This informative book reveals the pervasive nature of large inaccuracies in economic statistics. Drawing on numerous real-world examples including case studies from the COVID-19 pandemic, Peter van Bergeijk presents profound insights into how downplaying these errors undermines the scientific rigour of economic analysis, and outlines how to manage uncertainty in economic analysis moving forward. Global in scope, the book reflects on the current problematic practices within economics, including measurement errors in the analysis of GDP, inflation, trade and employment. Chapters examine key case studies from advanced and developing countries, detailing how the persistence of measurement error impacted the assessment of these events at the time and in retrospect. The author further identifies the best practices for the assessment of error in statistics and equips the reader with the tools to self-assess inaccuracies in economic data in a way that improves evidence-based analysis and decision-making processes. Championing a fresh perspective on econometrics, this book is vital for scholars and students of economics, data science and research methods. Additionally, policy analysts and data producers will value this book’s perspective on the reliability of their data and its provision of problem-solving strategies.