1) Filter out measurement errors with error message that suggests to explicitly write measurement errors in model definition
2) allow identification checks with correlations, by switching to numerical derivatives
1) allow to compute derivatives starting from NUMERICAL derivatives of jacobian and steady state: this has a minor cost in accuracy and allow apply without errors identification and estimation with numerical derivatives;
2) added trap in dynare_estimation_init: if steadystate changes param values, automaticly shifts to numerical derivs of jacoban and steady state + analytic derivatives of all the rest;
3) bug fixes for 2nd order derivatives w.r.t. model parameters;
Removed globals from DsgeVarLikelihood and changed the calling sequence. As in DsgeLikelihood, the penalty is now a
persistent variable.
Added a global structure for the data: dataset_.
Removed globals from dsgevar_posterior_density and mode_check.
Simplification of the clode, definition of the variable objective_function at the top of dynare_estimation_1 (equal
to 'DsgeLikelihood' or 'DsgeVarLikelihood').