Analysis of Factors Affecting Economic Growth in Bangka Belitung Province, Indonesia With LSDV and FGLS Methods

Darman Saputra

MPRA Paper from University Library of Munich, Germany

Abstract: The Least Square Dummy Variable (LSDV) method can be used to estimate parameters in the panel data regression model incomplete one-way fixed effect. To produce the best model with GDP data of GRASB. Variables that do not occur heteroscedasticity and models that meet the smallest sum square of error is the variable Mining and Processing Industry, this variable affects the per capita income. The Feasible Generalized Least Square (FGLS) method can be used to estimate the regression parameters for incomplete panel data for a one-way random effect. In this model produce the best model with non-oil and gas GRDP data. The variables that fulfil it are the processing Industry, service, and agriculture of Forestry and Fishery. Therefore looking at the above model can be concluded non-oil and Gas GRDP has three factors that affect per capita income in Bangka Belitung. This should be a reference of local governments to further improve the quality or production in agriculture and services because this potential is more promising for the future. Software used to analyze data in this paper is with R.

Keywords: Heteroscedasticity; Panel data is not complete; Least Square Dummy Variable (lSDV); Feasible Generalized Least Square (FGLS); R. (search for similar items in EconPapers)
JEL-codes: O41 O47 (search for similar items in EconPapers)
Date: 2017-01-30
New Economics Papers: this item is included in nep-sea
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/84676/1/MPRA_paper_84676.pdf original version (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:pra:mprapa:84676

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().