Journal of International Economics Research
Journal DOI
PendingISSN (Online)
Volume 2 , Issue 1 , PP: 27-36, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Safarov Baxtiyor 1 *
Doi: https://doi.org/10.54216/JIER.020105
Given its rapid expansion and growing policy salience among global digital markets, we know considerably less about how these digital economy and e-commerce dynamics change during a regime of cross-border data flows. While previous research has emphasized the role of digital trade openness in shaping patterns of online market participation, limited attention has been given to how regulatory frictions in cross-border data transmission may be an underlying constraint to improve digital market integration. The aim of the study was to identify causal mechanisms for participation of different types of firms in e-commerce activities, their entry, use, intensity, and the resulting trade outcomes. In this paper, the analysis examines the determinants of cross-border digital engagement at the firm level, in combination with a comparative evaluation of digitally active and non-active enterprises. The empirical strategy of the study was structured by analyzing the selection bias of firms into e-commerce adoption, followed by some counterfactual estimations of the matched samples to produce unbiased treatment effects. An overview is provided of the econometric framework and identification strategy used for the estimation in the presence of non-random participation. The key variables with statistically significant effects in the matched estimations were digital connectivity and regulatory data openness, indicating that the likelihood of e-commerce participation would be easily amplified and sustained in a liberal and predictable cross-border data environment. Some evidence of the more heterogeneous and asymmetric relationships between firm characteristics and e-commerce outcomes is provided, and persistence of digital participation in the post-entry period is confirmed (average treatment effect; t = 2.87). Future research should include longitudinal datasets to test the stability of cross-border data flow effects for different stages of firm digitalization. These findings suggest that this line of empirical evidence provides credible guidance to policymakers in economies that require balanced digital trade regulation.
Cross-border data flows , Digital trade regulation , Firm-level e-commerce participation , Regulatory data openness , Propensity score matching , Selection bias and treatment effects , Digital market integration
Pepper, R. (2016). Cross-border data flows, digital innovation, and the global digital economy. World Economic Forum. https://www3.weforum.org/docs/GITR2016/WEF_GITR_Chapter1.2_2016.pdf
Liu, Q., Zhang, Y., Chen, J., & Li, X. (2021). Analyzing the effects of cross-border e-commerce on the development of green logistics. Complexity, 2021, Article 9916304. https://doi.org/10.1155/2021/9916304
Potluri, S. R. (2020). Effects of data localization on digital trade: An agent-based modeling approach. Telecommunications Policy, 44(10), 102028. https://doi.org/10.1016/j.telpol.2020.102028
Basile, F. (2021). Digital trade and cross-border data flows: A comparison between the EU and US approaches (Master’s thesis, Luiss University). https://tesi.luiss.it/36556/1/253061_BASILE_FLAVIA.pdf
Manyika, J., Lund, S., Bughin, J., Woetzel, J., Stamenov, K., & Dhingra, D. (2015). Cross-border data flows enable growth in all industries. Information Technology and Innovation Foundation. https://www2.itif.org/2015-cross-border-data-flows.pdf
Mukhopadhyay, A. (2020). E-commerce trade and data localization: A developing country perspective. Institute of Online Research Journal, HSE University. https://iorj.hse.ru/data/2020/12/08/1356185203/6%20Mukhopadhyay.pdf
Organisation for Economic Co-operation and Development. (2022). Cross-border data flows. OECD Publishing. https://www.oecd.org/content/dam/oecd/en/publications/reports/2022/10/cross-border-data-flows_91466bb8/5031dd97-en.pdf
Liu, Y., Li, Y., Tao, F., & Wang, Y. (2019). Cross-border e-commerce firms as supply chain integrators: The management of three flows. International Journal of Production Economics, 211, 28–42. https://doi.org/10.1016/j.ijpe.2019.01.024
Institute of International Finance. (2020). Data localization: Costs, tradeoffs, and impacts across the economy. https://www.iif.com/portals/0/Files/content/Innovation/12_22_2020_data_localization.pdf
Gomez-Herrera, E., Martens, B., & Turlea, G. (2014). The drivers and impediments for cross-border e-commerce in the EU. European Commission Joint Research Centre. https://publications.jrc.ec.europa.eu/repository/bitstream/JRC78588/lfna25778enn.pdf
Nguyen, D., & Paczos, M. (2020). Measuring the economic value of data and cross-border data flows: A business perspective (OECD Digital Economy Papers No. 297). OECD Publishing.
Han, L., Ma, Y., & Addo, P. C. (2023). Cross-border e-commerce and digital trade facilitation in Africa. Journal of Sustainability.
Chander, A., & Lê, U. P. (2015). Data nationalism. Emory Law Journal, 64(3), 677–739.
Organisation for Economic Co-operation and Development. (2019). Trade and cross-border data flows. OECD Publishing. https://www.oecd.org/content/dam/oecd/en/publications/reports/2019/06/trade-and-cross-border-data-flows_84946670/bcc99984-en.pdf
Liu, Q., Zhang, Y., Chen, J., & Li, X. (2022). The development relationship between cross-border e-commerce and IoT technology. Wireless Communications and Mobile Computing, 2022, Article 9482480. https://doi.org/10.1155/2022/9482480
