Can we still find the true effect of a job training program on earnings if we compare trainees with ordinary survey respondents instead of a randomized control group? This Python tutorial shows that adding background characteristics fixes the estimate only when they adjust the expected earnings trend of the comparison group. It comes with an interactive app that runs in your web browser.
Do gender quotas raise the share of women in national parliaments? In Stata, we compare 9 countries that adopted quotas in different years with look-alike groups built from 110 countries without quotas, and find an average gain of about 8 percentage points that varies a lot across countries. The tutorial includes an interactive app that runs in your web browser.
Did the 1988 tobacco tax in California reduce smoking? In Stata, we compare three ways of building a comparison for California from other states, including a newer method that blends their strengths, and all three agree that cigarette sales fell, though by different amounts. It comes with an interactive app that runs in your web browser.
What happens to nearby home prices when a registered sex offender moves into a neighborhood? We compare homes close to the address with homes a little farther away, before and after the move, and show how the distance chosen as the cutoff can change the answer. This R tutorial comes with an interactive app that runs in your web browser.
Did expanding Medicaid health coverage to low-income adults reduce deaths? We compare counties in states that expanded coverage with counties in states that did not, and show how counting each county equally or each person equally can change the answer. This R tutorial includes an interactive app that runs in your web browser.
Did an after-school tutoring program really raise student grades, or were grades rising everywhere? This Python tutorial compares 10 tutored high schools with 25 others, before and after the program, to separate its effect from the general upward trend. It comes with an interactive app that runs in your web browser.
Did an after-school tutoring program raise the grades of low-income high school students? Using simulated data on 35 schools in Stata, we compare how grades changed in schools with and without the program, and we check whether both groups were on similar paths before it started. It comes with an interactive app that runs in your web browser.
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.
Did expanding Medicaid in some American states raise health insurance coverage among low-income adults, and how much can we trust that answer? In Stata, we measure how far the states could drift apart before the estimated gain would disappear, turning a yes-or-no check into a clear measure of robustness. It comes with an interactive app that runs in your web browser.
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.