Table of Contents
Greener Journal of Agricultural Sciences
ISSN: 2276-7770
Vol. 15(4), pp. 142-155, 2025
Copyright ©2025, Creative Commons Attribution 4.0 International.
https://gjournals.org/GJAS
DOI: https://doi.org/10.15580/gjas.2025.4.012825012
1 Department of Economics, University of Uyo, Nigeria.
Email: udoffiadave@gmail.com; davidudoffia@uniuyo.edu.ng
2 Department of Economics, University of Uyo, Nigeria.
Email: udofialawrence@gmail.com
3 Department of Economics, University of Uyo, Nigeria.
Email: Princesunday535@gmail.com
Type: Research
Full Text: PDF, PHP, HTML, EPUB, MP3
DOI: 10.15580/gjas.2025.4.012825012
Accepted: 19/02/2025
Published: 31/12/2025
Udoffia, DT
E-mail: udoffiadave@gmail.com, davidudoffia@uniuyo.edu.ng
Keywords: Diversification, Agricultural Sector output, Economic growth
The study examined the role of agricultural sector in the diversification of Nigeria economy employing annual time series data obtained from Central Bank of Nigeria statistical bulletin and World Bank Data base for the period 1982 to 2023. The specific objectives were to determine the impact of Agricultural Sector Output on economic growth and causal relations between Agricultural Sector Output and other sectors of the economy in Nigeria. The study employed the Augmented Dickey Fuller (ADF) unit root test, ARDL Bounds test for cointegration, the error correction mechanism and Granger causality test. The results of the ARDL and ECM indicated that the agricultural sector’s production significantly impact economic growth of Nigeria. The coefficient of the ECM was negative and statistically significant at 5%, Findings of the study from the Granger causality test reveals a unidirectional causal relation running from Agricultural sector to Manufacturing sector while there’s no significant causal relation between Agriculture, Trade and Transportation for the period of study. The research proposed, among other things that, Government should strongly diversify the economy through sufficient investment and budgetary allocation into the agricultural sector, efficient utilization of allocated resources in order to guarantee agricultural productivity.
The issue of economic diversification in developing countries, including Nigeria, has received appreciable attention from researchers (Adeola and Evans, 2017; Anyaehie and Areji, 2015; Ogochukwu, 2016; Sertogluet et al, 2017). In Nigeria, the agricultural sector accounted for a larger share of the GDP before the discovery of crude oil in commercial quantity in 1956 in Oloiribi and became a major oil producer led to a shift in the country’s focus from agriculture to crude oil. The government revenue rose from 10% of GDP in the 1960s to 30% in 1980s with the increase attributed to higher oil production and prices and oil exports from 5% to 24% (Bevan et al ,1999 and Ross, 2012).
Nigeria is blessed with various natural resources, vast and fertile lands which can enhance the production of food, crops and other agricultural produce but the underutilization of these resources have led to poverty, increasing unemployment, low standard of living and food insecurity (Awad, 2010; Eze and Ogiji, 2013). The neglect of other sectors such as: Manufacturing, Agriculture, Mining, Tourism, service sector among other sectors of the economy and over dependent on oil has been blamed for increased poverty, unemployment and other problems facing the Nigerian economy (Inakwu, 2013; Rioba, 2014, Udofia and Essang, 2015). The contribution of agriculture rose to 26.38% as at 2003 with a further rise to 25.56% as at 2006. In 2018, agriculture contributed 25.13% to GDP (Central Bank of Nigeria, 2018). Comparing to the 1960s, agriculture was a major source of export earnings, it contributed, on the average, over 65% of total export, with attendant emphasis on export of cash crops such as cocoa, rubber, hides and skin, groundnut, and palm oil (Kamil, Sevin, and Festus, 2014).
Nigerian government opted for importation of food to feed its growing population due to the agricultural sector not playing an optimal role in the Nigerian economy. If these challenges are addressed by government and stakeholders in the agricultural sector, it will bring an immense improvement in the levels of agricultural output and would translate to opportunities that could reposition Nigeria as a leader in the food chain and agro-allied products globally, and therefore the need for diversification of the Nigerian economy through agriculture.
The broad objective of this study is to examine the role of agricultural sector in the diversification of the Nigerian economy using annual data covering the period of 1982 to 2023. Further to this, the aim of the study is disaggregated into some specific objectives presented thus;
Given the above objective, attempts were made to provide answers to a series of questions including;
The hypotheses of the study include:
H01: Agricultural production does not have a significant impact on economic growth in Nigeria.
H02: There is no significant causal-effect between agricultural sector performance and the growth of other sectors in Nigeria.
Based on the objectives the study is very significance because agricultural sector plays an important and significant role in the diversification of the Nigerian Economy, a study of possible strategies towards revamping of the agricultural sector is crucial. Arguments against the over dependence on crude oil from policy makers, economists and researchers are too strong to be ignored. Some of these include: Vulnerability to oil price fluctuations. Relying heavily on oil revenue makes the economy susceptible to changes in global oil prices, which can lead to economic instability and budget deficits; Overemphasis on oil can result in neglect of other sectors such as agriculture, manufacturing, and services, which are essential for sustainable economic growth and job creation; lack of economic diversification can limit job opportunities outside the oil sector, leading to high unemployment rates and income inequality; lack of diversification can stifle innovation and hinder the development of new industries or technologies, making the economy less competitive in the long run.
The scope of this study was on the role of agricultural sector in the diversification of the Nigerian economy using time series data which covered a period of 41 years, that is, from 1982 to 2023, a time long enough to assess the subject under consideration
The study is organized as follows: Part II provides a review of relevant literature, Part III outlines the methodology, Part IV analyzes the findings, and Part V contains conclusion and recommendations.Top of Form
The Concept of the Agriculture
Agriculture is a way of life that involves production of animals, fishes, crops, forest resources for the consumption of man and supply of agro-allied products required by various sectors. It is seen as the inherited and dominant occupation employing about 70% of Nigerians. Agriculture is a vital sector that supports food security, economic development, and employment, especially in rural areas. It encompasses both traditional farming methods and modern agricultural technologies designed to increase productivity and sustainability.
Though, subsistence agriculture is practiced in this part of the world, it will not be an overstatement to say that it is the life-wire of the economies of developing countries. Broadly speaking, agricultural activities are undertaken as peasant farming and plantation farming. Peasant farming involves cultivation of small-scale acres of land. This is also called subsistence agriculture because it is undertaken to meet domestic needs and survival or to eke out living from the farm produce. The size of the land used by peasant farmers is determined by the size of their family. Rudimentary agriculture equipment such as hoes, cutlasses, and axes etc. which are crude in nature, and are usually used.
Plantation farming involves the use of a large estate of land permanently planted with economic or commercial crops which include cocoa, tea, cotton, sugar, tobacco, rubber, sugarcane, palm tree, coffee and other commercial crops. In plantation farming land could be owned by government, private individuals or corporate bodies. Mechanized equipment and modern inputs are mainly used in plantation farming.
Overview of the Nigerian Agricultural Sector
The Nigerian agricultural sector is composed of the following sub-sectors whose contribution to the agricultural output vary significantly towards a monopolistic structure. They include crop production, livestock, fishery and forestry. According to Statista (2023), in the second quarter of 2023, the agricultural sector generated about 21% of Nigeria’s Gross Domestic Product. The largest contribution was from crop production, which covers 18.56% of the GDP. Livestock subsector accounts for 1.27% of the GDP, Fishing accounts for 1.04% and forestry contributes the lowest with 0.21% of the GDP. Agriculture accounts for a significant portion of Nigeria’s GDP as a key activity for the country’s economy after oil.
Crop Production Subsector:
Crop production involves the cultivation of different crops which may be food or cash crops. It is arguably the largest subsector of the Nigerian agriculture sector as it accounts for over 90% of the sector’s growth according to (CBN, 2018). This giant stride is accorded to peasant or small-holder farmers who are engaged largely in the production of food staples such as; oil palm, rice, maize, beans, guinea corn, millet, yam etc. It was further stated that the subsistent farmers produce 90% of our food products within Nigeria. Two notable crops that Nigeria is known for in this subsector are rice and cassava. The FAO (2018) rates Nigeria not only Africa’s first in rice consumption but also ranks it among the largest if not the first in both production and importation of rice. Empirics from FAO (2018), have shown that, production hit approximately two million metric tons during the year 2018 whereas importation dwarfed this number by a million metric tons. Commenting further, the Food and Agriculture Organization declared Nigeria as the global champion in cassava farming. Several challenges have been identified as bottleneck to the sector, among which are; seasonality reliance, lack of fertilizer, shortage in extension services, low capital and financial exclusion of farmers etc.
Livestock Subsector:
Livestock is concerned with the rearing of domestic animals such as goat, ram, sheep, poultry birds among others for consumption. They are also referred to as “food animals”. The country’s livestock profile from World Bank (2017) reveal that, the livestock sub-sector has been growing at a rate of 12.7%, higher than agricultural growth rate of 6.8% annually. The subsector is vital to the socio-economic development and key for nutritional security, providing 36.5 percent of the proteins consumed by the populace in Nigeria. Majority of Nigerian livestock owners are the rural poor, and a significant proportion of the urban poor as well, and evidence indicate that livestock development would positively contribute to poverty alleviation. Despite the large herd size, apart from eggs, livestock sub-sector’s production does not meet the current need. The difference between domestic demand and supply is projected to widen in future which is beginning to play out (World Bank, 2017). Nigeria currently imports more than 70% of its poultry and 25% of its beef requirement to meet its domestic demand. The North region has the largest population of livestock in the country, about 90% of the country’s cattle population and 70% of country’s the sheep and goat population (World Bank, 2017). On the other hand, poultry is distributed across Nigeria with greater concentration in the South-West and South-East regions of Nigeria.
Fisheries:
This subsector is involved in the catching, processing and selling of fish and other aquatic animals. According to the Food and Agriculture Organization statistics of 2017, Nigeria is ranked 1st in sub-Saharan Africa. Its production was estimated at 21,700 during a year before the new millennium but steadily increased to 316,700 tons in 2015. The FAO statistics further reveal that, an estimate of over a million tons of fishes were produced during the year 2015 out of which catches from marine and inland coastlines had 36% and 33% respectively whereas the remaining 31% was from aquaculture. Although the fishery subsector is a very good source of the proteins to Nigerians; however, it has remained at the bottom of the list in terms of its share to the GDP as its contributed only 0.5% in 2015. With a total bill of USD 284 million and USD 1.2 billion for exports and imports Nigeria is regarded as a net importer of fish in 2013 (FAO, 2017). This is largely attributable to the fact that almost 80% of the domestic production is generated by low-skilled, poor and subsistent fishermen within the inland waterways as opposed to a high-tech, capital-intensive aquaculture mode of production. Rondon and Nzeka (2010) as cited in Oyakhilomen and Zibah, (2013) reported Nigeria’s fish demand amounting to nearly $1.8 billion in 2009. The subsector is a major occupational hub particularly to the rural dwellers in the riverine areas such as the Niger Delta region. As at 2018, FAO put the number of inland fishermen to be over 700,000 out of which 20% were women. Whereas the Nigeria fishery industry employs 490,000 in 1990, but as the new millennium enters, employment increased to 1.1m, 1.4m, 1.5m in 2010, 2015, 2016 respectively (FAO, 2018).
Forestry:
Forestry is the science and practice of managing, conversing and using forests and forest lands to meet various ecological, economic, and social objectives. Forest is important in the sense that it houses pharmaceuticals, regulates the atmosphere as it neutralizes the solar heat, protect the soil, provides wax, rubber, pulp, oils and other essential industrial input of economic value. It is regarded as a national economic resource due to its primary nature in the line of production. The trees found here, are not only a source of wood for our furniture or fuel in both the rural and semi urban cities they are more importantly a primary source of inputs to the Pharmaceutical industry. In Nigeria, there exist game reserves and national parks; a total of 32 and 7 respectively with an estimated coverage of over a total of about 4 million as at 2000 (FAO, 2010). Additionally, Larinde and Chima (2018) report that the Nigeria forest repository are: Olokemeji forest reserve, Gambari forest reserve, Omo forest reserve, Akure/Ofosu forest reserves, Idanre forest reserve, Ifon/Owo forest reserves, Eba forest reserve, Ofogbo forest reserve, Obiaruku forest reserve, Ngel-Nyaki forest reserve, Afi River Forest Reserve, IITA forest reserve, Ibadan, Kagoro-Nindam forest reserve, Donga River Basin forest reserve, Upper Orashi forest reserve, Biseni forest reserve, and Akassa forest reserve.
Concept of Economic Diversification
Economic diversification is creating new avenues for economic growth. It involves using the right strategy to boost revenue generated from other sectors of the economy. That is, facilitating growth of other sectors of the economy (Eluogu, 2017). In more specific terms, it is the process of expanding the range of economic activities both in the production and distribution of goods and services. It is the widening of the economy to create opportunities for diverse economic activities in order to create a broad-based economy (Anyaehie and Areji, 2015). Diversification is a multi-sector economic growth strategy that can be likened to investing in a variety of assets (Ojefia, 2016). In the view of Uzonwanne (2015), it demands active participation in a wide range of sectors. Underlying economic diversification is the idea of having multiple streams of income by creating multiple revenue centers (Ojefia, 2016). This will, in turn, encourage the creation of different ways to increase cash flow as opposed to building a single income stream. During recession, diversification serves as a mechanism for checks and balances. The positive performance of some sectors (or subsectors) neutralizes, balances, or cancels out the negative performance of others, thereby minimizing risks.
Theoretical Review
Vent for Surplus Theory:
This theory is predicated on the availability of surplus and idle people and material resources, particularly in developing nations. Access to overseas markets allows “surplus productive capacity” to be utilized under the “vent for surplus” model of agricultural growth. Even after the immediate benefits of trade are achieved, the “indirect impacts” of trade contribute to long-term economic growth and development. The distribution of new revenue streams among the population may have ramifications for long-term economic prospects.
The idea stresses the efficiency of production systems, resulting in excess production when the output surpasses the starting input. When a particular sector produces more than the country’s demand, the surplus is approved by the authority and exported abroad in exchange for something they can’t produce at home. Without such exportation, a portion of the country’s productive labor will be reduced, and the value of its annual produce of their labor may exceed home consumption. This encourages the country to improve its productive process and augment its annual produce.
However, under the vent-for-excess method, trade does not result in any resource reallocation; rather, it assumes that additional raw materials will be produced from available surplus land and labor, i.e., trade induces a “vent” or an outlet for underused resources. To create additional raw resources, Nigeria employs primitive equipment and massive land cultivation. However, as raw material costs rise due to insufficient supply vs rising demand, foreign commerce declines, and the country’s economic process slows even more as a result of its inability to maintain and become competitive in international trade.
This theory is relevant and applicable to the Nigerian Agricultural sector in that it helps us to utilize our idle land and labour. Nigeria have vast areas of arable land that remain underutilized. By bringing these lands into cultivation, Nigeria can increase its agricultural output. Additionally, a significant portion of the rural population is engaged in subsistence farming with low productivity. By effectively utilizing this labour, agricultural productivity can be enhanced.
Surplus agricultural production if achieved in Nigeria will improve food security reducing reliance on food imports, this particularly important given the growing population. Also, if agricultural sector produces a surplus, it can lead to development of other industries and sectors. This diversification makes the economy more resilient and less dependent on a single sector.
Structural Change Theory:
The theory, formulated by W. Arthur Lewis in the mid-1950s, emphasized on the mechanism by which developing economies can transform their domestic structure from a heavy dependence on traditional subsistence agricultural to a more modern and advanced agricultural practices through sufficient financial support. An extended version of this theory adds that increased agricultural development cannot be realized unless government builds a supporting system which creates and provides the necessary incentives, opportunities and most importantly productivity in the agricultural sector.
By applying structural change theory, Nigeria can strategically shift resources from traditional, low-productivity agricultural practices to more modern, high-productivity sectors. Introducing machinery and modern equipment can increase efficiency and productivity. This transformation can lead to increased agricultural output, higher incomes for farmers, job creation, and overall economic development. It requires a coordinated effort involving government policies, private sector investment, and capacity building to achieve sustainable and inclusive growth in the agricultural sector.
Sustainable Livestock Theory:
Chamber and Conway (1991) extended the sustainable livestock theory for capabilities, including capital and other social resources as well as other farming practices required for a means of living. The theory holds that increase output can only be achieving by ensuring secured ownership of, or access to capital resources and income earning activities which includes; reserves and assets to offset risk, ease stocks and meet contingencies as well as enhancement and maintenance of productive resources on a long-term basis. Therefore, increase agricultural output (food security) is not just food affordability but the ability to produce food and earn income on a long-term basis by farmers.
By applying sustainable livestock theory, Nigeria can achieve a balance between livestock production and environmental, economic, and social sustainability. By implementing rotational grazing and improved pasture management can prevent overgrazing, soil degradation, and desertification. These practices help maintain healthy ecosystems and improve land productivity. Investing in improved breeds, better veterinary services, and nutritional management can increase livestock productivity. This leads to higher milk, meat, and egg production, enhancing farmers’ incomes.
Empirical Review
There are plethora of literatures and related studies that examines the role of agriculture sector in diversification of Nigerian Economy. These works of literature differ in terms of time, space, setting, and methodology.
Iganiga and Unemhilin (2012) using an Ordinary Least Squares (OLS) econometrics approach on a time series data set spanning over 30 years between 1980 and 2012, studied the influence of government investment on agricultural and economic growth. According to the findings, there is a positive and substantial relationship between GDP and agricultural output. The research also identified a few obstacles, including a lack of money accessible to rural farmers and insufficient infrastructure, as well as a focus on timely and adequate agricultural extension services among all important agricultural agents.
Ideba (2012) examined the influence of agricultural development on Nigerian growth over a 30-year period (1980-2010). The study uses the OLS approach to evaluate whether the agricultural sector functions as an engine room for growth and development by employing agricultural development, capital formation, inflation rate, and interest rate. According to the findings, there is a beneficial association between the agricultural sector and economic growth. According to this study, the government should establish and implement modern policies to help the industry compete with other areas of the economy.
Dim (2013), in his work entitled. Does agriculture important for economic growth, empirical evidence from Nigeria, disagrees with other scholars. In Nigeria, he discovered, using the unit root test and the Newey-West approach, that agricultural production had a negative but statistically significant influence.
Going through the empirical work of Anyanwu, Ibekwe and Adesope (2010) were they examined trend analysis of the impact of agriculture to GDP for a period of 53 years, precisely between 1960 and 2012 using time series data. The finding from their work revealed that the agricultural sector’s share of GDP experiences a decline. Regardless of the retrogression, agricultural sector still had a superior lead over other sectors from 1960 to 1975.The study also depicts a fluctuation between the industrial sector around 1967 to 1989.The regression results, shows that there exist a positive and significant relationship between the agricultural sector with GDP accounting for 66.4 percent of the variation in the economy, and also displays the dominance of the agricultural sector relative to other sectors of the economy. The study recommended that there should be a conducive and enabling environment provided by the government and decision makers so that the full gains can be derived from the sector, and also the Nigeria state can realize the much-clamored vision of being the among the top 20 leading economies in the year 2020.
Kenny (2014) performed study on the influence of agriculture on economic growth and development during a 30-year period spanning the years 1981 to 2012. He looked at the importance of agriculture in the progress of the Nigerian economy, considering the government’s and decision-makers’ negligence over the years. Kenny employed econometrics to test his hypothesis, using the Solow growth model, which includes gross capital formation (GCF) as a proxy for capital, post-secondary enrolment as a substitute for labor, and real gross domestic product as a proxy for agricultural production and economic growth and development (RGDP). For the long-term partnership, the Restricted Error Correction Approach was used. Agriculture, according to the report, plays a significant part in Nigeria’s economic growth and development. According to his results, the agricultural sector still contributed to GDP, however there has been a reduction since the 1990s, which may be attributed to the coming of the new bride (oil discoveries) in the late 1970s.
Olajide, Akinlabi and Tijani (2012) used a multivariate Johansen co-integration analysis to look at the association between agricultural export and economic growth in Nigeria from 1980 to 2012. To assess the long-run and short-run link between agricultural export and economic growth, they used a stationarity test utilizing Phillips-Peron unit root test, Johansen co-integration, and Error Correction Method. The outcomes of this study indicated that agricultural export and agricultural output have a long-term link and are considered a vital driver of Nigerian economic growth and development. It was suggested that the government pay more attention to agricultural exports since they act as a stimulant for Nigeria’s much-needed economic expansion and development.
Eboh, Oduh and Ujah (2012) examined the factors that drive Nigeria’s agricultural growth. Using hypothesized traditional factor inputs, they estimated a global agricultural production function for Nigeria based on the Cobb-Douglas model, assuming Hicks-neutral technological progress. Also, they estimated an econometric model of total factor productivity (TFP) based on ‘Solow Residual’. Their analysis showed that Nigerian agricultural sector is characterized by increasing returns to scale, which implies that farmers are operating at the low end of the production function. The relatively more important factors that were found to influence Nigeria’s agricultural value added include rainfall, technology (efficiency parameter) and fertilizer use; land area is the least important factor. Capital expenditure on agriculture, price of agricultural commodities, per capita income and investment rate in agriculture, human capital and access to credit are positive influences on total factor productivity.
Inusa, Daniel, Dayagal and Chiya (2018) investigates the impact of agriculture on economic growth of Nigeria using Ordinary Least Squares (OLS) regression technique on a time series data from 2016 to the second quarter of 2017. The study discovered that exchange rate has positively and significantly impacted agricultural output. Loans and advances, and total savings were also discovered to have significantly impacted agricultural output as a component of GDP. The study recommends that agricultural inputs be largely sourced locally and foreign exchange be made favorable, government allocation to the sector be increased and monitored to ensure prudency in its usage.
In their paper, Effiong, Inyang and Okon (2020) examined the role of agriculture in Nigeria diversification agenda and economic growth. Obtained time series data covering 1986 to 2018 with the econometric result based on error correction modelling framework. Findings of the study further revealed that all the components of agricultural production – crop production, livestock production, forestry, and fisheries – exerted a positive and significant long-run effect on economic growth, with livestock production exerting the greatest effect within the study period. The error correction mechanism indicated that 71.07% of the short-run disequilibrium is corrected in the long-run. The paper recommended that for the country to strongly diversify, government needs to invest aggressively on the agricultural sector so as to reap its full potentials
More recently, Uzonwanne, Mbah, Obi and Onyedibe (2023) analyzed the impact of crop production on the gross domestic product in the Nigerian economy using time series data ranging from 1981 to 2021. The study adopted OLS techniques for the regression analysis. The variables of the study were subjected to unit root tests and were found to be stationary at first difference. Johansen cointegration was adopted and the result posits a short-run relation between the variables of interest (GDP, crop production (CP) as well as labor output (LO). The result from the error correction model shows that crop production has a positive and significant impact on economic growth in Nigeria. This study also finds that labor productivity has a positive and significant impact on economic growth. The study concluded that crop production has a positive and statistically significant impact on economic growth in Nigeria.
Based on the empirical literatures reviewed above, most studies span from 1960 to 2021 thus limiting insights into recent developments and policy impacts. However, a major gap identified in the literatures above is that it doesn’t efficiently capture the contribution of agricultural sector output performance on the growth of other sectors in Nigeria. On this ground, this study seeks examine the contribution of agricultural sector output performance on the growth of other sectors in Nigeria considering a sample of other sectors (Industrial Sector i.e. Manufacturing, Services Sector i.e. Transportation, Trade) assessing if there be any economic linkages and interdependencies as well as its impact on economic growth over the period (1982-2023).
Model specification
In order to appropriately study the impact of agricultural sector output on economic growth in Nigeria, the method of Olabanji, Adebisi, Ese and Emmanuel (2017) will be adopted in this study. The original model is stated below:
RGDP = f(AGPO, INTR, INFL, EXR) (1)
Where:RGDP= Economic growth proxy by real Gross Domestic Product (in naira)AGPO = Agricultural Output
INTR = Interest rate (per cent)EXR = Exchange rate (naira per US dollar)INFL= Inflation rate (per cent)
The model, as specified in equation 1, is modified for this study to capture Total Government Expenditure and Gross Fixed Capital Formation as they are also some of the variables that affect economic growth in relation to the agricultural sector. Therefore, the model becomes:
RGDP = f (ASO, INTR, INFR, GFCF, TGE) (2)
Where:RGDP = Economic growth given by real GDP (in naira);ASO = Agricultural sector output (% GDP);
INTR = Lending interest rate (annual %);
INFR = Inflation rate (Consumer Prices, annual %);
GFCF = Gross fixed capital formation (investment) as a percentage of GDP;TGE = Total Government expenditure;
Re-writing equation (2) in an econometric form, we have the equation in an estimable and transformed form below:
LogRGDPt = β0 + β1LogASOt + β2INTRt + β3INFRt + β4GFCFt + β5LogTGEt + µt (3)
Where log is the natural log, β0 – β5 are parameters to be estimated, µt is the Error term and subscript “t” to indicate it is time series. INTR and INFR are not in log form since they are rates. The essence of the log is to help us in linearizing the variables and in explaining the coefficients of the explanatory variables in elasticities.
A-Priori Expectations
β1>0; β2<0; β3<0; β4>0 and β5>0; The sign (>0 or <0) associated with the β’s represents the a-priori expectation of each explanatory variable used in the study. An explanatory variable with a β>0 (positive parameter) is expected to have a positive impact on the independent variable and vice versa.
Nature and Sources of Data
The data employed for this study is basically secondary in nature which comprise of annual time series spanning from 1982-2023. The data will be extracted from the publication of the Central Bank of Nigeria Statistical Bulletin (2022) and World development index (2023). There was no special procedure for collection of the data as these figures were merely extracted from these sources.
Method of Data Analysis
The method of data analysis employed was based on the specific objectives of the study. This research work employed both descriptive and econometric techniques. The descriptive techniques used include tables and charts. But the main instrument of data analysis will be multiple regression. The data will be first tested for stationarity using the Augmented Dickey Fuller (ADF). Based on the results of the test, a cointegration procedure will be performed and Error Correction Model specified and estimated. The research also will employ Granger causality test to ascertain the direction of causality among the variables in the model.
Unit Root Test (Stationarity Test)
Unit root test was carried out to determine if the variables are stationary and if not, to determine their order of integration. Following the submission of Granger and Newbold, stationarity of the data is tested directly with a unit root test using Augmented Dickey-Fuller (ADF) and Philips Perron Test, the ADF and PP test corrects for high order serial correlation. The time series properties of all variables used in estimation are examined to obtain reliable result. This development arises from prevalence of substantial co-movement among the time series data
Co-integration Test
Objective I: Assess the impact of agricultural production/output on economic growth in Nigeria
To evaluate the long and short run impact of Agricultural sector output as well as other explanatory variables on the Nigerian Economy, ARDL bounds test was used to test for a long run relationship between the variables of the study, especially Agricultural sector and economic growth. This is based on the results from Unit root test, in which, ADF test was employed. This technique of estimation was employed in the study in order to obtain a well-rounded result through the employment of the correct method of analysis. Unit root test was carried out on each of the variables to ascertain the level of integration of the variables. On this ground, the results from the ADF indicated that the variables were stationary at both level and after first differencing, hence, they are I (0) and I (1) series.
Also, the Error Correction Model was estimated to examine whether or not the variables will adjust back to the long run equilibrium if there is a distortion from the equilibrium point and at what speed.
Granger Causality Test
In order to determine which variable in the model cause variable in the other, Granger causality test was used. The Granger Causality regression model for pairs is adapted from Etuk (2020) to estimate equations 1 to 6 in an attempt to determine the direction of causation between agricultural sector performance and other sectors of the economy. The data required include Agricultural sector output (ASO), Manufacturing sector output in Industrial sector (MSO), Trade output in Services sector (TRAD), Transportation output in Services sector (TRAN) which are logged to be in an estimable form.
logASOt = Ʃα1jlogMSOt + ɛt (1)
logMSOt = Ʃβ1jlogASOt + ɛt (2)
logASOt = Ʃα1j logTRAD t+ ɛt (3)
logTRAD t = Ʃβ1jlogASOt + ɛt (4)
logASOt = Ʃα1jlogTRANt+ ɛt (5)
logTRAN t = Ʃβ1jlogASOt + ɛt (6)
Equations 1 to 6 represent the Granger causality equation to evaluate the causal relationship between Nigeria’s Agricultural sector performance and the other sectors listed above.
In this section, line charts showing the distributions of the variables in their units, the results from descriptive statistics, unit root test using Augmented Dickey Fuller (ADF), ECM results, Granger causality tests and diagnostic tests are presented.
FIG. 4.1 Agriculture, Manufacturing, Trade and Transportation sector output
Source: Authors’ Computation 2024
Figure 4.1 shows the graphical trend of Agriculture, Manufacturing, Trade and Transportation sector output. It is evident in the figure that Agricultural sector output from the period of the study has experienced a gradual increase although there was a sharp decline in 2001 due to low agricultural productivity. On the other hand, there has been fluctuation in Manufacturing sector during the period of study, with rise and fall in the output. While Trade experienced a continuous rise till 2017 where its output drops. Conversely, Transportation has maintained an almost constant trend during the period of study. The trend of agricultural sector rises above that of other sectors which implies that agriculture produces a highest output.
FIG. 4.2 Inflation rate, Gross Fixed Capital Formation and Government Expenditure
Figure 4.2 shows the graphical trend of inflation rate, gross fixed capital formation and total government expenditure. Inflation has experienced a cyclical movement from 1983 to 2019. With its maximum point at 1995. Also, GFCF has seen a reducing trend over the period of study. In other words, the variable has constantly reduced from 1985 to 2013, where it registered its minimum point and later increased till 2023. Total Government Expenditure has also increased throughout the period of study at a steady rate.
Descriptive Statistics
Table 4.1: Summary statistics
Mean
13.30027
Table 4.1 presents the summary statistics of RGDP, ASO, INT, INF, GFCF and TGE. Based on the result, it is seen that the mean values were 13.5428, 12.8538, 17.4456, 19.0382, 34.2501 and 11.7871 respectively. While the standard deviation of the variables was 0.2390, 0.3193, 4.6614, 16.4763, 16.7079 and 1.0571 respectively. Given their means and standard deviation values above, it is evident that the mean value of all the variables for this study exceed their respective standard deviations. This implies that the variables are stable over the period of study (1982-2023). All the variables except Agricultural sector output and Total Government Expenditure are positively skewed towards normality as shown by the positive values of the skewness statistics of the variables. The Kurtosis statistic which depicts the flatness of the graph of a frequency distribution revealed that RGDP, ASO, INT, INF, GFCF, TGE are normally distributed. Given that their P-values are greater than the conventional 5% level of significance, the Jaque-Bera statistic shows that the variables are normally distributed.
Unit Root Test
Unit root test was conducted for the model in order to ascertain the nature of the variables, whether or not they are I(0), I(1) or I(2) series. This was done using Augmented Dickey Fuller test and is presented below:
Augmented Dickey Fuller (ADF) Test for Stationarity
Table 4.2: ADF Test Result
The unit root results are carried out using Augmented Dickey‑fuller (ADF) as shown in table 4.2 which revealed that all the variables considered are all stationary after the first difference except for inflation rate and gross fixed capital formation that was stationary at level. Since the above results is a mixed order of integration, we adopt the ARDL analytical technique, hence, we present the ARDL Bounds test to ascertain whether or not a long run relationship exists among the variables used in the model
ARDL Bounds test was used to ascertain the whether there exists a long run relationship between the variables in the model. This test is only best for variables that are integrated at mixed orders of I(0) and I(1). This test is presented below:
Table 4.3: ARDL Bounds Test
The result from the ARDL Bounds test shows that the value of the F-statistics (6.8272) is greater than the lower bound critical value and the upper bound critical value at both 5% and 10% levels of significance. This implies that there is a long run relationship between Agricultural sector output and economic growth in Nigeria as shown by the long-run connection that bounds all the independent variables with RGDP.
Dependent Variable: RGDP
Table 4.4: Long Run Coefficients
0.837402
(*) denotes significance at 5% level.
ARDL Short Run Test
To establish the short run connection and estimate the speed of adjustment to long run equilibrium, the study performed an error correction test which will also be used to define the short run coefficients for the RGDP model. The table below shows the results of the error correction test.
Dependent Variable (RGDP)
Table 4.5: ARDL Error Correction Regression Model
Schwarz Criterion = 3.102878, Hannan-Quin Criterion = 2.551693
The results above show the short run estimates of the model as depicted by its error correction form. From the table above, the R-squared is given as 0.81. This means that the model fits the data well and it also implies that the 81% variations in the dependent variable (LNRGDP) are explained by the various independent variables.
As a rule, a Durbin Watson stat value that is approximately 2 (between 1.6 and 2.4) depicts the absence of autocorrelation in a model. Given the value of the Durbin Watson statistic (2.28) which approximate 2, it can be concluded that the model is free from autocorrelation.
The Error Correction term is (-0.3044), this is line with theoretical expectation that demands that it should be negative and statistically significant. This shows that about 30.44% disequilibria in RGDP in the previous years were corrected for in the current year. It therefore, follows that the ECM could rightly correct any deviations from short-run to long-run equilibrium relationship between RGDP and the explanatory variables.
Granger Causality
Table 4.6: Results of Granger Causality Test
LNASO does not Granger Cause LNTRANS
The nature of association of the variables in the model is summarized in the table 4.6 above. Given the result, it is evident that there exists a uni-directional causal relationship between ASO and MSO in Nigeria during the period of study. This implies that during the period of study, MSO does not Granger causes ASO. Based on the result, there is no causal relationship between TRAD and ASO in Nigeria during the period of this study. This implies that the aforementioned variables do not granger cause each other. Similarly, there is no causal effect between ASO and TRANS over the period of study. By implication, both variables do not granger cause each other.
Table 4.7: Summary of Diagnostic test
Table 4.7 presents the summaries of the diagnostic tests for heteroscedasticity, serial correlation, normality and specification error for the model. From the table above, it appears that the error term in the model follows a normal distribution. This notion is based on the fact the probability value of the Jarque-Bera Statistic (0.8548) is greater than the conventional level of significance (5%). Also, with a F-statistic of 3.182839 and a probability value of 0.0812, the Breusch-Godfrey Serial Correlation LM Test indicates that the model is free from serial correlation. The Heteroskedasticity Test: Breusch-Pagan-Godfrey which is given by its F-Stat and probability value of 0.306197 and 0.9941 respectively, shows that the model is Homoscedastic and that the error terms have constant variance. Lastly, considering the F-statistic and probability value of the Ramsey RESET test which were 0.064933 and 0.8032 respectively, it follows that there is no specification error in the model. Overall, the model passes all the test as evidenced in the findings above.
Stability Test
The stability test was based on the Cumulative Sum of Square (CUSUM) and the Cumulative Sum of Square Residual (CUSUMQ) in order to ascertain the dependability of the estimate of the regression model. This is presented below:
Figure 4.3: Cumulative Sum of Square (CUSUM)
Figure 4.4: Cumulative Sum of Square Residual (CUSUMQ)
Figures 4.3 and 4.4 above shows the result of the stability test based on cumulative sum of recursive residual (CUSUM) and cumulative sum of squares of recursive residual (CUSUMQ). From fig.4.3, it is seen that the recursive errors fall between the critical line at 5% level of significance. This proves that the residual variance is stable. Similarly, in fig. 4.4, the recursive errors in the CUSUMQ test falls between the critical line at 5% level of significance. This denotes that the model is stable.
Hypothesis testing
H01: Agricultural production does not have a significant impact on economic growth in Nigeria
The finding of the study based on the Error Correction Model (ECM) shows that Agricultural Sector Output (ASO) had a positive and statistically significant relationship with Economic Growth in Nigeria, given its coefficient and probability value of 0.152707 and 0.0296 respectively. The correct sign of the ECM and its level of significance also confirms the existence of the short-run relationship.
The ARDL bounds test which shows that the F-statistic far exceeds the critical values at 5% confirms the fact that there exists a long run relationship between Agricultural Sector Output (ASO), hence, we conclude that there is a significant long and short run impact of Agricultural Sector Output on Economic Growth in Nigeria.
Following the study’s findings, we reject the null hypothesis (H01) and conclude that Agriculture Sector Output have significantly impacted Economic Growth in Nigeria.
The results from Granger causality test shows that agricultural sector performance have causal-effect on the growth of some sectors. From 1983 to 2023, Agricultural sector granger causes manufacturing sector while no causal relationship exists between agricultural sector, trade and transportation.
From the ECM results above in table 4.5, it was observed that the coefficient of Agricultural sector output (LNASO) was positive. This result conforms with the a-priori expectation which states that Agricultural sector output is positively related with economic growth. As such, a unit increase in Agricultural sector output will bring about a 0.152707 decrease in economic growth in Nigeria and vice versa. The probability value of LNASO (0.0296) is significant at 5%. It is on this basis that we conclude that Agricultural sector output has been a significant variable that has positively impacted on the Nigerian Economy over the period of study.
Also, the result shows that the relationship between interest rate and economic growth is positive as depicted by the positive value of the coefficient. Going by its coefficient, 1% increase in interest rate will bring about a 0.003873% increase in GRGDP in Nigeria. This is in contrast with the apriori expectation (the higher the interest rate, the lower the economic growth and vice versa). However, the justification for this positive relationship is based on the fact that high interest rates attract foreign investors who seek countries with high interest rate as it implies higher return on their investment; this foreign investment in turn contributes to economic growth.
Inflation rate was positive and follow the a-priori expectation as stated in the previous chapter of this work. Based on the result, 1% increase in INF will bring about a 0.000101% increase in Economic Growth in Nigeria as proxied by LNRGDP. It was seen to earmark an insignificant impact on LNRGDP, this is following its probability value which is more than the conventional 5% level of significance.
The negative relationship between Gross Fixed Capital Formation and economic growth as shown in the result does not conform to the apriori expectation. The result shows that a unit increase in gross fixed capital formation will bring about a 0.000947 decrease in economic growth in Nigeria and vice versa. This exception can be traced to insufficient investment (Amakom, 2012). The GFCF in Nigeria is not sufficient enough to drive significant Economic Growth as the investment level during the period of study have not been high enough to bring about a significant increase in capital stock, which would have transmitted to a significant increase in Economic Growth in Nigeria.
In the short run, total government expenditure has negative effect on economic growth as depicted by the negative value of its coefficient (-0.018877). As such, a unit increase in LNTGE will bring about a 0.029314 decrease in economic growth and vice versa. According to Effiong et al. (2020), the reasons for this could be the time lag for yields on government spending to be actualized. Also, the misappropriation of public funds meant for investment into unproductive purposes could, at least, in the short-run affect national output.
Lastly, the results from Granger causality test shows that there is a uni-directional relationship between Agricultural sector Output and Manufacturing sector in Nigeria as proxied by GRGDP. This implies that ASO can be used to predict changes in manufacturing sector in Nigeria. Conversely, no causal relationship exists between agricultural sector, trade and transportation. This could be due to less effective role agriculture plays in the overall economy and lack of productivity for the period under consideration.
Economic diversification has been a recurring concern in the history of the Nigerian economy. This is due to the fact that it has the capacity to identify and unleash the inherent potentials in the other sectors of the economy yet untapped, aside from the oil sector. Also, given the important role which food plays in the lives of humans; the importance of agriculture cannot be overemphasized. The current rate of high food prices, poverty among others in the country necessitates the need for diversification of its economic activities through the intensification of agricultural production (with more emphasis on crop and animal production).
From the empirical results, Agricultural sector output have a positive and statistically significant impact on economic growth. The outcome of this study indicates this sector has the potential of triggering economic growth in a higher scale with a trickle-down effect to other sectors of the Nigerian economy. However, the government through its diversification agenda, should invest more into the agricultural sector the benefit will be massive and the problem of food insecurity and poverty currently bedeviling the Nigerian economy will be mitigated. This requires a well-planned public – private investment partnership in agriculture supported by modern technology to achieve a sustainable increase in agricultural production.
Furthermore, agriculture-based productions in Nigeria are small-scale (operate at the subsistence level) and not sufficient to meet our domestic demand hence our farming systems need to evolve to accommodate the needs of our ever-increasing population, with the requisite level of innovation regarding inputs, harvesting, processing, distribution, and access to markets. These could be achieved through intensified research in the agricultural sector, increased funding through budgetary allocation, and well-structured provision of social infrastructure to support farming both in the rural and urban areas which will make agribusiness lucrative and attractive in the country.
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