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on Discrete Choice Models |
By: | Bartkowski, Bartosz; Massenberg, Julian Richard; Lienhoop, Nele |
Abstract: | Soils provide multiple benefits for human well-being, which are largely invisible to most beneficiaries. Here, we present the results of a discrete choice experiment into the preferences of Germans for soil-based ecosystem services. To tackle complexity and unfamiliarity of soils, we express soil-based ecosystem service attributes relative to the site-specific potential of soils to provide them. We investigate how knowledge about soils, awareness of their contributions to human well-being and experience with droughts and floods affect the preferences. We find substantial yet heterogeneous preferences for soil-based ecosystem services. Only some measures of familiarity exhibit significant effects on preferences. |
Keywords: | Agriculture,Discrete choice experiment,Ecosystem services,Nonmarket valuation,Stated preferences,Soil functions,Willingness to pay |
JEL: | Q15 Q24 Q51 Q57 |
Date: | 2022 |
URL: | http://d.repec.org/n?u=RePEc:zbw:ufzdps:32022&r= |
By: | Tatiana de Macedo Nogueira Lima (Conselho Administrativo de Defesa Econômica (Cade), Departamento de Estudos Econômicos) |
Abstract: | Analisa a aplicação de modelos de preços hedônicos e de disposição a pagar (willingness to pay – wtp) no estudo (i) do poder de mercado de prestadores de serviços de saúde e (ii) da influência da rede assistencial na dinâmica competitiva no setor de planos de saúde. |
Keywords: | Saúde suplementar, preços hedônicos, wtp, planos de saúde, Cade. |
Date: | 2020–06 |
URL: | http://d.repec.org/n?u=RePEc:atg:wpaper:32020&r= |
By: | Hélène Bouscasse (CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Sandrine Mathy (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Rim Rejeb (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Carole Treibich (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes) |
Date: | 2022–03–20 |
URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03622469&r= |
By: | Kaido, Hiroaki; Wuthrich, Kaspar |
Abstract: | The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen (2005)) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of conventional quantile regression subproblems which are convex and can be solved efficiently. This reformulation leads to new identification results and to fast, easy to implement, and tuning‐free estimators that do not require the availability of high‐level “black box” optimization routines. |
Keywords: | Instrumental variables, quantile regression, contraction mapping, fixed-point estimator, bootstrap, Econometrics |
Date: | 2021–05–01 |
URL: | http://d.repec.org/n?u=RePEc:cdl:ucsdec:qt362921wv&r= |