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Rational Choice

CHOICE

1. Scarcity (income constraint)

2. Tastes (indifference map/utility

function)

ECONOMIC RATIONALITY

 The principal behavioral postulate is

that a decision-maker chooses its

most preferred alternative from those

available to it.

 The available choices constitute the

choice set.

 How is the most preferred bundle in

the choice set located/found?

RATIONAL CONSTRAINED CHOICE

x2





More preferred

bundles







Affordable

bundles

x1

RATIONAL CONSTRAINED CHOICE

x2









x2*







x1* x1

RATIONAL CONSTRAINED CHOICE

x2 (x1*,x2*) is the most

preferred affordable

bundle.





x2* E







x1* x1

RATIONAL CONSTRAINED CHOICE

At Equilibrium E



MRS=x2/x1 = p1/p2





Slope of the Slope of the budget

indifference curve constraint





Individual’s Society’s willingness

willingness to trade to trade

RATIONAL CONSTRAINED CHOICE



 The most preferred affordable bundle

is called the consumer’s ORDINARY

DEMAND at the given prices and

income.

 Ordinary demands will be denoted by

x1*(p1,p2,m) and x2*(p1,p2,m).

RATIONAL CONSTRAINED CHOICE

x2

The slope of the

indifference curve at

(x1*,x2*) equals the

slope of the budget

constraint.

x2*







x1* x1

RATIONAL CONSTRAINED CHOICE

(x1*,x2*) satisfies two conditions:

 (i) the budget is exhausted, i.e.

p1x1* + p2x2* = m; and

 (ii) the slope of the budget constraint,

(-) p1/p2, and the slope of the

indifference curve containing (x1*,x2*)

are equal at (x1*,x2*).

COMPUTING DEMAND

 How can this information be used

to locate (x1*,x2*) for given p1, p2

and m?

 Two ways to do this

1. Use Lagrange multiplier method

2. Find MRS and substitute into the

Budget Constraint

COMPUTING DEMAND

Lagrange Multiplier Method

Suppose that the consumer has Cobb-

Douglas preferences

a 1 a

U ( x1 , x2 )  x x

1 2





and a budget constraint given by



p1 x1  p2 x2  m

COMPUTING DEMAND

Lagrange Multiplier Method

Aim

a 1 a 

max x1 x2 subject to p1 x1  p2 x2  m



Set up the Lagrangian



L a 

 x1 x 21  a    m  p1 x1  p2 x 2 

 x1 , x 2 ,  

COMPUTING DEMAND

Lagrange Multiplier Method

Differentiate



L 

 ax1 1 x21 a   p1  0

a

(1)

x1

L a 

 (1  a ) x1 x2 a   p2  0 (2)

x2

L

 m  p1 x1  p2 x2  0 (3)



COMPUTING DEMAND

Lagrange Multiplier Method

From (1) and (2)

 

ax1a-1  x21 a  1  a x1 x2 a

a 

λ 

p1 p2



Then re-arranging

p1 ax2



p2 1  a x1

COMPUTING DEMAND

Lagrange Multiplier Method

Rearrange

ap2 x2

p1 x1 

1  a 

Remember





p1 x1  p2 x2  m

COMPUTING DEMAND

Lagrange Multiplier Method

Substitute

ap2 x2

p1 x1 

1  a 





p1 x1  p2 x2  m

COMPUTING DEMAND

Lagrange Multiplier Method

Solve x1* and x2*



am

*

x1 

and p1



*

x2 

1  a m

p2

COMPUTING DEMAND

Method 2



Suppose that the consumer has

Cobb-Douglas preferences.





a

U( x1 , x 2 )  x1 xb

2

COMPUTING DEMAND

Method 2

that the consumer has

 Suppose

Cobb-Douglas preferences.

a

U( x1 , x 2 )  x1 xb

2

U

MU1   ax1  1xb

a

2

 x1

U

MU2   bx1 xb 1

a

2

 x2

COMPUTING DEMAND

Method 2

 So the MRS is



a1 b

dx 2  U/ x1 ax1 x 2 ax 2

MRS     .

dx1  U/ x 2 a b 1 bx1

bx1 x 2

COMPUTING DEMAND

Method 2

 So the MRS is



a1 b

dx 2  U/ x1 ax1 x 2 ax 2

MRS     .

dx1  U/ x 2 a b 1 bx1

bx1 x 2



 At (x1*,x2*), MRS = -p1/p2 , i.e. the

slope of the budget constraint.

COMPUTING DEMAND

Method 2

 So the MRS is



a1 b

dx 2  U/ x1 ax1 x 2 ax 2

MRS     .

dx1  U/ x 2 bx1 xb 1

a

2

bx1



 At (x1*,x2*), MRS = -p1/p2 so

ax* p1 * bp1 *

 

2  x2  x1 . (A)

* p2 ap2

bx1

COMPUTING DEMAND

Method 2

 (x1*,x2*) also exhausts the budget so

* *

p1x1  p2x 2  m. (B)

COMPUTING DEMAND

Method 2

 So now we know that

* bp1 *

x2  x1 (A)

ap2

p1x*  p2x*  m.

1 2 (B)

COMPUTING DEMAND

Method 2

So now we know that

* bp1 *

x2  x1 (A)

ap2

Substitute

p1x*  p2x*  m.

1 2 (B)

COMPUTING DEMAND

Method 2

So now we know that

* bp1 *

x2  x1 (A)

ap2

Substitute

p1x*  p2x*  m.

1 2 (B)

and get

* bp1 *

p1x1  p2 x1  m.

ap2

This simplifies to ….

COMPUTING DEMAND

Method 2

am

x* 

1 .

( a  b)p1

COMPUTING DEMAND

Method 2

am



*

x1

(a  b) p1

Substituting for x1* in

p1x*  p2x*  m

1 2

then gives

bm

*

x2 

(a  b) p2

COMPUTING DEMAND

Method 2

So we have discovered that the most

preferred affordable bundle for a consumer

with Cobb-Douglas preferences

a

U( x1 , x 2 )  x1 xb

2



is

( x1 , x2 ) 

* *

( am

,

bm

(a  b) p1 (a  b) p2

)

COMPUTING DEMAND

Method 2: Cobb-Douglas

x2 a

U( x1 , x 2 )  x1 xb

2





*

x2 

bm

( a  b )p 2







am x1

x* 

1

( a  b)p1

Rational Constrained Choice

 But what if x1* = 0 or x2* = 0?

 If either x1* = 0 or x2* = 0 then the

ordinary demand (x1*,x2*) is at a

corner solution to the problem of

maximizing utility subject to a budget

constraint.

Examples of Corner Solutions:

Perfect Substitutes

x2

MRS = -1









x1

Examples of Corner Solutions:

Perfect Substitutes

x2

MRS = -1







Slope = -p1/p2 with p1 > p2.





x1

Examples of Corner Solutions:

Perfect Substitutes

x2

MRS = -1







Slope = -p1/p2 with p1 > p2.





x1

Examples of Corner Solutions:

Perfect Substitutes

x2

MRS = -1 (This is the indifference

m curve)

x 

*

2

p2





Slope = -p1/p2 with p1 > p2.





x*  0 x1

1

Examples of Corner Solutions:

Perfect Substitutes

x2 ANOTHER

MRS = -1 EXAMPLE







Slope = -p1/p2 with p1 p2.

 2 

Examples of Corner Solutions:

Perfect Substitutes

x2

m MRS = -1

p2 Slope = -p1/p2 with p1 = p2.



The budget

constraint and

the utility curve

lie on each other



m x1

p1

Examples of Corner Solutions:

Perfect Substitutes

x2

y All the bundles in the

p2 constraint are equally the

most preferred affordable

when p1 = p2.







y x1

p1

Examples of ‘Kinky’ Solutions:

Perfect Complements

X2 (gin) U(x1,x2) = min(ax1,x2)







x2 = ax1 (a = .5)







X1 (tonic)

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)









x2 = ax1

MRS = 0





x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)



MRS = - 



x2 = ax1

MRS = 0





x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)



MRS = - 

MRS is undefined

x2 = ax1

MRS = 0





x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)









x2 = ax1







x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)



Which is the most

preferred affordable bundle?



x2 = ax1







x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)



The most preferred

affordable bundle



x2 = ax1







x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)









x2 = ax1

x2*



x1* x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)

and p1x1* + p2x2* = m





x2 = ax1

x2*



x1* x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)

(a) p1x1* + p2x2* = m

(b) x2* = ax1*



x2 = ax1

x2*



x1* x1

Examples of ‘Kinky’ Solutions:

Perfect Complements

(a) p1x1* + p2x2* = m; (b) x2* = ax1*

Examples of ‘Kinky’ Solutions:

Perfect Complements

(a) p1x1* + p2x2* = m; (b) x2* = ax1*.

Substitution from (b) for x2* in

(a) gives p1x1* + p2ax1* = m

Examples of ‘Kinky’ Solutions:

Perfect Complements

(a) p1x1* + p2x2* = m; (b) x2* = ax1*.

Substitution from (b) for x2* in

(a) gives p1x1* + p2ax1* = m

which gives m

x1 

*

p1  ap2

Examples of ‘Kinky’ Solutions:

Perfect Complements

(a) p1x1* + p2x2* = m; (b) x2* = ax1*.

Substitution from (b) for x2* in

(a) gives p1x1* + p2ax1* = m

which gives

m am

*

x1  ; x2 

*

p1  ap2 p1  ap2

Examples of ‘Kinky’ Solutions:

Perfect Complements

(a) p1x1* + p2x2* = m; (b) x2* = ax1*.

Substitution from (b) for x2* in

(a) gives p1x1* + p2ax1* = m

which gives m am

x1 

*

; x2 

*

p1  ap2 p1  ap2

Examples of ‘Kinky’ Solutions:

Perfect Complements

x2 U(x1,x2) = min(ax1,x2)







*

x2  x2 = ax1

am

p1  ap 2

m

x* 

1 x1

p1  ap2



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