Empirical Estimates of the Direct Rebound Effect: A Review
Abstract
This paper reviews the empirical evidence on the direct rebound effect for personal automotive transport, space heating, and other energy services in OECD countries. Direct rebound effects are generally found to be in the range of 10-30% for these services, with evidence suggesting they may be declining over time in some cases.
★ Curator Summary
Sorrell's meta-review is the most rigorous compilation of rebound effect magnitudes we have. The finding that direct rebound is typically 10-30% gives us an empirical anchor for the Service Demand Rebound Model. Combined with indirect rebound (~11%) and potential economy-wide effects, total rebound of 30-70% becomes a defensible range. I use Sorrell's three-tier taxonomy (direct, indirect, economy-wide) directly in the SDRM framework.
Why It Matters
This paper provides the quantitative basis for telling executives: 'Your 40% containment rate will deliver 25-35% actual savings, not 40%.' The rebound formula — Actual Savings = Projected Savings x (1 - R) — where R is the rebound coefficient, lets you build realistic savings projections. The distinction between short-run and long-run rebound is critical for multi-year business cases.
Caveats
The evidence is from energy economics, not service operations. Rebound magnitudes in service demand may differ. The review focuses on OECD countries. Some studies have methodological weaknesses that Sorrell acknowledges. The range (10-30%) is wide enough that specific applications need context-specific calibration.
Discussion
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