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Price Measurements of Residential Real Estate Markets

Posted: 26-12-2008 | Views: 185

is no perfect measure for any broad financial market activity, and real estate markets are one of the most difficult to measure accurately. There are a number of methods for measuring prices and price changes in residential real estate markets. These include the median price, the median price per-square-foot, and the Case-Shiller indices.

Markets for stocks, bonds and other securities are the most widely reported and measured financial markets. It is relatively easy to measure activity in these markets because all sales are recorded at a few central exchanges and the "products" are uniform (one share of stock is equal to another). In contrast, real estate markets are much more difficult to evaluate. Real estate transactions are recorded into the public record in thousands of locations across the country. Keeping an organized database of these records is such a daunting task that the title insurance industry has taken this responsibility as part of its business model, and many people are devoted to the arduous task of obtaining and organizing these records on a daily basis. Real estate does not have the uniformity of stocks or other financial instruments. Each property has unique qualities that differentiate it from all other properties making like-kind comparisons very difficult. Geographical location is a major influence on the value of real estate. Even if two properties could be found with identical physical characteristics, the values of these properties could vary considerably based on where they are located. Ideally, a market measure would record the changes in sales prices of identical assets or in the case of an index, a group of similar assets. The unique nature of real estate assets makes it difficult to use standard measures of reporting utilized in other financial markets.

Due to the problems of asset uniformity and variability based on location, real estate markets are typically measured using some form of median pricing over a specified geographic area. The median is a statistical measure of central tendency where half the data points are above and half the data points are below. For instance, in a list of 5 numbers sorted by size ($100,000, $200,000, $300,000, $500,000, $900,000,) the third number in the list ($300,000) would be the median because it has two numbers that are larger and two numbers that are smaller. The median ($300,000) is used rather than an average ($400,000) because a few very expensive properties can increase the average significantly, and the resulting number does not represent the bulk of the price activity in the market.

One of the problems with a median as a measure of house prices is a lag between when a top or a bottom actually occurs and when this top or bottom is reflected in the index. During the beginning of a market decline, the lower end of the market has a more dramatic drop in volume than the top of the market. This causes the median to stay at artificially high levels not reflective of pricing of individual properties in the market. In other words, for a time things look better than they are. At the beginning of a market rally, transaction volume picks up at the bottom of the market at first restarting the chain of move ups. During this time, the prices of individual properties can be moving higher, but since the heavy transaction volume is at the low end, the median will actually move lower.

The median is a good measure of general price activity in the market, but is does have a significant weakness: it does not indicate the value buyers are obtaining in the market. The houses or structures built on the land compose the most significant portion of real estate value in most markets. These structures deteriorate over time and require routine maintenance that is often deferred. During times of prosperity, many people renovate homes to add value and improve their living conditions. The impact of deterioration and renovation of individual properties is not reflected in the median resale value. Also, at the time of sale, there are often buyer incentives which inflate the recorded sales price relative to the actual cost to the buyer. These buyer incentives also distort the median sales price as a measure of value.

Many data reporting services measure, record, and report the average sales cost on a per-square-foot basis to address the problem of evaluating what buyers are getting for their money. For instance, in a declining market if people start buying much larger homes at the limit of affordability, the generic median sales price would remain unchanged, but since buyers are getting much larger homes for the same money, the average cost per-square-foot would decline accordingly. This makes the average cost per-square-foot a superior measure for capturing qualitative changes in house prices; however, this method of measurement does not capture the relative quality of the square footage purchased, only the price paid for it. High quality finishes may justify a higher price per square foot. There is no way to objectively evaluate the impact finish quality has on home prices. The main problems with using the average cost per-square-foot to measure price is that it does not provide a number comparable to sales prices since it has been divided by square feet, and it is not widely measured and reported.

To address some of the weaknesses of the generic median sales price as a measure of market value, Karl Case and Robert Shiller developed the Case-Shiller indices for measuring market trends. This index measures the change in price of repeat sales. It solves the dilemma of pricing like-kind properties, almost. Although these indices capture the price movements of individual properties far better than the generic median sales price, it does not take into account value added through renovation and improvement. To address this issue, the index gives less weight to extreme price changes assuming the outlier is a significant renovation. However, if there is a market-wide renovation of properties, as was the case in many markets during the Great Housing Bubble; this will cause a distortion in the index. The other weaknesses of the Case Shiller indices concern how and where it is reported. Since it is an index of relative price change rather than a direct measure of price, the index is reported as an arbitrary number based on a baseline date; therefore, the numbers are not useful for evaluating current pricing. The index is also confined to 20 large metropolitan areas around the United States. The large geographical coverage areas are required to obtain enough repeat sales to construct a smooth index. The broad yet limited geographical coverage fails to capture price changes in smaller markets. Also, since the Case-Shiller index is a measure of changes in prices of sales of the same home, it does not include any newly constructed homes. No measure is perfect, but the Case-Shiller index is the best at measuring historic movements in pricing because its methodology is focused on repeat sales of the same property.

The Great Housing Bubble was an asset bubble of unprecedented proportions. Between 2000 and 2006 Home prices increased 45% nationally, and in California home prices increased 135%. Had this amazing price increased coincided with a period of high inflation, it may not have been indicative of a price bubble, merely the general increase in prices of all goods and services; however, inflation was low during this period. The inflation adjusted price increases nationwide were 23% and in California it was 100%. There was no great improvement in the quality of houses justifying the higher prices. Although some homeowners made cosmetic improvements, the vast majority of homes were unchanged during this period, and many deteriorated with age. Resale homes did not undergo any form of manufacturing process where value was added to the final product. There was little real wealth created during the bubble, just a temporary exaggeration of value.

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