{"title":"Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries","authors":"Joachim Wagner","doi":"10.1007/s11079-024-09777-2","DOIUrl":null,"url":null,"abstract":"<p>The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.</p>","PeriodicalId":46980,"journal":{"name":"Open Economies Review","volume":"25 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Economies Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s11079-024-09777-2","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.
期刊介绍:
The topics covered in Open Economies Review include, but are not limited to, models and applications of (1) trade flows, (2) commercial policy, (3) adjustment mechanism to external imbalances, (4) exchange rate movements, (5) alternative monetary regimes, (6) real and financial integration, (7) monetary union, (8) economic development and (9) external debt. Open Economies Review welcomes original manuscripts, both theoretical and empirical, dealing with international economic issues or national economic issues that have transnational relevance. Furthermore, Open Economies Review solicits contributions bearing on specific events on important branches of the literature. Open Economies Review is open to any and all contributions, without preferences for any particular viewpoint or school of thought. Open Economies Review encourages interdisciplinary communication and interaction among researchers in the vast area of international and transnational economics. Authors will be expected to meet the scientific standards prevailing in their respective fields, and empirical findings must be reproducible. Regardless of degree of complexity and specificity, authors are expected to write an introduction, setting forth the nature of their research and the significance of their findings, in a manner accessible to researchers in other disciplines. Officially cited as: Open Econ Rev