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  • Faculty of Economics
  • Economics (English)
  • Course Structure Diagram with Credits
  • Econometrics I
  • Learning Outcomes
  • Description
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  • Explain the Foundations of Econometrics
  • Define econometrics and explain the three disciplines on which econometrics is built
  • Summarize the methodology of econometrics and explain the steps of an econometric analysis
  • Evaluate the structure of economic data and explain main types of data that can be used in economic analysis
  • Identify the difference between causality and correlation
  • Explain Regression Analysis and Model Estimation
  • Recognize the role of an econometric model in economics
  • Differentiate between model, data, parameter and variable expressions of population and sample data
  • Differentiate and explain the properties, assumptions, and statistics of population and sample regression using OLS estimator formulas
  • Recognize that OLS estimators are random variables
  • Explain the goodness of fit measures
  • Calculate the OLS estimators
  • Develop and Estimate Multiple Regression Models using Ordinary Least Squares (OLS)
  • Explain the concept of a multiple regression model
  • Interpret the coefficients in a multiple regression model
  • Estimate the coefficients in a multiple regression model
  • Assess the adequacy of a multiple regression model
  • Explain Inference for Regression Analysis
  • Perform t-test to examine the significance of individual regression parameters
  • Calculate confidence intervals for the regression parameters
  • Perform F-test to determine the significance of the overall model
  • Conduct hypothesis testing on linear equality restrictions
  • Explain Dummy Variable Regression Model
  • Incorporate qualitative information into linear regression analysis
  • Estimate and interpret regression models with qualitative independent variables
  • Describe interactions among dummy variables
  • Use dummy variables to test for differences among regression models
  • Explain Qualitative Response Regression Models
  • Examine the distinctions among various categories of limited dependent variables
  • Determine the most suitable model for analysis
  • Interpret and assess the logit and probit models
  • Describe the intuition behind the maximum likelihood estimation
  • Explain the Significance of Choosing the Right Model for Making Economic Decisions
  • Discuss several criteria used for selecting models
  • Recognize the theory-based approach to model selection
  • Analyze the impact of relaxing the assumption of normality in error terms in econometric models on the process of model selection
  • Apply Different Model Selection Techniques
  • Apply model selection techniques for an autoregressive (AR) function
  • Apply model selection techniques for a skewed distribution and kurtosis
  • Apply Machine Learning (ML) approach for model selection

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