This dissertation studies nonparametric identication and estimation of stochastic frontiermodels. It is composed of three chapters. The rst chapter investigates the identication and estimation of a cross sectional stochastic frontier model with Laplacian errors and unknown variance, which is built on a nonparametric density deconvolution strategy. Chapter two studies a zero-ineciency stochastic frontier model utilizing a penalized sieve estimator, which allows flexible function forms and arbitrary distributions of ineciency. The third chapter explores identication and estimation of a nonparametric panel stochastic frontier model based on Kotlarski's Lemma and moments derived from conditional characteristic functions.
","abstract_html":"<p>This dissertation studies nonparametric identication and estimation of stochastic frontiermodels. It is composed of three chapters. The rst chapter investigates the identication and estimation of a cross sectional stochastic frontier model with Laplacian errors and unknown variance, which is built on a nonparametric density deconvolution strategy. Chapter two studies a zero-ineciency stochastic frontier model utilizing a penalized sieve estimator, which allows flexible function forms and arbitrary distributions of ineciency. The third chapter explores identication and estimation of a nonparametric panel stochastic frontier model based on Kotlarski's Lemma and moments derived from conditional characteristic functions.</p>","abstract_has_math":false,"creators":["Cai, Jun"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["William W. Horrace"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-12-22T08:00:00Z","date_published":"2020-12-22T08:00:00Z","updated_at":"2026-07-24T04:55:57Z","subjects":["Deconvolution","Kernel Estimation","Panel Data Model","Productivity","Sieve Estimation","Stochastic Frontier Model","Social and Behavioral Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://surface.syr.edu/etd/1196","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["William W. Horrace"]},{"key":"dc:creator","label":"Author","values":["Cai, Jun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Deconvolution","Kernel Estimation","Panel Data Model","Productivity","Sieve Estimation","Stochastic Frontier Model","Social and Behavioral Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://surface.syr.edu/etd/1196"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation studies nonparametric identication and estimation of stochastic frontiermodels. It is composed of three chapters. The rst chapter investigates the identication and estimation of a cross sectional stochastic frontier model with Laplacian errors and unknown variance, which is built on a nonparametric density deconvolution strategy. Chapter two studies a zero-ineciency stochastic frontier model utilizing a penalized sieve estimator, which allows flexible function forms and arbitrary distributions of ineciency. The third chapter explores identication and estimation of a nonparametric panel stochastic frontier model based on Kotlarski's Lemma and moments derived from conditional characteristic functions.
"]},{"key":"dc:title","label":"Title","values":["NONPARAMETRIC IDENTIFICATION AND ESTIMATION OF STOCHASTIC FRONTIER MODELS"]}]}],"canonical_facts":{"dc:contributor":["William W. Horrace"],"dc:creator":["Cai, Jun"],"dc:description.abstract":["This dissertation studies nonparametric identication and estimation of stochastic frontiermodels. It is composed of three chapters. The rst chapter investigates the identication and estimation of a cross sectional stochastic frontier model with Laplacian errors and unknown variance, which is built on a nonparametric density deconvolution strategy. Chapter two studies a zero-ineciency stochastic frontier model utilizing a penalized sieve estimator, which allows flexible function forms and arbitrary distributions of ineciency. The third chapter explores identication and estimation of a nonparametric panel stochastic frontier model based on Kotlarski's Lemma and moments derived from conditional characteristic functions.
"],"dc:identifier":["https://surface.syr.edu/etd/1196"],"dc:subject":["Deconvolution","Kernel Estimation","Panel Data Model","Productivity","Sieve Estimation","Stochastic Frontier Model","Social and Behavioral Sciences"],"dc:title":["NONPARAMETRIC IDENTIFICATION AND ESTIMATION OF STOCHASTIC FRONTIER MODELS"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:55:57Z"}