arXiv 6 Apr 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2404.04494 · PDF · DOI · OpenAlex · Extracted main text
This study investigates computationally efficient inner-loop algorithms for estimating static/dynamic BLP models. It provides the following ideas for reducing the number of inner-loop iterations: (1). Add a term relating to the outside option share in the BLP contraction mapping; (2). Analytically represent the mean product utilities as a function of value functions and solve for value functions (for dynamic BLP); (3). Combine an acceleration method of fixed-point iterations, especially the Anderson acceleration. They are independent and easy to implement. This study shows the good performance of these methods using numerical experiments.
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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 | Nevo, A (2001) Measuring market power in the ready-to-eat cereal industry | 1.000 | 8 | 3 | 100% |
| 2 | Sun, Y. and Ishihara, M (2019) A computationally efficient fixed point approach to dynamic structural demand estimation | 0.956 | 8 | 4 | 88% |
| 3 | Pál, L. and Sándor, Z (2023) Comparing procedures for estimating random coefficient logit demand models with a special focus on obtaining global optima | 0.950 | 7 | 5 | 86% |
| 4 | Gowrisankaran, G. and Rysman, M (2012) Dynamics of consumer demand for new durable goods | 0.950 | 7 | 4 | 86% |
| 5 | Berry, S., Levinsohn, J., and Pakes, A (1999) Voluntary export restraints on automobiles: Evaluating a trade policy | 0.928 | 10 | 4 | 80% |
| 6 | Berry, S., Levinsohn, J., and Pakes, A (1995) Automobile prices in market equilibrium | 0.923 | 14 | 5 | 79% |
| 7 | Conlon, C. and Gortmaker, J (2020) Best practices for differentiated products demand estimation with PyBLP | 0.902 | 15 | 7 | 73% |
| 8 | Lee, J. and Seo, K (2015) A computationally fast estimator for random coefficients logit demand models using aggregate data | 0.894 | 7 | 6 | 71% |
| 9 | Dubé, J.-P., Fox, J. T., and Su, C.-L (2012) Improving the numerical performance of static and dynamic aggregate discrete choice random coefficients demand estimation | 0.860 | 11 | 6 | 64% |
| 10 | Berry, S. T (1994) Estimating discrete-choice models of product differentiation | 0.843 | 4 | 3 | 75% |
Showing the top 10 of 41 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Sequential algorithm for structural estimations with equilibrium constraints | 0.860 | 11 | 4 |