Chapter 1: The Nature of Econometrics and Economic Data

An Introduction to Empirical Analysis

What Is Econometrics?

Econometrics is the use of statistical methods to analyze economic data, test economic theories, and evaluate government and business policy.

Key Goals:

  • Estimating relationships between economic variables.
  • Testing economic theories.
  • Forecasting macroeconomic variables (GDP, inflation, etc.).
  • Evaluating the impact of policies (e.g., job training programs).

Steps in an Empirical Analysis

A typical empirical project involves a few key steps:

  1. Start with an economic model or a question of interest.
    Example: How does education affect a person's wage?
  2. Turn it into an econometric model by specifying a functional form and including an error term `u` for unobserved factors.
    wage = β0 + β1educ + u
  3. Collect appropriate data.
  4. Use econometric methods to estimate the parameters (the β's) and test hypotheses about them.

The Structure of Economic Data

The type of data we have dictates the methods we can use. Here are the main types:

Cross-Sectional

Many different units (people, firms, countries) at a single point in time.

Time Series

A single unit (a country, a company) observed over multiple time periods.

Pooled Cross-Sections

Combines two or more different cross-sections from different time periods.

Panel / Longitudinal

The same cross-sectional units are followed over multiple time periods.

Check Your Understanding

You have data on the unemployment rate for every county in the United States for the years 2000 and 2010. What kind of data structure is this?

Answer:

This is a Panel Data set. The key is that you are observing the same units (counties) at multiple points in time (2000 and 2010).

If you had data on a different set of counties for each year, it would be a pooled cross-section.

The Central Problem: Causality

The goal of most empirical studies is to estimate a causal effect. We want to know the effect of a variable on another, ceteris paribus ("holding other relevant factors fixed").

Example: The Return to Education. What is the effect of one more year of education on wages, holding innate ability, experience, and all other factors constant?

This is incredibly difficult with nonexperimental (observational) data, because we can't run controlled experiments. We can't randomly assign education levels to people! People choose their education, and that choice is likely correlated with other factors that affect wages (like ability).

Chapter 1 Summary

  • Econometrics provides the tools to estimate economic relationships, test theories, and evaluate policies using data.
  • Empirical analysis involves specifying an economic and then an econometric model, collecting data, and using statistical methods for estimation and inference.
  • Economic data can be cross-sectional, time series, pooled cross-sectional, or panel data.
  • The most difficult task in econometrics is establishing causality due to the nonexperimental nature of most economic data.