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Constructing and Evaluating an Autoregressive House Price Index

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Topics in Applied Statistics

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 55))

Abstract

We examine house price indices, focusing on an S&P/Case-Shiller-based index and an autoregressive method. Issues including the effect of gap time on sales and the use of hedonic information are addressed. Furthermore, predictive ability is incorporated as a quantitative metric into the analysis using data from home sales in Columbus, Ohio. When comparing the two indices, the autoregressive method is found to have the best predictive capabilities while accounting for changes in the market due to both single and repeat sales homes in a statistical model.

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Author information

Authors and Affiliations

  1. Fordham University, 5 Columbus Circle, New York, NY, 10019, USA

    Chaitra H. Nagaraja

  2. University of Pennsylvania, 400 Jon M. Huntsman Hall, 3730 Walnut St., Philadelphia, PA, 19104, USA

    Lawrence D. Brown

Authors
  1. Chaitra H. Nagaraja
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  2. Lawrence D. Brown
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Corresponding author

Correspondence to Lawrence D. Brown .

Editor information

Editors and Affiliations

  1. Takeda Pharmaceuticals, Cambridge, Massachusetts, USA

    Mingxiu Hu

  2. Takeda Pharmaceuticals, Cambridge, Massachusetts, USA

    Yi Liu

  3. Takeda Pharmaceuticals, Cambridge, Massachusetts, USA

    Jianchang Lin

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Nagaraja, C.H., Brown, L.D. (2013). Constructing and Evaluating an Autoregressive House Price Index. In: Hu, M., Liu, Y., Lin, J. (eds) Topics in Applied Statistics. Springer Proceedings in Mathematics & Statistics, vol 55. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7846-1_1

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