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Economic dynamics : theory and computation

Stachurski, John - 2022 - Second edition

Persistent link: https://www.econbiz.de/10013041036

Economic dynamics : theory and computation

Stachurski, John - 2009

Persistent link: https://www.econbiz.de/10013481462

Optimal timing of decisions : a general theory based on continuation values

Ma, Qingyin; Stachurski, John - In: Journal of economic dynamics & control 101 (2019), pp. 62-81

Persistent link: https://www.econbiz.de/10012131026

Continuous state dynamic programming via nonexpansive approximation

Stachurski, John (contributor) - 2006

Persistent link: https://www.econbiz.de/10003289625

Fitted value function iteration with probability one contractions

Pál, Jenő; Stachurski, John - In: Journal of economic dynamics & control 37 (2013) 1, pp. 251-264

Persistent link: https://www.econbiz.de/10009703597

Dynamic programming deconstructed : transformations of the Bellman equation and computational efficiency

Ma, Qingyin; Stachurski, John - In: Operations research 69 (2021) 5, pp. 1591-1607

Persistent link: https://www.econbiz.de/10012661074

Dynamic programming with state-dependent discounting

Stachurski, John; Zhang, Junnan - In: Journal of economic theory 192 (2021), pp. 1-36

Persistent link: https://www.econbiz.de/10012805413

Coase meets Bellman : dynamic programming for production networks

Kikuchi, Tomoo; Nishimura, Kazuo; Stachurski, John; … - In: Journal of economic theory 196 (2021), pp. 1-25

Persistent link: https://www.econbiz.de/10012813353

Unbounded dynamic programming via the Q-transform

Ma, Qingyin; Stachurski, John; Akira Toda, Alexis - In: Journal of mathematical economics 100 (2022), pp. 1-13

Persistent link: https://www.econbiz.de/10013367209

Fitted value function iteration with probability one contractions

Pál, Jenő; Stachurski, John - In: Journal of Economic Dynamics and Control 37 (2013) 1, pp. 251-264

This paper studies a value function iteration algorithm based on nonexpansive function approximation and Monte Carlo integration that can be applied to almost all stationary dynamic programming problems. The method can be represented using a randomized fitted Bellman operator and a corresponding...

Persistent link: https://www.econbiz.de/10011051986