Joint-outcome prediction markets for climate risks

Mark S. Roulston; Kim Kaivanto

doi:10.1371/journal.pone.0309164

Peer Review History

Original SubmissionMarch 22, 2023
6 Jul 2023 Decision Letter - Robin Haunschild, Editor PONE-D-23-08410Joint-outcome Prediction Markets for Climate RisksPLOS ONE Dear Dr. Roulston, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Aug 20 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: No ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Predicting future climate is still very important in human history. This study proposes a joint-outcome-market approach to predict the monthly averaged daily high temperature and total monthly rainfall for the United Kingdom, for the months of April to September 2018. The approach has important contribution if the empirical result is more robust. However, the authors just adopt six joint markets and special period to support their claims. The study should give a clear conclusion instead of discussion. Reviewer #2: Lack of Context: Without setting the stage, the work quickly dives into a discussion of climate forecasting. It would be useful to begin with some background information on the significance and present methods of climate prediction, as well as some discussion of the shortcomings of these methods. This would lay the groundwork for learning about the importance of non-traditional approaches like prediction markets. The document alludes to the "circularity" (or interdependence) between climate projections and mitigation programs, but fails to provide a clear explanation of this connection. The importance of explaining why climate predictions are dependent on greenhouse gas emissions and how these projections guide efforts to reduce such emissions cannot be overstated. Readers may struggle to grasp the implications of this circular dependence without a thorough explanation. Although the practicality of prediction markets with joint-outcome spaces is briefly discussed with reference to UK rainfall and temperature instances, the book does not give a thorough examination or analysis of the outcomes. To prove the usefulness of prediction markets in meeting the aforementioned issues, it would be helpful to incorporate in-depth data, statistical analysis, and comparisons with other prediction approaches. The manuscript alludes to knowledge asymmetry as a challenge, but does not address the issue head-on or offer any answers. To assure the reliability of predictions, it is essential to investigate ways to deal with the information asymmetry that plagues prediction markets. The manuscript's argument might benefit from some illumination on this point. The manuscript's narrow focus on monthly rainfall and temperature in the UK makes it difficult to evaluate the wider relevance of prediction markets for climate-related risks. Prediction markets could be useful for making global or regional climate forecasts, but there are some caveats and obstacles to be aware of. The manuscript's authority would also increase if it addressed potential objections to the use of prediction markets. The paper only briefly touches on the use of prediction markets for policy making, planning, and risk disclosure, but it does not dive into the precise consequences or potential benefits of doing so. The manuscript's effect and relevance would increase if it included a more in-depth examination of how prediction markets might influence policy decisions, strengthen planning tactics, and boost risk communication. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. 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Revision 1
13 Jul 2023 Author Response Dear Dr. Haunschild, We would like to submit our revised manuscript, “Joint-outcome Prediction Markets for Climate Risks” to be considered for publication in PLOS ONE as a Research Article. We believe we have addressed the comments made by both reviewers. The changes we have made to our manuscript are described below. 3. Have the authors made all data underlying the findings in their manuscript fully available? Reviewer #1: No Reviewer #2: No RESPONSE: The code used to produce the plots, and the underlying data (in two different formats) can be downloaded from https://drive.google.com/drive/folders/1oAC5LxyospVf00u-lpVlg04wtQjNqEYz ________________________________________ 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Predicting future climate is still very important in human history. This study proposes a joint-outcome-market approach to predict the monthly averaged daily high temperature and total monthly rainfall for the United Kingdom, for the months of April to September 2018. The approach has important contribution if the empirical result is more robust. However, the authors just adopt six joint markets and special period to support their claims. The study should give a clear conclusion instead of discussion. RESPONSE: We have added a conclusion section [L459-L486] which makes clear that we are claiming that the markets demonstrate that using an LMSR market maker overcomes the liquidity issues experienced by previous climate-related markets, and allow a joint-outcome market, with a large number of outcomes to actually work. As Reviewer #1 points out, there are only six markets, and we mention that this is not enough to make conclusions about the statistical accuracy of the prediction market approach compared to other methods. This, however, is an intrinsic problem with all climate forecasting because of the horizons involved. Reviewer #2: Lack of Context: Without setting the stage, the work quickly dives into a discussion of climate forecasting. It would be useful to begin with some background information on the significance and present methods of climate prediction, as well as some discussion of the shortcomings of these methods. This would lay the groundwork for learning about the importance of non-traditional approaches like prediction markets. RESPONSE: The introduction now includes a discussion of current approaches to climate forecasting using coupled general circulation models (CGCMs) [L47-L68] as well as an explanation of “downscaling” these models to produce higher resolution forecasts [L96-L110]. We also emphasize that prediction markets are not a replacement for existing methods for climate forecasting but a mechanism to synthesize different approaches; both traditional CGCMs and non-traditional methods such as ML and AI [L145-L148]. The document alludes to the "circularity" (or interdependence) between climate projections and mitigation programs, but fails to provide a clear explanation of this connection. The importance of explaining why climate predictions are dependent on greenhouse gas emissions and how these projections guide efforts to reduce such emissions cannot be overstated. Readers may struggle to grasp the implications of this circular dependence without a thorough explanation. RESPONSE: We have expanded the explanation of circularity and provided a description of how CGCM forecasts are contingent on the GHG concentration scenarios used [L47-L68]. Although the practicality of prediction markets with joint-outcome spaces is briefly discussed with reference to UK rainfall and temperature instances, the book does not give a thorough examination or analysis of the outcomes. To prove the usefulness of prediction markets in meeting the aforementioned issues, it would be helpful to incorporate in-depth data, statistical analysis, and comparisons with other prediction approaches. RESPONSE: Unfortunately, the data set essentially consists of only six independent forecasts, which severely constrains what conclusions can be drawn concerning accuracy. This is, of course, an intrinsic issue with making any forecasts on seasonal time scales and even more so for forecasts on climate time scales. We discuss this issue in the manuscript [L457-L465]. All the pricing data for the market is available for download so any reader who wishes to conduct a specific form of statistical analysis is free to do so. Our primary conclusion is that using subsidised AMMs overcomes the liquidity problem encountered in previous markets for climate-related outcomes, and with a large number of outcomes, and therefore such AMMs make highly granular joint-outcome markets viable. The manuscript alludes to knowledge asymmetry as a challenge, but does not address the issue head-on or offer any answers. To assure the reliability of predictions, it is essential to investigate ways to deal with the information asymmetry that plagues prediction markets. The manuscript's argument might benefit from some illumination on this point. RESPONSE: Asymmetric information is one of the key problems that prediction markets resolve, through what is termed ‘incentive compatibility’ – i.e., given the way in which a forecaster’s payoff in a prediction market is dependent on the provision of accurate forecasts, the forecaster has the incentive to truthfully provide accurate forecasts. In one sense therefore, prediction markets are an antidote to the problem of asymmetric information, rather than yet another context where information asymmetry is a problem. We have included more information about the problem of information asymmetry, including a reference (Sandroni 2014) that explains how paying forecasters according to a proper scoring rule is incentive compatible – even in the case of a single forecast [L128-L130]. The manuscript's narrow focus on monthly rainfall and temperature in the UK makes it difficult to evaluate the wider relevance of prediction markets for climate-related risks. Prediction markets could be useful for making global or regional climate forecasts, but there are some caveats and obstacles to be aware of. The manuscript's authority would also increase if it addressed potential objections to the use of prediction markets. RESPONSE: There is now a discussion of the possibility of manipulation of prediction markets, and how this can undermine the confidence decision makers have in the information they produce, even when its accuracy is not compromised [L439-L449]. The paper only briefly touches on the use of prediction markets for policy making, planning, and risk disclosure, but it does not dive into the precise consequences or potential benefits of doing so. The manuscript's effect and relevance would increase if it included a more in-depth examination of how prediction markets might influence policy decisions, strengthen planning tactics, and boost risk communication. RESPONSE: In the discussion we now talk about how the output of prediction markets might be useful to policy makers and useful for communicating information about climate risks [L408-L420]. Yours sincerely Mark Roulston Attachments Attachment Submitted filename: Response to Reviewers.pdf https://doi.org/10.1371/journal.pone.0309164.r002
7 Aug 2024 Decision Letter - Robin Haunschild, Editor Joint-outcome Prediction Markets for Climate Risks PONE-D-23-08410R1 Dear Dr. Roulston, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. 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Has the statistical analysis been performed appropriately and rigorously? Reviewer #3: Yes Reviewer #4: Yes Reviewer #5: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #3: No Reviewer #4: Yes Reviewer #5: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #3: Yes Reviewer #4: Yes Reviewer #5: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #3: The sample time of the articles is too old, the contribution is very limited, and the comments of the reviewers are not completed. Reviewer #4: After the revisions made suggested by other reviewers, the paper can be acepted. The paper is well structured. Reviewer #5: (No Response) ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #3: No Reviewer #4: Yes: Hélder Silva Lopes Reviewer #5: No ******** https://doi.org/10.1371/journal.pone.0309164.r003
Formally Accepted
12 Aug 2024 Acceptance Letter - Robin Haunschild, Editor PONE-D-23-08410R1 PLOS ONE Dear Dr. Roulston, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Robin Haunschild Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0309164.r004

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