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Goller, Daniel; Heiniger, Sandro (2024). A general framework to quantify the event importance in multi-event contests. Annals of operations research, 341(1), pp. 71-93. Springer 10.1007/s10479-023-05540-x
Goller, Daniel; Wolter, Stefan C. (November 2023). Reaching for Gold! The Impact of a Positive Reputation Shock on Career Choice (IZA Discussion Paper 16607). IZA – Institute of Labor Economics 10.2139/ssrn.4636863
Späth, Maximilian; Goller, Daniel (September 2023). Gender differences in investment reactions to irrelevant information (CEPA Discussion Papers 67). Center for Economic Policy Analysis
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, 93, p. 102372. Elsevier Science 10.1016/j.econedurev.2023.102372
Goller, Daniel; Späth, Maximilian (2023). ‘Good job!’ The impact of positive and negative feedback on performance (arXiv). Cornell University
Goller, Daniel; Gschwendt, Christian; Wolter, Stefan Cornelis (2023). “This time it’s different” Generative Artificial Intelligence and Occupational Choice
Goller, Daniel (2022). Analysing a built-in advantage in asymmetric darts contests using causal machine learning. Annals of operations research, 325(1), pp. 649-679. Springer 10.1007/s10479-022-04563-0
Goller, Daniel; Diem, Andrea; Wolter, Stefan Cornelis (2022). Sitting Next to a Dropout Academic Success of Students with More Educated Peers (Unpublished)
Goller, Daniel; Heiniger, Sandro (2022). A general framework to quantify the event importance in multi-event contests
Goller, Daniel; Knaus, Michael C.; Lechner, Michael; Okasa, Gabriel (2021). Predicting match outcomes in football by an Ordered Forest estimator. In: Koning, Ruud H.; Kesenne, Stefan (eds.) A Modern Guide to Sports Economics (pp. 335-355). Edward Elgar Publishing 10.4337/9781789906530.00026
Goller, Daniel; Wolter, Stefan C. (2021). "Too shocked to search" The COVID-19 shutdowns' impact on the search for apprenticeships. Swiss journal of economics and statistics, 157(1) Springer 10.1186/s41937-021-00075-z
Goller, Daniel (2021). Active labour market policies for the long-term unemployed: New evidence from causal machine learning (Unpublished)
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, 286(2), pp. 740-754. Elsevier 10.1016/j.ejor.2020.03.062
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, 65, p. 101855. Elsevier 10.1016/j.labeco.2020.101855
