Linking Trade Data from Different National Statistical Offices Through a Private Set Intersection

National Statistical Offices (NSOs) collect extensive data on the international activities of firms within their borders. However, they typically lack information about the foreign partners with whom these firms trade. Linking import data from one NSO to corresponding export data from a partner NSO could significantly enhance statistics on firms’ international operations. While technically feasible, such linkage is legally constrained by strict privacy laws. Private set intersection (PSI) protocols may help address privacy concerns but require unique identifiers to avoid linkage errors. To overcome this limitation, we propose a PSI protocol with three innovations. First, we estimate the rates of linkage error by modeling the number of links from a given record. Second, we adjust an estimated population mean according to the estimated linkage accuracy. Lastly, our adjustment explicitly accounts for this accuracy without assuming a particular relationship among the target variables.

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Publication Details

Journal
Journal of Official Statistics
Published
2025-05-02
DOI
https://doi.org/10.1177/0282423x251329407
Citations
2
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
4.21
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article

Linking Trade Data from Different National Statistical Offices Through a Private Set Intersection

Abel Dasylva, Fabrizio De Fausti, Massimo De Cubellis, Loe Franssen
2 citations
Journal of Official Statistics
Data Quality and Management
4.21
article

Linking Trade Data from Different National Statistical Offices Through a Private Set Intersection

Abel Dasylva, Fabrizio De Fausti, Massimo De Cubellis, Loe Franssen
article en
2 citations

Abstract

National Statistical Offices (NSOs) collect extensive data on the international activities of firms within their borders. However, they typically lack information about the foreign partners with whom these firms trade. Linking import data from one NSO to corresponding export data from a partner NSO could significantly enhance statistics on firms’ international operations. While technically feasible, such linkage is legally constrained by strict privacy laws. Private set intersection (PSI) protocols may help address privacy concerns but require unique identifiers to avoid linkage errors. To overcome this limitation, we propose a PSI protocol with three innovations. First, we estimate the rates of linkage error by modeling the number of links from a given record. Second, we adjust an estimated population mean according to the estimated linkage accuracy. Lastly, our adjustment explicitly accounts for this accuracy without assuming a particular relationship among the target variables.

Journal of Official StatisticsVol. 41(2)
Statistics Canada (CA), Centraal Bureau voor de Statistiek (NL), Istituto Nazionale di Statistica (IT)
Openalex Percentile: Top 7%
Data Quality and Management
4.21
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