Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/2763
Title: Causal relationship between monetary Policy and house prices: A comparative analysis of Kenya and South Africa
Authors: Masai, Wilfred Cherokony
Keywords: Monetary
Policy
Issue Date: Aug-2019
Publisher: Moi University
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
URI: http://ir.mu.ac.ke:8080/jspui/handle/123456789/2763
Appears in Collections:School of Business and Economics

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