Economics Book
Economics and Finance Lecture
Cointegration
Test Model One
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Cointegration
Test - Model Two
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Regression
Model Three
Residual
Analysis
Regression
Model Four
Stability Test
Regression
Model One
Model building
Unit Root
Testing.
Model One
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Part 2
Part 1 + Part 2
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Removal of
Heteroscedasticity.
Model One
Model One
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Removal of
Serial
Correlation
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Part 2
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Regression
Model Two
Part 1
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Part 3
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Conversion of a
variable into
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Best
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Model. Model
One
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What is F
statistics?
F statistics
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What is R
square in
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R square
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Optimal lag
selection
Model One
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Optimal lag
selection
Model Two
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Error Correction
Model
Model One
Part 1
Part 2
Part 3
Part 4
Part 5
Part 1 to Part 5
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Data conversion
to Normal.
Model One
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Granger
Causality Model
One
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Part 2
Part to Part 2
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Impulse
response
function in
Unrestricted VAR
Model One
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Part 2
Part 1 + Part 2
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Impulse
response
function in
Restricted VAR
(VECM) : Model
Two
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Part 2
Part 1+  Part 2
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Dummy Variable
in VECM.
Model One
Part 1
Part 2
Part 3
Part 4
Part 1 to 4
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Transmission
Channel in
VECM.
Model One
Part 1
Part 2
Part 3
Part 4
Part 5
Part 1 to 5
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Lag selection in
VAR using LR,
AIC, SC and HQ.
Model One
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General to Specific
Model. Model One
Part 1
Part 2
Part 3
Part 4
Part 5
Part 6
Part 1 to Part 6
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Johansen long
run co-integration
equation.
Model One
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Growth Model.
Model One
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Part 2
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Import and Open
Economy using
dummy variable
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Part 2
Part 1 to Part 2
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We take one period lag
residual from Johansen
long run  Co-integrating
equation and use  
it as error correction
term in ECM Model
Multicollinearity
and Regression
Part 1
Part 2
Part 3
Part 1 to Part 3
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Granger
Causality
Model Two
Part 1
Part 2
Part 3
Part 1 to 3
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Cointegration
Test Model Three
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Q Statistics and
LM Test for
Serial correlation
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Part 2
Part 1 + Part 2
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Static
forecasting
Model One
Part 1
Part 2
Part 3
Part 1 to 3
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Dynamic
forecasting
Model Two
Part 1
Part 2
Part 3
Part 4
Part 5
Part 1 to 5
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Static forecasting
Model Three
Part 1
Part 2
Part 3
Part 4
Part 1 to 4
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Impact of
Financial Crisis
on Economy
Model One
Part 1
Part 2
Part 3
Part 4
Part 5
Part 1 to Part 5
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EVIEWS Applications
Why digital economy
is important ?
Regression
Model Three
Model Three
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SPSS Applications
Pearson
Correlation
Model One
Part 1
Part 2
Part 3
Part 1 to 3
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Paired Sample T
Test. Compare
Means.
Model One
Part 1
Part 2
Part 1 to  Part 2
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Paired Sample T
Test. Compare
Means.
Model Two
Part 1
Part 2
Part 1 to Part 2
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Pearson
Correlation
Model Two
Part 1
Part 2
Part 3
Part 1 to 3
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Pearson
Correlation
Model Three
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Part 2
Part 1 to 2
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Pearson
Correlation
Model Four
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Part 2
Part 1 to 2
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Unit Root
Testing.
Model Two
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Part 2
Part 1 + Part 2
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Anova analysis
Manova analysis
T-Test
Error Correction
Model
Model Two
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Part 2
Part 3
Part 1 to Part 3
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Shor run Long
Run Causality.
Model One
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Part 2
Part 3
Part 4
Part 1 to Part 4
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Short run Long
Run Causality.
Model Two
Part 1
Part 2
Part 3
Part 4
Part 1 to Part 4
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Shor run
Causality.
Model Three
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Part 2
Part 3
Part 4
Part 1 to Part 4
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Residual from
Johansen
Cointegartion.
Model One
Model One
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Comparison of
ARCH, GARCH,
EGARCH and
TARCH model.
Model One
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Part 2
Part 3
Part 1 to 3
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Adam Smith
John Maynard Keynes
Milton Friedman
AMOS Applications
LINDO and LINGO Applications
Introduction to
Strucrural
Equation
Introduction
Stock Portfoio
Model. Model One
Model One
Structural
equation model.
Model One
Model One
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Structural
equation model.
Model Two
Model Two
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Agriculture
Portfoio Model.
Model Two
Model Two
Quadratic and
MOTAD
programming.
Model Three
Model Three
Covariance analysis
Path analysis
GIF
Quadratic programming
Minimum variance
Portfolio management
Introduction to EVIEWS
Lag selection
Unit root testing - ADF Test
Cointegration Test
Granger causality
Error correction model
Impulse response function
Forecasting
Unrestricted VAR
Various applications
ARCH, GARCH, EGARCH, TARCH, ARCH-M, PARCH
General to specific model
Transmission Channel among variables
Leverage effect
in the TARCH
model. Model
One
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Part 2
Part 3
Part 1 to 3
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Leverage effect
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One
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Part 3
Part 1 to 3
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Single equation regression model
T - Test
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GARCH(2,0)
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Model Two
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Part 1 to Part 2
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Best
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Model.
Model Two
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Lag variable
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Econometrics Modules
Regression
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Module One
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Multicollinearity in the Regression
Multicollinearity in
the Regression
Line. Model One
Part 1
Part 2
Part 3
Part 1 to  Part 3
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Normality of Residual in the regression
Normality of
residual in the
regression. Model
One
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Part 3
Part 1 to  Part 3
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Introduction to thesis/disseration writing
Introduction to
thesis/dissertation
writing
Model One
Model Two
Thesis/dissertaion Writing
Transmission
channel among
variables. Model
Two
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Part 3
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Serial correlation in the regression
Serial correlation
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Model One
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Microeconomics
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Economics and Finance Essays
Serial Correlation
Data mangement
Multicollinearity
Heteroscedasticity
Vector Error Correction Model : Causal analysis.
Best regression model
Y = Bx + E
Relationship
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R square and F
Statistics. Model
One
Model One
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Detection of Serial
Correlation in
Autoregressive
Model. Model two
Model Two
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Conversion of a
variable into
stationary.
Model Two
Model Two
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Removal of
Heteroscedasticity.
Model Two
Model Two
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Regression
Model Two
Model Two
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We take one period lag
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long run  Co-integrating
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