The fix for this is to re-run the analysis without the offending parameters. The reason is that they are overwhelmed by the high impact parameters (GLA, date of sale, lot size differences) and/or unquantified parameters such as condition and quality. This happens most often with low impact parameters (independent variables) such as bath count and garage spaces. In most cases when I’ve used this method, multiple regression produces one or more adjustment factors (regression coefficients) that are negative when they should be positive. For example, date of sale, lot size, GLA, stories, age, bath count, garage spaces, fireplace, pool & spa etc. Multiple regression analysis is another method that should be the gold standard as it uses statistical analysis to produce adjustment factors for a whole range of parameters. There are almost always differences in lot size, condition and other features that can compromise the validity of this approach. However, this is an ideal situation that is rarely encountered. Given two properties with different GLAs, but otherwise identical, in the same neighborhood on equivalent lots and with the same date of sale, the adjustment factor is calculated as the difference in sales prices is divided by the difference in GLAs. Matched pair analysis is one acceptable method. I have, however, done a certain amount of research on methods of arriving at GLA adjustments based on data analysis as opposed to rules of thumb. Most of the appraisals I have prepared have not included support, either. Over the past several years, I have reviewed dozens of appraisals and I can’t recall one instance where the appraiser has included such support. However, the production of reasonable results does not satisfy the requirement to provide support for adjustment factors. For the most part, it seemed to produce reasonable results. We also have the original 6 Solomon calculators at $15/month recurring and $150 annual subscription levels.“One of the best courses that I have had in 17 years!”Įducation designed to help you appraise worry-free and earn higher fees.Ī Spreadsheet Solution for Estimating GLA AdjustmentsĪs an appraiser trainee, I was taught to calculate GLA adjustments by averaging the comparables’ sales price per square foot and multiplying it by 50%, up to a maximum of about $80/sq. When you are ready, choose between a $30/month recurring subscription and a $300 annual subscription. The Free Trial option is Solomon Plus which includes 10 calculators. Watch Training videos. Then give us a try at Subscribe. Read about The Sample Problem and how Depreciated Cost aligns with USPAP. We show you how.Ĭlick the Theory tab and look at the drop down menu. We license cost data so there is nothing more to buy.ĭepreciated cost adjustments are market based when you extract depreciation from the market. We have developed a suite of calculators that make the Depreciated Cost Method fast and convenient. Our search for a method that is predictive and repeatable has lead us to the Depreciated Cost Method. GLA, bedrooms and baths are often combined into one predictor. Regression does a great job of predicting value for a group of 30+ houses, meeting the needs of assessors and mortgage portfolio managers very well.īut using regression coefficients as grid adjustments is hit or miss. Statistical analysis tools are not designed for the sales grid. ![]() More recently, statistical analysis is applied to a large group of houses located near the subject.Īfter 20 years and over 6,000 appraisals, I have come to understand the limitations of these methods. ![]() Grid adjustments, remaining economic life, site value and more.įor grid adjustments, the traditional method has been to search for paired sales that are equal in every way except the characteristic being analyzed. ![]() We help appraisers support assignment results.
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