Does the estimated impact of wildfires vary with the housing price distribution? A quantile regression approach

Mueller, Julie M.; Loomis, John B.

doi:10.1016/j.landusepol.2014.05.008

Cited by 43 publications

(18 citation statements)

References 21 publications

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“…The coefficients are estimated based on the procedure described by Koeneker and Hallock (2001) using the ‘qreg’ command in STATA (version 13). According to Mueller and Loomis (2014), qreg estimates the regression using linear programming techniques as described in Armstrong et al (1979). It also estimates the variance–covariance matrix of the coefficients using a method proposed by Koenker and Bassett (1982) and Rogers (1992).…”

Section: Methodsmentioning

confidence: 99%

Insights from analysing tourist expenditure using quantile regression

Almeida

Garrod

2016

Tourism Economics

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This is the author accepted manuscript. The final version is available from Tourism Economics via http://dx.doi.org/10.1177/1354816616668108Like many other small-island tourism destinations, Madeira faces considerable challenges due to its limited resources and mature markets, including decreasing daily expenditures, a dependency on repeat tourists and decreasing length of stay. Product diversification is frequently recommended as a strategic response and rural tourism as a candidate product. The efficacy of rural tourism as a strategy for increasing destination-wide tourism receipts remains, however, largely unproven. The purpose of this study is to examine the determinants of the daily expenditure of tourists staying in the rural interior of Madeira, based on quantile regression analysis. The results suggest that such tourists are rather passive, wishing mainly to rest and relax. As such, their daily expenditures are not appreciably greater than those of coastal tourists who comprise the mainstay of Madeira?s clientele. Quantile analysis nevertheless provides some useful insights for developing strategies to increase their spending, including family groups and first-time tourists.authorsversionPeer reviewe

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Section: Methodsmentioning

confidence: 99%

Insights from analysing tourist expenditure using quantile regression

Almeida

Garrod

2016

Tourism Economics

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“…As a useful supplement to OLS regression, quantile regression produces a complete description of the impact across the entire distribution of housing prices and is robust to non-normal random errors [59,60]. This method has been widely used in the field of social sciences and some scholars have recently tried introducing it into the field of real estate [61][62][63][64][65]. For example, Kang and Liu [66] investigated the influence of the 2008 financial crisis on housing prices at different quantiles of the price distribution in Taiwan.…”

Section: Of 23mentioning

confidence: 99%

Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China

et al. 2018

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Most existing studies empirically investigated the impact of rail transit on housing prices using the traditional hedonic price model, which is based on ordinary least squares (OLS). This method can estimate only the average implicit prices of housing characteristics and may ignore possible heterogeneous impacts of rail transit at different housing price levels. As a useful supplement to OLS regression, quantile regression can measure how implicit prices of explanatory variables vary across different price levels, thereby providing a comprehensive picture of the relationship between housing characteristics and prices. By using Hangzhou, China as an example, this study adopts the traditional hedonic price model and quantile regression model to investigate the capitalization effect of a new subway line on housing prices. Empirical results suggest the significant impacts of accessibility to subway stations. The average housing price within 2 km of the station is 2.1% to 6.1% higher than those outside. We also find that the impacts of the subway differ significantly across the distribution of housing prices, wherein the absolute value of estimated coefficients increased from 0.023 for the 15th quantile to 0.086 for the 95th quantile. The subway opening strengthens the capitalization effect of traffic accessibility. The absolute value of price elasticity increases from 0.044 to 0.053, and the range of influence is expanded from 1500 m to 2000 m.

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“…Individual tolerance for fire risk can impact land use change. Economic studies [24,25] of land use change have shown that some risk averse landowners are less likely to develop fire prone areas, although this aversion is often balanced by the fact that many fire prone areas also have natural amenities that are desired by home owners (for instance fire prone steep slopes may also offer wonderful views) [26,27]. While it is a common assumption in many fire prone areas that landowners typically rebuild after a fire, empirical evidence suggest that this is not always the case, and indeed a re-wilding of some previously subdivided land may take place after fires [28].…”

Section: Fire Risk and The Management Of Fire Risk As Drivers Of Landmentioning

confidence: 99%

Land Use and Wildfire: A Review of Local Interactions and Teleconnections

Butsic

Kelly

Moritz

2015

Land

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Abstract:Fire is a naturally occurring process of most terrestrial ecosystems as well as a tool for changing land use. Since the beginning of history humans have used fire as a mechanism for creating areas suitable for agriculture and settlement. As fires threaten human dominated landscapes, fire risk itself has become a driver of landscape change, impacting landscapes through land use regulations and fire management. Land use changes also influence fire ignition frequency and fuel loads and hence alters fire regimes. The impact of these changes is often exacerbated as new land users demand alternative fire management strategies, which can impact land cover and management far from where land use change has actually occurred. This creates nuanced land use teleconnections between source areas for fires and economic cores, which demand and fund fire protection. Here we will review the role of fire and fire risk as a driver of land use change, the ways land use changes impact drivers of fire, and suggest that the integration of land use teleconnections into the fire/land use discussion can help us better understand and manage the complex interactions between fire and land use.

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Does the estimated impact of wildfires vary with the housing price distribution? A quantile regression approach

Cited by 43 publications

References 21 publications

Insights from analysing tourist expenditure using quantile regression

Insights from analysing tourist expenditure using quantile regression

Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China

Land Use and Wildfire: A Review of Local Interactions and Teleconnections

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