ECONOMETRICS I

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Learning Outcomes

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