Higher Technological Institute Construct an Econometric Model Statistics Questions

King Saud University
College of Business Administration
Department of Economics
Following guidelines to be adopted for the first assignment on Classical Liner Regression Model
(CLRM):
PART 1: Estimating CLRM
1) Construct an econometric model i.e., classical liner regression model (one dependent
variable and at least 3 independent variables). The relationship among the variables
must be supported by the theory. Any topic can be selected from the areas of economics,
finance and business.
Example: Yt = B0 + B1X1+ B2X2 + B3X3 + Et
2) Estimate the equation (Using OLS Method and Eviews Software)
3) Evaluate the model (R2 and F statistics)
PART 2: Hypothesis Testing
1) Hypothesis testing (individual coefficient test using P values or t-statistics)
2) Testing Joint significance based on F statistics
3) Restricted Test using F-statistics (using Wald Test in Eviews)
Part: 3 Diagnostic Testing
1) Detections and remedies of the following violation of the assumptions under Classical
Regression Model:
a) Heteroscedasticity and its remedies. Heteroscedasticity Test.
b) Testing for Autocorrelation and its remedies. Durbin-Watson Test & Breusch –
Godfrey LM Test
c) Testing for non-normality and its remedies. Normality Test using Jarque- Berastatistic
d) Testing for Multicolinearity and its remedies. Using Correlation Matrix and VIF
(Variance Inflation Factors)
e) Testing for Misspecification and its remedies: Ramsey RESET
f) Chow test or a parameter stability test and its remedies.
Part 4: Inference/Forecasting
1) Interpret the result.
Note:
i) You can obtain data from World Bank database to run the Classical Liner Regression Model
(CLRM). ( https://databank.worldbank.org/source/world-development-indicators# )
ii) Attached are the two sample paper which could be supportive to follow the above guidelines
(part 1-part 4)
iii) Each part carries some weightages, so exclusion any of the above (part 1-part 4) will cause
deduction of the point respectively.
Submission: 5th February, 2023 (By 12pm)
**Late submission for this take-home midterm exam paper will not be accepted for
any reason. I would suggest you to submit your exam paper as early as could possible
to confirm my acknowledgement.
Data Source
Last Updated Date
World Development Indicators
12/22/2022
Country Name
Saudi Arabia
Saudi Arabia
Country Code
SAU
SAU
Indicator Name
Oil rents (% of GDP)
Electric power consumption (kWh per capita)
Indicator Code
NY.GDP.PETR.RT.ZS
EG.USE.ELEC.KH.PC
1971
1972
34.1438218 39.1399509
308.754978 340.409205
1973
1974
1975
1976
1977
1978
1979
46.6040056
70.142846 55.7183178 54.2663044 54.0169195 45.8117117 87.1843145
392.734524 473.574819 502.054816 681.887351 786.045443 1044.88715 1522.30913
1980
1981
1982
1983
1984
1985
1986
71.1820409 55.9532391 35.3507971
33.670178 32.5668625
26.347707
22.680567
1878.05197 2170.77561 2604.99945 2723.13516 3079.27607 3124.92121 3478.43848
1987
1988
1989
1990
1991
1992
1993
27.8743945 26.7246932 34.5422411 47.1329836 32.4128546 33.6203632 32.1797623
3748.74076
3847.7706 3938.19488 4075.22436 4151.30625 4397.80457 4723.00923
1994
1995
1996
1997
1998
1999
2000
28.6133003 29.6460548 33.2368717 29.2233611 20.6607808
26.657333 41.1395814
4794.65718 4864.71998 4871.18166 4991.42934 5287.26716
5394.9469 5432.67653
2001
2002
2003
2004
2005
2006
2007
33.163749 31.0836894
36.769969 42.1153903 51.5429904 51.2529369 47.5069102
5709.42703 5830.59631 6306.37834 6210.34538
6457.3858 6604.29652 6622.89961
2008
2009
2010
2011
2012
2013
2014
54.4482807 34.2978033
38.957475 50.7764398 48.3847017 45.1807426 40.4257798
6796.86557 6990.53571 7435.04447 7514.49084 8043.07559 8385.61159 9047.68551