Hi all,
We are currently designing a multi-select stated choice experiment and would really appreciate some advice on whether the analysis we have in mind is practical in Apollo before we finalize the design.
Our setup is:
21 inside goods plus a no-buy/outside good
Respondents can select multiple items and report a quantity for each, so we observe both participation and continuous consumption
Approximately 3,000 respondents completing 10 choice tasks each, giving 30,000 panel observations
We are planning to estimate and compare an MDCEV model and a nested version. Ideally, we would like to consider specifications both with and without a budget constraint and allow for random heterogeneity across respondents.
Our main question is whether this scale is reasonable for these models in Apollo, particularly once we introduce continuous mixing. Are there practical limits or challenges we should anticipate in terms of runtime, number of draws, identification, or convergence?
Any guidance from those who have estimated similar models in Apollo would be greatly appreciated.
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Runtime and convergence for large multi-select MDCEV models
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stephanehess
- Site Admin
- Posts: 1370
- Joined: 24 Apr 2020, 16:29
Re: Runtime and convergence for large multi-select MDCEV models
Hi
the version without mixing should not cause problems, especially as the forthcoming version of Apollo will include analytical gradients for MDCEV and MDCNEV. For the version with mixing, you'll want to ensure you run this on a machine with sufficient RAM and a large number of cores
Stephane
the version without mixing should not cause problems, especially as the forthcoming version of Apollo will include analytical gradients for MDCEV and MDCNEV. For the version with mixing, you'll want to ensure you run this on a machine with sufficient RAM and a large number of cores
Stephane