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“Efect o Education on Income”

Course: Applied Economics

Supervised by:

  Dr. Faisal Mehmood

Submitted by:

  UsmanAhmad !"#$!%"!%$'

  Syed Musa (a)a !"#$!%"!%*

  Momna +arve) !"#$!%"!"%'

  ,ahra Sha-i !"#$!%"!#%'

  Memmona /-ti0har !"#$!%"!!1'

  A)0a !!#!!%"!!2'

Semester 3S *th

Department o- Economics

University o- 4u5rat

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Efect o Education on Income

Introduction:

 The returns to education may be higher for individuals with higher abilities,

since they tend to attain more years of schooling as it is more convenient forthem. We investigate the eect of education on income in this paper. There

are ve variables used in this paper monthly income which is measured by

Rs. And it used as dependent variable and independent variables are

monthly expenditure which is also measured by Rs, edu. Which is measured

by the year of schooling and there are two dummy variable gender in which

assign for male and ! for female and profession which is assigned by to "

which indicates dierent professions and use the primary data for the

research. The ob#ective of the paper to investigate the eect of education on

income by using the primary data which collected from $! dierentindividuals and estimated by %&'

 There are four dummy models are estimated in this paper. All models showed

dierent results which relates to the theory but model $ shows the spurious

result and model ( is the best model which shows the signicant results.

Results and Dissection:

Model 1:

)onthly income * +-..!!!!+"montheltexpen./0"-.$$0

experience/00+.!$0- education.

1n the rst model results shows that the average monthly income is

+-Rs. when all other variables are 2ero. And results suggest that when

there is one percent increase in expenditure will lead to decrease monthly

income by .!!!!+"Rs. And when experience increased by year will

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increase the monthly income by 0"-.$$Rs. And when there is increase in

education by one year it will increase the income by 00+.!$Rs.

Results reveal that monthly expenditure has negative and signicant

relationship with monthly income, experience and education has positive

and signicant relationship with income.

Model 2

1n model- we introduce one dummy variable which is gender categories in

two category for male and ! for female and education is dependent

variables and dependent variable is also same as per model

)onthly income * +--"".+3/ +$.-+ edu/ -0!".$0 gender

 The value of intercept is +--"".+3 which indicate that the average monthly

income is +--"".+3Rs when all other variables are 2ero mean 2ero

experience and 2ero year of education.

 The interpretation of other variable is almost same which showed in model.

4ummy variable shows that the average wage of male is -0!".$0Rs is

greater than female. 5ducation has positive and signicant relationship with

income and gander has also positive but insignicant relationship with

income.

Model3

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1n model( introduce edummy variable which is the combination of edu and

gender. 1t has positive relationship with income.

Model4

)onthly income *+++$3/.!!!"+! month expen/0-+.3- experience

!"0.0" edu(!($$.( gender/(.$- edummy

Results reveal of this model that monthly expenditure and experience haspositive and signicant relationship and education and gender has

negative insignicant relationship with income. )odel $ shows the

spurious results which are against the theory.

Comparison or Model 1 2 3 4:

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  1n all models dependent variable is same 6monthly income7.in model

independent variables are monthly expenditures, education and experience.

1n model - education and gender are independent variable. 1n model (

edummy6gender/eucation7 is independent variable and in model $ all

independent variables of model ,-8( are included.

)odel ( is the best tted model which shows the signicant results and has

probability !.(3 which mean it has signicant relationship with income and R

s9uare of this model is !.- which is very less.

Conclusion:

 The purpose of this paper to investigates the eect of education on income

by using primary data which collected from $! individuals and estimated by

%&'. There are ve variable used in this paper in which there are two dummy

variable gender and profession. There are four dierent dummy models are

estimated while model $ shows the spurious results All variable shows

positive and signicant relationship with income except expenditure which

has signicant but negative relationship with income and dummy variable

shows that the average monthly income of male is greater the female. )odel

( is the best which have signicant relationship with income it has .(3

probability which indicates signicant relation of the independent variables

with income.

:

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