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Assessing autonomous algorithmic collusion : Q-learning under short-run price commitments
Klein, Timo - 2018 - Revision: September 2018
well-established self-learning algorithm) learns to profitably coordinate on either a fixed price or on asymmetric price …
Persistent link: https://www.econbiz.de/10011869980
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Finite sample evaluation of causal machine learning methods : guidelines for the applied researcher
Naghi, Andrea A.; Wirths, Christian P. - 2021
The econometrics literature proposed several new causal machine learning methods (CML) in the past few years. These methods harness the strength of machine learning methods to flexibly model the relationship between the treatment, outcome and confounders, while providing valid inferential...
Persistent link: https://www.econbiz.de/10012650104
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Critical factors for achieving multiple goals with water tariff systems : combining limited data sources and expert testimony
Dalhuisen, Jasper M.; Nijkamp, Peter - 2001
Persistent link: https://www.econbiz.de/10001633103
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Artificial collusion : examining supracompetitive pricing by Q-learning algorithms
Boer, Arnoud V. den; Meylahn, Janusz M.; Schinkel, … - 2022
We examine recent claims that a particular Q-learning algorithm used by competitors 'autonomously' and systematically … detailed analysis of the inner workings of this algorithm reveals that there is no immediate reason for alarm. We set out what … is needed to demonstrate the existence of a colluding price algorithm that does form a threat to competition. …
Persistent link: https://www.econbiz.de/10013375353
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Possibly ill-behaved posteriors in econometric models
Hoogerheide, Lennart; Dijk, Herman K. van - 2008
Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the likelihood information is allowed to dominate and data information is weak. We explain the issue of highly non-elliptical posteriors in a model for the effect of education on income...
Persistent link: https://www.econbiz.de/10011374406
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A simple strategy to prune neural networks with an application to economic time series
Kaashoek, Johan F.; Dijk, Herman K. van - 1997
A major problem in applying neural networks is specifying the sizeof the network. Even for moderately sized networks the number ofparameters may become large compared to the number of data. In thispaper network performance is examined while reducing the size of thenetwork through the use of...
Persistent link: https://www.econbiz.de/10010371106
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Modelling inter-urban transport flows in Italy : a comparison between neural network analysis and logit analysis
Nijkamp, Peter; Reggiani, Aura; Tritapepe, Tommaso - 1996
Persistent link: https://www.econbiz.de/10000932247
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Analysis of complex networks : an overview of methodologies and a neural network application to intermodal transport in Italy
Nijkamp, Peter; Reggiani, Aura; Tritapepe, Tommaso - 1996
Persistent link: https://www.econbiz.de/10000932260
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On forecasting exchange rates using neural networks
Franses, Philip Hans; Homelen, Paul van - 1996
Persistent link: https://www.econbiz.de/10000945702