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利用预测市场预测移民流动情况。

Forecasting migration movements using prediction markets.

作者信息

Morgenstern Sandra, Strijbis Oliver

机构信息

Mannheim Centre for European Social Research (MZES), University of Mannheim, Mannheim, Germany.

Franklin University Switzerland, Sorengo, Switzerland.

出版信息

Comp Migr Stud. 2024;12(1):45. doi: 10.1186/s40878-024-00404-0. Epub 2024 Oct 9.

DOI:10.1186/s40878-024-00404-0
PMID:39398899
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11464559/
Abstract

UNLABELLED

Migration forecasts are crucial for proactive immigration and integration management. While the demand for accurate migration forecasts continues to grow, the current state of migration forecasting is still unsatisfactory, because they tend to lack precision. We introduce an alternative method to forecast migration movements: prediction markets. While prediction markets are mainly unknown in migration studies, they are established in the political economy of forecasting election outcomes. For its application to a complex phenomenon in a more constrained information environment such as migration movements, we argue that prediction markets allow to balance complementarities of current qualitative and quantitative approaches if they provide solutions to avoid thin trading and integrate expert knowledge into the market. We apply the prediction market to forecast immigration in four West European countries in 2020 and find encouraging results. We discuss the strengths and limitations of prediction markets to migration forecasting, including ethical considerations, and guide its future application.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40878-024-00404-0.

摘要

未标注

移民预测对于积极的移民和融合管理至关重要。虽然对准确移民预测的需求持续增长,但目前的移民预测状况仍不尽人意,因为它们往往缺乏精确性。我们引入一种预测移民流动的替代方法:预测市场。虽然预测市场在移民研究中主要不为人知,但它们在预测选举结果的政治经济学中已确立。对于其在诸如移民流动等更受限信息环境中的复杂现象的应用,我们认为,如果预测市场能提供避免交易清淡的解决方案并将专家知识融入市场,那么它们能够平衡当前定性和定量方法的互补性。我们应用预测市场来预测2020年四个西欧国家的移民情况,并取得了令人鼓舞的结果。我们讨论了预测市场在移民预测方面的优势和局限性,包括伦理考量,并为其未来应用提供指导。

补充信息

在线版本包含可在10.1186/s40878-024-00404-0获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/ba03784b3c7f/40878_2024_404_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/cd78f997613c/40878_2024_404_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/98862aaecef3/40878_2024_404_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/98dfc9c88a1b/40878_2024_404_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/ba03784b3c7f/40878_2024_404_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/cd78f997613c/40878_2024_404_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/98862aaecef3/40878_2024_404_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/98dfc9c88a1b/40878_2024_404_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d48a/11464559/ba03784b3c7f/40878_2024_404_Fig4_HTML.jpg

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