{"title":"人工智能对提前退休决策的影响","authors":"Pablo Casas, Concepción Román","doi":"10.1007/s10663-024-09613-3","DOIUrl":null,"url":null,"abstract":"<p>This paper examines the impact of Artificial Intelligence (AI) on early retirement (ER) decisions in Europe. For the analysis, we utilize microdata from the Survey of Health, Ageing and Retirement in Europe, along with occupation-level data on AI advances and AI exposure. Initially, we investigate the influence of AI advances and AI exposure separately, finding in both instances a significant reduction in ER likelihood, though this only applies to workers with higher education. Subsequently, we explore the interaction between AI advances and AI exposure concerning ER probability. This interaction proves critical in determining AI’s impact on ER transitions. Specifically, we observe a significant reduction in ER probabilities for workers whose occupations exhibit high levels of AI advances and high expectations for further implementation of this technology in the future. Finally, we jointly analyse the interaction between AI advances, AI exposure, and education level. This analysis highlights that workers’ ER probabilities may either increase or decrease in response to the AI revolution, depending on their education level and the characteristics of their occupations in terms of AI advances and AI exposure.</p>","PeriodicalId":46526,"journal":{"name":"Empirica","volume":"9 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of artificial intelligence in the early retirement decision\",\"authors\":\"Pablo Casas, Concepción Román\",\"doi\":\"10.1007/s10663-024-09613-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper examines the impact of Artificial Intelligence (AI) on early retirement (ER) decisions in Europe. For the analysis, we utilize microdata from the Survey of Health, Ageing and Retirement in Europe, along with occupation-level data on AI advances and AI exposure. Initially, we investigate the influence of AI advances and AI exposure separately, finding in both instances a significant reduction in ER likelihood, though this only applies to workers with higher education. Subsequently, we explore the interaction between AI advances and AI exposure concerning ER probability. This interaction proves critical in determining AI’s impact on ER transitions. Specifically, we observe a significant reduction in ER probabilities for workers whose occupations exhibit high levels of AI advances and high expectations for further implementation of this technology in the future. Finally, we jointly analyse the interaction between AI advances, AI exposure, and education level. This analysis highlights that workers’ ER probabilities may either increase or decrease in response to the AI revolution, depending on their education level and the characteristics of their occupations in terms of AI advances and AI exposure.</p>\",\"PeriodicalId\":46526,\"journal\":{\"name\":\"Empirica\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Empirica\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1007/s10663-024-09613-3\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Empirica","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s10663-024-09613-3","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
The impact of artificial intelligence in the early retirement decision
This paper examines the impact of Artificial Intelligence (AI) on early retirement (ER) decisions in Europe. For the analysis, we utilize microdata from the Survey of Health, Ageing and Retirement in Europe, along with occupation-level data on AI advances and AI exposure. Initially, we investigate the influence of AI advances and AI exposure separately, finding in both instances a significant reduction in ER likelihood, though this only applies to workers with higher education. Subsequently, we explore the interaction between AI advances and AI exposure concerning ER probability. This interaction proves critical in determining AI’s impact on ER transitions. Specifically, we observe a significant reduction in ER probabilities for workers whose occupations exhibit high levels of AI advances and high expectations for further implementation of this technology in the future. Finally, we jointly analyse the interaction between AI advances, AI exposure, and education level. This analysis highlights that workers’ ER probabilities may either increase or decrease in response to the AI revolution, depending on their education level and the characteristics of their occupations in terms of AI advances and AI exposure.
期刊介绍:
Empirica is a peer-reviewed journal, which publishes original research of general interest to an international audience. Authors are invited to submit empirical papers in all areas of economics with a particular focus on European economies. Per January 2021, the editors also solicit descriptive papers on current or unexplored topics.
Founded in 1974, Empirica is the official journal of the Nationalökonomische Gesellschaft (Austrian Economic Association) and is published in cooperation with Austrian Institute of Economic Research (WIFO). The journal aims at a wide international audience and invites submissions from economists around the world.
Officially cited as: Empirica