Vector Autoregression: VAR Impulse Responses
vector autoregression explains how inflation and unemployment interact through lagged feedback, coefficient matrices, and impulse response functions with confidence bands.
Econometrics
Unlock the power of econometrics with insights on key models and tools that help explain and forecast economic trends. Perfect for both beginners and advanced researchers.
Cointegration and Engle-Granger Method: Long-Run Testing
Cointegration and Engle-Granger Method tests whether non-stationary economic variables share a stationary long-run equilibrium instead of a spurious trend relationship.
Granger Causality: Predictive Order in Time Series
Granger Causality tests whether past oil-price movements improve gasoline-price forecasts after gasoline’s own history is included in the time-series model.
Augmented Dickey-Fuller Test: Detecting Unit Roots in Economic Time Series
The Augmented Dickey-Fuller test is the standard procedure for detecting unit roots in economic time series, preventing the spurious regression...
Bayesian Econometrics: Priors, Posteriors, and Practical Uses
Bayesian econometrics combines prior beliefs with observed data to produce probability statements about parameters that frequentist methods cannot deliver. This...
Causal Machine Learning for Economists: Double ML and Causal Forests Explained
Causal machine learning combines flexible ML methods with econometric rigour. This guide explains Double ML and Causal Forests for economists...
Advanced Difference-in-Differences Methods: Beyond Two-Way Fixed Effects
Advanced difference-in-differences methods correct TWFE bias of 66-79% in staggered designs. Callaway-Sant'Anna, Sun-Abraham, and Goodman-Bacon have transformed applied econometrics.
A Practical Guide to Causal Inference in Economics
Causal Inference in Economics relies on three core methods of the credibility revolution: Difference-in-Differences, Regression Discontinuity, and Synthetic Control. These...
Exploring Machine Learning in Econometrics: Transforming Data Analysis and Forecasting
Machine Learning in Econometrics enhances data analysis by addressing high-dimensional data, modeling nonlinear relationships, and improving predictions, while maintaining causal...
Quantile Regression: Analyzing Conditional Distributions in Econometrics
Quantile regression goes beyond mean-based analysis to uncover how relationships between variables vary across a distribution. Ideal for addressing heterogeneity,...