Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 7 Sayı: 1, 68 - 79, 26.04.2020
https://doi.org/10.30897/ijegeo.588032

Öz

Kaynakça

  • Adams, M. D., Kanaroglou, P. S., & Coulibaly, P. (2016). Spatially constrained clustering of ecological units to facilitate the design of integrated water monitoring networks in the St. Lawrence Basin. International Journal of Geographical Information Science, 30(2), 390-404. doi: 10.1080/13658816.2015.1089442
  • Anselin, L., Syabri, I., & Kho, Y. (2006). GeoDa: an introduction to spatial data analysis. Geographical analysis, 38(1), 5-22.
  • Anyanwu, J. C. (2014). Marital Status, Household Size and Poverty in Nigeria: Evidence from the 2009/2010 Survey Data. African Development Review, 26(1), 118-137. doi: 10.1111/1467-8268.12069
  • Ashford, L. S. (2007). Africa’s youthful population: Risk or opportunity, (pp. 4). Washington DC: Population Reference Bureau.Buchanan, K. M., & Pugh, J. C. (1955). Land and people in Nigeria: The human geography of Nigeria and its environmental background: University of London Press.
  • Ceccato, V., & Uittenbogaard, A. C. (2014). Space–Time Dynamics of Crime in Transport Nodes. Annals of the Association of American Geographers, 104(1), 131-150. doi: 10.1080/00045608.2013.846150
  • Central Intelligence Agency. (2015). Nigeria: The World Factbook. Retrieved November 8, 2015, 2015, from https://www.cia.gov/library/publications/the-world-factbook/geos/ni.html
  • Central Intelligence Agency. (2016). Age Structure: The World Factbook. Retrieved November 11, 2017, from https://www.cia.gov/library/publications/the-world-factbook/fields/2010.html
  • Duque, J. C., Anselin, L., & Rey, S. J. (2012). The Max-P-Regions Problem. Journal of Regional Science, 52(3), 397-419. doi: 10.1111/j.1467-9787.2011.00743.x
  • ESRI. (2015). ArcGIS Desktop (Version 10.4). Redlands, CA: Environmental Systems Research Institute.
  • Fan, C., & Myint, S. (2014). A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation. Landscape and Urban Planning, 121(0), 117-128. doi: http://dx.doi.org/10.1016/j.landurbplan.2013.10.002
  • Feyrer, J. (2007). Demographics and productivity. The Review of Economics and Statistics, 89(1), 100-109.
  • Fukuda, S.-I., & Morozumi, R. (2004). Economic growth under the demographic transition: a theory and some international evidence* The Economics of an Ageing Population Macroeconomic Issues. Cheltenham, UK: 'Edward Elgar Publishing, Inc.'.
  • GeoData Insitute. (nd). Alpha version 2010 and 2014 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates. Nigeria: Population per 100 meters grid Cell Retrieved 20th January, 2015, from www.worldpop.org.uk http://esa.un.org/wpp/
  • Griffith, D. A. (1987). Spatial autocorrelation. A Primer. Washington DC: Association of American Geographers.
  • Grineski, S. E., & Collins, T. W. (2010). Environmental injustices in transnational context: urbanization and industrial hazards in El Paso/Ciudad Ju rez. Environment and Planning A, 42(6), 1308-1327.
  • IBM. (2015). IBM SPSS Statistics (Version 23). Armonk, New York: IBM Corporation.
  • Kim, C. W., Phipps, T. T., & Anselin, L. (2003). Measuring the benefits of air quality improvement: a spatial hedonic approach. Journal of environmental economics and management, 45(1), 24-39.
  • Kögel, T. (2005). Youth dependency and total factor productivity. Journal of Development Economics, 76(1), 147-173. doi: http://dx.doi.org/10.1016/j.jdeveco.2003.11.003
  • Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259-263. doi: 10.1127/0941-2948/2006/0130
  • Lawal, O. (2009). Analysis of land use changes in the Thames Gateway: the change-pattern approach. (PhD), University of East London, London.
  • Lawal, O. (2015). Geodemographic analysis of age dependencies in Nigeria. . Port Harcourt Journal of Social Sciences, 6(1&2), 115 – 132.
  • Lawal, O. (2017). Mapping Economic Potential Using Spatial Structure of Age Dependency and Socio-economic factors. African Journal of Applied and Theoretical Economics, Special Edition(November), 32-49.
  • Lawal, O. (2017). Mapping economic potential using spatial structure of age dependency and socio-economic factors. African Journal of Applied and Theoretical Economics, Special Edition(November, 2017), 32-49.
  • Legendre, P. (1987). Constrained clustering Developments in Numerical Ecology (pp. 289-307): Springer.
  • Linard, C., Gilbert, M., Snow, R. W., Noor, A. M., & Tatem, A. J. (2012). Population Distribution, Settlement Patterns and Accessibility across Africa in 2010. PLoS ONE, 7(2), e31743. doi: 10.1371/journal.pone.0031743
  • Longley, P. A., & Tobón, C. (2004). Spatial Dependence and Heterogeneity in Patterns of Hardship: An Intra-Urban Analysis. Annals of the Association of American Geographers, 94(3), 503-519. doi: 10.1111/j.1467-8306.2004.00411.x
  • Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3-42. doi: http://dx.doi.org/10.1016/0304-3932(88)90168-7
  • Miles, D. (1999). Modelling the Impact of Demographic Change Upon the Economy. The Economic Journal, 109(452), 1-36. doi: 10.1111/1468-0297.00389
  • Myrdal, G. (1957). Economic Theory and Under-Development Regions: Gerarld Duckworth.
  • Myrdal, G. (1968). Corruption: Its causes and effects Asian drama: An inquiry into the poverty of nations (Vol. 2, pp. 953-961). New Yor: Pantheon.National Bureau of Statistics. (2012). Nigeria Socio-economic Indicators. Retrieved from: http://nigeria.opendataforafrica.org/rugbred/nigeria-socio-economic-indicators-november-2012
  • Pirani, E. (2014). Youth Dependency Ratio Encyclopedia of Quality of Life and Well-Being Research (pp. 7287-7288): Springer.
  • Prskawetz, A., Fent, T., Barthel, W., Crespo-Cuaresma, J., Lindh, T., Malmberg, B., & Halvarsson, M. (2007). The Relationship Between Demographic Change and Economic Growth in the EU (pp. 1-112). Wien: Institut Für Demographie Österreichische Akademie Der Wissenschaften.
  • Sinding, S. W. (2009). Population, poverty and economic development. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1532), 3023-3030. doi: 10.1098/rstb.2009.0145
  • The World Bank Group. (2015). Nigeria. Retrieved 9th December, 2016, from http://www.worldbank.org/en/country/nigeria/overview
  • The World Bank Group. (2016a). Annual Population Growth Rate. Retrieved December 23, 2016, from The World Bank Group http://data.worldbank.org/indicator/SP.POP.GROW?contextual=aggregate&locations=NG
  • The World Bank Group. (2016b). Poverty and Equity Data Portal: Nigeria. Retrieved November 11, 2017, from The World Bank Group http://povertydata.worldbank.org/poverty/country/NGA
  • The World Bank Group. (2017). World Bank Development Indicators: Age dependency ratio. Retrieved September 12, 2017, from The World Bank Group http://data.worldbank.org/indicator/SP.POP.DPND
  • The World Bank Group. (2018). Annual Population Growth Rate. Retrieved April 24, 2019, from The World Bank Group https://data.worldbank.org/indicator/SP.POP.GROW?contextual=aggregate&locations=NG
  • Udo, R. K. (1970). Geographical Regions of Nigeria: University of California Press.
  • United Nations Department of Economic and Social Affairs Population Division. (2013). World Population Prospects: The 2012 Revision, DVD Edition.
  • United Nations Department of Economic and Social Affairs Population Division. (2019). World Population Prospects 2019: Highlights. New York: United Nations.
  • Vijayakumar, S. (2013). An Empirical Study on the Nexus of Poverty, GDP Growth, Dependency Ratio and Employment in Developing Countries. Journal of Competitiveness, 5(2), 67-82.
  • Yu, D., Wei, Y. D., & Wu, C. (2007). Modeling spatial dimensions of housing prices in Milwaukee, WI. Environment and Planning B: Planning and Design, 34(6), 1085-1102.
  • Zou, Y. (2014). Analysis of spatial autocorrelation in higher-priced mortgages: Evidence from Philadelphia and Chicago. Cities, 40, Part A(0), 1-10. doi: http://dx.doi.org/10.1016/j.cities.2014.04.003

Spatially Constrained Clustering of Nigerian States: Perspective from Social, Economic and Demographic Attributes

Yıl 2020, Cilt: 7 Sayı: 1, 68 - 79, 26.04.2020
https://doi.org/10.30897/ijegeo.588032

Öz

Creation
and differentiation of regions are some of the basic tasks in geographic
analysis. Regionalisation attempts to create a generalised representation of
the processes which is taking place at the level of the amalgamated geographic
units. To this end, this study examined the combined use of demographic,
economic and poverty characteristics of States across Nigeria to create regions
relevant for economic and development planning. The study utilised dependency
ratios derived from gridded age structure data, Gross domestic product (GDP),
poverty index. K-Means and Max-p algorithm were used for identification of
regions.
Correlation analysis showed that
Youth dependency and total dependency have a strong statistically significant
positive relationship (r=0.998, p<0.01) indicating that dependency in the
country is driven by youth. The best K-Mean clustering implementation without
considering contiguity identified 12 regions with a ratio of between and total
sum of squares (RBTSS) of 0.789. The Max-p algorithm was tested with population
constrain, the best result identified 9 regions with RBTSS of 0.611 constrained
by a minimum population of 8% and implemented with the greedy local search
algorithm, this was the same for the simulated annealing approach (SA). With
high dissimilarity still common across a handful of the regions identified, a
further test was carried out using a minimum bound of 3 States and the SA local
search approach. The best result identified 11 contiguous regions with only one
region having a relatively high within region dissimilarity and a RBTSS of
0.626. The results confirmed that there are more than 6 regions as currently
defined for the country. The analyses showcased an example of knowledge
discovery from a spatial dataset which could support regional development
planning. From the results, there is a clear need for re-examination of current
regions and designing of better-defined regions to ensure that development is
guided by evidence.

Kaynakça

  • Adams, M. D., Kanaroglou, P. S., & Coulibaly, P. (2016). Spatially constrained clustering of ecological units to facilitate the design of integrated water monitoring networks in the St. Lawrence Basin. International Journal of Geographical Information Science, 30(2), 390-404. doi: 10.1080/13658816.2015.1089442
  • Anselin, L., Syabri, I., & Kho, Y. (2006). GeoDa: an introduction to spatial data analysis. Geographical analysis, 38(1), 5-22.
  • Anyanwu, J. C. (2014). Marital Status, Household Size and Poverty in Nigeria: Evidence from the 2009/2010 Survey Data. African Development Review, 26(1), 118-137. doi: 10.1111/1467-8268.12069
  • Ashford, L. S. (2007). Africa’s youthful population: Risk or opportunity, (pp. 4). Washington DC: Population Reference Bureau.Buchanan, K. M., & Pugh, J. C. (1955). Land and people in Nigeria: The human geography of Nigeria and its environmental background: University of London Press.
  • Ceccato, V., & Uittenbogaard, A. C. (2014). Space–Time Dynamics of Crime in Transport Nodes. Annals of the Association of American Geographers, 104(1), 131-150. doi: 10.1080/00045608.2013.846150
  • Central Intelligence Agency. (2015). Nigeria: The World Factbook. Retrieved November 8, 2015, 2015, from https://www.cia.gov/library/publications/the-world-factbook/geos/ni.html
  • Central Intelligence Agency. (2016). Age Structure: The World Factbook. Retrieved November 11, 2017, from https://www.cia.gov/library/publications/the-world-factbook/fields/2010.html
  • Duque, J. C., Anselin, L., & Rey, S. J. (2012). The Max-P-Regions Problem. Journal of Regional Science, 52(3), 397-419. doi: 10.1111/j.1467-9787.2011.00743.x
  • ESRI. (2015). ArcGIS Desktop (Version 10.4). Redlands, CA: Environmental Systems Research Institute.
  • Fan, C., & Myint, S. (2014). A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation. Landscape and Urban Planning, 121(0), 117-128. doi: http://dx.doi.org/10.1016/j.landurbplan.2013.10.002
  • Feyrer, J. (2007). Demographics and productivity. The Review of Economics and Statistics, 89(1), 100-109.
  • Fukuda, S.-I., & Morozumi, R. (2004). Economic growth under the demographic transition: a theory and some international evidence* The Economics of an Ageing Population Macroeconomic Issues. Cheltenham, UK: 'Edward Elgar Publishing, Inc.'.
  • GeoData Insitute. (nd). Alpha version 2010 and 2014 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates. Nigeria: Population per 100 meters grid Cell Retrieved 20th January, 2015, from www.worldpop.org.uk http://esa.un.org/wpp/
  • Griffith, D. A. (1987). Spatial autocorrelation. A Primer. Washington DC: Association of American Geographers.
  • Grineski, S. E., & Collins, T. W. (2010). Environmental injustices in transnational context: urbanization and industrial hazards in El Paso/Ciudad Ju rez. Environment and Planning A, 42(6), 1308-1327.
  • IBM. (2015). IBM SPSS Statistics (Version 23). Armonk, New York: IBM Corporation.
  • Kim, C. W., Phipps, T. T., & Anselin, L. (2003). Measuring the benefits of air quality improvement: a spatial hedonic approach. Journal of environmental economics and management, 45(1), 24-39.
  • Kögel, T. (2005). Youth dependency and total factor productivity. Journal of Development Economics, 76(1), 147-173. doi: http://dx.doi.org/10.1016/j.jdeveco.2003.11.003
  • Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259-263. doi: 10.1127/0941-2948/2006/0130
  • Lawal, O. (2009). Analysis of land use changes in the Thames Gateway: the change-pattern approach. (PhD), University of East London, London.
  • Lawal, O. (2015). Geodemographic analysis of age dependencies in Nigeria. . Port Harcourt Journal of Social Sciences, 6(1&2), 115 – 132.
  • Lawal, O. (2017). Mapping Economic Potential Using Spatial Structure of Age Dependency and Socio-economic factors. African Journal of Applied and Theoretical Economics, Special Edition(November), 32-49.
  • Lawal, O. (2017). Mapping economic potential using spatial structure of age dependency and socio-economic factors. African Journal of Applied and Theoretical Economics, Special Edition(November, 2017), 32-49.
  • Legendre, P. (1987). Constrained clustering Developments in Numerical Ecology (pp. 289-307): Springer.
  • Linard, C., Gilbert, M., Snow, R. W., Noor, A. M., & Tatem, A. J. (2012). Population Distribution, Settlement Patterns and Accessibility across Africa in 2010. PLoS ONE, 7(2), e31743. doi: 10.1371/journal.pone.0031743
  • Longley, P. A., & Tobón, C. (2004). Spatial Dependence and Heterogeneity in Patterns of Hardship: An Intra-Urban Analysis. Annals of the Association of American Geographers, 94(3), 503-519. doi: 10.1111/j.1467-8306.2004.00411.x
  • Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3-42. doi: http://dx.doi.org/10.1016/0304-3932(88)90168-7
  • Miles, D. (1999). Modelling the Impact of Demographic Change Upon the Economy. The Economic Journal, 109(452), 1-36. doi: 10.1111/1468-0297.00389
  • Myrdal, G. (1957). Economic Theory and Under-Development Regions: Gerarld Duckworth.
  • Myrdal, G. (1968). Corruption: Its causes and effects Asian drama: An inquiry into the poverty of nations (Vol. 2, pp. 953-961). New Yor: Pantheon.National Bureau of Statistics. (2012). Nigeria Socio-economic Indicators. Retrieved from: http://nigeria.opendataforafrica.org/rugbred/nigeria-socio-economic-indicators-november-2012
  • Pirani, E. (2014). Youth Dependency Ratio Encyclopedia of Quality of Life and Well-Being Research (pp. 7287-7288): Springer.
  • Prskawetz, A., Fent, T., Barthel, W., Crespo-Cuaresma, J., Lindh, T., Malmberg, B., & Halvarsson, M. (2007). The Relationship Between Demographic Change and Economic Growth in the EU (pp. 1-112). Wien: Institut Für Demographie Österreichische Akademie Der Wissenschaften.
  • Sinding, S. W. (2009). Population, poverty and economic development. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1532), 3023-3030. doi: 10.1098/rstb.2009.0145
  • The World Bank Group. (2015). Nigeria. Retrieved 9th December, 2016, from http://www.worldbank.org/en/country/nigeria/overview
  • The World Bank Group. (2016a). Annual Population Growth Rate. Retrieved December 23, 2016, from The World Bank Group http://data.worldbank.org/indicator/SP.POP.GROW?contextual=aggregate&locations=NG
  • The World Bank Group. (2016b). Poverty and Equity Data Portal: Nigeria. Retrieved November 11, 2017, from The World Bank Group http://povertydata.worldbank.org/poverty/country/NGA
  • The World Bank Group. (2017). World Bank Development Indicators: Age dependency ratio. Retrieved September 12, 2017, from The World Bank Group http://data.worldbank.org/indicator/SP.POP.DPND
  • The World Bank Group. (2018). Annual Population Growth Rate. Retrieved April 24, 2019, from The World Bank Group https://data.worldbank.org/indicator/SP.POP.GROW?contextual=aggregate&locations=NG
  • Udo, R. K. (1970). Geographical Regions of Nigeria: University of California Press.
  • United Nations Department of Economic and Social Affairs Population Division. (2013). World Population Prospects: The 2012 Revision, DVD Edition.
  • United Nations Department of Economic and Social Affairs Population Division. (2019). World Population Prospects 2019: Highlights. New York: United Nations.
  • Vijayakumar, S. (2013). An Empirical Study on the Nexus of Poverty, GDP Growth, Dependency Ratio and Employment in Developing Countries. Journal of Competitiveness, 5(2), 67-82.
  • Yu, D., Wei, Y. D., & Wu, C. (2007). Modeling spatial dimensions of housing prices in Milwaukee, WI. Environment and Planning B: Planning and Design, 34(6), 1085-1102.
  • Zou, Y. (2014). Analysis of spatial autocorrelation in higher-priced mortgages: Evidence from Philadelphia and Chicago. Cities, 40, Part A(0), 1-10. doi: http://dx.doi.org/10.1016/j.cities.2014.04.003
Toplam 44 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Research Articles
Yazarlar

Olanrewaju Lawal 0000-0001-6468-1982

Yayımlanma Tarihi 26 Nisan 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 7 Sayı: 1

Kaynak Göster

APA Lawal, O. (2020). Spatially Constrained Clustering of Nigerian States: Perspective from Social, Economic and Demographic Attributes. International Journal of Environment and Geoinformatics, 7(1), 68-79. https://doi.org/10.30897/ijegeo.588032