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Dataset on Sectoral Heterogeneity and Uncertainty in GVCs: US, China, and Europe

Version 1.0

Zamojska, Anna, 2026, "Dataset on Sectoral Heterogeneity and Uncertainty in GVCs: US, China, and Europe", https://doi.org/10.18150/JS78JA, RepOD, V1

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Description

The dataset was prepared for a study on international trade, comparative advantages, and the impact of global tensions and uncertainty on selected technology sectors. The data have a panel structure and cover 31 countries from 1998–2024, for a total of 837 country-year observations. The file consists of two worksheets: “data”, containing the raw empirical data, and “notes”, which describes the meaning of the individual variables.

The data cover export and import values in eight sectors identified by the codes 751, 752, 759, 761, 762, 763, 764, and 776, expressed at current prices in thousands of US dollars. In addition, the dataset includes Revealed Comparative Advantage (RCA) indicators for each analysed sector, as well as three variables describing the uncertainty environment: the Global Supply Chain Pressure Index, the Trade Policy Uncertainty Index, and the US–China Tension Index.

The study aims to assess how changes in global supply chains, trade policy uncertainty, and tensions between the United States and China relate to countries' export and import levels and comparative advantages in the analysed sectors. The study combines trade data with measures of uncertainty to identify changes in countries’ competitive positions and their potential sensitivity to disruptions in the global economy.

(2026-09-28)
Subject
Social Sciences
Keyword

Technology trade, Uncertainty shocks, Global value chains, Trade-policy uncertainty, Geopolitical risk, Panel VARX

Related Publication

Technology trade under uncertainty: sectoral heterogeneity across the US, China, and Europe doi: 10.1007/s10644-026-10075-9

CC BY - Creative Commons Attribution 4.0 CC BY - Creative Commons Attribution 4.0

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Journal Paper 18 data raw data.xlsx
MS Excel (XLSX) - 174.9 KB - Sep 30, 2026 - 1 Download
MD5: 877be20a8ac24782852d00270f5b8acb
License: CC BY - Creative Commons Attribution 4.0
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Journal Paper 18 data notes.xlsx
MS Excel (XLSX) - 9.6 KB - Sep 30, 2026 - 0 Downloads
MD5: 9a0cf1d8ef2f647eaf5105f16f625800
License: CC BY - Creative Commons Attribution 4.0
Description of Columns in the Raw Data File
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