Stranded Value and Capex-at-Risk in India's Oil Sector: Replication Data and Code

A 2026 replication package for a study assessing transition risks in India's oil sector to 2050. It contains Python valuation engines, public input data on refinery capacity and reserves, and computed results for stranded value and capital expenditure at risk. The package was authored by Adesh Mishra and hosted on Harvard Dataverse.

Use Cases

• Reproduce financial risk assessments for oil refining assets based on the provided valuation engines and demand paths.
• Conduct sensitivity analysis on transition risk metrics using the included one-at-a-time sensitivity sweep tools.
• Analyze the announced refinery-expansion pipeline in India against modeled demand scenarios.
• Validate aggregate financial parameters derived from company reports against public disclosures.

Strengths

• Includes three distinct Python valuation engines for different risk calculations.
• Contains all public input data from sources like PPAC and DGH.
• Provides computed results and publication-ready figures in multiple formats (PDF, EPS, PNG).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Some proprietary data sources, like the CMIE Prowess panel, are withheld and required for full regeneration.

Provenance

Source

Harvard Dataverse

Collection Method

Compiled from public sources (PPAC, DGH) and derived analysis for a research paper.

Time Range

Projections to 2050

Freshness

Last updated 2026-07-06 18:31:33; freshness should be verified.

Geography

India