The Real Estate Cycle and its Double Positive Impact on Property Values
by Petros S. Sivitanides, Ph.D.
Real estate investors can use the real estate cycle, an important attribute of real estate market behavior, to time their investments and maximize their returns and profits.
As it will be seen in the discussion that follows, timing the movements of rents and prices in real estate markets may be less difficult and, perhaps, less risky compared to stock and bond markets. Due to the rigidities regulating the behavior of the real estate market, and the (by nature) slow response of property supply to favorable and unfavorable economic shocks, property rents and values move mostly in a slow and smooth fashion and in this sense are more predictable, as opposed to the irregular and unpredictable movements of stocks and bond prices. Forecasts of real estate market movements by property type and market can be obtained by various vendors.
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It has been shown empirically (Wheaton, 1987) 1 that the office space market is characterized by cyclical movements with long periodicity due to a number of idiosyncrasies. These idiosyncrasies include the sluggishness of the supply response (that is, the construction of new buildings) to changes in demand and prices due to the long time that it takes to plan and build a multi-story office building, as well as the slow adjustments of market rents/prices and demand, due to long-term rental contracts, which prevent tenants from changing their consumption of space when market conditions change. Within this context, one could argue that movements in real estate markets and the real estate cycle are predictable to a significant extent. As the figure below shows, the periodicity of a cycle is the time it takes to move from peak to peak (see figure below), while amplitude is the difference between the price/rent level at the peak of the cycle and the price/rent level at the trough of the cycle. Having in mind how market capitalization rates move (see Chapter 1) 2, and looking at the real estate cycle from the perspective of value increases, it appears that property values and sales prices get a double boost as the market moves from trough to peak. As the market improves, occupancy, rental income, and property income increase (see Figure 5). Increasing property income, in turn, exerts upward pressures on property values. Improved occupancy and rising rents reduce risk in the eyes of investors and reinforce expectations for continuing market improvements. These perceptions exert downward pressures on market capitalization rates, which start to decrease, pushing values further up. Thus, when the market reaches a peak, property income climbs to its highest level, while capitalization rates drop to their lowest level. Within this context, property values get a double boost when the market is strong, and a double hit when the market is soft (see Figures below).
1Wheaton, W. 1987. “The Cyclic Behavior of the National Office Market.” American Real Estate and Urban Economics Association Journal, Vol. 15, pp: 289-299
DOES THE REAL ESTATE CYCLE EXIST?
Based on data of historical real estate market behavior, the real estate cycle is more prominent in the commercial real estate market (and especially the office market) rather than the residential markets. This cycle affects all the players in the real estate market, that is, owners, tenants, lending institutions, investors, buyers and sellers. The cyclical movements in the real estate market are manifested in its basic indicators, that is, occupancy rates, rents, cap rates and values. It has to be emphasized that the real estate cycle has different characteristics depending on property type. First of all, analysis of the historical real estate value patterns (based on appraisals) for the four major property types (office, industrial, retail and apartments), using data provided by the National Council of Real Estate Fiduciaries (NCREIF) by Sivitanides (2007) has clearly revealed cyclical property value movements in the case of all types of commercial real estate, that is, office, retail and industrial, but not clearly in the case of apartments. These cyclical movements though were more profound and intense in the case of office property and less intense in the case of retail and industrial. Differences in the cycle characterizing each property type are due to differences in the economic and demographic factors that drive demand for each property type. For example, demand for office space is driven primarily by employment in services and financial sector, while demand for warehouse/distribution space is driven by employment in wholesale trade transportation and manufacturing. Demand for retail space by retailers is driven primarily by population and income growth. Real estate cycle differences across property types are also due to differences in supply. For example, the supply of industrial is less capital intensive, involving smaller and simpler structures, thus allowing industrial and warehouse projects to be completed faster compared to office buildings. This reduces the construction lag and allows supply to respond faster to changes in demand, thus preventing the market from accumulating a significant amount of excess supply. That is why the industrial vacancy rate has rarely exceeded the 12% mark historically, while the office vacancy rate at its cyclical peak has climbed over the 20% mark. It has to be also clarified that the real estate cycle varies across the different geographies. For example, the national real estate cycle, describing the average behavior of the national real estate market, is different than the local real estate cycle that takes place in each metropolitan/city real estate. The metropolitan cycle may differ from the national real estate cycle in terms of timing, duration, and amplitude (movement from trough to peak) depending on the idiosyncratic demand-supply conditions that prevail in the local market and the dependence of the local economy to the national economy. For example, the local real estate market may enter the cycle later and last shorter period, because of tight local supply conditions. Notice that the real estate cycle differs across metropolitan markets and cities, because of differences in their economic structure and dynamics, as well as differences in local demand-supply dynamics at the time that the national economic shocks trigger the beginning of the cycle. Understanding the real estate cycle by property type and location is very important for making profitable real estate investment decisions. Sophisticated real estate investors and professionals in the real estate industry are aware of the overbuilding of the 1980s and its subsequent negative effects on the real estate industry. With supply of real estate exceeding demand, vacancy rates rose and rent growth decelerated and turned negative. The effect of oversupply on rents and values in the commercial real estate market was not really felt until 1991, when the national recession resulted in a sharp decrease in demand for real estate, and induced sharp decreases in commercial space rents and values. With institutional real estate investors and professionals being well aware of the cyclical nature of the real estate market, the need for modeling and forecasting the real estate cycle is very well understood and demanded in the real estate industry today. Competent real estate cycle forecasting can provide to real estate investors several valuable clues, such as whether property income and values will be increasing or decreasing in the years ahead, which markets and sub-markets are more likely to register the strongest rent and value increases and which markets are the most risky in the sense that they are more likely to become oversupplied and register property income and value losses. Real estate cycle forecasting is important in analyzing performance and estimating expected return measures for a property investment such as the internal rate or return (IRR), or modified rate of return (MIRR). The estimation of such measure requires forecasts of the cash flow of the property and especially rents and values. Reliable real estate cycle forecasting can help generate more accurate forecasts of such measures. The real estate information industry has been improving since the 1980’s, when institutional investors started pouring capital in the real estate market and has reached a point where the nation’s 50 markets and their sub-markets are well documented across all major property types. This has allowed the development of sophisticated forecasting models by market and property type by several vendors that provide econometric forecasts that capture the most likely cyclical movements of the real estate market and can help investors understand at what stage of the real estate cycle a market is at the time they are contemplating entering the market.
MODELING THE REAL ESTATE CYCLE
Econometric modeling and forecasting of the real estate cycle requires the development of a system of statistical equations that describe the behavior of the real estate market. Ideally, in order to develop such forecasting equations, the analyst needs a long historical series of data that describe the movements of the basic drivers of the real estate market under consideration, that is, demand, supply, and prices. This data is used to estimate the statistical equations that describe the changes in these indicators in response to changes in the factors that drive their movements, as well as their interactions. Estimation of the demand equation can help us quantify, for example, how much demand for office space will increase in response to an increase in the area’s office employment; and how much demand for office space will decrease in response to an increase in rents. Estimation of the rent equation can help us quantify how much market rents will increase in response to a decrease in the market vacancy rate. Using these forecasting equations and forecasts of the economic indicators that drive, real estate demand and supply for each market and property type the analyst can develop forecasts of the local real estate cycle. This is possible for about 50-60 markets for which adequate historical data are available. Data availability varies by property type and market. Historical data available by vendors extend back 20 years or more for several large markets mostly for commercial property types, while apartment data may not go that far back.
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