Statistics seminar 2019 - “Robust decision making for cost minimization under uncertainty”

  • Data: 17 gennaio 2019 dalle 14:30 alle 16:30

  • Luogo: Dipartimento di Scienze Statistiche - via delle Belle Arti 41 - Aula III - 2° piano

Mike Tsionas - University of Lancaster

We propose a minimax regret approach to optimal factor demand under uncertainty. Regret is the deviation of any given decision from the optimal decision based on a specified set of possible scenarios for the uncertain variables. The new approach does not require the specification of instrumental variables to back out unobserved states of nature, neither it requires specifying the number of possible states in advance. Importantly, ex post production shocks can be estimated using the new approach, and full statistical inferences can be performed. Econometric techniques are based on Bayesian analysis using Markov Chain Monte Carlo techniques. A substantive empirical application is provided to illustrate the new techniques.

Prof. Giorgio Tassinari


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