4.75 MB, PDF document
Research output: Working paper
Research output: Working paper
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TY - UNPB
T1 - Machine learning for dynamic incentive problems
AU - Renner, Philipp
AU - Scheidegger, Simon
PY - 2017/11
Y1 - 2017/11
N2 - We propose a generic method for solving infinite-horizon, discrete-time dynamic incentive problems with hidden states. We first combine set-valued dynamic programming techniques with Bayesian Gaussian mixture models to determine irregularly shaped equilibrium value correspondences. Second, we generate training data from those pre-computed feasible sets to recursively solve the dynamic incentive problem by a massively parallelized Gaussian process machine learning algorithm. This combination enables us to analyzemodels of a complexity that was previously considered to be intractable. To demonstrate the broad applicability of our framework, we compute solutions for models of repeated agency with history dependence, many types, and varying preferences.
AB - We propose a generic method for solving infinite-horizon, discrete-time dynamic incentive problems with hidden states. We first combine set-valued dynamic programming techniques with Bayesian Gaussian mixture models to determine irregularly shaped equilibrium value correspondences. Second, we generate training data from those pre-computed feasible sets to recursively solve the dynamic incentive problem by a massively parallelized Gaussian process machine learning algorithm. This combination enables us to analyzemodels of a complexity that was previously considered to be intractable. To demonstrate the broad applicability of our framework, we compute solutions for models of repeated agency with history dependence, many types, and varying preferences.
KW - Dynamic Contracts
KW - Principal-Agent Model
KW - Dynamic Programming
KW - Machine Learning
KW - Gaussian Processes
KW - High-performance Computing
M3 - Working paper
T3 - Economics Working Papers Series
BT - Machine learning for dynamic incentive problems
PB - Lancaster University, Department of Economics
CY - Lancaster
ER -