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Estimators for Persistent and Possibly Non-Stationary Data with Classical Properties / Yuriy Gorodnichenko, Anna Mikusheva, Serena Ng.
- Format:
- Book
- Author/Creator:
- Gorodnichenko, Yuriy.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w17424.
- NBER working paper series no. w17424
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2011.
- 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.
- Notes:
- Print version record
- September 2011.
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