Qualitative Analyses in the
Sales Comparison Approach
Revisited
abstract
Most practicing
by Gene Rhodes, MAI
appraisers agree that
when analyzing a group
of five or six compa-
T
rable sales with four or
five value-influencing
his article is written with the sole intent of further advocating qualitative
analyses of comparable sales through an objective ranking system. The qualitative
ranking technique has been promoted by such leading valuation thinkers and
scholars as Henry Babcock, Gene Dilmore, Richard Ratcliff, James Graaskamp,
and others. It was most recently defended by D. Richard Wincott, MAI, in the
Fall 2012 issue of The Appraisal Journal.
The discussion that follows is that of an ordinary practitioner who has spent
many years investigating property sales and trying to answer a single, but most
important and complex question: “Why did the property sell for that price?” When
appraisers approach the analysis of a comparable sale in that manner, they lay
the foundation for developing an objective and sound opinion of the value of
the appraised property. This article attempts to assist in developing answers to
the question and is written with the intent of guiding field appraisers in their
analyses of comparable sales in relation to the appraised property and with the
hope that it may help in achieving more reliable results.
differences, it is often
quite difficult to extract
the appropriate adjustments through paired
sales analysis. The
appraiser’s objective
should be to simulate
the actions and thought
processes of the buyers who acquired the
comparable sales.
These buyers do not
typically have a list of
comparable sales on
which they make plus
and minus adjustments
An Attribute Scoring and Analysis System
for the observed differ-
As indicated above, the subject of this article is qualitative analysis, as opposed
to the more traditional and more commonly accepted application of quantitative adjustments. Ultimately, however, the qualitative analyses, as suggested
herein, lead to market-supported and convincing quantitative adjustments. While
quantitative adjustments are grounded in paired sales analyses, most appraisers
recognize that there are almost always multiple value-impacting variables among
a typical set of five or six good comparable sales. These multiple differences
make it quite difficult, if not impossible, to extract adjustments for each material
feature that may have impacted the price paid for the comparable properties.
As a result, the appraiser’s adjustments for property characteristics typically
stem from either subconscious qualitative analyses or subjective judgment, or
a combination of both.
The analysis technique discussed herein may adequately be described as an
attribute scoring and analysis system. The use of an attribute scoring system was
presented by James A. Graaskamp, noted professor and chair of real estate at the
University of Wisconsin–Madison, at a national meeting of the Appraisal Institute
ences in formulating
Qualitative Analyses in the Sales Comparison Approach Revisited
a purchase decision.
They do, however, go
through the process of
qualitative analyses.
This article attempts to
demonstrate how easily
qualitative analysis can
lead to objective and
market-supported quantitative adjustments.
The Appraisal Journal, Fall 2014
281
(then the American Institute of Real Estate
Appraisers) in 1987. Graaskamp’s ideas and thought
processes were most notably set forth in the monograph and demonstration appraisal report titled The
Appraisal of 25 N. Pickney: A Demonstration Case for
Contemporary Appraisal Methods.1 Graaskamp often
used what he termed “price sensitive attributes” in
appraisals and research papers.2 Thus, applications
of this analytical process are entirely attributable to
Graaskamp’s knowledge of real estate and appraisal
methodology, especially to his intellect and ability
to think beyond commonly accepted techniques.
Readers are asked to be open to the premise that
new methods or techniques may produce more reliable and convincing results when considering the
analytical processes presented herein. The intent of
this article is to offer further support of Graaskamp’s
valuation methodologies and expand on D. Richard
Wincott’s more recent and excellent discussion of
this topic in The Appraisal Journal.3
The sales comparison approach in the appraisal
process is focused on comparable sales. In the
analysis of each of the comparable sales, the central
question should be, “Why did this property sell for this
particular price? And the extension of this question
is: “Given these sale prices and their respective
sale conditions and characteristics, what do they
indicate as a reasonable selling price/market value
for the subject property, considering its conditions
and characteristics? To answer these questions, the
appraiser must examine aspects inherent in the sale
transaction itself and features related to the physical
characteristics of the property, including its location.
An investigation of each sale transaction may
reveal specific conditions that impacted the sale price,
regardless of locational and physical characteristics.
Such differences in sale and market conditions
lead to transactional adjustments. Transactional
adjustments include real property rights conveyed,
financing terms, conditions of sale, expenditures
made immediately after purchase, and market
conditions.4 Transactional adjustments are made
initially so that the comparable sales and the subject
are on an equal basis prior to making adjustments
for locational and physical differences. Since
transactional adjustments are often quantifiable, this
article, which deals with qualitative adjustments,
focuses on location and physical characteristics and
influences. As The Appraisal of Real Estate states,
A major premise of the sales comparison approach
is that an opinion of the market value of a property
can be supported by studying the market’s reaction to
comparable and competitive properties.5
Comparative analysis is the general term used to identify
the process in the sales comparison approach in which
quantitative and qualitative techniques are applied to
comparable sales data to derive a value indication. An
appraiser may use both quantitative adjustments and
qualitative analysis in comparative analysis.6
The following discussion attempts to illustrate how
qualitative analysis can lead to appropriately supported quantitative adjustments, both of which are
recognized for use by the Appraisal Institute.
Qualitative Analysis Framework
To set the framework for this article, think of two
jars filled with marbles of value. If each marble has
the same value, the value of each jar can be determined by simply counting the number of marbles
in the jars. If each marble is worth $1.00 and Jar
A contains 50 marbles, it is less valuable than Jar
B with 70 marbles. However, if the marbles have a
different value based on their colors, Jar A can be
more valuable than Jar B if it has a higher ratio of
the more expensive colored marbles.
Although the analytical process set forth
herein can be used equally well when analyzing
an improved property, as will be subsequently
illustrated, the primary discussion is focused on an
appraisal of a vacant parcel of land. With the few
exceptions related to contaminated properties and
other atypical conditions, every parcel of land has
what may be referred to as a base value, just because
it is a piece of real estate and some demand exists
or it. The level of demand, coupled with available
supply, is the primary driver of its base value. Clearly
1. James A. Graaskamp, The Appraisal of 25 N. Pickney: A Demonstration Case for Contemporary Appraisal Methods (Madison, WI: Landmark Research,
Inc., 1977), 71–77.
2. These papers are available for review through the University of Wisconsin Digital Collections at http://uwdc.library.wisc.edu/collections/RealEstate
/Graaskamp.
3. D. Richard Wincott, “An Alternative Sales Analysis Approach for Vacant Land Valuation,” The Appraisal Journal (Fall 2012): 310–317.
4. Appraisal Institute, The Appraisal of Real Estate, 14th ed. (Chicago: Appraisal Institute, 2013), 392, 405.
5. Ibid., 377.
6. Ibid., 396.
282
The Appraisal Journal, Fall 2014
Qualitative Analyses in the Sales Comparison Approach Revisited
with all other things being equal, land prices rise and
fall in concert with the pressures stemming from
the interrelationships of supply and demand. Land
parcels that are reasonably comparable and located
in a given market area may have similar base values
but sell for significantly different prices because they
have observably different locational and physical
attributes; these are what Graaskamp referred to as
“price sensitive attributes.”
The property’s physical attributes of prime
importance to the market and the appraiser are its
characteristics that may have been most important to
the purchasers of the comparable sales and that may,
in turn, be most important to a prospective purchaser.
For an unimproved parcel of land, the most important
physical attributes may be overall location, size, corner
influence, topographic characteristics, exposure,
the use permissible by zoning, etc. For an improved
property, the most important attributes may be quality
of construction, age and condition of the improvements,
land-to-building ratio, visibility/exposure, overall
location, occupancy at the time of sale, etc.
In laying the groundwork for an additional
understanding of qualitative analysis, follow the
thought processes of prospective purchasers who
have just been shown five single-family houses that
meet their criteria and for which they have been
prequalified. Upon returning to the broker’s office, the
broker asks the prospective purchasers the expected
question: “What do you think of the houses you looked
at?” Suppose the responses were something on the
order of Property 1 was okay; there were some things
we liked and some that we didn’t; it may be worth
considering. Property 2 absolutely did not interest us;
the room layout and architectural style are not for us.
Property 3 we didn’t like it too much; we’d probably put
it toward the bottom of the list. Property 4 we thought it
was outstanding; we liked everything about it. Property
5 impressed us very much; we liked it a lot, but not
quite as much as Property 4. Based on these responses,
qualitative ratings for the attribute of purchaser appeal
can be assigned, using a ranking of excellent, good,
average, fair, and poor:
Property 1
Property 2
Property 3
Property 4
Property 5
Average
Poor
Fair
Excellent
Good
Qualitative Analyses in the Sales Comparison Approach Revisited
The five quality ratings of excellent, good, average,
fair and poor generally encompass the spectrum of
quality ratings most observers would assign to items
being examined for relative levels of quality. Within
the data set, including the appraised property, the
attribute(s) of a property that stands out as being
most superior would be rated excellent, and the
attribute(s) that stands out as being most inferior
would be rated poor. For those property attributes
that are rather ordinary, being somewhere near the
midpoint between the best and worst on the quality
scale, a rating of average would be appropriate. If the
attribute is better than average, but does not rise to the
level of excellent, it would be rated good. Similarly,
if the attribute is below average but does not deserve
a rating of poor, it is assigned a quality level of fair.
Now consider a simplistic view of two
development sites, Parcel A of 50,000 square feet
and Parcel B of 40,000 square feet. It is a given that
with all other things being equal, Parcel A is more
valuable, simply because it has a greater number
of productive units in measure of square feet of
land area. So, setting aside any differential in value
per square foot attributed to the 10,000-square-foot
difference in size, and with all other things being
equal, if Parcel A recently sold for $500,000, it is
reasonable to assume that Parcel B has a value of
$400,000 since Parcel A sold at a price of $10.00
per unit (square feet). Now assume that Parcel A
and Parcel B are equal in all other features except
for location. With all other things being equal, it is
reasonable to expect that the site with the superior
location will be the more valuable. Consider that
the characteristic of location is also comprised
of units. Therefore, the site that has the superior
location has more units of location than does the
inferior site. Both sites have a highest and best use
for commercial development. Parcel A is located on a
secondary thoroughfare and lies adjacent to existing
improvements that are not well maintained, whereas
Parcel B is located on a heavily traveled thoroughfare
in an area of recent development activity. Thus, since
Parcel B has more units of superior location than
Parcel A, its value per square foot of land area may
reasonably be expected to be higher.
In taking this analysis of comparables to extremes,
enter Parcels C, D and E, each also having a highest
and best use for commercial development. Parcel C is
located on a major thoroughfare near the intersection
of another major arterial street at the center of business
The Appraisal Journal, Fall 2014
283
activity. Parcel D is located on a secondary street in a
transitional area between commercial and residential
uses. Parcel E is located on an important arterial
street and is surrounded by stable, well-maintained
commercial developments. On a quality rating or
ranking scale of excellent, good, average, fair and poor,
Parcel C is rated excellent, Parcel B is rated good, Parcel
E is rated average, Parcel A is rated fair, and Parcel D is
given a relative rating of poor. This qualitative analysis
can be used in developing quantitative adjustments
by assigning numerical values to the quality ratings
according to the following scale:
Excellent50
Good40
Average30
Fair20
Poor10
It is important to note that any range of numbers can
be used as long as the spread between the numbers
is the same, for example 25, 20, 15, 10, 5, or 100, 80,
60, 40, 20, or 5, 4, 3, 2, 1.
Using the quality rating scale, if Parcel A, with a
quality rating of fair and a point score of 20, sold for
$10.00 per square foot, it also sold for the equivalent of
$0.50 per square foot per quality rating score, assuming
there were no other elements affecting value. Likewise,
if Parcel B, with a quality rating of good and a point
score of 40, sold for $15.00 per square foot, it sold for
the equivalent of $0.375 per square foot per quality
rating score. The average of the two sale prices per
square foot per location quality rating score is $0.44
(rounded). Thus, with the recognized limitations of
only two sales, and the assumption that there are no
other elements affecting the value of the five properties,
the data would indicate a value of $22.00 per square
foot for Parcel C with quality rating of excellent ($0.44
x 50), $13.20 per square foot for Parcel E with a quality
rating of average ($0.44 x 30), and $4.40 per square foot
for Parcel D with a quality rating of poor ($0.44 x 10).
This analytical process can be applied in everyday
appraisal situations where the properties that must be
analyzed have multiple attributes that affect value. It
has been observed that most appraisers of commercial
properties do not typically make more than five
adjustments for locational and physical differences.
Therefore, the following illustrations use the analysis
of five primary attributes, including location. The
illustrations are also based on the assumption
284
The Appraisal Journal, Fall 2014
that the cited prices of the comparable sales have
been adjusted appropriately for transactional
considerations, if necessary.
Case Study Analysis of a Lakefront Lot
Consider the appraisal of a lakefront lot on a large
reservoir within a convenient distance of a major
metropolitan area. The primary demand stems from
retirement and weekend or recreational users. For a
purchaser of a lakefront lot, it is reasonable to assume
that the quality of the lake view is a major consideration. Therefore, with all other things being equal, it
is reasonable to assume that a lakefront lot with an
unobstructed view of the lake and an evening sunset
is more valuable than a lot with only a partial view
and no opportunities for an over-the-lake sunset or
sunrise view. Thus, it may be safely concluded that
lake view is an important attribute of lakefront lots.
Reservoirs are constructed in areas that are
ideally suited for such purposes, much of which is
dictated by topographic conditions and availability of
feeder creeks and drainage areas. Thus, topographic
characteristics around a lake can range from gently
sloping to somewhat dramatic slopes. While the lots
with the steeper slopes often benefit from adjacent
water depth, they usually entail extra development
costs for site grading, extended piers, retaining
walls, etc. Topographic characteristics have been
considered as a price sensitive attribute.
The amount of lake frontage is clearly an
important attribute. When lake lots are fairly uniform
in shape and depth, the sale price per linear foot of
lake frontage may be the best unit of comparison.
However, due to the irregularities of many shore lines
and inconsistent lot sizes, the price per front foot may
be inappropriate and unreliable. In those instances,
the price per square foot is used and the extent of
lake frontage is treated as a price sensitive attribute.
As with residential properties in an urban
neighborhood, the approach to the property may have
a measurable impact on its value. In the case study,
some lakefront areas have access via paved roads and
pass through restricted subdivisions with attractive,
well-maintained homes. At the other extreme are
lakefront lots adjacent to subdivisions that originally
permitted mobile homes with few, if any, restrictions;
many of those mobile home units now are either poorly
maintained or are vacant and in need of demolition
or removal.
Qualitative Analyses in the Sales Comparison Approach Revisited
The operators of the lake/reservoir in question
allow lakefront home owners to construct private
boathouses adjacent to their lots, but the reservoir
is not a constant level lake. Therefore, under
drought conditions, which are not uncommon at
this particular location, the lake level may fall six
to seven feet, leaving some home owners with the
inability to use their boats. Some lots are known
as shallow water lots that are fine when the lake
is full, but render boathouses unusable when the
level falls three to four feet. Other lots are deep
water lots that benefit from steeply declining lake
bottoms or adjacency to old creek beds; these lots
allow boathouse usage year round, even under
most drought conditions. Realtors confirm that
water depth adjacent to the lot is an important
consideration in the minds of prospective lakefront
home owners.
Assume the appraisal of a lakefront lot on
a reservoir with the conditions described. The
appraiser has inspected the property, considered
preliminary data on recent sales, and selected and
confirmed the sale prices of six properties considered
to be most comparable to the subject. Transactional
adjustments have been made where necessary. What
remains is the analysis of the locational and physical
attributes. Following the inspection of the subject
and the comparables, the appraiser has concluded
that the five primary attributes affecting the sale
prices of the comparable sales are quality of lake
view, topographic characteristics, lakefront footage,
approach, and water depth.
Quality of Lake View
The appraised property has a lake view that is well
above average, effectively covering a range of about
120 degrees, but it does not have a direct over-the-lake
view of either the sunset or sunrise. Comparable 1 is
located on a promontory, has a lake view that is greater
than 180 degrees and has an unobstructed view of the
evening sunsets. Comparable 2 has a lake view that
spans about 90 degrees and has only a spring and summer view of an over-the-lake sunrise. Comparable 3 is
located on a cove that gives it lake frontage and water
access, but its view of the open lake, per se, is very
limited. Comparable 4 is also located on a cove, but the
cove is larger and the view of the lake is slightly better
than that of Comparable 3. Comparable 5 has an openwater view of the lake that spans about 100 degrees and
Qualitative Analyses in the Sales Comparison Approach Revisited
benefits from a variable view of the evening sunset.
Comparable 6 is located on a cove that gives it both
lake frontage and water access, but looks over a larger
finger of the lake, as opposed to the lake itself.
After inspecting the subject property and the
comparable sales, the following quality ratings,
which are relative among the data set, were indicated:
Property
Quality Rating
Score
Comparable 1
Excellent
50
Comparable 2
Average
30
Comparable 3
Poor
10
Comparable 4
Fair
20
Comparable 5
Good
40
Comparable 6
Fair
20
Subject
Good40
Topographic Characteristics
The subject property being appraised has gently
sloping topography that should not present any
unusual site preparation and construction problems;
plus, it contains several mature native trees that add
to the appeal of the lot. Comparable 1 has gently sloping features that should not present any construction
difficulties, but does not benefit from the advantages
of mature native trees. Comparable 2 has rather steep
slopes at the building site and extra site work will be
required at the time of construction; it has two large
oak trees located outside of the building pad site.
Comparable 3 has sloping topography but a level,
construction-ready building site completed by a prior
owner; it also has some native trees. Comparable
4 has gently sloping topography and some mature
trees that add to its appeal. Comparable 5 has gently
sloping topography but does not have any mature
trees. Comparable 6 has rather rough topographic
characteristics and only native scrub brush.
After inspecting the appraised property and the
comparable sales, the following quality ratings, which
are relative to the data set, were considered appropriate:
Property
Quality Rating
Score
Comparable 1
Average
30
Comparable 2
Fair
20
Comparable 3
Excellent
50
Comparable 4
Good
40
Comparable 5
Average
30
Comparable 6
Poor
10
Subject
Good40
The Appraisal Journal, Fall 2014
285
Lakefront Footage
The appraised property has 90 feet of frontage on the
lake line. The comparable sales have the following
approximate linear feet of lake frontage: Comparable
1, 97 feet; Comparable 2, 85 feet; Comparable 3, 105
feet; Comparable 4, 59 feet; Comparable 5, 70 feet; and
Comparable 6, 115 feet. The overall range of lake frontages is from a low of 59 feet to a high of 115 feet. The
quality ratings for this attribute can be objectively developed by creating a rating scale similar to the following.
Lakefront Linear Feet
Quality Rating
50–64Poor
65–79Fair
80–94Average
95–109Good
110–124Excellent
Thus, the comparable sales and the subject would
be rated and scored as follows.
Property
Quality Rating
Score
Comparable 1
Good
40
Comparable 2
Average
30
Comparable 3
Good
40
Comparable 4
Poor
10
Comparable 5
Fair
20
Comparable 6
Excellent
50
Subject
Average30
Approach
The quality of the approaches to the subject property
and the comparable sales is quite varied, ranging
from Comparable 2 with a rather wide and fully
improved access street through an established and
well-maintained subdivision of newer to mid-life
houses, to Comparable 6 with access via a narrow,
asphalt paved but poorly maintained street through an
older mobile home subdivision with vacant lots and
poorly maintained units. Based upon the inspections
of all properties, Comparable 2 is clearly deserving of
the highest quality rating of excellent and Comparable
6 is clearly deserving of the lowest quality rating of
poor. Access to the subject is through an older mobile
home subdivision but the street is wider and has been
well maintained. Comparable Sale Nos. 1 and 3 have
paved access through traditional subdivisions with
limited, but some signs of neglect. Comparable 4, like
the subject, has access via a well-maintained street,
but through an older and poorly maintained mobile
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The Appraisal Journal, Fall 2014
home subdivision. Comparable 5 has paved access
through mixed-quality residential areas that improve
significantly in the vicinity of the property.
After inspecting the subject property and the
comparable sales, the following quality ratings were
considered appropriate:
Property
Quality Rating
Score
Comparable 1
Average
30
Comparable 2
Excellent
50
Comparable 3
Average
30
Comparable 4
Fair
20
Comparable 5
Good
40
Comparable 6
Poor
10
Subject
Fair20
Water Depth
Detailed topographic maps are most helpful in analyzing the water depths at the probable location of a
boathouse adjacent to the waterfront of the lot. When
the subject lake is full, the water level is at an elevation
of 325 feet mean sea level (MSL). To allow for a safety
factor, the water depth at the location of the boathouse
should be at a minimum of about three feet. Since the
typical drought periods have not dropped the lake level
by more than seven feet, a minimum water depth of
ten feet is required for a reasonable expectation that
boat usage will not be affected by normal fluctuations
in the water level of the lake. The full-lake water depth
at the probable location of a boathouse adjacent to the
appraised lot is estimated to be approximately twelve
feet. With this depth the subject property would clearly
be deserving of the highest quality rating of excellent. Comparable Sale 3 has an approximate water
depth of eleven feet and would also be rated excellent.
Comparable Sale 5 has a full-lake water depth of only
four feet and is clearly deserving of the lowest quality
rating of poor. The approximate water depths of the
remaining four properties were: Comparable 1, six
feet; Comparable 2, five feet; Comparable 4, seven feet;
and Comparable 6, nine feet. The quality ratings for the
water depth attribute can be objectively developed by
creating a rating scale similar to the following.
Water Depth (in Feet)
Quality Rating
3–4Poor
5–6Fair
7–8Average
9–10Good
11–+
Excellent
Qualitative Analyses in the Sales Comparison Approach Revisited
Thus, the comparable sales and the subject would
be rated and scored as follows.
Property
Quality Rating
Score
Comparable 1
Fair
20
Comparable 2
Fair
20
Comparable 3
Excellent
50
Comparable 4
Average
30
Comparable 5
Poor
10
Comparable 6
Good
40
Subject
Excellent50
Once the appropriate attributes have been selected
and all properties have been analyzed accordingly,
an adjustment grid can be created in a form similar
to that of Table 1. The transactional adjustments for
expenditures made immediately after purchase are
excluded as being irrelevant for this property type and
data set. The indicated value per square foot of the
subject is derived by multiplying the average sale price
per square foot per total point score by the subject’s
total point score.
Prior to any adjustments, the standard deviation
of the six sale prices per square foot was 0.54519, and
following all adjustments the standard deviation is
notably lower at 0.39725.
It should be noted that in the above analysis each
attribute is of equal importance and carries the same
weight, 20% for each of the five attributes. In reality,
however, some of the attributes are more significant
to the value of the property than others and their
respective scores should carry a greater weight.
However, while the quality ratings for each attribute
may be assigned with a high degree of objectivity, the
assignment of proportionate weights to the attributes
may be arbitrary and subjective. For example, in the
analysis of the above lake lots, Appraiser A might
conclude that the most appropriate weights are as
follows: quality of lake view - 50%; topographic
characteristics - 10%; lakefront feet - 20%; approach 15%, and water depth - 5%. While Appraiser B assigns
the same quality ratings and scores, concluding
that the appropriate weights should be as follows:
lake view - 20%; topographic characteristics - 15%;
lakefront feet - 40%; approach - 5%; and water depth 20%. Furthermore, Appraiser C develops the opinion
that the following weights are most appropriate: lake
view - 35%; topographic characteristics - 5%; lakefront
feet - 5%; approach - 50%; and water depth - 5%. The
Qualitative Analyses in the Sales Comparison Approach Revisited
resulting differences are shown in Table 2 for Appraiser
A, Table 3 for Appraiser B, and Table 4 for Appraiser C.
In the following procedures the total weighted
point scores are divided into the adjusted sale prices
per square foot to derive a sale price per square foot
per weighted point score for each comparable sale,
the average of which is multiplied by the subject’s
weighted point score to develop the subject’s indicated
value. Since the average of the sale prices per square
foot per weighted point score is used to develop the
indicated value for the subject, its reliability can be
tested by using it as a predictor of the sale price of each
comparable sale, which is obtained by multiplying the
weighted point score of each respective sale property
by the average of the sale prices per square foot per
weighted point score.
In Table 2 (Appraiser A), the results from this
weighting process appear to be somewhat unreliable
since only one of the six sales has a predicted price
that is within 10% of the actual sale prices and four
have a difference that exceeds 15%.
In Table 3 (Appraiser B), the standard deviation
of the adjusted sale prices per square foot following
all adjustments is lower than that of Appraiser A in
Table 2, but still higher than the standard deviation
derived from the equal weight attributes in Table 1.
Additionally, the results appear to be more reliable
than those of Appraiser A since three of the sales have
predicted prices that are within 10% of the actual sale
price and two are within a range of about 12% to 13%.
In Table 4 (Appraiser C), the standard deviation
of the adjusted sale prices per square foot following
all adjustments is materially higher than that of both
Appraiser A and Appraiser B, and is significantly higher
than the standard deviation derived from the equal
weight attributes in Table 1. Additionally, the results
appear to be unreliable since one of the predicted prices
exceeds the actual sale price by more than 50%, one
exceeds its actual sale price by about 46%, one falls
short by about 36%, and one falls short by about 15%.
Let the Market Select the Attribute Weights
As the standard deviations from the previous three
analyses indicate, the reliability of the resulting indication of value increases as the standard deviation
declines. Since it is somewhat unlikely that the weighting of any single attribute would be greater than 50%
and that increments of 5% are reasonable, an electronic
spreadsheet can be created with all of the possible
combinations of weights for five attributes between 5%
The Appraisal Journal, Fall 2014
287
Table 1Comparable Sales Adjustment Grid, Analysis of Lot Sales with Equal Weight Attributes
Element
Sale 1
Sale 2
Sale 3
Sale 4
Sale 5
Sale 6
Sale price
$51,000
$40,000
$58,000
$34,500
$45,000
$55,000
11,520
11,475
14,000
12,000
12,900
14,950
Size (sq. ft.)
Sale price per sq. ft.
Property rights
Adjustment
Adjusted sale price
Financing terms
Adjustment
Adjusted sale price
Conditions of sale
Adjustment
Adjusted sale price
Subject
$4.43
$3.49
$4.14
$2.88
$3.49
$3.68
Fee simple
Fee simple
Fee simple
Fee simple
Fee simple
Fee simple
0
0
0
0
0
0
$51,000
$40,000
$58,000
$34,500
$45,000
$55,000
Cash
Cash
Cash
Cash
Cash
Cash
0
0
0
0
0
0
$51,000
$40,000
$58,000
$34,500
$45,000
$55,000
Normal
Normal
Normal
Normal
Normal
Normal
0
0
0
0
0
0
$51,000
$40,000
$58,000
$34,500
$45,000
$55,000
10/17/12
2/05/13
5/17/13
6/14/13
7/25/13
8/30/13
11,700
Fee simple
Cash
Market conditions
Date of Sale
Adjustment
Adjusted sale price
Adjusted price/sq. ft.
Current
+5.0%
0.0%
0.0%
0.0%
0.0%
0.0%
$53,550
$40,000
$58,000
$34,500
$45,000
$55,000
$4.65
$3.49
$4.14
$2.88
$3.49
$3.68
Excellent
Average
Poor
Fair
Good
Fair
Good
50
30
10
20
40
20
40
Average
Fair
Excellent
Good
Average
Poor
Good
Physical attributes
Quality of lake view
Scores
Topographic
characteristics
Scores
30
20
50
40
30
10
40
Good
Average
Good
Poor
Fair
Excellent
Average
Scores
40
30
40
10
20
50
30
Approach
Average
Excellent
Average
Fair
Good
Poor
Fair
Lakefront feet
Scores
30
50
30
20
40
10
20
Water depth
Fair
Fair
Excellent
Average
Poor
Good
Excellent
Scores
20
20
50
30
10
40
50
170
150
180
120
140
130
180
$0.02735
$0.02327
$0.02300
$0.02400
$0.02493
$0.02831
Total scores
Sale price per sq. ft. per
total point score
Average sale price/sq. ft./point score =
Ind. subj. values/sq. ft. =
$4.92
$0.02514
$4.19
Indicated value of the subject per sq. ft. =
$4.14
$4.32
$4.49
Standard deviation of sale prices per sq. ft. prior to any adjustments =
0.54519
Standard deviation of sale prices per sq. ft. after transactional adjustments =
0.60898
Standard deviation of sale prices per sq. ft. after all adjustments =
0.39725
$5.10
$4.53
$4.53
Note: The indicated value per square foot for each comparable is derived by multiplying the subject’s total point score by the sale price per square foot per total point
score of that comparable. The indicated value of the subject is derived by multiplying its total point score by the average sale price per square foot per total point
score of the six comparable sales.
288
The Appraisal Journal, Fall 2014
Qualitative Analyses in the Sales Comparison Approach Revisited
Table 2Comparable Sales Adjustment Grid with Attribute Weights Selected by Appraiser A
Element
Sale 1
Sale 2
Sale 3
Sale 4
Sale 5
Transactional adjusted sale price
$53,550
$40,000
$58,000
$34,500
$45,000 $55,000
$4.65
$3.49
$4.14
$2.88
$3.49
$3.68
50
30
10
20
40
20
40
25.00
15.00
5.00
10.00
20.00
10.00
20.00
30
20
50
40
30
10
40
3.00
2.00
5.00
4.00
3.00
1.00
4.00
40
30
40
10
20
50
30
8.00
6.00
8.00
2.00
4.00
10.00
6.00
30
50
30
20
40
10
20
4.50
7.50
4.50
3.00
6.00
1.50
3.00
20
20
50
30
10
40
50
Adjusted price/sq. ft.
Physical Attributes
50%
Topographic characteristics – scores
Weights/weighted pt. scores
10%
Lakefront feet – scores
Weights/weighted pt. scores
20%
Approach – scores
Weights/weighted pt. scores
15%
Water depth – scores
Weights/weighted pt. scores
Total weighted scores
Subject
Weights
Quality of lake view – scores
Weights/weighted pt. scores
Sale 6
5%
1.00
1.00
2.50
1.50
0.50
2.00
2.50
100%
41.50
31.50
25.00
20.50
33.50
24.50
35.50
Sale price per sq. ft. per weighted point score
$0.11205 $0.11079 $0.16560 $0.14049 $0.10418 $0.15020
Average sale price/sq. ft./point score =
$0.13055
Indicated value of the subject per sq. ft. =
Adjusted indicated values of subject/sq. ft. =
$3.98
$3.93
$5.88
$4.99
$3.70
$5.33
Predicted prices of the comparable sales =
$5.42
$4.11
$3.26
$2.68
$4.37
$3.20
16.51%
17.83%
−21.17%
% Difference of predicted price to actual price =
Standard deviation of sale prices per sq. ft. after transactional adjustments =
Standard deviation of sale prices per sq. ft. after all adjustments =
−7.07%
$4.63
$4.63
25.31% −13.08%
0.60898
0.88984
Note: The percentage differences may not correspond precisely to the numbers shown due to lack of rounding in the calculation of the predicted prices. Example,
Sale 1 ($5.42 - $4.65)/$4.65 = 16.56%.
Table 3Comparable Sales Adjustment Grid with Attribute Weights Selected by Appraiser B
Element
Sale 1
Sale 2
Sale 3
Sale 4
Sale 5
Transactional adjusted sale price
$53,550
$40,000
$58,000
$34,500
$45,000 $55,000
$4.65
$3.49
$4.14
$2.88
Adjusted price/sq. ft.
Physical Attributes
50
30
10
20
40
20
40
10.00
6.00
2.00
4.00
8.00
4.00
8.00
30
20
50
40
30
10
40
15%
4.50
3.00
7.50
6.00
4.50
1.50
6.00
40
30
40
10
20
50
30
40%
16.00
12.00
16.00
4.00
8.00
20.00
12.00
30
50
30
20
40
10
20
5%
1.50
2.50
1.50
1.00
2.00
0.50
1.00
20
20
50
30
10
40
50
20%
4.00
4.00
10.00
6.00
2.00
8.00
10.00
36.00
27.50
37.00
21.00
24.50
34.00
37.00
Lakefront feet – scores
Weights/weighted pt. scores
Approach – scores
Weights/weighted pt. scores
Water depth – scores
Weights/weighted pt. scores
Total weighted scores
$3.68
20%
Topographic characteristics – scores
Weights/weighted pt. scores
Subject
Weights
Quality of lake view – scores
Weights/weighted pt. scores
$3.49
Sale 6
100%
Sale price per sq. ft. per weighted point score
$0.12917 $0.12691 $0.11189 $0.13714 $0.14245 $0.10824
Average sale price/sq. ft./point score =
$0.12597
Adjusted indicated values of subject/sq. ft. =
Predicted prices of the comparable sales =
% Difference of predicted price to actual price =
$4.78
Indicated value of the subject per sq. ft. =
$4.70
$4.14
$5.07
$5.27
$4.00
$4.53
$3.46
$4.66
$2.65
$3.09
$4.28
−2.47%
−0.74%
12.58%
−8.15%
−11.57%
16.39%
Standard deviation of sale prices per sq. ft. after transactional adjustments =
Standard deviation of sale prices per sq. ft. after all adjustments =
Qualitative Analyses in the Sales Comparison Approach Revisited
$4.66
$4.66
0.60898
0.50191
The Appraisal Journal, Fall 2014
289
Table 4Comparable Sales Adjustment Grid with Attribute Weights Selected by Appraiser C
Element
Sale 1
Sale 2
Sale 3
Sale 4
Sale 5
Transactional adjusted sale price
$53,550
$40,000
$58,000
$34,500
$45,000 $55,000
$4.65
$3.49
$4.14
$2.88
$3.49
$3.68
50
30
10
20
40
20
40
17.50
10.50
3.50
7.00
14.00
7.00
14.00
30
20
50
40
30
10
40
1.50
1.00
2.50
2.00
1.50
0.50
2.00
40
30
40
10
20
50
30
2.00
1.50
2.00
0.50
1.00
2.50
1.50
30
50
30
20
40
10
20
15.00
25.00
15.00
10.00
20.00
5.00
10.00
20
20
50
30
10
40
50
Adjusted price/sq. ft.
Physical Attributes
35%
Topographic characteristics – scores
Weights/weighted pt. scores
5%
Lakefront feet – scores
Weights/weighted pt. scores
5%
Approach – scores
Weights/weighted pt. scores
50%
Water depth – scores
Weights/weighted pt. scores
Total weighted scores
5%
1.00
1.00
2.50
1.50
0.50
2.00
2.50
100%
37.00
39.00
25.50
21.00
37.00
17.00
30.00
Sale price per sq. ft. per weighted point score
$0.12568 $0.08949 $0.16235 $0.13714 $0.09432 $0.21647
Average sale price/sq. ft./point score =
$0.13758
Indicated value of the subject per sq. ft. =
Adjusted indicated values of subject/sq. ft. =
$3.77
$2.68
$4.87
$4.11
$2.83
$6.49
Predicted prices of the comparable sales =
$5.09
$5.37
$3.51
$2.89
$5.09
$2.34
% Difference of predicted price to actual price =
9.47%
53.74%
−15.26%
Standard deviation of sale prices per sq. ft. after transactional adjustments =
Standard deviation of sale prices per sq. ft. after all adjustments =
and 50% that add up to a total of 100%. It appears that
the total number of possible combinations is 3,238. To
illustrate the possibilities, any combination of weights
that contains five different numbers can be arranged
in 120 different positions, such as (5%, 15%, 20%, 25%,
35%), or (15%, 20%, 25%, 35%, 5%), or (20%, 25%, 35%,
5%, 15%), and on and on for a total of 120 different positions. The same applies to 5%, 10%, 20%, 25%, 40%, etc.
With the database created, an electronic
spreadsheet can be built that uses each one of
the 3,238 different combinations of weights, then
calculates the sale price per square foot (or other
unit) per weighted point score, and calculates the
standard deviation in each iteration. The combination
of weights for each of the five attributes that results
in the lowest standard deviation in the sale prices
per unit per weighted point score is the combination
that most closely predicts the actual sale prices of the
comparable sales used. If the analysis can predict
the actual sale prices of the comparable sales with
a reasonable degree of accuracy, it is then fair to
conclude that it can produce a reasonably reliable
indication of value for the appraised property.
By testing the multiple combinations of weights
on the selected attributes and quality rating scores
290
Subject
Weights
Quality of lake view – scores
Weights/weighted pt. scores
Sale 6
The Appraisal Journal, Fall 2014
0.32%
$4.13
$4.13
45.86% −36.44%
0.60898
1.41752
as used in the preceding four tables, the marketindicated weights are: quality of lake view - 35%;
topographic characteristics - 15%; lakefront footage
- 25%; approach - 5%; and water depth - 20%. The
results of the analysis and the indicated value of the
subject property are shown in Table 5.
With the application of the market-selected
weights to each of the five property attributes, the
standard deviation of the adjusted sale prices per
square foot is a modest 0.06085 and the reliability
of the results appears to be quite high since the
predicted prices are all within 2% of the actual sale
prices. Given its total weighted point score of 38.50,
it is indicated that the appraised property is superior
to all of the comparable sales.
It is noted that if the sale prices per square foot
and the weighted point scores are used in a regression
analysis, the indicated value of the subject property
is approximately $4.80 per square foot, as reflected
in Figure 1. The coefficient of determination (R­2) is
0.996387.
In lieu of a database with 3,238 combinations of
weights that can be tested for the most appropriate
fit, appraisers can create a spreadsheet similar to that
used in Tables 2, 3, and 4 and first enter the quality
Qualitative Analyses in the Sales Comparison Approach Revisited
Table 5Comparable Sales Adjustment Grid with Market-Generated Attribute Weights
Element
Sale 1
Sale 2
Sale 3
Sale 4
Sale 5
Transactional adjusted sale price
$53,550
$40,000
$58,000
$34,500
$45,000 $55,000
$4.65
$3.49
$4.14
$2.88
$3.49
$3.68
50
30
10
20
40
20
40
17.50
10.50
3.50
7.00
14.00
7.00
14.00
30
20
50
40
30
10
40
4.50
3.00
7.50
6.00
4.50
1.50
6.00
40
30
40
10
20
50
30
10.00
7.50
10.00
2.50
5.00
12.50
7.50
30
50
30
20
40
10
20
1.50
2.50
1.50
1.00
2.00
0.50
1.00
20
20
50
30
10
40
50
Adjusted price/sq. ft.
Physical Attributes
35%
Topographic characteristics – scores
Weights/weighted pt. scores
15%
Lakefront feet – scores
Weights/weighted pt. scores
25%
Approach – scores
Weights/weighted pt. scores
5%
Water depth – scores
Weights/weighted pt. scores
Total weighted scores
Subject
Weights
Quality of lake view – scores
Weights/weighted pt. scores
Sale 6
20%
4.00
4.00
10.00
6.00
2.00
8.00
10.00
100%
37.50
27.50
32.50
22.50
27.50
29.50
38.50
Sale price per sq. ft. per weighted point score
$0.12400 $0.12691 $0.12738 $0.12800 $0.12691 $0.12475
Average sale price/sq. ft./point score =
$0.12633
Indicated value of the subject per sq. ft. =
Adjusted indicated values of subject/sq. ft. =
$4.77
$4.89
$4.90
$4.93
$4.89
$4.80
Predicted prices of the comparable sales =
$4.74
$3.47
$4.11
$2.84
$3.47
$3.73
% Difference of predicted price to actual price =
1.88%
−0.46%
−0.83%
−1.30%
−0.46%
1.27%
Standard deviation of sale prices per sq. ft. after transactional adjustments =
0.60898
Standard deviation of sale prices per sq. ft. after all adjustments =
0.06085
$4.86
$4.86
Figure 1 Lakefront Lot Sales Regression Line with Intercept
Sale Prices per Square Foot
5.00
4.50
R2 = 0.9964
4.00
3.50
3.00
2.50
2.00
20.00
25.00
30.00
Weighted Point Scores
ratings and respective scores for each attribute. After
having done so, the appraiser can select four or five
best-thought combinations of weights for the five
attributes, and then calculate the standard deviations
Qualitative Analyses in the Sales Comparison Approach Revisited
35.00
40.00
of the sale prices per square foot per weighted point
score. The combination of weights producing the
lowest standard deviation is the one that would develop
the best indication of value for the subject property.
The Appraisal Journal, Fall 2014
291
Case Study Application of the
Attribute Scoring System to an
Improved Property
The following illustration demonstrates how the attribute scoring system applies equally well to the analysis
of an improved property, in this case a strip shopping
center, as to a parcel of unimproved land. While the
chosen attributes for the comparable sales and the subject are identified, the selections of the quality ratings
are somewhat summarized for the sake of brevity.
The pertinent information on the comparable
sales and the subject are provided in Table 6. This
table reflects the sale prices of each property prior
to various transactional adjustments required for
rent losses and lease-up costs, conditions of sale, and
market conditions. In Table 7, the cited sale prices in
row 2 were obtained after having made the required
transactional adjustments.
Table 6Comparable Sale Summary Data for Strip Shopping Center
Date of Sale
Actual Sale
Price
Year
Built
GLA*
(sq. ft.)
Land/Bldg.
Ratio
Occupancy
1
Mar 24, 2011
$3,000,000
2000
18,900
5.82
95.0%
$158.73
2
Aug 2, 2011
$1,950,000
1996
16,570
5.23
85.0%
$117.68
3
Jan 13, 2012
$4,700,000
1998
36,721
4.33
85.0%
4
Feb 23, 2012
$2,200,000
2007
19,692
4.41
5
Dec 12, 2012
$2,813,500
1999
16,718
6
May 6, 2013
$3,675,000
1984
48,290
1997
1995
26,149
17,129
Sale
Averages
Subj.
Current
Sale Price/ Stab.
GLA
EGIM†
Stab.
OAR‡
Net Income
Ratio
7.17
9.10%
65.22%
6.79
9.88%
67.09%
$127.99
7.70
8.78%
67.59%
76.0%
$111.72
7.14
9.51%
67.86%
4.60
96.0%
$168.29
7.54
9.18%
69.23%
3.61
65.7%
$76.10
6.62
9.80%
64.91%
4.67
4.59
83.8%
93.6%
$126.75
7.16
9.38%
66.98%
* Gross leaseable area
† Effective gross income multiplier
‡ Overall capitalization rate
Table 7 Comparable Sales Adjustment Grid for Improved Property—A Strip Shopping Center
Element
Sale 1
Transactional adjusted sale price
$174.60
$150.86
$135.82
$132.77
$168.29
$82.32
30
20
10
50
10
40
3.00
2.00
1.00
5.00
1.00
4.00
50
40
20
20
30
10
30
20%
10.00
8.00
4.00
4.00
6.00
2.00
6.00
40
30
30
50
30
10
30
20%
8.00
6.00
6.00
10.00
6.00
2.00
6.00
30
20
30
10
20
30
40
15%
4.50
3.00
4.50
1.50
3.00
4.50
6.00
30
30
30
30
40
20
30
35%
10.50
10.50
10.50
10.50
14.00
7.00
10.50
32.50
Quality of construction – scores
Weights/weighted pt. scores
Subject
30
Exposure/accessibility – scores
Weights/weighted pt. scores
Sale 6
3.00
Age and condition – scores
Weights/weighted pt. scores
Sale 5
10%
Land-to-building ratios – scores
Weights/weighted pt. scores
Sale 4
Weights
Overall location – scores
W
eights/weighted pt. scores
Sale 3
$3,300,000 $2,499,750 $4,987,500 $2,614,500 $2,813,500 $3,975,000
Adjusted price per sq. ft.
Physical Attributes
Sale 2
Total weighted scores
100%
Sale price per sq. ft. per weighted
point score
36.00
30.50
27.00
27.00
34.00
16.50
$4.85000
$4.94623
$5.03037
$4.91741
$4.94971
$4.98909
Average sale price/sq. ft./point score =
$4.94714
Adj. indicated values of subject/sq. ft. =
$157.63
$160.75
$163.49
$159.82
$160.87
$162.15
Predicted prices comparable sales
% Difference of predicted price to
actual price =
$178.10
$150.89
$133.57
$133.57
$168.20
$81.63
2.00%
0.02%
−1.65%
0.60%
−0.05%
−0.84%
Indicated value of the subject per sq. ft. =
Standard deviation of sale prices per sq. ft. of GLA after transactional adjustments =
Standard deviation of sale prices per sq. ft. of GLA after all adjustments =
292
The Appraisal Journal, Fall 2014
$160.78
$160.78
33.19196
2.00420
Qualitative Analyses in the Sales Comparison Approach Revisited
Types of Attributes
After inspecting each comparable property and the
subject, the appraiser concluded that the most important attributes affecting value were overall location,
land-to-building ratio, age and condition, exposure/
accessibility, and quality of construction.
Overall Location. Surrounding demographic characteristics and the quality and nature of existing
developments in the immediate neighborhood of
each property are considered. The most appropriate
location quality ratings were as follows:
Property
Quality Rating
Score
Comparable 1
Average
30
Comparable 2
Average
30
Comparable 3
Fair
20
Comparable 4
Poor
10
Comparable 5
Excellent
50
Comparable 6
Poor
10
Subject
Good40
Land-to-Building Ratios. The land-to-building
ratios for the comparable sales and the subject range
from a low of 3.61:1 to a high of 5.82:1. The quality
ratings for this attribute can be objectively developed
by creating a rating scale as follows.
Land/Building Ratios
Quality Rating
3.5–3.99
Poor
4.0–4.49Fair
4.5–4.99Average
5.0–5.49Good
5.50–5.99
Excellent
Thus, the comparable sales and the subject would
be rated and scored as follows.
Property
Quality Rating
Score
Comparable 1
Excellent
50
Comparable 2
Good
40
Comparable 3
Fair
20
Comparable 4
Fair
20
Comparable 5
Average
30
Comparable 6
Poor
10
Subject
Average30
Age and Condition. The dates of construction of the
comparable sales ranged from 1984 to 2007, and the
average date was 1997; the construction date of the
Qualitative Analyses in the Sales Comparison Approach Revisited
subject was 1995. The following scale has been used
as a guide in the analysis of the aspects of age and
condition. Refinements are made, when necessary,
based on observed physical condition.
Date of Construction
1984–1989
1990–1994
1995–1999
2000–2004
2005–2009
Quality Rating
Poor
Fair
Average
Good
Excellent
Given this scale, the comparable sales and the subject would be rated and scored as follows.
Property
Quality Rating
Score
Comparable 1
Good
40
Comparable 2
Average
30
Comparable 3
Average
30
Comparable 4
Excellent
50
Comparable 5
Average
30
Comparable 6
Poor
10
Subject
Average30
Exposure/Accessibility. Based on careful observation of the relevant aspects of each comparable and
the subject, the following quality ratings for exposure/
accessibility were considered reasonably appropriate.
Property
Quality Rating
Score
Comparable 1
Average
30
Comparable 2
Fair
20
Comparable 3
Average
30
Comparable 4
Poor
10
Comparable 5
Fair
20
Comparable 6
Average
30
Subject
Good40
Quality of Construction. After on-site inspections of
the comparable sales and the subject, the appraiser
concluded that the construction quality ratings set
forth below were reasonably appropriate.
Property
Quality Rating
Score
Comparable 1
Average
30
Comparable 2
Average
30
Comparable 3
Average
30
Comparable 4
Average
30
Comparable 5
Good
40
Comparable 6
Fair
20
Subject
Average30
The Appraisal Journal, Fall 2014
293
Given the above analyses of the comparable sales and
the subject, and after the attribute weights were tested
for the most appropriate fit, the indicated value of the
appraised property has been developed in Table 7.
With the market-generated attribute weights,
the reliability of the resulting indication of value
appears to be quite high since all six of the predicted
prices are within 5% of the actual sale prices, and
the highest difference is only 2%. When a linear
regression analysis is performed using the sale prices
per square foot and the weighted point scores, the
resulting R2 is 0.997708 and the indicated value of
the subject is $159.96 per square foot.
Conclusions
The author of this article is well aware that many fellow appraisers do not advocate the use of qualitative
adjustments when analyzing comparable sales, and
many review appraisers will not accept appraisals
that rely upon qualitative adjustments. But they should
reconsider. After all, qualitative comparisons are a
reality of the market which the appraiser seeks to
simulate. Whole dollar and percentage adjustments
for differences are grounded in paired sales analyses.
However, there are typically too many differences in
the various value-influencing characteristics of a package of five or six comparable sales to reliably extract
each adjustment required. Consequently, many of the
quantitative adjustments that are used stem from the
best-guess estimates of the analyst.
It would seem that the most appropriate analysis
is one that generally replicates or simulates the actions
of buyers and sellers in the market, and that is one of
qualitative analysis, rather than positive and negative
quantitative adjustments. The objective of analyzing
comparable sales is to allow the sales to guide the
analyst in forming an opinion of reasonable value
for the property being appraised. The sale price of a
comparable sale may be viewed as a base value that has
been shaped by the interactions of each of the primary
attributes with the relative quality level of that attribute.
While analysts can objectively rate the quality levels,
they cannot objectively select the attribute weights if a
weighting of the attributes is to be used. Appraisers can
put the marbles in the jars (the quality rating scores),
but they cannot assign values to the colors (the weights
of each primary attribute). That is done by the market.
Appraisers can, however, refine their analysis by testing
some of the most reasonable combinations of attribute
weights after analyzing the properties in the data set.
A final comment is in order. Even if the weighting
of the attributes is not used in the analysis and each
attribute is allowed to bear an equal weight, the results
are likely to be better market-supported, and superior
to the application of positive and negative quantitative
adjustments since the analyst simulates the interactions
of the market and has a better opportunity to develop
and assign objective quality ratings during the analysis
of the subject property and comparable sales.
Gene Rhodes, MAI, received his designation from
the American Institute of Real Estate Appraisers in
1975 and served as president of North Texas Chapter
17 in 1987. Rhodes is head of Gene Rhodes &
Associates, a commercial real estate appraisal firm
based in Addison (Dallas), Texas. Having previously
served as an officer with the Henry S. Miller Appraisal
Corporation and the Appraisal & Consulting Services
Group of Grubb & Ellis Co., Rhodes has appraised a
wide range of major commercial, industrial, and multifamily properties throughout Texas. He is a previous
contributor to The Appraisal Journal. Rhodes is a state
certified general real estate appraiser in Texas, and
he received a BBA degree from Texas State University.
Contact: gene.rhodes@sbcglobal.net
Web Connections
Internet resources suggested by the Y. T. and Louise Lee Lum Library
Analyze The Market! Qualitative vs. Quantitative
http://appraisalnewsonline.typepad.com/appraisal_news_for_real_e/2009/09/analyze-the-market-qualitative-vs
-quantitative-.html
Qualitative Analysis vs. Quantitative Analysis
http://www.waao.org/Meetings/2014/Class_Documents/REVISED_2014_Quant_vs_Qual_Analysis.pdf
Qualitative vs. Quantitative Adjustments
http://www.bbrec.com/attachments/articles/49/q%20adj.pdf
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The Appraisal Journal, Fall 2014
Qualitative Analyses in the Sales Comparison Approach Revisited