Finally Understanding Panel Data

You have panel data: the same customers, firms, patients, stores or students observed over several years. Then the questions start. Fixed or Random Effects? What is the Hausman test actually telling you? Should your standard errors be clustered? Can you trust a Difference-in-Differences when the treatment started at different times?

This guide answers those questions in plain English, for people who use panel data but are not econometricians: students and researchers in marketing, management, health and the social sciences.

Every method is explained with the same simple example, and the practice data were built with a known effect. You can see for yourself which methods recover it and which do not.

What’s inside (13 chapters)

• Part I – Understanding your data: what makes data a panel, and why ordinary regression is not enough.
• Part II – The core models: Fixed Effects, Random Effects, the within-between (Mundlak) model, the Hausman test and First Differences.
• Part III – Policies and interventions: Difference-in-Differences step by step, event studies and Triple Differences.
• Part IV – When the design gets realistic: time fixed effects, two-way fixed effects, and what to do when treatment starts at different times, including the Goodman-Bacon decomposition.
• Part V – Putting it into practice: a decision map, how to read regression output field by field, clustered standard errors and a checklist.
• A software cheat sheet, a glossary of 32 terms and references.

What you get

• The guide (PDF, 75 pages)
• Four practice datasets (CSV)
• All the code in Stata, R and SPSS, chapter by chapter, with the expected result next to every command so you can check your own output.

All Stata and R code was run on the practice data and reproduces the results shown in the guide.

Who it is for: master’s and PhD students, researchers and analysts who need to choose, run and explain a panel-data model. This is an applied guide rather than a theoretical textbook, with minimal algebra and no proofs.

Not sure yet? Download the free sample from the preview button on this page.

Launch price: US$29 until October 25, then US$39.

Licence: for personal use by the purchaser. Instructors can share the guide with a class through the Classroom Licence.

Need an invoice for your department? Email danielle@dmpinheiroconsulting.com.

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About the author

Hi, I’m Danielle Martins Pinheiro. My MSc in Applied Financial Economics at HEC Montréal put panel-data methods at the centre of my research, with difference-in-differences and triple-difference designs on large administrative datasets. Before that, more than a decade as a product manager at major financial institutions in Brazil, followed by customer-facing roles in Canada, taught me how to explain complex ideas to people who need answers rather than jargon. This guide brings those two sides together, explaining each method in plain English, with the kind of practical examples that helped me most along the way.