This repository presents a comprehensive econometric analysis of the Modern Phillips Curve using macroeconomic data sourced from the Federal Reserve Economic Data (FRED). Unlike the traditional model, this version focuses on inflation dynamics, inflation expectations, and the output gap—excluding unemployment as an explanatory variable.
The Modern Phillips Curve posits that current inflation is influenced by:
- Past inflation (inflation persistence)
- Expected inflation
- Real economic activity (output gap)
This notebook empirically examines the validity of this modern specification for the U.S. economy using quarterly macroeconomic data and standard econometric techniques.
- Python Libraries:
pandas,matplotlib,seaborn,statsmodels,fredapi - Econometric Tests: ADF, KPSS, PP, White test, Jarque-Bera, Breusch-Pagan
- Regression Model: OLS (Ordinary Least Squares)
- Diagnostic Checks: Residual normality, heteroskedasticity, autocorrelation
| Variable | Description |
|---|---|
| Inflation Rate | Current inflation rate (based on CPI) |
| Lagged Inflation | One-period lag of inflation (captures persistence) |
| Inflation Expectation | Expected inflation (proxy via 1Y inflation breakeven or survey) |
| Real GDP | U.S. real GDP (seasonally adjusted, billions of chained $) |
| Log GDP | Natural logarithm of real GDP |
| Output Gap (%) | % difference between actual and potential GDP |
Time Period: Quarterly data from Q1 1982 to Q1 2024
The OLS regression evaluates the influence of lagged inflation, expected inflation, and the output gap on the current inflation rate. Each variable reflects a theoretical aspect of price-setting behavior in modern macroeconomic models.