scholarly journals Using stated preference methods to design cost-effective subsidy programs to induce technology adoption: An application to a stove program in southern Chile

2014 ◽  
Vol 132 ◽  
pp. 346-357 ◽  
Author(s):  
Walter Gómez ◽  
Hugo Salgado ◽  
Felipe Vásquez ◽  
Carlos Chávez
Author(s):  
Denzil G. Fiebig ◽  
Hong Il Yoo

Stated preference methods are used to collect individual-level data on what respondents say they would do when faced with a hypothetical but realistic situation. The hypothetical nature of the data has long been a source of concern among researchers as such data stand in contrast to revealed preference data, which record the choices made by individuals in actual market situations. But there is considerable support for stated preference methods as they are a cost-effective means of generating data that can be specifically tailored to a research question and, in some cases, such as gauging preferences for a new product or non-market good, there may be no practical alternative source of data. While stated preference data come in many forms, the primary focus in this article is data generated by discrete choice experiments, and thus the econometric methods will be those associated with modeling binary and multinomial choices with panel data.


2021 ◽  
pp. 105527
Author(s):  
Tensay Hadush Meles ◽  
Alemu Mekonnen ◽  
Abebe D. Beyene ◽  
Sied Hassen ◽  
Subhrendu K. Pattanayak ◽  
...  

Author(s):  
Joe Kerkvliet

Economics plays strong roles in the design, implementation, and evaluation of the Endangered Species Act (ESA). First, the ESA’s language allows for economic analysis of critical habitat designations, recovery plan implementations, listing postponements, and the design of habitat-conservation plans. Extensive administrative changes to the ESA in the 1990s were designed to reduce economic costs and to elicit landowners’ cooperation. These reforms were partly motivated and guided by economic analysis. Second, economic analysis plays a role in providing credible estimates of the economic costs of ESA implementation. Cost estimates are highly variable and likely to depend on species’ characteristics and the effectiveness of recovery programs. Emerging evidence suggests that the 1990 reforms are reducing costs and increasing effectiveness. Third, economic science contributes to estimation of benefits. Because of the “public goods” nature of nearly all ecosystem and species conservation efforts, estimates must be based on stated preference methods. This use leads to difficulties in establishing the authenticity of benefits estimates. Also, research suggests that benefits estimates are highly sensitive to the spatial nature of the market (beneficiaries’ geographic locations). Future research needs to tackle both authenticity and spatial issues. Fourth, benefit–cost analysis (BCA) is required by law to inform many resource decisions affecting ecosystem and species conservation. Four illustrative BCAs show that whether benefits exceed costs is highly dependent on the authenticity of benefits based on stated preference methods and assumptions about the spatial nature of the market. Substantial uncertainty accompanies both benefit and cost estimates.


2018 ◽  
Vol 31 ◽  
pp. 35-46 ◽  
Author(s):  
Viktoriya Kolarova ◽  
Felix Steck ◽  
Rita Cyganski ◽  
Stefan Trommer

2018 ◽  
Vol 201 ◽  
pp. 140-151 ◽  
Author(s):  
Tobias Börger ◽  
Anne Böhnke-Henrichs ◽  
Caroline Hattam ◽  
Joanna Piwowarczyk ◽  
Femke Schasfoort ◽  
...  

Author(s):  
Matthew Boutelle ◽  
Fluvio Lobo ◽  
Mohammad Odeh ◽  
Jack Stubbs

This paper discusses the design and application of magnetic-based position tracking in surgical trainers. The utilization of magnetic-based position tracking in Laparoscopic Trainers provides a cost-effective solution to the next generation of medical education, training and evaluation. The utilization of 3D printed parts as well as off the shelf electronics allows us to maximize accuracy while minimizing design cost. Our current design costs less than $300.00 while providing results with an error of 1.474–14.265%.


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