Determinants of the South African residential real estate grown cycle

[摘要] ENGLISH ABSTRACT: As from the beginning of 2000 house prices have seen four consecutiveyears of sustained price increases for the first time since 1984. These priceincreases enhanced activity in and redirected investment focus to the residentialproperty market. It appears that the boom in house prices was preceded andsupported by a number of economic variables, such as growth in disposableincome, greater affordability, low inflation and low interest rates.Based on the above, the primary objective of this study is to identifythrough regression analysis the leading indicators of the house price growthcycle. The results indicate that one-quarter lagged growth in house prices, onequarterlagged interest rate growth, one-quarter lagged growth in the rand/dollarexchange rate and growth in the one-quarter lagged construction cost could beused to predict the growth in house prices.The analysis is extended to include a regression analysis of the upswingand downswing phases of the house price growth cycle, which is intended toidentify potential leading indicators of an upswing and downswing in theproperty cycle.The results for the upswing phase indicate that one-quarter laggedgrowth in house prices, one-quarter lagged interest rates, one-quarter laggedgrowth in household consumption, one-quarter lagged growth in JSE ALSI andone-quarter lagged growth in the rand/dollar exchange rate may be used topredict the growth during the upswing phase of house prices. The results forthe downswing phase indicate that one-quarter lagged growth in house prices,one-quarter lagged growth in interest rates, one-quarter lagged growth inhousehold saving and one-quarter lagged growth in construction cost could beused to predict the growth of house prices during the downswing phase. No indicator series could consistently predict the direction of growth inhouse prices. To test which economic variables appear most frequently asindicators of growth in house prices a second regression analysis is performedfor the cycle and the upswing and the downswing phases using a longerpredictive period. The initial regression analysis is based on data from 1974 to2000 and the second regression analysis is performed on data from 197 4 to1995 and tested on data from 1996 to 2004.A comparison between the relevant regression analyses performed onthe complete house price growth cycle found that only one-quarter laggedgrowth in house prices is a common variable for the prediction of growth in thecomplete house price cycle. The regression analysis performed on data from197 4 to 1995 for the upswing phase produced three models. The regressionshave four variables in common; one-quarter lagged growth in house prices,one-quarter lagged growth in building plans passed, one-quarter laggedhousehold savings and one-quarter lagged consumption.The regression is repeated on the downswing phase and a comparisonof the results of the regression analysis from 197 4 to 2000 and the regressionanalysis from 197 4 to 1995 showed that one-quarter lagged growth in houseprices, one-quarter lagged growth in interest rates and one-quarter laggedgrowth in construction costs consistently predicted changes in the growth ofhouse prices during the downswing phase. Only one-quarter lagged growth inhouse prices are consistently identified as a growth indicator for the completecycle, upswing phase and downswing phase.

[发布机构] Stellenbosch University