Content uploaded by Yaseen Othman
Author content
All content in this area was uploaded by Yaseen Othman on Feb 27, 2023
Content may be subject to copyright.
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
http://jaes.tu.edu.iq
Tikrit Journal of Administration
and Economics Sciences
ISSN: 1813-1719 (Print)
Estimating the Demand Function of Private Cars in Kurdistan
region of Iraq-Erbil Governorate as a Model
Assist. Prof. Dr. Yaseen O. Abdulaah
Prof. Dr. Saber Perdaood Othman
Collage of Administration and Economics
Collage of Administration and Economics
Salahadin University/Erbil
Salahadin University/Erbil
yaseen.abdulaah@su.edu.krd
saber.othman@su.edu.krd
Assist. Lecturer: Himdad Amin Abubakr
Collage of Administration and Economics
Salahadin University/Erbil
himdad.abubakr@su.edu.krd
Abstract:
Transportation has a major role in economic activities and a vital role in human
life. This study has focused on the factors that affected the demand on chauffeur
services in order to provide quantitative indicators such as income elasticity of demand
on cars and others in indicators. Thus, this study helps individuals to make decisions
which are related to demand on cars, such as import policies, taxes and fees imposed on
cars, and their repercussions that help decision makers to be guided by these indicator.
This study aimed to estimate the function of demand for chauffeur services in
Erbil governorate and to estimate the income elasticity of demand for chauffeur
services. The study has approached standard models as a quantitative method and
applied the SPSS program, and the study collected data for (714) families in Erbil
governorate during 2015
Eventually, the study concluded that most of the explanatory variables included
in the model have a significant effect on car ownership and that the demand for cars
increases with the increase in the number of family members
Keywords: demand for the car, logistic model, family income.
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
SPSS
714
Logistic regressionBinary
1
0
t
0.211
21
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Deductive
Inductive
SPSS 20
714
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
yQualitative
Binary
Gujarati & Porter, 2009, 542-543
LPMLogitProbitTobit
2 , 1 = inX
Y1y0ui
1, 1
= =
E
1, 2Gujarati, 2009, 553-543
OLS1, 2
Gujarati, 2009, 553-543
uiOLS
uiOLS
yipredicted
10
LPM
XX
XY
Gujarati & Porter, 2009, 549-553
1, 4
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
X
0
1
Gujarati & Porter, 2009, 553-554
LogitProbit
Logit Model
PiXi
Xiii
1, 5
1, 6
Cumulative Logistic Distribution-Function
01
X
1, 5
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
1, 5
1, 7
1, 51, 8
6-2-2
Odds Ratio
1, 10
1, 11LX
L
LogitLogit
1, 11Gujarati & Porter, 2009, 553-554
Studenmund and Johnson, 2017, 66-68
Y=1Y=0
m
N
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
NW
NL
R1
0
H1
0
Ratio N18
Cirillo, 2010
AgeEkains, 2013, 22Scasny & Urban, 2011, 559
G 1
0Scasny and Urban, 2011, 559Ekains, 2013, 22
EDrebee, et al., 2012, 23
1, 11
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
LRM ML 1, 12
Logit
Odds
Ln OddsM
10000.487
GRH
10
Intercept
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
AgeNW
OddsOdd ratio
Age
2530
NW
Odds
Anti Ln1, 10
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Odds
Multiplecative
Xi
Odds
1000Odds
1.627
Odds
NWAgeOdds
e
G
RH
Odds1
0 1
Odds Ratio: OR
OddsOdds Ratio
OROdds
ORORe
OR
1000OR1.627
1000
160
AgeNW OR
Odds
Odds
Ratio NOdds
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
OR
OddsOR
1, 5
1, 13
714
5535537140.775
1000
0.0848.4
77.58.477.585.9
1000
0.002
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
0.2
1
2, 1
2, 2 0.084
0.775
1.93
2, 3
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
SPSS V.20
Waldt
WaldHoshmer & Lemshow, 2003, 16
i
WZW
poston, 2004W Z
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
X1, N1
10
Wald R A
Ratio N
Wald
Likelihood ratio
poston, 2004
i1
H0
154.882
101
121.666
-2LL
Y
Y
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Chi-Square
154.882
10
0.000
SPSS V.20
Homser Lemsho
H0H1
Hosmer & Lemshow, 2000, 137-149
H
g-2g
g
nn/gH
g-2
H0
yx
6.937
80.0515.51
0.05
Chi-Square
6.937
8
0.543
SPSS V.20
binary
pseudo Mc Fadden
Gujarati and Porter, 2009, 563
0.0
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
11
Greens, 2018, 561Sicosovo, etc; 2019, 86
Mc Fadden, 1974
H0:
H1:
0.20
20
R-2 OLS
LRM R-2
Gujarati & Porter, 2009, 206
178-Goldberger, 1991, 177
0.30
0.90Kunts, 2001, 107Wooldrige, 2003, 200 & p370
Pseudo
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
ML
residualerror term
LPM
LPM LPM
Multicolinearity
VIF 3.615 5
VIF
Autocorrelation
D-W 5
10
200 dl=1.665
du=1.874 D-W 1.94
20du4-du2.126D-W1.874
Gujarati, 2008, 419
Studenmund, 2017, 282
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Wald
Wald
Wald
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
OddsOdds ratio
Journal, Periodical, Thesis and Books:
1. Cirillo, Cinza, (2010), Automobile Ownership model, University of Maryland, USA.
2. Drebee, Hayder Abas . Abdulrazak, Nor Azan & Abd Karim, Mohd Zaini, (2012), The Impact
of Household Characteristics on Automobile Choice in Malaysia:An Application of The
Multinomial Logit Model, Utra University, Malaysia. IJER, Vol.9, No.1, pp17-33.
3. Ekains, John, (2013), the Determinants of Household Car Ownership: Empirical Evidence from
the Irish Household Budget Survey, University of Surrey, UK.
4. Goldberger, Arthur S., (1991), "A Course in Econometrics", Harvard University Press,
Cambridge, Massachusetts. Cited in (Gujaratti, 2009, 123-124)
5. Gujaratti, Damodar Porter, Dawn C, (2008), Basic Econometrics 5th ed., McGraw-Hill
companies, New York, USA.
6. Hosmer, Daivd W & Lemeshow, Stanley (2000), Applied Logistic Regresson, Second Edition,
John Wiley & Sons, Inc, USA.
7. Kunst, Robert M., (2011), "Introductory Econometrics, University of Vienna and Institute for
Advanced Studies", Vienna,robert.kunst@univie.ac.at.
8. Scasny, Milan & Urban, Jan, (2011), Passenger Car Ownership in Czech Republic, International
Days of Statistics & Economics, Prague, September 2011.
9. Studenmund, A. H. (2006), Using Econometrics: A practical Guide, 5thed., Pearson
International Edition, Addison Wesley Longman, Inc.
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
10. Train, Kenneth, (1989), Qualitative Choice Analysis, Theory, Econometrics, and an Application
to Automobile Demand, Cambridge, Massachusetts, Landon.
11. Wooldridge, Jeffery M., (2013), "Inroductory Econometrics: A modern Approach", 4th ed.,
South-Western, Cengage Learning, Mason, USA.
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34
Tikrit Journal of Administration and Economics Sciences, (31/12/2021);Vol. 17, No. 56, Part (2): 573-595
Doi: www.doi.org/10.25130/tjaes.17.56.2.34