An appraiser uses sale prices adjusted by a supported market-conditions analysis to one effective date as the regression response. What is the intended purpose?
Correct Answer
B) Reduce confounding from price movement across the sale dates
Supported time adjustments seek to put sale prices on a common effective-date basis so estimated market movement does not confound other modeled differences. Their accuracy and any remaining time pattern still require checking. They neither guarantee a higher R-squared nor eliminate transaction verification. Including another time effect must be justified and checked for double counting; it is not categorically forbidden.
Why This Is the Correct Answer
Option B is correct because supported market-conditions adjustments put sale prices on a common effective-date basis, so price movement across sale dates does not confound the estimated effects of other variables. The accuracy of the adjustment and any remaining time pattern still need to be checked. The goal is cleaner comparison, not a particular statistical outcome.
Why the Other Options Are Wrong
Option A: Increase the R-squared of the fitted model
Option A says the purpose is to increase the R-squared of the fitted model. Time adjustment may or may not change R-squared, and raising a fit statistic is not the reason for adjusting; the aim is to remove time-related distortion.
Option C: Eliminate the need to verify each of the underlying transactions
Option C claims time adjustment eliminates the need to verify each of the underlying transactions. Adjusting for market conditions does nothing to confirm the price, terms or arm's-length nature of a sale, so verification is still required.
Option D: Make otherwise unsupported sales into acceptable inputs
Option D suggests the adjustment makes otherwise unsupported sales into acceptable inputs. A time adjustment changes only the date basis of a price; it does not cure a sale that is unverified, non-arm's-length or otherwise unsuitable.
Same date, fair comparison
Time-adjusting prices is like converting all prices to the same currency before comparing them: it puts all sales on one market-date basis.
How to use: Use this to recall that time adjustment removes date-driven price differences so other effects can be measured.
Exam Tip
Choose the answer about removing market-movement distortion; time adjustment does not replace sale verification or rescue poor data.
Common Mistakes to Avoid
- -Believing time adjustment is done mainly to improve R-squared
- -Assuming adjusted prices no longer need transaction verification
- -Adding a separate time variable on top of adjusted prices without checking for double counting
Concept Deep Dive
Analysis
This question tests why sale prices are time-adjusted before being used as a regression response. Sales that close on different dates reflect different market conditions, and that price movement can be mistaken for the effect of other property characteristics. Adjusting each price to one effective date with a supported market-conditions analysis aims to remove that confounding influence.
Background Knowledge
Comparable sales must be analyzed for changes in market conditions between the contract date and the effective date of the appraisal. In statistical models, time trends left unaddressed can bias the coefficients of other variables. Any additional time variable in the model should be checked for double counting with the adjustment already applied.
Real-World Application
An appraiser models 18 months of sales in a rising market. Before regression, each price is adjusted to the effective date using a supported paired-sales and resale trend analysis. This keeps later, higher-priced sales from making newer features look more valuable than they are.
More Statistics Questions
Sale prices are $270,000, $290,000, $300,000, $310,000, $330,000. Treat the listed observations as the complete population and divide by n when computing the standard deviation. Report to the nearest dollar.
A sales sampling frame systematically excludes a relevant part of the target market. What is the principal risk?
An appraiser estimates a market-wide price trend using only sales data from one brokerage that specializes in luxury homes, without checking how other segments are represented. What is the principal concern?
Compared with analyzing one matched sale pair for one feature, what can a suitably specified multiple regression do?
The base-period median sale price is $400,000 and the current-period median is $460,000. Compute the price relative defined as current ÷ base, as a decimal to three places.
The assessment-to-sale ratios are 0.8, 0.85, 0.9, 0.92, 0.95, 0.98, 1.02, 1.05, 1.08, 1.1, 1.15, 1.2. Calculate COD as [average absolute deviation from the median ÷ median]×100. For even n, average the two middle ratios. Report the COD as a percentage to two decimals.
Assessment-to-sale ratios are 0.94, 0.96, 0.98, 1, 1.01. Compute the arithmetic mean. Report as a decimal ratio to three places.
Market data show a first quartile sale price of $405,000 and a third quartile sale price of $495,000. What is the interquartile range, to the nearest dollar?
Assessment-to-sale ratios are 0.96, 0.98, 0.99, 1.01. Compute the arithmetic mean. Report as a decimal ratio to three places.
Given first quartile $400,000, median $440,000 and third quartile $500,000, compute the trimean (Q1+2×median+Q3)/4. Report to the nearest dollar.
People Also Study
Real Estate Market
13.6% of exam
Property Description
11.8% of exam
Land or Site Valuation
4.5% of exam
Sales Comparison Approach
16.4% of exam
Cost Approach
13.6% of exam
Previous Question
While reviewing a data vendor's report on five closed sales in a neighborhood, an appraiser finds four prices: $380,000, $400,000, $450,000 and $550,000. The fifth price is missing, but the report states a median of $400,000 for all five sales. What can the appraiser conclude about the missing price?
Next Question
First quartile Q1 is $390,000 and third quartile Q3 is $470,000. Compute the midhinge (Q1+Q3)/2 to the nearest dollar.