Residential Property Price Index (RPPI) Fundamentals

Measuring changes in residential property prices is critical for economic analysis, policymaking, and investment decisions. This text-based course guides you through the essential concepts, data collection strategies, and mathematical formulations needed to construct a reliable Residential Property Price Index (RPPI). You will transition from understanding basic real estate metrics to confidently explaining and applying index compilation methodologies. Through clear written explanations and practical calculation exercises, you will learn how to handle data limitations, choose the right index formulas, and account for quality changes in housing over time. What you'll learn: • Understand the core terminology and economic significance of Residential Property Price Indexes. • Identify and evaluate key data sources, including administrative registries, tax records, and modern web-scraped real estate listings. • Apply standard index formulas, such as Laspeyres, Paasche, and Fisher, to aggregate property price data. • Address quality-mix changes using stratification, hedonic regression, and repeat-sales methods. • Configure data validation workflows to ensure index accuracy and consistency. The course begins with foundational concepts of real estate economics and index theory, then progresses to data acquisition strategies and advanced quality adjustment methodologies. You will practice calculations using step-by-step written scenarios designed to simulate real-world statistical challenges. This course is designed for beginning data analysts, economic researchers, real estate professionals, and public sector statisticians who want to understand how housing price indexes are constructed. No prior experience in index compilation is required. Start reading today to build a solid foundation in real estate statistical analysis.