RT Journal Article
T1 Dealing with endogeneity in data envelopment analysis applications
A1 Santín González, Daniel
A1 Sicilia, Gabriela
AB Although the presence of the endogeneity is frequently observed in economic production processes, it tends to be overlooked when practitioners apply data envelopment analysis (DEA). In this paper we deal with this issue in two ways. First, we provide a simple statistical heuristic procedure that enables practitioners to identify the presence of endogeneity in an empirical application. Second, we propose the use of an instrumental input DEA (II-DEA) as a potential tool to address this problem and thus improve DEA estimations. A Monte Carlo experiment confirms that the proposed II-DEA approach outperforms standard DEA in finite samples under the presence of high positive endogeneity. To illustrate our theoretical findings, we perform an empirical application on the education sector.
PB Elsevier
SN 0957-4174
YR 2017
FD 2017
LK https://hdl.handle.net/20.500.14352/18905
UL https://hdl.handle.net/20.500.14352/18905
LA eng
NO Ministerio de Economía y Competitividad (MINECO)
DS Docta Complutense
RD 21 abr 2025