AVM and high dimensional data: Do ridge, the lasso or the elastic net provide an "automated" solution?

Nils Hinrichs, Jens Kolbe and Axel Werwatz

No 22 (2020), FORLand Working Papers from Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation"

Abstract: In this paper, we apply Ridge Regression, the Lasso and the Elastic Net to a rich and reliable data set of condominiums sold in Berlin, Germany, between 1996 and 2013. We their predictive performance in a rolling window design to a simple linear OLS procedure. Our results suggest that Ridge Regression, the Lasso and the Elastic Net show potential as AVM procedures but need to be handled with care because of their uneven prediction performance. At least in our application, these procedures are not the "automated" solution to Automated Valuation Modeling that they may seem to be.

Keywords: Automated valuation; Machine learning; Elastic Net; Forecastperformance (search for similar items in EconPapers)
JEL-codes: C14 R31 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:forlwp:222020

DOI: 10.18452/21263

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