Time Series & Panel Data Models Using STATA Software
provided in Arabic Language
What you will learn
Identify and conduct Diagnostic tests of the regression model
Detect Structural Breaks in Time Series
Check Stationary of Time Series Models (Unit root test)
Estimate Vector Autoregressive (VAR) Models & Granger causality test
Estimate Cointegration & Vector Error Correction Models
Estimate Panel Data Models (Fixed effects & Random-effects & Dynamic Panel data models)
Why take this course?
This training course includes these training sessions:
Session (1):Introduction & Diagnostic tests of the regression model
This session includes:
introduction to STATA software
import data from excel file
descriptive statistics·
Assumptions of OLS regression.
Checking Linearity.
Model Specification: omitted variables.
Serial correlation.
Heteroskedasticity.
Multicollinearity.
Normality of the error term.
Session (2): Structural Breaks in Time Series
This session includes:
What are structural break models?
Types of a structural break.
How to detect structural breaks?
Known Breakpoints
Unknown Structural Breaks.
Session (3): Stationary of Time Series Models
This session includes:
Stationary & Non-Stationary time series.
Types of Non-Stationary time series.
Methods to check the stationarity of time series.
Autocorrelation Function (ACF) plot.
Unit root tests: Augmented Dickey-Fuller (ADF) Test & Phillips-perron test.
Unit root test for Panel Data.
Session (4): Vector Autoregressive (VAR) Models & Granger causality test
This session includes:
Vector autoregressive (VAR) model.
Choosing optimal lag length in the VAR model.
Stability of the VAR model.
Testing for Residual Autocorrelation.
The Granger causality test.
Impulse response functions (IRFs).
Session (5): Cointegration test and Error Correction Model
This session includes:
The concept of co-integration.
Engle-Granger co-integration.
Error Correction Model (ECT).
Johansen- Juselius cointegration analysis.
Vector Error Correction Model (VECM).
Autoregressive Distributed Lag (ARDL) model
Diagnostics tests (Goodness of fits).
Session (6): Panel Data Models
This session includes:
The concept of Panel Data.
Descriptive statistics of Panel Data.
Panel Unit Root Test.
Fixed effects & Random effects models.
Dynamic Panel data models:
Arellano and Bond (1991) estimator (difference GMM estimator)
Arellano and Bover (1995) (System GMM estimator)
Panel ARDL Model.
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