The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation
Erik Biorn
No 02/2012, Memorandum from Oslo University, Department of Economics
Abstract:
The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors is assumed. Two specializations of GMM are considered: (i) using instruments (IVs) in levels for a differenced version of the equation, (ii) using IVs in differences for an equation in levels. Index sets for lags and lags are convenient in examining how the potential IV set, satisfying orthogonality and rank conditions, changes when the memory pattern changes. The joint occurrence of measurement errors with long memory may sometimes give an IV-set too small to make estimation possible. On the other hand, problems of ‘IV proliferation’ and ‘weak IVs’ may arise unless the time-series length is small. An application based on data for (log-transformed) capital stock and output from Norwegian manufacturing firms is discussed. Finite sample biases and IV quality are illustrated by Monte Carlo simulations. Overall, with respect to bias and IV strength, GMM inference using the level version of the equation seems superior to inference based on the equation in differences.
Keywords: Panel data; Measurement error; Dynamic modeling; ARMA model; GMM; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: C21 C23 C31 C33 C51 E21 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2012-02-13
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.sv.uio.no/econ/english/research/unpubl ... 012/Memo-02-2012.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hhs:osloec:2012_002
Access Statistics for this paper
More papers in Memorandum from Oslo University, Department of Economics Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway. Contact information at EDIRC.
Bibliographic data for series maintained by Mari Strønstad Øverås ().