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Forecasting house prices in Italy

Simone Emiliozzi, Elisa Guglielminetti () and Michele Loberto

No 463, Questioni di Economia e Finanza (Occasional Papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: Forecasting house prices is a difficult task given the strong relationship between real estate markets, economic activity and financial stability, but it is an important one. This paper evaluates the out-of-sample forecasting performance of various models of house prices in a quasi-real time setting. Focusing on Italy, we consider two structural models (using simultaneous equations) and a Bayesian VAR and compute both conditional and unconditional forecasts. We find that the models perform better than a simple autoregressive benchmark; however, the relative forecast accuracy depends on the forecast horizon and also changes over time. For the full sample period the simultaneous equation model, which takes into account credit supply restrictions and real estate taxation, shows the best performance measured in terms of root mean squared forecasting error (RMSFE). In the first part of the sample (2005-2010), medium-term forecasts of house prices greatly benefit from conditioning on the evolution of households’ disposable income, whereas from 2010 onwards the path of the stock of mortgages becomes important.

Keywords: house prices; forecasting; structural model; BVAR (search for similar items in EconPapers)
JEL-codes: C32 C53 E37 R39 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-eur, nep-for, nep-mac and nep-ure
Date: 2018-10
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