We propose an importance-sampling procedure to improve the computational performance of the simulated method of moments (SMM) for the estimation of structural models with fixed parameter heterogeneity. The main advantage of the procedure is that it does not require to simulate observations every time that the structural parameters change during the minimization of the SMM criterion function. We illustrate the use of our method by estimating a neoclassical model of investment for a sample of US manufacturing companies, allowing the technological parameters to vary across firms.