Local identification in DSGE models

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Identification and frequency domain quasi-maximum likelihood estimation of linearized dynamic stochastic general equilibrium models (2012, unknown): “We now compare the above analysis with those of Iskrev (2010) and Komunjer and Ng (2011). Iskrev (2010) suggested to identify the parameters from the mean and the first T autocovariances of the observables. Because his result (Theorem 2) assumes T is finite, the resulting conditions are sufficient b”
Evaluating the strength of identification in DSGE models. An a priori approach (2010, methodology): “which applies to any estimation approach that utilizes only first and second moments of the data, is developed in Iskrev (2010). Applying that result, one can determine if θ is identifiable from, for instance, the covariance and first-order autocovariance matrix of some observable endogenous variabl”
Dynamic Identification of Dynamic Stochastic General Equilibrium Models (2011, methodology): “Iskrev (2010) used it to numerically evaluate the T analytical autocovariances, while Qu and Tkachenko (2010) used it to evaluate the discretized spectral density.”