INFLUENCE OF SELECTED ECONOMIC FACTORS ON VOLATILITY OF HOUSING PRICES IN NAKURU AND KIAMBU COUNTIES, KENYA

Abstract

Kenya's middle-class population is expanding, which has put more strain on the housing market by driving up demand for houses. Housing unit production is scheduled based on anticipated demand. The increase in population and consumer power fuels demand. The level of pricing affects the capacity to purchase. The study's goal was to evaluate how selected economic factors influenced Nakuru and Kiambu housing price instability. The aim of the research was to determine the impact of housing demand on volatility of housing prices, economic growth on volatility of housing prices, the influence of mortgage rate on volatility of housing prices and influence of demographic characteristics on volatility of housing prices in Nakuru and Kiambu Counties. The ideal competitive theory of the housing market, the search theory and the housing market, and the life-cycle model of household consumption served as the study's pillars. The research design used in the study was descriptive. 600 sales managers from 26 members of the Kenya Property Developers Association who had been in existence for more than 10 years and had developed Nakuru and Kiambu County made up the study's population. Nassiuma's technique and simple random sampling selected 164 sales managers for the study. Semi-structured questionnaires were used to collect primary data. 17 sales managers from Kenya property developer association members were surveyed in Machakos County, Kenya. The instrument was reliable because Cronbach's alpha values for all research variables were between 0.7 and 0.9. Descriptive and inferential statistics were analyzed and presented in tables, percentages, frequencies and central tendencies. The findings of the study indicated that demand of houses had a positive statistically significant effect on housing price volatility (β1=0.596, p=0.013), economic growth had positive statically significant influence on housing price volatility (β2=0.233, p=0.006), mortgage rate had a positive statistically significant effect on housing price volatility (β3 = -0.446, p=0.044) and finally, demographic characteristics had a positive statistically significant effect on volatility of housing prices in Nakuru and Kiambu counties (β4 = 0.456, p= 0.13). The study recommended that the government should effectively regulate the mortgage market by setting lending standards and limiting the availability of risky loans, which can help to reduce the likelihood of a housing price bubble.