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Under weak assumptions on the error components, we derive nonparametric tests for thin\u2010tailed distributional assumptions imposed on these two components. The tests are useful diagnostic tools for stochastic frontier analysis and kernel deconvolution density estimation. A simulation study and applications to four previously studied datasets are provided. In two of these applications, the new tests reject the thin\u2010tailed distributional assumptions such as normal or Laplace, which are commonly imposed in the existing literature.<\/jats:p>","DOI":"10.1002\/jae.2888","type":"journal-article","created":{"date-parts":[[2021,12,16]],"date-time":"2021-12-16T10:58:27Z","timestamp":1639652307000},"page":"537-562","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Nonparametric tests of tail behavior in stochastic frontier models"],"prefix":"10.1002","volume":"37","author":[{"given":"William C.","family":"Horrace","sequence":"first","affiliation":[{"name":"Department of Economics and Center for Policy Research Syracuse University  Syracuse New York USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Economics and Center for Policy Research Syracuse University  Syracuse New York USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,1,12]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(77)90052-5"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-8008-3_3"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2017.05.005"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.2307\/2951753"},{"key":"e_1_2_8_6_1","volume-title":"A First Course in Order Statistics","author":"Arnold B. 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