The effect of macro economic variables on the development of housing in Kenya

Abstract

Over the past few years, the world real estate industry has been undergoing drastic reforms due to the liberalization of financial markets, the drastic fall of interest rates, the obsolescence of the existing stock of housing, and a change in consumer norms on housing uses. According to Deutsche Bank Research (2008) the major macro indicators for the housing development are Gross Domestic Product (GDP) growth trend, GDP per capita, population, median age, population growth, financial market development, legal system and average inflation. Research from Liow et al. (2006) analyze macroeconomics influences on worldwide property market and finds that GDP, inflation and interest rate are the most relevant macroeconomic indicators to examine. The mortgage interest rate is a very important variable that influences the decisions of individuals on whether or not to buy a house in developing countries Kenya included. When the mortgage rate increases, people are prevented from buying houses; therefore, the demand for housing decreases. This study sought to answer the following question; what are the effects of macroeconomic variables on the development of housing in Kenya over the period 2004–2013? The research design of this research was a descriptive survey research. The study used secondary data collected from the Central Bank of Kenya for interest rates and inflation rate and Kenya National Bureau of Statistics for aggregate number of house units built annually and Gross Domestic Product. The time period that this study covered was 10 years, (2004-2013). The data obtained was analyzed using multiple linear regression technique. From the regression model, the study found out that there were macroeconomic variables influencing the development of housing in Kenya, which are interest rate, inflation rate and Gross Domestic Product growth (GDP). The two variables in the study (inflation rates (- 0.105) and interest rates (-0.264)) were negatively correlated with the number of house units built while the third variable GDP (0.417) was positively correlated with the number of house units built. The study found out that the intercept was 0.481 for all years. The three independent variables that were studied, explain only 94.9% of the number of house units built as represented by the adjusted R2. This therefore means the three variables contribute to 94.9% of the number of house units built, while other factors not studied in this research contributes 5.1% of the number of house units built. The study recommends that a similar study should also be carried out on the effect of micro-economic variables on the development of housing in Kenya