Replication package: Measuring circular-economy performance in a resource-based region — eco-efficiency, decoupling, and the uneven transition of Saudi Arabia's Eastern Province (2015–2023)

Data and code to reproduce all quantitative results of the paper "Measuring circular-economy performance in a resource-based region: eco-efficiency, decoupling, and the uneven transition of Saudi Arabia's Eastern Province (2015–2023)." A single Python script (replicate_all.py) regenerates every table and figure from the raw indicator file: the coefficient-of-variation weights (Table 4), the composite resource and environmental efficiency series (Table 5), the Tapio-type decoupling classification (Table 6), the grey relational grades (Figure 6), and the indicator and trajectory figures (Figures 3–6). The dataset covers the Eastern Province of Saudi Arabia over 2015–2023. Gross value added is aggregated to annual frequency from the quarterly provincial GVA database of Lopez-Ruiz & Hasanov (2025, KAPSARC). Resource indicators are drawn from GaStat, the Saudi Electricity Company, the Saline Water Conversion Corporation, and the DataSaudi platform. The seven environmental indicators are spatially downscaled from national totals (Ministry of Environment, Water and Agriculture) using a time-varying allocation key equal to the province's annual share of national industrial energy consumption; the procedure is documented in the README and in the paper. The package is deterministic: given the input file it reproduces the published values exactly. Requirements: Python 3.8+ with numpy, pandas, matplotlib, and openpyxl.