000	02125nam  2200397zi 4500
001	9.929015
003	CaOODSP
005	20231018131934
006	m     o  d f
007	cr |n|||||||||
008	231018t20232023oncd    ob   f|0| 0 eng d
040	|aCaOODSP|beng|erda|cCaOODSP
041	|aeng|beng|bfre
043	|an-cn---
086	1 |aFB3-5/2023-53E-PDF
100	1 |aHoule, Stéphanie,|d1973- |eauthor.
245	10|aIdentifying nascent high-growth firms using machine learning / |cby Stephanie Houle and Ryan Macdonald.
264	1|a[Ottawa] : |bBank of Canada = Banque du Canada, |c2023.
264	4|c©2023
300	|a1 online resource (ii, 31 pages) : |bcharts.
336	|atext|btxt|2rdacontent
337	|acomputer|bc|2rdamedia
338	|aonline resource|bcr|2rdacarrier
490	1 |aStaff working paper = |aDocument de travail du personnel, |x1701-9397 ; |v2023-53
500	|a"Last updated: October 16, 2023."
500	|aCover title.
504	|aIncludes bibliographical references (pages 29-31).
520	|a"We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data. We apply a suite of supervised machine learning algorithms (elastic net model, random forest and neural net) to determine whether a large set of variables on Canadian firm tax filing financial and employment data, state variables (e.g., industry, geography) and indicators of firm complexity (e.g., multiple industrial activities, foreign ownership) can predict which firms will be high-growth firms over the next three years"--Abstract.
546	|aIncludes abstract in French.
650	5|aBusiness enterprises|zCanada.
650	0|aMachine learning.
650	6|aEntreprises|zCanada.
650	6|aApprentissage automatique.
710	2 |aBank of Canada, |eissuing body.
830	#0|aStaff working paper (Bank of Canada)|x1701-9397 ; |v2023-53.|w(CaOODSP)9.806221
856	40|qPDF|s605 KB|uhttps://publications.gc.ca/collections/collection_2023/banque-bank-canada/FB3-5-2023-53-eng.pdf