Spatial Econometric Model of Poverty in Java Island
American Journal of Theoretical and Applied Statistics
Volume 4, Issue 6, November 2015, Pages: 420-425
Received: Aug. 26, 2015;
Accepted: Sep. 15, 2015;
Published: Sep. 26, 2015
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Mulugeta Aklilu Zewdie, Department of Statistics, Faculty of Natural and Computational Science, Mekelle University, Mekelle, Ethiopia
M. Nur Aidi, Department of Statistics, Faculty of Mathematics and Science, Bogor Agricultural University, Bogor, Indonesia
Bagus Sartono, Department of Statistics, Faculty of Mathematics and Science, Bogor Agricultural University, Bogor, Indonesia
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This paper gives the concept of spatial econometric model and applies it to analyze the spatial dimensions of poverty and its determinants using data from Java Island 2010 census survey, for 105 districts of Java Island. Dependent variable used in this research is percentage of poverty rate at particular district and predictors are some selected variables that are correlated to poverty. Weighted matrix is obtained by using queen contiguity criteria and four statistical models are applied to the data, Ordinary Least Square regression model, Spatial Error Model, Spatial Lag Model and Spatial Durbin Model. It is shown that the OLS estimates of the poverty function suffer from spatial effects that indicated the OLS model are miss specified since Moran Index test also confirmed the existence of spatial autocorrelation. LM and Robust LM are used for testing the existence of spatial effect. The Likelihood Ratio common factor test and AIC are used for model selection criteria. Gauss Markov Assumptions are done and the Spatial Lag model proved to be better than other model for a given data and the result shows that Education and Working hours has significant impact on poverty.
Poverty, Spatial Effects, Econometrics, Spatial Error Model, Special Lag Model, Spatial Durbin Model, LM, Robust LM, LRcom, Gauss-Markov &AIC
To cite this article
Mulugeta Aklilu Zewdie,
M. Nur Aidi,
Spatial Econometric Model of Poverty in Java Island, American Journal of Theoretical and Applied Statistics.
Vol. 4, No. 6,
2015, pp. 420-425.
Anselin L. 1988. Spatial Econometrics: Methods and Model, Kluwer, Dordrecht.
Anselin L. 2001. Spatial Econometrics, in a companion to Theoretical Econometrics (Baltagi B. H., ed). Blackwell, Oxford.
Anselin L. 2010. Lagrange multiplier diagnostics for spatial dependence and heterogeneity, Geographical Analysis Willy on line library.
Andrew Mckay and David Lawson 2003. Assessing the Extent and Nature of Chronic Poverty in Low Income Countries: Issues and Evidence, University of Nottingham, UK.
Andy M. & Emilie P. 2011. How strong is the evidence for the existence of poverty traps? A multi country assessment, Working Paper series.
Ann H. 2007. Globalization and Poverty, NBER Books, National Bureau of Economic Research.
Coudouel A., Jesko H. and Quentin W. 2002. Poverty Measurement and Analysis, in the PRSP Sourcebook, World Bank, Washington D. C.
Giuseppe A. 2006. Spatial Econometrics Statistical Foundations and Applications to Regional Convergence, Italy.
Hentschel J., Lanjouw P. and Poggi J. 2000. Combining census and survey data to trace the spatial dimensions of poverty: a case study of Ecuador. World Bank Econ.
Jay lee and David W. 2001. Statistical analysis with arc view GIS, John Wiley, New York.
Lesage James P. 1999. The Theory and Practice of Spatial Econometrics, Department of Economics University of Toledo.
Lesage J. and Pace K. 2009.Introduction to Spatial Econometrics, Boca Raton: CRC Press.
Mur J. and Angulo A. 2006. The Spatial Durbin Model and the Common Factor Tests, Spatial Economic Analysis.
National Development Planning Agency (BAPPENAS) 2010. Report on the Achievement of the Millennium Development Goals Indonesia.
Paraguas F. & Anton A. 2005. Spatial Econometrics Modeling of Poverty paper presented on the 8th WSEAS International Conference on applied mathematics, Tenerife, Spain.
Pebley R. and Sastry N. 2003. Neighborhoods, Poverty and Children’s Well-being, University of California, Los Angeles.
Rawlings J., Sastry G. Pentula, David A. 1998. Applied Regression Analysis A Research Tool Second Edition. Raleigh, North Carolina USA.
Sohair F. 2013. Application of Spatial Regression Models to Income Poverty Ratios in Middle Delta Contiguous Counties in Egypt. Tanta University, Tanta, Egypt
Székely M., N. Lustig, M. Cumpa, J. Antonio M. 2000. Do We Know How Much Poverty There Is? Inter-American Development Bank, Felipe Herrera Library.