Are poorer regions catching up, and is inequality falling? geometrics answers with spatial methods in Python, Plotly figures, and no-code Streamlit apps.
An introduction to regional impact evaluation using modern causal-inference methods with worked examples and publicly available data for full reproducibility.
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.
When a state raises cigarette prices, do smokers simply buy in the state next door? Using cigarette demand in 46 American states from 1963 to 1992, we measure how prices and income affect smoking at home and in neighboring states, and how habits carry over from year to year. This R tutorial comes with an interactive app that runs in your web browser.
Do regions with high or low human development cluster together on the map of South America, and did those clusters shift between 2013 and 2019? This Python tutorial maps 153 regions and uses spatial statistics to test whether neighbors are more alike than chance would suggest. It comes with an interactive app that runs in your web browser.
Do poorer districts in Indonesia catch up with richer ones at the same pace everywhere? This Python tutorial uses a map-based regression that lets each relationship change from place to place, each at its own geographic scale, across 514 districts. It comes with an interactive app that runs in your web browser.
How can we tell whether regions are developing over time when the measuring stick itself must stay the same? Using education, health and income data for 153 South American regions in 2013 and 2019, this Python tutorial builds one development index from both years together so that scores can be compared across time. It comes with an interactive app that runs in your web browser.
Can satellite images tell us how well each municipality in Bolivia is developing? This beginner-friendly Python tutorial trains a random forest, a machine learning model that averages many decision trees, tests it on places it never saw, and finds that the images hold real but limited information. It comes with an interactive app that runs in your web browser.