Introduction to Econometrics

Overview

• What is Econometrics?
  • Application of statistical methods in economics.
  • Often involves regression analysis.

Key Concepts

• Regression Analysis:
  • Relationship between independent variables and a dependent variable.
  • Example:
    • Dependent variable Y affected by independent variables X1, X2, ..., Xn.
  • Important for understanding how changes in independent variables impact Y.
• Importance of Econometrics:
  • Estimating relationships between economic variables.
  • Testing economic theories and hypotheses.
  • Forecasting economic variables.
  • Evaluating government/business policy.

Types of Economic Data

1. Time Series Data
   • Observations over time.
   • Example: GDP of a country measured over several years.
2. Cross-Sectional Data
   • Observations across subjects at a specific time.
   • Example: Annual GDP of various countries in a specific year.
3. Panel Data
   • Observations over time and across individuals.
   • Example: Annual GDP of a set of countries over multiple years.

Simple Linear Regression

• Definition:
  • Analyzing the relationship between one dependent variable and one independent variable.
• Multiple Linear Regression:
  • Involves two or more independent variables.
• Basic Function:
  • Standard form:
    • Y = mx + b
      • Y = dependent variable
      • m = slope
      • x = independent variable
      • b = y-intercept
• Regression Equation with Error Term:
  • Y = β0 + mX + U
    • β0 = intercept
    • m = slope
    • U = error term (distance between the line and individual data points)

Understanding Causality

• Economists often seek to determine how changes in X affect Y while holding other variables constant.
• In simple linear regression, we assume X is the only variable affecting Y.

Next Steps

• Upcoming videos will cover interpretation of regression coefficients and intercepts.