by Filip Palda
Control allows you to draw a clear line between a causal and a dependent variable. Statistics then lets you say with what likelihood the link you are seeing is the result of chance. Control is part of every scientist’s way of reasoning. Yet economists have done perhaps more than any other group of thinkers to broaden the applicability of control to respond to three types of data. The worst data, from the economist’s standpoint, are those that the economy generates without any reference to the economist’s research needs. Economists responded to this unhelpful state of affairs by inventing econometrics, the science of the study of causal relations between economic variables. To make up for the uncontrolled nature of the data they invented elaborate statistical techniques. These techniques were pattern-searching algorithms that relied on the economist to provide a model. The model narrowed the range of the pattern search.
By the 1980s the grossly subjective nature of these exercises became obvious to most economists and a cry went up for a “credibility revolution” in economic data analysis. The answer was to focus far less on developing fancy statistical techniques for reading patterns in economic tea leaves, and to instead focus on creating a second type of dataset that could be analyzed by the simple comparison of average performances between treatment and control groups.
Controlled experiments are costly, so economists also focused on finding a third type of dataset which arose from what they called “natural experiments”. Government interventions that resembled lotteries were the best type of natural experiment to analyze. A government lottery to participate in some initiative creates similar groups of participants and non-participants. Similarity allows you to subtract the results of the treatment from the control group. What you are left with is the net effect of the program. Which is all the news that’s fit to print.
References
Angrist, Joshua D., and Jörn-Steffen Pischke. 2010. “The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics.” Journal of Economic Perspectives, volume 24: 3–30.
Galiani, Sebastian, Martín A. Rossi, and Ernesto Schargrodsky, 2011. “Conscription and Crime: Evidence from the Argentine Draft Lottery.” American Economic Journal: Applied Economics, volume 3: 119–136.
Hendry, David F. 1980. “Econometrics—Alchemy or Science?” Economica , volume 47: 387–406.
Hicks, J.R. 1937. “Mr. Keynes and the Classics—A Suggested Interpretation.” Econometrica, volume 5: 147–159.
Keynes, John Maynard. 1936/2007. The General Theory of Employment, Interest and Money. (London: Macmillan).
Lalonde, Robert J. 1986. “Evaluating the Econometric Evaluations of Training Programs with Experimental Data.” American Economic Review, volume 76: 604–620.
Leamer, Edward E. 1983. “Let’s Take the Con Out of Econometrics.” The American Economic Review, volume 73: 31–43.
Lucas, Robert E., Jr. 1976. “Econometric Policy Evaluation: A Critique.” Carnegie Rochester Conference Series on Public Policy, volume 1: 19–46.
Munk, Nina. 2013. The Idealist: Jeffrey Sachs and the Quest to End Poverty. Doubleday.
Nunn, Nathan, and Nancy Qian. 2012. “Aiding Conflict: The Impact of U.S. Food Aid on Civil War.” NBER Working Paper No. 17794.
Peterson, Paul, William Howell, Patrick J. Wolf, and David Campbell. 2003. “School Vouchers. Results from Randomized Experiments.” In Caroline M. Hoxby (ed.). The Economics of School Choice. University of Chicago Press: 107-144. Available at http://www.nber.org/chapters/c10087.
Sims, C.A. 1980. “Macroeconomics and Reality.” Econometrica, volume 48: 1–48.
Sims, Christopher A. 2010. “But Economics Is Not an Experimental Science.” Journal of Economic Perspectives, volume 24: 59–68.
Slemrod, Joel, Marsha Blumenthal, Charles Christian. 2001. “Taxpayer Response to an Increased Probability of Audit: Evidence from a Controlled Experiment in Minnesota.” Journal of Public Economics, volume 79: 455–483.
Slutsky, Eugen. 1937. “The Summation of Random Causes as the Source of Cyclic Processes.” Econometrica, volume 5:105-146.
Stock, James H. 2010. “The Other Transformation in Econometric Practice: Robust Tools for Inference.” Journal of Economic Perspectives, volume 24: 83–94.
EPILOGUE 9
THE SEVEN STEPS TO MASTERING economics are actually not all that difficult to ascend. The difficulty lies in deciding what to do when you get to the top of the staircase.
Economics can be a hobby or it can be a way of looking at the world. A light reading of this book will give you an idea of what the fundamental issues in economics are. The concepts of moral hazard, adverse selection, Nash equilibrium, equalizing differences, time-inconsistency, permanent income, mean-preserving spreads, efficient frontiers, Pareto efficiency, mechanism design, randomized controlled experiments, and many more will no longer be strangers to you. But while individually interesting, these islands of thought form part of larger archipelago. For what unites all of economics is a quest to establish a science of social accounting. In this pursuit the many ideas we have discussed have an important place. The method of social accounting into which they fit is known as Pareto-efficiency.
Provided that decisions on how to use resources are taken in a context that encourages Pareto-efficiency, societies will be able to experiment with new ways of using resources without risking the wellbeing of the many. Pareto-efficiency puts a floor on the losses from social interactions involving property because any Pareto-improving exchange must benefit at least one person without harming anyone else. The result of this economic error-correction protocol is a society in which social accounts tend to be balanced. What people believe they are getting out of the “system” is at least as large as what they think they are putting into it.
Such a belief can be the bedrock of a stable society of people who live together in large numbers but may not even know who their neighbors are. The need to understand whether the system of social accounts under which we labor is stable or will lead to ruin makes of economics a science to be taken seriously, explained with intent, and appreciated for its solemnity.
The Apprentice Economist is no book of quips, or witty anecdotes. It is a guide to mastering some of the most important ideas that govern the individual and society. When faced with material crises governments do not call upon historians, anthropologists, political scholars, or psychologists. They call on economists. These have developed the most coherent and convincing description of how society organizes itself through a system of accounting amenable to precise analysis. Mastering this analysis is the challenge of the apprentice economist.
Table of Contents
PREFACE 1
References
SUBSTITUTION 2
The pervasiveness of trade-offs
The Substitution Games
The demand curve
The Slutsky equation
Uses of the Slutsky Equation
The relative philosophers
Gold in the theory
Substitution as the road to riches
Renting substitution
Prices are in your hands
From consumers to capitalists
Economist, economist
Conclusion
References
TIME 3
Time’s simple face
Present value
Permanent income, life-cycle hypothesis
Life-cycle theory and government
The complex face of time
The fall and rise of growth theory
Statistics and the social engineer
Eine kleine time paradox
Other applications of inter-temporal analysis
Time in the general economic view
A brief time of history
Conclusion
References
CHANCE 4
The constraint
The odds ratio
Happiness in an uncertain world
Risk aversion
The
troublesome question of separable utility
Crime
CAPM
The risk-return frontier
The Markowitz algorithm
Stock market equilibrium
Diversification, efficiency
Rational Expectations
Money illusion
Self-fulfilling equilibria
Chance and the individual
References
SPACE 5
Hotelling and the competitive continuum
Lancaster and characteristics space
The ideology of constraints vs. preferences
A new perspective of the meaning of price
Rosen and the equalizing difference
Cyanide and gold
Equalizing differences and segregation
Racism and the dissipation of wealth
The curse of dimensionality
Curving economic space
Married in space
The final frontier
References
EQUILIBRIUM 6
Balancing social accounts
From central control to markets
Pareto efficiency
Market equilibrium
The efficiency of equilibrium
The second welfare theorem
The deep waters of equilibrium
Enter Pigou
Socialist free-marketers
Political equilibrium
The dark matter of economics
References
GAMES 7
The essence of games
Superior intellect of no use
The minimax theorem
The Nash Supremacy
Hunting for stag
The Schelling Point
Subgame perfection
The Harsanyi Renaissance
Fusion of game theory and information economics
Ex ludis probitas et oboedentia
The Spence Signal
The Vickrey auction
Mechanism design and the size of government
Centralized (Vickrey-Clark-Groves) vs. decentralized (Spence) mechanisms
The mechanism zoo
Are free markets better or worse?
The apprenticeship of game theory
References
CONTROL 8
The Dark Ages of econometrics
The role of models
The credible path to control
Randomness cannot be controlled but can be measured
Hearing through the noise
Finding similar groups
Randomized experiments
A few examples
Natural experiments
Computer experiments
What about prediction?
Summary
References
EPILOGUE 9