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Inference on poverty indicators for Ghana

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  • Dioggban Jakperik
  • Romanus Otieno Odhiambo
  • George Otieno Orwa

Abstract

Poverty indicators are the fundamental statistics used to optimally determine the standards of living of people in any country. These are used for policy planing and analysis. Poverty indicators were estimated using linearization techniques with a fourth-order multiplicative semiparametric bias reduction density estimator based on the Ghana Living Standards Survey Round 6 data. The study revealed that the Western Region has the highest At-Risk-of-Poverty Threshold (GHC3; 935:67) with the Upper East having the least value of GHC1; 003:79. Poverty levels were high among the three Northern Regions. The highest percentage of persons living below the poverty threshold was found in the Upper West Region whilst the lowest percent was found in the Western Region. Poverty levels were observed to be high in the rural areas compared to the urban centers. Therefore, to combat poverty in Ghana requires a multifaceted approach with good political will and much concentration on the youth since they are the major source of labour to feed the largely agrarian economy. There is the need to intensify education among the youth on capacity building in all endeavors to enhance productivity, hence improving their standards of living.Mathematics Subject Classification: 62G07, 62G08Keywords: poverty indicators; linearization technique; Living standards; density estimator; Quantile

Suggested Citation

  • Dioggban Jakperik & Romanus Otieno Odhiambo & George Otieno Orwa, 2019. "Inference on poverty indicators for Ghana," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(1), pages 1-4.
  • Handle: RePEc:spt:stecon:v:8:y:2019:i:1:f:8_1_4
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    References listed on IDEAS

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    1. Castro-Leal, Florencia & Dayton, Julia & Demery, Lionel & Mehra, Kalpana, 1999. "Public Social Spending in Africa: Do the Poor Benefit?," The World Bank Research Observer, World Bank, vol. 14(1), pages 49-72, February.
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    3. Vijay Verma & Gianni Betti, 2011. "Taylor linearization sampling errors and design effects for poverty measures and other complex statistics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1549-1576, August.
    4. Adams, Richard H., Jr. & Cuecuecha, Alfredo & Page, John, 2008. "The impact of remittances on poverty and inequality in Ghana," Policy Research Working Paper Series 4732, The World Bank.
    5. Demery, Lionel & Squire, Lyn, 1996. "Macroeconomic Adjustment and Poverty in Africa: An Emerging Picture," The World Bank Research Observer, World Bank, vol. 11(1), pages 39-59, February.
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