- LancasterWP2020_010
Final published version, 346 KB, PDF document

Research output: Working paper

Published

**An augmented first-order approach for incentive problems.** / Renner, Philipp.

Research output: Working paper

Renner, P 2020 'An augmented first-order approach for incentive problems' Economics Working Papers Series, Lancaster University, Department of Economics, Lancaster.

Renner, P. (2020). *An augmented first-order approach for incentive problems*. (Economics Working Papers Series). Lancaster University, Department of Economics.

Renner P. An augmented first-order approach for incentive problems. Lancaster: Lancaster University, Department of Economics. 2020 May 28. (Economics Working Papers Series).

@techreport{c04dff55358c48478bb79a47f25eadd5,

title = "An augmented first-order approach for incentive problems",

abstract = "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.",

keywords = "incentive constraints, fi rst order approach, parametric optimization, value function approach",

author = "Philipp Renner",

year = "2020",

month = may,

day = "28",

language = "English",

series = "Economics Working Papers Series",

publisher = "Lancaster University, Department of Economics",

type = "WorkingPaper",

institution = "Lancaster University, Department of Economics",

}

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 -