Real Estate Valuation: Methods, Subjectivity, and Biases11-15 August 2025
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Instructor
Simon Thaler Lecturer, University of Applied Sciences Kufstein; External Research Fellow, University of Reading; and Lecturer, Technical University of Munich |
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Course description
This doctoral-level summer course offers a rigorous and critical examination of real estate valuation methodologies. Emphasizing both traditional techniques and contemporary developments, the course investigates the intersection of quantitative valuation, subjective assessment, and behavioral influence. Key topics include cost, sales comparison, income, and hedonic approaches, as well as image-based valuation, visual perception, and the use of automated valuation models (AVMs). Participants will develop advanced analytical skills through lectures, applied casework, and reflective assignments.
Learning Outcomes
Course Structure
Each day includes:
Day-by-Day Breakdown
Day 1: Introduction to Valuation Principles
Required and Supplementary Materials
Required Text: Thaler, S. (2025). Valuation. Real Estate Briefs - European Real Estate Society.
Supplementary: Selected papers by the instructor, datasets, valuation cases, and AVM outputs.
Assessment
This doctoral-level summer course offers a rigorous and critical examination of real estate valuation methodologies. Emphasizing both traditional techniques and contemporary developments, the course investigates the intersection of quantitative valuation, subjective assessment, and behavioral influence. Key topics include cost, sales comparison, income, and hedonic approaches, as well as image-based valuation, visual perception, and the use of automated valuation models (AVMs). Participants will develop advanced analytical skills through lectures, applied casework, and reflective assignments.
Learning Outcomes
- Apply core valuation techniques (cost, comparison, income, hedonic)
- Understand the influence of behavioral and visual biases on valuation
- Critically evaluate the strengths and weaknesses of AVMs
- Incorporate subjective and objective components into valuation reports
- Reflect on the role of the valuer in an increasingly data-driven environment
Course Structure
Each day includes:
- Morning Lecture: 3 hours
- Afternoon Exercise: 3 hours
- Evening Self-Study: 3 hours
Day-by-Day Breakdown
Day 1: Introduction to Valuation Principles
- Lecture: Market vs. investment value, documents and inputs in valuation, core methods
- Exercise: Assigning valuation methods by purpose, discussion of subjectivity
- Self-Study: Reading Chapters 1-3, Reflection: "what are key input drivers for subjectivity?"
- Lecture: Depreciation, replacement cost, comparables and adjustments
- Exercise: Valuation using comparables and cost estimation
- Self-Study: Reading Chapter 4, Critical reflection of model choice
- Lecture: DCF, hedonic pricing applications
- Exercise: DCF modeling, optional hedonic model (R/Python)
- Self-Study: Reading Chapter 5, Identify potential caveats in AVMs
- Lecture: Condition, aesthetics, layout, image-based assessments, behavioral economics in valuation
- Exercise: Image-based valuation workshop
- Self-Study: Reading: Thaler & Koch (2023), commentary on image-based valuation
- Lecture: AVMs, machine learning, ethics and transparency
- Exercise: Compare AVM and human estimates
- Self-Study: Reading Chapter 7, Reflect on mitigation strategies
Required and Supplementary Materials
Required Text: Thaler, S. (2025). Valuation. Real Estate Briefs - European Real Estate Society.
Supplementary: Selected papers by the instructor, datasets, valuation cases, and AVM outputs.
Assessment
- Participation in all sessions
- Completion of daily exercises
- Submission of an 2000 word position paper by end of course
