United Nations General Assembly Ideal Points

This dataset contains ideal point estimates based on voting behavior in the United Nations General Assembly. This is the first version where the ideal point estimates are based on years rather than UNGA sessions. The reasons for this are that researchers in practice virtually always use years as the basis of analysis and that UNGA sessions increasingly spill over into the following year and are held in special emergency sessions on issues such as the Gaza and Ukraine. There are two types of ideal point estimates: • idealpointfp: ideal point estimates based only on votes on the final passage of resolutions (including failed votes). These are now available from 1946-2024 in IdealPointsJuly2025.tab. These estimates are updated most frequently as the raw data can readily be found online. • Idealpointall: ideal point estimates based on all votes, including votes on paragraphs, motions, and amendments. These votes are based on more data and thus should be more precise. One word of caution is that in some years this means that there are very large numbers of votes on a specific issue, such as the war in Gaza. The correlation between these ideal points is .9846 but there could of course still be some important differences. The data also includes idealpointlegacy, which is based on sessions (all votes). The correlation with idealpointall is .9877. Aside from the 2024 final passage votes, the raw UN voting data are from the UNGA-DM Database: https://unvotes.unige.ch/ Citation: Fjelstul, Joshua, Simon Hug, and Christopher Kilby. \"Decision-making in the United Nations General Assembly: A comprehensive database of resolution-related decisions.\" The Review of International Organizations (2025): 1-18. The ideal point estimates are based on the methodology described in: Citation: Bailey, Michael A., Anton Strezhnev, and Erik Voeten. 2017. Estimating dynamic state preferences from united nations voting data. Journal of Conflict Resolution 61 (2): 430-56.

本数据集收录基于联合国大会（United Nations General Assembly）投票行为的理想点估计值。本版本为首个以年份而非联合国大会届会作为基准的理想点估计数据集。

作出此调整的原因在于，实际研究中几乎均以年份作为分析基准；同时联合国大会届会日益延伸至次年，且会就加沙、乌克兰等议题召开特别紧急会议。

本数据集包含两类理想点估计值：
• idealpointfp：仅基于决议最终表决（含未获通过的表决）投票结果生成的理想点估计值。文件IdealPointsJuly2025.tab收录了1946年至2024年的此类估计值，由于原始数据可便捷在线获取，因此更新频率较高。
• Idealpointall：基于所有投票（包括段落表决、动议表决与修正案表决）生成的理想点估计值。此类估计依托更丰富的数据，因此精度更高。需注意的是，在部分年份中，特定议题（如加沙战争）的投票数量会大幅攀升。

两类理想点估计值的相关系数为0.9846，但二者仍可能存在部分具有实际意义的差异。

数据集还收录了基于届会（仅统计全量投票）生成的idealpointlegacy，其与Idealpointall的相关系数为0.9877。

除2024年的最终表决投票数据外，本数据集的联合国大会原始投票数据均来自UNGA-DM数据库：https://unvotes.unige.ch/

引用文献1：Fjelstul, Joshua, Simon Hug, and Christopher Kilby. "Decision-making in the United Nations General Assembly: A comprehensive database of resolution-related decisions." 《国际组织评论》(The Review of International Organizations) (2025): 1-18.

本数据集的理想点估计方法基于以下文献：
引用文献2：Bailey, Michael A., Anton Strezhnev, and Erik Voeten. 2017. "Estimating dynamic state preferences from united nations voting data." 《冲突解决杂志》(Journal of Conflict Resolution) 61(2): 430-56.