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Different theories of expectation formation and learning usually yield different outcomes for realized market prices in … dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental …
Persistent link: https://www.econbiz.de/10011333266
Persistent link: https://www.econbiz.de/10003314828
estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic …
Persistent link: https://www.econbiz.de/10011381034
We apply the dynamic stochastic framework proposed by recent evolutionaryliterature to the class of strict supermodular games when two simplebehavior rules coexist in the population, imitation and myopic optimization.We assume that myopic optimizers are able to see how well their payoff...
Persistent link: https://www.econbiz.de/10011302143
macroeconomic models in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous … estimate it empirically. Two prominent learning algorithms are considered, namely constant gain and decreasing gain learning …. For each of the two learning rules, the analysis proceeds in two stages. First, the paper derives the asymptotic …
Persistent link: https://www.econbiz.de/10011333062
learning strategy will be used, because each performs better when it is less popular. Despite that, clustering may occur if … players choose their learning strategy on the basis of largely similar information. Finally, on average players will play Hawk …
Persistent link: https://www.econbiz.de/10011348697
The novelty of our model is to combine models of collective action on networks with models of social learning. Agents …
Persistent link: https://www.econbiz.de/10010227321
Persistent link: https://www.econbiz.de/10010191331
We study social learning in a social network setting where agents receive independent noisy signals about the truth …
Persistent link: https://www.econbiz.de/10011801379
, Simpson, and Gelman(2018), to a setting where dynamic learning occurs about features of predictive densities of possibly … misspecified models. This improves the averaging process of good and bad model forecasts. We summarise how this learning is done in … connection with machine learning. We illustrate our suggestion using results from Ba̧stürk, Borowska, Grassi, Hoogerheide, and …
Persistent link: https://www.econbiz.de/10011895574