Go figure

What those MLS numbers mean and how to use them to help you market and price homes.

by Jack Harris   Many multiple listing services provide monthly statistical reports to their members. These reports provide a picture of market conditions and recent trends. But usually there is no narrative explanation, so each user is required to make her own interpretation. In addition, the Real Estate Center at Texas A&M University provides similar and additional figures for most metro markets in Texas. Each of these indicators has a story to tell as well as limitations that can mislead the unwary observer. Here’s an overview of some of the reasons you may want to look at housing stats and see which indicators are most promising.

How active is the market?

The best measure of housing market activity is the number of home sales closed each month. The sales number also is a good indicator of underlying housing demand, since sales activity most often is driven by the number of able buyers rather than the supply of available homes. Demand and consequent sales activity are important because they indicate the health of the market. You may have rising prices even when sales are dwindling. Rather than a good sign, this combination is characteristic of a speculative market, an unstable condition usually preceding a steep downturn in sales.

For the number of sales in any one month to mean anything, it has to be related to something. Most often, we like to show how the current month compares to a previous time period. One problem we run into with many economic data series is that some months tend to be more or less active than others on a regular basis. Economists call this pattern "seasonality," and it can complicate our ability to measure change using monthly data.

The table shows the number of sales closed through Texas multiple listing services during 2002. Note how sales build during the spring and tail off after the summer. You probably experience the same seasonal pattern in your business: relatively more busy in the spring than in the fall and winter. Remember that these numbers reflect closed sales and lag the actual sales agreement by one or two months.

If you calculate the percentage rate of change from month to month (column 3), you pick up mainly the seasonal effect. As you can see from the table, this reveals little about where the market is headed. To overcome the problem, we compare each month with the same month in the previous year (column 4). Now you can see that the year started out surging ahead of last year’s pace, but ran into resistance after May as the economy began to discourage new sales. The apparent boost in September and October was due to the depressed level of activity around the terrorist attacks in 2001. Finally, we see how interest-rate declines boosted sales in December.

Another way to overcome the problem of seasonality is to use 12-month moving averages, or in this case, 12-month moving sums. A moving sum is just the total of the current month and the previous 11 months to provide a full year’s total sales. Since each number includes a full year of months, seasonality is nullified. The problem with any moving sum or average is that the current month can get lost by being thrown in with all those previous months, making it impossible to pick up any kind of short-term trend with this indicator.

If you have a long series of data, you can construct a seasonally adjusted monthly number. This is what NAR does in its report on national and regional sales. The seasonally adjusted sales indicator has been modified to compensate for expected seasonal variation, as determined by analysis of past years. The number reported is a forecast of the total annual sales based on sales in the current month. This is good for assessing trends, but it can be hard to interpret if the numbers show no consistent trend.

What are homes selling for?

Sales price is a useful piece of housing market data. Expressed as an average or median price, this indicator reflects the value of a typical home. Because housing prices often are distributed unevenly, and the fact that there is a lower limit of zero but no upper limit on prices, market analysts prefer the median price over the average. The median price is a number that exceeds the price of half the sales and is less than the other half. Its advantage is that extreme prices at either end of the scale do not affect the level of the median.

When the median price is compared over time, we get a sense of where property values are headed. For example, median prices for several years have been rising. At the same time, inventories of listings have declined, indicating a seller’s market. Under such conditions, you would expect steady price increases.

But does that mean that homes are going up in value? Probably, but tracking median values can give a misleading indication of value change. There is no control on the sample of homes sold in any one period. If a lot of small, inexpensive homes sell in one period, while a lot of upper-end homes sell in a later period, median price will increase. However, that does not mean that the value of a typical home increased over that time.

Here is an example using real-world numbers. In 1996, the Texas housing market began to boom. Sales reported through the MLS jumped to 138,000 from 121,000 the previous year, and the median price went from $81,600 to $86,400. According to these numbers, the typical home gained almost 6% in value. A good portion of this increase, however, must have been caused by buyers upgrading the size and quality of their purchase, since the home value index compiled by the federal government shows Texas homes appreciated by only 1.3% during 1996.

In many cases, median-price increases do indicate higher values, but the indicator is not foolproof and the amount of increase may be distorted. Moreover, there are better measures. Many MLSs provide median sales price per square foot, thereby neutralizing the issue of comparing sales of different-sized homes. This measure is a better indication of value change, even though it does not control for quality or location differences. Some markets are covered by a constant-quality price index compiled by an appraisal firm or university research center. If your market does not have such coverage, you may want to look at the index compiled by the Office of Federal Housing Enterprise Oversight (www.ofheo.gov). This federal agency is charged with keeping track of Fannie Mae and Freddie Mac, and they use data from the loans purchased by those companies to calculate an index of market value. The data come out quarterly and are available for states and metropolitan areas.

How affordable are homes now?

The price level per se can be important as an indication of how expensive homes are. Rising home prices are great for current homeowners, but they can be a big problem for first-time buyers and people moving into the market area. These types of buyers are vital to keeping a market going, since they buy the homes of local residents who want to upgrade. If newly entering buyers can’t afford homes, it can bog down the whole market.

Despite rising prices in recent years, affordability has not suffered, because interest rates continue to slide downward. If mortgage rates fall from 7% to 6%, a buyer can pay about 10% more for a home and still have the same monthly principal and interest payment. Just looking at median prices fails to reflect the effect of interest-rate change.

To judge affordability, you have to look at buyers’ ability to pay. What is affordable to a $125,000-per-year family would be overwhelming to a $30,000-per-year household. So, we have to relate cost to ability to pay. That is what we do at the Real Estate Research Center in compiling the Texas Housing Affordability Index (THAI). We first calculate the monthly payment required to buy the median-priced home in each market. This is based on current interest rates, a 30-year term, 20% downpayment, and an estimate of local tax and insurance costs. We then divide that into 28% of the local median monthly household income (similar to what a mortgage loan officer would do to qualify a buyer). The resulting ratio is the value of the index. A THAI value of 1.10 means the median income is 10% higher than needed to buy a median-priced home. Likewise, a value of 0.90 would indicate that income was 10% short of what is needed. We also calculate a First Time Housing Affordability Index that is based on the ability of resident renters to afford an entry-level home using FHA financing. Indicators are estimated quarterly for the state and most metro markets and reported on the center’s Web site (http://recenter.tamu.edu).

Is it a buyer’s or seller’s market?

Most experienced agents recognize that there are times when sellers can get everything they ask for and times when buyers are hard to find and can drive a hard bargain. There often are situations when part of the market is a seller’s market and other parts are buyer’s markets. Generally, a high number of sales corresponds to a seller’s market, while depressed activity favors buyers, but just looking at sales volume does not really indicate the balance of supply and demand.

One statistic often used for this purpose is average days on the market (DOM). The indicator is the average time required to sell (period between the date when the listing was put in the MLS and the date of the sales contract) those listings sold during the current period. If the average listing takes only a month or two to attract a buyer, that is indicative of an active (seller’s) market. Conversely, average DOM of five or six months might indicate a slow (buyer’s) market. Average DOM can be tricky when markets are particularly slow, because some sales fall through after the contract is signed, and some listings fail to sell and have to be renewed. A listing leaving the system to be renewed or re-entered may be recorded as a new listing, and the DOM starts from scratch. So the average might be distorted.

An alternative to DOM is months inventory (MI). This indicator is calculated by dividing the current inventory of listings by the average monthly sales for the previous year. In other words, MI is an estimate of how long it would take to sell off the entire inventory if recent sales trends continue.

As shown in the chart, low values of MI tend to coincide with higher rates of increase in the median sales price. In other words, when inventory is relatively tight, prices tend to rise faster than when inventory is abundant. The relationship is far from perfect, but it appears that MI values greater than eight are associated with buyer’s markets (low rise in prices) and those below six signal seller’s markets (high price increases).

Some MLSs report average-sales-price-to-listing-price ratios. This stat reflects the relative bargaining power of sellers and buyers and, thereby, the existence of a buyer’s or seller’s market. A zero or small discount shows sellers are in charge, and a large discount suggests buyers are getting their way. However, if conditions do not change, eventually sellers will learn to price listings according to the market and the indicator loses value.

What are the hottest areas?

Earlier, I mentioned that some parts of the market may be stronger or weaker than other parts. It may be that certain neighborhoods are especially sought after, or that a whole price range of homes is in short supply while other price classes languish. It is important to know the condition of the market in the area or price range of the homes you are trying to sell or the type of home your customers are looking at. This can be helpful when advising clients on pricing and negotiating decisions.

You can get some indication by looking at a distribution of sales by price bracket. A typical distribution table shows the percentage of total sales in each price range over a period of years (the center’s Web site includes such a chart for most Texas metro areas). By comparing sales over the years, you can see if homes priced at the level you’re interested in are selling more or less in the current market.

One problem with comparing years is that overall prices tend to climb each year, and this tendency distorts the brackets. The price increase means that more homes will sell in the higher brackets and fewer in the lower brackets each year. Some MLSs report months inventory by price range. With this indicator, not only do you not have the problem of bracket creep, but you also get an indication of how sales compare with available supply. In a recent report on the Dallas-Fort Worth market, MI varied from 2.7 months for $100,000 to $109,999 homes to 21.5 months for those asking $1 million or more.

Months inventory also may be reported by the market area subdivisions established by the MLS. So you can tell where the buyer’s and seller’s market areas are located from these data. Some MLSs also have a "hotness" indicator for each subdivision. This measure shows pending sales as a percentage of available inventory. Normally, a listing is taken out of the active inventory when a sales contract is signed. Until it is closed, the listing becomes a pending sale. The hotness ratio indicates the significance of the most recent sales (i.e., those that are still pending). By comparing the ratio for different areas, you get an indication of where people are buying homes today. Consider that all the other stats on sales are based on closed transactions, meaning that the actual decision may have occurred a month or two previously. The hotness indicator is an attempt to present more current data.

We have become accustomed to being surrounded with data and are becoming aware that raw numbers do not necessarily provide a clear picture of what is happening. A better understanding of how the numbers are derived and what they mean is essential to getting the most out of the flood of data available.

Jack Harris, Ph.D., is research economist at the Real Estate Research Center at Texas A&M University.

Photo © PictureQuest.

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