Estimators for persistent and possibly non-stationary data with classical properties / Yuriy Gorodnichenko, Anna Mikusheva, Serena Ng.

Author/creator Gorodnichenko, Yuriy
Other author Mikusheva, Anna.
Other author Ng, Serena.
Other author National Bureau of Economic Research.
Format Electronic
Publication InfoCambridge, MA : National Bureau of Economic Research,
Supplemental ContentFull text available from NBER Working Papers

SeriesNBER working paper series ; working paper 17424
Working paper series (National Bureau of Economic Research : Online) ; working paper no. 17424. UNAUTHORIZED
Summary "This paper considers a moments based non-linear estimator that is root-T consistent and uniformly asymptotically normal irrespective of the degree of persistence of the forcing process. These properties hold for linear autoregressive models, linear predictive regressions, as well as certain non-linear dynamic models. Asymptotic normality is obtained because the moments are chosen so that the objective function is uniformly bounded in probability and that a central limit theorem can be applied.Critical values from the normal distribution can be used irrespective of the treatment of the deterministic terms. Simulations show that the estimates are precise, and the t-test has good size in the parameter region where the least squares estimates usually yield distorted inference"--National Bureau of Economic Research web site.
General noteTitle from PDF file as viewed on 12/1/2011.
Bibliography noteIncludes bibliographical references.
Access restrictionAvailable only to authorized users.
Other formsAlso available in print.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2011657359

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