Title: Technical note detailing the background, data and parameters used to model the upgraded UK-Republic of Korea Free Trade Agreement in an NQTM

This technical note presents the background, data sources, and parameter choices underpinning the modelling of the upgraded United Kingdom–Republic of Korea Free Trade Agreement (UK–RoK FTA) within a Newtonian Quantitative Trade Modelling (NQTM) framework. The aim is to provide a transparent, reproducible account of the modelling process, including the rationale for the data selected, the structural assumptions embedded in the model, and the interpretation of the resulting outputs.

1. Context and objectives
– Rationale for upgrading the UK–RoK FTA: Since the UK’s departure from the European Union, trade policy has sought to deepen economic integration with major trading partners. The upgraded FTA proposal aims to enhance market access, harmonise rules of origin, and streamline regulatory procedures to strengthen bilateral trade flows, investment, and supply chains.
– Modelling objective: To quantify potential welfare effects, sectoral trade adjustments, and broader macroeconomic implications of the upgraded FTA under baseline and alternative policy scenarios, using a robust NQTM framework that can accommodate non-tradi tional tariff structures, rules of origin complexities, and potential dynamic effects.

2. Modelling framework: NQTM overview
– Core structure: The NQTM represents bilateral trade with a multi-sector, general-equilibrium encoder that captures price-taking behaviour, production technologies, and consumer preferences. The model typically features:
– Armington-style product differentiation by country of origin
– CES (constant elasticity of substitution) production functions
– Armington demand for tradables and a representative consumer utility function
– Trade costs comprising MFN tariffs, applied preferences, and iceberg transport costs
– Upgraded FTA integration: The model incorporates tariff liberalisation schedules, revised rules of origin, potential regulatory convergence, and any sector-specific trade facilitation measures included in the upgrade package. It also allows scenario testing of partial liberalisation, phased implementation, or jurisdiction-specific exemptions.

3. Data sources and data preparation
– Tariff and preferences data:
– MFN tariffs prior to the upgrade, applied preferential tariffs under the upgraded agreement, and any staged tariff concessions.
– Rules of origin: documentary requirements, regional value content thresholds, and accumulation rules integrated into the upgraded framework.
– Trade and production data:
– Sector-by-sector trade volumes and values between the UK and RoK, at the most disaggregated level available (ideally HS6 or SITC-based classifications).
– Production functions and input-output linkages, drawn from national accounts, industry surveys, and input-output tables to reflect input shares and technology coefficients.
– Elasticities and behavioural parameters:
– Armington elasticity estimates for imports by sector and origin.
– Price and income elasticities governing demand responses.
– Substitution elasticities across sectors where data exist, or calibrated values informed by literature and prior calibrations.
– Macroeconomic controls:
– Baseline GDP, exchange rate paths, and other macro-shocks to capture interaction effects and to facilitate sensitivity analyses.
– Data harmonisation:
– All data are harmonised to a common year (or chained across years if a dynamic dimension is included) and aligned to the model’s sectoral taxonomy. In cases of missing data, transparent imputation or calibration targets are documented, with sensitivity checks performed.

4. Key assumptions and parameter choices
– Tariff treatment:
– Automatic application of tariff concessions where the upgrade includes tariff liberalisation, with full implementation assumed in the central scenario unless a phased approach is specified.
– Rules of origin effects captured through a binary or continuous accessibility parameter reflecting the ease of preferential access for intermediate inputs and final goods.
– Demand and substitution:
– Armington assumption: imports are imperfect substitutes across origins; elasticities are sectorally differentiated where possible.
– Domestic vs. imported goods: relative price changes drive substitution, with calibration to observed import shares.
– Production technologies:
– Constant returns to scale or diminishing returns as dictated by the sectoral specification; factor endowments adjusted for potential productivity gains or investment flows resulting from the upgrade.
– Dynamic considerations (if included):
– Short- to medium-term horizons with potential transition dynamics, investment responses, and lag structures for trade and productivity effects.
– Policy scoping:
– The upgrade’s scope is treated with clarity: sectors covered, exclusions, and any staged liberalisation timelines. Regulatory or non-tariff measures (NTMs) may be modelled as adjustments to transaction costs or entry barriers where appropriate.

5. Calibration, validation and robustness
– Calibration targets:
– The model is calibrated to reproduce the observed baseline trade flows and sectoral patterns prior to the upgrade, ensuring that current trade emissions and supply responses align with empirical data.
– Validation:
– Model outputs are validated against historical episodes of tariff liberalisation in comparable FTAs, where feasible, to check for plausible magnitudes of welfare gains and trade shifts.
– Sensitivity analysis:
– Key parameters—tariff liberalisation levels, rules of origin sensitivity, Armington elasticities, and the speed of implementation—are varied to test the stability of results.
– Scenario analysis includes optimised, partial, and no-access baselines to illustrate a range of potential outcomes.

6. Outputs and interpretation
– Welfare effects:
– Consumer surplus and producer welfare changes across sectors, measured in percentage terms and absolute values, with attention to distributional impacts.
– Trade flows:
– Changes in bilateral trade volumes and imports by sector, highlighting substitution or diversification effects.
– Macroeconomic indicators:
– GDP-level effects (levels and percent deviations), terms of trade adjustments, and potential investment flows linked to the upgraded FTA.
– Sectoral insights:
– Identification of sectors with the largest gains or losses, informing policy prioritisation or complementary measures.

7. Limitations and caveats
– Assumptions about tariff implementation timetables, RoO complexity, and NTMs are subject to data quality and availability constraints. Real-world frictions such as administrative capacity, customs procedures, and regulatory alignment may exert additional effects not fully captured in the model.
– The NQTM abstracts certain dynamic feedbacks and strategic tariff setting by trading partners; results should be interpreted as indicative, scenario-based projections rather than precise forecasts.
– Uncertainty in elasticities and sectoral production technologies remains a central source of model risk; robustness checks are essential for credible inference.

8. Reproducibility and transparency
– Model code, data sources, and parameter specifications are documented comprehensively to enable replication and scrutiny. Where possible, datasets used are cited with versioning details and access instructions.
– Any deviations from standard defaults (e.g., alternative elasticity values, modified sector classifications) are explicitly justified and tested through sensitivity analyses.

9. Conclusions
– The upgraded UK–RoK FTA modelling within the NQTM framework provides a structured, transparent basis for evaluating potential welfare improvements, trade realignments, and macroeconomic implications. By detailing the data inputs and parameter choices, the analysis aims to support informed policy discussion and evidence-based decision-making, while clearly communicating the uncertainties and limitations inherent in complex trade modelling.

If you would like, I can tailor this draft to reflect specific sectors of interest, incorporate a hypothetical scenario set (e.g., phased tariff liberalisation over five years), or adapt the terminology and structure to align with your organisation’s reporting standards.

August 7, 2026 at 12:00PM
研究：用于升级版英国-韩国自由贸易协定建模论文的新定量贸易模型（NQTM）
https://www.gov.uk/government/publications/new-quantitative-trade-model-nqtm-used-in-the-upgraded-uk-republic-of-korea-fta-modelling-paper
技术说明，详述在NQTM中用于建模升级版英国-韩国自由贸易协定的背景、数据与参数。

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