markets as institutions: discovering foundations and properties through experiments shyam sunder,...

Markets as Institutions:Discovering Foundations and Properties

through Experiments

Shyam Sunder, Yale University

Economic Science Association Asia-Pacific MeetingInstitute of Social and Economic ResearchOsaka University, February 10-11, 2007

Sunder: Market Institutions 2

Humanities and Science• Science does not know its debt to imagination. Ralph Waldo Emerson • Vivisection is a social evil because if it advances human knowledge, it

does so at the expense of human character. George Bernard Shaw

• The theoretical broadening which comes from having many humanities subjects on the campus is offset by the general dopiness of the people who study these things. Richard P. Feynman

• Economics is more complicated than physics. Benoit Mandelbrot• Economics has an amazing capacity to summarize staggeringly complex

phenomena by the application of only a handful of principles. Charles R. Plott

• Being outside and above local contingencies, collective consciousness sees things only in their permanent and fundamental aspects, which it crystallizes in ideas that can be communicated. Emile Durkheim


An Overview

• Origins of experimental economics in exploration of aggregate phenomena

• Progressive shift to micro-level phenomena• This shift accentuates the dilemma of social

sciences between science and humanities• A three-way classification of experimental work• Aggregate phenomena can fit into science• Examples: ZI, structural market games• Evolution, biology, sub-optimality and free-will


Overview• Origin of experimental economics in examination of aggregate phenomena• Gradual, steady shift towards study of micro-level phenomena due to

– Analytical process and reasoning– Incremental research questions– Unlike assumption in theory, people do not optimize well by intuition

• Today, much experimental work has shifted to examination of individual behavior and of economies populated by artificial agents

• Shift to individual behavior has accentuated the ever-present dilemma of social sciences in trying to be a science on one hand, and handle humans at the same time

• What are the antecedents and consequences of this trend?• Usefulness of organizing experimental economics into three streams:

– Structural: macro properties of social structures– Behavioral: behavior of individuals, and – Agent-based: exploration of links between the micro and macro phenomena

• At least the structural part of economics can be firmly rooted in the tradition of sciences, bypassing the free-will dilemma of social sciences


Examining Market Institutions

• Chamberlin (1948) examined the behavior of a market institution under controlled conditions of his classroom

• Vernon Smith (1962), a subject of Chamberlin) redesigned and systematically varied the market conditions to examine price, allocation, and extraction of surplus

• Both designs deviated significantly from Walrasian tatonnement abstraction; they fleshed them out with details, using stock market as a guide– Economic environment (market demand and supply) and market

design as independent variables– Market level outcomes as dependent variables


Data from Experiments

• Experiments can yield a great deal of data• Data are limited only by interest and imagination of the

experimenter, and ingenuity in capturing data without distracting subjects from their task in a significant way

• Chamberlin gathered three pieces of data for each transaction (price, seller cost and buyer value), and the transaction sequence

• Some examples of data he did not gather: the clock time of transactions, details of the bargaining process (time elapsed, price proposals, number of proposals, number of counter-parties bargained with), etc.


Data to Meet Experimental Goals

• Most experiments can yield a great deal of data• We gather only what we need in order to address the

question(s) we wish to answer on the basis of the experiment

• Constraints:– Technology of data gathering, eased by development of

computer technology to conduct economics experiments)– The possibility of interaction between data capture and subjects

• Given Chamberlin’s goals, asking subjects to report their transactions immediately after they completed each transaction served his purposes well, causing little interference with subjects’ trading


Shift Towards Micro Phenomena

• Focus of experimental economics work is gradually shifting from aggregate market or institution level phenomena towards individual behavior

• Three factors appear to drive this shift– The logic of analytical method– Incremental nature of research designs– Empirical finding that people, acting by intuition alone,

are not good at optimization as typically assumed in derivation of equilibria in economic theory


1. Logic of Analytical Method

• It is rare for the correspondence between the predictions of the theory of interest, and experimental data, to be either complete or totally absent

• If the experimenter has no, or low, expectation of correspondence between the two, observation of even a moderate relationship is seen as half full glass of water

• However, most experiments are designed to examine specific theories that have some legitimate prior claim to predictive power

• Conducting experiments where no predictive power is expected is simply too wasteful

• By definition, theories are simple models designed to capture some general tendency, without claim to perfect explanation of the phenomenon of interest


Logic of Analytical Method

• Before data are gathered and examined, few theories inform us of the extent of their explanatory power (which must be estimated from the data from the field or lab)

• Accordingly, any imperfections of correspondence between data and theory tends to be seen as half empty, not half full, glass of water

• Seeking a fuller explanation to close the gap between data and theory is a natural instinctive reaction of most of us investigators


Search for Higher Explanatory Power

• Following this logic, analysis and discussion of most experiments ends in a search for ways to increase the correspondence (e.g., R-square) between data and theory

• Better prediction and explanation is the currency of scientific progress

• We look for ways to modify the model to enhance its explanatory power through analysis—breaking the problem down into progressively smaller components

• This logical pursuit shifts research question(s) to the next level of detail causing “micro-nization” of economics

• Analysis dominates• Synthesis (discarding chosen details, to step back and see

the big picture) is a much less common reaction to data


Example: Demand, Supply and Experiments

• Simple economic theory: point of intersection of demand and supply determines price and allocations

• Economists’ long-held deep faith in theory with sparse empirical support

• Neither Chamberlin’s nor Smith’s data corresponded precisely to the theory

• Chamberlin: none of the 19 transactions occurred at the equilibrium price of 57; average price of 52 was considerably lower

• Smith: the first transaction at equilibrium occurred in the later part of the third repetition

• Thus neither experiment yielded results that corresponded to the predictions of the Walrasian tatonnement

• In fact neither was conducted as a Walrasian tatonnement (which is an important point to which I shall return later talk)


Chamberlin (1948), Figure 3


Smith (1962) Chart 1


Different Reactions to Results

• Two distinguished economists reacted to their results very differently

• Smith saw half full glass of water, and interpreted the results as first empirical evidence in favor of significant explanatory power of the simple demand-supply model

• Chamberlin saw the half empty part and set out to build a model to better explain the residual variation left unexplained by the simple demand-supply model (instantaneous demand/supply)

• Dominance of analytical (instead of abstraction) tendency helps propel experimental research towards examination of increasingly finer details


2. Incremental Research Designs

• A good part of our research (including experimental) is incremental, originating in proposals to – Capture some additional uncontrolled variation in the underlying

conditions to explain any deviation of data from theory– Gather data about some additional aspect of behavior, or additional

analysis of existing data– Measure sensitivity of behavior to some additional controlled variations

in underlying conditions• We make conjectures about how such data or analysis might help

explain some part of residual variation• Incremental work dominates graduate seminars focused on critique

and replication of extant work• Easy to think of additional observations, motivations, and

information conditions associated with individual participants to improve the fit between data and model

• Pursuit of incremental research designs comes naturally an easily, and dominates research (including experimental work)


Change in Models and Questions

• Both analytical logic and incremental pursuits change the model used

• Additional variables use up some degrees of freedom, but observations at micro-level are far more numerous than at macro-level

• Shift to micro level also changes the research question(s) being asked– “Why is the price equal x?” might be replaced by “why

did trader y bid z?”– This apparently innocuous change has major

consequences in experimental economics


3. Humans as Imperfect Intuitive Optimizers

• Well-known that, when acting by intuition alone, people are not very good at optimization, especially in unfamiliar tasks

• We can devise laboratory tasks in which, no matter how well we explain them, performance will be poor at first, much experience, even instruction, is necessary before they get better

• Apparently, cognition necessary for formulating and solving unfamiliar problems are no easier for lab subjects than for academics who take decades or centuries

• That it takes more than a paragraph or two of problem description for intelligent people to comprehend and solve a problem is common sense

• Learning takes time and effort, and is imperfect– Indeed, if we were not, a good part of our education (and us, the

teachers) would be unnecessary


Cognitive Sciences and “As-If” Assumption

• Assumption that agents optimize is the staple of economic modeling In building economic theory

• Questionable descriptive validity of the assumption (from cognitive sciences) is juxtaposed against its use in modeling– If the optimization assumption on part of individuals is

descriptively invalid, the equilibrium models based on the assumption must also be invalid—so goes the argument

• “As-if” assumption is a weak defense for theory• Widespread acceptance of this criticism of economic

theory is a third element in preoccupation of experimental economics with micro (individual) behavior


Dilemma of Social Sciences

• This increasing emphasis on study of individual behavior in experimental economics brings us to the middle of the dilemma of social sciences

• Shall we try to be human and social?

• Or shall we try to be a science?

• Can we be both? If so, how and to what extent?


Science: Eternal Laws• Identifying laws of nature valid everywhere and all the time• Essence: regularities of nature captured in known and

knowable relationships among observable elements (including stochastic elements)

• It helps understand, explain, and predict the phenomena of interest (mechanics, sound, light, electricity, magnets)

• If I know X, can I form a better idea of whether Y was, is or will be (compared to what is possible without knowing X)?

• Our knowledge of these laws has no effect on their validity• Objects of science have no free will

– A photon does not pause to enjoy the scenery– A marble rolling down the side of a bowl does not wonder about

how hot the oil at the bottom is


Humanities: Eternal Truths

• Humanities celebrate infinite variety of human behavior, but no laws of behavior

• In epics and literature: eternal verities, but no laws of behavior– Epics (Mahabharata, Iliad)

• Duryodhana, Yudhishtira, Arjuna– Literature (Dante’s Inferno, Shakespeare’s Hamlet)

• Human truths, questions, and tendencies repeated through history, but always with a new twist

• People choose in ways unpredictable on the basis of their circumstances

• Celebration of infinite variation in human nature• Each of us is unique, not subject to identifiable laws


Individual Behavior and the Dilemma of Social Sciences

• This shift towards micro-behavior confronts economics with a fundamental dilemma shared among the social sciences

• As a science, we seek general laws that apply everywhere at all time, emulating physics, chemistry and biology

• Perfecting the scope and power of general laws of human behavior also implies squeezing out the essence of humanity—our free will

• What does it mean to have a science of individual human behavior?


Free Will

• Free will, independent thinking, and ability to choose are essential to our concept of self

• We believe in our power and ability to do what we wish, beyond what is predictable on the basis of our circumstances, beliefs, and tendencies

• Ability to rise above our circumstances as the essence of human identity

• We can choose deliberately, in ways unpredictable to others

• Else, we would slip to the status we assign to animals, plants and stones


Social Science: Irresistible Force Meets Immovable Object

• Free will essential to our concept of self• Without the freedom to act, we would be

no different than a piece of rock• Yet, the object of study in social science is

us• As a science, it must look for eternal laws

that apply to all humanity at all times• But stripped of freedom to act, and subject

to such laws, there can be no humanity


Mismatch of Science and Personal Responsibility

• Objects of science can have no personal responsibility• They do not choose to do anything• They are merely driven by their circumstances, like a

piece of paper blown by gusts of wind, or a piece of rock rolling down the hill under force of gravity in the path of an oncoming car (will you “blame” the rock for the resulting damage)

• In social settings, when we link an abused childhood to growing up to be an abusive parent, we absolve the person for personal responsibility for such behavior

• Science and personal responsibility do not mix well


Social Science: Neither Fish Nor Fowl

• This problem of social science is exemplified in the continuing attempts to build a theory of choice

• From science end: axiomatization of human choice as a function of innate preferences. People choose what they prefer

• How do we know what they prefer? Look at what they choose

• The circularity between preferences and choice might be avoided if there were permanency and consistency in preference-choice relationship across diverse contexts


Choice Theory

• One could observe choice in one context, tentatively infer the preferences from these observations, and assuming consistent preferences, predict choice in other contexts

• Unfortunately, half-a-century of research has yielded little predictability of choice from inferred preferences across contexts (Friedman and Sunder 2004)

• Individual human behavior appears to be unmanageably rowdy for scientists to capture in a stable set of laws

• While humanists may not take delight at such disappointments, but they can hardly be surprised (if they pay any attention at all to our choice theory)


Back to the Dilemma of Social Sciences

• Do we abandon free will, personal responsibility, and special human identity; and treat humans like other objects of science?

• That is, drop the “social” and become a plain vanilla science

• Or, do we abandon the search for universal laws, embrace human free will and unending variation of behavior, and join the humanities

• Either way, there will be no social science left• Is there a way to keep “social” and “science”

together in social science?


Isolating Three Streams of Work• Perhaps there is no general solution to this dilemma• The dilemma does, however, point to the potential value of isolating

streams of work where it may be more or less of a problem• Significant parts of social sciences, and a large part of economics,

are concerned with aggregate level outcomes of socio-economic institutions

• Institutions are human artifacts, and they do not need to be ascribed intentionality or free will

• Characteristics of the institutions can be analyzed by methods of science without running into these dilemmas

• This will leave analysis of individual behavior in the territory between science and humanities

• Agent-based models (in economics and elsewhere) could serve the bridging function between aggregate and individual phenomena

• Let us consider these possibilities


Individual Behavior

• I do not have much to add on the most complex problem of examining individual behavior

• It seems that we shall continue to examine ourselves and our behavior using both humanities as well as science perspectives, without ever reconciling the two into a single logical structure

• There seems to be no way out, as far as I can see


Institutions• Experimental economics started out as investigation of aggregate

level outcomes of market institutions using human subjects• Attention has gradually shifted from aggregate outcomes to micro

behavior– Logic of analytical approach– Incremental research designs

• A third reason is that predictions of aggregate outcomes (equilibrium analysis) are typically made assuming optimization by individuals

• Cognitive psychology showed that individuals are not very good at optimization by intuition

• This mismatch between the optimization assumption actual behavior at individual level has given additional impetus to “micro-nization” of experimental economics

• Thanks to the development of experimental as well as agent-based methods, we can conduct the study of social-economic institutions using methods of science


Optimization and Equilibrium

• The standard approach of economic analysis has been to assume that individuals choose actions by optimizing given their preferences, information and opportunity sets

• Interaction of individual actions in the context of institutional rules yield outcomes (e.g., prices and allocations), of which equilibrium outcomes are of special interest

• Equilibrium predictions derived from assuming individual rationality could be suspect when such rationality assumption is not valid

• Agent-based simulations suggest that individual rationality may not necessary for attaining equilibria in the context of specific market institutions


Discovering Structural Properties of Market Institutions

• Double auctions with three kinds of agents• Agent traders randomly pick bids and asks

from a fixed support (0-200)• Human traders motivated by profit• Agent-traders randomly pick bids and asks

from a fixed support (0-200) subject to budget constraint

• Results of the constrain ZI traders close to the results obtained from human traders


What Makes the Difference


Why Equilibrium without Individual Optimization

• Why do the markets populated with simple budget-constrained random bid/ask strategies converge close to Walrasian prediction in price and allocative efficiency

• No memory, learning, adaptation, maximization, even bounded rationality

• Search for programming and system errors did not yield fruit

• Modeling and analysis supported simulation results


Inference

• Perhaps it is the structure, not behavior, that accounts for the first order magnitude of outcomes in competitive settings

• Computers and experiments with simple agents opened a new window into a previously inaccessible aspect of economics

• Ironically, it was not the celebrated optimization capability of computers that made it possible

• Instead, it was possible through deconstruction of human behavior– Isolating the market level consequences of simple or arbitrarily

chosen classes of individual behavior modeled as software agents


Optimization Principle• In physics: marbles and photons “behave” but are not attributed any

intention or purpose• Yet, optimization principle has proved to be an excellent guide to

how physical and biological systems as a whole behave– At multiple hierarchical levels--brain, ganglion, and individual cell—

physical placement of neural components appears consistent with a single, simple goal: minimize cost of connections among the components. The most dramatic instance of this "save wire" organizing principle is reported for adjacencies among ganglia in the nematode nervous system; among about 40,000,000 alternative layout orderings, the actual ganglion placement in fact requires the least total connection length. In addition, evidence supports a component placement optimization hypothesis for positioning of individual neurons in the nematode, and also for positioning of mammalian cortical areas.

– (Makes you wonder what went wrong with human design when you see all the biases and incompetence of human cognition.

– Could it be just the wrong benchmark?)• Questions about “forests” versus questions about “trees”


Optimization Principle Imported into Economics

• Humans and human systems as objects of economic analysis

• Conflict between mechanical application of optimization principle and our self-esteem (free will)

• Optimization principle became re-interpreted as a behavioral principle, shifting focus from aggregate to individual behavior

• Cognitive science: we are not good at optimizing• Combination of the two leads to the willingness among

economists to abandon the optimization principle


Dropping the “Infinite Faculties” Assumption

• Conlisk: – Empirical evidence in favor of bounded rationality– Empirical evidence on importance of bounded

rationality– Proven track record of bounded rationality models (in

explaining individual behavior)– Unconvincing logic of unbounded rationality

• All these reasons focus on the “trees” not “forest”


Seduction by Reductionism

• Past fifty years have been characterized by a powerful reductionist program in economics

• Robert Lucas and the New Classical school rapidly conquered the discipline of macroeconomics by integrating doctrine of rigorous microfoundations:– Individual substantive rationality– Intertemporal optimization with rational expectations– Representative agent to map individual to aggregate– Seeking penetrate deeper into microstructure to erect

theory of harder and safer ground


Unity of Science Movement

• While the “microfoundations” program remained inside economics, the Unity of Science movement (Neurath et al. 1955) was a power force in the first half of the twentieth century

• The grand vision of integrating all science into one• But all sciences must make assumptions about

phenomena at the level of details they do not wish to delve into

• Reluctance to make such assumptions leads to the infinite regress of Unity of Science movement that failed

• Unification and descriptive validity of all assumptions places unreasonable burden on science


Equilibrium and Simon• Simon understood the dangers of reductionism, though many who

claim to bear his legacy don’t• In the third edition of The Sciences of the Artificial he wrote:• “This skyhook-skyscraper construction of science from the roof

down to the yet un-constructed foundations was possible because the behavior of the system at each level depended on only a very approximate, simplified, abstracted characterization of the system at the level next beneath. This is lucky, else the safety of bridges and airplanes might depend on the correctness of the ‘Eightfold Way’ of looking at elementary particles.”

• Indeed, the powerful results of economic theory were derived from “a very approximate, simplified, abstracted characterization of the system at the level next beneath,”—the economic man so maligned, and its scientific purpose and role so misunderstood, by many who claim to be followers of Simon


Shaking the Free of Reduction

• The recent work suggests an idea opposite to the reductionist program

• The deeper we go into microstructure, we sink into the sandy grounds of heterogeneity, bounded rationality, and all sorts of behavioral vagaries

• Serious pursuit of methodological individualism and microfoundations is a one-way journey with no return ticket to meso- or macro-surface

• Rigorous microfoundations do not appear to be “serious” scientifically

• “Serious” microfoundations discovered through scientific investigation of human behavior are hardly susceptible to “rigorous” aggregation procedures


Whither Micro-foundations?

• Gode and Sunder (1993): some well-behaved properties that emerge at the macro-level of the economy need not have any counterpart at the micro-level. It is constraints and transactions technologies (i.e., institutions) no individual rationality, that give rise to well-behaved aggregative properties

• Combine with Sonnenschein-Mantel to conclude that individual substantive rationality is neither necessary nor sufficient to obtain well-behaved macro properties


Economics: Structural or Behavioral

• Economics can be usefully thought of as a behavioral science in the sense physicists study the “behavior” of marbles and photons

• Given the pride we take in attributing the endowment of free will to ourselves, this interpretation of behavior is a hard sell in social sciences

• To build on the achievements of theory, it may be better if we think of optimization in economics as a structural principle, Just as physicists (and many biologists) do


Division of Work into Three Streams

• At least the structural part of economics can be firmly rooted in the tradition of sciences, bypassing the free-will dilemma of social sciences

• Individual behavior is likely to remain as a shared domain of humanities and sciences

• Modeling specific behaviors as software agents in the context of specific economic institutions allows us to make conditional statements about the links between individual and aggregate level phenomena (as in the case of ZI agents and the great deal of other work in agent-based economics)

• There is hope for the “science” in “social science”, in studying the structure

• Richard Posner: “Try harder”• Source of power of science (and economics): KISS

A Visit to Farmers’ Market in Kochi

Thank You

Please send comments to

[email protected]

www.som.yale.edu/faculty/sunder

mailto:[email protected]

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