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Estimation and Inference by Stochastic Optimization: Three Examples

Jean-Jacques Forneron, Serena Ng

arXiv 20 Feb 2021 · Econometrics · publishedAEA Papers and Proceedings (2021)

arXiv:2102.10443 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper illustrates two algorithms designed in Forneron & Ng (2020): the resampled Newton-Raphson (rNR) and resampled quasi-Newton (rqN) algorithms which speed-up estimation and bootstrap inference for structural models. An empirical application to BLP shows that computation time decreases from nearly 5 hours with the standard bootstrap to just over 1 hour with rNR, and only 15 minutes using rqN. A first Monte-Carlo exercise illustrates the accuracy of the method for estimation and inference in a probit IV regression. A second exercise additionally illustrates statistical efficiency gains relative to standard estimation for simulation-based estimation using a dynamic panel regression example.

Citation extraction

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1J. Forneron \ S. Ng (2020) Estimation and Inference by Stochastic Optimization0.92843100%
2Russell Davidson \ James G. MacKinnon (1999) Bootstrap Testing in Nonlinear Models0.64422100%
3A. Nevo (2000) A Practitioner's Guidel to Estimation of Random-Coefficietns Logit Models of demand0.51121100%
4D. W. K. Andrews (2002) Higher-Order Improvements of a Computationally Attractive k-Step Bootstrap for Extremum Estimators0.40511100%
5Steven Berry, James Levinsohn \ Ariel Pakes (1995) Automobile Prices in Market Equilibrium0.40511100%
Gourieroux2010unmatched citation key Gourieroux20100.40511100%
Honore2017unmatched citation key Honore20170.40511100%
8Patrick Kline \ Andres Santos (2012) A Score Based Approach to Wild Bootstrap Inference0.40511100%
9Daniel Brunner, Florian Heiss, André Romahn \ Constantin Weiser (2017) Reliable estimation of random coefficient logit demand models. DICE Discussion Paper0.40511100%

Showing the top 9 of 9 scored citations. 2 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Estimation and Inference by Stochastic Optimization0.84333
2Fast Inference for Quantile Regression with Tens of Millions of Observations0.40511