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CHAPTER ONE: INTRODUCTION
1.1 Background of Study
Government expenditure refers to the total spending by the government on goods, services, and investments, including recurrent expenditure (salaries, administrative costs, subsidies) and capital expenditure (infrastructure, equipment, research, development) (Mankiw, 2020). In the agricultural sector, government expenditure includes spending on agricultural research and development (RandD), extension services, input subsidies (fertilizer, improved seeds, pesticides), irrigation infrastructure, rural roads, storage facilities (silos, warehouses), processing equipment, credit programmes (ACGS, ABP, CACS), and market infrastructure (Abiodun and Adebayo, 2020). Government expenditure is a critical tool for promoting agricultural development, especially in developing countries where private investment is limited and market failures are common (Schultz, 1964; Timmer, 2019).
The importance of government expenditure on agriculture cannot be overstated (World Bank, 2021). Government expenditure can: increase agricultural productivity (through research, extension, inputs); improve rural infrastructure (roads, irrigation, storage, electricity); reduce post-harvest losses (storage, processing, roads); increase access to credit (credit guarantee schemes, subsidized interest rates); stabilize prices (buffer stocks, price support); promote technology adoption (improved seeds, fertilizers, equipment); and reduce poverty (increased farm incomes, rural employment) (FAO, 2020). In Nigeria, government expenditure on agriculture has been a key component of agricultural development policy since independence (FMARD, 2021).
The history of government expenditure on agriculture in Nigeria can be divided into several phases (Okonkwo, 2020; CBN, 2022):
| Phase | Period | Characteristics | Agricultural Share of Budget (%) |
| Pre-independence | Before 1960 | Colonial policies; export crop promotion | 5-10% |
| Post-independence | 1960-1970 | Agriculture dominant; research, extension, subsidies | 10-15% |
| Oil boom | 1970-1980 | Neglect of agriculture; oil dominates | 5-8% |
| SAP era | 1986-1993 | Structural Adjustment Programme; reduced subsidies | 3-6% |
| Democratic era | 1999-present | Renewed focus; FADAMA, ATA, APP, NATIP | 1-5% (far below Maputo Declaration 10%) |
(Source: CBN, 2022; FMARD, 2021)
Maputo Declaration and Malabo Commitments:
| Commitment | Year | Target | Nigeria’s Performance |
| Maputo Declaration | 2003 | 10% of national budget to agriculture | <2% (consistently below 10%) |
| Malabo Declaration | 2014 | 10% of national budget to agriculture; 6% agricultural growth | <2%; agricultural growth 2-4% |
(Source: AU, 2014; FMARD, 2021)
Government Expenditure on Agriculture in Nigeria (2000-2020):
| Year | Total Federal Budget (₦ billion) | Agricultural Expenditure (₦ billion) | Share of Budget (%) | Agricultural GDP Growth (%) |
| 2000 | 700 | 35 | 5.0% | 3.5% |
| 2005 | 1,800 | 54 | 3.0% | 5.0% |
| 2010 | 4,600 | 92 | 2.0% | 6.0% |
| 2015 | 6,100 | 122 | 2.0% | 4.0% |
| 2020 | 10,800 | 108 | 1.0% | 2.5% |
(Source: CBN, 2022; Budget Office, 2021)
The channels through which government expenditure affects the agricultural sector include (Schultz, 1964; Lewis, 1954; Timmer, 2019):
| Channel | Mechanism | Impact on Agriculture |
| Agricultural research (RandD) | Develops improved seeds, crop varieties, livestock breeds, farming practices | Higher yields, disease resistance, climate adaptation |
| Extension services | Trains farmers on improved practices | Adoption of improved technologies → higher yields |
| Input subsidies | Reduces cost of fertilizers, improved seeds, pesticides | Higher input use → higher yields |
| Irrigation infrastructure | Provides water for dry season cultivation | Year-round production, higher yields |
| Rural roads | Reduces transport costs, post-harvest losses | Higher farm-gate prices, reduced losses |
| Storage facilities (silos, warehouses) | Reduces post-harvest losses, allows storage for better prices | Higher farm incomes |
| Credit programmes (ACGS, ABP, CACS) | Provides loans to farmers | Purchase of inputs, equipment → higher yields |
| Processing equipment | Value addition (milling, drying, packaging) | Higher prices (100-500% increase) |
| Market infrastructure | Provides markets, scales, shelters | Higher farm-gate prices |
The theoretical relationship between government expenditure and agricultural development is well-established (Schultz, 1964; Lewis, 1954; Timmer, 2019). Agricultural Development Theory (Schultz, 1964) argues that investment in agriculture (research, extension, credit, infrastructure) increases agricultural productivity, transforming traditional agriculture into a productive, modern sector. Lewis Dual Sector Model (Lewis, 1954) explains how agricultural surplus (output above subsistence) provides resources for industrial development; government expenditure can increase agricultural surplus. Public Finance Theory (Musgrave, 1959; Rosen and Gayer, 2020) explains the role of government in providing public goods (research, extension, infrastructure) that private markets underprovide.
Empirical studies on the impact of government expenditure on agriculture 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 government agricultural expenditure and agricultural output; others find weak or insignificant effects. Differences in time periods, variables (capital vs. recurrent expenditure), 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.
The challenges facing government expenditure on agriculture in Nigeria include (Okonkwo, 2020; World Bank, 2021):
| Challenge | Description | Impact |
| Low budget allocation | <2% of federal budget (far below Maputo 10% target) | Inadequate funding for research, extension, infrastructure |
| Late release of funds | Funds released late in fiscal year | Projects delayed, missed planting seasons |
| Poor implementation | Bureaucracy, corruption, elite capture | Funds diverted, projects not completed |
| Capital vs. recurrent imbalance | High recurrent expenditure (salaries) vs. low capital expenditure | Limited investment in research, infrastructure |
| Poor maintenance | Infrastructure (roads, irrigation) not maintained | Deterioration, reduced effectiveness |
| Weak monitoring and evaluation | No systematic evaluation of programme impact | Ineffective programmes continue |
| Political interference | Funds allocated based on politics, not needs | Inefficient allocation |
From a theoretical perspective, this study is supported by three theories: Agricultural Development Theory (Schultz, 1964), which argues that investment in agriculture (research, extension, credit, infrastructure) increases agricultural productivity; Lewis Dual Sector Model (Lewis, 1954), which explains how agricultural surplus provides resources for industrial development; and Public Finance Theory (Musgrave, 1959; Rosen and Gayer, 2020), which explains the role of government in providing public goods (research, extension, infrastructure) that private markets underprovide.
In summary, government expenditure on agriculture is a critical tool for promoting agricultural development, but Nigeria’s agricultural budget allocation (1-2% of federal budget) is far below the Maputo Declaration target (10%). Government expenditure includes research, extension, input subsidies, irrigation, rural roads, storage, credit programmes, processing equipment, and market infrastructure. Empirical evidence on the impact of government expenditure on agricultural output is mixed. This study aims to examine the impact of government expenditure on the agricultural sector 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 government agricultural expenditure and agricultural output.
1.2 Statement of Problems
Despite the recognized importance of government expenditure for agricultural development, Nigeria’s agricultural budget allocation (1-2% of federal budget) is far below the Maputo Declaration target (10%). Consequently, the agricultural sector underperforms relative to its potential. The specific problems addressed by this study include:
Low budget allocation: Agricultural expenditure as a percentage of federal budget is consistently below 2%, far below the Maputo Declaration target of 10% and the Malabo Declaration commitment.
Late release of funds: Funds allocated for agriculture are often released late in the fiscal year (e.g., after planting season), reducing their effectiveness.
Capital vs. recurrent imbalance: A large proportion of agricultural expenditure is recurrent (salaries, administrative costs) rather than capital (research, extension, infrastructure, equipment).
Poor implementation: Bureaucratic bottlenecks, corruption, and elite capture lead to incomplete projects, diverted funds, and poor service delivery.
Poor maintenance: Infrastructure (roads, irrigation, storage) is not maintained, leading to deterioration and reduced effectiveness.
Weak monitoring and evaluation: There is no systematic evaluation of the impact of agricultural programmes, so ineffective programmes continue.
Limited empirical evidence: There is limited empirical evidence quantifying the impact of government agricultural expenditure on agricultural output (yield, GDP) using rigorous time-series methods.
Mixed findings: Existing studies have produced mixed findings (positive vs. insignificant; long-run vs. short-run only; unidirectional vs. bidirectional causality).
Limited period coverage: Many studies cover periods ending in 2018 or 2019. An updated study through 2020 is needed.
The problem this study addresses is the need to empirically examine the impact of government expenditure on the agricultural sector 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 government agricultural expenditure and agricultural output.
1.3 Aim of the Study
The specific aim of this research work is to examine the impact of government expenditure on the agricultural sector 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 government agricultural expenditure (capital and recurrent) and agricultural output (agricultural GDP).
1.4 Objectives of the Study
- To determine the time-series properties (stationarity) of government agricultural expenditure (total, capital, recurrent) and agricultural output (agricultural GDP) in Nigeria.
- To examine the long-run relationship (cointegration) between government agricultural expenditure and agricultural output.
- To estimate the short-run dynamics (error correction mechanism) of the relationship between government agricultural expenditure and agricultural output.
- To determine the direction of causality (Granger causality) between government agricultural expenditure and agricultural output.
- To quantify the magnitude of the effect (elasticity) of changes in government agricultural expenditure on agricultural output.
1.5 Research Questions
- What are the time-series properties (stationarity) of government agricultural expenditure (total, capital, recurrent) and agricultural output (agricultural GDP) in Nigeria?
- Is there a long-run relationship (cointegration) between government agricultural expenditure and agricultural output in Nigeria?
- What are the short-run dynamics (error correction mechanism) of the relationship between government agricultural expenditure and agricultural output?
- What is the direction of causality (Granger causality) between government agricultural expenditure and agricultural output?
- What is the magnitude of the effect (elasticity) of changes in government agricultural expenditure on agricultural output?
1.6 Research Hypotheses
Hypothesis One
- H₀ (Null): Government agricultural expenditure has no significant impact on agricultural output in Nigeria.
- H₁ (Alternative): Government agricultural expenditure has a significant impact on agricultural output in Nigeria.
Hypothesis Two
- H₀ (Null): There is no long-run relationship (cointegration) between government agricultural expenditure and agricultural output.
- H₁ (Alternative): There is a long-run relationship between government agricultural expenditure and agricultural output.
Hypothesis Three
- H₀ (Null): There are no significant short-run dynamics (error correction) between government agricultural expenditure and agricultural output.
- H₁ (Alternative): There are significant short-run dynamics between government agricultural expenditure and agricultural output.
Hypothesis Four
- H₀ (Null): Government agricultural expenditure does not Granger-cause agricultural output.
- H₁ (Alternative): Government agricultural expenditure Granger-causes agricultural output.
Hypothesis Five
- H₀ (Null): Agricultural output does not Granger-cause government agricultural expenditure.
- H₁ (Alternative): Agricultural output Granger-causes government agricultural expenditure.
1.7 Justification of the Study
This study is justified on several grounds. First, despite the importance of government expenditure for agricultural development, Nigeria’s agricultural budget allocation is far below the Maputo Declaration target (10%). Second, there is limited empirical evidence quantifying the impact of government agricultural expenditure on agricultural output using rigorous time-series methods. Third, 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. Fourth, determining the direction of causality (Granger causality) is essential for policy: if government expenditure Granger-causes agricultural output, then increasing expenditure will increase output; if output Granger-causes expenditure, then output growth will stimulate expenditure. Fifth, quantifying the magnitude of effects (elasticity) will inform budget allocation to agriculture.
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 government expenditure on agricultural output, informing budget allocation, policy design, and programme prioritization. To the Ministry of Finance, Budget and National Planning, the findings will inform fiscal policy (budget allocation to agriculture, recurrent vs. capital expenditure). 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 National Planning Commission, the findings will inform agricultural development planning. 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 government expenditure-agriculture linkages, testing and extending agricultural development theory, Lewis dual sector model, and public finance theory.
1.9 Scope of the Study
The scope of this study is delimited to the impact of government expenditure on the agricultural sector in Nigeria. The study uses annual time-series data from 1981 to 2020 (40 observations). Variables include: government agricultural expenditure (total agricultural expenditure (₦ billion, nominal and real); capital agricultural expenditure (₦ billion); recurrent agricultural expenditure (₦ billion); agricultural output (agricultural GDP at constant prices (₦ billion); agricultural GDP growth rate (%); agricultural output index (base year = 100)). Control variables: agricultural credit (commercial bank credit to agriculture (₦ million, real)); fertilizer use (kg/ha); rainfall (mm); population growth rate (%); exchange rate (₦/USD); inflation rate (CPI %). 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 (manufacturing, services, oil).
1.10 Definition of Terms
Government Expenditure (Agricultural): Total spending by the federal government on the agricultural sector, including recurrent expenditure (salaries, administrative costs, subsidies) and capital expenditure (research, extension, irrigation, rural roads, storage, processing equipment, market infrastructure).
Capital Expenditure (Agricultural): Government spending on long-term investments in agriculture, including agricultural research and development (RandD), extension services, irrigation infrastructure, rural roads, storage facilities (silos, warehouses), processing equipment, market infrastructure, and agricultural machinery.
Recurrent Expenditure (Agricultural): Government spending on short-term operational costs in agriculture, including salaries of agricultural staff, administrative expenses, input subsidies (fertilizer, improved seeds, pesticides), and credit programme administration.
Agricultural Output: The total value of agricultural production (crops, livestock, forestry, fisheries) measured as agricultural GDP at constant prices (₦ billion) or agricultural GDP growth rate (%).
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.
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 agricultural output (agricultural GDP) resulting from a 1% change in government agricultural expenditure.
Agricultural Development Theory: A theory (Schultz, 1964) arguing that investment in agriculture (research, extension, credit, infrastructure) increases agricultural output, transforming traditional agriculture into a productive, modern sector.
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 government expenditure) increases surplus.
Public Finance Theory: A theory (Musgrave, 1959; Rosen and Gayer, 2020) explaining the role of government in providing public goods (research, extension, infrastructure) that private markets underprovide, and in correcting market failures.
CHAPTER TWO: LITERATURE REVIEW
2.1 Conceptual Framework
The conceptual framework for this study is organized around the key concepts of government expenditure, agricultural sector, the channels through which government expenditure affects agriculture, and the measures of both variables. These concepts are defined, operationalized, and related to one another below.
2.1.1 Concept of Government Expenditure on Agriculture
Government expenditure on agriculture refers to total spending by the federal government on the agricultural sector, including recurrent expenditure (salaries, administrative costs, subsidies) and capital expenditure (research, extension, irrigation, rural roads, storage, processing equipment, market infrastructure) (CBN, 2022).
Components of Government Agricultural Expenditure:
| Component | Description | Examples |
| Capital expenditure | Long-term investments | Agricultural research, extension, irrigation, rural roads, storage, processing equipment, market infrastructure |
| Recurrent expenditure | Short-term operational costs | Salaries of agricultural staff, administrative expenses, input subsidies, credit programme administration |
(Source: FMARD, 2021)
Government Agricultural Expenditure in Nigeria (1981-2020):
| Period | Average Annual Expenditure (₦ billion, nominal) | Share of Total Budget (%) |
| 1981-1985 | 0.5-1.0 | 3-5% |
| 1986-1993 | 1.0-5.0 | 2-4% |
| 1994-1998 | 5.0-10.0 | 1-2% |
| 1999-2007 | 10.0-50.0 | 2-4% |
| 2008-2012 | 50.0-100.0 | 2-3% |
| 2013-2020 | 100.0-150.0 | 1-2% |
(Source: CBN, 2022; Budget Office, 2021)
2.1.2 Concept of Agricultural Sector
The agricultural sector in Nigeria encompasses crop production, livestock, forestry, and fisheries (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 |
Trends in Agricultural GDP (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)
2.1.3 Channels Through Which Government Expenditure Affects Agriculture
Government expenditure affects agriculture through multiple channels (Schultz, 1964; Lewis, 1954; Timmer, 2019).
Channel 1: Agricultural Research and Development (RandD)
| Expenditure | Mechanism | Impact on Agriculture |
| Crop breeding | Develops improved seeds (disease-resistant, high-yielding, drought-tolerant) | Higher yields (30-100% increase) |
| Livestock breeding | Develops improved breeds (faster growth, disease-resistant) | Higher meat, milk, egg production |
| Pest and disease research | Develops control methods (integrated pest management, resistant varieties) | Reduced losses (20-50% reduction) |
| Soil fertility research | Develops fertilizer recommendations, soil conservation practices | Higher yields, sustainable production |
Channel 2: Extension Services
| Expenditure | Mechanism | Impact on Agriculture |
| Training of extension agents | Agents trained on improved practices | Farmers receive current information |
| Farm visits | Agents visit farmers | Personalized advice → adoption |
| Demonstration plots | Visual demonstration of improved practices | Farmers see results → adoption |
| Field days | Farmers visit demonstration plots | Social learning → adoption |
Channel 3: Input Subsidies
| Expenditure | Mechanism | Impact on Agriculture |
| Fertilizer subsidy | Reduces price of fertilizer (₦20,000-30,000/bag → ₦5,000-10,000/bag) | Higher fertilizer use → higher yields (40-60% increase) |
| Improved seed subsidy | Reduces price of improved seeds | Higher adoption → higher yields (30-100% increase) |
| Pesticide subsidy | Reduces price of pesticides | Better pest control → higher yields |
Channel 4: Irrigation Infrastructure
| Expenditure | Mechanism | Impact on Agriculture |
| Dam construction | Stores water for dry season | Year-round cultivation |
| Irrigation canals | Distributes water to farms | Higher yields, reduced drought risk |
| Boreholes and pumps | Provides water for dry season | Second cropping season |
Channel 5: Rural Roads
| Expenditure | Mechanism | Impact on Agriculture |
| Road construction | All-weather roads | Reduced transport costs |
| Road maintenance | Maintains passability | Reduced post-harvest losses, higher farm-gate prices |
Channel 6: Storage Facilities
| Expenditure | Mechanism | Impact on Agriculture |
| Silo construction | Stores grains | Reduced post-harvest losses, sell when prices higher |
| Warehouse construction | Stores produce | Reduced post-harvest losses |
| Cold storage | Stores perishable produce | Reduced losses for tomatoes, vegetables, fruits |
Channel 7: Credit Programmes
| Expenditure | Mechanism | Impact on Agriculture |
| ACGS (credit guarantee) | Guarantees 75% of loan | Increased bank lending to agriculture |
| ABP (anchor borrowers) | Input loans + off-taker guarantee | Increased credit to smallholders |
| CACS (commercial agriculture) | Low-interest loans (5-9%) | Increased credit to agribusiness |
Channel 8: Processing Equipment
| Expenditure | Mechanism | Impact on Agriculture |
| Rice mills | Milling paddy to milled rice | Value addition (₦200 → ₦450/kg, +125%) |
| Cassava processing equipment | Garri, HQCF, starch production | Value addition (+100-500%) |
| Fruit juice processing | Juice extraction, pasteurization | Value addition (+400%) |
2.1.4 Conceptual Framework Diagram (Described in Text)
The conceptual framework can be visualized as follows:
Government Expenditure (Independent Variable) → Channels → Agricultural Output (Dependent Variable)
Independent Variables (Government Expenditure):
- Total agricultural expenditure (₦ billion, constant prices)
- Capital agricultural expenditure (₦ billion)
- Recurrent agricultural expenditure (₦ billion)
↓ Channels (Mediating Variables):
- Agricultural research and development (RandD)
- Extension services
- Input subsidies
- Irrigation infrastructure
- Rural roads
- Storage facilities
- Credit programmes
- Processing equipment
↓ Dependent Variable (Agricultural Output):
- Agricultural GDP (₦ billion, constant prices)
- Agricultural GDP growth rate (%)
Control Variables:
- Agricultural credit (₦ million, real)
- Fertilizer use (kg/ha)
- Rainfall (mm)
- Population growth rate (%)
- Exchange rate (₦/USD)
- Inflation rate (CPI, %)
The framework posits that government expenditure (independent variable) affects agricultural output (dependent variable) through eight channels: agricultural research, extension, input subsidies, irrigation, rural roads, storage, credit programmes, and processing equipment. The magnitude of the effect is moderated by control variables (credit, fertilizer, rainfall, population, exchange rate, inflation).
2.2 Theoretical Framework
This study is anchored on three supporting theories that provide a comprehensive theoretical foundation for understanding the impact of government expenditure on the agricultural sector. These theories are Agricultural Development Theory, Lewis Dual Sector Model, and Public Finance Theory.
2.2.1 Agricultural Development Theory
Agricultural Development Theory, associated with Nobel laureate Theodore Schultz (1964), argues that investment in agriculture (research, extension, credit, inputs, infrastructure) is essential for transforming traditional agriculture into a productive, modern sector (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.
- Government investment is critical: Private investment in agriculture is limited due to high risk, long gestation periods, and public goods characteristics (research, extension, infrastructure). Government investment is needed to complement private investment.
- Transforming traditional agriculture requires: (a) new technology (high-yielding varieties, fertilizers), (b) incentives (profitable prices for outputs), (c) credit (to purchase inputs), (d) education (extension to teach practices), and (e) infrastructure (roads, storage, markets).
Application to Government Expenditure
Agricultural Development Theory predicts (Schultz, 1964; Timmer, 2019):
- Government expenditure on agricultural research (improved seeds), extension (training), credit (subsidies), and infrastructure (roads, irrigation, storage) will increase agricultural output.
- The returns to government agricultural investment are high (30-50% or more), given low current productivity and large gaps between actual and potential yields.
- Underinvestment in agriculture (low budget allocation) keeps farmers trapped in low-productivity traditional agriculture.
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 Government Expenditure in the Lewis Model
Government expenditure on agriculture (research, extension, credit, inputs, infrastructure) increases agricultural productivity, generating surplus (output above subsistence) that can be used to (Lewis, 1954; Timmer, 2019):
- Feed the industrial workforce (food surplus)
- Provide labour (workers released from agriculture as productivity increases)
- Provide capital (savings from agriculture can be invested in industry)
- Provide 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 |
| Agricultural budget share | <2% | Underinvestment in agriculture |
| Industrial employment share | ~10% | Low absorption of surplus labour |
2.2.3 Public Finance Theory
Public Finance Theory, developed by Musgrave (1959) and extended by Rosen and Gayer (2020), explains the role of government in providing public goods (research, extension, infrastructure) that private markets underprovide, and in correcting market failures (Musgrave, 1959; Rosen and Gayer, 2020).
Core Propositions (Musgrave, 1959; Rosen and Gayer, 2020):
- Public goods: Some goods (research, extension, infrastructure) are non-rival (one person’s consumption does not reduce availability for others) and non-excludable (cannot exclude non-payers). Private markets underprovide public goods; government must provide them.
- Market failures: Markets fail when there are externalities (positive or negative), information asymmetry, or missing markets. Government intervention (expenditure, regulation) can correct market failures.
- Agricultural research as a public good: Agricultural research (improved seeds, crop varieties, farming practices) benefits all farmers (non-excludable) and the benefits do not diminish with use (non-rival). Private firms underinvest in agricultural research; government must fund it.
- Extension as a public good: Extension services (training, advice) benefit all farmers; private firms underprovide extension; government must provide it.
- Infrastructure as a public good: Rural roads, irrigation, storage facilities benefit all farmers; private firms underprovide; government must provide them.
Application to Government Expenditure on Agriculture
Public Finance Theory predicts (Rosen and Gayer, 2020):
- Government expenditure on agricultural research is justified because private firms underinvest in research (public good).
- Government expenditure on extension services is justified because private firms underprovide extension (public good).
- Government expenditure on rural infrastructure (roads, irrigation, storage) is justified because private firms underprovide infrastructure (public good).
- Input subsidies (fertilizer, improved seeds) may be justified if there are positive externalities (e.g., improved nutrition, food security).
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 | Investment in agriculture for transformation | Explains why government expenditure (research, extension, credit, infrastructure) increases agricultural output |
| Lewis Dual Sector | Agricultural surplus supports industrial development | Explains how increased agricultural output (enabled by government expenditure) supports industrial development |
| Public Finance | Role of government in providing public goods | Explains why government must provide agricultural research, extension, and infrastructure (private markets underprovide) |
Together, these theories support the study’s examination of the impact of government expenditure on the agricultural sector, recognizing that: (1) government investment in agriculture increases output (Agricultural Development); (2) agricultural surplus supports industrial development (Lewis); and (3) government must provide public goods (research, extension, infrastructure) that private markets underprovide (Public Finance).
2.3 Review of Related Empirical Studies
This section reviews empirical studies relevant to the impact of government expenditure on the agricultural sector.
2.3.1 Studies on Government Expenditure and Agricultural Output (Nigeria)
Adebayo and Ogunyemi (2020) studied the impact of government agricultural expenditure on agricultural output in Nigeria (1981-2018). Using a Vector Error Correction Model (VECM), they found that government agricultural expenditure had a positive and significant effect on agricultural GDP in the long run (elasticity 0.25, p<0.05). A 1% increase in government agricultural expenditure increased agricultural GDP by 0.25% in the long run. In the short run, the effect was positive but not significant. The study recommended increasing government agricultural expenditure to 10% of the federal budget (Maputo Declaration target).
Eze and Nweze (2019) studied the effect of government agricultural expenditure on agricultural output in Enugu State (1990-2018). Using Ordinary Least Squares (OLS) regression, they found a positive and significant relationship (R² = 0.58, p<0.01). However, they did not test for stationarity or cointegration; OLS on non-stationary data may produce spurious results. The study recommended increasing government agricultural expenditure.
Okafor and Nwosu (2020) studied the effect of government agricultural expenditure on agricultural GDP in Nigeria (1981-2019). Using Autoregressive Distributed Lag (ARDL) bounds testing, they found a long-run relationship (cointegration) between government agricultural expenditure and agricultural GDP. The long-run elasticity was 0.22 (p<0.05). The study concluded that government agricultural expenditure significantly affects agricultural output.
Okonkwo (2020) studied the effect of government agricultural expenditure on agricultural productivity in Nigeria (1981-2018). Using a VECM, he found that government agricultural expenditure had a positive but small effect (elasticity 0.12, p<0.10). The study recommended increasing government agricultural expenditure as a percentage of the total budget (currently <2% of federal budget, far below the 10% Maputo Declaration target).
2.3.2 Studies on Capital vs. Recurrent Expenditure (Nigeria)
Adebayo and Adeyemi (2021) studied the differential impact of capital and recurrent agricultural expenditure on agricultural output in Nigeria (1981-2018). Using an ARDL model, they found that capital expenditure had a positive and significant effect (elasticity 0.18, p<0.05), while recurrent expenditure had a positive but insignificant effect. The study recommended shifting budget allocation from recurrent to capital expenditure.
2.3.3 Studies on Government Expenditure and Agricultural Output (Other Countries)
| Study | Country | Period | Key Findings |
| Fan, Hazell and Thorat (2000) | India | 1970-1995 | Agricultural research and infrastructure had highest returns (40-60%) |
| Thirtle, Lin and Piesse (2003) | Africa | 1960-1990 | Agricultural research had high returns (30-50%) |
| Diao, Hazell and Thurlow (2010) | Africa | 2000-2007 | Agricultural expenditure has higher poverty reduction impact than non-agricultural expenditure |
2.3.4 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 |
2.3.5 Summary of Empirical Findings
The empirical literature reveals consistent findings: (1) government agricultural expenditure has a positive impact on agricultural output in Nigeria (elasticities 0.12-0.25); (2) capital expenditure has a stronger effect than recurrent expenditure; (3) the effect is stronger in the long run than the short run; (4) agricultural research and infrastructure have high returns; (5) constraints include low budget allocation (<2% of federal budget), late release of funds, poor implementation, and weak monitoring. 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 government expenditure on the agricultural sector.
| Author(s) and Year | Focus of Study | Strength | Weakness | Limitation | Gap Identified |
| Schultz (1964) | Agricultural Development Theory | Investment in agriculture for transformation | 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 |
| Musgrave (1959); Rosen and Gayer (2020) | Public Finance Theory | Role of government in providing public goods | General | General theory | Application to Nigeria needed |
| Adebayo and Ogunyemi (2020) | Government expenditure and output (1981-2018) | VECM; elasticity 0.25 | Period includes post-2007 structural breaks | Period gap | Updated study needed |
| Eze and Nweze (2019) | Government expenditure and output (Enugu) | Positive relationship | OLS (no stationarity test) | Methodological gap | Cointegration test needed |
| Okafor and Nwosu (2020) | Government expenditure and GDP (1981-2019) | ARDL; elasticity 0.22 | Period includes post-2007 breaks | Period gap | Updated study needed |
| Okonkwo (2020) | Government expenditure and productivity (1981-2018) | Elasticity 0.12 | Period includes post-2007 breaks | Period gap | Updated study needed |
| Adebayo and Adeyemi (2021) | Capital vs. recurrent expenditure | Capital > recurrent | Short period | Period gap | Updated study needed |
| Fan, Hazell and Thorat (2000) | Research and infrastructure returns (India) | High returns (40-60%) | India, not Nigeria | Geographic gap | Nigeria replication needed |
| Thirtle, Lin and Piesse (2003) | Agricultural research returns (Africa) | High returns (30-50%) | Not Nigeria-specific | Geographic gap | Nigeria-specific needed |
| Diao, Hazell and Thurlow (2010) | Agricultural expenditure and poverty (Africa) | 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 |
| Budget Office (2021) | Federal budget reports | 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 |
