Journal of Forest Economics > Vol 17 > Issue 4

Annual use, economic life and residual value of cut-to-length harvesting machines

Raffaele Spinelli, , spinelli@ivalsa.cnr.it Natascia Magagnotti, , magagnotti@ivalsa.cnr.it Gianni Picchi, , picchi@ivalsa.cnr.it
 
Suggested Citation
Raffaele Spinelli, Natascia Magagnotti and Gianni Picchi (2011), "Annual use, economic life and residual value of cut-to-length harvesting machines", Journal of Forest Economics: Vol. 17: No. 4, pp 378-387. http://dx.doi.org/10.1016/j.jfe.2011.03.003

Published: 0/12/2011
© 0 2011 Raffaele Spinelli, Natascia Magagnotti, Gianni Picchi
 
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Keywords
JEL Codes:L24L73C93
Machine ratesCostHarvestingMachineryCTL
 

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In this article:
Introduction
Materials and methods
Results
Discussion
Conclusions
Funding

Abstract

Recognizing the absence of up-to-date empirical data on the economic life, the annual use and the residual value of dedicated cut-to-length (CTL) harvesting machinery, the authors gathered a large database of second-hand machine sale offers containing over 1000 records, coming from Europe and North America. The statistical analysis of these data pointed at an economic life in the vicinity of 18,000h for both harvesters and forwarders, which confirms previous assumptions. The average annual use for the machines in the database is 1424 and 1581h year−1, respectively for the harvesters and the forwarders. Nordic users achieve a higher annual use than central European users, and the difference is statistically significant. Nevertheless, the average annual use recorded for both groups falls below the levels commonly adopted in current estimates, which may therefore represent ideal reference figures rather than actual averages. Residual value is strongly related to machine age, and the authors calculated some simple functions for estimating it. The study points at a better retention of the original value, compared to the figures reported in previous literature. At 5 years of age the harvesters and forwarders in the study keep respectively 38% and 44% of the new value. The information contained in the study is crucial to machine rate calculation, which has often been based on rule-of-thumb assumptions, in the absence of empirical data.

DOI:10.1016/j.jfe.2011.03.003