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Lesson 4: Derivatives, Apuntes de Administración de Empresas

Asignatura: corporate mathematics, Profesor: Clement Kanyida-Malu Kabiena, Carrera: Business Administration and Management, Universidad: URJC

Tipo: Apuntes

2017/2018

Subido el 09/01/2018

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LESSON 4. DERIVATIVES
Mathematics – 2011/201 2- 1 -
LESSON 4
DERIVATIVES
1. Rate of change and the derivative.
Let us suppose that we are interested in the rate of change of any variable y in response
to a change in another variable x, where the two variables are related by the function,
i.e. y=f(x).
The variable y could be for example, the equilibrium value of an endogenous
variable, and x a parameter.
The difference quotient:
When a variable x changes from x
0
to x
1
, the change us measured by the
difference x
1
-x
0
. Let denote this change by
01
xxx =
.
When x changes from an initial value x
0
to a new variable
xxx +=
01
the value of the
function y=f(x) changes from f(x
0
) to
)(
0
xxf +
. The change in y per unit of change in x
can be defined by the difference quotient.
x
xfxxf
x
y
+
=
)()(
00
This quotient which measures the average rate of change of y, can be calculated if we
know the initial value of x, or x0 and the magnitude of change in x, or Dx.
Example: Given y=f(x)=3x
2
-4, we can write
4)(3)(4)(3)(
2
00
2
00
+=+= xxxxfxxf
.
Therefore:
xx
x
xxx
x
xxx
x
y+=
+
=
+
=
36
)(36)43(4)(3
0
2
0
2
0
2
0
If we know x0 and Dx, we can evaluate this quotient difference.
Definition
Frequently, we interested in the rate change of y when Dx is very small. In this case, it
possible to obtain an approximation of Dy/Dx by dropping all the terms in the difference
quotient involving the expression Dx.
If Dx approaches zero in the above example, we can write:
00
00
6)36(
limlim
xxx
x
y
xx
=+=
pf3
pf4
pf5

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LESSON 4

DERIVATIVES

1. Rate of change and the derivative.

Let us suppose that we are interested in the rate of change of any variable y in response

to a change in another variable x, where the two variables are related by the function,

i.e. y=f(x).

The variable y could be for example, the equilibrium value of an endogenous

variable, and x a parameter.

The difference quotient:

When a variable x changes from x 0 to x 1 , the change us measured by the

difference x 1 -x 0. Let denote this change by ∆ x = x 1 − x 0.

When x changes from an initial value x 0 to a new variable x 1 = x 0 +∆ x the value of the

function y=f(x) changes from f(x 0 ) to f ( x 0 + ∆ x ). The change in y per unit of change in x

can be defined by the difference quotient.

x

f x x f x

x

y

This quotient which measures the average rate of change of y, can be calculated if we

know the initial value of x, or x0 and the magnitude of change in x, or Dx.

Example: Given y=f(x)=3x

2

-4, we can write

2 0 0

2

f x 0 = x 0 − f x +∆ x = x +∆ x −.

Therefore:

x x x

x x x

x

x x x

x

y = + ∆ ∆

0

2 0

2 0

2 0

If we know x0 and Dx, we can evaluate this quotient difference.

Definition

Frequently, we interested in the rate change of y when Dx is very small. In this case, it

possible to obtain an approximation of Dy/Dx by dropping all the terms in the difference

quotient involving the expression Dx.

If Dx approaches zero in the above example, we can write:

0 0 0 0

lim lim(^6 x^3 x )^6 x

x

y

x x

∆→ ∆ →

Using this notation, we can define the derivative of a given function y=f(x) as follows:

x

y f x dx

dy

x

∆→

lim 0

Example: y=3x

2

-4, we get for example: x

dx

dy = 6

Derivative with respect to a vector.

Let us define a derivative of f with respect to a vector v at x 0 as

λ

( ) lim 0 0 0 0

f x v f x fv x

We consider all the canonical directions

e 1 = ( 1 , 0 , 0 ,K 0 ); e 2 =( 0 , 1 , 0 ,K, 0 ); e 3 =( 0 , 0 , 1 ,K, 0 );K; en =( 0 , 0 , 0 ,K, 1 ),

so ( )

f (^) ei x 0

is called as i- th partial derivative and it can be written as

xi

f

Example

2 f x 1 x 2 x 3 = x 1 + xx +

→ λ

λ

λ

λ

λ

λ

λ

2 1

2 2 3 1

2 2 3 1

2 1 1 0 1

lim

f x e f x x x x x xx x x

x

f

1 0 1

2 1 2 2

x x

x = +  →

λ→

3

2 3 3

2 2 3 1

2 2 1 0 2

lim x

f x e f x x x x x x x x

x

f = =

λ

So, in the same way 2

3

x x

f

2 1 1 2 1

2 2 : 2 x y

f xy x

f f f x y = ∂

1 1 (^1 ,^1 )

ln( )

2

2 2 2 Jf

y

x

x

xy

Jf y y

f

x x

f f xy

Properties of the gradient

1. fv ′^ ( x 0 )=∇ f ( x 0 )⋅ v

2. The gradient vector shows the greatest increasing direction at point x 0.

Example

f ( x , y )= xe v =( 1 , 2 )

y

  • Try to get ( 1 , 1 ) ( , )

y y f (^) vf = e xe

f ( 1 , 1 )=( e , e )

fv ′ ( 1 , 1 )=( e , e )⋅( 1 , 2 )= e ⋅ 1 + e ⋅ 2 = 3 e

  • Which is the greatest increasing direction at ( 0 , 0 )?

0 0 ∇ f = e e

Remark

Every partial derivative

xi

f

is a function : ℜ →ℜ,

∂ (^) n

xi

f

. Therefore, it is possible to

calculate the second partial derivatives of

xi

f

, i.e.,

xi xj

f

2

Example

f x y = x y + x yx

2 4 3 ( , )

Try to work out the second partial derivatives

4 2 2 3 3 2 3 1 4 x y x y

f xy x y x

f = + ∂

y xy x

f

x x

f 2 6

4 2

2 = +  

2 2 2

2 12 x y y

f

y y

f

 

2 3 2 8 3

f f xy x y x y x

2 3 2 8 3

f f xy x x y x y

Definition

We call Hessian matrix the second partial derivatives’ matrix of f

2

2

2

1

2

2

2 1

2

2 1

2

n

n i

n

i j

x

f

x x

f

x x

f

x x

f

x x

f

x

f

Hf

2. Economic applications

In economic analysis we can distinguish four main measures, and each one of them has

a mathematical expression:

a) Total value: y = f ( x 1 ,..., xn )it expresses the value of a magnitude (y) at each point

of its domain.

Example: the demand of a good in terms of its price can be expressed by:

2 d = − pp

b) Mean value: the mean value of y with respect to the xi variable is the division of y

into xi

y = f ( x 1 ,..., xn )

i

m x x

f x Y x i

There are as many mean value functions as the parameters:

p

p dM

2 100 −

= represents the slope of a straight line which links the origin point to

the point ( p , d ( p ))

c) Marginal value: It is defined as

lim 0

x x

f x e f x f

i

i

λ

It can be interpreted as the increase of a function

f ( x 1 ,..., xn )when there is an infinitesimal change in the xi variable keeping

constant all the other variables. d ′=− 2 p