{ "docId": "019dd923-5e88-73ef-bd59-6131f37efc2b", "docSlug": "71b5b657f034a972", "documentTitle": "ey net zero centre carbon offset publication 20220530", "authorId": "MorganStanley", "authorName": "Grantham Research Institute", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "equity_research", "sourceTypeLabel": "Equity research", "presentationDate": null, "orientation": "portrait", "aspectRatio": 0.707, "pageNumber": 29, "pageCount": 45, "prevPage": 28, "nextPage": 30, "slideType": "appendix_methodology", "function": "diagnose", "density": "overcrowded", "nDataPoints": 0, "notes": "Page 27 of a research paper or consulting report; contains footnotes 14 and 15.", "elementsJson": [ "paragraph", "footnote" ], "metadataConfidence": 0.9, "imagePath": null, "slideHref": "/slides/019dd923-5e88-73ef-bd59-6131f37efc2b/29", "deckHref": "/decks/019dd923-5e88-73ef-bd59-6131f37efc2b", "deckJsonHref": "/decks/019dd923-5e88-73ef-bd59-6131f37efc2b.json", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd59-6131f37efc2b#slide-29", "components": [ { "bbox": { "h": 0.18, "w": 0.78, "x": 0.11, "y": 0.3 }, "kind": "paragraph", "text": "As we relax each monotonicity condition, we instead require projects to be matched in more dimensions, which naturally results in a drop in the size of the test statistics. Still, the CDM is more likely to produce greater BLIMP capacity and a greater quantity of BLIMP offsets than a lottery. We also see that most of the identification of BLIMPs in our original analysis comes from relative capacity. This is reassuring for two reasons. First, of the three variables that enter monotonically into the value function, capacity is the only one we have direct measurements of and do not estimate. Capacities are easily observed and therefore are at least risk of measurement error. The second reason is the strong empirical association between capacity and project costs. The strength of relationship provides an additional reason for confidence on the monotonicity condition on capacity.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "2ae16ef4-9d2e-47a3-bb7e-4b83509e1a28", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.06, "w": 0.78, "x": 0.11, "y": 0.09 }, "kind": "paragraph", "text": "Though we have ample reason to think that larger wind farms, with higher capacity factors, located closer to electrical substations, will be more profitable developments, it is still worth investigating which of these monotonicity conditions are most important for determining the result.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "7fcef3df-30cd-42b8-98ff-7cd05f863996", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.07, "w": 0.78, "x": 0.11, "y": 0.5 }, "kind": "paragraph", "text": "Incomplete Data: If our database is missing any wind farms, we will tend to under-count the number of BLIMPs. If a lot of these missing projects are smaller CDM projects, in more remote locations, and with lower capacity factors, then their inclusion might improve the CDM's observed pattern of decision-making compared to a lottery.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "81918c60-9cab-4a1d-91cb-abaf24f83a61", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.78, "x": 0.11, "y": 0.68 }, "kind": "paragraph", "text": "Row (17) of Table 1 shows the results under the assumption that all 200 of the unconfirmed wind farms were actually built. The total quantity of CERs allocated to BLIMPs would increase, but increases slightly more under a lottery, which makes the CDM look better by comparison. This arises because the 200 unconfirmed projects are, on average, smaller, more remote, and have lower capacity factors, which makes them better candidates for support. It is unfortunate, then,", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "88d5d6f9-0ddd-4b58-b0ec-69291256f0a6", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.13, "w": 0.78, "x": 0.11, "y": 0.16 }, "kind": "paragraph", "text": "In rows (14), (15), and (16) of Table 1, we relax each monotonicity condition in turn. We accomplish this by making sure that CDM wind farms are matched to non-CDM wind farms for each monotonicity condition and then use the remaining two conditions to determine whether the project is a BLIMP. In row (14) we match CDM wind farms to non-CDM wind farms within ±5% of their connection distance, dn, and then use their relative capacities and capacity factors to determine whether each project is a BLIMP or not. For rows (15) and (16), we match on capacity factor or capacity and rank-order projects based on the remaining two monotonicity conditions.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "dd8b79a8-533d-4b82-b2eb-e98a54bb5382", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.78, "x": 0.11, "y": 0.58 }, "kind": "paragraph", "text": "The CDM pipeline includes nearly 200 Indian wind farms that were scheduled to start delivering electricity by 2013, but which we were unable to match to anything in our database. It is likely that these unconfirmed projects were never completed, in which case our earlier analysis stands without modification. We explore the consequence of including them, however, just in case they were built and we were unable to independently confirm their existence.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "f47f0f37-6a5a-4430-bb50-1adacc33f0b3", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.03, "w": 0.78, "x": 0.11, "y": 0.79 }, "kind": "source-note", "text": "14 For capacity factor and capacity, we were able to match projects within ±1% without totally negating our ability to identify any BLIMPs.", "attrs": { "numbered": true }, "subkind": null, "toolName": null, "toolSlug": null, "confidence": null, "componentId": "1e4fd799-5931-40aa-823e-46ff9bfbeaef", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.78, "x": 0.11, "y": 0.82 }, "kind": "source-note", "text": "15 In a traditional subsidy program, supporting 200 projects that are never built would be a big waste of resources. However, since the CDM offers a conditional subsidy—CERs are only distributed once a project starts delivering electricity—there is no cost to registering proposed projects that fail to materialize. These are the projects with an index number greater than j in equation 2. Our suspicion that these projects were not completed is also supported by the fact that adding these projects to our database results in more built capacity than nation-wide figures indicate. See appendix A for more.", "attrs": { "numbered": true }, "subkind": null, "toolName": null, "toolSlug": null, "confidence": null, "componentId": "ac56d67e-eb79-45ba-a834-8c982dbd810b", "frameworkName": null, "frameworkSlug": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [], "loops": [], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }