Energy and the Wealth of Nations pp 361-376 | Cite as

# The Required Quantitative Skills

## Abstract

If you glance at an advanced economics journal, you will see that many of the pages are filled with dense mathematical equations. Quite often these equations are presented as «proofs» of some economic idea. It is really quite an intimidating experience, even for those of us with a fairly good background in quantitative analysis! How can you, aspiring perhaps to become an economist, or at least to be able to understand others’ economic conclusions, do so if your skills in mathematics are limited? We are not sure, but there may be some hope for you. This is because although we believe in the critical importance of a good *quantitative* understanding of economic systems, we are not so sure as to the utility of very strong *mathematica*l analysis and skills except perhaps to understand others’ work that uses them, including that, as the wonderful economist Joan Robinson said, we are not bamboozled by those who are hiding their simple or even ludicrous ideas behind impenetrable mathematics. If you are confused by this sentence, *quantitative* means referring to the use of numbers and basic, although well thought out, arithmetic usually relating to some kind of data and the relations among data. *Mathematical* has many meanings but in this context generally means the ability to use advanced paper and pencil mathematics, often called «mathematical analysis,» «analysis,» or «deriving closed form solutions,» often for theoretical work related only loosely to quantitative analysis. We believe that economics has suffered from the excessive use of complex mathematics, sometimes linked to poorly formulated problems—and sometimes under the misleading assumption that the basic understanding of economics as given in most economics textbooks is always an accurate representation of real economies. We think far too many good minds have spent far too much time undertaking such «mental masturbation» when instead we should be examining much more carefully our basic assumptions of what it is that economists should be doing and how—empirically—actual economies operate. We are not alone in this view. For example, Paul Krugman, a Nobel Prize winner in economics and a very thoughtful and productive economist, said in 2009 while referring to the enormous financial crash of 2008 (and alluding to the famous poem by John Keats «Ode to a Grecian urn»):

## References

- 1.Hall, C.A.S. 1988. An assessment of several of the historically most influential theoretical models used in ecology and of the data provided in their support.
*Ecological Modeling*43: 5–31.CrossRefGoogle Scholar - 2.Hall, C.A.S., and J.W. Day, eds. 1977.
*Ecosystem modeling in theory and practice. An introduction with case histories*. New York: Wiley Interscience.Google Scholar - 3.Hall, C. 1991. An idiosyncratic assessment of the role of mathematical models in environmental sciences.
*Environment International*17: 507–517.CrossRefGoogle Scholar - 4.Gowdy, J. 2004. The revolution in welfare economics and its implications for environmental valuation.
*Land Economics*80: 239–257.CrossRefGoogle Scholar - 5.Kaufmann, R.K. 1992. A biophysical analysis of the energy/real GDP ratio: implications for substitution and technical change.
*Ecological Economics*6: 35–56.CrossRefGoogle Scholar - 6.Kaufmann, R.K., and D.I. Stern. 1997. Evidence of human influence on climate from hemispheric temperature relations.
*Nature*388: 40–44.CrossRefGoogle Scholar - 7.Krugman, P. 2009. How did economists get it so wrong?
*Editorial New York Times Sept.*2: 2009.Google Scholar - 8.John G. Kemeny. BASIC and DTSS: Everyone a programmer (Obituary). http://www.columbia.edu/~jrh29/kemeny.html
- 9.Mary Williston Ecological Bulletin, Personal Communication.Google Scholar