Zillow Home Value Index Methodology, 2019 Revision: What’s Changed & Why
Editor’s Note: Starting with the January 2023 data release, and for all subsequent releases, the full Zillow Home Value Index time series has been upgraded to harness the power of the neural Zestimate. Please refer to this page with the current methodology for the most up-to-date information on how the Zillow Home Value Index is calculated.
The Zillow Home Value Index (ZHVI), built from the ground up by measuring monthly changes in property-level Zestimates, captures both the level and appreciation of home values across a wide variety of geographies and housing types (e.g. all 1-bedroom condominiums in ZIP Code 98101).
The index is optimized to achieve three main objectives:
- Timeliness: Data for a given month is published on the third Thursday of the following month – i.e., data for November 2019 is published Thursday, December 19.
- Other housing indices often publish monthly data at a significant lag of one month or more after the close of a given month.
- Comprehensiveness: The ZHVI draws on Zestimates calculated on more than 100 million U.S. homes, including new construction homes and/or homes that have not traded on the open market in many years.
- This offers a fuller picture than indices that rely solely on data recorded only on those homes that sell in a given period.
- Visibility: Because of the way the ZHVI is constructed, it gives users the ability to observe dynamics in very small regions and/or among very specific subsets of homes.
The ZHVI was launched in 2006, and in its most recent iteration prior to publication of November 2019 data it was calculated as the median Zestimate value for a fixed (over time) set of homes in a given area, representing that area’s median home value. Because the stock of homes was fixed over time, month-over-month growth under these assumptions could be interpreted as appreciation of the typical home.
Beginning with publication of November 2019 data, and for all subsequent releases, the ZHVI has been recomputed using a new methodology. November 2019 data is historically recalculated through 2008. A more complete time series dating to the mid-1990s will be published in 2020.
The ZHVI will now be calculated using a new set of assumptions:
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- The average Zestimate within some range of home values determines the index level, meaning the index retains its interpretation as the dollar value of a typical home.
- Monthly changes in the index are now calculated using a weighted mean of the appreciation of individual homes, as proxied by changes in the Zestimate. The weight of each home in the index is proportional to its Zestimate in the first month of any monthly pair.
- For any geography or cut, index appreciation can now be interpreted as the market’s total appreciation. In other words, the ZHVI appreciation can now be viewed as the theoretical financial return that could be gained from buying all homes in a given subset (by geography and/or home type) in one period and selling them in the next period.
Several other new features have been incorporated into the new methodology, leading to a number of improvements.
More representative of a market’s overall appreciation
Changes in median home value, as calculated previously, do not necessarily reflect how the overall market is moving. For example, a market in which the median home value is barely moving could be a reflection of homes at the higher end falling in value while homes at the lower end grow in value. In this example, the overall market could actually be trending downward, which would be reflected through the price weighting features of the new methodology but would not be captured by simply looking at the median.
Historical appreciation is based on the housing stock that actually existed at that time
Previously, the ZHVI was calculated over a fixed basket of homes over its entire history to ensure that the median comparison across periods had a value appreciation interpretation. Had it not been calculated across this fixed set of homes, differences in the median could have reflected differences in the composition of the housing stock — such as the opening of a large subdivision of higher-end homes — rather than more comprehensive appreciation driven by market forces. But under the older method, appreciation was always taken over this fixed set of homes, regardless of whether they existed at that point in time or not (new construction and demolitions were ignored).
To better reflect the appreciation of both the historical and current housing stock composition, the new methodology resizes the housing stock annually based on what actually exists. This makes it a more accurate current and historical measure of home value appreciation, especially in smaller regions that may have grown a lot and in which the housing stock has changed considerably over the years.
The price level of the current housing stock is accurately presented
Another advantage from updating the housing stock is that the most recent index level will represent the average value of what is actually built reasonably close to the current date. In contrast, the old index’s median would have been restricted to the housing stock at the latest fixed basket, which could have represented the years-ago state of a given area’s housing stock.
Corrects for home appreciation driven by home improvements
Homes that have had significant changes in features, quality and/or size will experience associated value changes that are unrelated to market movements. For example, adding a bedroom to a home will generally increase its value regardless of market forces. These types of changes are not reflective of overall market appreciation, but instead reflect the change in quantity and/or quality of the housing stock and as such should not be included in an appreciation calculation. The new methodology addresses these issues by imputing the appreciation values for such homes as if they had had no improvement.
Ability to create more custom-weighted versions
The flagship version of the ZHVI uses a value-based weighting for each home’s appreciation. But the general methodology is much more flexible and allows custom versions that skew the weights away from a value basis. For example, a municipality could measure the increase in its property tax base by using a weighting scheme proportional to individual properties’ assessed value instead of their Zestimate. Or the index could be used to track an institutional investor’s exposure to a portfolio of homes, such as in a securitized mortgage pool or a residential REIT, by weighting those homes proportional to their dollar exposure in those financial instruments.