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Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia

Received: 19 March 2021     Accepted: 5 July 2021     Published: 5 November 2021
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Abstract

Poverty is getting a serious social problem in the world and drawing attention of the international community for global solution. It remains challenging particularly in Developing Countries. Ethiopia is among the countries which, striving toward alleviating the problem for many years; however the problem has still persisted and caused many suffering. This study was carried out in Silte Wereda of South Nations Nationalities Regional State (SNNPRS); specifically, the study aim at measuring the magnitude and identifying determinants of poverty in the Wereda. Thus, to meet these objectives, primary data was collected by structured interview from 365 selected sample household. Thus applied descriptive statistics and econometric (logit) model in order to identify the poor and non-poor; analyze the incidence, depth and severity of poverty; and associating livelihood capital with rural poverty have been made. In setting poverty line, Cost Benefit Necessity approach was employed. This has been done by using basket of food items actually consumed by the households and converted to calorie. Based on this, the total poverty line was estimated to Birr 4,380.00 adult equivalent per year, out of this Birr 2,989.50 for food poverty line and Birr 1,390.50 for non-food. The Foster-Greer-Thorbecke (FGT) Poverty Index result shows 41.1% of the sample households have lived under the poverty line, the total consumption required to lift up the poor households to the poverty line is 11.3%, and poverty severity is 4.3%. The binary logit regression econometric model result indicated that out of the twelve variables which included in the model, seven explanatory variables were found significant up to less than 5% probability level. Accordingly, off-farm and non-farm income, educational level, access to credit and contact of agricultural extension worker, ownership of livestock and cultivated land were found as theoretical expectation statistically significant and had negatively association and family size positively associating with the status of poverty of rural households in surveyed area. Thus, promoting education, family planning, diversification credit accessibility, linkage between rural and urban, strengthens research extension-farmer linkage and productivity of land suppose to be policy intervention for targeting rural poverty.

Published in American Journal of Theoretical and Applied Business (Volume 7, Issue 4)
DOI 10.11648/j.ajtab.20210704.14
Page(s) 98-104
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), 2021. Published by Science Publishing Group

Keywords

Binary Logit, Livelihood Capitals, Rural Poverty, Silte Wereda

References
[1] Adugna, E., & Sileshi, M. (2013). Determinants of poverty in agro-pastoral societies of Southern Ethiopia. Livest. Res. Rural Dev, 25, 20.
[2] Afera, N. (2015). Determinants of Poverty in Rural Tigray: Ethiopia Evidence from Rural Households of Gulomekeda Wereda. Journal of Poverty, Investment and Development, 10, 95-102.
[3] Apata, T. G., Apata, O. M., Igbalajobi, O. A., &Awoniyi, S. M. O. (2010). Determinants of rural poverty in Nigeria: Evidence from smallholder farmers in South-western, Nigeria. International Journal of Science and Technology Education Research, 1 (4), 85-91.
[4] Beegle, K., Christiansen, L., Dabalen, A., & Gaddis, I. (2016). Poverty in a rising Africa. World Bank Publications.
[5] Demissie, S. B. (2016). The Issue and Determinants of Rural Poverty in Ethiopia. Vol 7, No 2: pp (1-18).
[6] EHNRI (2000). Food Composition Table for Use in Ethiopia. Ethiopian Health and Nutrition Research Institute, Part III, Addis Ababa. Ethiopia.
[7] Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic development and cultural change, 33 (2), 255-298.
[8] FAO (2016). Food Outlook: Biannual report on global food markets.
[9] Geda, A., Shimeles, A., & Zerfu, D. (2008). Finance and Poverty in Ethiopia: A Household-levelAnalysis. In Financial Development, Institutions, Growth and Poverty Reduction (pp. 61-86). Palgrave Macmillan, London.
[10] Greene, W. H. (1993): Econometric Analysis (2nd edition). Englewood Cliffs, NJ, Prentice Hall.
[11] Gujarati, D. N. (1995). Basic Econometrics; McGraw-Hill, Inc. 3rd edition. New York.
[12] Gujarati, D. N. (2003). Basic Econometrics Fourth Edition McGraw Hill Gujarati, DN. Basic Econometrics.
[13] MoFED (2012). Interim Report on the 2010/11 Poverty Analysis. Addis Ababa: Federal Democratic Republic of Ethiopia.
[14] Molla, T., Zemedu, L., & Legesse, B. (2014). Analysis of Rural Poverty and Exit time: The case of Gozamn District of East Gojjam Zone, Ethiopia. Analysis, 5 (27).
[15] National Plan Commission (2017). Ethiopia’s Progress towards Eradicating Poverty an Interim Report on 2015/16 Poverty Analysis Study. Addis Ababa.
[16] Ravallion, M., & Bidani, B. (1994). How robust is a poverty profile? The world bank economic review, 8 (1), 75-102.
[17] Semere Gebretsadik (2008). Dimensions and Determinants of Rural Household Poverty: The Case of Eastern Zone, Tigray National Regional State. M. sc Thesis in Agricultural Economics, Alemaya University, April 2008.
[18] Swiatowy, B. (2015). Global Monitoring Report 2014/2015: Ending poverty and sharing prosperity.
[19] World Bank (2017). The World Bank, Annual Report. Washington, D. C.
[20] Yamane, T. (1967). Statistics, an Introductory Analysis, 2nd Edition. New York, NY.
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  • APA Style

    Engdawork Yirga Asfaw. (2021). Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia. American Journal of Theoretical and Applied Business, 7(4), 98-104. https://doi.org/10.11648/j.ajtab.20210704.14

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    ACS Style

    Engdawork Yirga Asfaw. Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia. Am. J. Theor. Appl. Bus. 2021, 7(4), 98-104. doi: 10.11648/j.ajtab.20210704.14

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    AMA Style

    Engdawork Yirga Asfaw. Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia. Am J Theor Appl Bus. 2021;7(4):98-104. doi: 10.11648/j.ajtab.20210704.14

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  • @article{10.11648/j.ajtab.20210704.14,
      author = {Engdawork Yirga Asfaw},
      title = {Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia},
      journal = {American Journal of Theoretical and Applied Business},
      volume = {7},
      number = {4},
      pages = {98-104},
      doi = {10.11648/j.ajtab.20210704.14},
      url = {https://doi.org/10.11648/j.ajtab.20210704.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtab.20210704.14},
      abstract = {Poverty is getting a serious social problem in the world and drawing attention of the international community for global solution. It remains challenging particularly in Developing Countries. Ethiopia is among the countries which, striving toward alleviating the problem for many years; however the problem has still persisted and caused many suffering. This study was carried out in Silte Wereda of South Nations Nationalities Regional State (SNNPRS); specifically, the study aim at measuring the magnitude and identifying determinants of poverty in the Wereda. Thus, to meet these objectives, primary data was collected by structured interview from 365 selected sample household. Thus applied descriptive statistics and econometric (logit) model in order to identify the poor and non-poor; analyze the incidence, depth and severity of poverty; and associating livelihood capital with rural poverty have been made. In setting poverty line, Cost Benefit Necessity approach was employed. This has been done by using basket of food items actually consumed by the households and converted to calorie. Based on this, the total poverty line was estimated to Birr 4,380.00 adult equivalent per year, out of this Birr 2,989.50 for food poverty line and Birr 1,390.50 for non-food. The Foster-Greer-Thorbecke (FGT) Poverty Index result shows 41.1% of the sample households have lived under the poverty line, the total consumption required to lift up the poor households to the poverty line is 11.3%, and poverty severity is 4.3%. The binary logit regression econometric model result indicated that out of the twelve variables which included in the model, seven explanatory variables were found significant up to less than 5% probability level. Accordingly, off-farm and non-farm income, educational level, access to credit and contact of agricultural extension worker, ownership of livestock and cultivated land were found as theoretical expectation statistically significant and had negatively association and family size positively associating with the status of poverty of rural households in surveyed area. Thus, promoting education, family planning, diversification credit accessibility, linkage between rural and urban, strengthens research extension-farmer linkage and productivity of land suppose to be policy intervention for targeting rural poverty.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Analysis of Rural Poverty at Household Level in Silte Wereda, Southern Ethiopia
    AU  - Engdawork Yirga Asfaw
    Y1  - 2021/11/05
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    JF  - American Journal of Theoretical and Applied Business
    JO  - American Journal of Theoretical and Applied Business
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    AB  - Poverty is getting a serious social problem in the world and drawing attention of the international community for global solution. It remains challenging particularly in Developing Countries. Ethiopia is among the countries which, striving toward alleviating the problem for many years; however the problem has still persisted and caused many suffering. This study was carried out in Silte Wereda of South Nations Nationalities Regional State (SNNPRS); specifically, the study aim at measuring the magnitude and identifying determinants of poverty in the Wereda. Thus, to meet these objectives, primary data was collected by structured interview from 365 selected sample household. Thus applied descriptive statistics and econometric (logit) model in order to identify the poor and non-poor; analyze the incidence, depth and severity of poverty; and associating livelihood capital with rural poverty have been made. In setting poverty line, Cost Benefit Necessity approach was employed. This has been done by using basket of food items actually consumed by the households and converted to calorie. Based on this, the total poverty line was estimated to Birr 4,380.00 adult equivalent per year, out of this Birr 2,989.50 for food poverty line and Birr 1,390.50 for non-food. The Foster-Greer-Thorbecke (FGT) Poverty Index result shows 41.1% of the sample households have lived under the poverty line, the total consumption required to lift up the poor households to the poverty line is 11.3%, and poverty severity is 4.3%. The binary logit regression econometric model result indicated that out of the twelve variables which included in the model, seven explanatory variables were found significant up to less than 5% probability level. Accordingly, off-farm and non-farm income, educational level, access to credit and contact of agricultural extension worker, ownership of livestock and cultivated land were found as theoretical expectation statistically significant and had negatively association and family size positively associating with the status of poverty of rural households in surveyed area. Thus, promoting education, family planning, diversification credit accessibility, linkage between rural and urban, strengthens research extension-farmer linkage and productivity of land suppose to be policy intervention for targeting rural poverty.
    VL  - 7
    IS  - 4
    ER  - 

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Author Information
  • Department of Development Economics, Ethiopia Civil Service University, Addis Ababa, Ethiopia

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