American Journal of Theoretical and Applied Statistics

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Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis

Received: 27 September 2020    Accepted: 24 October 2020    Published: 04 November 2020
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Abstract

This study focused on impact assessment of indigenous Chicken (KALRO Improved Chicken) in terms of the Socio-economic Status of the beneficiaries. Data analyzed comprised of household assets owned and housing characteristics. Studies have been done to assess the impact of new agricultural technologies to the beneficiaries, however, the measurement of the impact indicator (Socio-economic Status) has been a challenge. Studies rely on monetary data (reported income and expenditure), however the collection of high quality (precise and accurate) income data and expenditure is difficult and requires more resources particularly for household surveys, this approach is usually affected by unreliable reportage and measurement error, high-quality income data and expenditure will still produce biased estimates of household socio-economic status because they measure economic flows which are stochastic and include temporary income shocks. This study used principal component analysis model (PCA) to create an asset index to measure Socio-economic status. It was concluded that PCA is reliable in creating an asset index for measuring Socio-economic status, the results showed that about 40% of the households in Machakos County were poor which implies a small decline compared to 42.6% reported on [11] conducted by Kenya National Bureau of Statistics.

DOI 10.11648/j.ajtas.20200906.12
Published in American Journal of Theoretical and Applied Statistics (Volume 9, Issue 6, November 2020)
Page(s) 267-271
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Principal Component Analysis, Socio-economic Status, KALRO Improved Chicken

References
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[2] Anne M., (2014). Construction of Household Asset-Based Wealth Index for Eastern Region, Kenya.
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[7] Chuma, J., & Molyneux, C., (2009). Estimating inequalities in ownership of insecticide treated nets: Does the choice of socioeconomic status measure matter? Health Policy and Planning, 24, pp. 83–93.
[8] Cochran, W. G., (1963) Sampling Techniques, Wiley, New York.
[9] Cope JR, Doocy S, Frattaroli S, McGready J., (2012). Household Expenditures as a Measure of Socioeconomic Status Among Iraqis Displaced in Jordan and Syria. World Health Popul 2012; 14 (1): pp. 19-30. doi: 10.12927/whp.2013.23063.
[10] Denis, Daniel, (2020). Principal Component Analysis. 10.1002/9781119549963.ch10.
[11] Economic survey, (2014). Kenya National Bureau of Statistics.
[12] Filmer D., Pritchett LH. (2001). Estimating wealth effect without expenditure data – or tears: an application to educational enrollments in states of India. Demography 38: pp. 115–32.
[13] Gwatkin DR., Rustein S., Johnson K. et al., (2000a). Socio-economic differences in Brazil. Washington, DC: HNP/Poverty Thematic Group of the World Bank. Accessed 5 January 2004 online at: [http://www.worldbank.org/poverty/health/data/index.htm#lcr].
[14] Hope Michelson, Maria Muñiz & Kyle DeRosa, (2013) Measuring Socioeconomic Status in the Millennium Villages: The Role of Asset Index Choice, The Journal of Development Studies, 49: 7, 917-935, DOI: 10.1080/00220388.2013.785525.
[15] JolliffeI. T., Cadima J., (2016) .Principal component analysis: a review and recent developments. Phil. Trans. R. Soc. A374: 20150202. http://dx.doi.org/10.1098/rsta.2015.0202.
[16] McKenzie DJ. (2003). Measure inequality with asset indicators. BREAD Working Paper No. 042. Cambridge, MA: Bureau for Research and Economic Analysis of Development, Center for International Development, Harvard University.
[17] Mishra, Sidharth & Sarkar, Uttam & Taraphder, Subhash & Datta, Sanjoy & Swain, Devi & Saikhom, Reshma & Panda, Sasmita & Laishram, Menalsh. (2017). Principal Component Analysis. International Journal of Livestock Research. 1. 10.5455/ijlr.20170415115235.
[18] Sahn D., Stifel D., (2003). Exploring alternative measures of welfare in the absence of expenditure data. Review of Income and Wealth 49: pp. 463–89.
[19] Sidharth Prasad Mishra, Uttam Sarkar, et al., (2017). Multivariate Statistical Data Analysis-Principal Component Analysis (PCA). International Journal of Livestock Research eISSN: 2277-1964 NAAS Score -5.36.
[20] Vyas, S. Kumaranayake L. (2006). Constructing socio-economic status Indices. How to use principal components analysis. Health policy plan, 21 (6): pp. 459-68.
Author Information
  • Department of Mathematics, Multimedia University of Kenya, Nairobi, Kenya

  • Department of Mathematics, Multimedia University of Kenya, Nairobi, Kenya

  • Department of Mathematics, Technical University of Kenya, Nairobi, Kenya

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    Ngetich Titus, Karanjah Anthony, Cheruiyot Kipkoech. (2020). Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis. American Journal of Theoretical and Applied Statistics, 9(6), 267-271. https://doi.org/10.11648/j.ajtas.20200906.12

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    Ngetich Titus; Karanjah Anthony; Cheruiyot Kipkoech. Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis. Am. J. Theor. Appl. Stat. 2020, 9(6), 267-271. doi: 10.11648/j.ajtas.20200906.12

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    AMA Style

    Ngetich Titus, Karanjah Anthony, Cheruiyot Kipkoech. Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis. Am J Theor Appl Stat. 2020;9(6):267-271. doi: 10.11648/j.ajtas.20200906.12

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  • @article{10.11648/j.ajtas.20200906.12,
      author = {Ngetich Titus and Karanjah Anthony and Cheruiyot Kipkoech},
      title = {Measuring the Socio-economic Status of Adopters of Indigenous Chicken in Mwala and Machakos Central, Kenya: Application of Principal Component Analysis},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {9},
      number = {6},
      pages = {267-271},
      doi = {10.11648/j.ajtas.20200906.12},
      url = {https://doi.org/10.11648/j.ajtas.20200906.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20200906.12},
      abstract = {This study focused on impact assessment of indigenous Chicken (KALRO Improved Chicken) in terms of the Socio-economic Status of the beneficiaries. Data analyzed comprised of household assets owned and housing characteristics. Studies have been done to assess the impact of new agricultural technologies to the beneficiaries, however, the measurement of the impact indicator (Socio-economic Status) has been a challenge. Studies rely on monetary data (reported income and expenditure), however the collection of high quality (precise and accurate) income data and expenditure is difficult and requires more resources particularly for household surveys, this approach is usually affected by unreliable reportage and measurement error, high-quality income data and expenditure will still produce biased estimates of household socio-economic status because they measure economic flows which are stochastic and include temporary income shocks. This study used principal component analysis model (PCA) to create an asset index to measure Socio-economic status. It was concluded that PCA is reliable in creating an asset index for measuring Socio-economic status, the results showed that about 40% of the households in Machakos County were poor which implies a small decline compared to 42.6% reported on [11] conducted by Kenya National Bureau of Statistics.},
     year = {2020}
    }
    

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    AU  - Ngetich Titus
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    AB  - This study focused on impact assessment of indigenous Chicken (KALRO Improved Chicken) in terms of the Socio-economic Status of the beneficiaries. Data analyzed comprised of household assets owned and housing characteristics. Studies have been done to assess the impact of new agricultural technologies to the beneficiaries, however, the measurement of the impact indicator (Socio-economic Status) has been a challenge. Studies rely on monetary data (reported income and expenditure), however the collection of high quality (precise and accurate) income data and expenditure is difficult and requires more resources particularly for household surveys, this approach is usually affected by unreliable reportage and measurement error, high-quality income data and expenditure will still produce biased estimates of household socio-economic status because they measure economic flows which are stochastic and include temporary income shocks. This study used principal component analysis model (PCA) to create an asset index to measure Socio-economic status. It was concluded that PCA is reliable in creating an asset index for measuring Socio-economic status, the results showed that about 40% of the households in Machakos County were poor which implies a small decline compared to 42.6% reported on [11] conducted by Kenya National Bureau of Statistics.
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