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© 2022 by the authors; licensee Asian Online Journal Publishing Group 
 

Agriculture and Food Sciences Research 
Vol. 9, No. 1, 9-16, 2022 

ISSN(E) 2411-6653/ ISSN(P) 2518-0193 
DOI: 10.20448/aesr.v9i1.3768 

© 2022 by the authors; licensee Asian Online Journal Publishing Group 

 
 

 
 
 
Effects of Demographic Factors on Population Dynamics in Imo State, Nigeria; 
Implications for Farm Labor Availability and Supply 

 
Anyanwu U.G.1  

Osuji E.E.2   
Nwaiwu I.U.O.3 

Tim-Ashama A.C.4  
Ibekwe C.C.5  
Osuala M.O.6  
Eze E.U.7  
Praise C.N.8 

 

 
( Corresponding Author) 

 
1,3,4,6Department of Agricultural Economics, Federal University of Technology Owerri Imo State, Nigeria. 
1Email: uchechigerarda@gmail.com Tel: +2348036900536 
3Email: niuche2004@yahoo.com Tel: +234703 133 6540 
4Email: timashama5@gmail.com Tel: +2347034773356 
6Email: mercbright1@yahoo.com Tel: +2348036900536 
2Department of Agriculture, Alex-Ekwueme Federal University Ndufu-Alike Abakaliki, Nigeria. 
2Email: osujiemeka2@yahoo.com Tel: +2348037351597 
5Department of Agricultural Science, Alvan Ikoku Federal College of Education, Owerri, Nigeria. 
5Email: ibchigozie@yahoo.com Tel: +2347035202787 
7,8Department of Cooperative Economics and Management, Institute of Management and Technology, Enugu, 
Nigeria. 
7Email: emy4jesus@gmail.com Tel: +2348034809184 
8Email: praisechris4@gmail.com Tel:  +2348037132395   

 
Abstract 

The study assessed the effects of demographic factors on population dynamics in Imo State, 
Nigeria. Multi-stage sampling technique was used select 60 respondents. Data collected were 
analyzed using descriptive statistics and the ordinary least square regression technique. Results 
showed that the area was dominated by female farmers 56.7%, and are married 66.7%. Most of the 
farming lands used was inherited, with more of hired laborers 76.7% used due to rural-urban drift. 
Results also showed that over 70% of the people migrated from rural to urban communities. 
Result further showed that age, gender, educational status, income level and poverty index were 
important and significant factors affecting population dynamics (expressed as index of rural–
urban migration). The study recommended the crop farmers to join cooperative societies to raise 
funds to support large-scale production while the government is to provide basic rural 
infrastructures to checkmate rural-urban drift in the area. 

 
Keywords: Population dynamics, Farm labor supply, Rural-urban drift, Farm productivity, Demographic factors, White collar jobs, Efficient 
labor utilization, Food shortage, Cost of labor, Imo state. 

 
Citation | Anyanwu U.G.; Osuji E.E.; Nwaiwu I.U.O.; Tim-Ashama 
A.C.; Ibekwe C.C.; Osuala M.O.; Eze E.U.; Praise C.N. (2022). 
Effects of Demographic Factors on Population Dynamics in Imo 
State, Nigeria; Implications for Farm Labor Availability and Supply. 
Agriculture and Food Sciences Research, 9(1): 9-16. 
History:  
Received: 5 January 2022 
Revised: 17 February 2022 
Accepted: 3 March 2022 
Published: 11 March 2022 
Licensed: This work is licensed under a Creative Commons 

Attribution 4.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Funding: This study received no specific financial support. 
Authors’ Contributions: All authors contributed equally to the conception 
and design of the study. 
Competing Interests: The authors declare that they have no conflict of 
interest. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study; that no vital features of the 
study have been omitted; and that any discrepancies from the study as planned 
have been explained. 
Ethical: This study followed all ethical practices during writing. 

 

 

Contents 
1. Introduction ...................................................................................................................................................................................... 10 
2. Methodology ..................................................................................................................................................................................... 11 
3. Results and Discussion ................................................................................................................................................................... 11 
4. Conclusion and Recommendations ............................................................................................................................................... 15 
References .............................................................................................................................................................................................. 16 
 

mailto:uchechigerarda@gmail.com
mailto:niuche2004@yahoo.com
mailto:timashama5@gmail.com
mailto:mercbright1@yahoo.com
mailto:osujiemeka2@yahoo.com
mailto:ibchigozie@yahoo.com
mailto:emy4jesus@gmail.com
mailto:praisechris4@gmail.com
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/licenses/by/4.0/
https://www.doi.org/10.20448/aesr.v9i1.3768
https://orcid.org/0000-0001-8605-834X


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Contribution of this paper to the literature 
The paper posited novel implications of rural-urban drift in Imo State, Nigeria as it affects farm labor 
availability and supply. It equally averred the various socio-demographic factors influencing population 
dynamics, productivity and efficient utilization of labor supply in Imo State, Nigeria. 

 

1. Introduction 
In recent times, there has been concerted campaign to increase the food production level in Nigeria to feed her 

teeming population of about 162 million [1]. Efforts have been geared at indigenously encouraging food 
production, production of agricultural raw materials, agricultural value-chain addition and establishing a 
formidable platform for the overall growth of the agricultural sector [2]. These and many others are periodically 
affected by population dynamics which influences agricultural production cum farm labor availability. Population 
dynamics refers to short and long term changes in the size and age composition of populations and the biological 
and environmental processes influencing those changes. It deals with the way populations are affected by birth rate, 
death rate, immigration and emigration [3]. Population dynamics is the study of how and why populations change 
in size and structure over time. World Bank [4], viewed “population dynamics” as a media used to convey changes 
in the numbers, age, class distribution, sex ratio, and behavior of a population through time and space, determined 
by inherent characteristics of the individuals and mediated by environmental conditions, food resources, and 
interacting biotic agents. Population dynamics is centered on studying peculiar characteristics of a selected 
population; these characteristics include changes in population growth rates, age structures and distributions of 
people [5]. It is the responsive and long-term changes in the numbers, individual weights and age composition of 
individuals in one or several populations, and the associated physical discrepancies influencing the population at a 
time [4]. Population dynamics in this study is expressed as an index of rural-urban migration, (internal migration) 
which is in contrast to international or intercontinental migration, and this refers to movement within a country. It 
refers to the movement of people from the countryside that is from rural areas to cities often metropolitan cities of 
the country [3]. This change of residence is often related to labor migration and career change, i.e. from the 
primary to the second or third sector. This movement of people usually results in two outcomes that is one side or 
the destination area gains population, while the other side loses people respectively. In order to ensure a 
sustainable growth of both rural and urban areas, cooperation, networking and coordination between both parties 
are completely important and must be taken into consideration [6]. In developing countries such as Nigeria, 
numerous factors are known to cause rural-urban migration mainly - the push and pull factors. Push-factors drive 
migrants out of rural areas while the pull factors draw migrants to urban areas. Migration factors and 
determinants are very complex and can be separated into economic and non-economic factors. Economic drivers 
include rural unemployment or underemployment, low wages and no assets while non-economic drivers play an 
additional role and primarily involve poor rural infrastructures relating to housing, roads, educational 
opportunities, healthcare systems, thus, these causes’ people to move in search for new jobs and better economic 
opportunities [7]. Again, natural disasters, drought, famine, war and conflicts are additional factors that cause 
people to migrate. The nexus between population dynamics and farm labor availability is very complex; intense 
debates and widespread discourse have continued over several decades on population growth as it affects 
agriculture and farm labor availability. For the past decades, agricultural growth has been declining rapidly due to 
the mass movement of people out of the rural areas to the urban cities/town partly due to unfavorable living 
conditions and patterns and this exodus had resulted in the shortage of farm labor which is not readily available 
again [8]. Agricultural intensification in the state is ought to be boosted by farm labor supply arising from 
increasing population but this is not the case in the area as most of their able-bodied young men had migrated to 
cities/towns in search of greener pastures. The high population growth leads to intensified pressures on available 
farm lands, forest and other economic resources, thus leading to increasing poverty and low agricultural 
productivity [7]. Furthermore, overpopulation has resulted in land resource scarcity, fragmentation of farm plots, 
and ecological imbalance and degradation such as increasing emissions, soil erosion, deforestation, and over-use of 
natural resources, thus producing adequate food for the rapidly growing population remains a prime challenge. 
Despite series of agricultural development policies in the state, it had suffered multifaceted challenges ranging from 
land scarcity, deforestation, malnutrition, recurrent drought and lack of improved agro-technologies [9]. The 
existing agricultural land is unable to feed the over growing population and thus many of the crop farmers had 
remained trapped in vicious circle of poverty, disease and hunger.  Rising hikes in food prices, unemployment, lack 
of pasture for livestock, and intensive removal of natural vegetation further aggravates food shortages [10]. Land 
holdings has remained small and subjected to more divisions and fragmentations due to increasing or rising 
population as more demand is made on available lands, and however, land re-distribution is not anticipated in the 
near future. Consequently, the rising population is expected to provide farm labor both in the short and long run 
basis, of which when efficiently utilized would results in increased agricultural production and output [11]. On 
accounts, where farm labor supply is grossly unavailable and inadequate due to labor migrations, this evidently 
undermines agricultural production and further induces food importations. The issue of population dynamics is 
quite necessary to provide government; the adequate tools needed for fresh proper planning, implementation, 
monitoring and evaluation of any proposed developmental plan, without which the expected economic development 
will remain a mirage and will not be achieved. This is because the ability of a nation to function effectively as a 
social, cultural and economic entity is based on its population dynamics [12]. Efforts need to be put in place to 
bring forth a formidable growth plan for agricultural development especially (the rural areas of the country being 
at the core front as a result of cultivable lands available to them with the requisite labor supply readily available 
relative to the urban areas). Nigeria as a nation has over 71 million hectares of cultivable land of which half of it is 
barely used, with the nation relying solely on food importations which depletes our foreign reserves. It has reached 
at an appalling stage that importation of food has sustained an increase of 11% per annum [6]. This rising 
percentage has continued to affect both local and/ or indigenous production as well as increased unemployment in 
the nation. Again, increase in population density has further exacerbated and degraded the vegetation’s of most 
cultivated arable lands, hence forcing farmers to cultivate on marginal lands, with its attendant consequences [12]. 
In addition, population pressure has remained the most potent force for increased poverty and soil infertility among 



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household farmers. Studies had shown that efforts are being made to cushion soil infertility via fertilizer 
distribution based on soil maps so that farmers can apply a custom-based fertilizer to mitigate the depletion of soil 
nutrients. This operation is implemented by means of internally adopted and externally induced technologies. It is 
on this backdrop that the paper presents the implications of demographic factors on population dynamics and its 
effects on farm labor availability in Imo State, Nigeria based on the current evidences in knowledge on agriculture, 
population and farm labor supply or availability. However, the novelty of this study is consequent upon the 
implication of population dynamics on farm labor supply in the state which has not been documented. 
 

2. Methodology 
The study was undertaken in Imo State, which is one of the 36 states in Nigeria. It lies in the southern part of 

Nigeria with Owerri as its capital and its largest city. Imo State has 27 (Twenty-Seven) Local Government Areas 

and it is located between Latitude 4° 45ˡN and 7°15ˡ and Longitudes 6° 50ˡE and 7° 25ˡ. Imo State is bounded on 
the east by Abia State, north by Anambra State, south by Rivers State and on the west by Delta State and River 
Niger. The state has a total land mass of 5530 square kilometers (2,140 square Miles) [13]. The national 
population census of 2006 indicated that Imo State had a population of about 3,934,899 people which comprise of 
both males and females. Imo State was chosen for this study due to the high level of rural-urban migration 
recorded in the area which urgently calls for concern. A multi stage sampling technique was used for the sample 
selection. Recall that Imo State is divided into 3 (three) agro ecological zones which are Owerri, Orlu and Okigwe 
zones respectively. Firstly, one Local Government Area (LGA) was randomly selected from each of the 3 
agricultural zones of the state namely Oforola West LGA for Owerri agricultural zone, Njaba LGA for Orlu 
agricultural zone and Onuimo LGA for Okigwe agricultural zone. Secondly, one Autonomous Community was 
again randomly picked from the above selected Local Government Areas, For Owerri West LGA; Oforola 
Autonomous Community, For Njaba LGA; Umuele Amazano Autonomous Community and For Onuimo LGA, 
Owerri Okwe Autonomous Community. Thirdly, 20 farmers (respondents) each were randomly selected across the 
various Autonomous Communities from the sampling frame provided by the Agricultural Development Program 
(ADP) Coordinators in the respective zones, making a total of 60 respondents from whom information were 
sourced and used for data analysis. Data collected from the research were analyzed using descriptive statistical 
techniques such as percentages, means, frequency distributions and ordinary least square regression technique. The 
Ordinary Least Square Regression Technique is expressed implicitly as 

Y = F (X1, X2, X3, X4, X5, e)                                                                                (1) 
Where:  
Y = Population dynamics (Index of rural-urban migration in the area). 
X1 = Age composition of the farmers. 
X2 = Educational level. 
X3 = Gender composition of farmers. 
X4 = Income level of farmers. 
X5 = Poverty level (estimated using poverty line index). 
e = Error term. 
Note that individual ith households indicated dependents/household heads who were involved in rural-urban 
migration in the area. 
The Ordinary Least Square Regression is explicitly stated thus: 
Linear Functional Form: 

Y = bo + b1X1 + b2X2 + b3X3 + ……….. bnXn                                                        (2) 
      Power Functional Form 

InY = bo + b1InX1 + b2InX2 +b3InX3 + ……..+ bnInXn                                   (3) 
 
 
Semi-Log Functional Form: 

       
Y = bo + b1InX1 + b2InX2 + b3InX3 +………… + bnInXn                                  (4) 

       
       
      Exponential Functional Form: 
        

InY = bo + b1X1 + b2X2 + b3X3 + ………….. + bnXn                                                (5) 
(Note: X1, X2, X3, X4 X5 remains the same as stated earlier) 
 

3. Results and Discussion 
3.1. Demo-Graphic Characteristics of the Farmers  

Table 1 showed the age distribution of the respondents in the area. Majority of the respondents, 30.0% are 
between the ages of 51 and 60 years of age. Furthermore, 20.0% of the farmers lie within the age bracket of 61 - 70 
years with a mean age of 50 years. This implies that the respondents in the area are advancing in age and not likely 
to migrate but rather becomes conservative and non-receptive towards the use of improved technologies. 
Moreover, they provide the needed farm labour used in agricultural production [14].  

Table 2 revealed the marital distribution of the respondents in the area. It showed that 66.7% of the 
respondents were married while 8.3% and 25.0% were single and divorced. The 66.7% of the married group implied 
that they are likely to have some dependents who may likely support their farming activities (farm labor supply) 
and vis a vis less likely to migrate. This also calls for diversification of economic activities in order to meet family 
obligations [15]. 
 
 



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Table 1. Distribution of respondents by age. 

Age  Frequency Percentage 

21 – 30 6 10.0 

31 – 40 11 18.3 
41 – 50 11 18.3 
51 – 60 18 30.0 
61 – 70         12 20.0 
71 – 80 2 3.3 
Total 60 100.0 

Source: Field Survey Data, (2018). 

 
Table 2. Distribution of respondents by marital status. 

Marital Status Frequency Percentage 

Single  5 8.3 
Married  40 66.7 
Divorced  15 25.0 
Total  60 100.0 

Source: Field Survey Data, (2018). 

 
Table 3 revealed gender distribution of the respondents in the area. From the Table, 56.7% of the respondents 

were females while 43.3% were males. It therefore means that females dominated the farming activities in the area 
and this formed a major reason while the females stayed back in the area unlike their male counterparts who 
largely migrated and are involved in non-farming activities in the cities. More so, women are culturally restricted 
from migration due to native tradition, customs and believe systems which inhibit their movement and thus, 
provided the needed farm labor utilized in agricultural production [16]. 
 

Table 3. Distribution of respondents by gender. 

Gender Frequency Percentage 

Male  26 43.3 
Female 34 56.7 
Total 60 100.0 
Source: Field Survey Data, (2018). 

 
Table 4 showed the education distribution of the respondents in the area. According to the Table, 43.3% of the 

respondents have no formal education, 28.3% of them had completed primary education, 21.7% had secondary 
education and only 6.7% had tertiary education. It was gathered that respondents who had tertiary education 
abandoned their farm work and migrated to cities/towns in search of white collar jobs due to poor returns from 
their farming enterprises. It could be noted that their exit affected farm labor supply and/or availability in the area. 
Education is seen as a planned process of bringing desirable changes in the behaviors, skills, attitudes and 
knowledge of individuals. It is believed that educated farmers are more exposed to new ideas which enhance 
decision makings [17]. 
 

Table 4. Distribution of respondents by level of education. 

Level of Education Frequency Percentage 

No Formal Education 26 43.3 
Primary Education 17 28.3 
Secondary Education 13 21.7 
Tertiary Education 4 6.7 
Total      60 100.0 

Source: Field Survey Data, (2018). 

 
Table 5 revealed occupation distribution of the respondents in the area. 60% of the respondent took farming as 

a major occupation, 16.7% took to trading and 16.7% engaged in other economic activities (hunting, okada riding, 
fishing, etc.) as their source of livelihood. Farming in the area was characterized with small land holdings, low 
income due to small scale engagement and low investment, hence resulting to high poverty profile, rural-urban 
drift and shortage of farm labor [18]. 
 

Table 5. Distribution of respondents by occupation. 

Major Occupation Frequency Percentage 

Farming 36 60.0 
Trading 10 16.7 

Artisan 4 6.6 
Others 10 16.7 
Total 40 100.0 

Source: Field Survey Data, (2018). 

 
Table 6 showed the farming experience distribution of the respondents in the area. 41.7% of the respondents 

had between 11–20 years of farming experience. The mean farming experience in the area was 18.13 years, and this 
indicated that majority of the farmers were relatively experienced to handle farm challenges as they arise. Their 
years of experience could also help to increase profitability of the farm business. Again, experience farmers are less 
likely to migrate since they are well exposed to handle and overcome farm pressures and challenges and thus 
enhance farm labor supply [19].   

 
                                                   



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Table 6. Distribution of respondents by farming experience. 

Farming Experience Frequency Percentage 

1 – 10 19 31.7 
11 – 20 25 41.7 
21 – 30 5 8.3 
31 – 40 8 13.3 
41 – 50 3 5.0 
Total 60 100.0 

Note: Mean Farming Experience = 18.13years.  
Source: Field Survey Data, (2018).    

 
Table 7 indicated the household size distribution of the respondents in the area. Most of the respondents, 

40.0% had between 9–11 persons in their household; 36.7% had between 7–9 persons. The mean household size is 7 
persons per household. This indicated that on the average respondent had relatively large household size which 
implies that household head could engage them in agricultural activities (family labor supply) and hence reduce 
expenses on hired labor. It invariably indicated that the household head has more people to cater for which could 
cause them to migrate in search of greener pastures [6]. 
 

Table 7. Distribution of respondents by household size. 

Household size Frequency Percentage 

3 – 5 3 5.0 
6 – 8 22 36.7 

9 – 11 24 40.0 
12 – 14 9 15.0 
15 – 17 2 3.3 
Total 60 100.0 

Note: Mean Household Size = 7 persons. 
Source: Field Survey Data, (2018). 

     
Table 8 revealed the farm size distribution of the respondents in the area. It showed that 20.0% of the 

respondents had between 1.5–1.9 ha of farmland; only 16.7% of the respondents had farm size which ranges 
between 2.6–3.0 ha. The mean farm size is 1.7 ha. This indicated that majority of them possess relatively small 
farmland and practiced farming on a small-scale level. This could be as a result of the issue of land fragmentations 
which inhibit large scale agriculture. It could also be that the small land holdings of the farmers triggered rural-
urban drift in the area, hence shortage of farm labor supply [20].   
 

Table 8. Distribution of respondents by farm size. 

Farm Size Frequency Percentage 

0.1 – 0.4 12 20.0 
0.5 – 0.9 13 21.7 
1.0 – 1.4 8 13.3 
1.5 – 1.9 12 20.0 
2.0 – 2.5 5 8.3 
2.6 – 3.0 10 16.7 

Total 60 100.0 

 

Table 9 showed the methods of land acquisition distribution of the respondents in the area. It revealed that 
76.7% of the respondents acquired their land through inheritance. This means that such land is usually passed to 
offspring after owner’s death. This acquisition nature often leads to non-usage of such lands for agricultural 
purposes as the beneficiaries may not be interested in agriculture. It was gathered that most of the beneficiaries of 
inherited lands in the area sold off their lands and migrated to cities/towns to set up businesses with the money got 
from the sale off thus, creating a reduction in farm labor supply. However, 5.0% and 13.3% of the respondents hired 
and purchased their lands respectively [21].  
 

Table 9. Distribution of respondents by method of land acquisition. 

Land Ownership Frequency Percentage 

Inheritance 46 76.7 
Hired 3 5.0 

Purchased 8 13.3 
Gift 3 5.0 

Total 60 100.0 

Source: Field Survey Data, (2018). 

 
Table 10 revealed the distribution of the respondents based on the type of labor used in the area. From the 

Table, 76.7% of the respondents used hired labor for their farming activities, while only 23.3% of the respondents 
used family labor. This indicated a grave consequence of rural–urban migration drift as most able-bodied young 
members of the households had migrated to the cities and towns in search of better economic activities and this 
also created a huge gap in farm labor supply [22]. 
 

Table 10. Distribution of respondents by types of labor used in farming. 

Types of Labor Frequency Percentages 

Family 14 23.3 
Hired 46 76.7 
Total 60 100.0 

Source: Field Survey Data, (2018). 

 



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Table 11 revealed the distribution of the respondents according to age categories of labor used in the area. 
33.3% of the respondents reported that they engaged people in age category of 14–60 years as hired laborers in 
farming activities, 40% used children under 14 years category while 26.7% employed people of above 60 years. It 
implied that 66.7% of the people that worked on the farms in the area were under aged children (less than 14 years) 
and advanced aged (above 60 years). This means that the active aged populace of the area had migrated to the cities 
and towns where economic activities are more favorable thus leaving the farming activities to the children and aged 
categories to handle [23]. 

                               
Table 11. Distribution of respondents according to age categories of labor used. 

Age categories Frequency Percentages 

0 – 14 24 40.0 

14 – 60 20 33.3 
Above 60 16 26.7 

Total 60 100.0 
Source: Field Survey Data, (2018). 

 

3.2. Cost of Labor in Farming Activities  
Table 12 revealed distribution of the respondents according to the cost of labor in farming activities in the area. 

Majority, 33.3% of the hired laborers earned wage between N1, 000 – N3, 999, 21.7% earned between N 4,000– N 
6,999. The mean wage was N4, 682.92 which is less than $1 per day. It indicated the low income returns and status 
of the hired laborers in the area and hence formed the major reason for rural–urban migration drift in the area; as 
active aged category tend to move to cities and towns where they could attract higher wage rate per man day 
thereby leading to a shortage in farm labor supply in the area [24]. 
 

Table 12. Distribution of respondents by cost of labor in farming activities. 

Cost of Labor Input Frequency Percentages 

1,000 – 3,999 20 33.3 
4,000 – 6,999 13 21.7 
7,000 – 9,999 4 6.7 

10,000 – 12,999 5 8.3 
13,000 – 15,999 9 15.0 

≥ 16,000 9 15.0 
Total 60 100.0 

Source: Field Survey Data, (2018). 

 

3.3. Factors Affecting Availability and Efficient Utilization of Farm Labor Supply 

Table 13 revealed the distribution of the respondents according to factors affecting availability and efficient 
utilization of labor supply in the area. It showed that 88.3% of the respondents cited scarcity of labor as a major 
constraints and impediment to availability and efficient utilization of farm labor. This is due to the migration of 
able-bodied men to cities and towns in search of better economic activities they considered less strenuous vis a vis 
farming. 76.7% were concerned about high cost of labor, this resulted from the huge migration of the active aged 
populace to the cities, thus the available remaining active category now places a high premium on labor cost 71.7% 
revealed inadequate fertile lands as a major issue impeding availability and efficient labor utilization as most 
available lands are infertile and less productive, hence requires little or no labor.  Furthermore, 63.3% complained 
about inadequate funds to hire laborers for farming activities, it could be deduced that this factor arose from high 
cost of labor force as a result of rural–urban migration drift in the area [20]. 
 

Table 13. Distribution of respondents according to factors affecting availability and efficient utilization of labor supply. 

Factors  Frequency* Percentage* 

High cost of labor 46 76.7 
Scarcity of labor 53 88.3 

Lack of adequate fund 38 63.3 
Inadequate fertile land 43 71.7 

Note: *Multiple responses recorded. 
Source: Field Survey Data, (2018).  

 

3.4. Reasons for Emigration of Labor Force Categories in the Area  
Table 14 revealed the major reasons for emigration of labor force out of the area. It was evident that economic 

interest 70%, i.e. eagerness of the respondents to look for better economic opportunities outside their domain; social 
stratification 68.3% i.e. people desire to belong to a higher social strata, occupation difference 60%, i.e. changing 
from one higher occupation to another; standard of living 58.3%, i.e. improvement in living standard; social 
mobility 36.7%, i.e. innate desires to move from one place to another; environmental difference 13.3% i.e. changing 
to a new environment; and rural community difference 11.7% were major reasons for rural–urban migration drift in 
the area. Hence, the quest to attain higher standard of living and social and economic strata largely contributed 
deeply to the movement of people from the rural areas to the cities and towns [20, 24]. 

Table 2 revealed the marital distribution of the respondents in the area. It showed that 66.7% of the 
respondents were married while 8.3% and 25.0% were single and divorced. The 66.7% of the married group implied 
that they are likely to have some dependents who may likely support their farming activities (farm labor supply) 
and vis a vis less likely to migrate. This also calls for diversification of economic activities in order to meet family 
obligations [15]. 

 
 
 



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Table 14. Distribution of respondents according to reasons for emigration of labor force categories. 

Reasons for Emigration Frequency* Percentages* 

Rural community difference 7 11.7 
Environmental difference 8 13.3 
Occupation difference 36 60.0 
Economic interest 42 70.0 
Social mobility             22 36.7 
Standard of living 35 58.3 
Social stratification 41 68.3 

Note: *Multiple responses recorded. 
               Source: Field Survey Data, (2018).  

 

x Linear, Semi-log, Cobb-Douglas and Exponential functional forms were employed to determine significant 
factors affecting the population dynamics in the area. In order to choose the lead equation, the functional forms 
were evaluated in terms of the statistical significance of the explanatory variables, the coefficient of multiple 
determinations (R2), and highest F-value. Among the four functional forms estimated; Double log functional forms 
was chosen as the lead equation based on the above criterion. The table revealed a coefficient of multiple 
determination of 0.813, indicating that 81.3% of the total variations in the dependent variable were explained by 
the independent variables investigated. The significant F- value indicated that the model has a good predictive 
ability and goodness of fit. The result shows that age, gender, educational status, income level and poverty index 
were important and significant factors affecting population dynamics (expressed as index of rural–urban 
migration). It was further revealed that gender, educational and poverty status have positive relationship with the 
dependent variable while age and income level had an inverse relationship with the dependent variable. Gender 
which comprises of both males and females’ influences population dynamics to an extent, as the males being 
anxious to acquire wealth at all cost migrate to the cities/towns in search of better economic opportunities and 
good standard of living, thus leaving the female folks with no choice other than farming, thereby affecting farm 
labor supply and availability [21]. Empirical literatures had consistently reported the dominance of women in 
agriculture more than their male counterparts as a result of rural-urban drift [20]. As expected, educational level is 
positive and significant meaning that education exposes and equip individuals for better opportunities as the more 
educated individuals in the area migrate to the urban areas (cities, town) looking for white collar jobs which often 
not readily available, hence abandoning farming to the less educated ones who cannot read nor write. It connote 
that their absence created a huge gap in farm labor supply and availability in the area. It is known fact that 
education is a veritable tool which influences rural-urban drift as it allows individuals to take major decisions as it 
affects their wellbeing and environment [22]. Poverty status was equally positively significant as any percentage 
increase in the poverty level of the respondents will evidently induce rural–urban drift. The deeper the poverty 
level, the increase in rural–urban drifts. Poverty pushes individuals to seek alternative means of survival and 
livelihood which often may take him/her out of their immediate environment in search of greener posture hence, 
creating a gap in farm labor supply in rural areas [12]. Age of the respondents and income level had an inverse 
relationship with population dynamics; hence any increase in age and income level of the respondents will 
automatically reduce rural-urban drift. This means that as farmers advance in age the eagerness to migrate to 
cities/towns in search of better opportunities diminishes as they prefer to stay back home and engage in any 
meaningful economic activities for survival and in return providing the needed farm labor supply and availability 
without any hindrance. Most times, the farm labor provided may not be really efficient and effective because 
advancement in age of the respondents [15]. This phenomenon literally explains why agriculture is still in the 
hands of ageing populace. Whereas, as income level of an individual increases, he/she is more relaxed and much 
comfortable to live in his/her immediate environment and therefore less anxious to consider rural–urban 
migration, thus closing the huge gap in farm labor supply and availability [18]. 
 

Table 15. Multiple regression estimates of demographic factors on population dynamics. 
Variables Linear Exponential *Double-log Semi-log 

Age in years 0.325 
(0.692) 

-0.061 
(-25.935)*** 

-0.294 
(-2.242)** 

0.602 
(0.808) 

Gender -0.047 
(-0.684) 

0.034 
(0.502) 

0.065 
(12.438)*** 

0.047 
(0.364) 

Educational status 0.022 
(1.971)* 

0.023 
(8.300)*** 

0.005 
(8.407)*** 

-0.32 
(0.244) 

Income level -0.268 
(-0.569) 

0.096 
(0.208) 

-0.278 
(-5.313)*** 

0.382 
(5.433)*** 

Poverty index 0.431 
(1.832)* 

-0.033 
(-0.145) 

0.558 
(2.468)** 

0.360 
(0.838) 

R2  0.779 0.786 0.813 0.669 
Adj. R2  0.739 0.747 0.768 0.550 
F- value 18.556 20.391 28.319*** 5.618 

Note: N/B *** = significant @ 1%,   ** = significant @ 5%.   
* = significant @ 10%,   t- values are figures in parentheses. 

 

4. Conclusion and Recommendations 
Population dynamics connote to short and long term changes in the size and age composition of populations 

and the structural and environmental processes influencing those changes. Its impacts have really being felt in 
agriculture and as a result initiated rural-urban migration drift among the rural populace. Findings of the study 
showed that majority of the respondents were females, married with a household size of 7 persons. Respondents 
were majorly in the age brackets of 51 and 60 years. Educational status showed that only 6.7% had tertiary 
education which initiated rural-urban drift in the area. It is noted that education equips one for better economic 



Agriculture and Food Sciences Research, 2022, 9(1): 9-16 

16 
© 2022 by the authors; licensee Asian Online Journal Publishing Group 

 

 

opportunities which was the case of the educated respondents met in the area. Due to the ceaseless migration of the 
populace, high cost of labor versus labor scarcity was highly rated among the factors influencing the availability 
and utilization of farm labor in the area. Again, people migrated due to occupational difference, rural community 
difference, social mobility, economic interest, social stratification, etc. The result further showed that age, gender, 
educational status, income level and poverty index were important and significant factors affecting population 
dynamics (expressed as index of rural–urban migration). The study recommended the farmers to join cooperative 
societies as to raise funds to support large-scale production while the government is to provide basic rural 
infrastructures to checkmate rural-urban drift. 
 

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