Introduction to Econometrics and Econometric Analysis

Overview

• Introduction to econometrics and its importance.
• Topics covered:
  • Definition and goals of econometrics.
  • Types of econometric data.
  • Basics of simple linear regression.

What is Econometrics?

• Application of statistical methods in economics.
• Primarily involves regression analysis.
  • Regression: Relationship between independent variables and the expected value of a dependent variable.
    • Example: Effect of education and experience on wages.

Goals of Econometrics

• Estimate relationships between economic variables.
• Test economic theories and hypotheses.
• Forecast economic variables.
• Evaluate and implement government or business policies.

Types of Econometric Data

1. Time Series Data
   • Observations over time.
   • Example: GDP of Canada over 10 years.
2. Cross-Sectional Data
   • Data across subjects at a single point in time.
   • Example: Annual GDP of multiple countries in a specific year.
3. Panel Data
   • Combination of time series and cross-sectional data.
   • Example: Annual GDP of a set of countries over several years.

Simple Linear Regression

• Explores the relationship between a dependent variable (Y) and an independent variable (X).
• Standard form: Y = mx + b
  • m: Slope of the line.
  • b: Y-intercept.
• Includes an error term (U) that accounts for deviations of data points from the line.

Multiple Linear Regression

• Involves more than one independent variable.
• Form: Y = β₀ + β₁X₁ + β₂X₂ + ... + U

Conclusion

• Econometrics helps to find causal relationships.
• The focus is on understanding how changes in X affect Y when other factors are constant.
• Next video will cover interpretation of coefficients and intercepts in regressions.

Note: This is a basic introduction. Further details and applications will be covered in subsequent lectures.