Previous analyses of small samples of mining projects have found that feasibility studies tend to well under-estimate the actual capital costs of the project. Our review of 63 mining and smelting projects completed over 4 decades confirms that as-built capital costs are, on average, 25 percent higher than as estimated at the bankable feasibility study stage. There appears to be little attenuation over time of this bias in capital cost estimation, at first appearing to reflect an absence of learning on the part of the consulting engineer. We instead argue that this persistence of bias is intentional, driven by a scarcity of project financing and the need to inflate the project economics in a bid to secure financing. Around this intentional bias is a considerable amount of scatter. Roughly half of all projects' as-built capita costs fall outside of the expected ±15 percent of the feasibility study capital cost estimate, even after allowing for intentional estimation bias. Cost overruns of 100 percent or more happen in roughly 1 out of 13 projects. The data reveal that a shifted lognormal probability distribution should be used when modeling mining project capital costs in a Monte Carlo analysis.
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