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Experimental economics is a field of economics which emerged in the 1990\'s [1] and uses experimental methods to evaluate theoretical predictions of economic behavior. In contrast to traditional economic empiricism, which relies on observing decisions in natural environments, experimental economics seeks to control causative factors in order to provide better ceteris paribus comparisons between situations.
In addition to testing the predictions and underlying assumptions of economic theory, experimental economics is also used to testbed institutions and environments implementable as policies.
Historically most economic experiments were conducted in the laboratory, but recently interest in economics field experiments has grown. The development of experimental economics has also led to increased interest in econometrics studies of natural experiments.
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Economics experiments can be loosely classified into the following topics: Markets, Games, Decision making, Bargaining, Auctions, Coordination, Social Preferences, Learning, Matching, and Field Experiments.
Coordination games are games with multiple equilibria, often Pareto ranked. There are two general sets of questions that experimental economists typically ask when examining such games: (1) Can laboratory subjects coordinate, or learn to coordinate, on one of multiple equilibria, and if so are there general principles that can help predict which equilibrium is likely to be chosen? (2) Can laboratory subjects coordinate, or learn to coordinate, on the Pareto best equilibrium and if not, are there conditions or mechanisms which would help subjects coordinate on the Pareto best equilibrium? Deductive selection principles are those that allow predictions based on the properties of the game alone. Inductive selection principles are those that allow predictions based on characterizations of dynamics.
The need for learning models comes from the fact that subjects in laboratory experiments often make decisions repeatedly. Moreover, in games of 2 players or more, subjects may form beliefs about what other subjects will do and these beliefs may be updated over time. Such a process is known as belief learning. Subjects may also move away from decisions that have given them bad payoff in the past and towards decisions that have rewarded them with high payoffs in the past. Such a process in known as reinforcement learning. Until the 1990s, simple adaptive models, such as Cournot best response or Fictitious Play, were generally used. In the mid-1990s, Alvin Roth and Ido Erev demonstrated that reinforcement learning can make useful predictions in experimental games. In 1999, Colin Camerer and Teck Ho introduced Experience Weighted Attraction, known as EWA, which was a general model that nested different forms of reinforcement and belief learning, and shows that fictitious play (with weights on past history) is mathematically equivalent to generalized reinforcement, where even unplayed strategies are reinforced. Criticisms of EWA include overfitting due to many parameters, lack of generality over games, and the possibility that the interpretation of EWA parameters may be difficult. The first criticism has been addressed by estimating parameters on some of the experimental periods or experimental subjects and forecasting behavior in the remaining sample (if models are overfitting, these out-of-sample validation forecasts will be much less accurate than in-sample fits, which they generally are not). The second criticism has been addressed by replacing fixed parameters with "self-tuning" functions of experience, which allows pseudo-parameters to change across the course of a game and also to vary systematically across games. While the debate between EWA and predecessors dominated the field for most of the past decade, the field appears to be re-emerging with new questions. Roberto Weber, for example, has raised issues of learning without feedback. David Cooper and John Kagel have investigated types of learning over similar strategies. Ido Erev and Greg Barron have looked at learning in cognitive strategies. Dale Stahl has characterized learning over decision making rules. Charles Holt has studied logit learning in different kinds of games, including games with multiple equilibria. Wilfred Amaldoss has looked at interesting applications of EWA in marketing. Amnon Rapoport, Jim Parco and Ryan Murphy have investigated reinforcement-based adaptive learning models in one of the most celebrated paradoxes in game theory known as "centipede games."
Vernon Smith, formerly of the University of Arizona and now at the Interdisciplinary Center for Economic Science at George Mason University conducted pioneering economics experiments on the convergence of prices and quantities to their theoretical competitive equilibrium values in experimental markets. Smith studied the behavior of "buyers" and "sellers", who are told how much they "value" a fictitious commodity, and then are asked to competitively "bid" or "ask" on these commodities following the rules of various real world market institutions, such as the Double auction (both sides can bid) used in many stock exchanges, as well the English auction and the Dutch auction (see Auctions). Smith found that in some forms of centralized trading, prices and quantities traded in such markets converge on the values that would be predicted by the economic theory of perfect competition, despite the conditions not meeting many of the assumptions of perfect competition (large numbers, perfect information).
Over the years, Smith pioneered -along with other collaborators- the use of controlled laboratory experiments in economics, and established it as a legitimate tool in economics and other related fields. Charles Plott of the California Institute of Technology collaborated with Smith in the 1970s and pioneered experiments in political science, as well as using experiments to inform economic design or engineering to inform policies. In 2002, Smith was awarded (jointly with Daniel Kahneman) the Bank of Sweden Prize in Economic Sciences "for having established laboratory experiments as a tool in empirical economic analysis, especially in the study of alternative market mechanisms".
The term "social preferences" refers to the concern (or lack thereof) that people have for each other\'s well-being, and it encompasses altruism, spitefulness, tastes for equality, and tastes for reciprocity. Experiments on social preferences generally study economic games including the dictator game, the ultimatum game, the trust game, the public goods game, and modifications to these canonical settings. As one example of results, ultimatum game experiments have shown that people are generally willing to sacrifice monetary rewards when offered unequal allocations, thus behaving inconsistently with simple models of self-interest. Economic experiments have measured how this deviation varies across cultures. (More market-oriented societies tend to have higher inequity aversion.)
Experimental economists generally adhere to the following methodological guidelines:
Please note: this brief list was compiled by Diego Aycinena for the ESA discussion list.
For recruiting subjects (via internet) for lab experiments:
ORSEE (by Ben Greiner) is a web-based Online Recruitment System, specifically designed for organizing economic experiments: http://www.orsee.org/ There is a test system online where you can log on without registering: http://orsee.sourceforge.net/web/test.php ORSEE will be installed on a local server (ExLab maintains your subject database on their server). A user manual and installation notes are available as well: http://orsee.sourceforge.net/web/doc.php The online web facility at ExLab: http://exlab.bus.ucf.edu is widely used around the world. CASSELL from CalTech (via internet). The CalTech lab has been developing both experiment management and experimental software in the past several years. They are due to release a new version of the experiment management/recruiting web application very soon.
For designing, programming and running experiments:
Ztree www.iew.unizh.ch/ztree/ Zurich Toolbox for Readymade Economic Experiments (Ztree) is a software software package allows to develop and to carry out economic experiments. LabSEE –a new experimental program. This program uses Java as programming environment to conduct experiments over the Internet. The functionality should be similar to Z-tree. The beta version and tutorial will be available soon at: http://www.ekonomiaeksperymentalna.edu.pl/node/3 Now, you can download version 0.5 with no documentation.
In addition, some bigger labs (SSEL, CASSEL, ICES, ESI) offer code or programs for free download. For instance: Veconlab http://veconlab.econ.virginia.edu/admin.htm provides about 50 on-line programs for different types of markets/experiments; jMarkets is open software to run markets experiments online, see http://jmarkets.ssel.caltech.edu
EconPort
The software on EconPort is designed to be used for research experiments as well as teaching experiments. It is Internet software, hence can be used in a laboratory or with subjects located elsewhere. EconPort contains the following software:
The AEELab Remote Launcher Package enables you to issue commands to client machines remotely, allowing you full control over the running of an experiment session from a single machine. http://www.aton.com.au/activeexperiments.html (It also offers a library of software for running various experiments).
For running experiments in finance, researchers in Lille (France) have developed a free, open-source -GPL- software package called jESSX (java Experimental and Simulated Stock Exchange). It is really easy to use and will allow soon (some packages being still under development) to mix human subjects and Artificial Intelligent Agents. For now there are still some restrictions concerning the number of subjects interacting (12 is a good number). The software is based on an order-driven market and a couple of orders are implemented (market orders, limited price orders etc...). There is also a web-based extension offering the possibility of running experiments or simulations remotely. Software and a users guide can be found at http://rb.ec-lille.fr/jessx/index.php.
Experiment Software for Teaching:
www.EconPort.org from the Experimental Economics Center at Georgia State University provides "an economics digital library specializing in content that emphasizes the use of experiments in teaching and research." http://www.marietta.edu/~delemeeg/games/ Games Economists Play: Non-Computerized Classroom-Games for College Economics FEELE (Finance and Economics Experimental Laboratory at Exeter) provides a Website of Teaching Experiments: http://www.projects.ex.ac.uk/feele/ExperimentList.shtml
The above guidelines have developed in large part to address two central critiques. Specifically, economics experiments are often challenged because of concerns about their "internal validity" and "external validity", for example, that they are not applicable models for many types of economic behavior, so the experiments simply aren\'t good enough to produce useful answers.
Some economic theorists, especially the Austrian school, reject the entire concept of economic empiricism, since they reach their conclusions strictly by deduction (from axioms arrived at introspectively).
A branch of Experimental economics is Experimental finance, which is the application of Experimental economics in financial markets. The goals of Experimental finance are to establish different market settings and environments to observe experimentally and analyze agents\' behavior and the resulting characteristics of trading flows, information diffusion and aggregation, price setting mechanism and returns processes. Presently, researchers use simulation software to conduct their research.
This article is licensed under the GNU Free Documentation License. It uses material from Wikipedia
