Quality Upgrading under Competitive Exposure: Evidence from Korea’s Automotive-Parts Trade

This dataset supports the study “Quality Upgrading under Competitive Exposure: Evidence from Korea’s Automotive-Parts Trade.” It contains processed annual data for 213 HS6 automotive-parts products in Korea’s bilateral trade with China, the United States, and Japan over 2000–2019. The products are classified into 76 electrical and electronics parts and 137 general parts. The workbook includes the fixed HS6 analytical product list, HS–IPC concordance information, and annual trade-structure indicators for each partner and product group. The indicators include the export similarity index (ESI), revealed comparative advantage (RCA), trade specialization index (TSI), intra-industry trade (IIT), horizontal and vertical intra-industry trade (HIIT and VIIT), and high- and low-quality vertical intra-industry trade (HQVIIT and LQVIIT). Unit-value-based classifications are calculated using export and import values and netweight, subject to the data-quality and classification rules described in the accompanying manuscript and Online Supplementary Material. The dataset also reports Korea- and partner-side patent counts linked to the automotive-parts classifications and a two-year-lagged patenting gap, calculated as ln(1 + partner patents at t−2) − ln(1 + Korea patents at t−2). Period-average patenting gaps and the corresponding valid observation counts are provided for transparency. The workbook contains the following sheets: HS Code, IPC-HS Code, EE, General, Dictionary, and Patent Gap. The Dictionary sheet explains the principal variables, classifications, scales, and interpretation rules. The data are intended to support descriptive analysis of competitive exposure, trade participation, quality-differentiated vertical specialization, and bilateral trade outcomes. ESI is interpreted as a proxy for potential competitive exposure rather than realized competition, unit values are treated as trade-based quality proxies, and the patenting gap is used only as supplementary contextual evidence. The dataset does not include annual Markov state assignments, SPI series, transition-matrix scripts, figure-generation code, or the original raw data obtained from UN Comtrade and the USPTO.