Enhancing High-Volume Comparable Sales Processing with Regression Models

 Coming Soon (08/28/2025) on Amazon

Book Summary: This is a practical guide to leveraging regression analysis for more efficient real estate valuation. Drawing on actual sales data from diverse counties and towns, the book features ten chapters, each dedicated to a complete regression model. These models incorporate real-world datasets, in-depth statistical analysis, and step-by-step implementation plans, making them accessible for both novices and experts.

Rather than building exhaustive predictive tools, the models focus on generating statistically significant baseline coefficients to support comparable sales (comps) processes. This approach aids key stakeholders—private entities like banks, brokerages, real estate investment trusts (REITs), funds, mass appeals filers, and research firms, as well as public assessing jurisdictions—in streamlining their in-house workflows for greater efficiency, transparency, and scalability.

A core methodology is the two-pass regression framework, applied consistently throughout. The first pass uses all available sales data to establish a baseline model. In contrast, the second pass refines it by excluding outliers based on metrics like sales ratios and Z-scores, yielding smoother, less noisy, and more reliable results. The book also demonstrates deriving objective time adjustments from market data via regression, avoiding subjective pre-treatments to raw sales prices.

To address economic variances across cities, towns, and zip codes, the book explores proven coding techniques for categorical variables, including dummy coding, effect coding, one-hot encoding, ordinal encoding, and custom deviation coding. These methods ensure models account for location-specific disparities effectively.

Finally, the book stresses the importance of supplementing baseline models with detailed, subject- and comps-specific data—often sourced from taxing jurisdictions and data providers—to produce comprehensive final reports. By combining regression with enhanced data collection, readers gain a holistic toolkit for insightful, high-volume comps analysis in dynamic real estate markets.