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Simultaneous Indirect Inference, Impulse Responses and ARMA Models

Department of Economics, Room C-870 Loeb Building, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6, Canada
Canada Mortgage and Housing Corporation, Homeowner Risk Management, Strategy and Products, 700 Montreal Road, Ottawa, ON K1A 0P7, Canada
Authors to whom correspondence should be addressed.
This work was supported by the Social Sciences and Humanities Research Council of Canada and the Fonds de recherche sur la société et la culture (Québec).
Econometrics 2020, 8(2), 12;
Received: 19 December 2018 / Revised: 11 February 2020 / Accepted: 26 February 2020 / Published: 2 April 2020
(This article belongs to the Special Issue Resampling Methods in Econometrics)
A two-stage simulation-based framework is proposed to derive Identification Robust confidence sets by applying Indirect Inference, in the context of Autoregressive Moving Average (ARMA) processes for finite samples. Resulting objective functions are treated as test statistics, which are inverted rather than optimized, via the Monte Carlo test method. Simulation studies illustrate accurate size and good power. Projected impulse-response confidence bands are simultaneous by construction and exhibit robustness to parameter identification problems. The persistence of shocks on oil prices and returns is analyzed via impulse-response confidence bands. Our findings support the usefulness of impulse-responses as an empirically relevant transformation of the confidence set. View Full-Text
Keywords: Indirect Inference; ARMA; Impulse-Response; Monte Carlo test; Root Cancelation Indirect Inference; ARMA; Impulse-Response; Monte Carlo test; Root Cancelation
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Khalaf, L.; Peraza López, B. Simultaneous Indirect Inference, Impulse Responses and ARMA Models. Econometrics 2020, 8, 12.

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