The Wall Street Journal recently reported that reducing capital-gains taxes by tying them to inflation would disproportionately benefit wealthy Americans and reduce tax revenue by about $100 billion over 10 years.
This forecast and others like it are the hallmark of the Penn Wharton Budget Model (PWBM), which since 2016 has been producing nonpartisan briefs and forecasts, providing the public a better understanding of how specific policy changes affect the U.S. economy.
The prominence of PWBM shows how data and analytics are a crucial and often overlooked keystone of democracy in the 21st century. It also illustrates how Wharton is reinventing decision-making at the federal level.
The budget model is made possible by key contributors to the More Than Ever campaign; an expert team of economists, data scientists, and software developers; and advisors from academia, the government, and the private sector.
Its influence largely comes from the accessibility and precision of its interactive models:
- Social Security simulator presents more than 4,000 policy scenarios; among them, it shows that the Social Security trust fund will become exhausted by 2031 under current law.
- Immigration simulator considers policy changes based on deportations, amnesty, and legal immigration. Increasing the net flow of immigrants while shifting the mix toward college graduates would have a small but positive impact on the economy.
- Wall Street Journal’s Tax Calculator is based on PWBM models and allows taxpayers to see whether President Donald Trump’s overhaul will increase or lighten their liability through 2027.
- An interactive map shows state-by-state population percentagesfor unauthorized immigrants as well as education levels of native- and foreign-born residents.
“PWBM’s online tools are publicly available,” said Faculty Director Kent Smetters. “We want to foster big ideas and nonpartisan discussion by providing research-based resources for policymakers, media, and average Americans alike. There is too much at stake not to do this.”
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