In econometrics, the method of simulated moments (MSM) (also called simulated method of moments[1]) is a structural estimation technique introduced by Daniel McFadden.[2] It extends the generalized method of moments to cases where theoretical moment functions cannot be evaluated directly, such as when moment functions involve high-dimensional integrals. MSM's earliest and principal applications have been to research in industrial organization, after its development by Ariel Pakes, David Pollard, and others, though applications in consumption are emerging. Although the method requires the user to specify the distribution from which the simulations are to be drawn, this requirement can be
relaxed through the use of an entropy maximizing distribution.[3]
^Cooper, Russell; Haltiwanger, John; Willis, Jonathan L. (May 2007). "Implications of Search Frictions: Matching Aggregate and Establishment-level Observations". NBER Working Paper No. 13115. doi:10.3386/w13115.
^McFadden, D. (1989). "A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration" (PDF). Econometrica. 57 (5): 995–1026. doi:10.2307/1913621. hdl:1721.1/63887. JSTOR 1913621.
^Schennach, S. M. (2014). "Entropic Latent Variable Integration via Simulation". Econometrica. 82 (1): 345–385. doi:10.3982/ECTA9748. hdl:10419/79553.
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