Reconciliation and Final Value Opinion

Chapter 11: Reconciliation and Final Value Opinion

I. Introduction: Understanding Reconciliation in Valuation

Reconciliation is a crucial step in the valuation process, representing the synthesis of various value indicators into a single, defensible opinion. It is not a mere averaging of values, but a reasoned judgment based on the appraiser’s expertise and a thorough analysis of the data. This chapter will explore the theoretical underpinnings and practical application of reconciliation, equipping you with the skills to form credible final value opinions.

II. The Science of Reconciliation: Principles and Theories

Reconciliation leverages several scientific principles to arrive at a robust value opinion:

• A. Statistical Inference: The reliability of value indicators is inherently linked to the underlying data’s statistical properties.

  • 1. Law of Large Numbers: Indicators derived from larger datasets are generally more reliable. A greater sample size reduces the influence of outliers and idiosyncratic factors. Let n be the sample size, x̄ be the sample mean, and μ be the population mean. As n increases, x̄ converges to μ.
  • 2. Central Limit Theorem: Even if the underlying data distribution is not normal, the distribution of sample means approaches normality as n increases. This allows us to use statistical methods to estimate the confidence interval for the true value. The standard error of the mean is σ/√n, where σ is the population standard deviation.

  • B. Decision Theory: Reconciliation involves making decisions under uncertainty. We weigh the evidence from different indicators, considering their respective strengths and weaknesses, to minimize the risk of error in our final value opinion.

  • 1. Bayesian Inference: Value indicators can be treated as pieces of evidence that update our prior beliefs about the value of the property. Bayes’ theorem states: P(A|B) = [P(B|A) * P(A)] / P(B), where P(A|B) is the probability of hypothesis A (e.g., value being within a certain range) given evidence B (e.g., a particular value indicator).
  • C. Information Theory: Each value indicator provides information about the property’s worth. Reconciliation involves extracting and synthesizing the most relevant information while minimizing the noise and bias inherent in each indicator.
  • D. Regression Analysis Principles: Adjustments in sales comparison rely on regression principles, estimating the impact of specific variables on price. Adjustments are more reliable when grounded in market data reflecting those impacts.

III. Steps in the Reconciliation Process

The reconciliation process involves the following steps:

• A. Review and Verification: Thoroughly scrutinize all data, calculations, and reasoning underlying each value indicator.

  • 1. Check for arithmetical errors in calculations for all appraisal approaches.
  • 2. Ensure consistent application of techniques to subject and comparables.
  • 3. Validate data sources, noting any potential biases or limitations.

  • B. Assess Reliability: Evaluate the strengths and weaknesses of each value indicator.

  • 1. Amount of Data: Indicators supported by larger and more detailed datasets are generally more reliable.
  • 2. Accuracy of Data: Verify the accuracy of the data sources used to derive each indicator.
  • 3. Relevance to the Appraisal Problem: Consider the relevance of each indicator to the specific characteristics of the subject property and the purpose of the appraisal.

  • C. Weighing Value Indicators: Assign weights to different value indicators❓❓ based on their assessed reliability and relevance.

  • 1. The appraiser’s judgment is the primary determinant, guided by experience and market knowledge.
  • 2. Consider the type of property. The income approach is more relevant for income-producing properties, while the sales comparison approach❓❓ is often preferred for residential properties.
  • 3. Consider the availability and reliability of data. If the cost approach relies on outdated cost manuals, it might be given less weight.
  • D. Forming a Final Value Opinion: Synthesize the weighted value indicators into a single, well-supported opinion of value.
  • E. Documentation: Clearly articulate the reasoning behind the chosen value and the weights assigned to each indicator in the appraisal report.

IV. Factors Influencing the Reliability of a Value Indicator

The reliability of a value indicator depends on several key factors:

• A. Amount of Data: A larger statistical sampling of data leads to more reliable value opinions.
• B. Accuracy of Data: Verified data leads to more reliable value opinions.

• C. Relevance of Technique: Choose the most appropriate technique for the specific appraisal problem.

  • 1. The technique used must be consistent with the terms of the appraisal assignment.
  • 2. The indicator itself must be derived in accordance with the terms of the appraisal assignment.

V. Practical Applications and Experiments

• A. Sales Comparison Approach: A value indicator derived by the sales comparison approach depends on how comparable sales data was verified. More reliable comparable properties are closer to the appraised property and require fewer adjustments.
• B. Cost Approach: A value indicator derived by the cost approach depends on reliable cost service used for the appraisal. An experiment can be comparing cost service A to cost service B, and verifying which cost service most accurately reflects the replacement value of the appraised property.
• C. Income Capitalization Approach: A value indicator derived by the income capitalization approach is least relevant to a single-family residence. An experiment can be comparing the property value estimate with the cost approach and the sales comparison approach and determining that the sales comparison approach most accurately estimates the property value.

VI. Mathematical Examples

While averaging is not the correct reconciliation process, mathematical tools can help inform the appraiser’s judgment.

• A. Weighted Average: Assign weights (percentages) to each indicator reflecting its reliability and relevance, and calculate a weighted average.

  • Value = (w1 * V1) + (w2 * V2) + (w3 * V3),
    • where:
      • V1, V2, V3 are the values from each approach.
      • w1, w2, w3 are the weights assigned to each approach (w1 + w2 + w3 = 1).
  • B. Sensitivity Analysis: Vary the weights assigned to each indicator to assess how the final value opinion changes. This helps identify the key drivers of value and the sensitivity of the opinion to changes in assumptions.

VII. Understanding and Applying Adjustments

• A. Qualitative Analysis: Describe the adjustments applied to the comparable properties with phrases like “inferior,” “similar,” or “superior.” However, be specific and descriptive when presenting the adjustment rather than generic language.
• B. Quantitative Analysis: Apply numerical dollar or percentage adjustments to comparable property characteristics. Apply quantitative adjustments based on the UAD.

VIII. Final Value Opinion

The appraiser must choose a value that is supported by the evidence, and the appraiser’s judgment must be the determining factor. The opinion of value of an appraised property is stated as a single dollar amount (point estimate) or as a range in which the property’s value is most likely to fall. Value opinions should be rounded.

IX. The Importance of Clear Communication

Ensure the appraisal is easily understandable to a non-appraiser reader. A well-written and logically presented report builds confidence in the appraiser’s opinion and withstands critical review.