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Daniel Goller

Not to be confused with: Daniel Goeller

Personal Details

First Name:Daniel
Middle Name:
Last Name:Goller
Suffix:
RePEc Short-ID:pgo856
[This author has chosen not to make the email address public]

Affiliation

Department Volkswirtschaftlehre
Universität Bern

Bern, Switzerland
http://www-vwi.unibe.ch/
RePEc:edi:vwibech (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Enzo Brox & Daniel Goller, 2024. "Tournaments, Contestant Heterogeneity and Performance," Papers 2401.05210, arXiv.org, revised Oct 2024.
  2. Daniel Goller & Chiara Graf & Stefan C. Wolter, 2024. "The virtues of going virtual," Economics of Education Working Paper Series 0224, University of Zurich, Department of Business Administration (IBW).
  3. Daniel Goller & Stefan C. Wolter, 2023. "Reaching for Gold! The Impact of a Positive Reputation Shock on Career Choice," CESifo Working Paper Series 10791, CESifo.
  4. Daniel Goller & Maximilian Spath, 2023. "'Good job!' The impact of positive and negative feedback on performance," Papers 2301.11776, arXiv.org.
  5. Daniel Goller & Christian Gschwendt & Stefan C. Wolter, 2023. "“This Time It’s Different” Generative Artificial Intelligence and Occupational Choice," CESifo Working Paper Series 10821, CESifo.
  6. Maximilian Späth & Daniel Goller, 2023. "Gender differences in investment reactions to irrelevant information," CEPA Discussion Papers 67, Center for Economic Policy Analysis.
  7. Goller, Daniel & Heiniger, Sandro, 2022. "A general framework to quantify the event importance in multi-event contests," Economics Working Paper Series 2204, University of St. Gallen, School of Economics and Political Science.
  8. Daniel Goller & Andrea Diem & Stefan C. Wolter, 2022. "Sitting next to a dropout: Study success of students with peers that came to the lecture hall by a different route," Economics of Education Working Paper Series 0190, University of Zurich, Department of Business Administration (IBW).
  9. Daniel Goller & Andrea Diem & Stefan C. Wolter, 2022. "Sitting Next to a Dropout - Academic Success of Students with More Educated Peers," CESifo Working Paper Series 9812, CESifo.
  10. Daniel Goller & Tamara Harrer & Michael Lechner & Joachim Wolff, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Papers 2106.10141, arXiv.org, revised May 2023.
  11. Daniel Goller & Stefan C. Wolter, 2021. ""Too Shocked to Search" The Covid-19 Shutdowns' Impact on the Search for Apprenticeships," CESifo Working Paper Series 9060, CESifo.
  12. Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
  13. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germany's programmes for long term unemployed," IAB-Discussion Paper 202005, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  14. Goller, Daniel & Krumer, Alex, 2019. "Let’s meet as usual: Do games on non-frequent days differ? Evidence from top European soccer leagues," Economics Working Paper Series 1907, University of St. Gallen, School of Economics and Political Science.
  15. Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018. "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series 1811, University of St. Gallen, School of Economics and Political Science.

Articles

  1. Daniel Goller & Sandro Heiniger, 2024. "A general framework to quantify the event importance in multi-event contests," Annals of Operations Research, Springer, vol. 341(1), pages 71-93, October.
  2. Daniel Goller, 2023. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Annals of Operations Research, Springer, vol. 325(1), pages 649-679, June.
  3. Goller, Daniel & Diem, Andrea & Wolter, Stefan C., 2023. "Sitting next to a dropout: Academic success of students with more educated peers," Economics of Education Review, Elsevier, vol. 93(C).
  4. Daniel Goller & Stefan C. Wolter, 2021. "“Too shocked to search” The COVID-19 shutdowns’ impact on the search for apprenticeships," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 157(1), pages 1-15, December.
  5. Goller, Daniel & Krumer, Alex, 2020. "Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues," European Journal of Operational Research, Elsevier, vol. 286(2), pages 740-754.
  6. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed," Labour Economics, Elsevier, vol. 65(C).

Chapters

  1. Daniel Goller & Michael C. Knaus & Michael Lechner & Gabriel Okasa, 2021. "Predicting match outcomes in football by an Ordered Forest estimator," Chapters, in: Ruud H. Koning & Stefan Kesenne (ed.), A Modern Guide to Sports Economics, chapter 22, pages 335-355, Edward Elgar Publishing.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Daniel Goller & Stefan C. Wolter, 2023. "Reaching for Gold! The Impact of a Positive Reputation Shock on Career Choice," CESifo Working Paper Series 10791, CESifo.

    Cited by:

    1. Daniel Goller & Chiara Graf & Stefan C. Wolter, 2024. "The virtues of going virtual," Economics of Education Working Paper Series 0224, University of Zurich, Department of Business Administration (IBW).

  2. Daniel Goller & Maximilian Spath, 2023. "'Good job!' The impact of positive and negative feedback on performance," Papers 2301.11776, arXiv.org.

    Cited by:

    1. Daniel Goller & Sandro Heiniger, 2024. "A general framework to quantify the event importance in multi-event contests," Annals of Operations Research, Springer, vol. 341(1), pages 71-93, October.

  3. Daniel Goller & Tamara Harrer & Michael Lechner & Joachim Wolff, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Papers 2106.10141, arXiv.org, revised May 2023.

    Cited by:

    1. Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
    2. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.

  4. Daniel Goller & Stefan C. Wolter, 2021. ""Too Shocked to Search" The Covid-19 Shutdowns' Impact on the Search for Apprenticeships," CESifo Working Paper Series 9060, CESifo.

    Cited by:

    1. Daniel Goller & Chiara Graf & Stefan C. Wolter, 2024. "The virtues of going virtual," Economics of Education Working Paper Series 0224, University of Zurich, Department of Business Administration (IBW).
    2. Katharina Werner & Ludger Woessmann, 2021. "The Legacy of Covid-19 in Education," CESifo Working Paper Series 9358, CESifo.
    3. Daniel Goller & Stefan C. Wolter, 2023. "Reaching for Gold! The Impact of a Positive Reputation Shock on Career Choice," CESifo Working Paper Series 10791, CESifo.
    4. Daniel Goller & Christian Gschwendt & Stefan C. Wolter, 2023. ""This time it's different" Generative Artificial Intelligence and Occupational Choice," Economics of Education Working Paper Series 0209, University of Zurich, Department of Business Administration (IBW).
    5. Thomas Bolli & Guillaume Morlet, 2023. "Does human capital theory govern the relationship between training provision and the business cycle? Evidence from Switzerland," French Stata Users' Group Meetings 2023 26, Stata Users Group.
    6. Monika Bütler, 2022. "Economics and economists during the COVID-19 pandemic: a personal view," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-15, December.

  5. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germany's programmes for long term unemployed," IAB-Discussion Paper 202005, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

    Cited by:

    1. Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Economics Working Paper Series 2108, University of St. Gallen, School of Economics and Political Science.
    2. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    3. Börschlein, Benjamin & Bossler, Mario, 2021. "A new machine learning-based treatment bite for long run minimum wage evaluations," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242441, Verein für Socialpolitik / German Economic Association.
    4. Caron, Laura & Tiongson, Erwin R., 2022. "Households in Transit: COVID-19 and the Changing Measurement of Welfare," IZA Discussion Papers 15670, Institute of Labor Economics (IZA).
    5. Dan A. Black & Jeffrey Grogger & Tom Kirchmaier & Koen Sanders, 2023. "Criminal charges, risk assessment and violent recidivism in cases of domestic abuse," CEP Discussion Papers dp1897, Centre for Economic Performance, LSE.
    6. Hoai An Le Thi & Manh Cuong Nguyen, 2017. "DCA based algorithms for feature selection in multi-class support vector machine," Annals of Operations Research, Springer, vol. 249(1), pages 273-300, February.
    7. Cappelletti, Matilde & Giuffrida, Leonardo M., 2022. "Targeted bidders in government tenders," ZEW Discussion Papers 22-030, ZEW - Leibniz Centre for European Economic Research.
    8. Matilde Cappelletti & Leonardo M. Giuffrida, 2024. "Targeted Bidders in Government Tenders," CESifo Working Paper Series 11142, CESifo.
    9. Cuiqing Jiang & Zhao Wang & Ruiya Wang & Yong Ding, 2018. "Loan default prediction by combining soft information extracted from descriptive text in online peer-to-peer lending," Annals of Operations Research, Springer, vol. 266(1), pages 511-529, July.
    10. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.
    11. Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
    12. Heigle, Julia & Pfeiffer, Friedhelm, 2020. "Langfristige Wirkungen eines nicht abgeschlossenen Studiums auf individuelle Arbeitsmarktergebnisse und die allgemeine Lebenszufriedenheit," ZEW Discussion Papers 20-004, ZEW - Leibniz Centre for European Economic Research.
    13. Barrera-Osorio, Felipe & Gertler,Paul J. & Nakajima,Nozomi & Patrinos,Harry Anthony, 2020. "Promoting Parental Involvement in Schools : Evidence from Two Randomized Experiments," Policy Research Working Paper Series 9462, The World Bank.
    14. Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org.
    15. Alena Bömmel & Song Song & Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Härdle, 2014. "Risk Patterns and Correlated Brain Activities. Multidimensional Statistical Analysis of fMRI Data in Economic Decision Making Study," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 489-514, July.
    16. Goller, Daniel & Krumer, Alex, 2020. "Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues," European Journal of Operational Research, Elsevier, vol. 286(2), pages 740-754.

  6. Goller, Daniel & Krumer, Alex, 2019. "Let’s meet as usual: Do games on non-frequent days differ? Evidence from top European soccer leagues," Economics Working Paper Series 1907, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Bryson, Alex & Dolton, Peter & Reade, J. James & Schreyer, Dominik & Singleton, Carl, 2021. "Causal effects of an absent crowd on performances and refereeing decisions during Covid-19," Economics Letters, Elsevier, vol. 198(C).
    2. Stefano Cabras & Marco Delogu & J.D. Tena, 2021. "Forced to Play Too Many Matches? A DeepLearning Assessment of Crowded Schedule," Working Papers 202110 Classification-, University of Liverpool, Department of Economics.
    3. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germany's programmes for long term unemployed," IAB-Discussion Paper 202005, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

  7. Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018. "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series 1811, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
    2. Michael Lechner & Gabriel Okasa, 2019. "Random Forest Estimation of the Ordered Choice Model," Papers 1907.02436, arXiv.org, revised Sep 2022.

Articles

  1. Daniel Goller & Stefan C. Wolter, 2021. "“Too shocked to search” The COVID-19 shutdowns’ impact on the search for apprenticeships," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 157(1), pages 1-15, December.
    See citations under working paper version above.
  2. Goller, Daniel & Krumer, Alex, 2020. "Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues," European Journal of Operational Research, Elsevier, vol. 286(2), pages 740-754.

    Cited by:

    1. Ferraresi Massimiliano & Gucciardi Gianluca, 2023. "Team performance and the perception of being observed: Experimental evidence from top-level professional football," German Economic Review, De Gruyter, vol. 24(1), pages 1-31, February.
    2. Bryson, Alex & Dolton, Peter & Reade, J. James & Schreyer, Dominik & Singleton, Carl, 2021. "Causal effects of an absent crowd on performances and refereeing decisions during Covid-19," Economics Letters, Elsevier, vol. 198(C).
    3. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Eliminating supportive crowds reduces referee bias," Economics Discussion Papers em-dp2020-25, Department of Economics, University of Reading, revised 01 Dec 2021.
    4. Franziska Braschke & Patrick Puhani, 2022. "Population Adjustment to Asymmetric Labour Market Shocks in India A Comparison to Europe and the United States at Two Different Regional Levels," RF Berlin - CReAM Discussion Paper Series 2214, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    5. Kai Fischer & Justus Haucap, 2020. "Does Crowd Support Drive the Home Advantage in Professional Soccer? Evidence from German Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8549, CESifo.
    6. J. James Reade & Carl Singleton, 2020. "Demand for Public Events in the COVID-19 Pandemic: A Case Study of European Football," Economics Discussion Papers em-dp2020-09, Department of Economics, University of Reading, revised 01 Oct 2020.
    7. Stefano Cabras & Marco Delogu & J.D. Tena, 2021. "Forced to Play Too Many Matches? A DeepLearning Assessment of Crowded Schedule," Working Papers 202110 Classification-, University of Liverpool, Department of Economics.
    8. Di Mattia, Alessandro & Krumer, Alex, 2023. "Fewer teams, more games, larger attendance? Evidence from the structural change in basketball's EuroLeague," European Journal of Operational Research, Elsevier, vol. 309(1), pages 359-370.
    9. Christopher Magee & Amy Wolaver, 2023. "Crowds and the Timing of Goals and Referee Decisions1," Journal of Sports Economics, , vol. 24(6), pages 801-828, August.
    10. Peter-J. Jost, 2021. "Competitive Balance and the Away Goals Rule During Extra Time," Journal of Sports Economics, , vol. 22(7), pages 823-863, October.
    11. Jeremy K. Nguyen & Adam Karg & Abbas Valadkhani & Heath McDonald, 2022. "Predicting individual event attendance with machine learning: a ‘step-forward’ approach," Applied Economics, Taylor & Francis Journals, vol. 54(27), pages 3138-3153, June.
    12. Richard Faltings & Alex Krumer & Michael Lechner, 2023. "Rot‐Jaune‐Verde: On linguistic bias of referees in Swiss soccer," Kyklos, Wiley Blackwell, vol. 76(3), pages 380-406, August.
    13. Bergantiños, Gustavo & Moreno-Ternero, Juan D., 2022. "Monotonicity in sharing the revenues from broadcasting sports leagues," European Journal of Operational Research, Elsevier, vol. 297(1), pages 338-346.
    14. Kai Fischer & Justus Haucap, 2021. "Does Crowd Support Drive the Home Advantage in Professional Football? Evidence from German Ghost Games during the COVID-19 Pandemic," Journal of Sports Economics, , vol. 22(8), pages 982-1008, December.
    15. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germany's programmes for long term unemployed," IAB-Discussion Paper 202005, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    16. Daniel Goller & Sandro Heiniger, 2024. "A general framework to quantify the event importance in multi-event contests," Annals of Operations Research, Springer, vol. 341(1), pages 71-93, October.
    17. Guajardo, Mario & Krumer, Alex, 2023. "Format and schedule proposals for a FIFA World Cup with 12 four-team groups," Discussion Papers 2023/2, Norwegian School of Economics, Department of Business and Management Science.
    18. Michael Christian Leitner & Frank Daumann & Florian Follert & Fabio Richlan, 2023. "The cauldron has cooled down: a systematic literature review on home advantage in football during the COVID-19 pandemic from a socio-economic and psychological perspective," Management Review Quarterly, Springer, vol. 73(2), pages 605-633, June.
    19. Scoppa, Vincenzo, 2021. "Social pressure in the stadiums: Do agents change behavior without crowd support?," Journal of Economic Psychology, Elsevier, vol. 82(C).
    20. Daniel Goller & Maximilian Spath, 2023. "'Good job!' The impact of positive and negative feedback on performance," Papers 2301.11776, arXiv.org.
    21. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Echoes: what happens when football is played behind closed doors?," Economics Discussion Papers em-dp2020-14, Department of Economics, University of Reading.
    22. Farai Jena & Barry Reilly, 2022. "Are spectator preferences weaker for cup compared to league competitions? Evidence from Irish soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 29(9), pages 835-841, May.
    23. Carl Singleton & J. James Reade & Dominik Schreyer, 2023. "A decade of violence and empty stadiums in Egypt: when does emotion from the terraces affect behaviour on the pitch?," Empirical Economics, Springer, vol. 65(3), pages 1487-1507, September.
    24. Thomas Peeters & Jan C. Ours, 2021. "Seasonal Home Advantage in English Professional Football; 1974–2018," De Economist, Springer, vol. 169(1), pages 107-126, February.

  3. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed," Labour Economics, Elsevier, vol. 65(C).
    See citations under working paper version above.

Chapters

  1. Daniel Goller & Michael C. Knaus & Michael Lechner & Gabriel Okasa, 2021. "Predicting match outcomes in football by an Ordered Forest estimator," Chapters, in: Ruud H. Koning & Stefan Kesenne (ed.), A Modern Guide to Sports Economics, chapter 22, pages 335-355, Edward Elgar Publishing.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Downloads through RePEc Services over the past 12 months

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 26 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-BIG: Big Data (12) 2018-11-05 2019-06-17 2019-09-02 2019-09-09 2020-09-07 2020-09-14 2021-06-28 2021-06-28 2021-07-12 2022-02-14 2022-08-22 2022-09-05. Author is listed
  2. NEP-EUR: Microeconomic European Issues (10) 2019-06-17 2019-09-02 2021-05-10 2021-05-17 2021-05-24 2021-06-28 2021-07-12 2022-02-14 2022-08-22 2022-09-05. Author is listed
  3. NEP-LMA: Labor Markets - Supply, Demand, and Wages (10) 2021-05-10 2021-05-17 2021-05-24 2023-12-11 2023-12-18 2024-01-08 2024-01-08 2024-01-08 2024-01-15 2024-08-26. Author is listed
  4. NEP-CMP: Computational Economics (9) 2018-11-05 2019-09-09 2020-09-07 2020-09-14 2021-06-28 2021-07-12 2022-09-05 2023-12-18 2024-01-08. Author is listed
  5. NEP-EDU: Education (5) 2022-02-14 2022-08-22 2022-09-05 2023-12-11 2024-01-08. Author is listed
  6. NEP-SPO: Sports and Economics (5) 2018-11-05 2019-06-17 2020-09-07 2020-09-14 2022-09-05. Author is listed
  7. NEP-HEA: Health Economics (3) 2021-05-10 2021-05-17 2021-05-24
  8. NEP-LAB: Labour Economics (3) 2019-09-02 2021-06-28 2021-07-12
  9. NEP-URE: Urban and Real Estate Economics (3) 2022-02-14 2022-08-22 2022-09-05
  10. NEP-AIN: Artificial Intelligence (2) 2023-12-18 2024-01-08
  11. NEP-ECM: Econometrics (2) 2019-09-02 2019-09-09
  12. NEP-GEN: Gender (2) 2023-02-20 2023-10-16
  13. NEP-HRM: Human Capital and Human Resource Management (2) 2023-02-20 2024-02-12
  14. NEP-NEU: Neuroeconomics (2) 2023-12-18 2024-01-08
  15. NEP-TID: Technology and Industrial Dynamics (2) 2023-12-18 2024-01-08
  16. NEP-CTA: Contract Theory and Applications (1) 2024-02-12
  17. NEP-CUL: Cultural Economics (1) 2019-06-17
  18. NEP-EXP: Experimental Economics (1) 2023-10-16
  19. NEP-GER: German Papers (1) 2023-10-16
  20. NEP-HIS: Business, Economic and Financial History (1) 2022-02-14
  21. NEP-MAC: Macroeconomics (1) 2024-01-08
  22. NEP-PAY: Payment Systems and Financial Technology (1) 2019-09-09
  23. NEP-UPT: Utility Models and Prospect Theory (1) 2022-09-05

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