Reconciliation: From Data to Final Value Opinion

Chapter 11: Reconciliation: From Data to final value❓ Opinion

This chapter delves into the critical reconciliation phase of property appraisal, where collected data transforms into a well-supported final value opinion. It moves beyond simple❓ averaging to explore the scientific principles and appraiser judgment required for credible value estimations.

I. Understanding Reconciliation

• A. Definition: Reconciliation is the process of critically analyzing the value indications derived from different approaches (Sales Comparison, Cost, Income) and data sources, to arrive at a single, supportable opinion of value. This isn’t a mathematical calculation; it’s a reasoned judgment.
• B. Key Objectives:
  1. Analyzing value indicators❓: Evaluating the strength and weaknesses of each value indicator derived from different approaches.
  2. Weighing Evidence: Assigning appropriate weight to each indicator based on its reliability and relevance.
  3. Justifying the Final Opinion: Clearly explaining the reasoning behind the final value opinion, supported by the analyzed data.

II. The Science of Data Reliability

The reliability of a value indicator, and consequently the weight it receives in the reconciliation process, is determined by several scientific factors related to the data itself.

• A. Amount of Data (Statistical Significance): A value indicator is more reliable when derived from a larger, more detailed, and independently sourced dataset. This stems from the principles of statistical inference.

  1. Larger Statistical Sample: A larger sample size reduces the standard error, increasing the confidence level in the value indicator. For example, if you see only 3 similar sales of similar single family homes, that is a small amount of data.
     Formula: Standard Error = s / sqrt(n), where ‘s’ is the sample standard deviation and ‘n’ is the sample size. As ‘n’ increases, the standard error decreases.
  2. Detailed Data: Value indicators that are derived from more detailed and accurately verified data are, as one would assume, more accurate and reliable.
  3. Independent Sources: Value indicators based on multiple independent data sources are considered more credible because they minimize the risk of bias or errors from a single source.

• B. Accuracy of Data & Techniques: A reliable value indicator requires accurate supporting data and the appropriate application of appraisal techniques.

  1. Verification of Data: Data accuracy is directly linked to how well it has been verified.
  2. Relevance of Appraisal Technique: The scientific validity of the appraisal technique depends on its applicability to the specific appraisal problem. The Sales Comparison approach may have more weight with a single family residence than a Cost approach.

• C. Relevance of Value Indicator: The relevance of a value indicator to the specific appraisal problem relies on its consistency with the appraisal assignment and the appropriateness of the technique used.

  1. Consistency with Assignment: The value indicator must align with the intended use, property rights appraised, and the definition of value (e.g., market value) outlined in the appraisal assignment.
  2. Appropriateness of Technique: The chosen appraisal technique must be suitable for the property type and available data. Using the income capitalization approach for a single-family owner-occupied home is generally inappropriate because the property does not generate income.

III. Appraiser Judgment: Bridging Science and Art

While data reliability is crucial, reconciliation also demands skilled appraiser judgment based on experience and market knowledge.

• A. Prioritizing Value Indicators: This is not simply averaging the various indicators together to get to a final opinion. The appraiser needs to assess which of the different value indications are the most reliable and relevant.
• B. Addressing Inconsistencies:
  1. Identifying Discrepancies: Appraisers must identify and investigate any significant differences between the value indicators.
  2. Explaining Deviations: Appraisers explain potential reasons for any deviations.
• C. The Final Value Opinion as a Point Estimate:
  1. Point Estimate: A single dollar amount is used as the point estimate.
  2. Range Value: An acceptable alternative is a range value.
  3. Value Opinions: Rounding to a reasonable and appropriate amount.

IV. Practical Applications and Examples

• A. Reconciliation Scenario:

  Assume that an appraisal has an indicated value of $400,000 for the Sales Comparison Approach, $390,000 for the Cost Approach, and $420,000 for the Income Approach. How can this be reconciled?
  1. Reliability Review: The appraiser reviews all relevant information, and determines that the Sales Comparison and Cost Approach are the most reliable, because of the amount and quality of the data.
  2. Analysis: The appraiser determines that $400,000 is a fair market price.

• B. Mathematical Considerations:

  To further validate the selection of the Sales Comparison Approach, the appraiser can calculate the Weighted Average, and see if the result comes close to the $400,000 result of the Sales Comparison Approach.

  Formula: Weighted Average = (Weight1 x Value1) + (Weight2 x Value2) + (Weight3 x Value3), using weights that add up to 1.

V. Ensuring Credibility in Critical Review

• A. Review Appraisers: Review Appraisers critically evaluate the appraisals and look for any opening to discredit the reasoning and conclusions of the appraiser.
• B. Work Review: All work should pass muster in a critical review.

VI. Key Takeaways

• Reconciliation is a critical component of the appraisal process, and involves a careful consideration of reliability, data, supportability, and scientific valuation methods.