Sales Ratio Study

As part of its modeling, Tyler needs to prove its algorithm works. So it handpicked 1294 sales (and counted two of those twice), and produced a “Sales Ratio Study“.

Based on those results, it looks great! And well within the limits for the coefficient of dispersion given by New York State: https://www.tax.ny.gov/pubs_and_bulls/orpts/ownershandbook.htm.

But that’s because they only cherry-picked 53% of the sales during the period they were looking at — they chose to ignore 1,135 sales! So what if we used ALL of the sales between 7/1/2013 and 7/1/2015? and what if we used the sales AFTER 7/1/2015?

sales ratio study analysis

Instead of a good R-squared metric of 0.97, you get under 0.9, with a coefficient of dispersion of 159% and 289%, showing how much worse the actual model is than implied by the 7.5% coefficient calculated when cherry-picking 1300 sales out of the available 2400.

This Excel file (sales ratio study check) shows the details of arriving at the above numbers.

Another look at the land model and the 2I7 neighborhood

Tyler printed and then scanned “details” of their land model, without any context or explanation.  As discussed in an earlier post, fewer than a third of land values actually follow this model, so let’s take a closer look at a particular neighborhood, “2I7” in Irvington; a commenter had asked about this in an earlier post.

Neighborhood “2I7” is the “village” area of Irvington and includes Main Street and its side streets, as well as Barney Park, Station Road and its side streets. There are about 401 parcels, of which 285 are “residential” parcels.

The land model published on their website is adjusted by a fudge factor in over 95% of the residences in this neighborhood, applying a 5% to 20% penalty, and some adjusting the land value 50% more than their published model. It seems that Tyler is admitting that their algorithm doesn’t work and is using these fudge  factors to chase the sales for the appearance of accuracy.

The land model assumes that the minimum value of any residential lot (0.3 acres) is $483,000, yet there were several sales in the neighborhood for larger lots and livable houses at values far less than this minimum value; some examples: one at $365,000 and another for $230,000. Clearly, this land model is inappropriate.

As we can see, based on the model, and the smallest parcel in the neighborhood, the first 0.3 acres is valued at $16million per acre, and after that, the remainder valued at $787,500 per acre, unless some of your lot is deemed to be “residual” or is divided legally into a separate parcel as “vacant land”, where that land would be valued at only $62,500 per acre.

So if you have a 0.2 acre parcel, Tyler would value the land at $617k, but if that same 0.2 acre parcel was legally two 0.1 parcels, the land would be valued at $544k; clearly this is a mistake.

The two charts below are just two demonstrations how ludicrous the model is:

valueperacre

The following assumes a change to “residual” value after 0.4 acres; that bend is arbitrary and may be applied per the whim of the Tyler adjuster:

landvalue

 

Some other notes on the neighborhood:

This neighborhood was one of the hardest hit, with Tyler’s initial preliminary assessment increasing the market value on 99% of the residences, more than half seeing their assessments increasing by 75%, and more than half seeing an increase of over $300,000

Between the preliminary assessment and the 2016 tentative rolls, Tyler made “corrections” on many of the residences, adjusting 41% downward, seemingly admitting that the whole algorithm is wrong.

This is another clear example of how Tyler Technologies got the reassessment completely wrong, yet the politicians and overseers of the project have 100% faith in the process, never once questioning it.

A closer look at Tyler’s “intra-class shift” analysis

On page 6 of Tyler’s “Reassessment Tabular Statistics” pdf document, they provide a disingenuous analysis of the intra-class shift. In this analysis, they include all ‘fully exempt’ properties, and classify them as ‘commercial’ properties, fudging the numbers to hide the full impact of the erroneous reassessment process.

Tyler’s analysis:

tylershift

Using the changes from the 2015 final roll to the 2016 tentative roll, only counting matching parcels whose “class” did not change, and not counting any fully exempt properties that have zero tax liability.

actualshift

Unlike Tyler, who has hidden behind selective analyses and has repeatedly refused to provide a full dataset which could be used to provide a competing (and arguably more correct) model or even validating analyses, I am providing an excel sheet that was used to generate this analysis, for anyone to download and analyze the data as they see fit. The data in this spreadsheet came directly from the assessor’s website:

 

I have more data available; if you want access to the full database, please email me and we can give you the whole dataset.

 

The Bottom Line for the Residential Class:

Median shift across the town is +1%.

Median shift within Irvington and Edgemont is 5%, approximately $1,000 increase.

Tyler Tech’s Corrections

Since the 2016 tentative rolls were published (http://www.greenburghny.com/Documents/2016%20TENTATIVE%20ASSESSMENT%20ROLL.pdf), we can check on how many lots Tyler adjusted:

of the approximately 27,000 taxable lots, 680 saw increases and 2880 saw decreases in the assessed value from the preliminary to what was published; total net decrease of about $376million.

Increases on single family homes were as much as 4million, with percentage increases of up to 150%. Decreases on single family homes reduced the assessed value as much as 48%.

Vacant lots were much more egregious; these saw decreases of as much as 100% (fully discounted!) and increases of over 350%.

By the type of lot:

single-family homes: 11.4% had decreases, 2.5% had increases (1984, 433 of 17422)

1, 2, and 3 family homes: 11.1% decreases, 2.4% increases (2080, 455 of 18672)

residential vacant land: 25.5% decreases, 0.9% increases (464, 16 of 1813)

 

Clearly, Tyler was doing something wrong to get that many changes, and so many with significant variances. Also note that the above does not count anything they didn’t look at again, like most under-assessed lots, as well as any lots they opted to not change out of pride, spite, or indifference.

 

breaking down the corrections based on school district:

school % homes decrease % homes increase
tarrytown 9.4% 2.9%
irvington 19.3% 3.5%
dobbs ferry 11.5% 7.2%
hastings 14.9% 2.9%
ardsley 9.7% 1.6%
edgemont 20.3% 2.0%
g7 5.2% 1.4%
elmsford 4.6% 0.6%
pocantico 12.8% 2.6%
valhalla 12.0% 1.0%