Growth of housing prices in Kenya and its dynamic relationship with selected macroeconomic variables
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Date
2017
Authors
Njaramba, Stephen Githae
Journal Title
Journal ISSN
Volume Title
Publisher
Kenyatta University
Abstract
In Kenya housing prices are considered high and have still continued to rise. This has
made housing affordability and access a preserve of the top income earners.
Consequently, large population live in houses with reduced access to clean water,
sanitation, unreliable and unhealthy energy sources, increased exposure to diseases and
low levels of financial security. Arable land is also being converted to residential
centers which is constraining on public goods provision and agricultural output. The
government of Kenya has struggled to make housing affordable and also to encourage
housing access and home ownership. This effort has not been quite successful since the
housing prices continue to rise and also declining access to descent housing. The
variables the housing prices respond towards and could inform the policies to manage
the housing prices are not clear. Housing prices behavior have also been known to
influence business cycle dynamics by affecting aggregate expenditure and also the
performance of the financial system through their effect on the profitability and
stability. The purpose of this study was therefore to analyze the variables the housing
prices respond to both in short-run and in long-run. The study also examined the
dynamic relationship between housing prices and selected macroeconomic variables. In
doing this, the study used time series data for the period 1960 to 2015 and adopted an
ARDL and VAR models. The ARDL and VAR models were selected since the housing
prices behaves differently from other goods’ prices, and as such, previous values of
housing prices and other variables used were required to explain current behaviors. The
ARDL model is best suited for small sample size and has a capacity to estimate short run
and long-run dynamics. The ARDL model also has no burden of establishing the
order of integration and it distinguishes dependent and explanatory variables. With
ARDL, it is possible to use differing optimal number of lags among the variables. For
VAR, the study used Toda and Yamamoto (1995) methodology. This is a modified
version of granger causality test based on augmented VAR modeling. The study
findings show that the sources of housing prices growth include household consumption
expenditure, construction cost and property taxes both in the short-run and long-run.
Private capital inflows and households’ indebtedness have a positive transitory effect to
the housing prices. Against the popular view, supply of housing have no effect on
housing prices. For the dynamic relationship between housing prices and the selected
macroeconomic variables, the results indicate that the housing prices dynamically relate
with the selected macroeconomic variables. The study therefore concludes that housing
prices have a positive contemporaneous impact on the selected macroeconomic
variables indicating the existence of mutually reinforcing cycles between the housing
prices and the selected macroeconomic variables. Therefore, there is need to observe the
housing prices to avoid the cost that could result in case of instability in the housing
market.
Description
A PhD thesis submitted to the school of economics in partial fulfillment of the requirements for the award of the degree of doctor of philosophy in economics of Kenyatta University, November 2017