Monday, September 29, 2014

Non-residential residents

Tax rate questions have been coming in recently, specifically around special situations that larger landowners or those who own multiple lots may face.

The Vermont Legislature defines three tax rates each year for Education Taxes:
  1. Homestead
  2. Income Sensitivity
  3. Non-residential
We usually comment that most residents pay a combination of the above rates.  This can include the Non-residential rate in certain circumstances.  Here are some of the most commonly overlooked cases:
  • Income Sensitivity rates (households that make less than $90k per year) apply only to your primary housesite.  A housesite is defined as your house plus (up to) two acres of land.   Additional acreage on the same lot are taxed at the Homestead rate.
  • If you own a lot adjacent to your primary house lot, it will be taxed at the Homestead rate only if its ownership is identical to that of your primary house lot.  If the name on both deeds is not identical, then the abutting lot is taxed at the Non-residential rate.  
  • Additional non-adjacent lots are taxed at the Non-residential rate.
 It is possible that Westford residents are affected by two or three of the above rates.  It is important to review your property tax bill to understand which situations apply to you. 

Friday, September 5, 2014

...compared to what?

When we discuss school data, you'll often hear me use the phrase "compared to what?".  This reflex is because a great deal of numbers we are inundated with are presented without context.  We are left to interpret the data without the basic foundation of what it is we should be measuring. 

"...compared to what?" should provoke us to look for three critical pieces of context:
  1. Compared to the standard.  How does our data look like versus an accepted standard?  Did we meet that standard?  
  2. Compared to ourselves.  What does the historical data say?  Does the data show movement from the last time we measured the same thing?  What are the trends over time? 
  3. Compared to others.  What are the possibilities?  How are others doing?  This will give us an idea of what we could aspire to do.  
When the above three pieces of context are provided, data can look very different.  A simple example of this would be in how student proficiency is reported for standardized testing.  The percentage of students deemed proficient is reported for three local schools.


Without any context, this data looks mixed.  All three school have a majority of their students considered proficient, but a gap exists.  How would you rank school quality?  Most would choose School A as the best school and School B as the worst.  But, compared to what?

Compared to the standard The expected standard for student proficiency subject was 65%.   All of the three schools met the standard, despite a wide margin between highest and lowest percentages.  Without including the context, it would be easy to label Schools B and C as under-performing.  Now how would you rank school quality?  Will that opinion change when the expected standard increases to 85% in the next year and none of the schools meet the standard?

Compared to ourselvesLooking back at four years of testing, we get a vastly different picture.


School A has shown a sharp decline, School B has shown dramatic improvement, and School C has remained very steady.  Clearly something has happened at School A and School C in the past four years which needs further explanation.

Has your opinion changed on Schools A, B, and C concerning school quality?

Compared to othersHow did other schools perform?  

When other schools are added to the comparison, it becomes clear that not all showed similar levels of success.  Schools A, B, and C have a significantly higher percentage of proficiency than other schools.  School B has shown that performance gains can be made, and may serve as a model to Schools D, E, and F.  


This example is meant to show how critical it is to ask for deeper context in each piece of data and decision we review.  The next time you see data or a statistic presented by itself, don't forget to ask...compared to what?