Determinants of Residential House Prices in Nairobi City County, Kenya

Abstract

House prices have been the main focal point of economic and social debate in recent times in many developing countries. House prices in Kenya have been rising in the past ten years and the latest findings have shown that the trend will continue into the foreseeable future. There are many factors affecting house prices, their influence however has to be established over time. The general objective of the study was to evaluate the determinants of house prices in Nairobi County, Kenya. The specific objectives examined the effect of; mortgage rate, exchange rate, interest rate, population, number of houses, inflation and GDP on house prices. The study adopted an explanatory research design in explaining the effect of mortgage rate, exchange rate, interest rate, population, number of houses, inflation and GDP on houses and covered the period 2004-2016. The target population consisted of 1,874,181 residential houses in Nairobi City County. Quarterly observations (2004Q1-2016Q4) of the House Price Index (HPI) from the Hass Property Consult Ltd and the quarterly observations of the independent variables from Kenya National Bureau of Statistics and Central Bank of Kenya was used. Vector Auto-regressive (VAR) model estimates were used to get variance decomposition and impulse response functions results. Variance decomposition results indicated that in the long run, exchange rate caused the largest randomness in house prices. Impulse response results indicated that mortgage rate, interest rate, inflation and GDP had a positive relationship with the house prices in the short run whereas exchange rate, population and new houses had a negative relationship in the short run. To determine the long-run relationship between the determinants and house prices, Vector Error Correction Model (VECM) estimates were used. Results confirmed the existence of a long-run equilibrium relationship among variables in the model. The size of the coefficient of the error correction term (β = - 0.397, p = 0.0122) suggested a relatively higher speed of adjustment from the short-run deviation to the long-run equilibrium. VECM coefficients specifically revealed that in the long-run, exchange rate (β= 0.174, p = 0.0428), population (β= 0.829, p = 0.0286), inflation (β= 0.039, p = 0.0015), mortgage rate (β= 0.658, p = 0.000), new houses (β = 0.367, p = 0.000 had a positive significant effect on house prices. Interest rate (β = - 0.444, p= 0.0025),) had a negative effect on house prices which was highly significant. Though having a negative relationship with house prices, the study failed to identify any long-run relationship between GDP (β= - 0.011, p = 0.8174) and house prices. The study concluded that exchange rate is the most important predictor of house price changes in Nairobi City County. The study recommends that Central Bank of Kenya should use expansionary monetary policies so as to induce development in the housing market thus enabling market participants. The government should also enhance remittance policy to target appropriate groups to grow the housing market. Consequently, the government should increase its budgetary allocation to housing so as to increase the supply of houses hence check the house prices. Further, there is need to check on urban population growth so as to match the number of houses available with the increase in population.