{"title":"A probabilistic method for reconstructing the Foreign Direct Investments network in search of ultimate host economies","authors":"Nadia Accoto, Valerio Astuti, Costanza Catalano","doi":"10.1007/s11634-023-00571-5","DOIUrl":null,"url":null,"abstract":"<p>The Ultimate Host Economies (UHEs) of a given country are defined as the ultimate destinations of Foreign Direct Investment (FDI) originating in that country. Bilateral FDI statistics struggle to identify them due to the non-negligible presence of conduit jurisdictions, which provide attractive intermediate destinations for pass-through investments due to favorable tax regimes. At the same time, determining UHEs is crucial for understanding the actual paths followed by FDI among increasingly interdependent economies. In this paper, we first reconstruct the global FDI network through mirroring and clustering techniques, starting from data collected by the International Monetary Fund. Then we provide a method for computing an (approximate) distribution of the UHEs of a country by using a probabilistic approach to this network, based on Markov chains. More specifically, we analyze the Italian case.</p>","PeriodicalId":49270,"journal":{"name":"Advances in Data Analysis and Classification","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Data Analysis and Classification","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11634-023-00571-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
The Ultimate Host Economies (UHEs) of a given country are defined as the ultimate destinations of Foreign Direct Investment (FDI) originating in that country. Bilateral FDI statistics struggle to identify them due to the non-negligible presence of conduit jurisdictions, which provide attractive intermediate destinations for pass-through investments due to favorable tax regimes. At the same time, determining UHEs is crucial for understanding the actual paths followed by FDI among increasingly interdependent economies. In this paper, we first reconstruct the global FDI network through mirroring and clustering techniques, starting from data collected by the International Monetary Fund. Then we provide a method for computing an (approximate) distribution of the UHEs of a country by using a probabilistic approach to this network, based on Markov chains. More specifically, we analyze the Italian case.
期刊介绍：
The international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from many types of data. It publishes articles on such topics as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; methods for the extraction of knowledge from data, and applications of advanced methods in specific domains of practice. Articles illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. The journal also publishes survey papers that outline, and illuminate the basic ideas and techniques of special approaches.
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