Reconciliation and Final Value Opinion

Chapter 11: Reconciliation and Final Value Opinion

I. Introduction

This chapter delves into the critical process of reconciliation and forming a final value opinion in property valuation. As highlighted in the course description, achieving accuracy in property value assessment is paramount for informed investment decisions❓❓ and a successful career in real estate appraisal. This chapter emphasizes the scientific rigor required in the reconciliation process, ensuring a robust and defensible final value conclusion. This is also important for the review appraiser, in order to avoid discredit, and have your work pass muster in a critical review.

II. Reconciliation: Principles and Process

A. Definition: Reconciliation is the process of critically analyzing and synthesizing the various value indicators❓ derived from different appraisal approaches (sales comparison, cost, and income) to arrive at a single, supportable opinion of value. It is not a mere averaging of values but a weighted analysis based on the reliability and relevance of each indicator.

B. Scientific Basis: Reconciliation relies on the principles of statistical inference and decision theory. Each valuation approach generates a value “estimate” with an associated degree of uncertainty. Reconciliation aims to minimize the overall uncertainty by weighing each estimate based on its variance (a measure of dispersion around the mean).

C. Reconciliation is Judgment-Based: While this is true (from the book), it is not a synonym for “guess”. A proper judgement is built on:
* Thorough data review.
* Calculation accuracy.
* Consistent methodology.
* Understanding the assignment parameters.

III. Factors Influencing the Reliability of Value Indicators

A. Amount of Data:

1. Statistical Significance: A larger sample size of comparable properties or market data generally leads to a more reliable value indicator. This is rooted in statistical theory, where larger samples reduce the standard error of the estimate.

   • Formula: Standard Error (SE) = SD / √n, where SD is the standard deviation and n is the sample size.
   • Practical Application: When using the Sales comparison approach❓❓, aim for a minimum of three strong comparables. A greater number of comparables, especially when supported by independent verification, increases confidence in the indicated value.
   • Experiment: Simulate the impact of sample size. Collect sales data for 100 similar properties. Randomly select samples of varying sizes (n=3, 5, 10, 20) and calculate the mean sales price for each sample. Observe how the range of mean values narrows as the sample size increases.

2. Data Detail: Value indicators based on more detailed and verified data are generally more reliable.

   • Example: In the cost approach, using detailed cost breakdowns from a professional costing service (e.g., Marshall & Swift) is more reliable than relying on rule-of-thumb cost estimates.

3. Independent Sources: Support by multiple independent sources❓❓ increases reliability.

   • Practical Application: Verify sales data from multiple sources (county records, MLS, real estate agents) to minimize the risk of inaccuracies.

B. Accuracy of Value Indicators:

1. Data Verification: Verified data is more accurate.

   • Practical Application: Always confirm sales data with at least one party involved in the transaction (buyer, seller, agent) and review supporting documentation.

2. Technique Relevance: The chosen appraisal technique must be appropriate for the appraisal problem.

   • Example: The income capitalization approach is highly relevant for income-producing properties but less suitable for single-family residences where rental income is not the primary driver of value.

C. Relevance of Value Indicators:

1. Consistency with Assignment: The value indicator must align with the purpose and scope of the appraisal assignment.

   • Example: If appraising for market value, consider sales in an open market without undue stimulus.
   • Book example: A report prepared to determine a partial property interest for tax purposes would hardly be relevant in obtaining a loan.

2. Appropriate Technique: The technique should match the property type and market conditions.

   • Example: Sales comparisons may be less relevant in a thin market with few recent transactions.

IV. Mathematical Considerations and Statistical Tools

A. Weighted Average: While simple averaging is discouraged, a weighted average can be a useful tool in understanding different weighting scenarios in reconciliation.
* Formula: Weighted Average = Σ (Weight * Value Indicator) / Σ Weight. The weights assigned should be justifiable and reflect the appraiser’s judgment regarding the reliability of each indicator.
* Example: Approach A (Sales Comparison): \$300,000 (Weight=0.5), Approach B (Cost): \$280,000 (Weight=0.3), Approach C (Income): \$290,000 (Weight=0.2). Weighted Average = (0.5 * 300,000) + (0.3 * 280,000) + (0.2 * 290,000) / (0.5 + 0.3 + 0.2) = \$291,000.

B. Sensitivity Analysis: Analyze how changes in key assumptions (e.g., discount rate, growth rate, market rent) affect the value indicators derived from different approaches.

C. Regression Analysis: If sufficient data is available, regression analysis can statistically assess the relationship between various property characteristics and sales prices, providing insights for adjustments in the sales comparison approach.

V. Reconciliation within the URAR (Uniform Residential Appraisal Report)

A. Understanding the URAR Format: Familiarize yourself with the structure of the URAR, specifically the reconciliation section on Page 2 and the supplementary space on Page 3.
* Listing Appraisal Approaches Used: Be clear on which approaches were used (sales comparison, cost, income).
* Stipulating Value Opinion: State the Market Value clearly.
* Acknowledging Appraisal Contingencies: Note if “as is”, or “subject to” repairs or alterations.
* Documenting and listing Conditioning Factors: Any conditions that affect the appraisal are to be listed.

B. Justifying the Final Value Opinion: The URAR requires a concise explanation of how the value indicators were reconciled. Clearly state which approach was given the most weight and why.
* Example: “The sales comparison approach was given the most weight due to the availability of numerous recent and comparable sales in the subject’s neighborhood. While the cost approach provides a supporting value indication, it is less reliable in this market due to the age of the subject property.”

VI. Common Reconciliation Pitfalls to Avoid

A. Averaging: Avoid simply averaging value indicators without a critical assessment of their reliability. This ignores the statistical principles underlying the valuation process.

B. Over-Reliance on One Approach: Do not automatically favor one approach (e.g., sales comparison) without considering the specific characteristics of the property and the availability of data for other approaches.

C. Confirmation Bias: Guard against unconsciously favoring value indicators that support a pre-determined opinion. Maintain objectivity throughout the reconciliation process.

VII. Practical Application: Case Study and Experiment

A. Case Study: Provide a detailed case study of a single-family residential appraisal where all three approaches to value were developed. Walk through the reconciliation process step-by-step, explaining the weighting applied to each indicator and the rationale behind the final value opinion.

B. Experiment: Provide an appraisal case with incomplete, poor, or unreliable information. Ask the class to create their opinion of value, and justify the weight given to each approach, in order to have the work pass muster in a critical review.

VIII. Conclusion

Reconciliation is a critical and scientifically grounded element of the appraisal process. By applying statistical principles, understanding the factors influencing the reliability of value indicators, and adhering to USPAP guidelines, appraisers can arrive at well-supported and defensible opinions of value, essential for building a successful career in real estate appraisal.