Fannie Mae

Elif Onmus-Baykal

Eric Rosenblatt

Benjamin Ross Hoffman

Herbert F Frymark, Jr

Dwayne D Seegars

Indexing and adjusting for property condition in an automated valuation model. Property data corresponding to a geographical area is accessed, and a regression is performed based upon the property data. The regression models the relationship between a dependent variable, such as price, and property-characteristic explanatory variables. Further regression is then performed and models or further explains the relationship between the dependent variable and property condition explanatory variables. Specifically, further regression may model the relationship between the residual from the first regression and the property condition variables. Optional examples of these variables are those based upon the presence of predetermined remarks in associated property listings, the number of photos in such listings, and a categorical year built variable. The regression is used to determine a property-condition index for the geographical area. The property-condition index identifies a predicted condition that is used to make adjustments to comparable properties in automated valuation modeling.

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Arlington, VA, United States of America

Elif Onmus-Baykal