Exploring Market Structures with Zero-Intelligence Agents

1
Exploring Market Structures with
Zero-Intelligence Agents

• Shyam Sunder, Yale University
• Eighth Trento Summer School
• Intensive Course in Agent-Based Finance
• July 5-6, 2007

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

3
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

4
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

5
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

6
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.

7
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 Chamberlins goals, asking subjects to
  report their transactions immediately after they
  completed each transaction served his purposes
  well, causing little interference with subjects
  trading

8
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

9
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

10
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

11
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 analysisbreaking
  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

12
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 Chamberlins nor Smiths 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)

13
Chamberlin (1948), Figure 3
14
Smith (1962) Chart 1
15
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

16
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)

17
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

18
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

19
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 invalidso 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

20
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?

21
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

22
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 (Dantes Inferno, Shakespeares
  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

23
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 humanityour free will
• What does it mean to have a science of individual
  human behavior?

24
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

25
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

26
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

27
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

28
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)

29
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?

30
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

31
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

32
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

33
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

34
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

35
Double Auctions with Intelligent Automatons

• Still converged to CE
• Greater variance in prices
• Many more bids/asks per transaction

36
Double Auctions with Zero-Intelligence
Automatons

• Random bids and asks
• No loss constraint internal or external
• Markets converge to CE
• Much greater variability in prices
• How could this be?
• Some algebra and statistics produce the same
  results

37
What Makes the Difference
38
Other Simulations

• Double auctions with uncertain reservation values
  and imperfect information (Jamal and Sunder)
• Multimple interlinked markets (Bosch and Sunder)
• Non-binding price controls (Gode and Sunder)
• Edgeworth Box (Gode, Spear and Sunder)

39
Bosch and Sunder (Computational Economics, 2000)
40
(No Transcript)
41
Non-Binding Price Controls
42
Figure 3 Demand and Supply  
 
43
Figure 1 Results from Laboratory Experiments
with Human Subjects (Figure 1. Experiment 226
from Smith and Williams, 1981)  
44
Figure 2 Results from Laboratory Experiments
with Human Subjects Figure 3 from Smith and
Williams (1981)
45
Table 4 Summary Statistics (100 periods for each
column)
46
Figure 4 Histograms of Transaction Price
Distributions
47
Figure 5 Intraperiod Mean of Transaction Price
Series
48
Figure 6 Intraperiod Median and Interquartile
Range of Transaction Price Series
49
Edgeworth Box

• Simulation

50
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

51
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

52
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 cellphysical 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

53
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

54
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

55
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

56
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

57
Equilibrium and Simon

• Simon understood the dangers of reductionism,
  though many who claim to bear his legacy dont
• 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

58
Shaking 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

59
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

60
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

61
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

62
A Visit to Farmers Market in Kochi
63
Thank You

• Please send comments to
• Shyam.sunder_at_yale.edu
• www.som.yale.edu/faculty/sunder