Higher Frequency Hedonic Property Price Indices: A State Space Approach

Robert Hill (), Alicia Rambaldi () and Michael Scholz ()
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Michael Scholz: University of Graz, Austria

No 2018-04, Graz Economics Papers from University of Graz, Department of Economics

Abstract: The hedonic imputation method estimates separate characteristic shadow prices for each period. These are used to construct matched samples, which are inserted into standard price index formulas. We implement two innovations to improve the method s effectiveness on housing data at higher frequencies. First, we use a time-varying parameter model in state-space form to increase the reliability of the estimated characteristic shadow prices. Second, we significantly reduce the number of parameters by replacing postcode dummies by a geospatial spline surface. Empirically, using a novel criterion, we show that in higher frequency comparisons our hedonic method outperforms competing alternatives.

Keywords: Housing market; Hedonic imputation; State Space Model; Geospatial data; Spline; Quality adjustment; Matched sample (search for similar items in EconPapers)
JEL-codes: C33 C43 R31 (search for similar items in EconPapers)
Date: 2018-02
New Economics Papers: this item is included in nep-ure
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Journal Article: Higher frequency hedonic property price indices: a state-space approach (2021)
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