International Journal of Data Science and Analysis
Volume 4, Issue 5, October 2018, Pages: 89-97
Received: Oct. 11, 2018;
Accepted: Oct. 23, 2018;
Published: Nov. 21, 2018
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Paul Kiarie Njoroge, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Jane Akinyi Aduda, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Carol Mugo, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
In the Kenyan real estate industry, laws of economics seem to be violated. The demand for houses has been increasing tremendously despite the oversupply. This violates the laws of economics indicating a possibility of a real estate bubble. The study aimed at estimating short term and long term real estate price dynamics in Kenya using co-integration tests. Secondly, the study aimed at identifying the presence of a Kenyan real estate bubble using the forward-recursive Generalized Augmented Dickey-Fuller test (GSADF) and finally measured the size of the bubble at a given time relative to other key macroeconomic variables. The study utilized quarterly data on house prices and rental prices in Kenya and macroeconomic determinants from the year 2004 to 2017 September. Stationarity test revealed that the variables were stationary in their first difference I (1). Cointegration test revealed that there was no long term and short term house price dynamics between house prices and the macroeconomic variables at a lag of 4 determined through AIC, SIC and HQ criterion. Again a Granger causality test was performed and the results revealed that the macroeconomic variables did not Granger-cause house prices and vice versa. To investigate the presence of a Kenyan real estate bubble, cointegration test, and GSADF were performed and the results indicated the existence of a bubble in the Kenyan real estate. Two time period bubbles were identified from September 2009 to January 2010 and the other from April 2011 to September 2011. Finally, the bubble sizes were measured and were found to be 15% each in the two periods.
Paul Kiarie Njoroge,
Jane Akinyi Aduda,
Investigating the Existence of a Bubble in the Kenyan Real Estate Market, International Journal of Data Science and Analysis.
Vol. 4, No. 5,
2018, pp. 89-97.
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