In this post I will be explaining how to run the Simple Linear Regression (Ordinary Least Square) to create the model using Eviews 7.0. Eviews is especially strong in analysis of time series data so for the purpose of elaborating the process we will be using the time series data of the GTI and Remittance of Pakistan for last thirty years from 1981 to 2010.
The process starts by opening a new file of Eviews. Here are the steps:
1. Open the new Eviews File.
2. Specify the time period from 1981 to 2010.
3. Now specify the variables, rem for remittance and gti for grand total investment. Write data rem gti in the space provided for this purpose.
4. This will make a table that will have space for the two variables, now copy and paste the data from excel sheet to this table.
5. Now go to Quick, Equation Estimate and write the expression defining the relation between the two variables. Write: gti c rem
6. Press ok to run the test. The results are viewed in a separate window. So here are the results:
Interpretation of Results:
The equation can be formed using the coefficients. In our case it will be GTI = 1008870 – 66900.59 REM.
Prob. Value explains that percentage of error in the coefficients, C has 0.56% error while REM has 27.36% error. R-Squared value states that our model is explained 4% by this equation (this is really undesirable; we need this value to be 50%+ range). F-Statics explains the combined effect of two variables and Prob (F-Statistic) states there are 27% chances of error in this estimate. Durbin Watson stat explains the autocorrelation exists on at 0.09; we can use LM Test to further confirm its existence.
Overall the model is poorly explained by the regression line, in such a case we either need to add more independent variables that explain further the relationship or take data for a longer time period to examine the relation. This was all about the post. You can download the sample files and try at your end.
Download EViews Sample File from here.
The process starts by opening a new file of Eviews. Here are the steps:
1. Open the new Eviews File.
2. Specify the time period from 1981 to 2010.
3. Now specify the variables, rem for remittance and gti for grand total investment. Write data rem gti in the space provided for this purpose.
4. This will make a table that will have space for the two variables, now copy and paste the data from excel sheet to this table.
5. Now go to Quick, Equation Estimate and write the expression defining the relation between the two variables. Write: gti c rem
6. Press ok to run the test. The results are viewed in a separate window. So here are the results:
RESULTS
Dependent
Variable: GTI
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Method:
Least Squares
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Date:
01/08/14 Time: 11:39
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Sample:
1981 2010
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Included
observations: 30
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Variable
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Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
C
|
1008870.
|
335774.6
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3.004605
|
0.0056
|
REM
|
-66900.59
|
59901.53
|
-1.116843
|
0.2736
|
R-squared
|
0.042648
|
Mean dependent var
|
665670.2
|
|
Adjusted
R-squared
|
0.008457
|
S.D. dependent var
|
744393.0
|
|
S.E. of regression
|
741238.7
|
Akaike info criterion
|
29.93437
|
|
Sum
squared resid
|
1.54E+13
|
Schwarz criterion
|
30.02779
|
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Log
likelihood
|
-447.0156
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Hannan-Quinn criter.
|
29.96426
|
|
F-statistic
|
1.247338
|
Durbin-Watson stat
|
0.095653
|
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Prob(F-statistic)
|
0.273554
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The equation can be formed using the coefficients. In our case it will be GTI = 1008870 – 66900.59 REM.
Prob. Value explains that percentage of error in the coefficients, C has 0.56% error while REM has 27.36% error. R-Squared value states that our model is explained 4% by this equation (this is really undesirable; we need this value to be 50%+ range). F-Statics explains the combined effect of two variables and Prob (F-Statistic) states there are 27% chances of error in this estimate. Durbin Watson stat explains the autocorrelation exists on at 0.09; we can use LM Test to further confirm its existence.
Overall the model is poorly explained by the regression line, in such a case we either need to add more independent variables that explain further the relationship or take data for a longer time period to examine the relation. This was all about the post. You can download the sample files and try at your end.
Download EViews Sample File from here.
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