Monitoring the dynamic of residential prices, even though is not trivial, has relevant importance especially in turbulent periods. Recent financial crises, triggered in the US due to a plunge on house prices, have highlighted the importance of monitoring house price dynamics. In emerging economies, there is a lack of official house price indexes developed by public institutions. Moreover, in Latin America house prices data are only available for some countries, and even when available, time series are usually of short span, with coverage often limited to large metropolitan areas (Cubeddu et al, 2012). Notwithstanding, there are some studies developed by private consulting, whose purpose depends on their customers’ needs, and due to the high costs of information gathering, are usually biased to a particular sample of properties. Particularly, in Chile some studies displayed to estimate house prices were developed by Morandé (1992) using hedonic prices for the Ñuñoa district,3 between 1975 and 1989, Bergoeing et. al. (2002) who expand the prior mentioned work until 1998, which finally Desormeaux and Piguillem (2003) continued until 2003. Later, using two methodologies (repeat sales and hedonic prices), Parrado, Cox and Fuenzalida (2009) estimated the house price index between 2001 and 2007, based on information from the Property Register Office (Conservador de Bienes Raíces). Moreover, using hedonic models, both Figueroa and Lever (1992) and Sagner (2009) estimate what factors determine house prices for Santiago.

This document presents alternative and preliminary estimations of the Chilean Residential Property Price Index (RPPI) employing a novel dataset that comes from the Internal Revenue Service, and includes all recorded transactions made within years 2001 and 2011. This dataset, considering its national coverage, allows exploring behaviors of property prices within cities, in order to make a more comprehensive monitoring of the real estate market and establish connections with past events, due to the length of the data. These estimations include methodologies based on mix adjustment stratification, hedonic model and repeat sales.4,5 The results presented in this paper are still preliminary and do not constitute an official statistic of the Central Bank of Chile.