Experimental Economics

Abstract

Experimental economics creates a controlled environment in which many of the unanswered questions about economics may be given careful study. This paper provides a comprehensive analysis of experimental economics and its role in studying the ever-changing global economic system of the twenty-first century.

Overview

One of the most iconic scientific findings of the early twentieth century was Alexander Fleming's discovery of penicillin. As luck would have it, a tiny amount of mold floated up into Fleming's laboratory from a mycology lab one floor below, and landed in an uncovered culture plate in 1928. When Fleming, who was on vacation at the time, returned to his workplace, he discovered the mold and its as-yet unrealized potential, and medical history was made. Years later, he visited another laboratory, one that was modernized and virtually free from contaminants. His host commented on the conditions in which Fleming had toiled and wondered aloud about what extraordinary discoveries Fleming could have made in such a facility. Fleming responded simply: "Not penicillin" ("Serendipity," 2009).

Indeed, science is often broken into two arenas: Laboratory environments in which controlled experiments are conducted and "real-world" settings in which the processes or concepts being studied are allowed to play out in uncontrolled conditions. In the science of economics, the same generalization can be made. On the one hand are the trends that occur and systems that are in operation which are the focus of observant economists. These individuals take such data and establish theoretical frameworks to help explain what transpires. On the other hand are the concepts that may be compiled in theoretical constructs and then applied in real world scenarios.

The latter of these two economic arenas is what is known as "experimental economics." Like Fleming's laboratory (as well as the modernized facility he visited later in life), experimental economics creates a controlled environment in which many of the unanswered questions about economics may be given careful study. This paper provides a more comprehensive analysis of experimental economics and its role in studying the ever-changing global economic system of the twenty-first century.

A Brief Overview of Experimental Economics. Economics is a science, complete with a wide range of analytical methods and theoretical frameworks. Of course, an arena as dynamic and multifarious as economics has largely been considered difficult to quantify or understand in a controlled environment. Many economists have therefore eschewed this approach, believing that the better avenue is to study economic trends in "real world" settings.

Then again, much of economics focuses on the balance between supply and demand. Demand may be considered the preference of the consumer or, to put it in a psychological context, a matter of individual choice. In 1931, L.L. Thurstone first applied such an approach, employing utility theory (a psychological attempt to ascertain the value, or "utility," of choice) to predict individual choice in consumerism. Several other studies, one in 1944 and two more in 1951 and 1953, supported Thurstone's theory. In fact, studies abounded over the next few decades, culminating in a series of studies in the 1990s that used utility theory to analyze irrational behaviors which could lend to rises in consumption and savings behavior (McKinney & Roth, 2006).

The Rules of the Marketplace. Part of what is being studied in experimental economics are the rules of the marketplace and how they impact the market itself. Over the course of the latter twentieth century, economist Vernon L. Smith conducted or oversaw thousands of experiments on social groups and the impact of consumer preference on the markets. He broke down the idea of market trading into simple interactions between individuals. In understanding the nature of consumer behavior, his laboratory studies of individual preference helped policymakers, industrialists, entrepreneurs and fellow economists better gauge consumer behavior. As Smith, a 2003 Nobel Prize winner, succinctly said, "The benefits of market exchange are easy to see in personal interactions, where you do something for me and I do something for you," he said, adding, "Out there in 'markets,' though, they're not always clear. If the price goes up, the oil companies get more money and I have less. That's the average person's perception and experience. Experimental economics helps put a human face on markets" (Gillespie & Lynch, 2002).

Smith's approach stemmed from his experience working with Edward Chamberlin. Chamberlin had become cynical of the predictability of the markets during the Great Depression, an era in which such understanding was absolutely necessary. Chamberlin focused on three areas.

• The first was a streamlined version of the natural markets.
• The second was a laboratory interpretation of the markets, in which the various subcomponents could be separated and applied in a number of game experiments.
• The third of these areas consisted of individual experiments; putting a focus on a microscopic level and analyzing patterns of individual choice for reapplication into market scenarios.

Through these market experiments (which entailed the employment of a number of test subjects—namely Chamberlin's graduate students, of whom Vernon Smith was one), Chamberlin constructed a number of early theories about consumer choice that would ultimately inspire Smith's later works (Davis & Holt, 1993).

Experimental economics is not employed to explain large, complex trends and systems in a given market. Rather, it is used to help analyze specific elements of a given system and, as a result, help explain how those elements contribute to the whole system in question. As California Institute of Technology Professor Charles Plott said in a 2008 interview:

Modeling. An important aspect of experimental economics is the use of modeling. Modeling entails placing elements of a given study area into a controlled framework in order to see how these parts interact. Models are general vehicles, to be sure, but have the potential to be flexible as internal elements are modified, supplemented or reduced in number.

Modeling has become a popular form of experimental economic analysis, particularly among large companies and governments who seek to maximize returns on investments, business practices or changes to policymaking strategies. In the modern era, computer technology has helped immeasurably to connect large quantities of complex and multifarious data into a working system whose parts' contributions can be studied individually or in the aggregate.

The use of models in experimental economics has caught on in many corporations who not only seek maximum return on investments and strategies, but to locate flaws or loopholes in their current endeavors. Models could be used to determine the optimum time to introduce new products by taking into account mitigating factors such as manufacturing, marketing and engineering. In big companies like Hewlett Packard, on-site economics labs are sometimes utilized to help predict and control business. For HP, such a lab meant the ability to predict demand from the company's distributors; forecasts which had previously been off by as much as 100 percent (Krakovsky, 2008).

Chamberlin used experimental economics and models to help make sense out of complex (and indeed daunting) economic circumstances. In periods in which cost-effective policies and strategies are paramount (particularly during recessions), studying and generating models of consumer behavior and supply-side management becomes critical. This paper next turns to a brief review of some of the forms of experiments used in experimental economics.

Games

The Prisoner's Dilemma. In 1950, mathematician Albert W. Tucker formalized a concept that he would call "The Prisoner's Dilemma." Within this theoretical design, a simple scenario was introduced that would ultimately play a tremendous role in the experimental economics arena by helping economists study the relationship between supply and demand.

In this "game," two hypothetical thieves are captured after they commit a crime. They could each get ten years in prison for being part of the crime. During their separate interrogations, each individual is given a simple choice: Confess and implicate the other, or refuse to confess. If Prisoners A and B both refuse to confess, they will only get one year in jail for a lesser crime (such as possession of a firearm). However, if Prisoner A confesses and implicates B while B does not confess or implicate A, A could be set free altogether while B gets put in jail for 20 years. If they both confess and implicate each other, each will get the ten-year sentence.

The key here is strategy—should Prisoner B refuse to confess, he or she could conceivably get one year instead of ten if his or her partner also refuses to confess. Then again, if he or she does not confess, B might also go to jail for 20 years if Prisoner A does confess and implicate him or her. Therefore, while the "rational" strategy would be for both to refuse to cooperate with the police, the temptation of getting away free for implicating the other means that both prisoners would likely be best served by confessing, even though the "irrational" course of action, bilateral silence, would in fact entail the best possible amount of jail time (McCain, 2008).

In experimental economics, games like the Prisoner's Dilemma help theorists determine dominant strategy equilibrium. Prisoner A, for example, must review all possible strategies for achieving the maximum gain for himself or herself (in other words, the least amount of jail time). If under the varying conditions that may become manifest Prisoner A maintains this strategy throughout the game, his or her course of action is known as the "dominant strategy." Of course, there is more than one player, and that adversary also seeks maximum gain from his or her interaction with A. With two competing strategies coming into contact with one another, the result is what is known as "dominant strategy equilibrium." In terms of the Prisoner's Dilemma, for example, the dominant strategy equilibrium of both prisoners confessing and implicating the other is both parties receiving 10-year sentences.

Games such as the Prisoner's Dilemma have implications and uses for a wide range of scientific study. These games allow individuals to make their own decisions and develop their own strategies; how well participants do in the game depends heavily on the choices and strategies of other players. Such conditions have particular use in experimental economics, as they often bear similarities to real economic situations and market conditions. In fact, economists experimenting with such games tend to do so to help form policy strategies and correct market or institutional issues as well as to validate economic theories (Shor, 2006).

Experimental economics, like any other form of scientific field, entails the study of certain elements of the subject matter in a relatively controlled environment. Games provide a vehicle for such study. Then again, there are those who believe that one of the great failings of economic theory is that it tends to emerge and return to textbooks without having a true basis in "real world" settings (Bergmann, 2009). This argument is particularly evident in macroeconomics (the field of economics in which the workings of the overall, national economy are studied), where relevant public policymaking enters the picture. In these arenas, another manifestation of experimental economics, field experiments, comes into play. This paper next takes a look at field experiments and their value in addressing the perceived shortcomings of traditional economic study.

Field Experiments. Laboratory experiments in economics are important because they help verify existing assumptions and theories in a controlled environment. However, many of these assumptions and theories are offered in response to situations and trend that occur in the natural economic environment. It is therefore useful to the science of economics to conduct field experiments.

Field experiments have increased in popularity and effectiveness over the last century. In the 1920s and 1930s, such experiments were conducted in the agricultural sector to define the trends within the industry. In the mid-twentieth century, the field was expanded significantly to focus on government-sponsored social studies, assessing individual and group behaviors. The practice of field study in economic circles has continued to evolve and develop, most recently to such a level that a very broad range of experiments occur in controlled settings outside of the laboratory (Levitt & List, 2009).

Field experiments are often useful in studying the relationship between individual behavior and economic trends. One such experiment assessed the behavior of charitable donors. The author took interest in philanthropic giving when asked to assist in soliciting funds for a new economics department at the University of Central Florida. Dividing the pool of potential donors into several groups, the author determined that a donor would be more likely to contribute if he or she was informed by the solicitor that seed money had been invested by the University (List, 2008).

Whereas the Prisoner's Dilemma, for example, presents a scenario in which individual choices and strategies present a theoretical outcome, real-world situations do not always create such controlled settings. In a similar study of the philanthropic analysis above, a 2007 essay looked into participant behavior in auctions. In a controlled laboratory setting, scientists would assume that there would be a fixed number of participants with predictable value based on the distribution of the materials on hand. They might even conclude that the revenue from that auction would be predictable based on a Nash equilibrium—a balance struck when two or more individuals' strategic decisions meet in such a way that the convergence of those strategies establish a common point.

Of course, such controlled circumstances lack an inclusion of a number of variables. For one, the rules of the auction might be such that individual strategies may differ or be adjusted, thereby effecting an alteration of bidding practices and revenue generation. Other factors may give rise to different predictive outcomes, such as increases in the number of bidders or a lack of information about the rules of the auction (Reiley & List, 2007).

As the above example suggests, field experiments should not be considered the alternative to laboratory studies within the experimental economics field. In fact, laboratory settings provide a strong theoretical foundation to a number of experimental subjects. Rather, field experiments are often seen as a valuable compliment to the controlled environment of the laboratory, bringing to light previously unanticipated or variable elements that can have a significant impact on study outcomes.

Conclusion

Vernon L. Smith once commented on his inspiration for moving into the field of experimental economics. "I gradually became persuaded that the subjects, without intending to, had revealed to me a basic truth about markets that was foreign to the literature of economics." Indeed, Smith and his mentor, Edward Chamberlin, saw that the constraints of traditional economics yielded useful theoretical information but fell short when the world evolved and economic systems grew more complex and less similar to those on which that literature was based.

As a result of this systemic evolution, Smith helped the study of economics evolve as well. He did not eschew theoretical or literature-based economics—he supplanted it and even helped validate much of it by fostering experimental economic methodologies. Over time, experimental economics techniques, such as the ones described in this essay, have demonstrated their worth not only for academic circles but for businesses and political leaders. Computer models and simulations and physical laboratories have created controlled settings for the careful study of the parts and subsystems that comprise larger issues. Additionally, the study of consumer choice and systemic operations is enhanced by the use of games and field experiments which help to predict trends and social developments for which the literature may not account. With the advent of a form of economic study that was considered radical as recently as the mid-twentieth century, economics has grown into a dynamic science that is as complex as the subject matter it studies.

Terms & Concepts

Dominant strategy: Economic concept whereby one strategy is beneficial to the individual regardless of the strategies of others within a relationship or system.

Dominant strategy equilibrium: The balance point at which two or more dominant strategies converge.

Nash equilibrium: A balance struck when two or more individuals' strategic decisions meet in such a way that the convergence of those strategies establish a common point.

Prisoner's dilemma: Analytical game whereby two subjects are left to decide their best strategy without knowing their respective counterpart's plan.

Utility theory: Psychological attempt to ascertain the value, or "utility," of choice.

Bibliography

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Suggested Reading

Englebrecht-Wiggans, R., & Katok, E. (2007). Regret in auctions: Theory and evidence. Economic Theory, 33, 81-101. Retrieved March 13, 2009, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=25811455&site=ehost-live

Fischbacher, U., & Stefani, U. (2007). Strategic errors and audit quality: An experimental investigation. Accounting Review, 82, 679-704. Retrieved March 13, 2009, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=25002329&site=ehost-live

Samuelson, L. (2005). Economic theory and experimental economics. Journal of Economic Theory, 43, 65-107. Retrieved March 13, 2009, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=17018313&site=ehost-live

Smith, V. (2017). Tribute to Sidney Siegel (1916-1961): A founder of experimental economics. Southern Economic Journal, 83(3), 664-667. doi:10.1002/soej.12196. Retrieved February 15, 2018, from EBSCO online database Business Source Ultimate. http://search.ebscohost.com/login.aspx?direct=true&db=bsu&AN=120999897&site=ehost-live&scope=site

Todd, K. (2007). Beyond theory: Experimental economics. Baylor Business Review, 25, 40-41. Retrieved March 13, 2009, from EBSCO online database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=25854075&site=ehost-live