Measures of investment performance in real estate investment analysis : current practice and predictive utility
Creators: name: Arthur, David Douglas
Publisher: name: University of British Columbia
Year: 2010

description: Real estate offers substantial returns to astute investors but the real estate investment decision is not generally well understood and as a consequence, this ignorance often causes inadequately prepared investors to venture into poorly conceived and subsequently financially disastrous projects. One of the most important considerations in the analysis of real estate investments is the measure of investment performance or return. Over the years, many different measures have been used to indicate the relative profitability of real estate investments with the interesting dilemma that different measures produced different relative rankings of investment desirability and different absolute indicators of investment return. In the past, real estate analysts have emphasized "traditional" or "first generation" measures of investment return which are mathematically unsophisticated, contain few financial variables and give no explicit consideration to the time value of money. Analysts in the fields of investments and corporation finance widely use the more sophisticated discounted cash flow or "second generation" measures of analysis. Academic researchers in real estate support the theoretical superiority of discounted cash flow measures and claim that their use is widespread among the real estate community. The purpose of this study is twofold: (1) to develop an understanding of the current practice regarding real estate investment analysis with particular emphasis on the measures of return used and the degree of sophistication in investment analysis according to the size and type of investor; and (2) to test the predictive utility of the various measures of return. The following hypotheses are to be tested: 1. Real estate investors remain relatively unsophisticated in their approach to investment analysis. 2. 2. The degree of sophistication in investment analysis is positively related to the size and type of investor. 3. 3. Failure to use available measures of investment return is due to a lack of understanding on the part of the neglecting investors and difficulties arising from the estimation of the necessary input data. 4. 4. The ability of the real estate community to make more accurate and hence, more profitable real estate decisions is directly related to the use of more sophisticated measures of return. 5. A questionnaire survey, the first in Canada, was developed and administered to the following samples: (1) 300 real estate equity investors and (2) 150 ICI real estate brokers. The findings strongly suggest that real estate investors remain unsophisticated in their approach to investment analysis relative to other business fields. The real estate community continues to rely on first generation or traditional measures of return or performance to evaluate real estate investment opportunities. The most popular before-tax measures of return employed by those surveyed were Return on Investment (net operation income/purchase price) and the Equity Dividend Rate (net operating income - debt service/equity). For those respondents employing an after-tax measure, the most popular were After-tax Cash Flow (first year)/Equity and the Internal Rate of Return. It was shown that many of the respondents lacked the knowledge and understanding required of the more sophisticated measures of performance common to other business fields. They appeared to select a particular measure and then fail to adhere to the specific methodology of the chosen measure. Sophistication in real estate investment analysis was shown to be a function of the type of company and portfolio size since large public real estate corporations employed more sophisticated methods and techniques with a greater frequency relative to other investors. An empirical test was developed to examine the predictive utility of the various measure of investment return identified in theory (Chapter 2) and in practice (Chapter 3). The approach taken was to compare the ex ante returns from a sample of 15 apartment properties over the period 1970 to 1977 with the ex post returns over the same period. Thus, it was possible to measure the deviations between the predicted and actual returns each with a corresponding investment ranking as a test of the accuracy and reliability of prediction using each measure of return. The findings suggest that first generation measures of return will predict investment returns and relative investment rankings as closely correlated to that which actually occurred as will the more sophisticated second generation or discounted cash flow (DCF) measures of return. This result can be traced to the implicit requirements of the methodologies of first generation measures necessitating only one year forecasts of input parameters. The failure of the DCF models to provide clearly superior predictions of investment performance was largely due to the inaccurate forecasts of key input parameters, particularly sales price at the end of the holding period. The empirical test revealed that different measures of return produced different relative rankings of investment desirability and different absolute indicators of investment return. The results do not allow any specific measure or group of measures (first generation or DCF) to be hailed as a more accurate and reliable predictor of investment return in real estate. Indeed, the poor predictive utility of the various measures raise a question as to the reliability of prediction into the future for real estate investment analysis in general. Thus, it is clear that the results of the sample test do not lend support to the hypothesis that the ability of the real estate community to make more accurate and reliable, and hence more profitable, real estate decisions is directly related to the use of the more sophisticated discounted cash flow measures of return.