{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/15593"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/15593","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Using panel data to estimate the returns to schooling in South Africa","abstract":"Returns to schooling have typically been estimated with cross-sectional data. However, these studies are fraught with difficulties arising from the endogeneity of education. Individual effects that cannot be measured, such as ability and family background, cause bias in the estimates because they are correlated with education. A panel data approach is thus potentially superior to a cross-sectional one, in that it allows the individual effects to be eliminated with time-differencing. However, time-invariant regressors, such as education, cannot be identified under these time-differencing techniques. This paper therefore uses a Generalized Instrumental Variables method that was developed by Hausman and Taylor (1981) to estimate returns to schooling under a panel data context. This approach both controls for endogeneity bias and allows the identification of time-constant regressors, in this case, education. The re- turns to schooling under this estimation method are approximately 21% for South African individuals who are consistently employed from 2008-2013.","abstract_html":"Returns to schooling have typically been estimated with cross-sectional data. However, these studies are fraught with difficulties arising from the endogeneity of education. Individual effects that cannot be measured, such as ability and family background, cause bias in the estimates because they are correlated with education. A panel data approach is thus potentially superior to a cross-sectional one, in that it allows the individual effects to be eliminated with time-differencing. However, time-invariant regressors, such as education, cannot be identified under these time-differencing techniques. This paper therefore uses a Generalized Instrumental Variables method that was developed by Hausman and Taylor (1981) to estimate returns to schooling under a panel data context. This approach both controls for endogeneity bias and allows the identification of time-constant regressors, in this case, education. The re- turns to schooling under this estimation method are approximately 21% for South African individuals who are consistently employed from 2008-2013.","abstract_has_math":false,"creators":["Miles, Caitlin Rose"],"institution":"School of Economics","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Daniels, Reza"],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-22T22:23:35Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/15593","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Daniels, Reza"]},{"key":"dc:creator","label":"Author","values":["Miles, Caitlin Rose"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-12-04T18:06:26Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-12-04T18:06:26Z"]},{"key":"dc:date.issued","label":"Date","values":["2015"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Economics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MCom"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/15593"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references"]},{"key":"dc:description.abstract","label":"Abstract","values":["Returns to schooling have typically been estimated with cross-sectional data. However, these studies are fraught with difficulties arising from the endogeneity of education. Individual effects that cannot be measured, such as ability and family background, cause bias in the estimates because they are correlated with education. A panel data approach is thus potentially superior to a cross-sectional one, in that it allows the individual effects to be eliminated with time-differencing. However, time-invariant regressors, such as education, cannot be identified under these time-differencing techniques. This paper therefore uses a Generalized Instrumental Variables method that was developed by Hausman and Taylor (1981) to estimate returns to schooling under a panel data context. This approach both controls for endogeneity bias and allows the identification of time-constant regressors, in this case, education. The re- turns to schooling under this estimation method are approximately 21% for South African individuals who are consistently employed from 2008-2013."]},{"key":"dc:title","label":"Title","values":["Using panel data to estimate the returns to schooling in South Africa"]}]}],"canonical_facts":{"dc:contributor.advisor":["Daniels, Reza"],"dc:creator":["Miles, Caitlin Rose"],"dc:date.accessioned":["2015-12-04T18:06:26Z"],"dc:date.available":["2015-12-04T18:06:26Z"],"dc:date.issued":["2015"],"dc:description":["Includes bibliographical references"],"dc:description.abstract":["Returns to schooling have typically been estimated with cross-sectional data. However, these studies are fraught with difficulties arising from the endogeneity of education. Individual effects that cannot be measured, such as ability and family background, cause bias in the estimates because they are correlated with education. A panel data approach is thus potentially superior to a cross-sectional one, in that it allows the individual effects to be eliminated with time-differencing. However, time-invariant regressors, such as education, cannot be identified under these time-differencing techniques. This paper therefore uses a Generalized Instrumental Variables method that was developed by Hausman and Taylor (1981) to estimate returns to schooling under a panel data context. This approach both controls for endogeneity bias and allows the identification of time-constant regressors, in this case, education. The re- turns to schooling under this estimation method are approximately 21% for South African individuals who are consistently employed from 2008-2013."],"dc:identifier.uri":["http://hdl.handle.net/11427/15593"],"dc:language.iso":["eng"],"dc:publisher.department":["School of Economics"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Using panel data to estimate the returns to schooling in South Africa"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MCom"]},"updated_at":"2026-07-22T22:23:35Z"}