Theoretical REsearch in Neuroeconomic Decision-making
Neuroeconomic Theory:
Using Neuroscience to Understand
the Bounds of Rationality
Juan D. Carrillo
USC and CEPR
Workshop – Biology and Economics (June 2011)
Neuroeconomic Theory
Use evidence from neuroscience, neurobiology and neuroeconomics to
revisit economic theories of decision-making
Neuroscience evidence
Existence of multiple
systems in the brain
Limited interactions
Hierarchical structure
Conflicting objectives …
in flow of information
Physiological
constraints
in processing capacity
in memory …
Neuroeconomic Theory
Revisit theories of decision-making
no!
Behavioral anomaly (“output”)
Model of
bounded rationality
yes
Obtain
“micro-microfoundations”
Brain architecture (“input”)
Processes taken for granted
(learning, information processing, etc.)
Characteristics traditionally exogenous
(discounting, risk-aversion, etc.)
Neuroeconomic Theory
Organizations (pre-theory of the firm): f(k,l)
Individual (pre-neuroeconomics): U(x,y)
The brain is, so it should be modeled as,
a multi-system organization
Model 1 (Brocas-Carrillo, AER 2008)
• Intertemporal choice: 2 dates of consumption / labor (c1 , n1 ) and (c2 , n2 )
• Utility
“Principal” P
cortical system
[1u(c1 )  n1 ]  [2u(c2 )  n2 ]
“Agent 1” A1
limbic system at date 1
1u(c1 )  n1
“Agent 2” A2
limbic system at date 2
 2u(c2 )  n2
where θt is valuation at date t known only by At
Intertemporal budget constraint:
c1 (1  r )  c2  n1 (1  r )  n2
At chooses his preferred pair … but P can restrain At ’s choices, and
we allow any rule / restriction
Model 1 (Brocas-Carrillo, AER 2008)
Optimal consumption / labor rule (under asymmetric information):
• Consumption at t depends on labor at t
 current consumption tracks earned income
• Informational conflict
 endogenous emergence of time-preference rate
 Positive ( (t+1) < (t) )
 Decreasing impatience ( (t+1) / (t) > (t) / (t-1) )
Model 2 (Brocas-Carrillo, AER 2008)
• “Incentive salience”
- One system mediates motivation to seek pleasure (wanting)
- A different system mediates the feeling of pleasure (liking)
Principal P
Agent A
 u (c )  n
  u (c )  n
•  > 1: A is tempted to over-consume (biased motivation)
• P does not integrate A’s “salience”
• P can impose any choice but θ is known only by A
Model 2 (Brocas-Carrillo, AER 2008)
Optimal consumption rule (under asymmetric information):
•
•
P imposes only two constraints: consumption cap and budget balance
A chooses:
- If θ < θ* : unconstrained optimal pair given his bias
- If θ > θ* : same pair as an agent with valuation θ*
 Rationale for simple rule: “do what you want but don’t abuse”
 Stronger bias ()  tighter control ()
Model 3 (Alonso-Brocas-Carrillo, mimeo 2011)
• CES allocates resources {x0, x1, x2} to A0, A1, A2
CES
central executive system
x0  x1  x2  k
U 0  U1  U 2
x0
A0
(lifting)
U 0 ( x0 , 0 )  
1
0
( x0   0 ) 2
x1
x2
A1
(rotation)
U1 ( x1 ,1 )  
1
1
( x1  1 ) 2
A2
(spelling)
U 2 ( x2 ,  2 )  
1
2
( x2   2 ) 2
Motor function
Cognitive functions 1 and 2
0 “public info.”
1 and 2 “private info.”
Model 3 (Alonso-Brocas-Carrillo, mimeo 2011)
Optimal allocation to each system (under asymmetric information):
•
•
P imposes a cap to Ai (weakly) decreasing in j
 Each system has minimum guaranteed resources
 Better performance in easy tasks than in difficult tasks
Task inertia: conditional on present needs, allocation of Ai is higher if
past needs were high.
Conclusions
• The brain is a multi-system organization.
• It is time to open the black box of decision-making processes:
- Neuroscience brings the knowledge
- Microeconomics brings the tools
• Bounded rationality models based not on inspiration but on physiological
constraints  derive behaviors from brain limitations