Collateral Analytics, a provider of automated valuation solutions and analytic products for the real estate industry, recently announced it has developed a new home price model that draws upon long-run factors and short-run market conditions to predict prices one year in the future.

Long-run factors consist of key drivers such as local employment and the affordable price, which is driven by household income and interest rates. Short-run market conditions incorporate a wide variety of factors related to the recent regional sales and the current set of listings of properties on the market, such as the months of remaining inventory and the number of foreclosure sales relative to regular sales.

In addition, Collateral Analytics also has produced its own index of overall market conditions that captures a larger set of these local market conditions.

“Our approach to modeling future price changes rests heavily upon the belief that such changes are heavily dependent upon local market conditions and the responsiveness of local house prices to these variables,” Collateral Analytics President and CEO Michael Sklarz said.

The key long-run factor is the gap between the level of prices and the level predicted by employment and affordable price data. All else equal, the larger this gap, the slower the predicted growth in prices. The three short-run factors in the new model are the months of remaining inventory, Collateral Analytics’ proprietary index of local market condition, and the ratio of foreclosure sales to total sales.

A key benefit of the new short-term indicators is that they better identify important inflection points in individual real estate markets.