FORECASTING HOUSING PRICE INDEX DATA BY CLASSICAL DECOMPOSITION AND ARIMA METHOD

Abstract

Author(s): Harun SARAÇ, Tunahan HACIİMAMOĞLU

Since the late 1990s, the rapidly developing housing sector worldwide and countries’ economic growth targeting by this sector shifted the whole interest to this area. Turkey is also one of those countries with its housing sector activities both domestic and abroad. Hence, with the effects of the 2008 crisis, the housing price index, which has started to increase again, has become the subject of the most recent follow-up and interpretation in our country. In response to a very high level housing price index, the fact that the supply has reached a certain degree of saturation and that the demand side has not met this level has led to comments that the “real estate bubble will burst” in the near future. In this study, forecasting values for the period up to August 2018 are presented by using the two methods of classical decomposition method and ARIMA model that are used for forecasting in the time series. Monthly housing price index data for the period of 2010:01 – 2017:12 is employed and the results obtained from two different models are compared, as a result, analyzes are made for the housing sector depending on the forecasting values of housing price index. According to the results obtained, both methods clearly shows that housing price index is on a declining trend.

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