Persistence, Signal-Noise Pattern and Heterogeneity in Panel Data: With an Application to the Impact of Foreign Direct Investment on GDP

Erik Biorn and Xuehui Han

No 04/2015, Memorandum from Oslo University, Department of Economics

Abstract: GMM estimation of autoregressive panel data equations in error-ridden variables when the noise has memory, is considered. The impact of variation in the memory length in signal and noise spread and in the degree of individual heterogeneity are discussed with respect to finite sample bias, using Monte Carlo simulations. Also explored are also the impact of the strength of autocorrelation and the size of the IV set. GMM procedures using IVs in differences on equations in levels, in general perform better in small samples than procedures using IVs in levels on equations in differences. A case-study of the impact of Foreign Direct Investment (FDI) on GDP, inter alia, contrasting the manufacturing and the service sector, based on country panel data supplements the simulation results.

Keywords: Panel data; Measurement error; ARMA; GMM; Error memory; Monte Carlo; Foreign Direct Investment; Economic development; Country panel (search for similar items in EconPapers)
JEL-codes: C21 C23 C31 C33 O11 O14 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2015-02-12
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)
http://www.sv.uio.no/econ/english/research/unpubli ... 015/memo-04-2015.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:2015_004

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 ().