Measuring Local Individual Housing Returns from a Large Transaction Database

The measure of housing returns is important for at least two major economic trade-offs : (i) the choice of housing tenure for households (buy/rent), (ii) the optimal portfolio composition for an investor and, in particular, the respective shares of financial and real estate assets. A comprehensive measure of the physical real estate returns should include proper estimates of both the rental returns (the rent-to-price ratio) and capital gains (price growth rates). Ideally, they should be measured at the individual level for at least two reasons: (i) to provide a valuable estimation of the amount of idiosyncratic risk supported by landlords, (ii) due to the non linear nature of the above formulae, aggregate estimates of the volatility of rents or transaction prices could lead to biased estimates of the average real estate return. This aggregation bias could be responsible for substantial differentials in empirical housing returns estimates in the literature. Finally, a definition of housing returns should encompass the main sources of risks: rent risk or price risk as usual, but also vacancy risk that is regularly omitted though negatively affecting expected rental rates. Using two very large French databases, we produce a local measure of rental returns, capital gains and associated risks over the last housing boom and burst that affected the French real estate market on a smaller scale than what has been observed in the United States of America or in the United Kingdom. We use the administrative registration by notaries of all the housing transactions between 1996 and 2007 (about 1 600 000 transactions) in the large Paris area and a panel of about 40 000 rented flats or houses surveyed on a yearly basis in the same area. On the one hand, we estimate local hedonic price equations with the first database. It is combined with a repeat-sale approach for a subset of about 7% of the sample in order to assess the average individual time correlation of the unexplained part of the hedonic equations. On the other hand, we estimate hedonic rent equations as well as occupation/vacancy spell equations with the second data base. These models allow us to impute local rent and occupation periods and measure real estate returns (rent and capital). We provide estimates of local means and variances of housing returns on Paris and its first suburbs for the 1996-2004 period. Our results also suggest that housing returns measure local market tightness and may serve as an indicator of the evolution of prices