Abstract:
The financial crisis which hit United States (US) in 2007 brought interaction between
housing prices and household borrowing in the limelight of economic policy debate,
attracting attention of the policy makers in economic stability. Given close interaction
between housing prices and monetary policy, this study aimed at coming up with
solution on housing deficits by the utilizing the relationship between the two
variables. The problem of housing deficit is in terms of both quantity of housing,
especially in urban areas where the quantity of available housing unit is grossly
inadequate and the quality of housing particularly in the rural areas. The purpose of
the study was to study causal relationship between housing prices and monetary
policy in Kenya and South Africa. South Africa was used as comparison because
South Africa financial institution have well established structures which can be used
to transmit monetary policy into the economy as compared to Kenya which have
structural problems in the financial market, including inadequate financial
infrastructure and weak legal framework (Cheng, 2006). The main variables tested
under this study were housing prices, lending rates and domestic credit to private
sector based on the data collected from Hassconsultant ltd, IMF-IFS, and ABSA bank
for a period spanning between 2001 and 2016. The study employed the use of vector
Auto regression (VAR) model due to its robustness in forecasting. The collected data
was first subjected to unit root test at levels using Augmented Dickey Fuller, and was
found to be non-stationary and therefore had to be transformed to remove non
stationarity so as to avoid spurious regression and misinterpretation of data. Vector
auto regression was used to establish the nature and direction of relationship between
the variables. It was established that house prices have statistical significance and
positive effect on lending rates while lending rates have statistical significance and a
positive effect on house prices. House prices have statistical significance and positive
effect on domestic credit to private sector while domestic credit to private sector have
no statistical significance on the housing prices. The study findings on comparison
between Kenya and South Africa indicate that results of Kenya or South Africa
cannot be used to predict or determine the movement of house prices in either
countries. the results show that monetary policy have causal relationship with house
prices and therefore based on this, it is recommended that policy makers pay close
attention to house prices while designing policies on economic stability. Specifically,
on relationship between lending rates and house prices, policy makers should reduce
the lending rates so as to reduce house prices. While on domestic credit and house
prices policy makers should avail more credit so as to allow individuals to purchase
more decent house. Policy makers should utilize country specific data in designing
policies because countries have different characteristics which may not be
generalized