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Estimation of Structural Vector Autoregressive Models Helmut Lütkepohl In: Communications for Statistical Applications and Methods 24 (2017), 5, S. 421-441

Abstract:

In this survey, estimation methods for structural vector autoregressive models are presented in a systematic way. Both frequentist and Bayesian methods are considered. Depending on the model setup and type of restrictions, least squares estimation, instrumental variables estimation, method-of-moments estimation and generalized method-of-moments are considered. The methods are presented in a unified framework that enables a practitioner to find the most suitable estimation method for a given model setup and set of restrictions. It is emphasized that specifying the identifying restrictions such that they are linear restrictions on the structural parameters is helpful. Examples are provided to illustrate alternative model setups, types of restrictions and the most suitable corresponding estimation methods.

Keywords:

Bayesian estimation, maximum likelihood estimation, generalized method-of-moments, method-of-moments, instrumental variables, structural vector autoregression