<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-08T11:06:28Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/125979" metadataPrefix="marc">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/125979</identifier><datestamp>2025-11-13T01:01:03Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_15</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Aparicio, Juan</subfield>
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      <subfield code="a">Perelman, Sergio</subfield>
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      <subfield code="a">Santín González, Daniel</subfield>
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      <subfield code="c">2022-06-14</subfield>
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      <subfield code="a">The main objective of this paper is to propose a tool for measuring the productivity and performance gaps across a set of Decision Making Units for monitoring their evolution and analyzing their components over time. To do this, we use the approach proposed by Aparicio and Santín (Eur J Oper Res 267(1):227–235, 2018) which is grounded on a base-group base-period productivity index and Data Envelopment Analysis. Additionally, we propose a new index for measuring the performance gap between two or more groups of production units and its decomposition in effectiveness gap and outcome possibility set gap. As an empirical illustration of the approach, we focus our attention on the educational sector. In particular, we analyze six Latin American countries over time. For this purpose, we rely on OECD– PISA data aggregated at school level. Over the period 2006–2018, performance and productivity followed very different paths in each country showing that the correlation between school performance and productivity is very low. Therefore, we suggest that the simultaneous analysis of performance and productivity gaps together with their evolution over time is a must in order to benchmark countries and monitor improvements and weaknesses in education systems.</subfield>
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      <subfield code="a">Aparicio, J., Perelman, S., &amp; Santín, D. (2022). Comparing the evolution of productivity and performance gaps in education systems through DEA: an application to Latin American countries. Operational Research, 22(2), 1443-1477.</subfield>
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      <subfield code="a">10.1007/s12351-020-00578-2</subfield>
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      <subfield code="a">https://hdl.handle.net/20.500.14352/125979</subfield>
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      <subfield code="a">https://doi.org/10.1007/s12351-020-00578-2</subfield>
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      <subfield code="a">https://link.springer.com/article/10.1007/s12351-020-00578-2</subfield>
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      <subfield code="a">Comparing the evolution of productivity and performance gaps in education systems through DEA: an application to Latin American countries</subfield>
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