20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You often split time between data work and writing. Mornings might mean cleaning datasets in Excel, SPSS, or Access and running regressions for a policy question.
Afternoons usually include meetings with NGOs, government clients, or students, writing reports in Word, and making slides in PowerPoint or Power BI. Some days are spent in the field collecting socioeconomic data.
Start with Microsoft Excel and Word — economists use Excel for cleaning data, quick charts, and simple forecasts, and Word for reports. Learn pivot tables, VLOOKUP/XLOOKUP, and basic charts.
Next add SPSS (for survey and statistical work), PowerPoint and Power BI for presentations and dashboards, and Access if you’ll manage larger relational databases.
Use AI as a drafting and data-cleaning assistant: generate first-draft report text, summarize papers, or suggest code snippets for SPSS or Excel macros. Always check outputs against the original data and your theory because AI makes plausible but wrong suggestions.
AI helps speed repetitive tasks but won’t replace judgment: designing surveys, choosing the right econometric model, interpreting policy impacts, or giving expert testimony still needs human expertise.
According to the U.S. Bureau of Labor Statistics (BLS) for 2025, about 17,790 people were employed as economists. The median pay was $124,720 per year; the lowest tenth earned $67,360, and the top tenth earned $238,060.
Salaries vary by sector: governments and nonprofits often pay less than private consultancies or international organizations, and experience, publications, and technical skills raise pay.
Major in economics or development studies and take lots of statistics, econometrics, and microeconomics classes. Learn to use Excel and SPSS in your coursework and do a senior thesis or research project you can show employers.
Intern with a think tank, NGO, or a university lab to get experience collecting financial and socioeconomic data, writing policy reports, and presenting findings.
Development economists focus on economic theory and empirical methods to study resource allocation, trade, labor, or agriculture and evaluate policy impacts. They commonly forecast trends and write reports for policy decisions or litigation support.
Policy analysts may work on broader policy areas with less emphasis on formal econometric methods. Data scientists often focus on machine learning and product feasibility with different toolsets and business metrics.
Being fluent in Excel (pivot tables, XLOOKUP, charting, basic VBA or macros) is the quickest way to contribute: teams use it for cleaning data, simple forecasts, and initial analyses.
Combine that with basic report writing in Word and presentation skills in PowerPoint or Power BI. Those three allow you to analyse statistical data, communicate findings, and help supervise small research tasks quickly.