Applied economists analyze data to understand trends like prices, jobs, or consumer behavior using tools like Excel or statistical software. They collect datasets from sources such as government reports or company records and organize them for analysis. They run calculations like averages, growth rates, or regressions to find patterns in the data. They create charts and dashboards that show trends clearly for managers or clients. They write reports that explain what the data means and what actions should be taken. They present findings in meetings and answer questions about how the analysis was done.
Most applied economists earn a bachelor’s degree in economics and complete coursework in statistics, data analysis, and math. During college, students build spreadsheets, run regressions in software like R or Python, and analyze datasets from real-world topics. Students complete projects where they clean data, calculate trends, and present results in written reports. Internships involve collecting data, updating spreadsheets, and assisting with analysis tasks for businesses or government offices. Entry-level roles require analyzing datasets, building charts, and writing reports that explain economic trends.
| School | Location | Distance from ZIP Code 61615 |
|---|---|---|
| Harvard University | Cambridge, Massachusetts | ~1000 miles |
| Stanford University | Stanford, California | ~2100 miles |
| University of Michigan - Ann Arbor | Ann Arbor, Michigan | ~330 miles |
| University of California - Berkeley | Berkeley, California | ~2100 miles |
| University of Chicago | Chicago, Illinois | ~140 miles |
| University of Pennsylvania | Philadelphia, Pennsylvania | ~800 miles |
| Columbia University | New York, New York | ~800 miles |
| University of Washington - Seattle | Seattle, Washington | ~2000 miles |
| New York University | New York, New York | ~800 miles |
| Yale University | New Haven, Connecticut | ~900 miles |
| Cornell University | Ithaca, New York | ~750 miles |
| Johns Hopkins University | Baltimore, Maryland | ~700 miles |
| University of California - Los Angeles | Los Angeles, California | ~2000 miles |
| Massachusetts Institute of Technology | Cambridge, Massachusetts | ~1000 miles |
| University of Wisconsin - Madison | Madison, Wisconsin | ~250 miles |
| University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | ~700 miles |
| University of Minnesota - Twin Cities | Minneapolis, Minnesota | ~400 miles |
| Princeton University | Princeton, New Jersey | ~800 miles |
| Ohio State University | Columbus, Ohio | ~350 miles |
| Pennsylvania State University | University Park, Pennsylvania | ~700 miles |
| Duke University | Durham, North Carolina | ~700 miles |
| University of Illinois at Urbana - Champaign | Champaign, Illinois | ~90 miles |
| University of Texas at Austin | Austin, Texas | ~1000 miles |
| University of Southern California | Los Angeles, California | ~2000 miles |
| Northwestern University | Evanston, Illinois | ~150 miles |
Employers look for candidates who can analyze datasets using tools like Excel, R, or Python to calculate trends and relationships. Strong applicants can run statistical models such as regression analysis to explain patterns in economic data. Hiring managers expect candidates to build charts and dashboards that clearly show results to non-technical audiences. Candidates stand out when they have completed projects where they cleaned messy data, calculated metrics, and wrote reports explaining the results. Employers also value candidates who can explain findings in meetings and answer questions about how the analysis was performed.