We use data on new apartment offerings in the municipality of Sao Paulo, Brazil to illustrate our main claim that the hedonic direct method using time dummies as well as the simple average method include cyclical behavior of observables and nonobservables in a house price index that may overestimate or underestimate the actual change in house prices, well beyond the composition effects. We propose the use of alternative characteristics hedonic functions to compute alternative Laspeyres house price indexes that differentiate the sources of observable shocks in the index. Our decomposition allows for the inclusion of level and cyclical behavior of sets of aggregate variables into the index. The housing market has become an important part of the modern economy and more recently, the sophisticated securitization of the real estate sector in the US has brought about a financial crisis of large proportion. Thus, it is important for modern economies at the local, state and national levels to measure the evolution of prices in the real estate sector. There has not been much research on this specific issue. In the U.S., Del Negro and Ostrok (2007) have examined the role of monetary policy in explaining house price movements. Their main finding is that the effects of aggregate policy shocks on house prices were small, relative to the magnitude of house price fluctuations in the early 2000s. However, more recently Aragon et al (2010) have criticized certain house price indexes in the U.S. claiming that they underestimate the potential downturn in house prices in recent years.1 In general, a house price index can be used to provide a signal to market participants on adjustments for rents, collagenized debts, other securities tied to the housing market, and risk assessment for mortgages and other instruments such as derivatives (MBS mortgage-backed securities). Hence, it is important that a house price index reflects the variation and cyclicality of the housing sector and does not incorporate other sources of real, nominal and other shocks that can potentially bias the index.