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CHAPTER ONE: INTRODUCTION
1.1 Background of Study
Agriculture has been the backbone of the Nigerian economy since pre-colonial times, providing food, employment, raw materials for industries, and foreign exchange earnings (CBN, 2022). Before the discovery of crude oil in commercial quantities in the 1950s, agriculture contributed over 60% of Gross Domestic Product (GDP) and over 70% of export earnings, with major export crops including palm oil, palm kernels, cocoa, groundnuts, rubber, cotton, and hides and skins (FMARD, 2021). Nigeria was the world’s largest producer of palm oil and groundnuts, and a major exporter of cocoa and rubber (NBS, 2022). The agricultural sector was the mainstay of the economy, employing over 70% of the labour force and providing raw materials for nascent industries (Okonkwo, 2020).
The discovery and exploitation of crude oil in the 1970s led to a dramatic shift in the structure of the Nigerian economy (CBN, 2022). Oil revenues soared, and the agricultural sector was neglected. Agricultural output stagnated, food imports increased dramatically, and the country went from being a net exporter of food to a net importer (World Bank, 2021). By the 1980s, agriculture’s share of GDP had fallen below 30%, and its share of exports had fallen below 5% (NBS, 2022). The neglect of agriculture during the oil boom years led to declining productivity, rural-urban migration, food insecurity, and increased poverty (Adebayo and Ogunyemi, 2020).
Since the 1980s, successive governments have implemented policies to revive the agricultural sector (Okonkwo, 2020). The Structural Adjustment Programme (SAP) of 1986 aimed to promote agriculture through currency devaluation, removal of subsidies, and trade liberalization, but the impact was mixed (Eze and Nweze, 2019). The National Fadama Development Project (1993-2010) focused on irrigable lowlands. The Root and Tuber Expansion Programme (RTEP, 2001-2009) promoted cassava, yam, and sweet potato. The Presidential Initiatives (Cassava, Rice, etc., 2003-2007) targeted specific value chains. The Agricultural Transformation Agenda (ATA, 2011-2015) introduced e-wallet for input supply and promoted value chains. The Agricultural Promotion Policy (APP, 2016-2020) focused on agribusiness and private sector investment. The National Agricultural Technology and Innovation Plan (NATIP, 2021-2025) promotes technology adoption and climate resilience (FMARD, 2021).
The current status of agriculture in Nigeria is characterized by (CBN, 2022; NBS, 2022):
| Indicator | Value | Significance |
| Agricultural GDP share | ~25% | Significant direct contribution |
| Agricultural employment share | ~35% | Largest employer |
| Agricultural GDP growth rate | 2-4% (2020-2021) | Modest growth |
| Food import bill | ₦2-3 trillion annually | High import dependence |
| Agricultural exports | <5% of total exports | Low compared to oil |
| Fertilizer use | <20 kg/ha | Very low (global average 135 kg/ha) |
| Improved seed adoption | <30% | Low |
| Irrigation coverage | <5% of cultivated area | Very low |
| Post-harvest losses | 20-50% | High for perishable crops |
| Access to credit | <20% of smallholders | Very low |
| Farmer:extension agent ratio | >3,000:1 | Very low (recommended 400:1) |
The relationship between agriculture and economic growth is well-established in development economics (Schultz, 1964; Lewis, 1954; Timmer, 2019). The direct contribution channel: agricultural output directly contributes to GDP. Employment channel: agriculture employs a large share of the labour force; increased agricultural productivity releases labour for industry and services (structural transformation). Food security channel: increased agricultural output reduces food imports, saves foreign exchange, and reduces food prices (real income increase). Foreign exchange channel: agricultural exports earn foreign exchange, diversifying export earnings away from oil. Raw materials channel: agriculture supplies raw materials to agro-industries (food processing, beverages, textiles, soap and cosmetics). Poverty reduction channel: increased farm incomes stimulate rural economies (multiplier effect of 1.5-2.5). Fiscal channel: agricultural taxes and reduced food import subsidies free up government resources for investment.
The theoretical framework for this study is supported by three theories (Schultz, 1964; Lewis, 1954; Timmer, 2019):
| Theory | Proponent | Core Proposition |
| Agricultural Development Theory | Schultz (1964) | Investment in agriculture (credit, inputs, technology, extension, research, infrastructure) increases agricultural output, which drives economic growth |
| Lewis Dual Sector Model | Lewis (1954) | Agricultural surplus (output above subsistence) provides food, labour, and capital for industrial development; agricultural growth enables structural transformation |
| Structural Transformation Theory | Kuznets (1966); Timmer (2019) | Employment and output shift from agriculture to industry to services as economies develop; agricultural growth is the first stage of transformation |
Empirical studies on the impact of agriculture on economic growth in Nigeria have produced mixed findings (Adebayo and Ogunyemi, 2020; Eze and Nweze, 2019; Okafor and Nwosu, 2020). Some studies find a positive, significant relationship between agricultural output and GDP; others find weak or insignificant effects. Differences in time periods, variables (agricultural GDP vs. overall GDP vs. sectoral GDP), methods (OLS vs. cointegration vs. VAR vs. VECM), and data quality contribute to these mixed findings. Few studies use rigorous time-series methods (cointegration, error correction, Granger causality) to test long-run relationships and causality direction. The period 1981-2020 (40 years) provides sufficient data for robust time-series analysis.
In summary, agriculture is a critical sector for Nigeria’s economy, contributing 25% of GDP and employing 35% of the labour force. However, the sector underperforms due to low productivity, limited input use, poor infrastructure, weak extension, limited credit, and climate change. Empirical evidence on the impact of agriculture on economic growth is mixed and limited. This study aims to analyze the impact of agriculture on economic growth in Nigeria using time-series econometric methods (cointegration, error correction modelling, Granger causality) to determine the long-run relationship, short-run dynamics, and direction of causality between agricultural output and economic growth.
1.2 Statement of Problems
Despite the recognized importance of agriculture for food security, employment, and economic diversification in Nigeria, the agricultural sector has underperformed relative to its potential. Agricultural output growth has been modest (2-4% annually, below population growth of 2.6%), and productivity (yields per hectare) is 30-60% below achievable levels. Consequently, Nigeria is a net importer of food, spending over ₦2-3 trillion annually on food imports (rice, wheat, sugar, fish, dairy). The contribution of agriculture to total GDP has stagnated around 25%, well below the pre-oil era levels (>60%). The agricultural sector’s share of exports has fallen below 5%, compared to over 70% in the 1960s.
The specific problems addressed by this study include:
Low agricultural productivity: Yields per hectare for major crops (cassava, maize, yam, rice) are 30-60% below potential due to low input use (fertilizer <20 kg/ha vs. global average 135 kg/ha; improved seed adoption <30%), poor crop management, and weak extension services.
Limited value addition: Most agricultural output is sold raw (unprocessed), capturing only a fraction of potential value. Processing (milling, drying, packaging) could increase value by 100-500%.
High post-harvest losses: Estimated at 20-50% for perishable crops (tomatoes, vegetables, fruits) and 10-20% for grains, reducing marketable output and farm incomes.
Poor infrastructure: Inadequate roads increase transport costs and post-harvest losses; unreliable electricity limits processing and storage; lack of storage facilities (silos, warehouses) forces distress sales.
Limited access to credit: Less than 20% of smallholder farmers have access to formal credit, limiting input purchase and technology adoption.
Weak extension services: Farmer-to-extension agent ratio >3,000:1 (recommended 400:1), limiting technology adoption and knowledge transfer.
Climate change: Changing rainfall patterns, droughts, floods, and heat stress reduce output and increase variability.
Limited empirical evidence: There is limited empirical evidence quantifying the impact of agriculture on economic growth using rigorous time-series methods (cointegration, error correction, Granger causality). Most studies use OLS regression without testing for stationarity, risking spurious results.
Mixed findings: Existing studies have produced mixed findings (positive vs. insignificant; long-run vs. short-run only; unidirectional vs. bidirectional causality). There is no consensus on the magnitude of the impact or the direction of causality.
Limited period coverage: Many studies cover periods ending in 2018 or 2019. An updated study through 2020 (or later) is needed to capture recent trends (recession, COVID-19).
The problem this study addresses is the need to empirically analyze the impact of agriculture on economic growth in Nigeria using rigorous time-series econometric methods (cointegration, error correction modelling, Granger causality), to determine the long-run relationship, short-run dynamics, and direction of causality between agricultural output and economic growth.
1.3 Aim of the Study
The specific aim of this research work is to analyze the impact of agriculture on economic growth in Nigeria using time-series econometric methods (stationarity tests, cointegration analysis, error correction modelling, Granger causality tests) to determine the long-run equilibrium relationship, short-run dynamics, and direction of causality between agricultural output (agricultural GDP) and economic growth (real GDP).
1.4 Objectives of the Study
- To determine the time-series properties (stationarity) of agricultural output (agricultural GDP) and economic growth (real GDP) in Nigeria.
- To examine the long-run relationship (cointegration) between agricultural output and economic growth.
- To estimate the short-run dynamics (error correction mechanism) of the relationship between agricultural output and economic growth.
- To determine the direction of causality (Granger causality) between agricultural output and economic growth.
- To quantify the magnitude of the effect of changes in agricultural output on economic growth (elasticity).
1.5 Research Questions
- What are the time-series properties (stationarity) of agricultural output (agricultural GDP) and economic growth (real GDP) in Nigeria?
- Is there a long-run relationship (cointegration) between agricultural output and economic growth in Nigeria?
- What are the short-run dynamics (error correction mechanism) of the relationship between agricultural output and economic growth?
- What is the direction of causality (Granger causality) between agricultural output and economic growth?
- What is the magnitude of the effect of changes in agricultural output on economic growth (elasticity)?
1.6 Research Hypotheses
Hypothesis One
- H₀ (Null): Agricultural output has no significant impact on economic growth in Nigeria.
- H₁ (Alternative): Agricultural output has a significant impact on economic growth in Nigeria.
Hypothesis Two
- H₀ (Null): There is no long-run relationship (cointegration) between agricultural output and economic growth.
- H₁ (Alternative): There is a long-run relationship (cointegration) between agricultural output and economic growth.
Hypothesis Three
- H₀ (Null): There are no significant short-run dynamics (error correction) between agricultural output and economic growth.
- H₁ (Alternative): There are significant short-run dynamics between agricultural output and economic growth.
Hypothesis Four
- H₀ (Null): Agricultural output does not Granger-cause economic growth.
- H₁ (Alternative): Agricultural output Granger-causes economic growth.
Hypothesis Five
- H₀ (Null): Economic growth does not Granger-cause agricultural output.
- H₁ (Alternative): Economic growth Granger-causes agricultural output.
1.7 Justification of the Study
This study is justified on several grounds. First, despite the importance of agriculture for Nigeria’s economy, there is limited empirical evidence quantifying the impact of agriculture on economic growth using rigorous time-series methods. Second, understanding whether the relationship is long-run (cointegrated) or only short-run has different policy implications: cointegration suggests a stable equilibrium relationship that policies can target; absence suggests that shocks have permanent effects. Third, determining the direction of causality (Granger causality) is essential for policy: if agricultural output Granger-causes economic growth, then policies to increase agricultural output will increase growth; if growth Granger-causes agricultural output, then growth-enhancing policies will indirectly increase agricultural output. Fourth, quantifying the magnitude of effects (elasticity) will inform budget allocation to agriculture. Fifth, the findings will inform agricultural policy (FMARD, CBN, State Ministries of Agriculture) and development partners.
1.8 Significance of the Study
The findings of this research will be significant to several stakeholders. To the Federal Ministry of Agriculture and Rural Development (FMARD) , the study will provide evidence on the impact of agriculture on economic growth, informing agricultural policy, budget allocation, and programme design. To the Central Bank of Nigeria (CBN) , the findings will inform agricultural credit policy (credit to agriculture targets, interest rate subsidies, credit guarantee schemes). To the Ministry of Finance, Budget and National Planning, the findings will inform fiscal policy (government expenditure on agriculture, infrastructure). To the National Bureau of Statistics (NBS) , the findings will inform agricultural statistics and monitoring. To development partners (World Bank, IFAD, FAO, AfDB) , the findings will inform project design and investment priorities for agricultural development programmes. To academic researchers, the study will contribute empirical evidence on agriculture-growth linkages, testing and extending agricultural development theory, Lewis dual sector model, and structural transformation theory.
1.9 Scope of the Study
The scope of this study is delimited to the analysis of the impact of agriculture on economic growth in Nigeria. The study uses annual time-series data from 1981 to 2020 (40 observations). Variables include: agricultural output (agricultural GDP at constant prices, ₦ billion; agricultural GDP growth rate, %); economic growth (real GDP at constant prices, ₦ billion; real GDP growth rate, %). Control variables: oil GDP (₦ billion, constant prices) – to control for oil sector dominance; manufacturing GDP (₦ billion, constant prices) – to control for industrial sector; services GDP (₦ billion, constant prices) – to control for services sector; inflation rate (CPI, %); interest rate (lending rate, %); exchange rate (₦/USD); trade openness (imports + exports / GDP). The study employs time-series econometric methods: unit root tests (Augmented Dickey-Fuller ADF, Phillips-Perron PP, Kwiatkowski-Phillips-Schmidt-Shin KPSS), cointegration tests (Engle-Granger, Johansen), error correction model (ECM), and Granger causality tests within VECM/VAR framework. The study does not extend to micro-level analysis (household/farm level), sectoral decomposition within agriculture (crops vs. livestock vs. fisheries), or other sectors of the economy beyond the aggregate indicators listed.
1.10 Definition of Terms
Agricultural Output: The total value of agricultural production (crops, livestock, forestry, fisheries) measured as agricultural GDP at constant prices (₦ billion). Represents the quantity of goods produced by the agricultural sector, adjusted for inflation.
Economic Growth: The sustained increase in the real gross domestic product (GDP) of Nigeria over time, measured as the annual percentage change in real GDP (constant prices) or as real GDP in ₦ billion.
Real GDP: Gross domestic product adjusted for inflation, measured in constant prices (₦ billion). Real GDP is used to isolate the effect of price changes (inflation) from changes in actual output.
Agricultural GDP Growth Rate: The annual percentage change in real agricultural GDP. Measures the rate of expansion of agricultural production.
Cointegration: A statistical property of two or more non-stationary time series that move together over the long run such that a linear combination of them is stationary; cointegration indicates a long-run equilibrium relationship.
Error Correction Model (ECM): A time-series model that captures the short-run dynamics of how variables adjust to deviations from long-run equilibrium; the error correction term (ECT) measures the speed of adjustment.
Granger Causality: A statistical concept of predictive causality (not necessarily true causal mechanism) where one time series (X) is said to “Granger-cause” another (Y) if past values of X help predict current Y better than past values of Y alone, controlling for other variables.
Unit Root Test: A statistical test (Augmented Dickey-Fuller ADF, Phillips-Perron PP, Kwiatkowski-Phillips-Schmidt-Shin KPSS) to determine whether a time series is stationary (no unit root) or non-stationary (has a unit root).
Elasticity (Economic): The percentage change in economic growth (real GDP) resulting from a 1% change in agricultural output. Measures the magnitude of the impact.
Agricultural Development Theory: A theory (Schultz, 1964) arguing that investment in agriculture (credit, inputs, technology, extension, research, infrastructure) increases agricultural output, which transforms traditional agriculture into a productive, modern sector, generating economic growth.
Lewis Dual Sector Model: A theory (Lewis, 1954) explaining how agricultural surplus (output above subsistence) provides the resources (food, labour, capital) for industrial development; increased agricultural output (enabled by development) increases surplus, accelerating structural transformation.
Structural Transformation Theory: A theory (Kuznets, 1966; Timmer, 2019) describing the shift of employment and output from agriculture to industry to services as economies develop; increased agricultural output (productivity) releases labour and capital for industrial development, initiating structural transformation.
CHAPTER TWO: LITERATURE REVIEW
2.1 Conceptual Framework
The conceptual framework for this study is organized around the key concepts of agriculture, economic growth, the channels through which agriculture affects economic growth, and the measures of both variables. These concepts are defined, operationalized, and related to one another below.
2.1.1 Concept of Agriculture in Nigeria
Agriculture in Nigeria encompasses crop production, livestock, forestry, and fisheries, with crop production (cassava, yam, maize, rice, sorghum, millet, cocoa, oil palm, rubber) dominating the sector (FMARD, 2021).
Components of Agricultural GDP (2021):
| Component | Share of Agricultural GDP (%) | Major Products |
| Crop production | 80-85% | Cassava, yam, maize, rice, sorghum, millet, cocoa, oil palm, rubber |
| Livestock | 8-10% | Cattle, goats, sheep, poultry, pigs |
| Forestry | 3-5% | Timber, fuelwood, non-timber forest products |
| Fisheries | 3-5% | Freshwater fish (wild and aquaculture), marine fish |
(Source: NBS, 2022)
Measures of Agricultural Output:
| Measure | Definition | Unit |
| Agricultural GDP (nominal) | Value of agricultural output at current prices | ₦ billion |
| Agricultural GDP (real) | Value of agricultural output at constant prices | ₦ billion |
| Agricultural GDP growth rate | Annual percentage change in real agricultural GDP | % |
| Agricultural output index | Index of agricultural production (base year = 100) | Index |
| Crop yield (major crops) | Output per hectare for cassava, maize, yam, rice | tons/ha |
2.1.2 Concept of Economic Growth
Economic growth refers to the sustained increase in the real gross domestic product (GDP) of Nigeria over time, reflecting the expansion of the economy’s productive capacity (Mankiw, 2020).
Measures of Economic Growth:
| Measure | Definition | Unit |
| Real GDP | Total output at constant prices | ₦ billion |
| Real GDP growth rate | Annual percentage change in real GDP | % |
| GDP per capita | Real GDP divided by population | ₦/person |
| Sectoral GDP | GDP by sector (agriculture, industry, services) | ₦ billion |
Sectoral Composition of GDP (2021):
| Sector | Share of GDP (%) | Growth Rate (%) |
| Agriculture | 25% | 3.2% |
| Industry | 29% | -2.5% (oil sector decline) |
| Services | 46% | 5.5% |
(Source: NBS, 2022)
2.1.3 Channels Through Which Agriculture Affects Economic Growth
Agriculture affects economic growth through multiple interconnected channels (Schultz, 1964; Lewis, 1954; Timmer, 2019).
Channel 1: Direct Contribution to GDP
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased crop production | Higher agricultural GDP | Direct contribution to total GDP |
| Increased livestock production | Higher agricultural GDP | Direct contribution to total GDP |
| Increased fisheries production | Higher agricultural GDP | Direct contribution to total GDP |
| Increased forestry production | Higher agricultural GDP | Direct contribution to total GDP |
Channel 2: Employment Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased output requires more labour | Higher agricultural employment | Reduced unemployment |
| Increased productivity releases labour | Labour moves to industry/services | Structural transformation |
| Value addition (processing) | Agro-industry employment | Diversification |
Channel 3: Food Security and Inflation Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased food supply | Lower food prices | Reduced food inflation |
| Reduced food imports | Saved foreign exchange | Improved trade balance |
| Improved food availability | Reduced hunger, malnutrition | Human capital development |
Channel 4: Foreign Exchange Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased agricultural exports | Higher export earnings | Foreign exchange for imports |
| Export diversification (non-oil) | Reduced oil dependence | Stability, reduced volatility |
| Reduced food imports | Lower import bill | Improved current account |
Channel 5: Raw Materials for Agro-Industry Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased raw material supply | Agro-industry growth | Manufacturing GDP growth |
| Local processing | Value addition | Employment, higher GDP |
| Reduced import of raw materials | Saved foreign exchange | Trade balance improvement |
Channel 6: Poverty Reduction and Demand Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased farm incomes | Higher rural demand | Multiplier effect (1.5-2.5x) |
| Rural employment | Wage income | Demand for local goods/services |
| Asset accumulation | Investment in education, health | Human capital development |
Channel 7: Fiscal Channel
| Agricultural Output Increase | Effect | Impact on Economy |
| Increased agricultural profits | Tax revenue (if formalized) | Government spending on infrastructure, education, health |
| Reduced food import subsidies | Fiscal savings | Reallocation to productive sectors |
| Agricultural export taxes | Revenue (if any) | Development spending |
2.1.4 Conceptual Framework Diagram (Described in Text)
The conceptual framework can be visualized as follows:
Agriculture (Independent Variable) → Channels → Economic Growth (Dependent Variable)
Independent Variable (Agriculture):
- Agricultural GDP (₦ billion, constant prices)
- Agricultural GDP growth rate (%)
↓ Channels (Mediating Variables):
- Direct contribution (agricultural GDP → total GDP)
- Employment (agricultural employment, labour release)
- Food security (food supply, food prices, imports)
- Foreign exchange (agricultural exports earnings)
- Raw materials (supply to agro-industries)
- Poverty reduction (rural incomes, multiplier effect)
- Fiscal (tax revenue, reduced subsidies)
↓ Dependent Variable (Economic Growth):
- Real GDP (₦ billion, constant prices)
- Real GDP growth rate (%)
Control Variables:
- Oil GDP (₦ billion, constant prices)
- Manufacturing GDP (₦ billion, constant prices)
- Services GDP (₦ billion, constant prices)
- Exchange rate (₦/USD)
- Interest rate (lending rate, %)
The framework posits that agriculture (independent variable) affects economic growth (dependent variable) through seven channels: direct contribution to GDP, employment, food security, foreign exchange, raw materials, poverty reduction, and fiscal channels. The magnitude of the effect is moderated by control variables (oil GDP, manufacturing GDP, services GDP, exchange rate, interest rate).
2.2 Theoretical Framework
This study is anchored on three supporting theories that provide a comprehensive theoretical foundation for understanding the impact of agriculture on economic growth. These theories are Agricultural Development Theory, Lewis Dual Sector Model, and Structural Transformation Theory.
2.2.1 Agricultural Development Theory
Agricultural Development Theory, associated with Nobel laureate Theodore Schultz (1964), argues that investment in agriculture (credit, inputs, technology, extension, research, infrastructure) increases agricultural output, which transforms traditional agriculture into a productive, modern sector and generates economic growth (Schultz, 1964).
Core Propositions (Schultz, 1964):
- Traditional agriculture is poor but efficient: Farmers in traditional agriculture allocate resources efficiently given the constraints they face (limited technology, no credit, poor infrastructure). However, traditional agriculture is “poor” (low output, low income) because of limited investment.
- Low productivity is not due to farmer irrationality: Farmers are rational but constrained. They do not adopt improved practices because they lack credit to purchase inputs, lack information (extension), or face high risk.
- Investment in agriculture yields high returns: Investment in agricultural research (improved seeds), human capital (farmer education, extension), credit (inputs), and infrastructure (roads, irrigation) generates high economic returns.
- Increased agricultural output drives economic growth: Higher agricultural output directly increases GDP (direct contribution), reduces food prices (real income increase), provides raw materials for agro-industry, and generates foreign exchange (exports).
- Returns to agricultural research are high: Schultz estimated returns to agricultural research of 30-50% or more, far exceeding returns to many industrial investments.
Application to Nigeria
Agricultural Development Theory predicts (Schultz, 1964; Timmer, 2019):
- Investment in agricultural research (improved cassava, maize, rice, cowpea varieties), extension services, fertilizer subsidies, irrigation, and rural roads will increase agricultural output.
- Increased agricultural output will directly increase GDP (direct contribution), reduce food imports (saving foreign exchange), reduce food prices (real income increase), and increase rural incomes (demand multiplier).
- The returns to agricultural investment in Nigeria are likely high (30-50%), given low current productivity and large gaps between actual and potential yields.
2.2.2 Lewis Dual Sector Model
The Lewis Dual Sector Model, developed by Nobel laureate Arthur Lewis (1954), explains how agricultural surplus (output above subsistence) provides the resources (food, labour, capital) for industrial development (Lewis, 1954).
Core Propositions (Lewis, 1954):
- Dual economy: The economy is divided into a traditional agricultural sector (low productivity, subsistence wages, surplus labour) and a modern industrial sector (higher productivity, higher wages).
- Unlimited supply of labour: The agricultural sector has surplus labour (disguised unemployment) where marginal product of labour is zero or below subsistence wage. This surplus labour can be withdrawn for industrial employment without reducing agricultural output.
- Capital accumulation in industry: Industrial capitalists reinvest profits to expand production, creating more industrial jobs, drawing more labour from agriculture.
- Turning point: Once surplus labour is exhausted, agricultural wages rise, and both sectors share in productivity gains.
Role of Agricultural Output in the Lewis Model
Increased agricultural output (above subsistence) (Lewis, 1954; Timmer, 2019):
- Provides food surplus: Higher agricultural output means more food to feed the industrial workforce.
- Releases labour: As output per worker increases (productivity growth), less labour is needed to produce the same output, releasing workers for industry.
- Provides capital: Savings from agriculture (if farmers save) can be invested in industry.
- Provides foreign exchange: Agricultural exports earn currency to import industrial machinery.
Application to Nigeria
| Indicator | Current Status | Lewis Model Implication |
| Agricultural employment share | ~35% | Surplus labour still exists |
| Agricultural productivity | Low (hand hoe) | Low surplus for industry |
| Industrial employment share | ~10% | Low absorption of surplus labour |
| Agricultural output growth | 2-4% | Modest surplus growth |
| Food import bill | >₦2 trillion | Low domestic surplus |
2.2.3 Structural Transformation Theory
Structural Transformation Theory, associated with Kuznets (1966) and extended by Timmer (2019), describes the shift of employment and output from agriculture to industry to services as economies develop (Kuznets, 1966; Timmer, 2019).
Core Propositions (Kuznets, 1966; Timmer, 2019):
- Stages of structural transformation:
| Stage | Employment Share | Output Share | Agricultural Output Role |
| Early | Agriculture dominant | Agriculture dominant | Increased output feeds population |
| Middle | Agriculture declines; industry rises | Industry rises | Output growth releases labour |
| Late | Agriculture small; services dominant | Services dominant | High productivity, small labour share |
- Agricultural output growth is the first stage: Increased agricultural productivity and output are necessary to release labour and capital for industrial development. Without agricultural surplus, industrialization is impossible.
- Differential productivity: Labour productivity is higher in industry and services than in agriculture. As labour moves from agriculture to higher-productivity sectors, overall GDP per capita increases.
- Kuznets curve: Inequality initially increases during early structural transformation (as some benefit more than others), then decreases after a turning point.
Application to Nigeria
| Indicator | Nigeria | Middle-Income Country | Developed Country | Stage |
| Agricultural employment share | ~35% | ~20% | <5% | Still high |
| Agricultural GDP share | ~25% | ~10% | <2% | Still high |
| Industrial employment share | ~10% | ~25% | ~20% | Low |
| Services employment share | ~55% | ~55% | ~75% | Emerging |
Nigeria is in the middle stage of structural transformation: agriculture’s shares are declining but still high; services have grown rapidly (often premature deindustrialization). Increased agricultural output growth is needed to accelerate the transformation (Timmer, 2019).
Integration of the Three Theories
The three theories are complementary and collectively provide a robust theoretical framework for this study:
| Theory | Focus | Contribution to Study |
| Agricultural Development Theory | Investment in agriculture increases output and growth | Explains why increasing agricultural output (through investment) drives economic growth |
| Lewis Dual Sector Model | Agricultural surplus supports industrial development | Explains how agricultural output above subsistence provides food, labour, and capital for industry |
| Structural Transformation Theory | Shift of employment/output from agriculture to industry/services | Explains Nigeria’s current stage and the role of agricultural output growth in accelerating transformation |
Together, these theories support the study’s analysis of the impact of agriculture on economic growth, recognizing that: (1) increased agricultural output (through investment) directly contributes to GDP and drives economic growth (Agricultural Development); (2) agricultural surplus (output above subsistence) provides food, labour, and capital for industrial development (Lewis); and (3) agricultural output growth initiates structural transformation (shift of labour and output from agriculture to industry/services) (Structural Transformation).
2.3 Review of Related Empirical Studies
This section reviews empirical studies relevant to the impact of agriculture on economic growth in Nigeria and other countries.
2.3.1 Studies on Agriculture and Economic Growth (Nigeria)
Adebayo and Ogunyemi (2020) conducted a study on the impact of agricultural output on economic growth in Nigeria (1981-2018). Using a Vector Error Correction Model (VECM), they found that agricultural GDP had a positive and significant effect on real GDP in the long run (elasticity 0.35, p<0.05). A 1% increase in agricultural GDP increased total GDP by 0.35% in the long run. In the short run, the effect was positive but not significant. The study recommended increasing investment in agriculture.
Eze and Nweze (2019) studied the effect of agricultural output on economic growth in Enugu State (1990-2018). Using Ordinary Least Squares (OLS) regression, they found a positive and significant relationship (R² = 0.65, p<0.01). However, they did not test for stationarity or cointegration; OLS on non-stationary data may produce spurious results. The study recommended expanding agricultural credit.
Okafor and Nwosu (2020) studied the effect of agricultural output on economic growth in Edo State (1981-2019). Using Autoregressive Distributed Lag (ARDL) bounds testing, they found a long-run relationship (cointegration) between agricultural GDP and real GDP. The long-run elasticity was 0.30 (p<0.05). The study concluded that agricultural output significantly affects economic growth.
Okonkwo (2020) studied the effect of agricultural output on economic growth in Nigeria (1981-2018). Using a VECM, he found that agricultural GDP had a positive and significant effect on real GDP in the long run (elasticity 0.28, p<0.05). The study recommended increasing agricultural output through investment in inputs, technology, and infrastructure.
2.3.2 Studies on Agriculture and Economic Growth (Other Countries)
| Study | Country | Period | Key Findings |
| Gollin, Parente and Rogerson (2002) | Cross-country | – | Agricultural productivity differences explain large share of income differences |
| Tiffin and Irz (2006) | Cross-country | 1960-1990 | Agricultural growth Granger-causes economic growth |
| Awokuse (2011) | Cross-country | 1960-2000 | Agricultural growth causes overall growth (causality from agriculture to economy) |
| Thirtle, Lin and Piesse (2003) | Africa | 1960-1990 | Agricultural productivity growth reduces poverty |
| Diao, Hazell and Thurlow (2010) | Africa | 2000-2007 | Agricultural growth has higher poverty reduction impact than non-agricultural growth |
2.3.3 Studies Using Time-Series Econometric Methods
| Method | Application | Advantage | Disadvantage |
| Unit root tests (ADF, PP, KPSS) | Test for stationarity | Determines appropriate model | Low power with small samples |
| Cointegration (Engle-Granger, Johansen) | Test for long-run equilibrium | Avoids spurious regression | Requires non-stationary variables |
| Error Correction Model (ECM) | Short-run dynamics | Captures adjustment to equilibrium | Requires cointegration |
| Granger causality (VAR/VECM) | Direction of causality | Informs policy | Correlational, not true causality |
| ARDL bounds testing | Cointegration with mixed order I(0)/I(1) | Allows both I(0) and I(1) variables | Sensitive to lag selection |
2.3.4 Summary of Empirical Findings
The empirical literature reveals consistent findings: (1) agricultural output has a positive impact on economic growth in Nigeria (elasticities 0.28-0.35); (2) the effect is stronger in the long run than the short run; (3) agricultural growth Granger-causes economic growth (causality from agriculture to the economy); (4) agricultural growth has higher poverty reduction impact than non-agricultural growth in Africa; (5) Nigeria-specific studies find elasticities of 0.3-0.4; (6) constraints include low agricultural credit (<20% of smallholders), low government expenditure (<2% of budget), low fertilizer use (<20 kg/ha), poor infrastructure. This study addresses gaps by using updated data (1981-2020) and rigorous time-series methods.
2.4 Summary of Literature Review
The table below summarizes key theoretical and empirical literature relevant to the impact of agriculture on economic growth.
| Author(s) and Year | Focus of Study | Strength | Weakness | Limitation | Gap Identified |
| Schultz (1964) | Agricultural Development Theory | Investment in agriculture increases output and growth | Pre-microfinance era | General theory | Application to Nigeria needed |
| Lewis (1954) | Lewis Dual Sector Model | Agricultural surplus supports industrial development | Assumes unlimited labour absorption | General theory | Application to Nigeria needed |
| Kuznets (1966); Timmer (2019) | Structural Transformation Theory | Shift of employment/output from agriculture | Descriptive (stages), not prescriptive | General theory | Application to Nigeria needed |
| Adebayo and Ogunyemi (2020) | Agriculture and growth (Nigeria 1981-2018) | VECM; elasticity 0.35 | Period includes post-2007 structural breaks | Period gap | Updated study needed |
| Eze and Nweze (2019) | Agriculture and growth (Enugu) | Positive relationship | OLS (no stationarity test) | Methodological gap | Cointegration test needed |
| Okafor and Nwosu (2020) | Agriculture and growth (Edo) | ARDL; elasticity 0.30 | Single state | Geographic gap | National-level needed |
| Okonkwo (2020) | Agriculture and growth (Nigeria 1981-2018) | VECM; elasticity 0.28 | Period includes post-2007 breaks | Period gap | Updated study needed |
| Gollin, Parente and Rogerson (2002) | Cross-country agricultural productivity | Agricultural productivity explains income differences | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| Tiffin and Irz (2006) | Cross-country Granger causality | Agricultural growth Granger-causes growth | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| Awokuse (2011) | Cross-country causality | Agricultural growth causes overall growth | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| Thirtle, Lin and Piesse (2003) | Africa agricultural productivity | Productivity growth reduces poverty | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| Diao, Hazell and Thurlow (2010) | Africa agricultural growth | Higher poverty reduction impact | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| CBN (2022) | Statistical bulletin | Official data | Not research; descriptive | No analysis | Analytical study needed |
| NBS (2022) | GDP report | Official data | Not research; descriptive | No analysis | Analytical study needed |
| FMARD (2021) | Agricultural sector report | Official data | Not research; descriptive | No analysis | Analytical study needed |
| World Bank (2021) | Nigeria agricultural review | Overview | Not primary research; descriptive | No primary data | Primary research needed |
| Mankiw (2020) | Macroeconomics (textbook) | Comprehensive theory | Not empirical | Not Nigeria-specific | Nigeria empirical needed |
