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Monday, October 5, 2020
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Saturday, September 19, 2020
To Analyze a Sales Population, Consider the Expanded Percentile Curve
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As we know, not all segments of the market move in tandem. When the market starts to move up, it generally begins at the bottom of the value strata (start-up homes) and graduates up the value ladder. Therefore, while analyzing a large sales population, it is prudent to use the entire percentile curve (as shown in the above Miami graphic) rather than just the Median as it may musk the actual pictures on both ends of the curve, say below the 25th percentile and above the 75th percentile and more precisely below the 10th and above the 90th.
How to Analyze a Sales Population
1. Single Parameter – Instead of just one parameter (like the Median), it's better to consider the expanded percentile curve, preferably 1st percentile to 99th percentile, avoiding minimum and maximum as they may skew the picture as well.
2. Sample Selection – When confronted with all sales meaning both arms-length and non-arms length and virtually no time to validate the sales, the 5th to 95th percentile sample is more meaningful, without having to spend time on manual validations. Conversely, if the sample comprises only the arms-length sales, the 1st to 99th percentile range could be more meaningful.
3. Outlier Analysis – Therefore, while studying outliers of a sample lacking validation, it's better to consider only the cases below the 5th and above the 95th percentile. Likewise, below 1st and above the 99th could be a better starting point for a validated sample, gradually extending out to the outliers on both ends of the percentile curve (as time permits).
4. Sales Timeframe – When the timeframe is extended (9 to 24 months), sales must be time-adjusted, preferably at the monthly level (deriving monthly time factors). If the sample comprises 3-4 years' of sales, quarterly adjustments will make more statistical sense. When an extended series (e.g., 10+ years) is analyzed, annual factors would be appropriate. Most extended series analyses are performed to detect seasonality in the data.
5. Growth Factors – As we all know, the residential market is as local as it gets. Therefore, a good sales analysis must additionally be broken down to the sub-market level as long as those sub-markets are well-established and accepted. Since the growth rates vary by the market, time adjustment factors must be derived at the sub-market level (e.g., 12% in our example for the City of Miami). Applying national or even regional factors could result in flawed and indefensible results. Time adjustment in AVM is generally different (will be discussed later).
6. Use of Median – Due to time constraints, If one has to choose one parameter to ascertain time's impact, it must be the Median, as it is less prone to outliers (outliers heavily influence average, often distorting the analysis). In an even like that, the sale's Median must be compared with the normalized (by Bldg SF) Median, ensuring they are close to each other.
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7. Spatial Distribution – As part of the sales sampling, one must also ensure that the sales are spatially distributed in line with the population, so a meaningful spatial chart is in order alongside the data tables. In the above example, one must understand that the Median ASP and Median Bldg SF are mutually exclusive, but they may be connected to get a general idea of the ASP/SF, but not for any serious analysis. To analyze the normalized ASP/SF, one needs to create the organic variable (row-wise ASP/SF) and the run percentile stats.
8. Creating Sales Ratios – In the above example, in addition to the percentile analysis of sales, the distribution of sales ratios (ratio of County Market Values to Time-adjusted Sales or ASP) is shown, thus connecting the apples-to-apples dots. The spatial chart additionally depicts the stratified sales ratios. Caution: While creating the sales ratios, one must time adjust the sales to the valuation date (in this case, 01-01-2019) as the tax roll values are as of that date, or else it would be an apples-to-oranges.
9. Regression Values – Ideally, ASP should be modeled (using multiple regressions or any other industry-accepted methodology). The resulting sales ratios of the regression values (which are smoother and statistically more significant) used all analyses, Including defining and removal of the model outliers. Regression values could also be used to challenge the tax roll market values additionally. When there is a paucity of comps, such regression values could also be used to proxy actual comps in a comparables grid.
In a nutshell, to get a better picture of the overall market, an expanded percentile distribution analysis of sales is significantly more meaningful than a simplistic median-based sales analysis. Additionally, normalized values and spatial sales ratios could provide better insight into the building blocks.
-Sid Som, MBA, MIM
homequant@gmail.com
Thursday, September 10, 2020
These 9 Enhancements will make most Assessment Rolls Fair and Equitable
Despite statistical modeling, the vast majority of assessment rolls remain moderate to highly regressive, meaning the middle-class homeowners often subsidize the upscale homes. In other words, the homes in the lower-to-mid value range tend to be over-assessed while the higher value segment gets a significant break. The use of the antiquated CAMA modeling cannot fix that problem in major jurisdictions with highly complex housing stock, but setting and adhering to the following issues would take those jurisdictions in the right direction, leading to more equitable tax rolls.
1. Backward-bending Status/Valuation Date: Since the Taxable Status Date (or the Valuation date) is often a futuristic date, the available market information and data tend to be quite inadequate to develop proper predictive (mass appraisal) models that, in turn, generate the assessment roll. Case in point: Many taxing jurisdictions utilizing the CAMA (mass appraisal) modeling generally build their models in August/September with the available data, targeting the next January as the status date, creating an enormous predictive (data) gap. A vast majority of those modelable sales would have been contracted in the first and early second quarter of the year (the gap is direr!). Therefore, the status/valuation date must be set back in line with the availability of the modelable data, to avoid having to produce (or gamble with) a futuristic roll.
2. Short-term Sales: When the holding period of the property is less than two years, those sale prices must be anchored as market values, thus forcing the potential gamers (institutions, flippers, etc.) to pay higher taxes. The point is that the housing market's rapid institutionalization needs to be evaluated separately, without having to redistribute their share (of the burden) on to the rest. Therefore, assessors must aggressively lobby to remove the application of any state/charter restrictions (e.g., annual growth capped at 5%, etc.) from short-term sales, so they stand on their own at the market level, without any pseudo protection. Exclusion: non-arms length sales (inter-company, distressed sales, etc.).
3. AVM/CAMA Application: Since Automated Valuation Modeling (AVM is a top-down econometric solution encompassing the vast majority of residential properties on the roll) is inherently more equitable, it must be applied to the rest of the tax roll, including the non-arms length from #1. An independently developed challenger model should point to the outliers at the population level, requiring them to be separately hand-worked (using the analysts' traditional comparable sales approach). Depending on each roll's complexity, these models generally work well between the 10th and 90th percentile of the value curve, so the rest should be scrutinized and perhaps hand-worked. Unfortunately, failing to pay proper attention to the aforesaid outer bounds often degrade the entire roll. The point is, AVM/CAMA should be applied where it is applicable.
4. Unique Properties: Again, due to the paucity of arms-length sales, AVM/CAMA values are not meant for this group (trophies, mansions, large waterfronts, tiny oceanfront bungalows, etc.), so they must be hand-worked by the assessing staff. The sale of unique or vastly atypical properties must not enter the modeling (AVM) sales sample. Right at the outset of modeling, separation of such categories must be discussed and isolated from the modeling spectrum altogether. Such decisions help enhance the marketability of the roll. Still, when the modelers arrogantly apply models to these strata, the values are generally indefensible, forcing taxpayers and other external agencies, including media, to question the entire roll value.
5. 2-to-4 Family Properties: Although assessment and mortgage statues generally lump these properties with the single-family residences (SFR), they must not co-share the SFR roll, considering these are inherently income-producing properties. Therefore, they must be modeled, valued, and taxed as a separate group or as a sub-group (small cap) under the multifamily group. Depending on the liquidity of this group, they could even be market modeled standalone or hand-worked. If the market approach, rather than the income approach, is used to value them, that approach must not change from year to year as that could introduce significant inequity.
6. Outsource AVM: It's much cheaper to outsource residential AVMs to a financial consulting/research firm (but not an appraisal or CAMA outfit) than maintaining a dedicated group of in-house modelers. It will also be more effective as those firms are non-political, and as such, their feet would be held to the fire for proper performance following the performance metrics contained in the contract. For example, one such metric could be the level of appeals meaning if the appeals go up due to flawed assessments, they could be forced to make the necessary corrections promptly without any political interventions or cover-ups. Conversely, partisan politics plays a significant role when the values are internally generated, especially when the Assessor is not an independently elected official.
7. Manpower Planning: Larger jurisdictions must learn from the private (FedEx, UPS, Amazon, etc.) how to use the seasonal help. For example, the seasonal help could be used to process exemptions, appeals applications, income/expense statements, etc. They can be used to perform field operations and inspections too. Alternatively, counties/taxing jurisdictions may maintain a "Central Pool" agency to cater to the different agencies based on their seasonal workforce requirements. Maintaining full-time personnel to handle seasonal activities is often the case – is an expensive and wasteful proposition, returning minimal value to the taxpayers. Even when an internal modeling group is maintained, it must be hired and kept outside of the civil service/union system, allowing navigational adjustments.
8. Practice Assessment: Instead of having an autonomous appeal or review department, it's better to have it under the Assessment umbrella. Having a separate government agency or department is inherently political and is not necessarily in the taxpayers' best interest. Often, the focus of such autonomous appeals/review agencies is to hire appraisers, rather than trained assessors, which does not promote equity of the roll as they generally lack the understanding of assessment equity. Moreover, such autonomous political agencies quickly learn that the workforce's growth solidifies the ground under their feet, thus gradually distancing themselves more and more from the Assessor's office and growing into a powerful political body. None of this helps improve the quality of the assessment roll.
9. Commercial Assessment: To promote equity of the commercial segment of the tax roll, departments must practice assessment, not an appraisal. Therefore, it's prudent to collect a sizeable Income and Expense (I/E) sample to develop meaningful local metrics for the commercial properties. These I/Es could also be used to formulate use-based AVMs to process the homogeneous properties like 4-to-10 family rental properties, small office complexes, mixed-use properties, public storages, smaller warehouses, and industrial properties, etc., in turn, creating more equity across such denominations. This approach would free up assessors to devote more time to the complex commercial properties where modeling is futile or unnecessary. Commercial appraisers must also be trained and groomed to transition from an all-appraisal mindset to an assessment equity-oriented thinking.
Flood Zone Insurance: Last but not least, it's essential to enforce the flood zone insurance. Homeowners inside the designated flood zones must be required to carry flood zone insurances. Should the situation arise, insurance companies would be on the hooks, not the rest of the taxpayer population. Of course, an annual credit could be offered to offset a minimum policy deductible.
Again, having an all-encompassing residential AVM does not make the roll fair and equitable; it must be properly sourced and targeted. Likewise, training and promoting a group of unqualified employees as AVM/CAMA technicians do real injustice to the roll. Finally, use-based Income models off of actual I/E data could promote equity across commercial property groups' homogeneous stretch.
-Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com
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