Housing Affordability for Homeowners
What does this measure?
The ratio of the median home value divided by the median household income, adjusted for inflation.
Why is this important?
This ratio provides a rough estimate of the affordability of homes in a community. A ratio less than 2 or 3 is considered affordable.
How is Ulster County performing?
In 2010-14, Ulster's housing affordability ratio was 3.07, higher than the state (excluding NYC) and national ratios and on par with the region. Ulster's rate was between Dutchess (3.12) and Orange (3.01) in 2010-14. As was the case for the region and the other counties, Ulster saw its ratio rise from 2.08 in 2000 to 3.40 in 2005-09, before falling somewhat from 2005-09 to 2010-14. However, the rate in 2010-14 remains 48% above its level in 2000.
The local municipalities with the least affordable homes were Olive (3.95), Shandaken (3.66), and Woodstock (3.86), while the most affordable homes were found in Rosendale (2.90), Ellenville (2.52), and Kingston (2.71).
Notes about the data
Multiyear figures are from the Census Bureau's American Community Survey. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval). The survey provides data on characteristics of the population that used to be collected only during the decennial census. Regional ratios calculated by weighting county medians based on share of population. Data for this indicator are expected to be released in the fourth quarter.