Research
Interest
Causal Machine Learning, Economics of Education, Labor Economics, 'Using Data from Sports to Answer Economic Questions', Microeconometrics, Econometrics, Statistical Learning,
Working / Discussion Papers
Brox, Enzo & Goller, Daniel. 2024 "Tournaments, Contestant Heterogeneity and Performance" working paper
Goller, Daniel & Gschwendt Christian & Wolter, Stefan C., 2023 "'This time it's different' Generativ artificial intelligence and occupational choice" working paper; Media: SRF Tagesschau 02.12.2023 (Hauptausgabe)
Goller, Daniel & Wolter, Stefan C., 2023. "Reaching for Gold! The impact of a positive reputation shock on career choice" working paper; Media: Der Bund (german) IZA World of Labor (english)
Goller, Daniel & Späth, Maximilian, 2023. "'Good Job!' The impact of positive and negative feedback on performance" working paper
Späth, Maximilian & Goller, Daniel, 2023. "Gender differences in investment reactions to irrelevant information" working paper; pre-analysis plan
Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning" working paper
Peer Reviewed Journals
"A general framework to quantify the event importance in multi-event contests", with Heiniger, Sandro, 2023, Annals of Operations Research. https://doi.org/10.1007/s10479-023-05540-x (working paper) Replication Code & Event Importance Values
"Sitting next to a dropout: Academic success of students with more educated peers", with Diem, Andrea, & Wolter, Stefan C., 2023, Economics of Education Review, 93, 102372. (working paper)
"Analysing a built-in advantage in asymmetric darts contests using causal machine learning", 2023, Annals of Operations Research, 325(1): 649-679. (working-paper)
"'Too shocked to search' The COVID-19 shutdowns' impact on the search for apprenticeships", with Wolter, Stefan C., 2021, Swiss Journal of Economics and Statistics, 157 (6): 1-15. (working paper); Media: Aargauer Zeitung (german)
"Let's meet as usual: Do games played on non-frequent days differ? Evidence from top European soccer leagues", with Krumer, Alex, 2020, European Journal of Operational Research, 286 (2): 740-754 (working paper)
"Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germany's Programmes for Long Term Unemployed", with Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020, Labour Economics, 65 (working paper)
Book chapters
"Predicting Match Outcomes in Football by an Ordered Forest Estimator", with Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2021 Chapter 22 in A Modern Guide to Sports Economics, ed. Ruud H. Koning & Stefan Kesenne, https://doi.org/10.4337/9781789906530.00026 (working paper)
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