Economic policy analysis is changing. Official statistics are increasingly complemented by administrative records, satellite imagery, mobile phone and payment data and prices collected from the web, while analysis that once lived in a single spreadsheet now runs in scripted, version-controlled code that others can check and rerun. Governments and research institutions that adopt these practices can respond faster and with more credible evidence.

The Digital Transformation in Applied Economics & Policy Analysis Training Course helps working economists make that shift. It starts with a reproducible analytical workflow and modern data acquisition, then covers data cleaning and exploratory analysis, applied econometrics for causal inference, nowcasting and forecasting with high-frequency indicators, simulation of policy options, and communication of findings through dashboards and briefs. Throughout, the emphasis is on judgement: choosing methods that fit the question and the data, and being clear about uncertainty.

Every session includes hands-on coding in Python or R, with Stata equivalents shown where useful. Participants work with real public datasets from African economies and finish the week by producing a short, fully reproducible policy analysis.

After the course, participants will be able to:

• Organise economic analysis as reproducible, version-controlled projects in Python or R.
• Acquire data programmatically from APIs, open data portals and web sources.
• Clean, merge and explore survey, administrative and high-frequency datasets.
• Estimate policy effects using difference-in-differences, regression discontinuity and instrumental variables.
• Nowcast GDP, inflation or trade using high-frequency and alternative indicators.
• Simulate the distributional effects of tax, subsidy or transfer reforms.
• Communicate results through interactive dashboards and concise policy briefs.

Analysts who produce evidence for economic and public policy decisions will benefit, in particular:

• Economists in finance and planning ministries and treasuries
• Research and statistics staff at central banks
• Policy analysts in think tanks, universities and research institutes
• Statisticians at national statistics offices
• Economists in development partner agencies and multilateral banks
• Revenue authority and trade ministry analysts
• Monitoring and evaluation specialists working on impact evaluation
• Private sector economists in banks and consultancies

Participants take away:

• A reusable project template with folder structure, scripts and Git history.
• Working code that pulls and updates indicators automatically from public APIs.
• A nowcasting model for a macroeconomic indicator of their choice.
• An impact evaluation script with diagnostics and robustness checks.
• A two-page policy brief and dashboard produced from their own analysis.
• A personal roadmap for moving their unit's work from spreadsheets to code.

Each day combines concept, code and critique:

• Short methodological briefings followed by guided coding labs
• Real public datasets on African economies, prices and trade
• Paired programming so participants with different coding experience learn from each other
• Clinics on participants' own data and policy questions
• A final reproducible analysis presented and reviewed by peers

Successful completion, meaning attendance at all sessions and submission of the coding labs and final policy analysis, leads to a CPD-accredited Certificate of Completion issued by Vision Reach Global Consultancy.