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This paper surveys four distinct approaches to frontier estimation of multi-output (and simultaneously multi-input) technologies, when nothing but noisy quantity data are available. Parametrized distributions for inefficiency and noise are necessary for identification of inefficiency, when only cross-sectional data are available. In other respects suitable techniques may differ widely, as is shown. A final technique presented rigorously exploits the possibilities from panel-data by dropping parametrization of distributions as well as functional forms. It is illustrated how this last technique can be coupled with the others to provide a state-of-the-art estimation procedure for this setting. (author's abstract)
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Stored only when both papers are in the corpus — 45 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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