MULTIVARIATE METHOD OF SIMULATED QUANTILES

Paola Stolfi, Mauro Bernardi and Lea Petrella

No 212, Departmental Working Papers of Economics - University 'Roma Tre' from Department of Economics - University Roma Tre

Abstract: In this paper the Method of Simulated Quantiles (MSQ) of Dominicy and Veredas (2013) is extended to a multivariate framework by introducing the Multivariate Method of Simulated Quantiles (MMSQ). In order to build the MMSQ procedure we rely on the definition of projectional quantile which allows us to estimate in the optimal way all the parameters involved in the multivariate setting. We provide asymptotic results underlying the MMSQ estimator. As a further improvement we introduce a penalty function in the procedure in order to account for sparsity by using the Smoothly Clipped Absolute Deviation function. Oracle properties are showed for the penalized MMSQ estimators while simulation results are considered to highlight the power of the inferential procedure.

Keywords: directional quantiles; method of simulated quantiles; quantile matching; sparsity. (search for similar items in EconPapers)
JEL-codes: C13 C15 C39 (search for similar items in EconPapers)
Pages: 28
Date: 2016-12
New Economics Papers: this item is included in nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:rtr:wpaper:0212

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