# INTRODUCTION TO MATHEMATICS ECONOMICS 1, Exercises for Economics

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DIFFERENTIATION MADE EASY FOR ALL ECONOMICS STUDENTS IN SECOND SEMESTER COURSE
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Introductory Mathematics for Economics MSc’s

INTRODUCTORY MATHEMATICS FOR ECONOMICS MSC’S. LECTURE 1: DIFFRENTIATION.

HUW DAVID DIXON

SEPTEMBER 2009.

1.1

1. Some Definitions.

 An Integer: A positive or negative whole number, as in “counting. -3,-2,-1,0,1,2,3

 A rational number: the ratio of two integers. 11 2,

23 3 

 An irrational number: cannot be represented as the ratio of two integers. E.g. 2, …..  Real Numbers and the Real line : the set of all rational and irrational numbers. This is a “continuum”:

o ={x:- < x<}=(-,) o + ={x:0 < x < }=[0,)

o Open interval: includes end-points. (0,1) means strictly greater than 0 and strictly less than 1 o Closed interval: includes end-points. [0,1].

o Half open interval: includes one of endpoints, but not the other. [0,1) includes 0, but not 1.

 In economics, use real numbers most of the time: x might be output, price, advertising

expenditure etc. This is an approximation (cannot set a price ), but as in physics, seems to work well.

1.2

2. Functions f.

 takes a real number (input) and transforms it into another real number (output).

 y = f(x). You take a real number input x and it is mapped onto output y.

 f(x): y=2+(3.x) x y=f(x)

-10 -28 10 32 1.2 5.6

 f(x): y=x2 x y=f(x)

-10 100 10 100 1.2 1.44

 A function is 1-1 if each input has a unique output, and each output has a unique input. If

we look above, y=x2 is not 1-1. the output 100 can be generated by two values of x: +10 and -10.

1.3

y=2+3x is monotonic: it is always strictly increasing and y gets larger as x gets larger. It is also 1-1. Each value of y is associated with one value of x and vice versa. y=x2 is non-monotonic. For x<0 y is decreasing in x; for x>0 it is increasing in x. it is not 1-1: for each value of y 0 there are two values of x which generate it, the positive and negative square roots. y=2+3x is invertible: we can write y as a function of x and x as a function of y:

2y 3 3

x  

1.4

Demand curve: 1X P  X=output/quantity: P=price Inverse Demand curve: 1P X  Revenue Function: 2. .(1 )R X P X X X X    

In Economics, we usually deal with the inverse demand curve, and treat price as a function of Quantity (Alfred Marshall, British economist in late C19th) That is why price is on the vertical axis!

1.5

3. Differentiation made simple. Differentiation was invented by Sir Isaac Newton, the great British 17th Century Physicist (Principia Mathematica). If you take a function and differentiate it, you get the SLOPE of the function.

the change in y is called y , the change in x is x . The ratio of the changes is y x  

The derivative is the ratio y x  

as x becomes very small.

For example: 2y x at x=1, y=1. As x becomes very small, the ratio is 2.dy dx

xyy x  

1 (x changes from 1 to 2) 3 (1 to 4) 3 0.1 (x changes from 1 to 1.1) 0.21 (1 to 1.21) 2.1 0.01 (1 to 1.01) 0.0201 (1 to 1.0201) 2.01 0.001 0.002001 (1 to 1.002001) 2.001

This is also called the tangent or slope of the function

1.6

At the point y=1, x=1 the green line is 2y x . The red line is the tangent at that point (1,1) which has the slope 2.dy

dx

1.7

The Rules of Differentiation: Rule 1: Power rule.

1

n

n

y ax dy anx dx

Examples: 4

2

5

8 9

; ' 2 3 ; ' 15 2 ; ' 16

y x f x y x f x y x f x 

 

 

  

Note: notation 'dy f dx

Rule 2: Natural Logarithm.

ln

1 y ax dy dx x

Example

ln 3 1

y x dy dx x

Rule 3: Exponential Function.

ax

ax

y e dy ae dx

Example

; ' ; '

x x

x x

y e f e y e f e   

  

1.8

These are the basic rules used in economics: we do not need to use trigonometric functions (sin, cosine etc) except for very specialised uses. We then combine Rules 1-3 with further rules: these deal with differentiation of combinations of two functions f(x) and g(x). The aim is to take a complex expression (equation) and break it down into simpler parts f and g. Rules 1-3 can be used to differentiate f and g themselves, Rule 4: Product rule.

( ). ( )

'. '.

y f x g x dy f g g f dx

 

Examples: (a)

This is the function.

We break it up into two simple functions

We apply rules 1 and 3 to the simple functions

We then apply the product rule 4 to the two simple functions

2

2

2

( ) ; ' ( ) ; '

' '

2 [2 ]

x

x x x

y x e f x x f g x e g

dy f g dx

xe e x xe x

2 e

g f

x x x 

  

 

 

 

   

1.9

(b)

we know the answer here: but the product rule gives us the same answer as the rule 1: it shows the rules are consistent!

4

3 2

3 2 3 3 3

4 ( ) 4 ; ' 4 ( ) ; ' 3

' ' 4 4 .3 4 12 16

y x f x x f g x x g x dy f g g f x x x x x x dx

  

 

      

(c)

1

1

ln ( ) ; ' 1 ( ) ln ; '

' ' ln . ln 1

y x x f x x f g x x g x dy f g g f x x x x dx

  

 

     

1.10

Rule 5: Function of a function (Chain rule) This is a widely used rule: you break down the expression so that there are two or more stages.

( ); ( )

. '. '

y f z z g x dy dy dz f g dx dz dx

 

 

Examples: (a)

2

ln ln

1 22

y x y z z x dy dy dz x dx dz dx z x

 

  

Break it down into two expressions we know how to differentiate

Apply the rule

1.11

2

2

2

2 2

x

z

z x

y e y e z x dy dy dz e x xe dx dz dx

  

(b) (c) reciprocals

2

1 2

2 4

3

1

; 2.2

2

y x

y z z x dy dy dz xz x dx dz dx x

x

 

    

 

1.12

2

2

( )

2

( )

( )

2 2 ( )

ax b

z

z x a

y e y e z w w ax b

dy dy dz dw e wa e a ax b dx dz dw dx

  

   

(e) exponential The last rule is actually implied by the previous two rules, but we state it for convenience! Rule 6: quotient rule.

2

( ) ( ) . ' . '

u xy v x

dy v u u v dx v

 

1.13

For example: 2

2

2 2

2

2 2 2

2 4

2 3

3 ; ' 2

3 ; ' 6 . ' . ' 6 6

9 2( 1)

3

x

x x

x x

x

ey x

u e u e v x v x

dy v u u v x e xe dx v x

xe x

 

 

   

 

To summarise: You take function. You use rules 4-6 to break down the expression into simple parts that you can differentiate using rules 1-3.

1.14

4 Economics applications. (a) Revenue and marginal revenue.

( ) ( ) . ( )

'

'(1 )

11

P P x R x x P x

dR xP P dx

xPP P

P

 

 

 

     

The inverse demand curve: (Price depends on output). Revenue: price times output: MR: differentiate using produce rule Rearrange, using elasticity formula

1 '

P P dx x P x dP

    

Let us look at some particular demand curves: these are ones you will see used in economics often!

1.15

Linear Demand. The Demand curve:

( ) ( ) .( )

' ( )

2 .

x a P P x a x R x x a x

dR xP P x a x dx

a x

     

     

 

a is the “intercept” term. It is the price when output is zero. Note that marginal revenue always has a slope that is twice that of the linear demand curve. Take the example of a=3.

What happens to the elasticity along the linear demand curve?

1.16

;

( )

P a x P dx x dP

a x x

 

 

 

As output increases, the elasticity increases;

2 2

( ) 0d x a x a dx x x        

If x=0 (P=a), =. If x=a (P=0) =0.

1.17

Demand curve 2: constant elasticity of demand.

Direct demand

1

1.

x aP

xP a P dx P a P x dP aP

   

 

     

   

Inverse Demand Elasticity.

If =1, then we have a rectangular hyperbola: P.x=a.

1.18

The Yellow line represents the unit elastic demand curve. Total expenditure P.X is constant. The red line represents an elastic demand curve: revenue is decreasing with price. The green line represents an inelastic demand curve: revenue is increasing with price.

1.19

Revenue: output times price Revenue as a function of output. Marginal Revenue: zero if =1 (yellow line), strictly positive if >1 (red line) and strictly negative if <1 (green line).

1

1 11

1 1

( ) .

1

xR x x a

a x

MR a x

 

  

     

     

Cost functions. C(x) Total cost of producing output x. For example:

2( ) . 2 cC x F x 

F: overhead cost, does not depend on output.

c is marginal cost (MC): dC c dx

1.20

Average Cost:

Average cost is total output divided by output. The Change in AC as output increases (slope of AC). AC is decreasing if MC<AC; increasing if MC>AC,

2

( )( )

' 1 '

1 ( )

C xAC x x

dAC xC C CC dx x x x

MC AC x

       

 

For example, take the previous cost function with F=2, c=1

2

2

1( ) 2 . 2

2 1 2

2 1 2

C x x

MC x

AC x x

dAC dx x

 

 

  

And MC>AC MC<AC MC=AC

2

1 12 4

2 0

2 0

2 0

dAC dx x

dACx dx

dACx dx

dACx dx

    

  

  

  

1.21

Thus “efficient” least cost production occurs when AC=MC.

1.22

Concavity and Convexity. The second derivative of a differentiable function is obtained by differentiating the first derivate:

y=f(x): the first derivative is written as 'f , the second derivative as ''f

2

2

2 2

22 2

d y d dy dx dx dx

dy d yy x x dx dx

     

    

A function is strictly concave if for all x 2

2 '' d y f dx  <0.

This means that the slope of the function is decreasing (becoming less positive, more negative). Example: The quadratic function

2

' 2 '' 2 0

y A x f x f

      

1.23

The red line is the quadratic 22y x  ; the green line is the first derivative ' 2f x  . This is decreasing in x '' 2 0f    . A concave function has the following shape: if it is increasing in x, the slope is becoming less steep as x increases (see x<0 above); if it is decreasing in x, the slope becomes more negative (steeper – see x>0 above). A concave function is like an upside down bow or Hill….

1.24

A function is strictly convex if the slope (derivative) is increasing in x. Take the quadratic

2

' 2 '' 2 0

y A x f x f

    

The green line is the quadratic (A=-2): the red the first derivative. A convex function is like a bowl. Note that the negative of a concave function is convex: if f(x) is strictly convex, then –f(x) is strictly concave and vice versa.

1.25