# DSGE estimation/inference game?

**URL:** <https://discourse.julialang.org/t/dsge-estimation-inference-game/63364>\
**Category:** Finance and Economics\
**Created:** [June 22, 2021, 1:23pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364 "2021-06-22T13:23:23Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![mcreel](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mcreel/32/30088_2.png) [@mcreel](https://discourse.julialang.org/u/mcreel)\
**Post date:** [June 22, 2021, 1:23pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364/1 "2021-06-22T13:23:23Z")

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I’ve been working on a method for estimating a DSGE model and doing inference on parameters, and it seems to work pretty well, for a fairly simple model ([https://github.com/mcreel/SimulatedNeuralMoments.jl/tree/main/examples/DSGE](https://github.com/mcreel/SimulatedNeuralMoments.jl/tree/main/examples/DSGE)). It’s fast enough so that Monte Carlo is possible. I’d be interested to see how other estimation methods compare, either for the model I used, or for some other model, and I’m hoping people might be willing to propose models and perhaps share results obtained using other methods. This sort of game might help to develop use of Julia for estimation/inference methods for DSGE models, and we might also learn more about how reliable are the methods that are used. Any interest and/or ideas about how to run such a game?

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**Author:** ![mschauer](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mschauer/32/13946_2.png) [@mschauer](https://discourse.julialang.org/u/mschauer)\
**Post date:** [June 22, 2021, 1:55pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364/2 "2021-06-22T13:55:45Z")

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What is DSGE? Not everyone knows, neither do I.

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**Author:** ![fbanning](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/fbanning/32/14972_2.png) [@fbanning](https://discourse.julialang.org/u/fbanning)\
**Post date:** [June 22, 2021, 1:58pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364/3 "2021-06-22T13:58:59Z")

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> [@mschauer](#):
>
> What is DSGE?

> **[Dynamic stochastic general equilibrium](https://en.wikipedia.org/wiki/Dynamic_stochastic_general_equilibrium)**
>
> Dynamic stochastic general equilibrium modeling (abbreviated as DSGE, or DGE, or sometimes SDGE) is a macroeconomic method which is often employed by monetary and fiscal authorities for policy analysis, explaining historical time-series data, as well as future forecasting purposes. DSGE econometric modelling applies general equilibrium theory and microeconomic principles in a tractable manner to postulate economic phenomena, such as economic growth and business cycles, as well as policy effect As...

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**Author:** ![tbeason](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tbeason/32/15898_2.png) [@tbeason](https://discourse.julialang.org/u/tbeason)\
**Post date:** [June 22, 2021, 2:00pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364/4 "2021-06-22T14:00:20Z")

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Sounds interesting. I’d guess you’d want to fix the model and the inputs and only focus on the estimation methods for this purpose.

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**Author:** ![mcreel](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mcreel/32/30088_2.png) [@mcreel](https://discourse.julialang.org/u/mcreel)\
**Post date:** [June 22, 2021, 2:14pm UTC](https://discourse.julialang.org/t/dsge-estimation-inference-game/63364/5 "2021-06-22T14:14:43Z")

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My way of thinking of a standard problem would be: (1) a model that can be used to generate data, given parameters, (2) a prior or parameter space for the parameters, and (3) a design vector of true parameters. Given those things, people could apply different methods to estimate the parameters and compute confidence (credible) intervals. Then, by Monte Carlo, RMSE, confidence interval coverage, and other measures of interest could be computed, using whatever method the user likes. If the standard problems were agreed on, then different users could report their results. Perhaps all of this could be put into a git repository, to facilitate and centralize it, if there were interested users.