Total Factor Productivity Across the Integrated Assessment Model Landscape: Cross-Country Panel Data and Replication Code
Description
This dataset and companion script accompany the manuscript "Total Factor Productivity Across the Integrated Assessment Model Landscape: A Comparative Framework and a CO-STIRPAT-Type Complementary Module" (Ick Jin, 2026). It reproduces the three worked examples in Section 3.3.5 (Tables 3-5): (A) EPS (Korea), Pattern (a) - Exogenous-Driver Injection; (B) DICE/RICE, Pattern (b) - Calibration-Target Adjustment, including the accompanying sensitivity analysis; and (C) GCAM, Pattern (c) - Diagnostic Overlay. Files: - analysis_code.py: a single Python script that loads analysis_data.xlsx and reproduces Tables 3, 4 (with sensitivity analysis), and 5 exactly as published. - analysis_data.xlsx: the curated subset of underlying data actually used by the script (EPS-Korea baseline GDP and OECD growth forecast; GCAM national-accounts fields for five regions; GCAM node-gamma/rho calibration parameters for all 32 regions; and the CO-STIRPAT interaction coefficients from Table 6), with a ReadMe sheet documenting the provenance of each sheet. Dependencies: Python 3 with openpyxl (standard library otherwise). Corresponding author: Ick Jin, Chief Economist, NEXT group. Email: realwing@nextgroup.or.kr; rwjin@naver.com. ORCID: https://orcid.org/0000-0001-9671-1488. The views expressed are the author's own and not those of any affiliated institution.