Reconciliation and Final Value Opinion

Chapter 11: Reconciliation and Final Value Opinion

I. Introduction: Integrating Scientific Rigor into the Valuation Process

This chapter, “Reconciliation and Final Value Opinion,” is the culminating step in the land valuation process using the Sales Comparison Approach (SCA), a core skill for appraisers❓, real estate professionals, and investors. It addresses the critical stage of synthesizing multiple value indicator❓s derived from comparable property analysis into a single, defensible value opinion. We move beyond mere arithmetic averaging and explore a more scientific and judgment-driven approach to ensure accuracy and credibility. The chapter emphasizes that while mathematical formulas❓ have no role in reconciliation, a sound understanding of statistical concepts and their limitations is essential for informed decision-making. All the calculations performed during the application of the Sales Comparison approach must be checked for accuracy to reduce errors, and build trust with the lender/client.

II. The Science of Reconciliation: Beyond Averaging

A. Defining Reconciliation

Reconciliation is not a mathematical averaging process. It is the process of critically analyzing and weighing the reliability and relevance of different value indications to arrive at a single, supported opinion of value for the subject land.

Reconciliation is used to:

1. Synthesize value indicators: From different comparable properties, adjustments, units of comparison, or even different appraisal techniques (though this course emphasizes the SCA).
2. Achieve a single Point Estimate: Or a defined range of value (“Range Value”) that accurately reflects the land’s fair market value as stated in the book content.

B. Reliability and Relevance: The Cornerstones of Reconciliation

The scientific rigor of reconciliation hinges on the appraiser’s ability to:

1. Assess Data Reliability: Quantify the confidence in the data used to derive each value indicator.
2. Judge Indicator Relevance: Evaluate how well each value indicator applies to the specific appraisal problem and property characteristics, as dictated by the appraisal assignment.

This process aligns with the course description by emphasizing a skilled, analytical approach over rote calculations, ultimately leading to a fair market value determination.

C. Statistical Considerations: Data Sufficiency and Error

1. sample size❓❓ and Statistical Power: A larger sample size (more comparable properties) generally leads to more reliable value indicators. This principle is rooted in statistical theory:

   • Let ‘n’ be the sample size (number of comparable properties).
   • As ‘n’ increases, the statistical power (probability of detecting a true effect, i.e., the true market value) increases, and the confidence interval around the estimated value narrows.
   • Formula for Standard Error: $$SE = \frac{s}{\sqrt{n}}$$ , where ‘s’ is the standard deviation of the data. A larger ‘n’ reduces the standard error.

2. Data Variation and Uncertainty: Real estate data inherently contains variation. Appraisers must acknowledge and account for this:

   • Sources of Variation: Differences in comparable properties, market conditions, data quality, and appraiser judgment.
   • Mitigation Strategies: Use of statistical measures (standard deviation, coefficient of variation) to quantify data spread and inform the weighing of value indicators.
   • The effect of statistical analysis: The results of statistical analysis and the proper management thereof will reduce errors and increase accuracy.
3. Error Analysis:
   * Errors can appear in the process and the identification, management, and remediation of errors can be a part of the reconcilliation process.

III. Practical Application: A Land Valuation Experiment

Consider the following land valuation scenario:

• Subject Property: 1-acre vacant lot in a suburban area.
• Comparable Properties:
  • Comparable 1: 0.9 acres, recently sold for \$200,000. Located within the same subdivision. Minimal adjustments required.
  • Comparable 2: 1.1 acres, sold 6 months ago for \$230,000. Located in a neighboring, slightly more desirable subdivision. Adjustments needed for location and time.
  • Comparable 3: 1 acre, sold a year ago for \$190,000. Located in a more distant, less desirable area. Significant adjustments for location and time.

A. Applying the Sales Comparison Approach

1. Comparable 1: \$200,000 (Minimal adjustments)
2. Comparable 2: \$230,000 - \$10,000 (Location) - \$5,000 (Time) = \$215,000
3. Comparable 3: \$190,000 + \$20,000 (Location) + \$10,000 (Time) = \$220,000

B. The Reconciliation Process

1. Data Reliability:

   • Comparable 1: High reliability due to proximity, recent sale, and minimal adjustments. Data was verified with the title company.
   • Comparable 2: Medium reliability. Adjustments are subjective and based on market analysis. Data was verified with the seller.
   • Comparable 3: Low reliability due to significant adjustments and location differences. Data was verified with the real estate agent.

2. Relevance:

   • Comparable 1: Highly relevant due to similarity and proximity.
   • Comparable 2: Moderately relevant. Location adjustment introduces subjectivity.
   • Comparable 3: Least relevant due to location and age of the sale.

3. Weighing Value Indicators:

   • Given Comparable 1’s high reliability and relevance, it should receive the most weight.
   • Comparables 2 and 3 provide supporting evidence but are less influential due to data limitations.

4. Final Value Opinion:

   • The appraiser, considering the above factors, might conclude a value of \$205,000. This is not an average; it’s a carefully considered judgment reflecting the strengths and weaknesses of each value indicator.

C. Experiment Extension: Sensitivity Analysis

To further test the robustness of the value opinion, conduct a sensitivity analysis:

1. Vary Adjustment Amounts: What if the location adjustment for Comparable 2 was +/- \$5,000? How would this affect the final value opinion?
2. Change Data Weighting: What if market data indicated that the neighboring subdivision was more similar than initially thought? How would this change the weighting of value indicators?
3. Evaluate Impact: Document how sensitive the final value opinion is to changes in assumptions. If the value is particularly sensitive to a small change in assumptions, the accuracy can be improved by increasing the sample size, or refining the technique used to estimate certain values.

This experiment reinforces the appraiser’s role as an analyst and critical thinker, not just a calculator.

IV. Mathematical Considerations: Limitations and Caveats

While mathematical averaging is inappropriate for reconciliation, some statistical concepts can inform the process:

A. Weighted Average (Used for Illustration Only, Not as a Primary Method)

A weighted average might be calculated after the appraiser has made the judgmental decision about relative reliability:

• Assign weights (ranging from 0 to 1, sum to 1) based on the reliability and relevance of each comparable.
• For example: Comparable 1 (Weight = 0.5), Comparable 2 (Weight = 0.3), Comparable 3 (Weight = 0.2)
• Weighted Average Value = (0.5 * \$200,000) + (0.3 * \$215,000) + (0.2 * \$220,000) = \$209,500

Important Caveat: The weights themselves are subjective and must be justified based on market data and appraisal judgment. This should not be used alone to determine value.

B. Measures of Central Tendency

The book refers to point estimate and range value. This is also an important calculation to look at when it comes to looking at the mean median and mode:

1. In some appraisals you can make a case for the mean. It is often the fairest determination of a value given the high and low data points.
2. In other cases the median can help. However, if a property is particularly higher or lower than the data set, it will not affect it.
3. The mode is the data set that occurs the most.

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

1. The appraiser is asked to provide values for the Sales Comparison, Cost, and Income approaches.
2. The appraiser reconciles if there are additional approaches used.
3. The appraiser states if the property is being appraised “as is,” “subject to repairs or alterations based on a hypothetical condition,” and “subject to inspection based on an extraordinary assumption.” Any extraordinary assumptions must be written into an addendum.
4. The market value and effective date of the property.

VI. Conclusion: Scientific Judgment in Land Valuation

Reconciliation is the bridge between data analysis❓ and value judgment. By carefully considering data reliability, market relevance, and the limitations of mathematical approaches, appraisers can arrive at well-supported, defensible value opinions that meet the requirements of USPAP and the expectations of clients and stakeholders. It is scientific reasoning and clear communication, not just calculations, that define a credible land valuation expert.

VII. Review of key terms

1. Market Rent
2. Contract Rent
3. Point Estimate
4. Range Value
5. Reliability
6. Relevance
7. Adjustments
8. Gross Adjustments
9. Net Adjustments

By following these steps, the student has made a case for how the final value opinion was made using data and information and is well prepared for their career.