| dc.description.abstract | This study provides estimates of the demand of housing in Kenya based on annual time series data for the period 1980-2009. As in other studies of housing demand, the loglinear demand equation was estimated to model the effect of house prices, income per capita, average lending interest rate, prices of other related goods and inflation on number of, J.lOusing units purchased. Time series techniques were applied to test for unit roots, cointegration and Granger causality. Tests of unit roots are critical to avoid spurious results in the estimation of the model. An error-correction model (ECM) was also estimated to capture short-run dynamics toward the long-run equilibrium.
The results show that income per capita is the most significant variable in explaining the demand for housing in Kenya both in the long-run and in the short-run. While the longrun income elasticity is greater than unity, the short-run income elasticity is less than unity. The results also show that the adjustment parameter is about 0.43 indicating significant but gradual adjustment toward the long-run equilibrium. The average lending interest rate which was used as a proxy for prices of housing does not have significant impact on demand for housing. Granger causality test indicate unidirectional causality from income per capita to number of housing units purchased. This implies that increase in income per capita directly affects housing demand. Consequently, to increase the uptake of modern housing units, the Government of Kenya should endeavor to overcome constraints on increasing income per capita. | en_US |
