But, it is not that easy to forecast the real estate prices. Firstly, the forecast has to account for the transaction costs which are at least 6 percent of the value of the property. Secondly, it is hard to find historical data, because the available data is maintained on a monthly or quarterly basis, which is quite short a duration. This makes it difficult to conduct estimation based predictions or hypothesis based testing. Thirdly, the predictive regression is governed by factors like coastal proximity, geographical location, type of the property (apartment, condo etc.). These factors account for the heterogeneity of the asset, but they cannot be considered as predictors in the real sense of the word. This is mainly because they do not change over a period of time and cannot be considered as the source for time-series predictions.[ii] Due to these limitations of individual indices for real estate forecasting, most commonly aggregate indices are used as they are available over a longer span of time. Along with the aggregate indices, cross sectional data also proves to be useful.
According to some of the leading US economists, the real estate prices in US, during the years 2014 and 2015 would increase slowly but steadily, leading to a mild price appreciation of your houses.[iii] The question that would come up now is, “why is only mild appreciation in the real estate rates forecasted in spite of the recovery of the market from the economic crash?” The answer to this question takes many factors into consideration. The rise in incomes has led to a preference to buy a property than rent it. Also, younger people are likely to move out, from their parents or roommates. This has led to an increase in the demand. On the other hand, the construction pace is too light today. This is because of problems like labor shortages, construction costs rising faster than inflation, and difficulty to obtain construction loans.[iv] This prevents the supply from exceeding the demand. As long as the economy maintains its current state, the market situation is favorable for an increase in the real estate prices. But, the unfavorable mortgage lending environment is dampening this increasing effect of the prices. The mortgage interest rates are forecasted to increase even further in the future. These higher mortgage interest rates, limit ability of the people to buy property. This eventually reduces the demand. Thus the supply almost meets the demand. This would prevent a high increase, and lead to a mild increase in the real estate prices.
These are the factors that affect the forecasting of residential property. Now the question arises, can the same factors be used to forecast the prices of commercial property?