Final published version, 346 KB, PDF document
Research output: Working paper
Research output: Working paper
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TY - UNPB
T1 - An augmented first-order approach for incentive problems
AU - Renner, Philipp
PY - 2020/5/28
Y1 - 2020/5/28
N2 - Incentive constraints are constraints that are optimization problems themselves.If these problems are non convex then the first order approach fails.We propose an alternative solution method where we use the value function as an additional constraint.This ensures that all solutions are incentive compatible.To get the value function we use a function interpolator like sparse grids.We demonstrate our approach by solving two examples from the literature were it was shown that the first order approach fails.
AB - Incentive constraints are constraints that are optimization problems themselves.If these problems are non convex then the first order approach fails.We propose an alternative solution method where we use the value function as an additional constraint.This ensures that all solutions are incentive compatible.To get the value function we use a function interpolator like sparse grids.We demonstrate our approach by solving two examples from the literature were it was shown that the first order approach fails.
KW - incentive constraints
KW - first order approach
KW - parametric optimization
KW - value function approach
M3 - Working paper
T3 - Economics Working Papers Series
BT - An augmented first-order approach for incentive problems
PB - Lancaster University, Department of Economics
CY - Lancaster
ER -