Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/263136 
Year of Publication: 
2022
Series/Report no.: 
IFRO Working Paper No. 2022/05
Publisher: 
University of Copenhagen, Department of Food and Resource Economics (IFRO), Copenhagen
Abstract: 
Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions, nor for test of common production possibility sets, when analysing productivity have been available. We develop three novel tests based on permutations of the observations. The first is a test for constant returns to scale. The other two are, respectively, tests for frontier differences and for whether the production possibility sets are nested. All tests are based on data envelopment analysis (DEA) estimates of efficiencies and are easily implementable. We show that our suggested permutations of the observations satisfy the necessary randomisation assumptions, and hereby that the sizes of the proposed tests are controlled. The advantages of permutation tests are that they are reliable even for relatively small samples and their size can generally be controlled upwards. We further add a lower bound showing that the proposed tests are very close to being exact. Finally, we show that our tests are consistent and illustrate the rate of convergence in simulation studies.
Subjects: 
Permutation tests
Returns to scale
Comparison of production frontiers
Dataenvelopment analysis (DEA)
Size
Consistency
JEL: 
C12
C13
C15
C18
D24
C67
Document Type: 
Working Paper

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