Quality Upgrading under Competitive Exposure: Evidence from Korea’s Automotive-Parts Trade
Description
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.
Files
Steps to reproduce
The dataset was constructed from publicly available trade and patent data. Annual export and import values and netweight were obtained from UN Comtrade for Korea’s trade with China, the United States, and Japan over 2000–2019. The sample comprises a fixed list of 213 HS6 automotive-parts products: 76 electrical and electronics parts and 137 general parts. The list follows HS 2017 and is used as an analytical classification rather than a complete concordance across historical HS revisions. Trade records were organized by partner, year, HS6 product, and trade flow. Observations with valid trade values were retained for value-based indicators. Export and import unit values were calculated as trade value divided by netweight. Observations with missing, zero, or invalid netweight were excluded from the unit-value-based classification but retained for value-based indicators when possible. The processed indicators include ESI, RCA, TSI, IIT, HIIT, VIIT, HQVIIT, and LQVIIT. HIIT was defined when the export-to-import unit-value ratio was between 0.85 and 1.15, inclusive. HQVIIT was defined when the ratio exceeded 1.15, and LQVIIT when it was below 0.85. Patent application counts were linked to HS6 groups using an IPC–HS concordance from the Korean Intellectual Property Office. When an IPC class was linked to multiple HS codes, the count was assigned in full to each linked code. Patent indicators were aligned with trade data using a two-year lag. The annual patenting gap was calculated as ln(1 + partner patents at t−2) − ln(1 + Korea patents at t−2), and sub-period values are arithmetic means of available annual gaps. The workbook contains product classifications, HS–IPC linkages, annual processed indicators, variable definitions, and patenting-gap calculations. It supports verification of the reported trade and patent indicators but does not include raw data, Markov state assignments, SPI series, analysis code, transition-matrix code, or figure-generation code. Full replication therefore requires access to the original UN Comtrade and USPTO data and independent implementation of the procedures described in the manuscript and Online Supplementary Material.
Institutions
- Hyundai Mobis (South Korea)Seoul, Seoul