Tools for the estimation of (structural) econometric models.

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  • License: MIT License (MIT)
  • Author: Janos Gabler
  • Tags econometrics, statistics, estimation, extremum estimation, optimization, inference, numerical differentiation, finite differences, richardson extrapolation, derivative free optimization, method of simulated moments, maximum likelihood
  • Requires: Python >=3.8
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Estimagic is a Python package that helps to build high-quality and user friendly implementations of (structural) econometric models.

It is designed with large structural models in mind. However, it is also useful for any other estimator that numerically minimizes or maximizes a criterion function (Extremum Estimator). Examples are maximum likelihood estimation, generalized method of moments, method of simulated moments and indirect inference.

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Avatar for janosg from gravatar.com janosg Avatar for timmens from gravatar.com timmens

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Project links
Meta
  • License: MIT License (MIT)
  • Author: Janos Gabler
  • Tags econometrics, statistics, estimation, extremum estimation, optimization, inference, numerical differentiation, finite differences, richardson extrapolation, derivative free optimization, method of simulated moments, maximum likelihood
  • Requires: Python >=3.8
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0.5.1

0.5.0

0.5.0rc1 pre-release

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.4

0.2.3

0.2.2

This version

0.2.1

0.2.0

0.0.1

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