An application of data envelopment analysis to investigate the efficiency of lumber industry in northwestern Ontario, Canada

Abstract

This study aims at exploring the technical efficiency of lumber industry in northwestern Ontario, Canada using data envelopment analysis (DEA). The DEA model analyzes relative technical efficiency of lumber mills with disproportionate inputs and outputs by dividing the 10-year time series data, for inputs and outputs of 24 lumber mills, over two periods (1999–2003 and 2004–2008). Four inputs, namely, material (log volume), labour (man-hours), two types of energy (hog-fuel and electricity), and one output (lumber volume) are used in this study. The trend analysis shows an annual reduction of 10%, 13% and 13% for lumber output, log consumption (input) and number of employees, respectively, during the period 1999–2008. The results from DEA with two scenarios with energy inputs and without energy inputs, for the two periods are found to be mixed and interesting. While some mills have improved their performance in terms of best use of available scarce inputs in the second period, some have shown negative per cent change in efficiency. In the with energy input and the without energy input scenario, some of the mills show a reduction in efficiency in the second period from the first period, with the highest estimated reductions of −13.9% and −47.6%, respectively. A possible explanation for these negative performances of mills in the latter period is the decline in production in the second period compared to the first period, where these mills were not able to adjust their inputs (mostly labour) as proportional lay-offs might not have been possible. These results provide policy makers and industry stakeholders with an improved understanding of the trends of efficiency and employment as well as reallocation opportunities of future inputs in order to increase benefits from this sector.

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