In real estate, the principle of regression is simple. It is the phenomenon of valuable properties having their value diminished by the surrounding lower-value properties. If you’re familiar with the advice to “buy the cheapest house on the block,” you’re familiar with the principle of progression, which is where a low-value property’s appraised value is boosted by the presence of the high-value properties surrounding it. Regression is the opposite of progression, and it is a legitimate concern for home sellers and buyers.

As a real estate agent, keep yourself up to date on the average home values in the neighborhoods where you make sales. New migration patterns, economic changes, dilapidation of older homes and buildings, and the influx of new businesses in a neighborhood – particularly specific retailers like Starbucks and Trader Joe’s – can drive property values up or down. Property value fluctuations don’t occur on an individual basis; when there’s a big change like one of those described above, property values throughout the neighborhood change. In cases where values regress, this means a value nosedive for the newer, more valuable homes in the neighborhood.

Examples of Regression in Action

The principle of regression operates similarly to the principle of conformity, which states that a home with amenities far outside its neighborhood’s typical offerings will not be appraised at its true value because of its deviation. For example, a large, modern home in a neighborhood comprised of smaller, older homes will be undervalued because the typical buyer looking for homes like the larger, modern one is not looking for homes in neighborhoods with small, old homes.

Put into dollar figures, regression works like this: in a neighborhood where the average home is valued at $300,000, a house worth $500,000 in another neighborhood won’t be appraised for $500,000, even if it’s identical to a home that is valued that high just a few blocks away.

Put into a hypothetical scenario, imagine an individual buys one of the houses in that neighborhood for $280,000, with the intention of adding on two additional bedrooms and another bathroom, bringing its value beyond what it had appraised for when it has only three bedrooms and one bathroom, typical for its neighborhood. Although a five bedroom, two bathroom house might sell for $450,000 on the other side of town, this particular house might only reach $425,000 because it’s surrounded by properties that are worth an average of $300,000.

How Real Estate Appraisers Use the Principle of Regression to Value Properties

The principle of regression is an important one to real estate appraisers. Here’s how it works in this context:

  • Appraisers determine the sales figures for similar properties around the one they are appraising. Home values are represented as price per square foot, or found by dividing the home’s determined value by its square footage;
  • With these figures in mind, the appraiser then looks at the differences between the properties. These could be differences in the number of bedrooms, differences in lot size, and differences in square footage. It is important to keep in mind that bigger does not automatically mean more valuable when it comes to homes. Other factors that impact individual property values include the condition of the home’s interior and its layout; then
  • Using this data, the appraiser can chart individual properties as points on a graph and see how, controlling for specific variables, an individual home’s value can be negatively impacted by lower-value properties nearby.

Ultimately, a home’s appraised value can do a lot of things. It can be the reason why a prospective buyer backs out of a deal – after seeing what a home is really worth, he or she may choose to look elsewhere to find a home that’s a better value. Or it can be used to determine a home’s value as a marital asset in a couple’s divorce. Commercial properties are appraised, too, for asset valuation purposes in bankruptcies, mergers, acquisitions, divorces, commercial sales, and commercial purchases.

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