The Role of Economics in Policy Analysis

 From  the Mercatus Center
 
"Economics is everywhere. It's at the gas pump, in foreign aid, in the fluctuation of currency values. Economics is not just graphs and charts. It's real-world knowledge about the decisions people make and the effects of those decisions.

Incentives affect the choices people make. Some basic social and political structures facilitate prosperity. These are some of the core economic concepts that policy makers must understand to be effective. Unfortunately, a gap often exists between economic understanding and real-world decision making. Policy decisions miss their targets and create unintended and sometimes harmful consequences."

Price Gouging and the Knowledge Problem

 If we should make price gouging illegal, then we have to ask, how do we solve the 'knowledge' problem? i.e.

Is there a 'more appropriate' price that should be charged? How do we find a price that ensures that the intensity of your desire/need for a generator is consistent with my willingness to provide one? Should we rely on market forces and prices at all or simply have some authority distribute generators based on some set of rules? Rules based on what criteria? How many generators are required and how do we make sure that they get to the people that have the greatest need/desire for them? i.e. how do we know if generators are allocated to the most highly valued use? What lessons can we learn from Hurricane Katrina about the government's ability to mobilize resources during a natural disaster? See also:

The use of knowledge in disaster relief: http://www.independent.org/publications/tir/article.asp?a=628

The Government's Response to Hurricane Katrina- A Public Choice Analysis: http://www.peterleeson.com/hurricane_katrina.pdf
The Problem with Price Gouging Laws-Regulation Spring 2011: http://www.cato.org/pubs/regulation/regv34n1/regv34n1-1.pdf

The Knowledge Problem - blog posts related to price gouging: http://knowledgeproblem.com/tag/price-gouging/ 

Environmental Economics blog post related to price gouging: http://www.env-econ.net/2009/06/mike-giberson-on-antiprice-gouging-laws.html 

Models and Assumptions: Efficient Markets, Imperfect Information, Rationality, and Prices

“The relevant question to ask about the “assumptions” of a theory is not whether they are descriptively “realistic,” for they never are, but whether they are sufficiently good approximations for the purpose in hand. And this question can be answered only by seeing whether the theory works, which means whether it yields sufficiently accurate predictions.” – Milton Friedman, Essays in Positive Economics 

"The great free market economic thinkers from Adam Smith to F. A. Hayek never argued that individuals were hyper-rational actors possessed with full and complete information, operating in perfectly competitive markets.... Efficient markets are an outcome of a process of discovery, learning, and adjustment, not an assumption going into the analysis." - http://theeuropean-magazine.com/348-boettke-peter/349-the-legacy-of-smith-and-hayek

 “the knowledge of the circumstances of which we must make use never exists in concentrated or integrated form but solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess. Fundamentally, in a system in which the knowledge of the relevant facts is dispersed among many people, prices can act to coördinate the separate actions of different people in the same way as subjective values help the individual to coördinate the parts of his plan. Of course, these adjustments are probably never "perfect" in the sense in which the economist conceives of them in his equilibrium analysis. But I fear that our theoretical habits of approaching the problem with the assumption of more or less perfect knowledge on the part of almost everyone has made us somewhat blind to the true function of the price mechanism and led us to apply rather misleading standards in judging its efficiency. To assume all the knowledge to be given to a single mind in the same manner in which we assume it to be given to us as the explaining economists is to assume the problem away and to disregard everything that is important and significant in the real world” – Hayek, The Use of Knowledge in Society

"I prefer true but imperfect knowledge, even if it leaves much indetermined and unpredictable, to a pretence of exact knowledge" - F.A. Hayek, The Pretense of Knowledge

 “The curious task of economics is to demonstrate to men how little they really know about what they imagine they can design.” - Frederick Hayek, The Fatal Conceit

“Neither all ends pursued, nor all means used, are known or need to be known to anybody, in order for them to be taken account of within a spontaneous order.” - Hayek, The Fatal Conceit

 "The financial crisis invalidated a naïve notion of "efficient markets," but the most sophisticated version is still viable. Whereas the invalidated version holds that markets never err and always adjust instantaneously, the sophisticated version, associated with the ideas of Adam Smith and F. A. Hayek, holds that markets mobilize individuals to realize gains from trade and to innovate and thereby produce generalized prosperity." http://www.independent.org/publications/tir/article.asp?a=762

Robert Murphy points out in his textbook 'Lessons for the Young Economist': "When we look at the world and try to make some sense of it, one of the most basic and crucial distinctions we all make—usually without even realizing it—is the difference between purposeful action versus mindless behavior...The lessons in this book apply to purposeful actions performed by conscious people who have goals in mind… The economic principles in this book are not confined to “perfectly rational people.” The lessons in these pages apply to real people who use their minds to make exchanges in the real world every day."

 Economics deals with the real actions of real men. Its [laws] refer neither to ideal nor to perfect men, neither to the phantom of a fabulous economic man (homo oeconomicus) nor to the statistical notion of an average man. . . . Man with all his weaknesses and limitations, every man as he lives and acts, is the subject matter of [economics]. —Ludwig von Mises, Human Action (Auburn, Ala.: Ludwig von Mises Institute, 1998), pp. 646–47

Job Creators? OR In Praise of Consumerism and Materialism?

The following video praises consumerism and materialism as drivers of job creation and economic growth. The policy implication is that higher tax rates on entrepreneurs and high income earners should have little impact on job creation and economic growth if consumerism and materialism (i.e. Keynesian aggregate demand) are key drivers of prosperity.
 However, their is quite a bit of empirical evidence to the contrary.

See: Can tax cuts impact entrepreneurial activity and job creation?

Is Capitalism Pro-Business?

No More Crying About Your Stats Class and Cry1Ab: An Application of the Coefficient of Variation

Lots of times students complain that either their statistics classes used silly examples that were too simple to ever be realistic, or that their course was too complicated and thus they leave the class without the capability of  any practical application.  A recent study looking at the safety of GMO corn provides a great case study for the practical application of the coefficient of variation (CV). 

In ‘Maternal and fetal exposure to pesticides associated to genetically modified Foods in Eastern Townships of Quebec, Canada’ the authors claim to have identified the toxin Cry1Ab in the blood of pregnant women.  Cry1Ab is a protein produced by the bacteria Bacillus thuringiensis (Bt) that is toxic to certain insect pests. Cry1Ab is just one version (event) of this Bt toxin.  Bt toxins have been used extensively by organic farmers and biotechnology has enabled seed companies to develop corn plants that express Cry1Ab proteins giving them a built in defense mechanism against insects susceptible to the toxin, while preserving the biodiversity of friendly insects.  Bt genetics have also been incorporated into cotton. The economic, environmental, safety, and health benefits have made this a very popular  tool used by the majority of family farmers. 

One of the major criticisms of the article was the use of the test used to identify the Cry1Ab protein. In the article the authors state:

‘Cry1Ab protein levels were determined in blood using a commercially available double antibody sandwich(DAS)enzyme-linked immune sorbent assay.’

In previous research, the enzyme-linked immunosorbent assay or ELISA test has been shown to be one of the most unreliable tests for detecting Cry1Ab proteins.  Recall, the CV is relative measure of variation measuring the standard deviation relative to the mean.   It can be used as a metric for risk and reliability (such a consistent yield performance or stock returns).  In the article ‘Comparison and Validation of Methods To Quantify Cry1Ab Toxin from Bacillus thuringiensis for Standardization of Insect Bioassays’ the authors investigate procedures commonly used to identify Cry1Ab.  The authors explain:

“We compared three methods of quantification on three different toxin preparations from independent sources: enzyme-linked immunosorbent assay (ELISA), sodium dodecyl sulfate-polyacrylamide gel electrophoresis and densitometry (SDS-PAGE/densitometry), and the Bradford assay for total protein....The Bradford method resulted in statistically higher estimates than either ELISA or SDSPAGE/ densitometry but also provided the lowest coefficients of variation (CVs) for estimates of the Cry1Ab concentration (from 2.4 to 5.4%). The CV of estimates obtained by ELISA ranged from 12.8 to 26.5%, whereas  the CV of estimates obtained by SDS-PAGE/densitometry ranged from 0.2 to 15.4%....we conclude that standardization of Cry1Ab production and quantification by SDS-PAGE/densitometry may improve data consistency.”

If we look at their reported statistics, we can see for ourselves just how high the CV is on the ELISA test (and therefore how unreliable it is as a method for quantifying Cry1Ab)  compared to other proven methods of quantification.

 

So there you have it. A practical example of an application of a very basic statistic, the coefficient of variation.

References:

Maternal and fetal exposure to pesticides associated to genetically modified foods in Eastern Townships of Quebec, Canada. Reprod Toxicol. 2011 May;31(4):528-33. Epub 2011 Feb 18.

Aris A, Leblanc S.

Comparison and Validation of Methods To Quantify Cry1Ab Toxin from Bacillus thuringiensis for Standardization of Insect Bioassays. Andre´ L. B. Crespo,1 Terence A. Spencer,1 Emily Nekl,2 Marianne Pusztai-Carey,3 William J. Moar,4 and Blair D. Siegfried1* APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Jan. 2008, p. 130–135 Vol. 74, No. 1

A Meta-Analysis of Effects of Bt Cotton and Maize on Nontarget Invertebrates. Michelle Marvier, Chanel McCreedy, James Regetz, Peter Kareiva Science 8 June 2007: Vol. 316. no. 5830, pp. 1475 – 1477

Comparison of Fumonisin Concentrations in Kernels of Transgenic Bt Maize Hybrids and Nontransgenic Hybrids. Munkvold, G.P. et al . Plant Disease 83, 130-138 1999.

Indirect Reduction of Ear Molds and Associated Mycotoxins in Bacillus thuringiensis Corn Under Controlled and Open Field Conditions: Utility and Limitations. Dowd, J. Economic Entomology. 93 1669-1679 2000.

Impact of Bt cotton on pesticide poisoning in smallholder agriculture: A panel data analysis. Shahzad Kouser, Matin Qaim. Ecological Economics

Volume 70, Issue 11, 15 September 2011, Pages 2105–2113

Communal Benefits of Transgenic Corn. Bruce E. Tabashnik  Science 8 October 2010:Vol. 330. no. 6001, pp. 189 - 190DOI: 10.1126/science.1196864

The Coefficient of Variation

Coefficient of Variation: A relative measure of variation measuring the standard deviation relative to the mean.  

Recall the standard deviation is the square root of variance.

CV = (standard deviation / mean) * 100

This metric is useful for comparing variables that have different standard deviations and different means.

For instance, let’s assume we have two corn hybrids that average 150 bushels an acre, and hybrid A’s yield has a standard deviation of 10 bushels per acre, while hybrid B’s yield has a standard deviation of 50 bushels an acre.  If we are about to plant one of these hybrids, we know that hybrid A is going to provide us more certainty about our expected yields in the fall.  The empirical rule tells us that about 95% of the time if we plant hybrid A, our yields will be between 130 and 170 bu/acre. If we plant hybrid B, 95% of the time yields will be between 50 and 250 bu/acre.

So, with two hybrids with the same average yield, we know that the one with the lower standard deviation will perform more consistently. But what if they both have different yields and different standard deviations?

Hybrid A:  mean 185 bu;/acre  std dev: 5 bu/acre

Hybrid B: mean: 200 bu/acre std dev: 30 bu/acre

Choosing the most reliably yielding hybrid in this case is not quite so easy. But the CV helps us make the comparison:

Hybrid A: CV = (5/185) *100 = 2.7%

Hybrid B: CV =  (30/200)*100 = 15%

We can see by the CV that hybrid A, even though it yields on average less than hybrid B,  will deliver more consistent results.
 

In the context of finance, we can think of the CV as a measure of relative dispersion that can be used to compare the risks of assets  that have different mean (expected )returns.

Reference: Principles of Managerial Finance.  11^th Edition. Lawrence J. Gitman.