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Minimum Distance Estimation Of Nonstationary Time Series Models

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  • Moon, Hyungsik Roger
  • Schorfheide, Frank

Abstract

This paper analyzes the limit distribution of minimum distance (MD) estimators for nonstationary time series models that involve nonlinear parameter restrictions. A rotation for the restricted parameter space is constructed to separate the components of the MD estimator that converge at different rates. We derive regularity conditions for the restriction function that are easier to verify than the stochastic equicontinuity conditions that arise from direct estimation of the restricted parameters. The sequence of matrices that is used to weigh the discrepancy between the unrestricted estimates and the restriction function is allowed to have a stochastic limit. For MD estimators based on unrestricted estimators with a mixed normal asymptotic distribution the optimal weight matrix is derived and a goodness-of-fit test is proposed. Our estimation theory is illustrated in the context of a permanent-income model and a present-value model.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 18 (2002)
Issue (Month): 06 (December)
Pages: 1385-1407

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Handle: RePEc:cup:etheor:v:18:y:2002:i:06:p:1385-1407_18

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Cited by:
  1. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  2. Hnatkovska, Viktoria & Marmer, Vadim & Tang, Yao, 2008. "Comparison of Misspecified Calibrated Models: The Minimum Distance Approach," Micro Theory Working Papers vadim_marmer-2008-14, Microeconomics.ca Website, revised 28 Sep 2011.

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