arXiv 20 Nov 2019 · Econometrics · 1 citations (OpenAlex)
arXiv:1911.09128 · PDF · DOI · OpenAlex · Extracted main text
Quasi-Monte Carlo (qMC) methods are a powerful alternative to classical Monte-Carlo (MC) integration. Under certain conditions, they can approximate the desired integral at a faster rate than the usual Central Limit Theorem, resulting in more accurate estimates. This paper explores these methods in a simulation-based estimation setting with an emphasis on the scramble of Owen (1995). For cross-sections and short-panels, the resulting Scrambled Method of Moments simply replaces the random number generator with the scramble (available in most softwares) to reduce simulation noise. Scrambled Indirect Inference estimation is also considered. For time series, qMC may not apply directly because of a curse of dimensionality on the time dimension. A simple algorithm and a class of moments which circumvent this issue are described. Asymptotic results are given for each algorithm. Monte-Carlo examples illustrate these results in finite samples, including an income process with "lots of heterogeneity."
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Gouriéroux, C., Monfort, A. and Renault, E (1993) Indirect inference | 1.000 | 10 | 4 | 100% |
| 2 | Duffie, D. and Singleton, K (1993) Simulated Moments Estimation of Markov Models of Asset Prices | 0.928 | 4 | 3 | 100% |
| 3 | Owen, A. B (1995) Randomly permuted (t, m, s)-nets and (t, s)-sequences | 0.928 | 4 | 3 | 100% |
| 4 | Browning, M., Ejrnaes, M. and Alvarez, J (2010) Modelling Income Processes with Lots of Heterogeneity | 0.874 | 5 | 2 | 100% |
| 5 | Lemieux, C (2009) Monte Carlo and Quasi-Monte Carlo Sampling | 0.874 | 5 | 2 | 100% |
| 6 | Jennrich, R. I (1969) Asymptotic properties of non-linear least squares estimators | 0.763 | 6 | 2 | 67% |
| 7 | White, H (1984) Asymptotic Theory for Econometricians | 0.737 | 4 | 3 | 50% |
| 8 | van der Vaart, A. W. and Wellner, J. A (1996) Weak Convergence and Empirical Processes | 0.737 | 3 | 3 | 67% |
| 9 | Pakes, A. and Pollard, D (1989) Simulation and the Asymptotics of Optimization Estimators | 0.737 | 3 | 2 | 100% |
| 10 | Dick, J. and Pillichshammer, F (2010) Digital Nets and Sequences | 0.693 | 5 | 1 | 100% |
Showing the top 10 of 46 scored citations.