panel data

Spatial Dynamic Panels with Common Factors in Stata: Credit Risk in US Banking

How does credit risk spread across banks? Using quarterly data on 350 American banks from 2006 to 2014 in Stata, we model bad loans that spill over between similar banks, persist over time and respond to shared economic shocks, and show that ignoring those shocks gives misleading answers. It comes with an interactive app that runs in your web browser.

Difference-in-Differences for Policy Evaluation: A Tutorial using R

Did raising the minimum wage cost teenagers their jobs? Using American states that raised their wage floors at different times, we compare states before and after each increase and show why the classic shortcut can mislead when policies start on different dates. This R tutorial comes with an interactive app that runs in your web browser.

Evaluating a Cash Transfer Program (RCT) with Panel Data in Stata

Does giving cash to poor households raise what they spend on everyday needs? Using a simulated randomized experiment with 2,000 households in Stata, we compare several ways of estimating the effect and see that all of them recover the true gain of about 12 percent. It comes with an interactive app that runs in your web browser.

High-Dimensional Fixed Effects Regression: An Introduction in Python

How much of the higher pay of union workers comes from the union itself, and how much from who joins? This Python tutorial shows how fixed effects, which compare each worker only with the same worker over time, remove hidden differences and cut the apparent union pay gain from about 18 to 8 percent. It comes with an interactive app that runs in your web browser.

Introduction to Difference-in-Differences in Python

Did a new policy really change outcomes, or were things already improving? This Python tutorial introduces the difference-in-differences method, which compares changes over time between places that got the policy and places that did not, using simulated data, and checks how solid the answer is. It comes with an interactive app that runs in your web browser.

Heterogeneous treatment effects via two-stage DID

An introduction to heterogeneous treatment effects using the two-stage DID estimator of Gardner (2021)

Spatial Panel Regression in Stata: Cigarette Demand Across US States

Do cigarette prices in one state change how much people smoke in neighboring states? Using data on 46 American states from 1963 to 1992 in Stata, we model cross-border shopping and smoking habits, and find that ignoring neighbors understates how much prices matter. It comes with an interactive app that runs in your web browser.

Staggered DiD (Ex1)

An introduction to difference in differences with multiple time periods and staggered treatment adoption.

Staggered DiD

An introduction to difference in differences with multiple time periods and staggered treatment adoption.