The monotonicity constraint is a common side condition imposed on modeling problems as diverse as hedonic pricing, personnel selection and credit rating. Experience tells us that it is not trivial to generate artificial data for supervised learning problems when the monotonicity constraint holds. Two algorithms are presented in this paper for such learning problems. The first one can be used to...

The present paper attempts to bring further evidence on the behavioral gap for organic food in Britain. The stated preferences are analyzed with the contingent valuation method while the revealed preferences are estimated with the hedonic pricing method. We find a small but significant gap in the premium for organic food between stated and revealed preferences. This gap may suggest a need for p...

One of the most widely appreciated problems of contingent valuation is the potential manipulability of the method, thus subjecting it to possible strategic bias. This paper shows that under usual conditions this problem also holds for market-based methods, such as travel cost and hedonic pricing. However, not all formats of these valuation methods are manipulable. This paper finds positive resu...

In order to value non-market goods, many governments and organisations elicit individuals’ revealed or stated preferences in relation to those goods. We compare this conventional approach to that of subjective well-being (SWB), which is based on individuals’ ratings of their happiness or life satisfaction rather than on their preferences. In the context of urban regeneration, we find that monet...

We hypothesize that quality signals improve over time with the quality performance of a wine producer, and that spillovers will affect other producers within the same region. For this purpose, we estimate a hedonic pricing model for premium California wine. Data source is the annual publication "California Wine Winners" accumulated over the judging years 1990-2001. Quality indicators for 19,583...

Information theoretic estimators for the first-order spatial autoregressive model are introduced, small sample properties are investigated, and the estimator is applied empirically. Monte Carlo experiments are used to compare finite sample performance of more traditional spatial estimators to three different information theoretic estimators, including maximum empirical likelihood, maximum empir...

A number of hedonic property pricing studies of flood risk indicate that properties within a designated higher flood risk zone sell for a lower price than an equivalent property outside of it. However, often the homes most at flood risk are also the most desirable in terms of their proximity to the water, and this concurrent existence of positive water-related amenities and negative flood risk ...

A number of hedonic property pricing studies of flood risk indicate that properties within a designated higher flood risk zone sell for a lower price than an equivalent property outside of it. However, often the homes most at flood risk are also the most desirable in terms of their proximity to the water, and this concurrent existence of positive water-related amenities and negative flood risk ...

This paper aims to explore the contribution of streetscape features Airbnb accommodation pricing, allowing hosts and tourists benefit from a more transparent pricing scheme. To this end, hedonic model based on Geographically Weighted Regression (GWR) is estimated using data in July November 2020 Amsterdam. With semantic segmentation Deeplabv3 trained by Cityscapes dataset, percentages 4 types p...