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| 01872cam 2200337zi 4500 |
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| 001 | 9.903820 |
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| 003 | CaOODSP |
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| 005 | 20221107180351 |
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| 006 | m o d f |
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| 007 | cr cn||||||||| |
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| 008 | 211004t20212021oncd ob f000 0 eng d |
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| 040 | |aCaOODSP|beng|erda|cCaOODSP |
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| 086 | 1 |aFB3-5/2021-45E-PDF |
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| 100 | 1 |bBachem, Milian,|eauthor. |
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| 245 | 10|aCovariates hiding in the tails / |cby Milian Bachem, Lerby M. Ergun, Casper G. de Vries. |
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| 264 | 1|aOttawa, Ontario, Canada : |bBank of Canada = Banque du Canada, |c2021. |
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| 264 | 4|c©2021 |
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| 300 | |a1 online resource (ii, 47 pages) : |bgraphs. |
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| 336 | |atext|btxt|2rdacontent |
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| 337 | |acomputer|bc|2rdamedia |
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| 338 | |aonline resource|bcr|2rdacarrier |
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| 490 | 1 |aStaff working paper = |aDocument de travail du personnel, |x1701-9397 ; |v2021-45 |
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| 500 | |a"September 29, 2021." |
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| 500 | |aCover title. |
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| 504 | |aIncludes bibliographical references (pages 34-35). |
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| 520 | 3 |a"Scaling behavior measured in cross-sectional studies through the tail index of a power law is prone to a bias. This hampers inference; in particular, time variation in estimated tail indices may be erroneous. In the case of a linear factor model, the factor biases the tail indices in the left and right tail in opposite directions. This fact can be exploited to reduce the bias. We show how this bias arises from the factor, how to remedy for the bias and how to apply our methods to financial data and geographic location data"--Abstract, page iii. |
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| 650 | 0|aEconometric models. |
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| 650 | 6|aModèles économétriques. |
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| 710 | 2 |aBank of Canada, |eissuing body. |
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| 830 | #0|aStaff working paper (Bank of Canada)|x1701-9397 ; |v2021-45.|w(CaOODSP)9.806221 |
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| 856 | 40|qPDF|s620 MB|uhttps://publications.gc.ca/collections/collection_2021/banque-bank-canada/FB3-5-2021-45-eng.pdf |
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