ARDL Bounds Testing Explained
The bounds test works with a mix of stationary and integrated series, which is why it fits short samples. The...
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.
Type I and Type II Errors Explained
Type I and Type II errors are the two ways every test fails, and the 5 percent convention is a...
P-Values and Statistical Significance
P-values answer one narrow question: how surprising the data would be if nothing were going on. The common readings claim...
Confidence Intervals in Econometrics
Confidence intervals report magnitude and uncertainty in one range, and everything the significance star says is readable off them, with...
Standard Errors: Measuring Uncertainty
Standard errors measure how well an estimate is known, shrink at square-root prices, and lie in known ways when data...
Dummy Variables in Regression
How to put categories into a regression: building dummy variables, avoiding the dummy variable trap, and reading each coefficient against...
Interaction Terms in Regression
An interaction term lets the effect of one variable depend on another. Here is how to add it, read the...
Spurious Regression Explained
Two unrelated trending series can produce a high R-squared and a large t-statistic. Why unit roots cause it, how to...
Weak Instruments in IV Estimation
Weak instruments drag two-stage least squares back toward biased OLS. The first-stage F test, the rule of ten, and what...
Omitted Variable Bias: Missing Variables Distort Estimates
Omitted variable bias explains how missing correlated variables distort regression estimates and weaken causal interpretation in econometric models.