Reference Dependent Aspirations and Peer Effects in Education
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Stefan Wager & Susan Athey, 2018.
"Estimation and Inference of Heterogeneous Treatment Effects using Random Forests,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
- Wager, Stefan & Athey, Susan, 2017. "Estimation and Inference of Heterogeneous Treatment Effects Using Random Forests," Research Papers 3576, Stanford University, Graduate School of Business.
- Zhao, Liqiu & Zhao, Zhong, 2021. "Disruptive Peers in the Classroom and Students’ Academic Outcomes: Evidence and Mechanisms," Labour Economics, Elsevier, vol. 68(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Duc, Julien & Poirier, Côme, 2024. "The optimal role model," Economics Letters, Elsevier, vol. 234(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lechner, Michael, 2018.
"Modified Causal Forests for Estimating Heterogeneous Causal Effects,"
IZA Discussion Papers
12040, Institute of Labor Economics (IZA).
- Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
- Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Economics Working Paper Series 1901, University of St. Gallen, School of Economics and Political Science.
- Michael Lechner, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Papers 1812.09487, arXiv.org, revised Jul 2019.
- William Arbour, 2021. "Can Recidivism be Prevented from Behind Bars? Evidence from a Behavioral Program," Working Papers tecipa-683, University of Toronto, Department of Economics.
- Dimitris Bertsimas & Agni Orfanoudaki & Rory B. Weiner, 2020. "Personalized treatment for coronary artery disease patients: a machine learning approach," Health Care Management Science, Springer, vol. 23(4), pages 482-506, December.
- Stephen Jarvis & Olivier Deschenes & Akshaya Jha, 2022.
"The Private and External Costs of Germany’s Nuclear Phase-Out,"
Journal of the European Economic Association, European Economic Association, vol. 20(3), pages 1311-1346.
- Stephen Jarvis & Olivier Deschenes & Akshaya Jha, 2019. "The Private and External Costs of Germany's Nuclear Phase-Out," NBER Working Papers 26598, National Bureau of Economic Research, Inc.
- Jarvis, Stephen & Deschenes, Olivier & Jha, Akshaya, 2022. "The private and external costs of Germany’s nuclear phase-out," LSE Research Online Documents on Economics 113634, London School of Economics and Political Science, LSE Library.
- Hayakawa, Kazunobu & Keola, Souknilanh & Silaphet, Korrakoun & Yamanouchi, Kenta, 2022. "Estimating the impacts of international bridges on foreign firm locations: a machine learning approach," IDE Discussion Papers 847, Institute of Developing Economies, Japan External Trade Organization(JETRO).
- Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
- Naguib, Costanza, 2019. "Estimating the Heterogeneous Impact of the Free Movement of Persons on Relative Wage Mobility," Economics Working Paper Series 1903, University of St. Gallen, School of Economics and Political Science.
- Labro, Eva & Lang, Mark & Omartian, James D., 2023. "Predictive analytics and centralization of authority," Journal of Accounting and Economics, Elsevier, vol. 75(1).
- J. Michelle Brock & Ralph De Haas, 2023.
"Discriminatory Lending: Evidence from Bankers in the Lab,"
American Economic Journal: Applied Economics, American Economic Association, vol. 15(2), pages 31-68, April.
- De Haas, Ralph & Brock, J Michelle, 2020. "Discriminatory Lending: Evidence from Bankers in the Lab," CEPR Discussion Papers 14340, C.E.P.R. Discussion Papers.
- Brock, J. Michelle & de Haas, Ralph, 2021. "Discriminatory Lending : Evidence from Bankers in the Lab," Other publications TiSEM 12af373a-8e1a-46dd-afd4-a, Tilburg University, School of Economics and Management.
- Brock, J. Michelle & de Haas, Ralph, 2021. "Discriminatory Lending : Evidence from Bankers in the Lab," Other publications TiSEM c54f4f4f-3ad0-4d68-8962-d, Tilburg University, School of Economics and Management.
- Brock, J. Michelle & de Haas, Ralph, 2021. "Discriminatory Lending : Evidence from Bankers in the Lab," Discussion Paper 2021-006, Tilburg University, Center for Economic Research.
- Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan & Vance, Colin, 2019.
"Local cost for global benefit: The case of wind turbines,"
Ruhr Economic Papers
791, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, revised 2019.
- Kussel, Gerhard & Frondel, Manuel & Vance, Colin & Sommer, Stephan, 2019. "Local Cost for Global Benefit: The Case of Wind Turbines," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203583, Verein für Socialpolitik / German Economic Association.
- Patrick Krennmair & Timo Schmid, 2022. "Flexible domain prediction using mixed effects random forests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1865-1894, November.
- Eliaz, Kfir & Spiegler, Ran, 2022.
"On incentive-compatible estimators,"
Games and Economic Behavior, Elsevier, vol. 132(C), pages 204-220.
- Eliaz, Kfir & Spiegler, Ran, 2018. "Incentive Compatible Estimators," CEPR Discussion Papers 12804, C.E.P.R. Discussion Papers.
- Piasenti, Stefano & Valente, Marica & van Veldhuizen, Roel & Pfeifer, Gregor, 2023.
"Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions,"
IZA Discussion Papers
16324, Institute of Labor Economics (IZA).
- Piasenti, Stefano & Valente, Marica & Van Veldhuizen, Roel & Pfeifer, Gregor, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," Working Papers 2023:7, Lund University, Department of Economics.
- Stefano Piasenti & Marica Valente & Roel van Veldhuizen & Gregor Pfeifer, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," Rationality and Competition Discussion Paper Series 410, CRC TRR 190 Rationality and Competition.
- Stefano Piasenti & Marica Valente & Roel van Veldhuizen & Gregor Pfeifer, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," Working Papers 2023-11, Faculty of Economics and Statistics, Universität Innsbruck.
- Stefano Piasenti & Marica Valente & Roel van Veldhuizen & Gregor Pfeifer & Gregor-Gabriel Pfeifer, 2023. "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," CESifo Working Paper Series 10572, CESifo.
- Elek, Péter & Bíró, Anikó, 2021. "Regional differences in diabetes across Europe – regression and causal forest analyses," Economics & Human Biology, Elsevier, vol. 40(C).
- Michael C. Knaus, 2021.
"A double machine learning approach to estimate the effects of musical practice on student’s skills,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
- Knaus, Michael C., 2018. "A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student's Skills," IZA Discussion Papers 11547, Institute of Labor Economics (IZA).
- Michael C. Knaus, 2018. "A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student's Skills," Papers 1805.10300, arXiv.org, revised Jan 2019.
- Montiel Olea, José Luis & Nesbit, James, 2021. "(Machine) learning parameter regions," Journal of Econometrics, Elsevier, vol. 222(1), pages 716-744.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Bokelmann, Björn & Lessmann, Stefan, 2024. "Improving uplift model evaluation on randomized controlled trial data," European Journal of Operational Research, Elsevier, vol. 313(2), pages 691-707.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021.
"A unified framework for efficient estimation of general treatment models,"
Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2018. "A Unified Framework for Efficient Estimation of General Treatment Models," Papers 1808.04936, arXiv.org, revised Aug 2018.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," CeMMAP working papers CWP64/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ai, C. & Linton, O. & Motegi, K. & Zhang, Z., 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," Cambridge Working Papers in Economics 1934, Faculty of Economics, University of Cambridge.
- Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
More about this item
Keywords
inequality; peer effects; education;All these keywords.
JEL classification:
- I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
- I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
- I29 - Health, Education, and Welfare - - Education - - - Other
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
NEP fields
This paper has been announced in the following NEP Reports:- NEP-EDU-2023-01-09 (Education)
- NEP-NET-2023-01-09 (Network Economics)
- NEP-URE-2023-01-09 (Urban and Real Estate Economics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp15785. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.