Time Series Analysis Model for Estimating Housing Unit Price

Paul Boye, Daniel Mireku-Gyimah, Hassan Sadiq

Abstract


This paper uses observed housing unit prices over fifteen (15) years to develop Time Series Analysis Model (TSAM) for determining Housing Unit Price (HUP) for one-bedroom and two-bedroom housing units. In the modeling, the observed prices were converted to real monetary values and AutoCorrelation Functions (ACF) and Partial AutoCorrelation Function (PACF) plots were used to estimate the model coefficients for one-bedroom and two-bedroom housing units respectively. The resultant developed models for one-bedroom and two-bedroom housing units are Autoregressive Integrated Moving Average, ARIMA (2, 1, 1) and ARIMA (3, 1, 1) respectively. The specific model for one-bedroom housing unit is HÛPt1-Bed = 440.531- 0.181 yt-1 + 0.022 yt-2 + 0.993 et-1 and that for two-bedroom hosing unit is HÛPt2-Bed = 278.474 - 0.166 yt-1 + 0.035 yt-2 - 0.062 yt-3 + 0.994 et-1. The TSAM was validated by using it to estimate the known HUP in the 15.5th year. From the results, the percentage absolute deviations of the estimated HUP from the known HUP for one-bedroom and two-bedroom housing units are all equal to 0.00% respectively, meaning that both models are good. The approach presented in this paper is a valuable contribution to the body of knowledge in modeling.


Keywords


Time Series Analysis, Housing Unit Price, Nominal and Real Monetary Housing Unit Prices.

Full Text:

PDF

References


Anon. (2007a), “The Housing Industry in Ghana: Prospects and Challenges”, Research Department, Bank of Ghana, pp. 1 - 6.

Anon. (2007b), The Housing Market in Ghana, Research Department, Bank of Ghana, pp.1- 46.

Chaphalkar, N. B. and Dhatunde, M. (2015), “Real Property Valuation Using Sales Comparison

Method and Multiple Regression Analysis”, International Journal of Modern Trends in

Engineering and Research, Vol. 2, No. 8, pp. 304 - 315.

Enders, W. (2015), Applied Econometric Time Series, 4th edition, Hoboken, NJ: Wiley, pp. 7 - 70.

Gebhard, K., Jürgen, W. and Uwe, H. (2013),

Introduction to Modern Time Series Analysis, 2nd edition, Springer Heidelberg New York Dordrecht London, pp. 10 - 89.

Isakson, H. R. (2002), “The Linear Algebra of the Sales Comparison Approach”, Journal of Real Estate Research, Vol. 24, No. 2, pp. 117 - 128.

Jadevicius, A. and Huston, S. (2015), “ARIMA Modeling of Lithuanian House Price Index”, International Journal of Housing Markets and Analysis, Vol. 8, No. 1, pp. 135 – 147.

Montgomery, D. C., Jennings, C. L. and Kulahci, M. (2008), Introduction to Time Series

Analysis and Forecasting, Hoboken, N.J: Wiley-Interscience (Wiley Series in Probability and Statistics), pp. 73 - 275.

Puri, A. K. and Lierop, J. V. (1988), “Forecasting Housing Starts”, International Journal of Forecasting, Volume 4, No. 1, pp. 125 – 134.

Stevenson, S. (2007), “A Comparison of the Fotecasting Ability of ARIMA Models”, Journal of Property Investment and Finance, Vol. 25, No. 3, pp. 223 – 240.


Refbacks

  • There are currently no refbacks.