An Energy-Centric Theory of Agglomeration

J.M. Cruz and M. Scott Taylor

Journal of Environmental Economics and Management, Vol. 84, July 2017, 153-172.

Appendix

Presentation

This paper sets out a simple spatial model of energy exploitation to ask how the location and productivity of energy resources affects the distribution of economic activity across geographic space. By combining elements from energy economics and economic geography we link the productivity of energy resources to the incentives for economic activity to agglomerate. We find a novel scaling law links the productivity of energy resources to population sizes, while rivers and roads effectively magnify productivity. We show how our theory's predictions concerning a single core, aggregate to predictions over regional landscapes and city size distributions at the country level. 

Important related work:

Head, Keith, and Mayer, Thierry, 2004. The empirics of agglomeration and trade. In: Henderson, J.V., Thisse, J.F. (Eds.), Handbook of Regional and Urban Economics, 4., Elsevier B.V, Amsterdam, The Netherlands. (Chapter 59).

Pindyck, R.S., 1978. The optimal exploration and production of nonrenewable resources. Journal of Political Economy. 86(5), 841–861.

Wrigley, E.A., 2010. Energy and the English Industrial Revolution. Cambridge University Press, Cambridge, UK.


A Spatial Approach to Energy Economics: Theory, Measurement and Empirics

J.M. Cruz and M. Scott Taylor

CESifo, Working Paper No: 4845, June 2014.

This paper sets out a simple spatial model of energy exploitation to ask how the location and productivity of energy resources may affect the distribution of economic activity around the globe. We combine elements from resource and energy economics into one framework linking the spatial productivity of energy resources (both renewable and non-renewable) to the incentives for economic activity to concentrate. Our theory provides a novel scaling law; a magnification effect; and reveals a complementarity between infrastructure investment and spatially productive energy resources. Our empirical work provides estimates of key magnitudes and reviews empirical work supporting our approach.

Important related work:

Allen, Robert C. 2009. “The British Industrial Revolution in Global Perspective." UK: Cambridge University Press

Fouquet, R. and R. Pearson. 1998. “A Thousand Years of Energy Use in the United Kingdom." The Energy Journal, 19(4): 1-41.

Kolstad, C.D. 1994. “Hotelling Rents in Hotelling Space: Product Differentiation in Exhaustible Resource Markets." Journal of Environmental Economics and Management, 26: 163-180.


Can Green Power Save Us from Climate Change?

M. Scott Taylor

Swiss Journal of Economics and Statistics, Vol. 150, No. 1, March 2014, 23-31.

Presentation

Can green energy save us from climate change? Answering this question turns out to be far more difficult than it might first appear, since it requires we address four smaller separate questions to generate a complete answer. First, we need to ask what “saving us” from climate change means. Although there are many potential answers, I will assume this implies producing a path for carbon emissions to 2100 that results in a less than 2 degree Celsius (3.6 degree Fahrenheit) increase in temperature. In terms of cumulative emissions, this implies a budget of approximately 500 gigatons carbon in the next 90 years. The 2 degree Celsius target is simple and was adopted by the Cancun Agreement. Second, we need to ask what the world would look like if something radical is not done to hasten the adoption of renewable power worldwide. To answer this question, I need to construct a Business As Usual (BAU) trajectory to develop an expected path for carbon emissions. Third, we need to ask what alternative path with rapid adoption of green power could meet the overall carbon budget. And finally, we need to ask whether the implied shift in the energy mix required to meet the carbon target is in some sense feasible.

Important related work:

National Research Council (2010), Climate Stabilization Targets: Emissions, Concentrations, and Impacts over Decades to Millennia, National Academies Press.

Exxon Mobil (2010), The Outlook for Energy: A View to 2030.

Smil, Vaclav (2010), Energy Transitions: History, Requirements, Prospects, Santa Barbara (CA): Praeger.


A Spatial Approach to Energy Economics

J.M. Cruz and M. Scott Taylor

The National Bureau of Economic Research, Working Paper No: 18908, March 2013.

We develop a spatial model of energy exploitation where energy sources are differentiated by their geographic location and energy density. The spatial setting creates a scaling law that magnifies the importance of differences across energy sources. As a result, renewable sources twice as dense, provide eight times the supply; and all new non-renewable resource plays must first boom and then bust. For both renewable and non-renewable energy sources we link the size of exploitation zones and energy supplies to energy density, and provide empirical measures of key model attributes using data on solar, wind, biomass, and fossil fuel energy sources. Non-renewable sources are four or five orders of magnitude more dense than renewables, implying that the most salient feature of the last 200 years of energy history is the dramatic rise in the use of energy dense fuels.


Back to the Future of Green Powered Economies

J.M. Cruz and M. Scott Taylor

The National Bureau of Economic Research, Working Paper No: 18236, July 2012.

Presentation

The purpose of this paper is to introduce the concept of power density [Watts/m²] into economics. By introducing an explicit spatial structure into a simple general equilibrium model we are able to show how the power density of available energy resources determines the extent of energy exploitation, the density of urban agglomerations, and the peak level of income per capita. Using a simple Malthusian model to sort population across geographic space we demonstrate how the density of available energy supplies creates density in energy demands by agglomerating economic activity. We label this result the density-creates-density hypothesis and evaluate it using data from pre and post fossil-fuel England from 1086 to 1801.

Important related work:

Ashraf, Q. and Oded Galor. 2011. “Dynamics and Stagnation in the Mathusian Epoch.” American Economic Review, 101(5):1-41

Broadberry, S., B. Campbell, and B. van Leeuwen. 2011. English Medieval Population: Reconciling Time Series and Cross Sectional Evidence. LSE: Discussion paper.

Clark, G. 2007. A Farewell to Alms: A brief Economic History of the World. Princeton, N.J.: Princeton University Press.

Davis, D. R. and Weinstein, D. (2002). “Bones, Bombs, and Break Points: The Geography of Economic Activity.” American Economic Review, 92(5):1269-1289.

Nunn, N. and N. Qian. 2011. “The Potato’s contribution to population and urbanization: evidence from a historical experiment.” Quarterly Journal of Economics, 126, 593-650.