Semiparametric hedonic price models: assessing the effects of agricultural nonpoint source pollution

Bontemps, Christophe; Simioni, Michel; Surry, Yves

doi:10.1002/jae.1022

Cited by 46 publications

(38 citation statements)

References 25 publications

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“…Our findings also agree with results obtained by Desmet (2000) for car markets and with recent empirical results by Bontemps et al (2008), obtained using a kernel-based semiparametric approach.…”

Section: Discussionsupporting

confidence: 82%

Nonparametric neural network modeling of hedonic prices in the housing market

Landajo

Bilbao

2011

Empir Econ

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This article addresses the contribution to hedonic modeling of a nonparametric approach based on artificial neural network (ANN) regressions. ANNs provide consistent estimates for the hedonic price of each attribute and permit a number of hypotheses on the hedonic price relationship to be tested nonparametrically. In particular, we exploit results by Stinchcombe and White (Econom Theory 14:295-324, 1998) in order to carry out misspecification testing in linear and semiloglinear hedonic models. The same approach directly applies to testing misspecification of any parametric specification for the hedonic relationship. A nonparametric significance test for the variables in the hedonic model is also proposed. The test extends the approach developed by Racine (J Bus Econ Stat 15(3):369-378, 1997) in kernel-based nonparametric testing to ANN-based inference. The finite sample performance of the proposed tests is analyzed through Monte Carlo experiments, and simulation-based algorithms for computation of the null distribution of the tests are proposed. Then, the performance of three classes of regression models-linear, semi-log, and ANNs-applied to Electronic supplementary material The online version of this article (123 988 M. Landajo et al.hedonic price modeling in a Spanish regional housing market is compared. Our results indicate the presence of nonlinear behavior, as predicted by economic theory, with the ANN-based tests detecting statistically significant evidence of misspecification-both in the linear and the semilog specifications-and ANN regressions providing moderate improvement of predictive performance.

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Section: Discussionsupporting

confidence: 82%

Nonparametric neural network modeling of hedonic prices in the housing market

Landajo

Bilbao

2011

Empir Econ

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“…However, previous research has shown that in hedonic models restrictive parametric specification can rarely be justified a priori (e.g., Cropper et al 1988;Ekeland, Heckman, andNesheim 2002, 2004) and that semi-and nonparametric alternatives can provide several advantages (Anglin and Gencay 1996;Parmeter, Henderson, and Kumbhakar 2007;Bontemps, Simioni, and Surry 2008). In addition, findings reported by Deschênes and Greenstone (2012) seem to indicate that the predicted impacts of climate change on farm profits are heavily dependent on the functional form assumed for the climatic and control variables.…”

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confidence: 70%

The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farmland Values

Fezzi¹,

Bateman²

2015

Journal of the Association of Environmental and Resource Econom

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“…A problem with the latter techniques is that it is very data‐intensive, as most hedonic price functions contain a large number of explanatory variables. This may lead to the so‐called “curse of multidimensionality”: estimation precision rapidly deteriorates when the number of explanatory variables increases (Horowitz and Savin, 2001; Bontemps, Simoni, and Surry, 2008; McMillen, 2010)…”

Section: Hedonic Price Methods and Mixed Land Usementioning

confidence: 99%

The Impact of Mixed Land Use on Residential Property Values*

Koster¹,

Rouwendal²

2012

Journal of Regional Science

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SummaryContemporary European urban planning policies aim to mix land uses in compact neighbourhoods. It is presumed that mixing land uses yields socio-economic benefits and therefore has a positive effect on housing values. In this paper, we investigate the impact of mixed land use on housing values using semiparametric estimation techniques. We demonstrate that a diverse neighbourhood is positively valued by households. There are various land use types which positively affect house prices, e.g. business services and leisure. Land uses that are incompatible with residential land use are, among others, manufacturing and wholesale. It appears that households are willing to pay up to 6 percent more for a house in a mixed neighbourhood than for an otherwise comparable house in a monofunctional area. We also show that there is substantial heterogeneity in willingness to pay for mixed land use. For example, apartment occupiers are willing to pay almost 25 percent more for diversity than households living in detached housing.Keywords: Mixed land use; diversity; hedonic price analysis; semiparametric estimation; AcknowledgementsWe would like to thank the NVM and Statistics Netherlands for providing data. The paper has benefited from a NICIS-KEI research grant. We are indebted to Piet Rietveld, Wouter Jacobs and Wendy Tan for valuable comments.

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Semiparametric hedonic price models: assessing the effects of agricultural nonpoint source pollution

Cited by 46 publications

References 25 publications

Nonparametric neural network modeling of hedonic prices in the housing market

Nonparametric neural network modeling of hedonic prices in the housing market

The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farmland Values

The Impact of Mixed Land Use on Residential Property Values*

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