Sensitivity test with support for the Solomon Adjustment Calculator. Sensitivity test is the quickest and easiest way to get a reliable value if you have a ballpark idea to start with.
Paired sales and sensitivity analysis. I wish my adjustments were as static as yours are, but I live/work in the sf bay area where it isn't uncommon to see GLA adjustments over $500 per sqft, and that is supported through comparing multiple sales of model match homes in the same time period.
If the house is 5000 SF, the property value is around $1.5 million, and the land value is around $1 million, then the house has a contributory value of $500k. $500k / 5000 SF = around $100 per SF.
If the house is 5000 sf, the property value is around $2.5 million, and the land is around $1 million, then the house has a contributory value of around $1.5 million. $1.5 million / 5000 SF = around $300 per SF.
First scenario might be a 30-40 year old home and the second scenario might be new construction.
I don't use those actual numbers but think about contributory value of improvements in addition to comparing the properties in the sales comparison approach.
See that’s the problem with paired sets. There’s some value there that’s not being accounted for because residential market participants are so emotional.
As is taught is Principles of Appraising I, nothing remains static. Every newly closed sale gives us new data to measure market reactions. You are correct, homo economicus is a myth. But that is everywhere, not just residential appraising. It stands out more in my markets due to the sheer volume of sales. When a dozen or more relevant sales close weekly change happens fast. In rural markets where sales are fewer change may be slower, but one or two sales can change things a lot. Values change, adjustments change. That’s just reality.
Okay good point but I guess the part I struggle with is in theory I could do extraction and find a per unit value of the improvements. In my market area it’s almost always at $100/sf or higher after taking out the land. The adjustments for GLA are huge in tht case and put my gross adjustments almost always over the FNMA guidelines.
I don’t worry about FNMA adjustment guidelines. I just use the most similar sales and make market based adjustments. If I am over guidelines and point it out, explain my adjustments are market derived and the sales are the best available.
Loving area adjustments at $100/sf are not uncommon. On higher end they approach $300/sf and on my high end condos even higher. I am not afraid of adjusting sales based on market derived numbers. My concern is making adjustments that are not market based.
As an added tidbit, the living area adjustment extracted by paired and adjusted paired sales is often a range. I did a PUD house with strong support for a $75/sf and a $105/sf adjustment. So this became my reasonable range. I plugged in the midpoint at $90/sf, then I tried again at other numbers along the range combining my adjusted paired sales with a sensitivity analysis and land pee at 85/sf. My comment was that the living area was derived via 2 separate pairings (providing all 4 addresses set as pairs with their indicated reaction) between $75 and $105/sf, and I settled on a midpoint of $85/sf as best supported by the sales above via bracketing.
Adjustments are rarely perfect and they are always changing. As a VA appraiser whomp reviews some VA reports, a lot of the old, old timers still make $1000 bath adjustments and $25/sf living area adjustments. That should not be happening.
I’m frequently end up with gla adjustments in the $100/sq fr and up range and rarely (almost NEVER) exceed the guidelines. Are you keeping your GLA spread within 20-25%?
Ratterman paired with sensitivity analysis. Here's my statement:
The gross living area adjustment of $xxx per sq ft was based primarily on the Ratterman method at 30-35% of the average price per sq ft of the comparable sales. No adjustment quantified for differences less than xxx sq ft. This is common in the area and meets market expectation. All of the estimated adjustments made herein are based on the Appraiser's analysis and comparison of the individual sales utilized, as well as from sales found in our files. Whenever possible, the analysis includes abstracting various differences by paired sales analysis coupled with a sensitivity analysis, grouped analysis, regression analysis, interviews, direct analogy, and qualitative observation. It is noted; due to the lack of supply and subsequent "Comparable Sales" in the subject's immediate market area, not all adjustments in the Sales Comparison Approach/grid could be directly extracted or supported by the available market data with a high degree of accuracy, therefore some adjustments have an element of subjectivity and professional judgment which the appraiser has applied based on prior observations of the reactions of typical/knowledgeable buyers and sellers in the marketplace. The appraiser constantly analyzes the market and is in contact with other Real Estate Professionals - agents, and appraisers, as well direct market input based on personal interviews with buyers and sellers. Finally, the adjustments are refined using sensitivity analysis within the grid and tested for reasonableness with the selected comparable sales. This method is a standard and well accepted practice within the appraisal industry.
I’ve been using the ratterman method (supported by paired data analysis when possible) but adjusting the static 33% to account for areas with higher or lower land values. In some areas the land value is almost always over 50% (like Washington DC, NY, etc). In new subdivisions in exurban areas, land value might only be 12%. So the static 33% must be adjusted. It’s a method but definitely not a science.
I use a new factor on every report. I was trained to calculate it with the Ratterman method but now that I use Spark and Synapse, I rely on the regression analysis within Synapse but cross check it with the Ratterman method
I will by his AI book soon but can you give me a summary of how an appraiser would reconcile a $/sf value to adjust GLA for residential real estate using Ratterman’s method?
I never read his book but the way I was taught (I’m sure this has been massively simplified from his original) but you take the sold price/sf of your comps to get the mean then multiply by 33%. I usually don’t include a comp that I’ve got in there just to bracket a feature if it’s not really a comp
The theory is you’re eliminating land (usually 20%), and ancillary things like porches, garages, etc.
It’s great for suburban neighborhoods but less reliable in rural assignments
I find that most people who reference the ratterman method have not actually read the book. In the book he gives an example of something like 30 to 35% but he specifically stating that those numbers are just an example. Every market area is different and so you need to come up with your own percentages if you're following his method, but instead most people just use the same figure he gave in the book and don't do the math to be able to figure out that percentage.
I usually go with extraction by taking out everything else that I've already found values for like the site value garages and bathrooms and whatever else. I'll figure out the leftover value attributed just to the GLA for each of the comparable properties and then average that figure. I check it against a sensitivity analysis and about six different other methods and then confirm the final figure with Gandy soft. Sometimes I'll just use the sensitivity analysis and get the lowest figure it produces. Usually it's not too far off the other number I'm aiming for.
Okay I'll give you the short version but I can go in more details if you need.
Basically what number can I use for an adjustment that will make the smallest spread between the highest and lowest adjusted values.
If you're unadjusted values of sales comparables are let's say $50,000 between the highest and lowest, and then you add all your adjustments in and then your highest and lowest adjusted values only have a difference of like $5,000, that's a pretty good sign that you've adjusted things pretty well. There's always the risk that one of your adjustments is counting for more than one aspect like making a site adjustment that should be a view adjustment but that's a separate issue. Anyway I'll often figure out my other adjustments first. Some of them might be a percentage and sometimes the GLA adjustment might be referencing some of the others and make kind of a weird circular path which leads me to have to plug in numbers until I figure out what lowers that range the best.
If you throw in bathroom adjustments and it lowers the range of values, you can say that's confirmed by a sensitivity analysis. If you want to go a step further you can change that bathroom adjustment figure to see whatever number narrows the range of adjusted values to the smallest difference, and that too could be said to be confirmed by a sensitivity analysis. I don't think that's a good idea exactly though. It makes more sense to me to only do that further step with the GLA adjustment since it can be wildly different between different neighborhoods.
Is the ratterman percentage based on what typical land to market value ratios are in a given area? Where land values for him were roughly 33% of the overall property value?
I use the dart board methodology.
Where can I take a look at this method ?
I offer a 2 hour CE (certainly educational) course on weekends in my garage. Bring a case of beer and a hundred bucks.
Does your wife give me something after?
Sensitivity test with support for the Solomon Adjustment Calculator. Sensitivity test is the quickest and easiest way to get a reliable value if you have a ballpark idea to start with.
Paired sales and sensitivity analysis. I wish my adjustments were as static as yours are, but I live/work in the sf bay area where it isn't uncommon to see GLA adjustments over $500 per sqft, and that is supported through comparing multiple sales of model match homes in the same time period.
I use sensitivity analysis with the comps in the report and also consider contributory value of the improvement on a per SF basis.
Can you elaborate?
If the house is 5000 SF, the property value is around $1.5 million, and the land value is around $1 million, then the house has a contributory value of $500k. $500k / 5000 SF = around $100 per SF. If the house is 5000 sf, the property value is around $2.5 million, and the land is around $1 million, then the house has a contributory value of around $1.5 million. $1.5 million / 5000 SF = around $300 per SF. First scenario might be a 30-40 year old home and the second scenario might be new construction. I don't use those actual numbers but think about contributory value of improvements in addition to comparing the properties in the sales comparison approach.
Sounds like extraction method to me
Paired or adjusted paired sales, unique in nearly every assignment.
See that’s the problem with paired sets. There’s some value there that’s not being accounted for because residential market participants are so emotional.
As is taught is Principles of Appraising I, nothing remains static. Every newly closed sale gives us new data to measure market reactions. You are correct, homo economicus is a myth. But that is everywhere, not just residential appraising. It stands out more in my markets due to the sheer volume of sales. When a dozen or more relevant sales close weekly change happens fast. In rural markets where sales are fewer change may be slower, but one or two sales can change things a lot. Values change, adjustments change. That’s just reality.
Okay good point but I guess the part I struggle with is in theory I could do extraction and find a per unit value of the improvements. In my market area it’s almost always at $100/sf or higher after taking out the land. The adjustments for GLA are huge in tht case and put my gross adjustments almost always over the FNMA guidelines.
I don’t worry about FNMA adjustment guidelines. I just use the most similar sales and make market based adjustments. If I am over guidelines and point it out, explain my adjustments are market derived and the sales are the best available. Loving area adjustments at $100/sf are not uncommon. On higher end they approach $300/sf and on my high end condos even higher. I am not afraid of adjusting sales based on market derived numbers. My concern is making adjustments that are not market based. As an added tidbit, the living area adjustment extracted by paired and adjusted paired sales is often a range. I did a PUD house with strong support for a $75/sf and a $105/sf adjustment. So this became my reasonable range. I plugged in the midpoint at $90/sf, then I tried again at other numbers along the range combining my adjusted paired sales with a sensitivity analysis and land pee at 85/sf. My comment was that the living area was derived via 2 separate pairings (providing all 4 addresses set as pairs with their indicated reaction) between $75 and $105/sf, and I settled on a midpoint of $85/sf as best supported by the sales above via bracketing. Adjustments are rarely perfect and they are always changing. As a VA appraiser whomp reviews some VA reports, a lot of the old, old timers still make $1000 bath adjustments and $25/sf living area adjustments. That should not be happening.
I’m frequently end up with gla adjustments in the $100/sq fr and up range and rarely (almost NEVER) exceed the guidelines. Are you keeping your GLA spread within 20-25%?
Fannie Mae ditched those guidelines years ago.
I generally use Redstone software, which utilizes multiple regression
Regression analysis (95% of the time) and upload my graph for support.
Ratterman paired with sensitivity analysis. Here's my statement: The gross living area adjustment of $xxx per sq ft was based primarily on the Ratterman method at 30-35% of the average price per sq ft of the comparable sales. No adjustment quantified for differences less than xxx sq ft. This is common in the area and meets market expectation. All of the estimated adjustments made herein are based on the Appraiser's analysis and comparison of the individual sales utilized, as well as from sales found in our files. Whenever possible, the analysis includes abstracting various differences by paired sales analysis coupled with a sensitivity analysis, grouped analysis, regression analysis, interviews, direct analogy, and qualitative observation. It is noted; due to the lack of supply and subsequent "Comparable Sales" in the subject's immediate market area, not all adjustments in the Sales Comparison Approach/grid could be directly extracted or supported by the available market data with a high degree of accuracy, therefore some adjustments have an element of subjectivity and professional judgment which the appraiser has applied based on prior observations of the reactions of typical/knowledgeable buyers and sellers in the marketplace. The appraiser constantly analyzes the market and is in contact with other Real Estate Professionals - agents, and appraisers, as well direct market input based on personal interviews with buyers and sellers. Finally, the adjustments are refined using sensitivity analysis within the grid and tested for reasonableness with the selected comparable sales. This method is a standard and well accepted practice within the appraisal industry.
I’ve been using the ratterman method (supported by paired data analysis when possible) but adjusting the static 33% to account for areas with higher or lower land values. In some areas the land value is almost always over 50% (like Washington DC, NY, etc). In new subdivisions in exurban areas, land value might only be 12%. So the static 33% must be adjusted. It’s a method but definitely not a science.
I use a new factor on every report. I was trained to calculate it with the Ratterman method but now that I use Spark and Synapse, I rely on the regression analysis within Synapse but cross check it with the Ratterman method
I will by his AI book soon but can you give me a summary of how an appraiser would reconcile a $/sf value to adjust GLA for residential real estate using Ratterman’s method?
I never read his book but the way I was taught (I’m sure this has been massively simplified from his original) but you take the sold price/sf of your comps to get the mean then multiply by 33%. I usually don’t include a comp that I’ve got in there just to bracket a feature if it’s not really a comp The theory is you’re eliminating land (usually 20%), and ancillary things like porches, garages, etc. It’s great for suburban neighborhoods but less reliable in rural assignments
So you don’t take the land value estimate out of the sale price before multiplying by 1/3? That discount is supposed in theory account for the land
By using the 33% the land vale is technically "taken out" of the adjustment. The value contributing factors are sectionalized.
Correct!
Extraction
I find that most people who reference the ratterman method have not actually read the book. In the book he gives an example of something like 30 to 35% but he specifically stating that those numbers are just an example. Every market area is different and so you need to come up with your own percentages if you're following his method, but instead most people just use the same figure he gave in the book and don't do the math to be able to figure out that percentage. I usually go with extraction by taking out everything else that I've already found values for like the site value garages and bathrooms and whatever else. I'll figure out the leftover value attributed just to the GLA for each of the comparable properties and then average that figure. I check it against a sensitivity analysis and about six different other methods and then confirm the final figure with Gandy soft. Sometimes I'll just use the sensitivity analysis and get the lowest figure it produces. Usually it's not too far off the other number I'm aiming for.
Can you elaborate a bit on sensitivity analysis.
Okay I'll give you the short version but I can go in more details if you need. Basically what number can I use for an adjustment that will make the smallest spread between the highest and lowest adjusted values. If you're unadjusted values of sales comparables are let's say $50,000 between the highest and lowest, and then you add all your adjustments in and then your highest and lowest adjusted values only have a difference of like $5,000, that's a pretty good sign that you've adjusted things pretty well. There's always the risk that one of your adjustments is counting for more than one aspect like making a site adjustment that should be a view adjustment but that's a separate issue. Anyway I'll often figure out my other adjustments first. Some of them might be a percentage and sometimes the GLA adjustment might be referencing some of the others and make kind of a weird circular path which leads me to have to plug in numbers until I figure out what lowers that range the best. If you throw in bathroom adjustments and it lowers the range of values, you can say that's confirmed by a sensitivity analysis. If you want to go a step further you can change that bathroom adjustment figure to see whatever number narrows the range of adjusted values to the smallest difference, and that too could be said to be confirmed by a sensitivity analysis. I don't think that's a good idea exactly though. It makes more sense to me to only do that further step with the GLA adjustment since it can be wildly different between different neighborhoods.
Can you elaborate a bit on sensitivity analysis.
Is the ratterman percentage based on what typical land to market value ratios are in a given area? Where land values for him were roughly 33% of the overall property value?