Course in Econometric Analysis of Data Sets

Introduction to Econometric Analysis

• Definition of econometric analysis.
• Basic principles in economic analysis.
• The difference between quantitative and qualitative economic analysis.

Statistical Foundations of Econometric Analysis

• Differences between independent and dependent variables.
• The role of statistical models in economic analysis.
• Basics of simple and multiple linear regression.

Economic Data Analysis Using Analytical Software

• Introduction to software used in economic analysis (such as EViews, SPSS).
• How to input and clean economic data.
• Creating simple economic models using statistical programs.

Advanced Regression Models in Econometric Analysis

• Multiple regression and its use in economics.
• Handling non-linear variables.
• Analyzing dummy variables in economic models.

Hypothesis Testing and Model Validation

• Basic hypotheses in econometric analysis.
• Testing for normal distribution of data.
• Model validity assessment using F-tests and t-tests.

Dealing with Multicollinearity and Heteroscedasticity in Economic Models

• Identifying multicollinearity and how to address it.
• Handling heteroscedasticity (non-homogeneous error variance).
• Advanced techniques for improving model accuracy.

Time Series Analysis and Sequential Data

• Introduction to time-series data and its importance in economic analysis.
• Using time-series regression for economic data analysis.
• Testing for stationarity in time-series data.

Advanced Time Series Regression Models

• Autoregressive (AR) and Moving Average (MA) models.
• The Autoregressive Integrated Moving Average (ARIMA) model and its economic applications.
• Cross-sectional data analysis with time integration.

Analysis Using Error Correction Models (ECM)

• Understanding Error Correction Models and their use in economic analysis.
• Differentiating between short-term and long-term models.
• Interpreting results in Error Correction Models.

Structural Models and Economic Forecasting Techniques

• Using structural models to analyze relationships between economic variables.
• Economic forecasting techniques using econometric models.
• Assessing the accuracy of economic forecasts.

Quantitative Analysis of Financial Markets

• Studying the relationship between asset prices and economic factors.
• Value at Risk (VaR) models in financial market analysis.
• Using regression to measure economic risks.