An appraiser includes months elapsed since each sale as a variable in a price model. What is this intended to capture?
Correct Answer
C) The change in market conditions over time
Why this is correct: Including a variable for the number of months since each sale (time variable) in a regression model is a direct method to estimate and capture the effect of changing market conditions over the sales period, holding other property characteristics constant. Why the other choices are wrong: "The physical depreciation of the improvements" is wrong; physical depreciation is related to age and condition, not simply the passage of time between sale dates. "The remaining economic life of each building" is wrong; that is not measured by months since sale. "The seasonal pattern in buyer preferences" is wrong; a simple time variable in months would not specifically isolate seasonal effects. Exam tip: In regression, a time variable estimates market trends, often called the "time adjustment."
Why This Is the Correct Answer
Why this is correct: Including a variable for the number of months since each sale (time variable) in a regression model is a direct method to estimate and capture the effect of changing market conditions over the sales period, holding other property characteristics constant. Why the other choices are wrong: "The physical depreciation of the improvements" is wrong; physical depreciation is related to age and condition, not simply the passage of time between sale dates. "The remaining economic life of each building" is wrong; that is not measured by months since sale. "The seasonal pattern in buyer preferences" is wrong; a simple time variable in months would not specifically isolate seasonal effects. Exam tip: In regression, a time variable estimates market trends, often called the "time adjustment."
More appraisal-statistical-methods Questions
A price index rises from 100 to 121 over two years. What compound annual rate does this represent?
A sample of four sales drawn from a market with 200 annual transactions is:
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An appraiser runs a regression of sale price on GLA, age, and a binary variable for 'renovated' (1 = yes, 0 = no). The estimated coefficient for 'renovated' is $18,400 with a standard error of $6,200 and a t-statistic of 2.97. Assuming a two-tailed test at Ξ± = 0.05 and 42 degrees of freedom, what conclusion is supported regarding the market's recognition of renovations?
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