




































 
 

 

8 
 

  Economy 
Vol. 5, No. 1, 8-16, 2018 

ISSN(E) 2313-8181 / ISSN(P) 2518-0118 
DOI: 10.20448/journal.502.2018.51.8.16 

 

 
 
 
 
Effect of Poultry Production on Agricultural Production in Nigeria 

 
Ewubare, Dennis Brown1

     

Ozar, Vivian2     

 

 
( Corresponding Author) 

 
1,2Department of Agricultural and Applied Economics, Rivers State University, Port Harcourt, Nigeria 

 

 
Abstract 

This study examined the effects of poultry production on agricultural output in Nigeria. 
Specifically, this study is tailored to explore the effects of poultry birds’ production, poultry eggs 
production and poultry meat production on agricultural output. The period covered by the study 
spanned from 1975 to 2016. Data on the variables of interests were obtained from the Food and 
Agricultural Organization Statistics (FAOSTAT) and National Bureau of Statistics. The 
analytical techniques comprise OLS and error correction model. The Phillips-Perron unit root 
test results show that all the variables have unit root at levels test, but become stationary after 
being differenced once. The cointegration test results indicate that each of the test statistics show 
evidence of two cointegrating equations. This suggests that in actual fact long run relationship 
exists among the variables. From the parsimonious ECM, it was revealed that poultry birds 
production negatively influence agricultural GDP. Poultry eggs production has an insignificant 
effect on agricultural GDP as evidenced in the parsimonious ECM.  The result further shows that 
poultry meat production is associated with a positive and significant coefficient. The implication of 
this finding is that the production of poultry meats enhances agricultural GDP through its 
important contribution to the livestock sub-sector. It was discovered from the result that the 
coefficient (-0.378) of error correction has the intended theoretical negative sign and also satisfies 
the statistical condition at 1 percent level. It is clear from this finding that any short run 
disequilibrium in the system can be corrected in the long run at 39 percent. Thus, this study 
recommends amongst others that governments at all levels should evolve measures that promote 
huge commitment to infrastructural development in agricultural sector in order to boost poultry 
output and promote self-sufficiency in poultry farming. 

 
Keywords: Poultry production, Agricultural output, Livestock. 

 
Citation | Ewubare, Dennis Brown; Ozar, Vivian (2018). Effect of 
Poultry Production on Agricultural Production in Nigeria. 
Economy, 5(1): 8-16. 
History:  
Received: 16 April 2018 
Revised: 28 May 2018 
Accepted: 31 May 2018 
Published: 4 June 2018 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher: Asian Online Journal Publishing Group 
 

Contribution/Acknowledgement: Both authors contributed to the 
conception and design of the study. 
Funding: This study received no specific financial support. 
Competing Interests: The authors declare that they have no conflict of 
interests. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study was reported; 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 follows all ethical practices during writing.   

 

 

Contents 
1. Introduction ......................................................................................................................................................................................... 9 
2. Literature Review ............................................................................................................................................................................... 9 
3. Research Methodology ................................................................................................................................................................... 11 
4. Data Analysis and Discussion of Results .................................................................................................................................... 13 
5. Conclusion and Policy Recommendation .................................................................................................................................... 15 
References .............................................................................................................................................................................................. 16 
 

 
 

 

http://crossmark.crossref.org/dialog/?doi=10.20448/journal.502.2018.51.8.16&domain=pdf&date_stamp=2017-01-14
http://creativecommons.org/licenses/by/3.0/
http://creativecommons.org/licenses/by/3.0/
https://orcid.org/orcid-search/quick-search?searchQuery=Ewubare, Dennis Brown
https://orcid.org/orcid-search/quick-search?searchQuery=Ozar, Vivian
https://orcid.org/orcid-search/quick-search?searchQuery=Ewubare, Dennis Brown
https://orcid.org/orcid-search/quick-search?searchQuery=Ozar, Vivian
https://orcid.org/orcid-search/quick-search?searchQuery=Ewubare, Dennis Brown
https://orcid.org/orcid-search/quick-search?searchQuery=Ozar, Vivian


Economy, 2018, 5(1): 8-16 

9 
 

 

1. Introduction 
In Africa, agriculture has remained at the forefront of economic activities, thus, accounting for 30 percent of the 

national income (Heise et al., 2015) and large proportion of the overall exports. For this reason, both public and 
private concerns in the agricultural sector continue to increase. According to Connolly (2014), about three-quarters 
of the total population in Africa depend on agriculture for livelihood and the demand for various agriculture 
products has continued to increase in recent years. With the increase in the disposable income of the population, 
the demand for agricultural produce especially poultry products (eggs and meat) has continued to increase across 
the African Continent.  

The popularity of poultry birds in Nigeria is noteworthy and can be attributed to the numerous benefits 
associated with poultry production and other value chain. Heise et al. (2015) argue that poultry birds are good 
sources of protein either used as eggs or meat. They further explained that the production of poultry birds is 
relatively cost effective, thus, making it possible for low income farmers to start up the business. More so, the 
return on poultry investment is relatively high compared to other livestock production and the high level of 
acceptability of the poultry meat across diverse ethnic backgrounds and religious beliefs broadens the market share 
and makes the business very viable. In addition to the benefits created by the poultry meat, Ojo (2003) and Aboki et 
al. (2013) remarked that poultry eggs are more affordable for low income earners compared to other sources of 
protein. This adds to the relative importance of poultry to agriculture. 

The distribution of poultry production across the six geo-political zones in Nigeria as provided by the 
Presidential Committee on Livestock (PCOL) (2003) include 17.8million birds, 15.8 million birds and 22.6million 
birds in the northwest, northeast and north central zones respectively while the south-east, south-south and south-
west geo-political zones have 16.0million birds, 15.2million birds and 24.3million birds respectively. The 
production estimates of poultry birds on report indicate that between 1998 and 2003, 179,667 metric tonnes of 
meat was produced while 434,000 metric tonnes of eggs was produced in Nigeria. In spite of the positive spill-over 
effects associated with poultry production, the output hardly meets the growing demand. This is because 
consumption increases rapidly than output. Rotschild (2002) posits that the domestic production shortfall is 
estimated at 25,000 metric toones. Thus, increasing importation undermines exchange rate stability and external 
reserve build-up. 

The shortfall in poultry production amidst the growing demand has remained key challenges as it reduces the 
net-marginal contribution of this livestock segment to the agricultural output. This lag in poultry production has 
remained major source of worry to the government and other relevant stakeholders in the agricultural sector. The 
current level of food insecurity calls for well-defined approaches in meeting the desired objectives. One of the 
generally adopted approaches is increased production and productivity of the poultry sub-sector.  Increasing 
productivity and efficiency within the agricultural sector, particularly among small-scale poultry egg producers 
require a good knowledge of the current efficiency or inefficiency inherent in the subsector as well as factors 
responsible for this level of efficiency or inefficiency. This is because despite the growth in egg and meat production 
industry since year 2000 in Nigeria (Tijjani et al., 2006), growing local demand has not matched the fluctuating 
local supply. It therefore, becomes imperative to gain more insight into the challenges and problems confronting 
poultry production and how poultry production contributes to agricultural GDP in Nigeria. It is against this 
backdrop that this study explored the effects of poultry production on agricultural output in Nigeria over the 
period of 42 years (1975-2016). 

 
2. Literature Review 
2.1. Theoretical Framework 
2.1.1. Input-Output Theory 

The input-output theory is credited to Leontief (1951). The theory focused on inter-industry relations and 
interrelationship in the economy wide aggregate as the input of one industry is the output of another industry. The 
theory was originally developed to analyze and measure the connection that exists between key sectors of an 
economy. The theory has been extended to include smaller systems of the economy, and on the broader scale, the 
economic relationship between countries. The theory argues that, the various sectors of the economy are 
interdependent as the output of a particular sector forms the input of another sector. The substructure of the input-
output (I-O) analysis incorporates input-output tables. Each table showcases the supply chain of inputs as 
expressed in rows and columns. The input-output model is instrumental in estimating three important type of 
impacts: direct, indirect and induced. 

By employing the I-0 model, poultry farmers could be able to estimate adjustment or changes in inputs used by 
them due to a change in output in one or more specific sector. The direct consequence of this would be the 
adjustment in money balance expended by them. The secondary consequence of this relates to the number of labour 
hired by the suppliers of input utilized by the poultry farmer. The induced impact comes from the workers or 
suppliers purchasing more goods and services. The input-output theory has been criticized on the grounds of its 
rigidity as it fails to reflect certain phenomena such as increasing costs, bottlenecks, etc. Also, the lack of 
mechanism for price adjustments in the model makes it unrealistic. 

 
2.1.2. Theory of Production  

The production theory concerns itself with the economic process that describes how certain specific inputs are 
jointly combined to produce a given level of output. The production theory has its footing in the works of the 
neoclassical economists. The neoclassicals argued that the economy comprises of two important agents – the 
consumer and producer. The former engages in consumption activities whilst the latter undertakes production 
activities. These decisions or activities taken by the aforementioned agents are considered inseparable owing to the 
fact that the decision bothering on consumption, labour supply, and production are looked at simultaneously 
through the behavioural lens of three key agents: consumers, workers, and producers (Mankiw, 2015). 



Economy, 2018, 5(1): 8-16 

10 
 

 

The cradle of this theory kicks starts from the poultry farmer making decisions on the number of labour to be 
utilized or employed in the course of his/her poultry farming activities; whether or not to utilize purchased labour 
or make do with self labour; the amount of capital to be invested into the poultry business; the source of capital 
(personal savings or loans from deposit money banks); the skills, talents and creativity inherent in the owner of the 
enterprise or the labour to be employed or currently employed, among others. These decisions shape the 
configuration of inputs to be utilized and quantum of output to be realized. What this exhumes is that, the poultry 
farmer can vary the level and composition of his or her farm inputs and outputs. 

In practical sense, poultry farmers tend to have a variety of goals ranging from income instability, ensuring 
household food security, achieving certain consumption preferences and giving back to his or her community. In 
achieving these, poultry farmers must produce the highest number of output given available or devoted resources 
as revenue depends on the level of output and the unit price of the output. However, the achievement of the highest 
level of output is limited by certain constraints that engulfs availability of capital, land being fixed in supply, the 
composition of labour in terms of quality, price, and availability. 

The behaviour of the poultry farmer as it borders on how resources can be best allocated so as to ensure the 
achievement of the highest level of output can be best scripted using the theory of cost minimization and output 
maximization. Farmers venturing into or engaged in poultry farming, like any other entrepreneur, are assumed to 
maximize total output, minimize production cost, or engage in both. In other to achieve any or both of the stated 
objectives (maximization or minimization), the poultry farmer sets out to maximize a set of utility subject to certain 
input constraints as defined by the set of utility subject to certain input constraints as defined by the production 
function. The poultry farmer derives satisfaction from the quantities of output (from instance broilers, layers, 
poultry-egg) produced subject to the input combination, with the latter dependent on each input’s price, the prices 
of other inputs, and other sets of socio-economic variables. 
 

2.2. Conceptual Framework 
Poultry are chickens, ducks, geese, guinea fowls, turkeys and other related birds kept for meat and egg. In 

Nigeria, the poultry population is estimated to be 140 million (Ocholi et al., 2006). They are the most commonly 
kept livestock and over 70% of those keeping livestock are reported to keep chickens (Amar-Klemesu and Maxwell, 
2000). Chickens have its scientific name to be Gallus domestics and it is one type of poultry. It belongs to the 
family phasiendae and it is estimated to be about 69% of the total number of birds kept in Nigeria (Sonaiya, 1990). 
Commercial poultry systems are industrialized and, therefore, based on large, dense, uniform stocks of modern 
poultry hybrids. However, most of the poultry is still kept in rural production systems, which are characterized by 
insufficient hygiene management. Even though many farmers would like to stock hybrids, which gain weight more 
quickly and are more disease resistant, their high mortality rates make hybrid production less profitable (Esiobu et 
al., 2014).  Additionally, farm and flock size correlates significantly to the output of poultry farms. Large farm size 
increases productivity as well as technical, allocative, and resource use efficiency (Esiobu et al., 2014). Many poultry 
farmers still work at a subsistence, small, or medium-sized level mainly due to limited financial resources (Aboki et 
al., 2013). 
 

2.3. Empirical Literature  
Hamid et al. (2017) examined the performance of the poultry industry in Bangladesh focusing on the 

contribution of private sector for the development and marketing of poultry products. The study also investigated 
the problems and constraints of poultry industry and the scope and opportunity cost of poultry industry. This 
investigation is mirrored through various programs designed and implemented by private enterprises in the 
poultry industry. The method of analysis dwelled on descriptive statistics with a focus on frequency distribution 
and simple percentage. The result shows that the availability of meat and egg is much lower than the demand, thus 
a creating a condition of deficit in the market system. Specifically, the study revealed that the contribution of 
poultry meat to the total meat products is about 35.2 percent whereas egg production is 63.65 percent of the total 
domestic demand. In comparative terms, the study showed that the per capita poultry meat consumption is much 
lower compare to other Asian countries as it averaged 1.9 kilogram. Based on the findings, the study recommended 
for synergy between private sector and the government as well as foreign investment in order to boost production 
in the livestock industry. 

Bamiro (2008) analyzed the economic importance of poultry production in some sampled local government 
areas in Oyo state, Nigeria. The sampling technique employed by the study in selecting the study area and 71 
respondents is purposive in nature. The method of analysis involved combinations of descriptive statistics and 
multiple regressions. It was uncovered from the result that the profitability of poultry farmers depends largely on 
enterprise combinations and extent of production. It was evident from the budgetary analysis that enterprises that 
operate in a large scale have highest turnover compared to those that operate relatively on low scale.  The 
descriptive analysis also show that poultry farmers engaged in eggs production have highest gross margin 
compared to those engaged in broiler production. Thus, egg production contributes more to agricultural GDP. The 
result of regression analysis revealed that poultry birds, feed and labour size are key drivers of productivity in the 
poultry sub-sector and by extension the overall agricultural sector. Owing to the findings, the study recommends 
that poultry farmers should focus more on egg production in order to boost the contribution of the poultry 
industry to agricultural GDP.  

Yusuf et al. (2016) used primary data collected through the instrumentality of questionnaire in exploring the 
economics of poultry production in Kwara State, Nigeria. They made use of the budgetary and profit index 
analysis. A structured questionnaire was administered to 80 registered poultry farmers selected using the 
systematic random sampling technique. Obtained data were analyzed using descriptive statistics, benefit cost ratio, 
ordinary least squares regression and the budgetary analysis. Empirical findings of the study disclosed that, 
commercial poultry farmers in Kwara State are well educated, highly experienced and young with a keen interest in 
the business of poultry farming. Upon analyzing the costs and returns, the findings showed that poultry farming is 
profitable in the study area as the gross income and net income for egg production were computed to be 



Economy, 2018, 5(1): 8-16 

11 
 

 

N4,062,422 and N1,255,965 respectively, whilst that of broiler productions were found to be N1,683,209 and 
N499,187 respectively. The outcome of the regression analysis carried out disclosed that, labour, equipment, feed, 
and stock capacity are significant facts that affects poultry farming in the study area. 

Ayieko et al. (2014)  sort to calculate the profit of indigenous chicken in Makueni County and to determine the 
association that exists amongst certain socio-economic factors and profit from IC. The multistage sampling was 
used and this gave birth to a sample size of 130 households to which structured questionnaires were administered 
to. With the growing usage of software applications in the analysis of data, STATA 11 was employed in carrying 
out both budgetary analysis and multiple regression analysis. The empirical findings of the study divulged that, the 
profit from the production of IC in Makueni was ksh. 5347 per 100 birds. On the socio-economic factors that has 
significant association with profit, the factors identified by the study includes: flock size, age, access to credit, 
education, and price and year in farmer group. 

Ezeh et al. (2012) measured the technical efficiency and its determinants in the production of broilers in 
Umuahia capital territory of Abia State, Nigeria. Using a multistage sampling technique, the sample size for the 
study is 60 poultry farmers. The study employed a stochastic production function. The employed production 
function brought to bear feed intake, stock-size, and labour input as critical variables that influences the output of 
farmers. The farm level technical efficiency, it was discovered, ranged from 87% to 97% with an average of 75%. 
The determinants of the farm level technical efficiency were household size, extension contact, age and the level of 
education. 

Assessed constraints to increased layers production among small-scale poultry farmers in Ibadan Area of Oyo 
State, Nigeria. The study made use of a multistage sampling technique which gave rise to 120 small scale poultry 
farmers to which structured questionnaires were administered to. The instrument for data analysis is pairwise 
correlation coefficient. Empirical findings of the study divulged that, disease and pest attack ranked top as 
constraints faced by the sampled farmers in carrying out their productive activities and these was accompanied by 
difficulty in the procurement of credit and loan. The results of the correlation analysis revealed a significant 
association between number of birds raised, income from sale of egg, and constraints to increased layers production 
among farmers involved in small-scale poultry farming. Hinging on the discoveries of the study, it was proposed 
that government tackle the problems associated with the procurement of credits and loans, and ensuring stability 
in price. 

Emokaro et al. (2016) carried out a study to analyze the economics of backyard poultry farming in Benin city. 
The sampling technique adopted for their work was the snowball sampling technique which produced the ninety-
six (96) backyard poultry farmers that formed the sample size for the study. Primary data were employed for the 
study with the needed data obtained through the issuance of a structured questionnaire. Descriptive statistics, 
profitability measures and multiple regression analysis were used in analyzing the obtained data gotten from 
responses as captured by the issued questionnaire. The empirical findings of the study points to the dominance of 
layers poultry production in the business of backyard poultry farming with it (layers) attracting 70% of all poultry 
business. The profitability analysis divulged the poultry business is a profitable one in Benin city averaging a 
positive gross margin of N573,346.01 yearly. Results of the regression analysis conducted lay bare the positive 
contribution of family size and farming experience to net returns from engaging in backyard farming. Conversely, 
the age of respondents was uncovered to negatively influence a farmers’ net income. On soliciting for hurdles or 
constraints faced by farmers, insufficient finance and high cost of feed were thrown into the open as limiting 
factors. 

Ume et al. (2016) examined the economics of Broiler production among rural women in Imo State. The study 
area focused on Ahiazu Mbaise local government area. A sample size of 200 rural women engaged in broiler 
farming was selected using a combination of both purposive and multi-stage sampling technique. A structured 
questionnaire was employed in soliciting for responses that formed the data relied upon and used for the study. In 
ensuring the achievement of outlined objectives, the gross margin analysis and percentage response techniques 
were used in analyzing obtained data. The outcome of the analysis carried out disclosed that, the gross margin for 
broiler production was N212,875, the total revenue realized was N925,000, with the aggregate variable cost 
standing at N712,125; whilst the benefit cost ratio was computed to be N1:1.2. In order of priority, the sampled 
farmers identified poor marketing price, expensive labour wage, poor access to credit, and pest and disease as 
constraining factors to their broiler production.  

Nwandu et al. (2016) applied descriptive statistics in appraising the potentiality of poultry production as a 
means of livelihood and poverty alleviation among its farmers in Nigeria. As part of the objectives, the study 
examined the profitability approaches for successful operation of poultry business. The findings revealed that 
poultry production business in its entire ramification is undoubtedly one of the viable farming enterprises 
providing the much needed animal protein sources, especially egg and meat in order to provide solution to food 
crisis in Nigeria in terms of protein deficiency. In view of the findings, the study therefore, recommended that the 
government should prioritize poultry production business as a means of empowering the teeming population of the 
youths in order to check the growing rate of unemployment and boost agricultural productivity. 
 

3. Research Methodology  
3.1. Research Design  

In view of the nature of this study, ex-facto research design was employed for this study. This is because this 
study is based on existing data which were documented over the past 42 years (1975-2016).  
 

3.2. Types and Sources of Data Collection  
This study focused mainly on secondary data. The data were collected on annual basis from 1975 to 2016 and 

the source for the indicators of poultry production is Food and Agricultural Organization Statistics (FAOSTAT). 
In addition to this, data on agricultural output over the sampled period were collected from the National Bureau of 
Statistics.  
 



Economy, 2018, 5(1): 8-16 

12 
 

 

3.3. Method of Data Analysis  
This study relied on the OLS techniques for estimating the effects of the underlying indicators of poultry 

production on agricultural output in the long run. The choice of this method stems from its attribute as the Best 
Linear Unbiased Estimator (BLUE). As the best estimator, the OLS estimates are preferred to estimates from other 
econometrics methods. More importantly, the Error Correction Model (ECM) is applied to estimate the short-run 
behaviors of the measures of poultry production and the speed at which the model adjusts to equilibrium in the 
long run. Before estimating the long run and short behaviors of the variables, the data were be subjected to unit 
root and cointegration tests. Again, the estimated model was subjected to some diagnostics tests which focused 
mainly on higher order serial correlation test, heteroscedasticity test and normality test amongst others. Each of 
these tests is discussed below: 
 

3.3.1. Pre-Estimation Tests 
i. Unit Root Test:  The time series characteristics of the variables were ascertained via stationarity test 

process. Specifically, this test is applied to ensure that each of the variables does not enter the model in an explosive 
manner (non-stationary status). The Phillips and Perron (1988) method, an alternative procedure to the popular 
Augmented (Dickey and Fuller, 1981) approach was adopted for the unit root test. The null hypothesis of a unit 
root (non-stationarity) was tested against the alternative hypothesis of no unit root (stationarity) at 5 percent level. 
The model for the unit root test is formalized below: 

                  ∑                                                                                                 

 

   

     

Where: Qt = variables included in the model,    and βi   = parameter estimates, K = length of lag, ∆= First 

difference operator, λt = Random disturbance term 
It is expected that each of the series be integrated of order zero [I(0)] for the OLS to be efficient and unbiased. 
However, a deviation from the expected stationarity process may yield a spurious result. 
 
ii. Cointegration Test     

Before estimating the error correction model, the series was subjected to cointegration test to determine 
whether their linear combinations lead to long run relationship. Evidence of long run among the underlying series 
shall prompt the estimation of the error correction coefficient in order to capture the speed of adjustment. Owing to 
its robustness, the Johansen system of cointegration test for multivariate models proposed by Johansen and 
Juselius (1990) is applied in ascertaining the presence of a long-run relationship among the variables. The algebraic 
formalization of the Johansen-Juselius cointegration model based on the required test statistics is as follows: 

(3.2) 

(3.3) 

Where J = estimated values of the characteristics roots of the trace statistics estimated from the cointegrating 
vector.  
k = estimated values of the characteristics root of the Maximum-Eigen statistics estimated from the cointegrating 
vector 
T = number of observations.  

For the trace test, the null that the number of distinct cointegrating vectors is equal to or less than r is tested 
at 5 percent level. On the other hand, the Max-Eigen statistic shall test the null hypothesis that the number of 
cointegrating vectors is r, against the alternative of that it is r +1. The critical values for each of these test statistics 
as provided by Johansen and Juselius (1990) shall be compared with the computed values at 5 percent critical value. 
Evidence of at least one cointegrating equation at selected 5 percent level of test implies that long run relationship 
exists among the series. 
 

3.4. Model Specification 
This study developed and estimated a single multivariate model to capture the production-output relationship 

between the indicators of poultry production and growth of agricultural sector. The functional specification of the 
relationship between agricultural output (APO) and the measures of poultry production such as stock of poultry 
birds (POB), eggs production (EPO) and poultry meat production (PMP) is as follows: 

APO = f (POB, EPO, PMP)         (3.4) 
Where: APO = agricultural output 
 POB = stock of poultry birds 
 EPO = eggs production 
 PMP = poultry meat production 
The linear and non-linear econometric models of Equation (3.4) are provided as: 

APOt = N0 + N1POBt + N2EPOt + N3PMPt  + U1t     (3.5) 
InAPOt = M0 + M1InPOBt + M2InEPOt + M3InPMPt + U2t   (3.6) 

 
Where: APO, POB, EPO and PMP are as explained in Equation (3.4). 
 N0 and M0 = intercepts or constant parameters 
 N1 – N 3and M1 – M3 = slope parameters 
 In = natural log notation 
 U1t – U2t = stochastic term 
Equations (3.5) and (3.6) respectively depict the linear and non-linear econometric models.   

  














n

ri

itrace InTrJ
1

1 

  











111,max rInTrrK 



Economy, 2018, 5(1): 8-16 

13 
 

 

The a priori expectations require that the coefficients of each of the poultry products should have a positive 
sign. This is because increase in poultry production is expected to boost agricultural output and thus, increase its 
share of GDP. Based on this premise, the expected signs of the coefficients of the explanatory variables are 
expressed algebraically as: N1>0, N2>0, N3>0,, M1>0,M2>0, and M3>0.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     
The short run dynamic behaviors of the explanatory variables are captured using an error correction model (ECM) 
and the model is expressed as: 

 

3.7 

Where:      = Constant parameter,       = short-run dynamic coefficients of the regressors, y = length of lag, 
ECM = Error correction term lagged for one period, = error correction coefficient lagged for one period,e1t = 

Random disturbance term. 
 

3.5. Description of Variables in the Model 
A. Dependent Variable 

i. Agricultural output (APO): This refers to crops, livestock, fisheries and forestry products produced in 
Nigeria over a period of time usually per annum. It excludes all kinds of agricultural produce and allied products 
imported to Nigeria from the rest of the world. The output of agricultural sector in the Nigerian economy between 
1975 and 2015 as reported by the National Bureau of Statistics shall serve as the dependent variable for this study. 

 
B. Explanatory Variables 

i. Stock of poultry birds (POB): These comprise domestic fowls such as chickens, turkeys, ducks, geese, 
pigeons and recently ostriches reared with the primary objective of producing meat and eggs. They are important 
sources of protein and play key roles in boosting food security. Increase in the sock of poultry birds is expected to 
stimulate agricultural output. 

ii. Eggs production (EPO): This involves the raising of chickens, especially layers for eggs production which 
important source of protein. It is expected that increase in eggs production will increase agricultural GDP.  

iii. Poultry meat production (PMP): This refers to broilers and other types of poultry meat produced 
domestically for meeting consumption and in some instances export needs. It is expected that increase in the 
production of poultry meat will contribute positively to agricultural output. Data on the total number of poultry 
produced over the sampled period shall be sourced from the FAO statistics. 
 

4. Data Analysis and Discussion of Results 
4.1. Descriptive Statistics 

As part of efforts to provide more information on the distribution of each of the series over the period covered, 
the descriptive statistics of the series are reported in Table 4.1. 
 

Table-4.1. Descriptive statistics for the series 

 APO POB EPO PMP 

 Mean  19378590  121776.4  384362.0  171631.9 

 Median  930328.1  124310.0  393500.0  169500.0 

 Maximum  2.54E+08  192313.0  660000.0  273000.0 

 Minimum  6028.330  64380.00  150000.0  82000.00 

 Std. Dev.  51719054  31592.73  156520.0  46397.60 

 Observations  42  42  42  42 
         Source: Compiled by the Author as computed from E-Views software 
 

The average values of APO, POB, EPO and PMP as observed from the descriptive statistics are ₦19378590 
million, 121776.4 tonnes, 384362.0 tonnes and 171631.9 tonnes respectively. From the respective standard 
deviation of the series, it was found that the observations for the variables do not converge around their mean 
values. This inference is based on the fact the respective standard deviations for the variables are more than the 
associated mean values. 
 

4.2. Ordinary Least Squares based Static Model 
The static regression model estimated using OLS as showed in Table 4.2 
The regression model was estimated using OLS as reported in Table 4.2 reveals that poultry eggs production 

is positive related to changes in agricultural output. 10 percent increase in poultry eggs production generates 68.9 
percent increase in agricultural output, indicating that poultry eggs production is a source of increasing returns to 
scale in agricultural GDP. However, stocks of poultry birds and poultry meat production are not significant in 
explaining changes in agricultural output. However, the entire model shows evidence of statistical significance, 
thus indicating that the regressors are jointly significant. Although the R-squared (0.875) attests to the high 
explanatory power of the regressors, the Durbin-Watson statistics (0.753) shows that there is serial correlation in 
the model. This econometric problem of serial correlation observed in the model can be as a result of unit root in 
the series, thus constraining any long term prediction based on the regression outcome. This provoked the test for 
unit root in the series 

 
 
 
















 
y

i

t

y

i

t

y

i

t

y

i

tt InPMPInEPOInPOBInAPOInAPO
1

14

1

13

1

12

1

110 

tt

y

i

t eECMInSOC  



 1

1

15





Economy, 2018, 5(1): 8-16 

14 
 

 

Table-4.2. OLS based regression result 

Dependent Variable: LOG(APO)   

Method: Least Squares   

Variable Coefficient Std. Error t-Statistic Prob.   

In(POB) -1.012 4.519 -0.224 0.823 

In(EPO) 6.899 1.155 5.969 0.000 

In(PMP) 0.647 4.156 0.155 0.877 

C -70.735 9.388 -7.534 0.000 

R-squared 0.875   

Adjusted R-squared 0.865     Durbin-Watson stat 0.753 

F-statistic 89.09   

Prob(F-statistic) 0.000    
Source: Compiled by the Author as computed from E-Views software 
NB: In denotes log natural transformation  

 

4.3. Unit Root Test 
The Philips-Perron (PP) procedure to stationarity was applied in testing whether or not the variables are 

stationary or not at 5 percent level. The results are displayed Table 4.3.  
 

Table-4.3. Philips-Perron (PP) test results 

Variable PP levels test results                 PP 1st difference test results Order of integration  

 Adjusted t-stat. 5% critical value Adjusted t-stat. 5% critical value  

In(APO) 0.780 -2.935 -13.763 -2.936 I (1) 
In(POB) -2.332 -2.935 -6.876 -2.936 I (1) 
In(EPO) -2.086 -2.935 -6.648 -2.936 I (1) 
In(PMP) -2.740 -2.935 -6.988 -2.936 I (1) 

Source: Compiled by the Author as computed from E-Views software 
NB: In denotes natural log transformation  

 
The results as showed in Table 4.3 revealed that none of the variables is stationary at levels. This is because 

their adjusted t-statistics are less than their associated critical values at 5 percent level. Following the non-
stationarity of the variables at levels, transformation of the variables via 1st differencing was carried out. The 
result shows evidence of stationarity upon 1st differencing. The implication of this finding is that all the variables 
are integrated of order one. This makes the Johansen cointegration variety appropriate for testing if the variables 
show any evidence of long run relationship. 
 

4.4. Cointegration Test 
The cointegration test proposed by Johansen and Juselius was applied in examining if long run relationship 

exists among the series or not. The results are reported in Table 4.4. 
 

Table-4.4. Results of cointegration test 

Series: In(APO) In(POB) In(EPO) In(PMP)   

Lags interval (in first differences): 1 to 2  

Hypothesized No. of CE(s) Eigenvalue Trace Statistic 0.05 Critical Value Prob.** 

None *  0.579  66.960  47.856  0.000 

At most 1 *  0.430  33.166  29.797  0.019 

At most 2  0.182  11.234  15.494  0.197 

At most 3  0.083  3.382  3.841  0.065 

Hypothesized No. of CE(s) Eigenvalue Max-Eigen Statistic 0.05 Critical Value Prob.** 

None *  0.579  33.794  27.584  0.007 

At most 1 *  0.430  21.932  21.131  0.038 

At most 2  0.182  7.851  14.264  0.394 

At most 3  0.083  3.382  3.841  0.065 
Source: Compiled by the Author as computed from E-Views software 
 * and In respectively implies rejection of the hypothesis at the 0.05 level and natural log transformation. 

 
In compliance with the econometric requirements for verifying the stationarity properties of the series and 

estimating the error correction model, cointegration test was undertaken at 5 percent level. The results indicate 
that both the Trace and Maximum Eigenvalue statistics confirm that two cointegrating equations exist in the 
model. In other words, the variables are cointegrated and the dynamic relationship among them can be represented 
as an ECM.  
 

4.5. Error Correction Model 
The error correction model was estimated to provide better information on the dynamic relationship between 

the dependent and the predictor variables. The result of its parsimonious representation is reported in Table 4.5. 
 

 
 
 
 
 
 
 
 



Economy, 2018, 5(1): 8-16 

15 
 

 

Table-4.5. Parsimonious ECM 

Dependent Variable: DLOG(APO)   

Method: Least Squares   

Variable Coefficient Std. Error t-Statistic Prob.   

ECM(-1) -0.378 0.076 -4.979 0.000 

C 0.522 0.073 7.072 0.000 

DIn(APO(-1)) 0.116 0.113 1.019 0.318 

DIn(APO(-2)) -0.442 0.091 -4.862 0.000 

DIn(POB) -1.048 1.093 -0.958 0.347 

DIn(POB(-1)) -3.098 0.699 -4.426 0.000 

DIn(POB(-2)) -3.975 0.747 -5.318 0.000 

DIn(POB(-3)) 2.299 1.232 1.865 0.074 

DIn(EPO) -0.231 0.401 -0.577 0.569 

DIn(EPO(-1)) -2.422 0.588 -4.114 0.000 

DIn(EPO(-2)) -1.785 0.500 -3.569 0.001 

DIn(EPO(-3)) -2.042 0.525 -3.888 0.000 

DIn(PMP) 2.119 0.986 2.147 0.042 

DIn(PMP(-3)) 1.792 1.169 1.532 0.138 

R-squared 0.865   

F-statistic 11.921       

Prob(F-statistic) 0.000   
        Source: Compiled by the Author as computed from E-Views software 
 

It was discovered from the result that the coefficient (-0.378) of error correction has the intended theoretical 
negative sign and also satisfies the statistical condition at 1 percent level. It is clear from this finding that any short 
run disequilibrium in the system can be corrected in the long run at a speed of 39 percent.  The results show that 
the dynamic coefficients of stocks of poultry birds are negative and significant. This implies that increasing stocks 
of poultry birds by 10 percent at lag 1 and 2 would respectively contract agricultural GDP by 31 percent and 39 
percent. Again, poultry eggs production lagged for one, two and three periods are negatively related to agricultural 
output. However, it was found that poultry meat production is associated with a positive and significant coefficient. 
The implication of this finding is that the production of poultry meats enhances agricultural GDP through its 
contribution to the livestock sub-sector. Both the R-squared (0.865) and F-statistic (11.92) reveal that the model 
well is fitted and satisfies the statistical condition. Thus, with R-squared (0.865) exceeding the benchmark of 0.50, 
it implies that the explanatory variables collectively explained 87 percent variations in agricultural GDP over the 
period covered.  
 

4.5.1. Post-Estimation Tests 
The estimation of the parsimonious ECM is followed by post-estimation tests. These tests particularly focused 

on higher order test for serial correlation and heteroskedastic test for constant variance of the residuals. The 
results are showed in Table 4.5.1A and 4.5.1B. 
 

Table-4.5.1A. Breusch-Godfrey Serial Correlation LM Test Result 

Breusch-Godfrey Serial Correlation LM Test:  

  

F-statistic 1.378     Prob. F(3,21) 0.2768 

Obs*R-squared 6.251     Prob. Chi-Square(3) 0.1000 
                      Source: Compiled by the Author as computed from E-Views software 

 
Table-4.5.1B. Harvey Heteroskedastic Test Result 

F-statistic 0.958     Prob. F(13,24) 0.5149 

Obs*R-squared 12.985     Prob. Chi-Square(13) 0.4489 

Scaled explained SS 11.091     Prob. Chi-Square(13) 0.6031 
       Source: Compiled by the Author as computed from E-Views software 

 
In furtherance of the efforts to determine if the estimated regression parsimonious ECM model satisfies 

important econometrics conditions, some post-estimation tests, especially tests for serial correlation and 
homoscedasticity was carried out at 5 percent level. It was discovered from the test results that the model 
(parsimonious ECM) is not serially correlated and free of the problem of heteroskedastic. The implication of this 
finding is that reliable and efficient forecast can be achieved based on the outcome of the model. 

 
5. Conclusion and Policy Recommendation 

This study examined the place of poultry production on agricultural GDP. The findings reveal that poultry 
meat production contributes positively to agricultural GDP, thus stimulating aggregate output and enhancing food 
security. Additionally, poultry birds’ population and output of poultry eggs significantly explained changes in 
agricultural GDP. Hence, the conclusion with regard to the findings is that the place of livestock sub-sector in 
meeting broad-based objective of improved productivity in the agricultural sector can be achieved through 
increased and sustained growth of poultry production in Nigeria. Hence, this study recommends that governments 
at all levels should evolve measures that promote huge commitment to infrastructural development in agricultural 
sector in order to boost poultry output and promote self-sufficiency in poultry farming.  
 



Economy, 2018, 5(1): 8-16 

16 
 

 

References 
Aboki, E., A.A. Jongur and J.I. Onu, 2013. Productivity and technical efficiency of family poultry production in Kurmi local government area 

of Taraba State, Nigeria. Journal of Agriculture and Sustainability, 4(1): 52-66. View at Google Scholar   
Amar-Klemesu, M. and D. Maxwell, 2000. Accra: Urban agriculture as an asset strategy. In: Supplementary income and diets, Bakker, N., 

Dubbeling, M., Gundel, S., Koschella, U.S and Dezeeuw, H. (Eds). Growing cities, growing food, Havana, Cuba. pp: 234-236. 
Ayieko, D.M.O., E.K. Bett and L.W. Kabuage, 2014. Profitability of indigenous chicken: The case of producers in Makueni County, Kenya. 

Journal of Economics and Sustainable Development, 5(11): 16-23.  
Bamiro, O.M., 2008. Economic performance of commercial poultry farms in Oyo State Nigeria. International Journal Poultry Science, 7(11): 

1117-1121. View at Google Scholar | View at Publisher 
Connolly, A.J., 2014. A glimpse into the future: A lens through which to consider ‘Africa’s rising’. International Food and Agribusiness 

Management Review, 17(B): 9-18. View at Google Scholar   
Dickey, D.A. and W.A. Fuller, 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Journal of the Econometric 

Society, 49(4): 1057-1072. View at Google Scholar | View at Publisher 
Emokaro, C.O., F.K. Akinrinmola and O.P. Emokpae, 2016. Economics of backyard poultry farming in Benin city, Edo State, Nigeria. 

Nigerian Journal of Agriculture, Food and Environment, 12(2): 50-57. View at Google Scholar   
Esiobu, N.S., C.S. Nwosu and G.C. Onubuogu, 2014. Economics of pineapple marketing in Owerri Municipal Council Area, Imo State, 

Nigeria. International Journal of Applied Research and Technology, 3(5): 3 – 12. View at Google Scholar   
Ezeh, C.I., C.O. Anyiro and J.A. Chukwu, 2012. Technical efficiency in poultry broiler production in Umuahia capital territory of Abia State, 

Nigeria. Greener Journal of Agricultural Sciences, 2(1): 001-007. View at Google Scholar | View at Publisher 
Hamid, M.A., M.A. Rahman, S. Ahmed and K.M. Hossain, 2017. Status of poultry industry in Bangladesh and the role of private sector for its 

development. Asian Journal of Poultry Science, 11(1): 1-13. View at Google Scholar | View at Publisher 
Heise, H., A. Crisan and L. Theuvsen, 2015. The poultry market in Nigeria: Market structures and potential for investment in the market. 

International Food and Agribusiness Management Review, 18(1): 197-222. View at Google Scholar   
Johansen, S. and K. Juselius, 1990. Maximum likelihood estimation and inference on cointegration—with applications to the demand for 

money. Oxford Bulletin of Economics and Statistics, 52(2): 169-210. View at Google Scholar | View at Publisher 
Leontief, W.W., 1951. The structure of the American economy 1919-1939: An empirical application of equilibrium analysis. New York: 

Oxford University Press. 
Mankiw, G., 2015. Yes, r > g. So what? American Economic Review, 105(5): 43-47. View at Google Scholar | View at Publisher  
Nwandu, P.I., J.A. Ojogbane, C. Okoh and F. Okechukwu, 2016. Poultry production business: A means of alleviating poverty among farmers. 

New York Science Journal, 9(7): 92-100.  
Ocholi, R.A., I.L. Oyetunde, P. Kumblish, O. M.O. and Taama, 2006. Epidemology of an outbreak of highly pathogenic avia influenza caused 

by the virus subtype. Journal of Veterinary Science National Veterinary Research Institute Jos, 2(8): 1-8.  
Ojo, S.O., 2003. Productivity and technical efficiency of poultry egg production in Nigeria. International Journal of Poultry Science, 2(6): 

459-464. View at Google Scholar | View at Publisher 
Phillips, P.C. and P. Perron, 1988. Testing for a unit root in time series regression. Biometrika, 75(2): 335–346. View at Google Scholar | View at 

Publisher 
Presidential Committee on Livestock (PCOL), 2003. Report of the Presidential Committee on Livestock, Consolidated Report, 1. 
Rotschild, J., 2002. Nigeria poultry and products poultry update. Gain Report. 
Sonaiya, E.B., 1990. The context and prospects for development of small-holder rural poultry production in Africa. Proceedings of the CTA 

International Seminar, Oct. 9-13. Thessaloniki, Greece. pp: 35-52. 
Tijjani, A.A., T. Alimi and A.T. Adesiyan, 2006. Profit efficiency among Nigerian poultry egg farmers: A case study of aiyedoto farm 

settlement, Nigeria. Research Journal of Agricultural Biological Sciences, 2(6): 256-261. View at Google Scholar   
Ume, S.I., P.C. Jiwuba, J.I. Obi and E. Dauda, 2016. Economics of broiler production among rural women in Ahiazu Mbaise L.G.A of Imo 

State, Nigeria. Asian Research Journal of Agriculture, 1(2): 1-8. View at Publisher 
Yusuf, T.M., S.A. Tiamiyu and R.O. Aliu, 2016. Financial analysis of poultry production in Kwara State. Nigeria African Journal of 

Agricultural Research, 11(8): 718-723. View at Google Scholar | View at Publisher 
 

 
  
 

 

 

 

 

 

 

 

 

 

 

 

  

Asian Online Journal Publishing Group is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use of the content. 
Any queries should be directed to the corresponding author of the article. 
 

https://scholar.google.com/scholar?hl=en&q=Productivity%20and%20technical%20efficiency%20of%20family%20poultry%20production%20in%20Kurmi%20local%20government%20area%20of%20Taraba%20State,%20Nigeria
https://scholar.google.com/scholar?hl=en&q=Economic%20performance%20of%20commercial%20poultry%20farms%20in%20Oyo%20State%20Nigeria
http://dx.doi.org/10.3923/ijps.2008.1117.1121
https://scholar.google.com/scholar?hl=en&q=A%20glimpse%20into%20the%20future:%20A%20lens%20through%20which%20to%20consider%20‘Africa’s%20rising’
https://scholar.google.com/scholar?hl=en&q=Likelihood%20ratio%20statistics%20for%20autoregressive%20time%20series%20with%20a%20unit%20root
http://dx.doi.org/10.2307/1912517
https://scholar.google.com/scholar?hl=en&q=Economics%20of%20backyard%20poultry%20farming%20in%20Benin%20city,%20Edo%20State,%20Nigeria
https://scholar.google.com/scholar?hl=en&q=Economics%20of%20pineapple%20marketing%20in%20Owerri%20Municipal%20Council%20Area,%20Imo%20State,%20Nigeria
https://scholar.google.com/scholar?hl=en&q=Technical%20efficiency%20in%20poultry%20broiler%20production%20in%20Umuahia%20capital%20territory%20of%20Abia%20State,%20Nigeria
http://dx.doi.org/10.15580/gjas.2013.3.1206
https://scholar.google.com/scholar?hl=en&q=Status%20of%20poultry%20industry%20in%20Bangladesh%20and%20the%20role%20of%20private%20sector%20for%20its%20development
http://dx.doi.org/10.3923/ajpsaj.2017.1.13
https://scholar.google.com/scholar?hl=en&q=The%20poultry%20market%20in%20Nigeria:%20Market%20structures%20and%20potential%20for%20investment%20in%20the%20market
https://scholar.google.com/scholar?hl=en&q=Maximum%20likelihood%20estimation%20and%20inference%20on%20cointegration—with%20applications%20to%20the%20demand%20for%20money
http://dx.doi.org/10.1111/j.1468-0084.1990.mp52002003.x
https://scholar.google.com/scholar?hl=en&q=Yes,%20r%20%3e%20g.%20So%20what?
http://dx.doi.org/10.1257/aer.p20151059
https://scholar.google.com/scholar?hl=en&q=Productivity%20and%20technical%20efficiency%20of%20poultry%20egg%20production%20in%20Nigeria
http://dx.doi.org/10.3923/ijps.2003.459.464
https://scholar.google.com/scholar?hl=en&q=Testing%20for%20a%20unit%20root%20in%20time%20series%20regression
http://dx.doi.org/10.2307/2336182
http://dx.doi.org/10.2307/2336182
https://scholar.google.com/scholar?hl=en&q=Profit%20efficiency%20among%20Nigerian%20poultry%20egg%20farmers:%20A%20case%20study%20of%20aiyedoto%20farm%20settlement,%20Nigeria
http://dx.doi.org/10.9734/arja/2016/27428
https://scholar.google.com/scholar?hl=en&q=Financial%20analysis%20of%20poultry%20production%20in%20Kwara%20State
http://dx.doi.org/10.5897/ajar2015.10690

