy-use and carbon-emissions increasing effects of economic growth.
- Energy economics
- Climate change
- Applied time series econometrics