This study assessed Non-Inclusive Growth among rural households in Nigeria. Secondary data from General Household Survey (GHS) of 2010/2011, 2012/2013 and 2015/2016 were used. The GHS is a panel data consisting of 5,000 Households) of which 3,347 rural households were used. Data were obtained on socio-economic characteristics, living condition characteristics and geopolitical zones. Poverty gaps were estimated and matched to the economic growth rate to categorise households into non-inclusive growth. Data were analysed using descriptive statistics, Foster-Greer-Thorbecke (FGT) and Probit model. The mean age of the rural households were 41.8±9.4, 43.7±9.4, and 46.9±9.4 years, while the mean household sizes were 8.0±2.0, 7.3±3.1 and 7.5±1.8 for 2010/2011, 2012/2013 and 2015/2016 respectively. Majority were male, 65.0%, 65.4% and 65.5%, while 64.3%, 63.1% and 63.4% were married in 2010/2011, 2012/2013 and 2015/2016, respectively. households with no formal education (45.3%) was higher in 2012/2013 than in 2010/2011 (43.3%) and 2015/2016 (40.2%). The non-inclusive growth was higher without access to health facilities, access to energy, access to potable water and employment in periods 2010–2013, 2013–2016 and 2010–2016. The Probit results show that age of rural households, household size, education, access to health facilities, access to energy, access to potable water, access to credit, North East zone, North West zone, South South zone and South West zone influenced non-inclusive growth among rural households. Therefore, access to facilities and equitable share of resources should be paramount in the rural areas in order to reduce the poverty status of the people vis a vis reduced non-inclusiveness of growth.
Published in | Agriculture, Forestry and Fisheries (Volume 11, Issue 3) |
DOI | 10.11648/j.aff.20221103.13 |
Page(s) | 110-120 |
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Copyright © The Author(s), 2022. Published by Science Publishing Group |
Non–inclusive Growth, Rural Households, Economic Growth, Poverty, Nigeria
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APA Style
Sikiru Ajijola, Bolarin Titus Omonona, Taiwo Timothy Awoyemi. (2022). Non-inclusive Growth Among Rural Households in Nigeria: A Micro Level Analysis of Income Growth and Equitable Distribution of Resources. Agriculture, Forestry and Fisheries, 11(3), 110-120. https://doi.org/10.11648/j.aff.20221103.13
ACS Style
Sikiru Ajijola; Bolarin Titus Omonona; Taiwo Timothy Awoyemi. Non-inclusive Growth Among Rural Households in Nigeria: A Micro Level Analysis of Income Growth and Equitable Distribution of Resources. Agric. For. Fish. 2022, 11(3), 110-120. doi: 10.11648/j.aff.20221103.13
AMA Style
Sikiru Ajijola, Bolarin Titus Omonona, Taiwo Timothy Awoyemi. Non-inclusive Growth Among Rural Households in Nigeria: A Micro Level Analysis of Income Growth and Equitable Distribution of Resources. Agric For Fish. 2022;11(3):110-120. doi: 10.11648/j.aff.20221103.13
@article{10.11648/j.aff.20221103.13, author = {Sikiru Ajijola and Bolarin Titus Omonona and Taiwo Timothy Awoyemi}, title = {Non-inclusive Growth Among Rural Households in Nigeria: A Micro Level Analysis of Income Growth and Equitable Distribution of Resources}, journal = {Agriculture, Forestry and Fisheries}, volume = {11}, number = {3}, pages = {110-120}, doi = {10.11648/j.aff.20221103.13}, url = {https://doi.org/10.11648/j.aff.20221103.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aff.20221103.13}, abstract = {This study assessed Non-Inclusive Growth among rural households in Nigeria. Secondary data from General Household Survey (GHS) of 2010/2011, 2012/2013 and 2015/2016 were used. The GHS is a panel data consisting of 5,000 Households) of which 3,347 rural households were used. Data were obtained on socio-economic characteristics, living condition characteristics and geopolitical zones. Poverty gaps were estimated and matched to the economic growth rate to categorise households into non-inclusive growth. Data were analysed using descriptive statistics, Foster-Greer-Thorbecke (FGT) and Probit model. The mean age of the rural households were 41.8±9.4, 43.7±9.4, and 46.9±9.4 years, while the mean household sizes were 8.0±2.0, 7.3±3.1 and 7.5±1.8 for 2010/2011, 2012/2013 and 2015/2016 respectively. Majority were male, 65.0%, 65.4% and 65.5%, while 64.3%, 63.1% and 63.4% were married in 2010/2011, 2012/2013 and 2015/2016, respectively. households with no formal education (45.3%) was higher in 2012/2013 than in 2010/2011 (43.3%) and 2015/2016 (40.2%). The non-inclusive growth was higher without access to health facilities, access to energy, access to potable water and employment in periods 2010–2013, 2013–2016 and 2010–2016. The Probit results show that age of rural households, household size, education, access to health facilities, access to energy, access to potable water, access to credit, North East zone, North West zone, South South zone and South West zone influenced non-inclusive growth among rural households. Therefore, access to facilities and equitable share of resources should be paramount in the rural areas in order to reduce the poverty status of the people vis a vis reduced non-inclusiveness of growth.}, year = {2022} }
TY - JOUR T1 - Non-inclusive Growth Among Rural Households in Nigeria: A Micro Level Analysis of Income Growth and Equitable Distribution of Resources AU - Sikiru Ajijola AU - Bolarin Titus Omonona AU - Taiwo Timothy Awoyemi Y1 - 2022/06/08 PY - 2022 N1 - https://doi.org/10.11648/j.aff.20221103.13 DO - 10.11648/j.aff.20221103.13 T2 - Agriculture, Forestry and Fisheries JF - Agriculture, Forestry and Fisheries JO - Agriculture, Forestry and Fisheries SP - 110 EP - 120 PB - Science Publishing Group SN - 2328-5648 UR - https://doi.org/10.11648/j.aff.20221103.13 AB - This study assessed Non-Inclusive Growth among rural households in Nigeria. Secondary data from General Household Survey (GHS) of 2010/2011, 2012/2013 and 2015/2016 were used. The GHS is a panel data consisting of 5,000 Households) of which 3,347 rural households were used. Data were obtained on socio-economic characteristics, living condition characteristics and geopolitical zones. Poverty gaps were estimated and matched to the economic growth rate to categorise households into non-inclusive growth. Data were analysed using descriptive statistics, Foster-Greer-Thorbecke (FGT) and Probit model. The mean age of the rural households were 41.8±9.4, 43.7±9.4, and 46.9±9.4 years, while the mean household sizes were 8.0±2.0, 7.3±3.1 and 7.5±1.8 for 2010/2011, 2012/2013 and 2015/2016 respectively. Majority were male, 65.0%, 65.4% and 65.5%, while 64.3%, 63.1% and 63.4% were married in 2010/2011, 2012/2013 and 2015/2016, respectively. households with no formal education (45.3%) was higher in 2012/2013 than in 2010/2011 (43.3%) and 2015/2016 (40.2%). The non-inclusive growth was higher without access to health facilities, access to energy, access to potable water and employment in periods 2010–2013, 2013–2016 and 2010–2016. The Probit results show that age of rural households, household size, education, access to health facilities, access to energy, access to potable water, access to credit, North East zone, North West zone, South South zone and South West zone influenced non-inclusive growth among rural households. Therefore, access to facilities and equitable share of resources should be paramount in the rural areas in order to reduce the poverty status of the people vis a vis reduced non-inclusiveness of growth. VL - 11 IS - 3 ER -