AVM Glossary

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  • d

  • Direct market models analyze how various housing characteristics influence sales prices in a particular period and geographic area. These models typically describe market value as a function of a property’s location and physical attributes. Direct market models are noted for their superior accuracy compared to other approaches; however, their substantial data requirements often result in a lower percentage of usable valuations, as many states lack sufficiently detailed property records to fuel this type of AVM. Hedonic models are location-specific and therefore difficult to generalize(...)
  • Discrete data are qualitative items that have three or more predefined values (for example, topography: level, rolling, or steep).
  • A variable for which it is not conceivable that, given any two observed values, a value lying between them may occur. For example, the number of rooms in a house is a discrete variable, but the living area of the house is not. See binary variable and continuous variable.
  • The degree to which data are distributed either tightly or loosely around a measure of central tendency. Measures of dispersion include the average deviation, coefficient of dispersion, coefficient of variation, range, and standard deviation.
  • A set of robust nonparametric methods whose interpretation or reliability does not depend on stringent assumptions about the distribution of the underlying population from which the sample has been drawn. See parametric statistics.
  • See binary variable.
  • e

  • (1) A cause of depreciation that is a loss in value as a result of impairment in utility and desirability caused by factors outside the property's boundaries. (2) Loss in value of a property (relative to the cost of replacing it with a property of equal utility) that stems from factors external to the property. For example, a buggy-whip factory, to the extent that it could not be used economically for anything else, suffered substantial economic obsolescence when automobiles replaced horse-drawn buggies.
  • The typical age of a structure equivalent to the one in question with respect to its utility and condition, as of the appraisal date. Knowing the effective age of an old, rehabilitated structure or a building with substantial deferred maintenance is generally more important in establishing value than knowing the chronological age.
  • From a regulatory standpoint, effective challenge of an AVM requires critical analysis by objective, informed parties that can identify model limitations and produce appropriate changes; effective challenge depends on a combination of incentives, competence and influence.
  • The extent to which an organization will be able to use a particular AVM or AVM cascade for a specific application. Analysts frequently measure efficiency or ‘usability’ through various hit rates, especially usable hit rates.
  • (1) The responsiveness of supply and demand to changes in price. Supply or demand that changes rapidly in response to price changes is "elastic." Supply or demand that changes slowly in response to price changes is "inelastic." (2) A measure of the responsiveness of tax yields to changes in economic conditions. The yield of an elastic tax increases rapidly in a growing economy. The yield of an inelastic tax increases slowly. Often measured by the formula: percent change in tax ÷ percent change in personal income.
  • The difference between the actual value of a variable and the expected value of the variable exclusive of sampling problems. Errors may be positive or negative, although in common speech taking the absolute value of the errors is sometimes implied. In multiple regression analysis, the term "error" is often used loosely to mean residual.
  • See real estate.
  • The estimated Market Value as of a specified date.
  • A measure of distance between two points “as the crow flies”. In property valuation it is used to find the nearest neighbor, or similar property based on an index of dissimilarity between property location, or attributes. When using multi-variate selection the squared difference is divided by the standard deviation of the variable so as to normalize the differences. Also see Minkowski Metric
  • That part of statistical practice concerned with reviewing the data set to isolate structures, uncover patterns, or reveal features that may improve the confirmatory analysis.
  • A symbol usually written to the right and above an expression to indicate particular mathematical operations. For example, 62 means 6 × 6, or six squared. Fractional exponents indicate inverse operations; for example, an exponent of 1/2 signifies a square root. Exponents are also called powers. Valuation models make use of the following properties of exponents: A number raised to the exponent 0 is always 1.00; zero raised to any power is zero; any number raised to the power 1 is itself. Negative numbers cannot have exponents less than 1.
  • f

  • (1) An underlying characteristic of something (such as a house) that may contribute to the value of a variable (such as its sale price), but is observable only indirectly. For example, construction quality is a factor defined by workmanship, spacing of joists, and materials used. Factor definition and measurement may be done subjectively or by a computer-assisted statistical algorithm known as factor analysis. (2) Loosely, any characteristic used in adjusting the sale prices of comparables. (3) The reciprocal of a rate. Assessments may be equalized by multiplying them by a factor equal(...)
  • An AVM Performance Metric that measures a combination of accuracy and precision. The mean absolute error percentage sales error for properties for which the AVM fails to predict selling prices to within +/- (a given percentage, for example, +/- 15%).
  • An AVM Performance Metric that measure a combination of accuracy and precision. The median absolute error percentage sales error for properties for which the AVM fails to predict selling prices to within +/- (a given percentage, for esample, +/- 15%).
  • An AVM Performance Metric that measures a combination of accuracy and precision. The percentage of properties for which the AVM fails to predict selling prices to within +/- (a given percentage, for example, +/- 10%).
  • According to the federal banking agencies’ appraisal regulations, any real estate-related financial transaction that requires a real estate appraisal.
  • Appraisal of properties one at a time for pay.
  • In land ownership, complete interest in a property, subject only to governmental powers such as eminent domain. Also fee simple absolute. See estate in fee simple; fee; and absolute ownership.
  • See adaptive estimation procedure.
  • The practice of reviewing the reasonableness of assessments by viewing the properties in question, sometimes by examining their interiors but more often by looking at their exteriors.
  • Any of a number of kinds of graphic descriptions of an algorithm, showing the operations, data flow, equipment, and so on.
  • A measure of the expected error range of an estimate by an AVM, expressed as a percentage or a decimal. The lower the FSD, the higher the confidence in the precision of the estimate. Example: if the FSD for an estimate is 10%, then the expectation is that 68% of the time the actual market value will fall within +/- 10% of the model estimate.
  • Estimate of value for subject property at a point in time in the future.
  • An AVM that forecasts future changes in property values based on a wide range of macroeconomic variables.


a)       AVMetrics

b)      AVMs 201: A Practical Guide to the Implementation of Automated Valuation Models, Jim Kirchmeyer, 2008.

c)       IAAO 2015, Glossary for Property Appraisal and Assessment, 2015. (2013 online: https://www.iaao.org/media/Pubs/IAAO_GLOSSARY.pdf )

d)      Collateral Assessment & Technologies Committee, Summary of Definitions & Terms, 2006.

e)      Joint Industry Task Force on AVMs, IAAO Standard on AVM Glossary, September 2003. https://www.iaao.org/media/standards/AVM_STANDARD.pdf

f)        Appraisal Institute, Joint Industry Task Force on Automated Valuation Models, Work Group Terminology, 2005.

g) Merriam-Webster (https://www.merriam-webster.com/)