What is he best known for?
The fields of study he is best known for:
- Statistics
- Microeconomics
- Ecology
Richard C. Bishop mainly focuses on Contingent valuation, Actuarial science, Microeconomics, Valuation and Dichotomous choice.
His Contingent valuation study integrates concerns from other disciplines, such as Bidding and Test validity.
As part of one scientific family, Richard C. Bishop deals mainly with the area of Actuarial science, narrowing it down to issues related to the Payment, and often Empirical research.
The study incorporates disciplines such as Ecological economics and Sustainability in addition to Microeconomics.
In his study, Ecosystem, Ecosystem services and Cost–benefit analysis is strongly linked to Environmental resource management, which falls under the umbrella field of Valuation.
Richard C. Bishop has included themes like Goods and services and Travel cost, Recreation in his Willingness to pay study.
His most cited work include:
- Measuring Values of Extramarket Goods: Are Indirect Measures Biased? (963 citations)
- Using donation mechanisms to value nonuse benefits from public goods (499 citations)
- Endangered Species and Uncertainty: The Economics of a Safe Minimum Standard (401 citations)
What are the main themes of his work throughout his whole career to date?
Contingent valuation, Actuarial science, Econometrics, Valuation and Recreation are his primary areas of study.
His Contingent valuation study combines topics from a wide range of disciplines, such as Payment and Public good.
His study in Actuarial science is interdisciplinary in nature, drawing from both Environmental good and Expected utility hypothesis.
The Valuation study which covers Environmental resource management that intersects with Environmental economics.
The Recreation study combines topics in areas such as Logistic regression, Site quality, Multinomial logistic regression and Fishing.
His work on Dichotomous choice is typically connected to Cumulative distribution function as part of general Willingness to pay study, connecting several disciplines of science.
He most often published in these fields:
- Contingent valuation (38.26%)
- Actuarial science (20.00%)
- Econometrics (18.26%)
What were the highlights of his more recent work (between 2008-2019)?
- Contingent valuation (38.26%)
- Actuarial science (20.00%)
- Payment (9.57%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Contingent valuation, Actuarial science, Payment, Valuation and Econometrics.
Many of his studies on Contingent valuation apply to Positive economics as well.
His Actuarial science research includes elements of Cheap talk and Set.
His work in Payment addresses issues such as Willingness to pay, which are connected to fields such as Econometric model.
His biological study spans a wide range of topics, including Natural resource and Environmental protection.
His work carried out in the field of Econometrics brings together such families of science as Affect, Demand curve, Travel cost, Recreation and Site quality.
Between 2008 and 2019, his most popular works were:
- A Comparison of Approaches to Mitigate Hypothetical Bias (61 citations)
- Putting a value on injuries to natural assets: The BP oil spill (46 citations)
- Reliability and Validity in Nonmarket Valuation (25 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Microeconomics
- Ecology
His primary scientific interests are in Contingent valuation, Valuation, Payment, Actuarial science and Econometrics.
As part of his studies on Contingent valuation, Richard C. Bishop often connects relevant areas like Content validity.
His Valuation research incorporates themes from Natural resource and Environmental protection.
His Payment research includes themes of Cheap talk, Econometric model and Willingness to pay.
His work on Revealed preference and Unobservable as part of general Econometrics study is frequently linked to Computer science, Nonmarket forces and Criterion validity, bridging the gap between disciplines.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
