Effects of Infrastructure Development, Human Capital Development, and Foreign Direct Investment on Housing in Kenya

Abstract

To establish a vibrant real estate sector and facilitate the construction of affordable, modern, and efficient housing units to all Kenyans, the government should establish measures and policies that impact investors positively. Primary, this is achievable through partnership with local and foreign investors to reduce the housing cost. The initial medium-term idea (MTI, 2009-2012) of vision 2030 in Kenya was to grant 250,000 housing items per year to all income levels by the year 2012. However, the goal was not achieved since only 50,000 out of 250,000 housing units were constructed. In Kenya, housing shortages will be more profound as a result of increased population growth rates and urbanization which is not accompanied by improvements in the housing sector. Affordable housing is one of Kenya’s Big 4 agendas aimed at transforming the economy of the country into a middle-income one. Therefore, the focus of this study is to suggest policies to Kenyan government and investors to solve problems of absence of sufficient housing units through evaluation of Infrastructural Development (ID), Human Capital Development (HCD), and Foreign Direct Investment (FDI) in relation to Housing in Kenya. The research will use quarterly non-stationary data for the period 2009-2020 to approximate a simple regression of housing growth rates and the chosen macroeconomic factors. This study will employ both causal and analytical design using auxiliary data from the CBK, KNBS, KIPPRA, KRA, and other Government records. Test of the unit root will be undertaken to determine stationarity of the data used using critical Dickey-Fuller where (P<0.05), Cointegration test is also performed to identify any existence of a relationship between the predictor variables and the predicted variable, in the long run, using Engle-Granger test(P<0.05). Multicollinearity is performed using variance inflation factor (VIF<10) to identify any correlation between the predictor variables. A test of Heteroscedasticity is done to establish whether the residual term is equally distributed using the Breusch-Pagan-Godfrey test and the Durbin Watson test for serial correlation coefficient (p<2.5). Using documentary research, the time series data will be collected and analyzed using STATA. The findings are expected to inform the government on the initiatives, measure, and policy options to adopt in order to reduce the housing deficit in Kenya.