Appraiser curriculum for today’s aspiring trainees rests firmly on “recognized methods and techniques.”

The old stuff.

“Methods” are a work-around for the sparse and messy data.  Methods are not models.  “Techniques” are procedures:  Practical skills.  The art.

What today’s trainees actually need is an understanding of empirical models, repeatable algorithms, and brain-machine interface.  Including proper use of artificial intelligence.  Empirics, not imitation heuristics!

The new stuff.

Traditional appraiser curriculum emphasized personal care and attentiveness to selecting comparable data.  And experience, or “adjustment guides,” of reasonable amounts.

This, not only for sales comparison, but for site/land comparables for the cost approach, and income characteristics for the income approach.

The “three approaches” evolved from the needs of the time.  Home lenders needed sales comparison.  Developers and construction lenders needed a rigorous cost approach.  This left income properties of all types in the “income approach” category.

With the advent of the spreadsheet, the DCF (discounted cash flow) method provided another process, often used as a supplement or replacement for the income approach.  But a reality of the DCF is that it is actually a forecasting method to bring to a present value “opinion.”

The idea is for the appraiser to attempt to replicate the typical buyer’s current beliefs/estimates of future income flow, size, and durability.

While other methods or approaches commonly apply to various value/risk problems – the three approach models cover most of the reasoning analysis needed.  But note, in the past we did have more than just three approaches, and other countries today specify more than three!  We need a broader and deeper understanding of what appraisers are to measure.

A new curriculum is needed for new appraisers in a new world.

So, what should this new curriculum include?

More than what one might expect!

• Economics – Two types: 1) the reality of localized, bi-lateral oligopoly; and, 2) behavioral economics – the nature of ‘subjective’ decision-making.
• Game theory versus the fairytale of perfect competition ‘equilibrium’.
• Data science – The broad replacement for “worthy of belief” standards.
• Empiricism (data and analytics) versus rationalism (intellectual innate ideas).
• Probabilistic analytics versus experience-based adjustments.
• Reliability estimates versus subjective “reconciliation.”
• Ethical behavior versus “ethics rules.”
• Market analysis before comp selection.
• Reproducible algorithms versus conviction and trust.
• Visualization and numerical summaries — in place of words.
• Prompts and “agent” instructions versus narrative “support.”
• Reasoning, judgment, logical inference, and thinking: critical, analytic, and statistical.

Most, if not all of the above – is missing from today’s appraiser education.

Yesterday was then.  Today is now!  Public policy please . . .

Stats, Graphs, and Data Science 1: Evidence-Based Valuation^(c) and AI. Register Here.