Abstract
The conceptualization of environmental policies aiming to promote pro-environmental behavior has long been based mainly upon the theoretical inputs provided by standard economics. As a result of a growing awareness about the limited effectiveness of such concepts there is to be observed a re-orientation of environmental policy toward “soft-policy” instruments. In this connection, social scientists and policymakers have increasingly given attention to behavioral economics as a basis for designing more effective policy instruments. Research concerning this approach and especially its actual application are, however, still at an early stage, and, moreover, the field of behavioral economics is still developing.
Against this background, it yet has to be researched in detail, which concrete input behavioral economics might provide for the conceptualization of different kinds of environmental policy instruments and fields of applications. That is the scope of this study, which presents the results of a worldwide online survey requesting scientists concerned with both behavioral and environmental issues as well as heterodox economists to assess (1) the current state of the art of standard economics and its implications for environmental policy, (2) in more detail, the current state of the art of behavioral economics and its implications for environmental policy, and (3) as a central focus, the relevance of behavioral effects, for example the endowment effect and bounded rationality, for different kinds of environmental policy instruments. The results point to the necessity of a further development of behavioral economics that is less closely tied to anomaly research and the analysis of single behavioral effects, and instead takes a more interdisciplinary perspective. The results also indicate the relevance of other-regarding preferences, especially for the design of soft environmental policy instruments. With a behavioral foundation, information-based as well as cooperative-based policy instruments are expected to gain more importance in the future.
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Notes
- 1.
- 2.
This is exemplified by the results of a search within the literature data base “Ebsco Scientific Discovery Service.” For this purpose, a search term was developed, using two different Booleans (AND, OR), one kind of expander (*) and one limiter (AB, which is the abbreviation for ‘abstract’): AB ((“Behavio* economics”) AND (ecolog* OR sustainab* OR environm* OR Green) AND (“regulation” OR “policy” OR “intervention” OR govern*)). The output obtained was 21 articles published in scientific journals (only five of them were related to the topics at stake). The substitution of the term (“Behavio* economics”) with the term (“psycho*”) resulted in 3,586 hits.
- 3.
It should be mentioned, that nudging is also discussed controversially. It is considered positively as an instrument which allows agents to maintain their freedom of choice, as the desired course of action is not enforced. However, more negatively, its potentially manipulative character is criticized, as is the underlying assumption behind such an approach that policymakers have an (unbounded) ability to identify and design efficient nudges (see Rizzo and Whitman 2008; Wilkinson 2013; White 2013; Qizilbash 2012).
- 4.
In the following presentation of the results of the study, only very brief introductory remarks will be made regarding the various topics evaluated. For readers who are not so familiar with the concepts and effects discussed in behavioral economics and environmental policy, it is therefore recommended to read Chap. 2 by Frank Beckenbach for the purpose of gaining a general overview. Both the paper by Beckenbach and this article are part of the project “Innovative approaches to improve the incentives of environmental instruments, Part I: State of the art” carried out on behalf of the German Federal Environmental Agency (UBA) (see Chap. 1). In this connection, Beckenbach’s paper provided the theoretical systematization of the concepts of behavioral economics and their related effects for the questionnaire which forms the basis of this article.
- 5.
Ten scientists belonging to both of the samples were assigned to the EBS.
- 6.
With question number 4, the questionnaire started to ask specific questions on the relation of behavioral economics and the concepts of environmental politics. With questions 8 and 11, these queries were then further specified.
- 7.
While researching the e-mail addresses of the scientist of both of the samples, the title and gender were also collected. The distribution of the title and gender of the respondent sample corresponds to the respective distribution of the initial sample.
- 8.
Cohen (1992) classifies effect sizes between 0.2 and 0.5 as small, between 0.5 and 0.8 as medium, and above 0.8 as large.
- 9.
It was also calculated if the responses differed significantly according to age groups, but this was not the case.
- 10.
In order to gain further insight about possible differences in the answers according to group specificities, the EBS and the HSS sample were divided separately according to the importance they ascribed to behavioral economics for their own research activities, thereby forming three groups respectively, each relating to two scale points. Thus, all in all, six groups were differentiated. For all pairwise combinations of these six groups, the effect sizes were calculated. Unfortunately, a complete description of the respective results would go beyond the size and scope of this paper. To summarize briefly, no surprising results were obtained and they confirm the results given in this article. In particular, the results showed that the most critical perspectives on behavioral economics and its application to environmental policy issues came to a large extent from those scientists less concerned with behavioral economics aspects. This is more pronounced for scientists belonging to the HSS sample.
- 11.
With regard to the group test, no relevant effect sizes occur.
- 12.
It should be mentioned that 11.3 % of the HSS respondents made no statement about prospect theory; commentaries on this question block reveal that this was due to a lack of knowledge about the concept.
- 13.
The percentage of missing responses of the HSS sample was again rather high. The percentages of the missing responses were as follows: aspiration level/satisficing (14.5 %), endowment effect (12.9 %), decision routines (12.9 %), framing effect (11.3 %), problem solving (9.7 %), fairness/altruism (6.5 %) and reciprocity (6.5 %).
- 14.
Approximately 20 % of both groups did not fill in the matrix at all. This again might be due to the specificity and, moreover, the complexity of the task. Thus, the results are based on the responses of 179 scientists, all of whom filled in the matrix completely.
- 15.
The analysis of the results was conducted both by row and by column since not all of the respondents conformed to the requested limitation. The values were adjusted accordingly.
- 16.
The queries were defined rather broadly to identify relevant articles to the greatest possible extent and to avoid an artificial narrowing of the query results by using keywords. The search algorithms used were, for example, “behavio#ral economics AND (environ* OR sustain*“OR ecologic*)” as well as “(“ecological economics“OR “environmental economics”) AND (psych* OR cogn* OR behav*)”.
- 17.
- 18.
http://www.plurale-oekonomik.de/?page_id=252; accessed on 16.03.2014.
- 19.
http://www.voeoe.de/; accessed on 16.03.2014.
- 20.
http://nachhaltige-oekonomie.de/de/netzwerk/mitglieder.html/; accessed on 16.03.2014.
- 21.
http://www.experimental-economics.org/index.html; accessed on 16.03.2014.
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Appendix
Appendix
1.1 Address Data Query
The basic population of the “Environmental Behavioral Scientists” (EBS) was collected by systematically querying the databases “Web of Knowledge” (query by topics) and “Econlit” (full text query) for corresponding keywords in articles published between 1980 and 2012.Footnote 16 In addition, the databases “Ebsco Science Discovery Service” and Google Scholar were queried. On this basis, and after eliminating duplicates, 1,532 articles potentially related to the subject were identified. To ensure that these 1,532 articles actually fit the present topic, the abstracts and also parts of the full text were read by the author. Subsequently, the number of the articles was reduced to 545. The names of the authors of these articles were then transferred to an address database, and corresponding e-mail addresses were assigned either by using the data provided in the articles or by Internet search. The database finally comprised the basic population of 930 researchers. It should be remarked that it was not possible to check the extent to which the researchers are still active in the present research area. Thus, the actual basic population may be significantly lower.
To assemble the basic population of the heterodox social scientists, researchers from the German-speaking area who either signed the memorandum “Für eine Erneuerung der Ökonomie: Memorandum besorgter Wissenschaftlerinnen und Wissenschaftler”Footnote 17 and/or are members of the “Netzwerk Plurale Ökonomie”Footnote 18 respectively the “Vereinigung für Ökologische Ökonomie”Footnote 19 were contacted. Furthermore, members of the network “Nachhaltige Ökonomie”Footnote 20 and the “Gesellschaft für Experimentelle Wirtschaftsforschung”Footnote 21 were added to the basic population.
1.2 Descriptive Statistic and Effect Sizes
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Daskalakis, M. (2016). Specification Required? A Survey of Scientists’ Views About the Role of Behavioral Economics for Assessing Environmental Policy Instruments. In: Beckenbach, F., Kahlenborn, W. (eds) New Perspectives for Environmental Policies Through Behavioral Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-16793-0_3
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