To read the full version of this content please select one of the options below:

Survival Analysis of Bank Note Circulation: Fitness, Network Structure, and Machine Learning

The Econometrics of Networks

ISBN: 978-1-83867-576-9, eISBN: 978-1-83867-575-2

ISSN: 0731-9053

Publication date: 19 October 2020


The efficient distribution of bank notes is a first-order responsibility of central banks. The authors study the distribution patterns of bank notes with an administrative dataset from the Bank of Canada’s Currency Inventory Management Strategy. The single note inspection procedure generates a sample of 900 million bank notes in which the authors can trace the length of the stay of a bank note in the market. The authors define the duration of the bank note circulation cycle as beginning on the date the bank note is first shipped by the Bank of Canada to a financial institution and ending when it is returned to the Bank of Canada. In addition, the authors provide information regarding where the bank note is shipped and later received, as well as the physical fitness of the bank note upon return to the Bank of Canada’s distribution centers. K–prototype clustering classifies bank notes into types. A hazard model estimates the duration of bank note circulation cycles based on their clusters and characteristics. An adaptive elastic net provides an algorithm for dimension reduction. It is found that while the distribution of the duration is affected by fitness measures, their effects are negligible when compared with the influence exerted by the clusters related to bank note denominations.




We thank Áureo de Paula, Jean-Frédéric Demers, David Drukker, Ben Fung, Ted Garanzotis, Harry J. Paarsch, Ramesh Paskarathas, Marcel Voia, and participants of the Advances in Econometrics conference on the “Econometrics of Networks” organized by the National Bank of Romania and the Faculty of Economic Sciences – Lucian Blaga University, Sibiu on May 16–17, 2019 for their various comments and suggestions on an earlier draft. We also acknowledge the efforts of Valerie Clermont, Ted Garanzotis, Mireille Lacroix, Andrew Marshall, Phil Riopelle, and Nathalie Swift and the use of the Bank of Canada’s Digital Analytical Zone Microsoft Azure Cloud. We thank Meredith Fraser-Ohman for providing excellent editorial assistance. The views expressed in this chapter are those of the authors. No responsibility for them should be attributed to the Bank of Canada.


Rojas, D., Estrada, J., Huynh, K.P. and Jacho-Chávez, D.T. (2020), "Survival Analysis of Bank Note Circulation: Fitness, Network Structure, and Machine Learning", de Paula, Á., Tamer, E. and Voia, M.-C. (Ed.) The Econometrics of Networks (Advances in Econometrics, Vol. 42), Emerald Publishing Limited, Bingley, pp. 235-262.



Emerald Publishing Limited

Copyright © Chapter 9. ‘Survival Analysis of Banknote Circulation: Fitness, Network Structure, and Machine Learning’, 2020 Bank of Canada