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Record Nr. |
UNINA9911015651103321 |
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Autore |
Mariel Petr |
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Titolo |
Environmental Valuation with Discrete Choice Experiments in R : A Guide on Design, Implementation, and Data Analysis / / by Petr Mariel, Danny Campbell, Erlend Dancke Sandorf, Jürgen Meyerhoff, Ainhoa Vega-Bayo, Rebecca Blevins |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (425 pages) |
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Collana |
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The Economics of Non-Market Goods and Resources ; ; 17 |
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Altri autori (Persone) |
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CampbellDanny |
SandorfErlend Dancke |
MeyerhoffJürgen |
Vega-BayoAinhoa |
BlevinsRebecca |
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Disciplina |
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Soggetti |
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Environmental economics |
Environmental policy |
Econometrics |
Environmental Economics |
Environmental Policy |
Quantitative Economics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1. Introduction -- Chapter 2. Steps of a Discrete Choice Experiment -- Chapter 3. Random utility models: Theoretical background -- Chapter 4. Case study -- Chapter 5. Experimental design -- Chapter 6. Data collection in Shiny -- Chapter 7. From Raw Data to Insights -- Chapter 8. Maximum Likelihood and Related Issues -- Chapter 9. Estimation -- Chapter 10. Post-estimation analysis -- Chapter 11. Final thoughts. |
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Sommario/riassunto |
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This open access book offers advice and practical guidance for conducting discrete choice experiments (DCEs) in environmental valuation. It covers essential aspects of designing, implementing, and analysing choice experiments. Each chapter includes scripts and |
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guidance, showcasing how to execute every step of a DCE using the free statistical computing and graphics software, R. This feature enhances accessibility and versatility for researchers in the field. While not providing strict guidelines, the book assists readers in steering clear of common mistakes encountered in applied work. With its insights and expertise, it equips researchers and practitioners to effectively navigate the complexities of DCEs. |
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