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

In: The Econometrics of Networks

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  • Diego Rojas
  • Juan Estrada
  • Kim P. Huynh
  • David T. Jacho-Chávez

Abstract

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.

Suggested Citation

  • Diego Rojas & Juan Estrada & Kim P. Huynh & David T. Jacho-Chávez, 2020. "Survival Analysis of Bank Note Circulation: Fitness, Network Structure, and Machine Learning," Advances in Econometrics, in: The Econometrics of Networks, volume 42, pages 235-262, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:aecozz:s0731-905320200000042018
    DOI: 10.1108/S0731-905320200000042018
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    References listed on IDEAS

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    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
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    More about this item

    Keywords

    Cash; big data; clustering; elastic net; hazard models; K-prototypes; E42; E51; C52; C65; C81;
    All these keywords.

    JEL classification:

    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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