Tranquilo: An Optimizer for the Method of Simulated Moments

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.