Template-Type: ReDIF-Paper 1.0
Title: Tranquilo: An Optimizer for the Method of Simulated Moments
Author-Name: Janoś Gabler
Author-Email: janos.gabler@gmail.com
Author-Name: Sebastian Gsell
Author-Email: sebastian.gsell@econ.lmu.de
Author-Name: Tim Mensinger
Author-Email: tmensinger@uni-bonn.de
Author-Name: Mariam Petrosyan
Author-Email: mpetrosyan@uni-bonn.de
Classification-JEL: C61
Keywords: derivative-free optimization, least-squares, trust region methods, stochastic optimization, mathematical software, method of simulated moments estimation

Abstract: We propose the tranquilo algorithm, a trust-region optimizer that aims to facilitate optimization
problems that arise during the method of simulated moments estimation (MSM). The algorithm is
particularly suited for this type of problem as it (1) can utilize the least-squares structure of the
MSM problem, (2) can be parallelized on the level of the algorithm, and (3) can adaptively deal
with noise in the objective function. The adaptive nature of tranquilo makes it particularly suited
for domain experts such as statisticians and social science researchers without extensive training in
numerical optimization. Extensive benchmarks show that tranquilo is competitive with state-of-the-art
algorithms in noise-free settings and outperforms them in the presence of substantial noise.

Note: 
Length: 65
Creation-Date: 2024-04
Revision-Date:
File-URL: https://www.crctr224.de/research/discussion-papers/archive/dp522
File-Format: application/pdf
Handle: RePEc:bon:boncrc:CRCTR224_2024_522