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5-24 Lecture: Using meta-analysis to explain the virtual error in the questionnaire survey

Time: 2018.5.24 9:30 AM

Location: Main Building 132

Speaker Profile:

Hu Wuyang is a professor and doctoral tutor of the AED Economics Department at the Ohio State University. Born in Beijing, China, in 1976 and taught in the United States in 2004 after receiving a Ph.D. in economics from the University of Alberta. Since 2011, he has served as Editor-in-Chief of the flagship publication of the Canadian Agricultural Economic Association, Canadian Journal of Agricultural Economics, a SSCI/SCI double-indexed journal, Chairman of the China Association of Agriculture and Applied Economics (2012-2015), China CCTV US headquarters invited TV commentators. Research interests include behavioral economics, marketing, development economics, and environmental resource economics. More than 60 papers published in many international SSCI journals such as "America's Agricultural Economy", "Agricultural Economy of Canada", "European Agricultural Economic Review", "Marine Resources Economy", "Growth and Change", and "Environmental Economics" He has served as a guest reviewer for more than 40 international journals for a long time.

 

Main content

Virtual errors arise when answering scientific research questions. The behaviors stated by the respondent are inconsistent with their behaviors in real life, which results in questionnaires and other scientific research methods failing to faithfully reflect true behavior. This study used meta-analysis to analyze more than 500 academic papers. The main purpose was to investigate the sources of virtual errors and analyze the solutions. This study pays particular attention to the application of dome new valuation methods that have never been seen in similar literature before, such as selection experiments, Turnbull distribution valuation methods, validity and deterministic tracking, etc., and draw some new conclusions. Different results, such as the use of so-called real-world choices such as auction experiments, do not necessarily produce smaller virtual errors than using traditional referendum methods. This study will help scholars in different disciplines such as resource and environmental assessment, marketing, transportation, and medical science to better understand the conditions for the generation of virtual errors, and to formulate effective solutions to the problems when collecting data.

 

                                                                                      

(Host, Undertaker: School of Management and Economics)

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