Sparse indirect inference

In this paper we propose a sparse indirect inference estimator. In order to achieve sparse estimation of the parameters, the Smoothly Clipped Absolute Deviation (SCAD) L1–penalty of Fan and Li (2001) is added into the indirect inference objectivefunctionintroducedbyGouri ́erouxetal.(1993).Wederivetheasymptotic theory and we show that the sparse–Indirect Inference estimator enjoys the oracle properties under mild regularity conditions. The method is applied to estimate the parameters of large dimensional non–Gaussian regression models

Country

Italy

Related Organizations

Sapienza University of Rome
Italy

Keywords

Indirect inference; sparse regularisation; SCAD penalty; stable non– Gaussian models

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