The Presentation is about one of the data type used in research known as time series data and the basic and simplest test of co integration Engle Granger

1. TIME SERIES DATAAND ENGEL
GRANGER TEST
Presenters:
Momina Ejaz
Noor Ul Ain

2. TABLE OFCONTENTS
• Introduction of Time Series
• Model
• Table
• Time Series Estimation
• Problem of Auto correlation
• Purpose of Time Series
• Engel Granger Test

3. INTRODUCTION
• Definition:
A Time series is a collection of observations made sequentially in
time.
‘’ Time series may be defined as a collection of readings
belonging to different time periods, of some economic variables or
composite of variables.’’
• Example:
 GDP of Pakistan for last for last 30 years
 Exchange rate
 Interest rate
 Inflation rate
 Electric power consumption

4. MODEL
• Model:
𝐺𝐷𝑃𝑡 = 𝛽0 +𝛽1 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝑡 + 𝛽2 𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡𝑡 + 𝛽3
𝐸𝑥𝑝𝑜𝑟𝑡𝑠𝑡+ 𝛽4 𝐼𝑚𝑝𝑜𝑟𝑡𝑠 𝑡 + 𝜇 𝑡
Whereas; t subscript shows data is ‘time series’

5. TABLE
Dependent Variable: GDP
Method: Least Squares
Date: 12/13/17 Time: 00:15
Sample: 2003 2016
Included observations: 14
Variable Coefficient Std. Error t-Statistic Prob.
C 1.13E+11 3.19E+10 3.550477 0.0040
DEBT 26.71708 13.00680 2.054086 0.0624
R-squared 0.360139 Mean dependent var 1.78E+11
Adjusted R-squared 0.338484 S.D. dependent var 2.83E+10
S.E. of regression 2.53E+10 Akaike info criterion 50.88032
Sum squared resid 7.70E+21 Schwarz criterion 50.97161
Log likelihood -354.1622 Hannan-Quinn criter. 50.87187
F-statistic 4.219270 Durbin-Watson stat 1.507381
Prob(F-statistic) 0.062420

6. TIME SERIES ESTIMATION
• We estimate time series data through following tests:
• Unit Root test is used to check the stationary of the variables.
 Augmented Dickey filler test
 Phillip Peron Test
• If probability values from these two tests come significant than the data is
stationary in nature.
• If data is stationary we use OLS.
• If data is not stationary we use Co integration.
• Co integration: ‘’A stationary relationship between non stationary variables’’
• Co integration have further 3 tests :
 Engle Granger
 Johnson Test
 ARDL Test

7. Problem ofAutocorrelation
• Problem of Autocorrelation exists in case of Time Series Data .
• Autocorrelation : “Correlation between the elements of a series
and others from the same series separated from them by a given
interval.”
• Durbin Watson Test is used to detect Autocorrelation.

8. PURPOSE OFTIME SERIES
• To identify the components, the net effects of whose
interactions is exhibited by the movement of a time series.
• To study, analyze and measure them independently i.e, holding
the other things constant.

9. ENGELGRANGERTEST
• Residual based test for co integration one of the most popular tests for a
single co integration has been suggested by Engle and Granger in1987.
• If there are two variables we use Engle Granger test for co Integration that
one variable is Dependent and other is Independent variable.
• This test is specifically designed for 1 Dependent and 1 Independent
variable.
• Both variables should be non stationary.
• Model:
• 𝐺𝐷𝑃𝑡 = 𝛽0 + 𝛽1 𝐸𝑥𝑝𝑜𝑟𝑡𝑠 𝑡 + 𝜇 𝑡
• For GDP t and Exports t to be co integrated, µt must be I (0).
• Otherwise, it is spurious. Thus, a basic idea behind is to test whether µt is I
(0) and I (1).
• I (0) - Stationary
• I (1) – Non Stationary.

10. THANK YOU !