Introduction to Applied Econometrics

Study Notes

Econometrics is the quantitative analysis of real-world economic phenomena, using theory and statistical techniques.
It merges economic theory, mathematical economics, economic statistics, and mathematical statistics.
Econometric research combines economic theory with actual measurements, using statistical inference.
Economic theory offers qualitative statements, but not numerical measures of relationships.
Econometrics provides the numerical estimates of these relationships.

Econometrics can be understood as "economic measurement."
It involves applying mathematical statistics to economic data to support mathematical economic models and derive numerical results.
It employs a quantitative analysis of economic phenomena, guided by both theory and observation, using appropriate inference methods.
It aims to empirically determine economic laws.

Combining economic theory and mathematical models requires a distinct approach since theory often lacks numerical measurement of relationships.
Economic theory provides qualitative statements or hypotheses.

Microeconomic theory suggests price reductions increase commodity demand.
This involves a negative relationship between price and quantity demanded, but it doesn't quantify the extent of the change.
Econometricians aim to provide these numerical estimates.

Mathematical economics expresses economic theory in mathematical forms (equations) without considering measurability or empirical verification.
Econometrics focuses on empirical verification of economic theory.

Economic statistics collects, processes, and presents economic data as charts and tables.
The economic statistician provides the baseline data; the econometrician builds on, and further-examines, these data.

Consumption (Y) is related to income (X) by a linear equation: Y = β1 + β2X, where:
- β1 is the intercept.
- β2 is the slope coefficient (MPC).

The exact mathematical relationship between consumption and income is not always true; it's influenced by other factors.
This is addressed by using a deterministic consumption function Y = β1 + β2 X +u (error term)

Obtaining consumption and income data is necessary to estimate the econometric model's parameters.
Real-world data (such as that in a table) is used to calculate the estimated consumption function parameters.

Statistical techniques like regression analysis provide numerical estimates of the parameters (β1 and β2) of the consumption function.
An estimated consumption function is provided: Y^ = -184.08 + 0.7064X

Testing whether the estimations align with the predictions of the theory (expected MPC to be positive and less than 1).
Calculating whether the model's predictions correlate accurately with real data.

Used to predict mean consumption expenditure for a specific year, using GDP figures.
The actual value of consumption in 1997 is compared to the forecast.

Using the estimated consumption function to determine income levels necessary for target consumer spending given the current unemployment rate.
Using the model to evaluate how policy can manipulate factors to produce economic goals.