statsmodels.gmm contains model classes and functions that are based on estimation with Generalized Method of Moments. Currently the general non-linear case is implemented. An example class for the standard linear instrumental variable model is included. This has been introduced as a test case, it works correctly but it does not take the linear structure into account. For the linear case we intend to introduce a specific implementation which will be faster and numerically more accurate.
Currently, GMM takes arbitrary non-linear moment conditions and calculates the estimates either for a given weighting matrix or iteratively by alternating between estimating the optimal weighting matrix and estimating the parameters. Implementing models with different moment conditions is done by subclassing GMM. In the minimal implementation only the moment conditions, momcond have to be defined.
|GMM(endog, exog, instrument[, nmoms])||Class for estimation by Generalized Method of Moments|
|GMMResults||just a storage class right now|
|IV2SLS(endog, exog[, instrument])||class for instrumental variables estimation using Two-Stage Least-Squares|
not sure what the status is on the following
|IVGMM(endog, exog, instrument[, nmoms])||Class for linear instrumental variables estimation with homoscedastic|
|NonlinearIVGMM(endog, exog, instrument, **kwds)||Class for linear instrumental variables estimation with homoscedastic|
|DistQuantilesGMM(endog, exog, instrument, **kwds)||Estimate distribution parameters by GMM based on matching quantiles|