Generalized Method of Moments (GMM)
The generalized method of moments estimates parameters from moment conditions. It nests least squares, instrumental variables, and maximum likelihood.
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.
The Heckman Selection Model
The Heckman selection model corrects sample selection bias in wage equations and anywhere the outcome is seen only for a...
Hausman Test: Fixed or Random Effects
The Hausman test decides whether panel data support fixed effects or random effects. The hypotheses, the decision rule, and what...
Maximum Likelihood Estimation (MLE)
Maximum likelihood picks the parameters that make the observed data most probable. Here is the method, its properties, and how...
GARCH Models: Volatility Clustering Explained
GARCH models explain volatility clustering: calm follows calm, crisis follows crisis. Here is the conditional variance equation and how to...
Vector Autoregression (VAR) Explained
A VAR lets several variables explain each other through lags. Here is the matrix form, lag selection, and how to...
Cointegration and the Engle-Granger Method
Two series can wander on their own yet stay tied together. Cointegration tests for that, and Engle-Granger is the two-step...
Granger Causality Explained
Granger causality tests whether one series helps forecast another once the target's own history is included. It is prediction, not...
The Augmented Dickey-Fuller Test
The standard test for a unit root in a time series. The null hypothesis, how to read the statistic, and...
Bayesian Econometrics Explained
Bayesian econometrics combines a prior with the data to give the probability that a parameter lies in a range. Here...