Date of Award

Spring 5-23-2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Economics

Advisor(s)

Horrace, William C.

Second Advisor

Li, Wei

Subject Categories

Economics | Social and Behavioral Sciences

Abstract

This dissertation studies the properties of the conditional mode estimator of stochastic frontier models and applies it to measure technical inefficiency. It consists of two chapters. The first chapter analyzes the conditional mode estimator's closed-form expressions, convergence, near-minimax optimality when interpreted using Lasso, and selection rules. The second chapter applies the true fixed effect stochastic frontier model (Greene, 2005a,b) to analyze the persistent and transient technical inefficiencies of 425 NYC public middle schools for cohorts of students that graduated between 2014 to 2016.

Access

Open Access

Included in

Economics Commons

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