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                <datestamp>2026-07-21T10:12:14Z</datestamp>
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    <dc:creator>Baba, Umut</dc:creator>
    <dc:title>Ergunsu-Yang. Why the models missed the surge</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Replication package for &quot;Why the models missed the surge: decomposing the forecast failure in China&apos;s electric heavy-truck transition, 2021–2026.&quot; Contains all analysis code (Python, pinned environment), the assembled monthly data panels with registry-basis and provenance tags (new-energy and LNG heavy-truck registrations, chained diesel and LNG price series, IEA GEVO 2026 anchors), a consolidated parameter-extraction audit record for the forecasting baselines, a primary-source verification record with URLs, and reference outputs with SHA256 checksums. Running run_all.py reproduces every table and figure in the manuscript deterministically (fixed seed), including the calibrated fleet cost-sensitivity (lambda = 1.66 per CNY/km) and the 32-run Shapley decomposition of the 2025 forecast wedge. All underlying statistics are from public sources cited in the documentation.</dc:description>
    <dc:subject>Energy Economics</dc:subject>
    <dc:subject>Road Transportation</dc:subject>
    <dc:subject>Electric Vehicles</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/zt55zy2vzj.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/zt55zy2vzj.1</dc:identifier>
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