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A concise guide to reproducible research using secondary data

This study guide is a resource for graduate students, PhD candidates, and early career researchers performing applied empirical research in economics and management sciences. The guide is meant for the field of analysis of health care markets using secondary data. Many textbook examples use readily available datasets for analysis of econometric problems. For students developing a related research question and generating their own analysis dataset, important steps that lead to a final analysis dataset are often missing. Additionally, many resources focus on labor economics problems. Resources that showcase processing and generating secondary data are scarce. One reason is that data sources used in health care applications are often subject to confidentiality and data protection issues.

This guide explains the five essential steps needed to create a reproducible research project. We introduce important terminology, highlight relevant tasks, and provide key resources in the form of textbooks and websites available via open access. We provide a concise guide that users can easily access when starting academic research. Each section takes about 10 to 15 minutes to read. We do not cover any specific data science or econometric method, but point to the relevant resources.

To use this guide most efficiently, users are required to have basic knowledge in statistics, econometrics and program evaluation methods. Users should be familiar with one essential programming language and one major statistical package such as R or Stata. For maximum benefit readers should have background knowledge and a research idea for their own reproducible project in mind.


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