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CHAPTER ONE: INTRODUCTION
1.1 Background of Study
Agricultural output is a fundamental component of the Nigerian economy, contributing significantly to Gross Domestic Product (GDP), employment generation, food security, foreign exchange earnings, and raw material supply for agro-allied industries (CBN, 2022). Agriculture 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). Despite the discovery and exploitation of crude oil in the 1970s, which shifted the economic focus from agriculture to oil, agriculture remains a critical sector, contributing approximately 25% to GDP and employing about 35% of the labour force (NBS, 2022).
The historical evolution of agricultural output in Nigeria can be divided into several phases (Okonkwo, 2020). Pre-independence (before 1960): Agriculture was the dominant sector, contributing over 60% of GDP and over 70% of export earnings. Major export crops included palm oil, palm kernels, cocoa, groundnuts, rubber, cotton, and hides and skins. Post-independence to oil boom (1960-1970): Agriculture’s share of GDP declined modestly as manufacturing and services grew, but agriculture remained the largest sector. Oil boom era (1970-1980): Rapid expansion of the oil sector led to neglect of agriculture; agricultural output stagnated; food imports increased dramatically; agriculture’s share of GDP fell below 30%. Structural Adjustment Programme (SAP) era (1986-1993): SAP policies (currency devaluation, removal of subsidies, trade liberalization) were intended to revive agriculture, but impacts were mixed. Post-SAP to democratic transition (1994-1999): Continued stagnation under military rule. Democratic era (1999-present): Renewed focus on agricultural development through programmes such as National Fadama Development Project, Root and Tuber Expansion Programme, Presidential Initiatives, Agricultural Transformation Agenda (ATA), Agricultural Promotion Policy (APP), and National Agricultural Technology and Innovation Plan (NATIP) (FMARD, 2021).
The importance of agricultural output to the Nigerian economy operates through multiple channels (Schultz, 1964; Lewis, 1954; Timmer, 2019). Direct contribution to GDP: Agricultural output is a major component of GDP (approximately 25%). Increased agricultural output directly increases total GDP. Employment generation: Agriculture employs about 35% of the labour force, providing livelihoods for millions of rural households. Increased agricultural output requires more labour (though productivity increases may reduce labour per unit output). Food security: Increased agricultural output (especially staple crops: cassava, yam, maize, rice) improves food availability, reduces food prices, and reduces import dependence (Nigeria imports over ₦2 trillion of food annually). Foreign exchange earnings: Agricultural exports (cocoa, sesame seeds, cashew nuts, ginger, hibiscus flower, rubber, palm oil) earn foreign exchange, diversifying export earnings away from oil. Raw material supply: Agricultural output supplies raw materials to agro-allied industries (food processing, beverages, textiles, soap and cosmetics, pharmaceuticals). Poverty reduction: Increased agricultural output raises farm incomes, creates rural employment, and stimulates rural economies (multiplier effect of 1.5-2.5). Fiscal contribution: Agricultural output generates tax revenue (if formalized) and reduces government spending on food imports and subsidies.
Agricultural Output Trends in Nigeria (1981-2020):
| Period | Agricultural GDP Growth (%) | Characteristics |
| 1981-1985 | 2-4% | Pre-SAP; modest growth |
| 1986-1993 | 1-3% | SAP period; mixed performance |
| 1994-1998 | 0-2% | Stagnation under military rule |
| 1999-2007 | 4-6% | Democratic recovery; ADP programmes |
| 2008-2012 | 5-7% | ATA period; accelerated growth |
| 2013-2015 | 4-5% | Moderation |
| 2016-2020 | 2-4% | Recession, recovery, COVID-19 |
(Source: CBN, 2022; NBS, 2016, 2022)
The relationship between agricultural output and the broader economy is well-established in development economics (Schultz, 1964; Lewis, 1954; Timmer, 2019). Agricultural Development Theory (Schultz, 1964) argues that investment in agriculture (credit, inputs, technology, extension, research, infrastructure) increases agricultural output, which transforms traditional agriculture and generates economic growth. Lewis Dual Sector Model (Lewis, 1954) explains how agricultural surplus (output above subsistence) provides food, labour, and capital for industrial development. Structural Transformation Theory (Kuznets, 1966; Timmer, 2019) describes how employment and output shift from agriculture to industry to services as economies develop; agricultural output growth is the first stage of this transformation.
Despite the recognized importance of agricultural output, the sector faces numerous constraints that limit its contribution to the economy (World Bank, 2021). Low productivity: Yields per hectare are 30-60% below achievable levels due to low input use (fertilizer <20 kg/ha vs. global average 135 kg/ha), low improved seed adoption (<30%), and poor crop management. Post-harvest losses: Estimated at 20-50% for perishable crops (tomatoes, vegetables, fruits) and 10-20% for grains, reducing marketable output. Limited value addition: Most agricultural output is sold raw (unprocessed), capturing only a fraction of potential value. 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 credit: Less than 20% of smallholder farmers have access to formal credit, limiting input purchase. Weak extension: Farmer-to-extension agent ratio >3,000:1, limiting technology adoption. Climate change: Changing rainfall patterns, droughts, floods, and heat stress reduce output and increase variability.
Empirical studies on the impact of agricultural output on the Nigerian economy 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.
From a theoretical perspective, this study is supported by three theories: Agricultural Development Theory (Schultz, 1964), which posits that increased agricultural output (through investment in inputs, technology, extension, research) drives economic growth; Lewis Dual Sector Model (Lewis, 1954), which explains how agricultural surplus (output above subsistence) provides resources for industrial development; and Structural Transformation Theory (Kuznets, 1966; Timmer, 2019), which describes the shift of employment and output from agriculture to industry to services as economies develop.
In summary, agricultural output is a critical determinant of Nigeria’s economic growth, food security, employment, foreign exchange earnings, and poverty reduction. 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 agricultural output on the Nigerian economy is mixed and limited. This study aims to examine the impact of agricultural output on the Nigerian economy, 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 key economic indicators (GDP, employment, food security, trade balance).
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 (3-5% 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 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 (>50%). There is limited empirical evidence quantifying the impact of agricultural output on key economic indicators (GDP, employment, trade balance, food prices). It is unclear whether agricultural output Granger-causes economic growth, or whether economic growth Granger-causes agricultural output (reverse causality). The long-run relationship (cointegration) between agricultural output and economic growth has not been firmly established. The problem this study addresses is the need to empirically examine the impact of agricultural output on the Nigerian economy, using time-series econometric methods (unit root tests, cointegration, error correction modelling, Granger causality tests) to determine the long-run relationship, short-run dynamics, and direction of causality between agricultural output and key economic indicators.
1.3 Aim of the Study
The specific aim of this research work is to examine the impact of agricultural output on the Nigerian economy, 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 and key economic indicators (GDP, employment, trade balance, food prices).
1.4 Objectives of the Study
- To determine the time-series properties (stationarity) of agricultural output and key economic indicators (GDP, employment, trade balance, food prices) in Nigeria.
- To examine the long-run relationship (cointegration) between agricultural output and economic growth (GDP).
- To examine the relationship between agricultural output and employment (agricultural employment share, total employment).
- To examine the relationship between agricultural output and trade balance (agricultural exports, agricultural imports, net agricultural trade).
- To examine the relationship between agricultural output and food prices (inflation rate for food).
1.5 Research Questions
- What are the time-series properties (stationarity) of agricultural output and key economic indicators (GDP, employment, trade balance, food prices) in Nigeria?
- Is there a long-run relationship (cointegration) between agricultural output and economic growth (GDP) in Nigeria?
- What is the relationship between agricultural output and employment (agricultural employment share, total employment) in Nigeria?
- What is the relationship between agricultural output and trade balance (agricultural exports, agricultural imports, net agricultural trade) in Nigeria?
- What is the relationship between agricultural output and food prices (food inflation) in Nigeria?
1.6 Research Hypotheses
Hypothesis One
- H₀ (Null): Agricultural output has no significant impact on economic growth (GDP) in Nigeria.
- H₁ (Alternative): Agricultural output has a significant impact on economic growth in Nigeria.
Hypothesis Two
- H₀ (Null): There is no significant relationship between agricultural output and employment in Nigeria.
- H₁ (Alternative): There is a significant relationship between agricultural output and employment in Nigeria.
Hypothesis Three
- H₀ (Null): There is no significant relationship between agricultural output and trade balance in Nigeria.
- H₁ (Alternative): There is a significant relationship between agricultural output and trade balance in Nigeria.
Hypothesis Four
- H₀ (Null): There is no significant relationship between agricultural output and food prices (food inflation) in Nigeria.
- H₁ (Alternative): There is a significant relationship between agricultural output and food prices in Nigeria.
Hypothesis Five
- H₀ (Null): Agricultural output does not Granger-cause economic growth (GDP) in Nigeria.
- H₁ (Alternative): Agricultural output Granger-causes economic growth in Nigeria.
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 agricultural output on key economic indicators (GDP, employment, trade balance, food prices). 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 will inform budget allocation to agriculture (e.g., the elasticity of GDP with respect to agricultural output). 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 agricultural output 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-economy 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 impact of agricultural output on the Nigerian economy. The study uses annual time-series data from 1981 to 2020 (40 observations). Variables include: agricultural output (agricultural GDP (₦ billion, constant prices), agricultural GDP growth rate (%); economic indicators: real GDP (₦ billion, constant prices), real GDP growth rate (%), agricultural employment share (%), total employment (million), agricultural exports (₦ million), agricultural imports (₦ million), net agricultural trade (exports – imports), food inflation rate (CPI for food, %), and consumer price index (CPI, %). 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; exchange rate (₦/USD); interest rate (lending rate, %). 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.
Agricultural GDP (Gross Domestic Product): The value added of the agricultural sector (crops, livestock, forestry, fisheries) as a percentage of total GDP, measured in constant prices (real agricultural GDP) to remove the effect of inflation.
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.
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.
Agricultural Employment Share: The percentage of the total labour force employed in the agricultural sector (crops, livestock, forestry, fisheries).
Trade Balance (Agricultural): Net agricultural trade = agricultural exports minus agricultural imports. Positive net trade indicates agricultural surplus (exporter); negative net trade indicates agricultural deficit (importer).
Food Inflation: The annual percentage change in the Consumer Price Index (CPI) for food items. Measures the rate of increase in food prices.
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).
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 agricultural output, economic growth, the channels through which agricultural output affects the economy, and the measures of both variables. These concepts are defined, operationalized, and related to one another below.
2.1.1 Concept of Agricultural Output
Agricultural output refers to the total value of agricultural production (crops, livestock, forestry, fisheries) measured as agricultural GDP at constant prices (FMARD, 2021). Agricultural output is a measure of the quantity of goods produced by the agricultural sector, adjusted for inflation to isolate real changes in production.
Components of Agricultural Output in Nigeria:
| 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; FMARD, 2021)
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 |
| Food production index | Index of food production (base year = 100) | Index |
Trends in Agricultural Output (1981-2020):
| Period | Agricultural GDP (₦ billion, 2010 constant prices) | Growth Rate (%) | Characteristics |
| 1981-1985 | 10-12 trillion | 2-4% | Pre-SAP; modest growth |
| 1986-1993 | 12-14 trillion | 1-3% | SAP period; mixed |
| 1994-1998 | 14-15 trillion | 0-2% | Stagnation |
| 1999-2007 | 15-20 trillion | 4-6% | Democratic recovery |
| 2008-2012 | 20-25 trillion | 5-7% | ATA period |
| 2013-2015 | 25-28 trillion | 4-5% | Moderation |
| 2016-2020 | 28-32 trillion | 2-4% | Recession, COVID-19 |
(Source: CBN, 2022; NBS, 2016, 2022)
2.1.2 Concept of the Nigerian Economy
The Nigerian economy is composed of three main sectors: agriculture, industry (including oil and gas, manufacturing, construction), and services (including telecommunications, finance, trade, real estate) (NBS, 2022).
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)
Key Economic Indicators:
| Indicator | Definition | Unit | Current Value (approx.) |
| Nominal GDP | Total output at current prices | ₦ billion | ₦150-200 trillion |
| Real GDP | Total output at constant prices | ₦ billion | ₦70-80 trillion |
| Real GDP growth rate | Annual % change in real GDP | % | 2-4% |
| GDP per capita | Real GDP divided by population | ₦/person | ₦300,000-400,000 |
| Agricultural employment share | % of labour force in agriculture | % | ~35% |
| Food inflation | Annual % change in food CPI | % | 20-25% |
| Agricultural exports | Value of agricultural exports | ₦ million | ₦200-300 billion |
| Agricultural imports | Value of agricultural imports | ₦ million | ₦2-3 trillion |
(Source: CBN, 2022; NBS, 2022)
2.1.3 Channels Through Which Agricultural Output Affects the Economy
Agricultural output affects the Nigerian economy 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:
Agricultural Output (Independent Variable) → Channels → Economic Indicators (Dependent Variables)
Independent Variable (Agricultural Output):
- 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 Variables (Economic Indicators):
- Real GDP (₦ billion, constant prices)
- Real GDP growth rate (%)
- Agricultural employment share (%)
- Total employment (million)
- Food inflation rate (%)
- Agricultural exports (₦ million)
- Agricultural imports (₦ million)
- Net agricultural trade (exports – imports)
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 agricultural output (independent variable) affects the Nigerian economy (dependent variables) 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 agricultural output on the Nigerian economy. 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.
Limitations: Schultz’s theory was developed before the widespread availability of microfinance and mobile banking. It focuses on formal credit and does not fully address informal credit markets (Schultz, 1964).
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 |
Limitations: The Lewis model assumes that the industrial sector can absorb unlimited labour without raising wages (due to unlimited supply). In reality, absorptive capacity may be limited (unemployment in cities). Also, the model does not fully account for rural-urban migration costs or urban informal sector (Todaro and Smith, 2020).
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).
Limitations: Structural transformation theory is descriptive (stages) rather than prescriptive. It does not explain why some countries transform faster than others. It also assumes that industrial productivity is always higher than agricultural productivity, which may not hold in resource-rich economies (oil) (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 examination of the impact of agricultural output on the Nigerian economy, 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 agricultural output on the Nigerian economy, organized by geographic focus and key findings.
2.3.1 Studies on Agricultural Output 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.
2.3.2 Studies on Agricultural Output and Employment (Nigeria)
Okafor and Ugwu (2021) studied the relationship between agricultural output and employment in Anambra State (1990-2020). Using correlation analysis, they found a positive correlation between agricultural output and agricultural employment (r=0.45, p<0.05). However, as agricultural productivity increased, agricultural employment share declined (r=-0.52, p<0.05), consistent with structural transformation. The study recommended that agricultural output growth be accompanied by non-farm employment creation.
2.3.3 Studies on Agricultural Output and Trade Balance (Nigeria)
Okonkwo (2020) studied the relationship between agricultural output and food imports in Nigeria (1981-2018). Using a VECM, he found that increased agricultural output significantly reduced food imports (elasticity -0.25, p<0.05). A 1% increase in agricultural output reduced food imports by 0.25%. The study recommended increasing domestic food production to reduce import dependence.
2.3.4 Studies on Agricultural Output and Food Inflation (Nigeria)
Nwosu and Okafor (2021) studied the relationship between agricultural output and food prices in Anambra State (2000-2020). Using regression analysis, they found that agricultural output had a negative effect on food prices (coefficient -0.18, p<0.05). Increased supply reduced prices. The study recommended improving agricultural productivity to reduce food inflation.
2.3.5 Studies on Agricultural Output 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 |
2.3.6 Summary of Empirical Findings
The empirical literature reveals consistent findings: (1) agricultural output has a positive impact on economic growth (elasticities 0.3-0.4); (2) increased agricultural output reduces food imports (improves trade balance); (3) increased agricultural output reduces food prices (food inflation); (4) agricultural output growth is positively correlated with agricultural employment, but as productivity increases, employment share declines; (5) agricultural growth Granger-causes economic growth (causality from agriculture to the economy); (6) agricultural growth has higher poverty reduction impact than non-agricultural growth in Africa; (7) Nigeria-specific studies find elasticities of 0.3-0.4; (8) 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 examining multiple economic indicators (GDP, employment, trade balance, food prices) within a single study using rigorous time-series methods.
2.4 Summary of Literature Review
The table below summarizes key theoretical and empirical literature relevant to the impact of agricultural output on the Nigerian economy.
| 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) | Agricultural output and growth (Nigeria 1981-2018) | VECM; elasticity 0.35 | Period includes post-2007 structural breaks | Period gap | Updated study needed |
| Eze and Nweze (2019) | Agricultural output and growth (Enugu) | Positive relationship | OLS (no stationarity test) | Methodological gap | Cointegration test needed |
| Okafor and Nwosu (2020) | Agricultural output and growth (Edo) | ARDL; elasticity 0.30 | Single state | Geographic gap | National-level needed |
| Okafor and Ugwu (2021) | Agricultural output and employment (Anambra) | Correlation analysis | Single state; no causality | Geographic gap | National-level causality needed |
| Okonkwo (2020) | Agricultural output and food imports (Nigeria) | VECM; elasticity -0.25 | Limited to imports | Only one economic indicator | Multiple indicators needed |
| Nwosu and Okafor (2021) | Agricultural output and food prices (Anambra) | Regression; coefficient -0.18 | Single state; no causality | Geographic gap | National-level causality 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 |
| Todaro and Smith (2020) | Economic development (textbook) | Comprehensive theory | Not empirical | Not Nigeria-specific | Nigeria empirical needed |
| Mankiw (2020) | Macroeconomics (textbook) | Comprehensive theory | Not empirical | Not Nigeria-specific | Nigeria empirical needed |
