Economic Theory: Structural
Abstraction or Behavioral
Reduction
Shyam Sunder
Yale University
History of Political Economy Conference
Duke University, April 22-24, 2005
(c) 2005 Shyam Sunder, April 23,
2005
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Outline: Psychology and
Reductionist Doubts
• Physics, optimization as an organizing principle of nature
• Borrowed into economics, optimization was gradually
transformed from equilibrium abstraction into a
behavioral principle
• Cognitive psychology: humans are not good intuitive
optimizers: noisy, imprecise, learners
• A reductionist attitude to science expects derivation of
aggregate outcomes from descriptively valid individual
behavior; it is difficult, sometimes not possible
• The difficulty leads to doubts about the foundations of
economic theory
(c) 2005 Shyam Sunder, April 23,
2005
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Outline: Computers Yield New
Insights into Economics
• Computers seep into inaccessible parts of economics (Mirowski,
2002), transforming it in fundamental ways
• Discovery: the apparent mismatch between the cognitively bounded
biological man and its optimizing cousin of econ texts is not
necessarily a problem
• A good news-bad news story
• The Good news: Economists can have their cake and psychologists
eat it too
• The Bad news: Have to give up insistence on reducing economics
and psychology into a single science
• The unity of science movement disbanded some 60 years ago, but
is alive and thriving in behavioral economics
• Each science chooses its own level of abstraction; economic theory
chose one, just as psychologists choose another
• A great deal of science would be impossible if we insist on
integrating all adjacent disciplines into a single logical structure
(c) 2005 Shyam Sunder, April 23,
2005
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Computation and Economics
• Each discipline is shaped by its tools
• Role of mechanical and electronic
computers in shaping economics
• Computers may yet help shift the recent
excessive preoccupation of economics
with individual behavior, back to structural
analysis
(c) 2005 Shyam Sunder, April 23,
2005
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Computers and Demand
• Lowered cost of transactions
• Exploration of previously inaccessible possibilities
(computational chemistry and biology)
• Fixed cost of discovery allows products to stay in the
market beyond the life of the discovery-enabling
technology
• Speculative demand due to knowledge of demand with
new communication technology
• New uses of older products and services
• Life-style, migration and social organization-driven
demand changes
• Endogeneity of demand and technology
(c) 2005 Shyam Sunder, April 23,
2005
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Computation and Markets
• Technology has given both greater specificity as
well as greater ambiguity to definition of markets
– Specificity through the salience of hardware and
software used to operate them
– Ambiguity: when an investor in Boston buys a share
of stock of a firm with its headquarters in Cleveland,
from another investor in Tokyo through a broker who
lives in San Francisco and works for a Chicago
brokerage house, in London Stock Exchange, with its
hardware located in Frankfurt, software from
Bangalore, and regulatory supervision of EU in
Brussels, where is the market, and what is its extent?
(c) 2005 Shyam Sunder, April 23,
2005
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Computers Transforming Markets
• Organization and operation of markets
• As traders or traders’ assistants
• Science and engineering of markets
(c) 2005 Shyam Sunder, April 23,
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Organization and Operation
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Reliable bookkeeping
Flexibility and accessibility of control information
Clearing and settlement
Reporting and dissemination of information
Monitoring and regulation (insider trading)
Risk management
Input of information to the markets
Demand for integration, legislation
Reorganization of markets
(c) 2005 Shyam Sunder, April 23,
2005
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Computer as a Trader
• Computational decision aids are ubquitous
• Substitution: exciting and controversial
– Do human intelligence and world view define
the outer limits of what computers can “see”
and do?
– Memory and speed are important components
of intelligence. Computer programs for chess
are already as good as the best human
players. It is just a matter of time before …
(c) 2005 Shyam Sunder, April 23,
2005
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Tooling Up for Computational
Economics
• William Norris, Control Data, PLATO for
education and training in 1976
• Use of PLATO for economics experiments
• PCs arrive
• Modeling traders in order to
– Identify human algorithms from trading data
– Design new, better algorithms
– Replace paid subjects in econ experiments
• Economics and finance literature were of little
help
(c) 2005 Shyam Sunder, April 23,
2005
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Stock Market Crash of 1987
• Blame on program trading
• Proposal to teach a course on program
trading (with a background research
agenda)
• Getting the platform, software, coding
language and tools ready
• Market 2001 (turned out to be too
optimistic)
• Show some data
(c) 2005 Shyam Sunder, April 23,
2005
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What Makes the Difference
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Class Experience
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Teaching becomes learning
Efficiency as a measure of intellence
Code length and performance
Difficulties of identifying strategies from
code
– Not modular
• Does a superior strategy exist?
• Where is your strategy, Sir?
(c) 2005 Shyam Sunder, April 23,
2005
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This Makes No Sense
• Why did 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
• Intensive search for programming and system
errors did not yield fruit
• Modeling and analysis supported simulation
results
• Students versus ZI traders
(c) 2005 Shyam Sunder, April 23,
2005
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Our Inference
• Perhaps it is the structure, not behavior that
accounts for the first order magnitude of
outcomes in competitive settings
• Computers opened a new window into a
previously inaccessible aspect of economics
• Ironically, it was not through computers’
celebrated optimization capability
• Instead, through deconstruction of human
behavior
– Isolating the market level consequences of simple or
arbitrarily chosen classes of individual behavior
(c) 2005 Shyam Sunder, April 23,
2005
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Time Dimension of Demand
• Theory largely abstracts away from the time dimension of demand:
defined as quantity per unit of time, with discrete periodic market
clearing through auction
• The difficulties of this abstraction became clear when Chamberlin
(1948) and Smith (1962) tried to implement demand in lab and
realized the difficulties
• Most markets require price making with continual trading (no
discrete clearing)
• Should demand be interpreted as a steady rate of inflow of demand
(and supply) units into the market with the hope that it will reach a
(stochastic) steady state?
– What would be the characteristics of market behavior?
– Do the untraded (mostly extramarginal) units accumulate, or do they exit
the market? When?
•
(c) 2005 Shyam Sunder, April 23,
2005
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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” and questions about “trees”
(c) 2005 Shyam Sunder, April 23,
2005
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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 interpreted as a
behavioral principle, shifting focus from
aggregate to individual behavior
• Cognitive science: we are not good at optimizing
• Increasing willingness among economists to
abandon the optimization principle
(c) 2005 Shyam Sunder, April 23,
2005
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Dropping the “Infinite Faculties”
Assumption
• Conlisk:
– Empricial 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 reasons focus on the “trees” not “forest”
(c) 2005 Shyam Sunder, April 23,
2005
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Equilibrium and Simon
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Some time in 1993, Simon came to my office, we sat in front of my
computer and I showed him the pictures I showed you
His reaction: So, there is an answer after all! (to the apparent contradiction
between the discrepancy between cognitive man and its economic model).
He was preparing the third edition of The Sciences of the Artificial and
wrote:
“This skyhook-skyscraper construction of science from the roof down to the
yet unconstructed 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
(c) 2005 Shyam Sunder, April 23,
2005
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Economics: Behavioral or
Structural
• 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
(c) 2005 Shyam Sunder, April 23,
2005
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Thank You
Please send comments to
Shyam.sunder@yale.edu
(c) 2005 Shyam Sunder, April 23,
2005
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