€¦ · Web viewAgricultural productivity returns to public spending across Major Agro-ecological Zones of Nigeria (1981-2014): An Empirical linkage. Abstract. This study examines

Agricultural productivity returns to public spending across Major Agro-ecological Zones of Nigeria

(1981-2014) An Empirical linkage

Abstract

This study examines agricultural-productivity returns to public spending across major agro-ecological zones

of Nigeria (1981-2014) Using public-finance data of agriculture and the non-agricultural sector at national-

level agricultural-productivity returns were analyzed Agricultural spending as a share of total public-

spending averaged 488 between 1981 and 2014 across zones Less than 25 of this allocation was spent

on developmentcapital project in Nigeria Agricultural-productivity returns to public spending were

enhanced by education health and access to moderate ruralfarm roads 1 increase in public spending on

agriculture is linked with 007 009 and 005 in educational sector health sector and ruralfarm roads

respectively with estimated benefit-cost-ratio of 75 However the estimated marginal effects and returns

vary for the four agro-ecological zones Hence harmonizing amid quality spending on access to health

education and rural roads enhanced agricultural productivity Public-spending can be effectively used to

stimulate economic growth and enhance agricultural productivity

Keywords Public Expenditure and Financings marginal returns agricultural productivity agro-ecological zones Nigeria

Introduction

Public spendingexpenditure in the form of budget is making a provision for development for today and also

for the future Over the years (1960-2010) sustainable public spending has been a contentious issue in

economic development (Mongues et al 2008 Kareem et al 2015 Arndt et al 2015 Anisimova 2016

Makhtar 2017) Few have argued that the concept of public spending is associated with sustainable

development because the coverage of sustainability related concepts is also in the purview of government

expenditure (Manyong et al 2005 Aparajita and John 2017) Public spending is a fiscal instrument that

government uses to sustain the economy and development For many developing countries agriculture is the

prime sector in terms of its contributions to gross domestic product (GDP) and employment In addition

most of the people living in poverty worldwide sought their income generating activities from agriculture

and agricultural related activities and resides in rural areas Developing an effectual agricultural policy

financing in developing countries must be a top priority and a well-organized government instruments must

be put in place to drive agricultural growth (Fan et al 2000 Arndt et al 2015 Ojiako et al 2016)

Guseh (1997) Wu et al (2010) and Karamba and Winters (2015) argued that agricultural growth and

poverty reduction correlates to cost-effective public expenditure Fan and Zhang (2008) and Wu et al

(2010) indicated that cost-effective funding of drivers of agricultural growth like extension services

efficient credit delivery systems research and development among others bring about agricultural growth

not the high public expenditures that could bring about the growth Benin et al (2009) and Diao et al (2010)

argued that it is only high public expenditure to agriculture that could bring about the growth However

evidence has shown that in developing countries public expenditure to agriculture is too low to bring about

meaningful development (Guseh 1997 Manyong et al 2005) Zhang and Fan (2004) and Yasin (2000)

contended that identifying the drivers of growth and funding these drivers promptly is the key

OPM (2005) Breisinger et al (2008) and Emerenini and Ihugba (2014) indicated that in Africa

expenditure in agricultural sector has (as a percentage of agricultural GDP) persisted at comparatively low

levels (54 - 74 per cent) while in Asia it was much higher (85 - 105 per cent) than in Africa (1971-2010)

Hence poor public expenditure in the agricultural sector in Nigeria is reflected in the poor infrastructures

and poor agricultural outputs Nigeria since its inception has set out policies that could transform

agricultural sector these policies have had a big influence in shaping the trend of government expenditures

But the countryrsquos huge agricultural resource base that offers great potential for growth has not really

achieved that feat due to poor funding given to drivers of agricultural growth (Ghura 1995 Mongues et al

2008 Ojiako et al 2016)

Manyong et al (2005) revealed that in the 1960rsquos agriculture in Nigeria contributed about 64 to the total

GDP due to heavy investment the sector enjoyed from both public and private organizations Kareem et al

(2015) indicated that in the 1970rsquos agriculture contribution to GDP declined from 65 to 48 in 1995 to

20 in 2005 to 19 and 15 in 2008 Evidence has shown that the root cause of the crisis is the poor

funding of major drivers of agricultural growth that led to its poor contribution (Mongues et al 2008

Breisinger et al 2008) Evidence from other African countries like Zimbabwe revealed that the government

of Zimbabwe has had extraordinarily high public expenditure to agriculture (1990-2010) most of the public

funds were channeled towards developing agriculture For example support was given to drivers of

agricultural growth like Farm Mechanization Programme and this policy improved access to important farm

inputs by majority of Zimbabwean farmers (Ansari et al 2007) Conversely neglect of funding to

agricultural sector over the years in Nigeria has influenced increase poverty among small farmers

Research on public expenditures and agricultural growth in Nigeria have been sparsely no research (to the

knowledge of researcher) have examined agricultural productivity returns to public spending across major

agro-ecological zones of Nigeria Public expenditure aims at financing the incentives for development of

enterprise and also to facilitate a fertile ground for the promotion of private sector investments and

enterprise growth Hence considering the largest employer of labour in most developing countries like

Nigeria which is agriculture public cost-effective financing of agriculture becomes a key developmental

strategy for economic growth (Diao et al 2007 Emerenimi and Ihugba 2014 Takesshima and Liverpool-

Tasie 2015) Consequently examination of agricultural productivity returns to public spending across major 2

agro-ecological zones of Nigeria could provide a strong basis for creating sound macroeconomics policies

that could chart a strong agricultural development Also the motivation of the paper is to offer agricultural

policy makers and leaders a better insight on the impacts of government expenditures on agricultural

productivity and assist them in better allocation of resources for national development

Economy Theory and Evidence based of public spending

Public spending in the last 3 decades has generated arguments and concerns one that has grasped the

attention of several researchers particularly as predictors of economic growth (Kareem et al 2015) Public

spending has been used considerably as fiscal policy by the government in many countries but its effect on

economic growth is debatable Mongues et al (2008) outlined 2 economic hypotheses as a basis to evaluate

the effect of public spending on growth ie Wagnerrsquos law and Keynesian hypothesis Wagnerrsquos law - law of

the expanding state role ndash is a model showing that public spending is endogenous to economic growth and

that there exist long-run tendencies for public spending to grow relatively to some national income

aggregates such as the gross domestic product (GDP) Wagner (1893) suggested that public spending is an

endogenous factor or an outcome but not a cause of economic development

On the other hand Keynesian hypothesis state that expansion of public spending hastens economic growth

(Aschauer 2000) Thus government expenditure is regarded as an exogenous force that changes aggregate

output (Alshahrami and Alsadiq 2014) Keynesian school of thought suggests that a proactive fiscal policy

is an important instrument governments used to stimulate economic activity and growth (Ansari et al 1997)

By increasing public spending andor cutting taxes governments can offset a slower pace of economic

activity hence fiscal policy is viewed as a counter-cyclical policy tool that mitigates short-run fluctuations

in output and employment (Hsaieh and lei 1994) In addition the Keynesian hypothesis suggests that any

kinds of public spending even of a recurrent nature can contribute positively to economic growth The

effectiveness of fiscal policy in stabilizing aggregate demand also depends on whether or not public

spending crowds out private spending An increase in government spending that is not matched by an

increase in revenues leads to a budget deficit If the deficit is financed by issuing domestic debt it can have

negative consequences for domestic interest rates which crowds out private (consumption and investment)

spending (Alexiou 2009)

Past studies on causality between public spending and economic growth adopted diverse theories and

methods to drive intentions Outcomes of their analysis revealed that the effect of public spending on

economic growth can run either be negative or positive Ghura (1995) using pooled time-series and cross-

section data for 33 countries in Sub-Saharan Africa (SSA) (1970-1990) evidenced a negative relationship

between public spending and economic growth Similarly Yasin (2000) studied the relationship of public 3

spending and economic growth in 26 sub-Saharan Africa (SSA) countries using panel data from 1987 to

1997 period and employing both the fixed effect and random effect techniques The result revealed a

positive outcome as against the negative consequence of Ghura (1995) Yasin (2000) argued that

government spending on capital formation create favorable economic environment

Alexiou (2009) explored seven countries in the South-Eastern Europe region (1995-2005) and adopting

similar econometric approaches of Yasin (2000) indicated that public spending on capital formation and

drivers of agricultural growth influenced a significant and positive effect on economic growth Hence policy

makers can create an appropriate environment conducive to nurturing government spending on capital

formation Alshahrani amp Alsadiq (2014) used Vector Error Correction Model (VECM) to examine this

causality of government expenditure on economic growth in Saudi Arabia engaging time-series data over the

period 1969 ndash 2010 the study found that private domestic and public spending as well as healthcare

expenditure stimulate growth in the long-run Similarly Knoop (1999) adopted time-series data to examine

the effects of government spending on economic growth in the US the results revealed that a reduction in

the size of the government (reduction in government spending) would have an adverse impact on economic

growth and welfare

However there are studies that reported a different outcome for instance Guseh (1997) used similar

econometric technique adopted by Knoop (1999) and exploited time-series data over the period 1960 ndash 1985

for 59 middle-income developing countries to examine the effects of government size on the rate of

economic growth His result suggested that growth in government size has negative effects on economic

growth Attari amp Javed (2013) examined this linkage in Pakistan using time series data (1980-2010) and

evidenced a statistically insignificant outputs Hsieh amp Lai (1994) examined the causality between public

spending and economic growth in G-7 countries namely Canada France Germany Italy Japan UK and

USA Their empirical analysis showed the relationship between government spending and growth can vary

significantly across time Using the structure adopted by Hsieh amp Lai (1994) Emerenini amp Ihugba (2014)

studied government expenditure and economic growth in Nigeria using the co-integration and error

correction methods and employing time-series data (1980 ndash 2012) found out that total capital expenditure

total recurrent expenditures and government expenditure on education have negative effect on economic

growth

The reviewed of literature and past studies on the causality between public spending and economic growth

suggest that public spending is helpful to the economic growth regardless of how the government

sizespending and economic growth is measured as evidenced in the works of Wu et al (2010) and (Ansari

et al (1997) Evidence from these reviews suggest that developing nations should limit their governmentsrsquo

consumption spending and invest in infrastructure to stimulate growth (Kareem et al 2015) The study 4

deduce that the effect of public spending on economic growth can be positive or negative The relationship

between government spending and economic growth is far from clear

Empirical Linkages amid Public expenditures and Agricultural Growth

Public expenditure is a significant factor for development and aims at financing the incentives for

development and creating a fertile ground for the promotion of private sector investments and enterprise

growth Hence increase public expenditures could also increase private sector investments and enterprise

growth and thus lower the incidences of poverty Therefore there is a need to develop a model that captured

link between public expenditure and agricultural growth Several model have been used to examine this

linkage The works of Fan et al (2000) and Benin et al (2009) that modelled a simultaneous-equations

approach to exemplary household farm production and government expenditures choice making to establish

the linkage between public expenditure and agricultural growth These studies argued that composition of

public expenditures to major drivers of that sector should be paramount Following the works of Wu et al

(2010) the composition of government expenditures is modeled in the following pattern

V iquest=k (PEXPGDP t GDP t DV t U t) helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip(1)

Where Vit is the share of ith sector (agricultural) in total government expenditure t for time PEXPGDP is

public expenditure as a percentage of GDP GDPt is per capita GDP DVt is a dummy variable that is

equal to 1 when macroeconomic regulations are implemented and equal to 0 otherwise and Ut comprises

added factors that may affect government expenditure in the sector Mongues et al 2008 argued that oil and

non-oil revenue assistance and structural adjustment programs can also be the function of government

revenue hence causing the occurrence of an endogeneity Thus it is hypothesized that Ordinary Least

Square (OLS) estimation technique will lead to biased estimation In order to evade the possibility of

endogeneity problem of the independent variables the GMM instrumental variable method will be adopted

Moreover GMM1 will be used to take care of any possible presence of unit roots or non-stationarity of

variables that may cause spurious regressions results To model the impact of public expenditures and

agricultural growth past studies have argued that public expenditures and investments affect productivity

through several means and the use of a simultaneous-equation will take care of all these incidences (Fan et

al 2000 and Benin et al 2009)

TOAGRk= f ( PUEXP p FACDEV p PRODET k DRIVERSk IDFACT p SOCIOXT k βk β p β f ) helliphelliphellip(2)

1 Dickey-Fuller approach have been used for tests of presence of unit roots or non-stationarity (Holtz-Eakin et al 1988) The results of these tests revealed that government revenues expenditures foreign assistance and agricultural expenditures the hypothesis of unit root is hence excluded

Where TOAGRk is the total value of agricultural output per capita of a household

PUEXPp is labelled as a function of public expenditure in agriculture

(where PUEXPp = PUEXPca + PUEXPrc

PUEXPca Public Capital expenditure in agriculture

PUEXPrc Public Recurrent expenditure in agriculture

FACDEV is other factors influencing public investment that motivate enterprise growth in

Agriculture like infrastructures (good farm access roads storage facilities) education access

quality health-care facilities

PRODET is the production function of determinants

DRIVERS is the drivers of agricultural growth that motivate enterprise development like

research and development credit delivery services extension services

IDFACT is indirect factors influencing agricultural enterprise growth

SOCIOXT is the socioeconomics characteristics that could influence production process like

gender income strategies level of education age Others are various cultural political and

institutional factors

βk β p β f are vectors of parameters to be estimated for the equation

FACDEV p=f (PUEXP p PRODET k DRIVERSk IDFACT p SOCIOXT k β l βa)helliphelliphelliphellip(3)

DRIVERS k=f (INTERPOLp PRODET k IDFACT p βa βk) helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip(4)

Where INTERPOL is the intervention policies of the government to stimulate and motivate

enterprise growth in agriculture

βa βk are vectors of parameters to be estimated for the respective equations 3 and 4

Equation (2) (total value of agricultural output per capita of a household) captures the level of impact of

public investments for enterprise growth in agriculture Other determinants of the total value of agricultural

output were the drivers of agricultural growth DRIVERS and factors influencing public investment that

motivate enterprise growth FACDEV Equation (3) examines enterprise growth from the function of public

expenditures and indirect effects of public expenditures on enterprise growth Equation (4) is on locational

effects (agro-ecological zone of the country) of public expenditures and government intervention on the

drivers of enterprise growth programs where prior agricultural performance and area characteristics may

have an influence Thus by including public expenditures and intervention in other sectors in equation 4 the

study tried to capture possible interaction effect between expenditure on the non-agricultural sectors and

agricultural sector

Marginal Effect of Public expenditure on Agricultural growth

Hence the marginal effect of public investments on agricultural growth can thus be estimated as

helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip

isinDRIVERS=dTOAGRdPUEXP

=part TOAGRpart PUEXP

+ partTOAGRpart FACDEV

X part FACDEVpart PUEXP ---------- (5)

isinDRIVERS is the marginal effects of the drivers of agricultural growth that motivate enterprise

development like research and development credit delivery services extension services Therefore

Equation (5) measures the direct effect of public investments in agriculture

dTOAGRdPUEXP

andpart TOAGR

part PUEXP+ part TOAGR

part FACDEVX part FACDEV

part PUEXP -captured the indirect effect

Equation 5 hypothesized the typical vector of production function estimates with respect to farm investments

(ie factors of production and inputs) This equation captured the elasticity of agricultural productivity with

respect to public investment in the other sectors (isin IDFACT ) which is a function of βp βk and βa and can

be obtained by

isin IDFACT=dFACDEVdIDFACT

=part FACDEVpart IDFACT

+ part FACDEVpart PRODET

X part PRODETpart IDFACT

+isinDRIVERS X dTOAGRdPUEXP helliphelliphellip(6)

Marginal Returns to Public Spending

Marginal returns to public investments (ie the benefit-cost ratio or BCR) can be computed by multiplying

equations (7) and (8) with the relevant ratio of agricultural output per capita to public investment taking a

cue from (Fan et al 2000 and Benin et al 2009)

BCR DRIVERS=isinDRIVERS X FACDEVDRIVERS helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip (7)

BCR IDFACT=isin IDFACT X FACDEVIDFACT helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip (8)

Marginal returns provide information for comparing the relative benefits of an additional unit of spending on

different sectors Thus data can then be used for locale future priorities for public expenditures and

intervention policies of government that could enhanced agricultural productivity 7

Estimation Techniques and Concerns

The study adopted estimation techniques of a Three-Stage Least Squares (3SLS) method to simultaneously

appraise equations (1) (2) (3) and (4) Past studies have argued that when these techniques are considered

some issues and concerns need to be considered (Fan et al 2000 and Benin et al 2009) Firstly the

estimation techniques require equal number of observations for each of the dependent variables and to

address this concern each low dependent variables data were aggregated upwards to be the same with others

(Fan et al 2000) In addition to estimate the variance and standard errors the study take a cue from the

work of Hsieh and Lai (1994) that adopted the delta method (isin) for the estimation technique Hence the

typical form of the probable elasticities of the method as adopted

isin=f iquest) helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip(9)

Also the variance of the probable elasticities adopting the delta method and the variance-covariance matrix

of the coefficients (sumisin ˆ ) can be achieved using the general form as

Var (isin )=iquest helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip(10)

The study taking into consideration the concern of the identification issue in the equation that might arises

during estimation especially in the equation (1) This concern was addressed by exploiting exclusion

restrictionsmdashie excluding some of the explanatory variables (or instruments) used in estimating equation

(2) from equation (1) because using weak instruments could produce more biased estimates than those

attained if the parameters were appraised by an ordinary least squares (OLS) method (Greene 1993)

Another concern the study looked into was the issue of multicollinearity due to large set of explanatory

variables data Basic multicollinearity complications can cause the parameters to be estimated loosely

giving wrong signs and wide variations in magnitudes among others (Greene 1993) Variance Inflation

Factor (VIF) was adopted to take care of this (Greene 1993) Hence the study regression results however

(to the knowledge of the researcher) do not reflect any biased estimates

METHODOLOGY

Area of study

Nigeria has a geographical area of 923 768 square kilometers with an estimated population of about 140

million (2006 estimates) people It lies wholly within the tropics along the Gulf of Guinea on the western

coast of Africa The country has a highly diversified agro ecological condition which makes it possible for 8

the production of a wide range of agricultural products Notwithstanding the country rich agricultural

resource endowment however the agricultural sector has been growing at a very low rate Less than 50 of

the countryrsquos cultivable agricultural land is under cultivation Even then smallholder and traditional farmers

who use rudimentary production techniques with resultant low yields cultivate most of these lands The

country is divided into a four major agro-ecological zones which is used as a base of analysis for this study

Figure 1 Map of Nigeria

Table 1 Major Agro-ecological zones in Nigeriasn Major Agro-

ecological zonesStates Major agricultural activities Vegetation

1 MarginalShort grass Savannah

Bauchi Borno Jigawa Kano Katsina Kebbi Sokoto Yobe and Zamfara

Cotton Groundnut Sorghum Millet Maize and Wheat Locust Bean trees (Parkia filicoidea) Tamarind tree (Tamarindus indica) and Mango (Mangifera indica)

Low average annual rainfall of 6573mm and prolonged dry season (6-9 months)

2 DerivedWoodland and Long grass Savannah

Abuja Adamawa Benue Gombe Kaduna Kogi Kwara Nassarawa Niger Plateau and Taraba

Grazing livestock such as cattle goats horses sheep camels and donkeys Maize Cassava Yam and Rice

This zone experiences lower rainfall shorter rainy season and long dry period

3 Rainforest Abia Anambra Ebonyi Edo Ekiti Enugu Ogun Ondo Osun and Oyo

Staple crops like yam cassava cocoyam sweet potatoes melon groundnut rice maize and Oil Palm (Elaeis guineensis) Cocoa (Theobroma cacao) Rubber (Hevea brasiliensis) bananaPlantain (Musa spp) Cotton and Cola nut (Cola nitida) Cowpeas and Beans as well as a number of fruits A number of timber trees such as the African Mahogany the scented Sapele wood (Entandrophragma cylindricum) and Iroko (Chlorophora excelsa)

Prolonged rainy season resulting in high annual rainfall above 2000mm

4 MangroveSwamp Akwa Ibom Bayelsa Oil-Palm Cocoa Cassava Maize Yam Prolonged rainy season 9

Cross Rivers Delta Lagos and Rivers

Various Palm and Fibre plants such as Raphia spp Raphia vinifera the Wine Palm and Raphia hookeri the Roof-mat Palm

and lagoons overflow banks in the wet season (8-9 months) Thus longer rains has led to badly leached soils and severe erosion

Sources [1] httpsoilsnigerianet [11]Oyenuga VA (1967) Agriculture in Nigeria Food and Agriculture Organization of the United Nations) FAO Rome Italy 308 pp[iii] Materials from httpwwwfaoorg[iv] Sowunmi FAand Akintola JO (2010) Effect of Climatic Variability on Maize Production in Nigeria Research Journal of Environmental and Earth Sciences 2(1) 19-30

Method of data collection

Secondary and primary data were collected for this study Data were sourced from the federal state and

local government levels from ministries of agriculture and other key ministries departments agencies and

offices responsible for finance revenue budget planning and local government affairs The study

conceptualized agriculture and agricultural activities to include arable and covers crop livestock production

forestry and fisheries While the study deduced public expenditures to be an annual and supplementary

appropriations that support the direct and indirect growth of the agricultural industry

Main data used include both budget and actual expenditures on agriculture Public finance data from

Ministry of finance public expenditure data from other key sectors and Central Bank of Nigeria (CBN)

Statistical Bulletin (2014) and CBN Annual reports (various issues) were also used as applicable Moreover

secondary data were obtained from Budget and economic planning office of the Federal ministry of Finance

Abuja National Bureau of Statistics (NBS) annual abstract of statistics (various issues) Ministry of

Agriculture Ministry of Information Agricultural Development Project (ADP) Offices Nigerian Institute of

Social Economic Research (NISER) Ibadan Primary information were sourced from questionnaires

administered on senior personnel in the Budget office of the Federal Ministry of Finance and NISER

Primary data helped to bridge information that was not provided for through secondary sources Information

were sourced also from websites of the secondary sources identified above

Public expenditures on the non-agricultural sector at national-level expenditure like education health and

feeder roads were obtained from the respective government ministries departments and agencies

Agricultural production private farm investments and data on other farm-household characteristics were

sourced from the most recent National Living Standards Survey (NLSS) 20092010 Data on access to

education and health services are from the 2009 Core Welfare Indicators Questionnaire (CWIQ) Data on

rural roads and related information are from the Federal Ministry of Transport and Aviation and State

Ministries of Transport The variables used in the analysis which capture the conceptual factors discussed

earlier are presented in Table 2 All monetary values were converted into year 2000 constant prices using

regional consumer price index to exclude the influence of inflation and other temporal monetary and fiscal

trends Below we briefly discuss the public spending and private investment variables and how they were

measured

Table 2 Variables Description and Statistical Summaries of Major Variables usedVariable name

Variable description Mean Standard Deviation

TOAGR Total value of agricultural output per capita of a household Itrsquos also the value of total agricultural investments made and inputs used by the household in the survey scenario (N6500 Naira per capita) 587227 13826

PUEXP Labelled as a function of public expenditure in agriculture It is also based on (i) developmental expenditures and (ii) recurrent expenditures

4305 14819

616 1362

FACDEV Other factors influencing public investment that motivate enterprise growth in Agriculture like infrastructures (good farm access roads storage facilities) education health care facilities 225 062

Access farm roads

This is to deduce the quality of farm access roads to residences and markets and its significance on income generation Marginal Derived Forest Mangrove

(i) Good farm access roads 05 025 00 00(ii) Moderate farm access roads 05 075 075 05(iii) Poor farm access roads 00 00 025 05

15 175 225

058 050 052

Education Proportion of household members that have completed level of formal education and its significance on income generation Marginal Derived Forest Mangrove

(i) No formal education 05 05 00 00

(ii) Completed primary school 05 05 025 05(iii) Completed secondary school 00 00 025 05(iv) Post-secondary attemptcompleted 00 00 05 00

15 25 325 25

057 058 096 058

Access to health care

Proportion of households living within vicinity of health facility(cf up to 15 minutes) Marginal Derived Forest Mangrove

(i) 15ndash29 minutes 000 000 025 000(ii) 30ndash44 minutes 025 050 050 025(iii) 45 minutes or more 075 050 025 075

20 25 275

082 058 050

SOCIOXT Household characteristics(i) Household size Number of household members (adult equivalents)(ii) Gender of head Dummy variable for head of household 0=female

1=male(iii) Age of head Age of household head (years)(iv) Adult labour Proportion of members aged 18 to 64 (v) Male labour Proportion of members that are male(vi) Female labour Proportion of members that are male(vii) Employment Proportion of members employed(viii) Income diversificationstrategy Marginal Derived Forest

MangroveSubsistence farming only 00 00 050 050Semi commercial farming only 00 00 00 00Subsistence farming + Market-oriented crops 025 025 025 025Semi commercial farming + Market-oriented 00 00 00 00Subsistence farming + Non-farm activity 050 025 025 025Semi commercial farming + Non-farm activity 025 05 00 00

(ix) Farm assets characteristics Marginal Derived Forest Mangrove

Population 2009 projections 63500175 45889717 22175254 18640172Proportion of households living below poverty line 3653 3387 3243 3873Total land area (1000 sq km) 338206 380728 121355

593 062 5123 032 047 052 035 157 00 20 00 325 30 150205318 3639 22734725 2504 451554

031 528 017 021 043 008

048 00 141 00 096 082 4423852 280 3843105 1708 249724

12969711

69100Farm size Acres of farmland () 3717 4190 1351 742Livestock assets No of tropical livestock units 1193641 542792 48252 21530Value of crop production equipment (N20000 per capita) 720315 91731 72817 25328 of population with agriculture as main activity 7126 6503 4103 3517

227548 5312

AGRO ZONE

Agro-ecological zones(i) MarginalShort grass Savannah public expenditures on agriculture

MarginalShort grass Savannah Agriculture contribution to GDP (ii) DerivedWoodland and Long grass Savannah public exp on agric

DerivedWoodland and Long grass Savannah agric con to GDP (iii) Rainforest public expenditures on agriculture

Rainforest Agriculture contribution to GDP (iv) MangroveSwamp public expenditures on agriculture

MangroveSwamp Agriculture contribution to GDP

3158 2998 4717 3132 3671 2527 1764 1334

382 417 524 302 414 502 616 528

Source Various federal and state government agencies

RESULTS AND DISCUSSION

Review of Government efforts on public spending in agricultural development in Nigeria

Review of public spending indicated that disproportionately high percentage of public spending (35) was

spent on major agricultural commodities (Kareem et al 2015) The study found out that about 81 of all

spending goes to 3 out of 179 sub-items that is Fertilizer supply (43) Food security component of

National Store of products and food services (NSPFS) (22) Grain purchase in Strategy Grain Reserve

(SGR) (16) (Mongues et al 2008 CBN 2016) Agricultural spending as a share of total federal spending

averaged 4-6 between 1990 and 2002 and has been trending downward precipitously In contrast Nigeria

recorded an annual average agricultural growth rate of more than 6 between 2003 and 2009 and 4

between 2010 and 2014 Budgetary allocation to agriculture compared with other key sectors is also low

despite the sectorrsquos role in the fight against poverty hunger and unemployment and in the pursuit of

economic development

Moreover agricultural spending in 1990 and 2008 averaged 55 and 46 respectively Actual expenditure

on agriculture rose by 577 in 2009 from its 2008 level but consistently declined after that until 2012 The

share of agricultural spending in total spending is lower than the corresponding shares of most of the sectors

at the federal level For example compared with an average of 46 for agriculture corresponding shares

for economic affairs public order and safety general public services and defense averaged 244 153

133 and 9 respectively between 2008 and 2012 Spending shares for similar key sectors such as

education and health are relatively closer in magnitude to that of agriculture averaging 74 and 54

respectively during the same period However agriculture was the only sector that saw a decline in

spending falling on an average by 148 from 2008 to 2012 In contrast spending on education and health

increased on average by 414 and 338 respectively (CBN 2016) Agricultural finance trend analysis

indicated fluctuation 1981-1985 had two sharp declines 1991-1994 and 1996-1998 Increase during

Structural Adjustment programmes (SAP) period 1985-1990 There was a notable decline in 1996-1998

during the military era when public spending was majorly on defense There was however a consistent

growth of public spending on agriculture from 2000 -2014 (CBN 2016)

Agricultural Budget and expenditures appropriation to agro-ecological zones and contribution to

Gross Domestic Product (GDP) (1981-2014)

Table 3 reviewed agricultural budget and expenditures appropriation to agro-ecological zones and its

contribution to GDP from 1981-2014 The results indicated that from 1981-1990 share of statutory budget

allocation to agricultural development was 488 on the average across zone but marginalshort grass

savanna agro-ecological zone took the highest (732) while mangroveswamp agro-ecological zone took

239 Agriculture contribution to GDP () from 1981- 2005 averaged 3514 with marginalshort grass

savanna agro-ecological zone took 2913 and mangroveswamp agro-ecological zone took 1432 Total

funding (shares) to agricultural sector also indicated 3252 4716 3780 and 1782 across the zones

marginalshort grass savanna derivedwoodland long grass savannah rainforest and mangroveswamp agro-

ecological zones respectively Agricultural spending across the agro-ecological zones have not been

encouraging the intervention of both local and foreign direct investments have been significant in this

regards Intervention of both local and foreign direct investments in public spending to agriculture showed

6347 7651 8034 and 7469 in marginalshort grass savanna derivedwoodland long grass savannah

rainforest and mangroveswamp agro-ecological zones respectively (table 3) This finding corroborated by

Mongues et al (2008) and Manyong et al 2005 acknowledged the role these intervention agencies played in

agricultural development in Nigeria To improve agricultural funding for development local and foreign

direct investment play a significant role Concerns arises whether public funding in agriculture translate to

agricultural outputs in the identified agro-ecological zones particularly the marginalshort grass savanna

This is a future research

Table 3 Agricultural Budget and expenditures appropriation to agro-ecological zones and contribution to Gross Domestic Product (GDP) (1981-2014)

Major Agro-ecological Zones

Share of States Statutory Budget allocation to agricultural development ()

Share of Federal Government intervention to agric dev ()

Share of Local and International AidsIntervention to agric dev ()

Total funding (Shares) to agric sector ()

Agriculture Contribution to GDP ()

1981 ndash 1985 3510

MarginalShort grass Savannah 0762 0501 2602 3865

DerivedWoodland and Long grass Savannah

0603 4105 5380 2494

Rainforest 0527 0492 2402 3421 2301MangroveSwamp 0262 0272 0891 1425 1203 1986 ndash 1990 3658MarginalShort grass Savannah 0702 0612 2983 4297

2371DerivedWoodland and Long grass Savannah 0562 0514 4288 5364 3952Rainforest 0318 0383 2281 2982 2504MangroveSwamp 0216 0292 0727 1235 1173 1991 ndash 1995 3266MarginalShort grass Savannah 0517 0504 1307 2328

3907 2747

0547 0582 3154

4283 3136

3957 2691

5404 3405

4719 3305

Rainforest 382 0203 2647 3232 2363MangroveSwamp 170 0157 1304 1631 1252

Sources Federal Ministry of Agriculture and Rural Development (FMARD)FAOSTAT data 2005 and 2015 World Bank NBS Annual abstract of statistics (various issues)Central Bank of Nigeria - Statistical Bulletin (various issues) Federal Ministry of Finance (Budget office)Authorsrsquo computation based on data from SPARC (2014) Based on data from Federal Ministry of Agriculture and Rural Development and State Ministries (1981-2014)Notes aggregate value for the scenarios considered

Regression estimates of the determinants of agricultural production in the Agro-ecological zones of

Nigeria

Three-stage least squares regressions results were presented in tables 4 and 5 where analysis were done in

phases firstly by means of the joint total sample and then separately for the four agro-ecological zones

Analysis was based on the data provided to actualized equations 2 and 3 on agricultural outputs and other

factors influencing public investment that motivate enterprise growth in Agriculture like infrastructures

(good farm access roads storage facilities) education health care facilities Table 4 Three-stage least squares regression estimates of the determinants of agricultural

production in Nigeria (Equation 2 Ln TOAGRk) using aggregate public agricultural expenditures

Explanatory variables Total Sample

Agro-ecological zoneMarginal Savannah

Derived Savannah

Rainforest Zone

MangroveSwamp Zone

Total value of agricultural output per capita of a householdLn TOAGR 0037 0015 0006 0312 -0436Public Capital expenditure in agriculture Ln PUEXPT (i) developmental expenditures and (ii) recurrent expenditures

02510712

00440682

03280841

0427-0735

-0512 -0438

Ln FACDEVAccess farm roads (i) Good farm access roads (ii) Moderate farm access (iii) Poor farm access roads

000403820885

006200610993

009206390841

0037 0839-0382

0731 0829 -0751

Education (i) No formal education (ii) Completed primary school (iii) Completed secondary school (iv) Post-secondary attemptcompleted

-00716 0071 0005 0000

0917009100180010

0310085200310049

0082 0554 0001 0000

0904 0628 0048 0006

Access to health care (i) 10ndash30 minutes (ii) 31ndash45 minutes (iii) 46 minutes or more

-00716 0071 0005

091700910018

031008520031

0082 0554 0001

0904 0628 0048

SOCIOXT (i) Gender of head Dummy variable for head of household 0=female 1=male(ii) Ln Household size(iii) Ln Age of head Age of household head (years)(iv) Adult labour Proportion of members aged 18 to 64 (v) Male labour Proportion of members that are male(vi) Female labour Proportion of members that are male(vii) Ln Employment Proportion of members employed

0028-0002-0028 0006 00911 0583 0004

0082009100480027008200730007

0175085200730076006302790028

0098 0554 0008 0005 0492 0048 0059

0497 0628 0937 0184 0739 0078 0066

Agro-ecological zonesPublic expenditures on agricultureAgriculture contribution to GDP

0005 0000

00180000

00270001

0073 0004

0846 0732

Intercept Model estimation statistics(i) Chi-square (ii) R-square Number of observations Model identification test (exclusion restriction)Hansenrsquos J chi-square statistic

190207 0371

428930282

631040341

310730258

29461 0225

Notes See Table 2 for a detailed description of the variables All continuous variables are transformed by natural logarithm which is indicated by Ln and means that the coefficient is statistically significant at the 10 percent 5 percent or 1 percent level respectively

Table 5 Three-stage least squares regression estimates of the determinants of agricultural production in Nigeria (Equation 3 Ln FACDEVp) using aggregate public agricultural expenditures

Derived Savannah

Rainforest Zone

MangroveSwamp Zone

Ln PUEXP (i) developmental expenditures and (ii) recurrent expenditures

0005-00301

004000714

004100649

0062-0021

-0942 -0007

Ln Access farm roads (i) Good farm access roads (ii) Moderate farm access (iii) Poor farm access roads

00230016-0062

007500320617

002900620153

0713 0912-0032

0615 0814 -0077

-005 0034 000 000

0013008300010000

0418040100040000

0995 0703 0000 0000

-0043 0001 0010 0000

Access to health care (i) 10ndash30 minutes 0003 0044 0005 0013 0037

(ii) 31ndash45 minutes (iii) 46 minutes or more

0031-003

0084-0038

0852-0048

0930 -0008

0111 -0017

SOCIOXT (i) Gender of head(ii) Ln Household size(iii) Ln Age of head Age of household head (years)(iv) Adult labour Proportion of members aged 18 to 64 (v) Employment Proportion of members employedIncome diversificationstrategy(i) Subsistence farming only (ii) Subsistence farming + Market-oriented crops (iii) Subsistence farming + Non-farm activity (iv) Semi commercial farming + Non-farm activity

001400000084 009 0927 0048 00800080001

00150000001700470187

0946001000040002

00080005002700000672

0074000000000004

0042 0006 0003 0018 0816 0007 0006 0006 0027

0067 0910 -0025 0837 0328 0729 0071 0067 0927

Intercept Model estimation statisticsChi-square R-square Number of observations

628106 0574

2800140497

4320910503

3006160417

110452 0389

Tables 4 and 5 clearly indicated the significant role public spending played in agricultural outputs and

factors influencing agricultural productivity Public spending on agricultural sector (1981-2010) had

significant and positive impact on agricultural outputs Model r-square of 523 indicated a moderately fit

by the explanatory variables considered in the model Moreover most of the variables considered had their

explanatory variables coefficients statistically significant at the 10 percent 5 percent or 1 percent level

respectively

Public agricultural spending and marginal agricultural productivity effects

Regression estimates of the drivers of agricultural public expenditures in Nigeria were presented in table 6

Model fit indicators revealed R2 of 054 which is 54 of the independent variables considered explained the

model Access to moderate farm road variable was significant at 1 and access to primary school education

completed variable significant at 5 but negative (-0041) Nonetheless access to education variable

significant at 0007 at 1 level Suggesting that a 1 increase in agricultural public expenditure is

associated with a 0007 increase in the value of agricultural production per capita Also access to health

within 15-45 minutesrsquo walk to health facility was significant

Regression estimates of the drivers of agricultural public expenditures in Nigeria (Equation 4 Ln PUEXPT)

was presented in table 6 Moderate access to farm roads was significant and positive (for capital

expenditures) but insignificant for recurrent expenditures Suggesting that poor access to farm roads

contributed negatively to agricultural productivity In addition secondary school education completed or

above variables were significant factors enhancing human development which translates to productivity

Access to health care variable (where majority could walk to health facilities center at most 45 minutes)

revealed a positive significance whereas walking for more than 45 minutes revealed a negative impacts 16

Meanwhile improved spending on health and rural roads independently could motivate better agricultural

productivity

The expectation that public agricultural spending would influenced agricultural outputs raised concerns

Past studies have indicated that public spending on the agricultural sector in the recent past years has not

translated to significant and corresponding agricultural outputs (Manyong et al 2005 Mongues et al 2008)

This is reflected in results of the marginal effect The marginal effects result indicated 0028 which is

significant and positive (Table 6) This implies that a 1 increase in agricultural public expenditure is

associated with a 0023 increase in the value of agricultural production per capita As expected there

exists a low government capital-recurrent expenditure ratio in the sector (which is less than 20 percent)

Table 6 Ordinary least squares regression estimates of the drivers of agricultural public expenditures in Nigeria (Equation 4 Ln PUEXPT) using aggregate public agricultural expenditures

Explanatory variables PUEXPTotal PUEXPcapital exp PUEXPrecurrent exp

DRIVERSLn Access farm roads (i) Good farm access roads (ii) Moderate farm access (iii) Poor farm access roads

00450067-0072

00320082-0062

03260824-0007

0842-004100710000

0518 0619 0043 0000

0739061800420007

00030036-0033

0007 0052-0025

00250839-0046

SOCIOXT Ln Population Ln Proportion of households living below poverty line Ln Total land area Ln Farm size Acres of farmland Ln Livestock assets Ln Value of crop production equipment Ln of population with agriculture as main activity

0583 0937 0617 0056 0038 0052-0071

0618 0738 0613 0043 0017 0048 0005

0528-0045 0816-0068 0062-0082-0083

Agro-ecological zones(i) MarginalShort grass Savannah(ii) DerivedWoodland and Long grass Savannah(iii) Rainforest(iv) MangroveSwamp

0006000200320069

0000000000150052

0835 0628-0081-0095

Intercept R-squareNumber of observations F-test statistic

6045052585009717

5015047385008205

4927062085007417

Marginal effects (elasticities) of public expenditures on agricultural productivity in Nigeria

Literature has deduced that the elasticities represent percentage change in the value of agricultural

production per capita due to a 1 increase in the public investment variable Table 7 presented the marginal

effects of increase in public spendinginvestment on change in value of agricultural production per capita on

education access to farm roads and access to health care The assessed effect of public spending on the

value of agricultural production per capita fluctuates substantially across the four agro-ecological zones

considered Marginal effect of the analysis of overall spending revealed positive and statistically significant

across the four zones The marginal effects of the outcome of PUEXPCE was insignificance only on

mangroveswamp zone but significant in the other agro-ecological zones with elasticities of 0782 0041

0042 and 035 in mangrove savannah derived savannah rainforest and mangroveswamp zones

respectively (table 7) Access to education access to farm roads and access to health care variables all

played a significant and positive role in enhancing agricultural productivity However there were few

exception particularly variable PUEXPRE on access to farm roads The resultants effect of the insignificance

of PUEXPRE in the mangroveswamp zone was due to the neutralizing negative effects associated with the

recurrent spending In addition recurrent expenditure was negative and significance in the rainforest zone

due to the response of the variable as an exclusive driver of positive agricultural productivity (table 7)

Table 7 Marginal effects (elasticities) of public expenditures in Nigeria

Derived Savannah

Rainforest Zone

MangroveSwamp Zone

Agriculture PUEXPTN

PUEXPCE

PUEXPRE

00260018-0047

00140035-0028

001700420037

00370041-0031

007107820419

EducationPUEXPTN

PUEXPCE

PUEXPRE

006400770006

009200620011

008400330025

002500800062

062605060371

Access farm roads PUEXPTN

PUEXPCE

PUEXPRE

00040007-0024

00020005-0017

000900020047

00640048-0062

000108170502

Access to health care PUEXPTN

PUEXPCE

PUEXPRE

000800070219

000100020772

000000020618

000000000529

000400210916

Notes Authorsrsquo calculations based on Tables 9-13 and equations and (4) (4) and (9)Estimate is statistically significant at the 10 percent 5 percent or 1 percent level respectively

Public spending on education health and farm access roads in Nigeria

Public spending on indicators enhancing agricultural productivity like education health care and standard

farm roads access revealed a decisive links in terms of volume and outputs Table 8 indicated that public

funding on these variables have witnessed increase over the years Examination on the volumes of public

spendinginvestment on these factors revealed that education got estimates 58-65 access to health care

received estimates 28-34 while access to farm roads estimate 2-5 respectively Appropriating these

volumes on agro-ecological zones indicated that marginal savannah derived savannah rainforest and

mangrove swamp received estimates 27-29 25-27 22-24 and 4-6 respectively (Table 8)

Table 8 Public spending on education health and farm access roads in Major Agro-ecological zone in Nigeria

Derived Savannah

Rainforest Zone

Mangrove Swamp Zone

1981-1985Education Health careFarm access roads

N Million 19445 9936 759

N Million 5451 2785 213

N Million 5058 2584 197

N Million 4521 2310 176

N Million 4415 2250 173

147223 33485 5598

41267 9362 1569

38293 8709 1456

32404 7785 1302

35259 7629 1271

550183 201093 51667

154216 56366 14482

143081 52280 13439

124947 45668 11734

123439 46779 12012

2830129 870279 721971

736117 243939 187785

793285 206689 204386

642722 197640 202224

658005 222011 127576

68905703765574 521961

1602058 875496 146306

1792237 855162 118537

1931427 1055490 137603

1564848 979426 119515

44354192 9120277 1664571

10072837 2071215 466579

10312350 2120464 432955

11536525 2372184 387013

12432480 2556414 378024

354603020141960 1882561

8053034 4465473 527682

8244520 4683006 489654

9223224 5238924 437695

9939522 5754557 427530

Sources Authorsrsquo calculation based on data from the Budget office of the Federal ministry of finance and Statistical Bulletin (various issues)

Marginal cost of public services and agricultural productivity

Literatures have revealed that public spending on infrastructural development and provision of basic

amenities like access to good roads and primary health is sine qua non to development hence evaluating

requisite cost that would achieve this purpose is significant Hence to estimate marginal returns to public

spending on these indicators require accessing information on the unit cost of providing the relevant public

capital that will be required to at least achieve the objective noticeably Evaluating the financial implication

of how much it would cost to educate majority of Nigerians to attend at least primary school age is to assess

various channels that could facilitate attendance and knowledge impartation Like provision of primary

school institution closer to the people adequate teachers and motivation of teachers to provide quality

teaching among others Hence financial implication was thus estimated based on these criteria (table 9)

Data were sourced from the Federal Ministry of education non-governmental agencies and other sources

and used to calculate average annual spending on public institution and then divided by the total number of

pupilsrsquo enrollment in the corresponding educational system Hence the estimated (on the average) annual

cost to do this was calculated to be N12 55000 ($3486) for primary school pupils over the years under

consideration This was then multiplied by the number of people corresponding to 1 increase in the

proportion of the population that have completed at least primary education to arrive at the marginal cost

(Table 9) The question arises can this cost enhanced human capital development

Data on access to health care were sourced through numerous outlets to estimate marginal cost Several

approaches had been used by past studies Benin et al (2009) estimated the average unit cost from previous

investments where the accrued public capital stock is divided by total expenditure over several years but

for this study lack of chronological data on public expenditures makes the use of this approach rather

difficult Also using the actual cost of building one unit of public capital under present conditions is quite

tedious (Fan et al 2000) Due to data availability the study modified the two approaches Firstly data were

sourced for to calculate the average annual spending on provision of health facilities and second access to

health care services by majority of Nigerian These steps enabled the study to source for data on proportion

of households living within 45 minutes of a health facilities and number of people that have

moderatequality access to health care For example access will improve when people themselves move

closer to an existing facility or service or when they invest in ways to reach the facility for prompt service

Following this deduction the study sourced data on this and estimated the total number of households that

lived within 45 minutes of a health facility and number of people visited these facilities for their health

concerns This total number of households was divided by the number of years under consideration to get

the average annual change of number of households living within 45 minutes of a health center Therefore

the study estimated the average annual cost of providing public health services by the Federal Ministry of

Health to be N6800600 ($18891) (this just an estimate) and divided by the number of households living

within 45 minutes of health facility To obtain the marginal cost the unit cost of one household member

within 15-45 minutesrsquo walk to a health facility to obtain quality health services was then multiplied by the

number of people that accessed these facilities (Table 9)

Table 9 Marginal (one percent increase in) stock and costs of public expenditures (1981-2014)

Derived Savannah

Rainforest Zone

Mangrove Swamp Zone

Education (N Billion)Marginal stock (population completedat least primary education) No in of the populationMarginal cost () (N Billion)

6567 1230

20665 3817 304

5648 325

8972 249

7829 183

Access to health care (N Billion)Marginal stock (households within 45minutesrsquo walk to health center) No in Marginal cost () (N Billion)

3674 3753

2816 1216

3328 1078

4726 712

3826 485

Access farm roads (N Billion)Marginal stock (farm access of km per sq km) No in Marginal cost () (N Billion)

4849 6277 2154

1345 8106 1215

1261 7292 790

1178 5836 305

1005 3872 170

Sources wwwepdcorgNigeria_coreusaid wwwibeunescoorg wwwnigerianstatgovngnadaindexphpcatalog27wwwpopulationgovng United Nations Population Division and Statistics Division United Nations Educational Scientific and Cultural Organisation UNESCO Institute for Statistique EFA Global Monitoring Report United Nations Development Programme World Bank Food and Agriculture Organisation of the United Nations httpwwwfmegovngorg httpwwwibeunescoorglinkshtmFederal Ministry of Education Country report of Nigeria International Conference on Education 47th session Geneva 2004 Federal Ministry of Health 2017 Health care Trends in Nigeria amp Impact on the West African Region Blue print presentation by Honorable Minister of Health Professor IF Adewole to the Federal GovernmentAdegbola SA (1979) An Agricultural Atlas of Nigeria Oxford University Press OxfordFAO 1993 Agriculture Towards 2010 Rome Italy Oyenuga VA (1967) Agriculture in Nigeria Food and Agriculture Organization of the United Nations) FAO Rome Italy 308 pp World Factbook 2016 National Bureau of Statistics Nigeria Country PastureForage Resource Profiles Annual Abstract of Statistics (various issues)Notes Marginal cost was calculated by estimating the actual number of population of the marginal

stock in the overall population and then multiplied it with the unit cost

Similarly estimating marginal stock (farm access of km per sq km in ) of people that have access to good

farm roads was estimated by calculating how much it would cost to build one kilometer of rural road and

number of people that have access to these roads To obtain the marginal cost concerning access to farm

roads total length of feeder roads was multiplied by the number of kilometers of road corresponding to a 1

increase in the total length of roads to obtain the marginal cost Hence this gave an estimated unit cost of

N23 60200 ($6556) (estimate) (Table 9) These marginal costs are then divided by their respective

marginal effects to obtain estimated marginal returns

Public investments and marginal agricultural productivity returns in Nigeria

Past studies have argued that effective and consistent public spendinginvestment on factors that enhanced

agricultural productivity is sine-qua non to development Hence estimating the marginal costs and marginal

effects on agricultural productivity is significant results of this analysis is presented in Table 10 Tables 7-9

presented estimates of marginal cost and the marginal effects that were used for the estimate

Table 10 Marginal agricultural productivity returns to public investments in Nigeria

Derived Savannah

Rainforest Zone

MangroveSwamp Zone

Agriculture 1297 805 708 592 205Education 303 191 134 082 042Access to health care 514 302 261 163 171Access farm roads 503 306 291 -235 -082

Marginal effects were derived using tables 4-5 as guide and presented in Table 7 The study computed the

marginal cost by estimating the actual number of population of the marginal stock in the overall population

and then multiplied it with the unit cost (table 9) Hence marginal cost and marginal effects were then used

to evaluate the marginal agricultural productivity returns to the different types of public investments on the

four agro-ecological zones as displayed in equations (7) and (8) The results of this outcomes were

presented in table 10 Results revealed that significant budget were appropriated to these indicators of

agricultural development and returns were disproportionate (Table 10) For the years under consideration

the country had invested over N7137 billion and marginal Nigerian Naira (N) invested in the agricultural

sector N1297 in terms of total value of agricultural production is returned Surprisingly on drivers of

agricultural productivity recorded a low marginal Naira invested on these indicators and its returns For

instance education N303 access to health care N 514 and access to farm roads N 503 Although these

indicators are significant and positive but according to World indicators it is very low Results of the

agricultural productivity returns to access to farm roads indicated a negative in the rainforest and

mangroversquos swamp zones which suggest that vegetation in these zones hardly created smooth access to

agricultural activities especially extension services (Kareem et al 2015) The estimated marginal returns to

the different types of public investments differ among the four agro-ecological zones The marginal returns

to agricultural spending are highest in the marginal and derived savannah zones followed by the rainforest

zone (table 10) Marginal returns to public spending on the education is highest followed by health sector

and access to farm roads

Policy implications of major findings

Research on causality between public spendingexpenditures and agricultural growth in Nigeria using a large

pool of data base (1981-2014) have been sparsely no research (to the knowledge of researcher) have

examined agricultural productivity returns to public spending across major agro-ecological zones of Nigeria

(1981-2014) Thus the paper examined empirical linkages between public spending and agricultural growth

Reviewed of past studies on similar experiences around the world has helped to facilitate the conceptual

framework adopted for this work Literature have indicated that in Nigeria 53 of the population is rural

70 of the poor live in rural areas deriving livelihood from agriculture and agricultural related activities

Hence improving welfare of majority of Nigerians agricultural activities must be significantly improved

The level of public spending in agriculture in Nigeria remains low regardless of the indicator used

Agricultural spending as a share of total public spending averaged 488 percent between 1981 and 2014 but

marginalshort grass savanna agro-ecological zone took the highest (732) while mangroveswamp agro-

ecological zone took 239 Budgetary allocation to agriculture compared with other key sectors is also low

economic development Agriculture contribution to GDP () from 1981- 2014 averaged 3270 while total

ecological zones respectively In this regards intervention in local and foreign direct investments in public

spending to agriculture showed 6347 7651 8034 and 7469 in marginalshort grass savanna

derivedwoodland long grass savannah rainforest and mangroveswamp agro-ecological zones respectively

This finding corroborated by Mongues et al (2008) and Manyong et al 2005 that acknowledged the role

these intervention agencies played in agricultural development in Nigeria

Public expenditures in agriculture in Ghana averaged 35-69 in 1995-2005 likewise in Kenya (65-75)

Uganda (3-10) In Uganda developmentcapital spending reliably accounts for around 15 of total sector

spending leaving 85 of the budget allocated to recurrent costs but non-government spending like donors

agencies have traditionally provided the majority of funding for developmentcapital spending (Otsuka and

Hayami 1988 OPM 2005 Makhtar 2017) Recurrent expenditures (personnel emoluments and general

administration) took 70 to 80 in Ghana and in Kenya 69 Intervention funding (such as donor) ie non-

government funding in agriculture (both local and direct investment) in Ghana is between 591-735 and

Kenya 62-83 (OPM 2005) Moreover in Asia public spending in agriculture revealed that China India

and Thailand allocated 10-15 of the state budget to agriculture with capital expenditure accounts for 75

of spending only 25 of the budget for salaries operations and maintenance These countries witnessed

higher return to agricultural productivity However some countries in Asia that earmarked poor funding to

agricultural sector like Vietnam which allocated 5-6 of total government spending to agricultural sector

beheld poor agricultural development (Fan et al 2000) South America experience revealed that in

Argentina Costa Rica Dominican Republic Honduras Panama Paraguay Peru Venezuela Ecuador and

Uruguay public funding to agriculture is more or less equally shared between the national government and

the provincial plus municipal governments Most national agricultural expenditure occurs through a series of

semi-autonomous government agencies While national government allocated 4-6 the

provincialmunicipal governments apportioned between 65-84 (Wu et al 2010) Evidence from the

regressions results of this study revealed positive and significant role public spending played in agricultural 23

outputs and factors influencing agricultural productivity This thus suggest that effective public spending in

agricultural development play a significant role Moreover agricultural expenditure intensity in Nigeria and

developing countries is extremely low (less than 5) whereas developed countries usually have an intensity

of more than 20

Past studies have argued that public spending on rural roads and rural education also has significant effects

on agricultural growth and poverty reduction although the effects are noticeably varied across regionsagro-

ecological zones within the same country Regression results on variable access to moderate farm roads was

significant at 1 level access to primary school education completed variable was significant at 5 but

negative (-0041) Nonetheless access to education variables were significant at 0007 at 1 level This

means that a 1 increase in agricultural public expenditure is associated with a 0007 increase in the value

of agricultural production per capita Also access to health within 15-45 minutesrsquo walk to health facility was

significant Public agricultural spending tends to be better in districts with moderate access to farm roads

while poor access to farm roads recorded a negative significance Thus suggesting that poor access to farm

roads contributed negatively to agricultural productivity In addition variables of secondary school

education completed and above is a significant factor enhancing human capital development which

translates to productivity Variable access to health care where majority could walk to health facilities center

at most 45 minutes revealed a positive significance whereas walking for more than 45 minutes revealed a

negative impacts Meanwhile improved spending on health and rural roads independently could motivate

better agricultural productivity Hence the outcomes of this study thus suggest that harmonizing amid

quality spending on access to health education and rural roads can enhanced agricultural productivity

The marginal returns to spending on rural education in Ghana was negative suggesting that the formal

education system has not benefited the agricultural sector there because better-educated and skilled farmers

tend to move away from farms leaving the less skilled in the agricultural sector (Benin et al 2009) In

Ethiopia Uganda and Tanzania the growth returns to spending on roads were positive because itrsquos enhanced

agricultural productivity (Mongues et al 2008) In addition the marginal effect of education in Nigeria was

positive (although insignificant) in the savannah zones suggesting that people with high education also

work on the farm This is supported by the positive and significant direct effect of secondary education or

greater on agricultural productivity in the zone and is coherent with the findings of Mongues et al 2008 and

Benin et al (2009) Also positive effect linked with better access to health services holds universally

hence inclusive access to health services enhanced productivity Concerning access to farm roads the effect

was significant and positive

Past studies have indicated that public spending in the agricultural sector in the recent past years has not 24

translated to significant and corresponding agricultural outputs in developing countries This is reflected in

the results of the marginal effect The marginal effects result indicated 0028 which is significant and

positive The implication of this finding is that a 1 increase in agricultural public expenditure is associated

with a 0023 increase in the value of agricultural production per capita As expected there exists a low

government capital-recurrent expenditure ratio in the sector (which is less than 20 percent) this reverberates

the detail that taking care of overhead costs administrative costs and other overheads is unlikely to yield any

functional outcomes this is most dominant in all parastatal of agricultural ministries and agencies in

Nigeria

Similarly marginal returns to spending on health has influenced agricultural productivity Past studies have

indicated that quality public spending on education health and infrastructures (like well-organized access to

farm roads) have contributed substantially to agricultural growth and poverty reduction in developed

countries (Fan et al 2008) Where health and educational sector took 86-103 and 276-28 in advance

countries but less that 5 in Nigeria and in most developing countries Consequently African governments

must increase public spending in agriculture education health and rural roads this is because the vast

majority of the poor reside in rural areas and depend on agriculture for their livelihoods

Education spending is the largest among all sectoral government expenditures in Asia at $87 per person

Sub-Saharan Africa (SSA) recorded $12-14 per person South America $45-52 per person respectively

Moreover SSA countries spent on the averaged a meager $11 per capita for agriculture and $8 for

infrastructure in 2007-2013 (Ojiako et al 2016) In Nigeria the study indicated that about $8 per person to

acquire minimum education (at least primary education) Hence public spending in educational sector in

Nigeria was low compared to other countries In Asia South-America and other developed countries

indicated that educational sector received priority in resource allocation with 16 of the total government

budget being dedicated to educational-related activities In Nigeria less than 9 was allocated to education

less than 7 of the budget was allocated to health expenditures on health-related activities year under the

year in review

The marginal effect of the analysis of overall spending revealed positive and statistically significant across

the four zones The marginal effects of the outcome of PUEXPCE was insignificance only on

respectively Variables education access to farm roads and access to health care all played a significant and

positive role in enhancing agricultural productivity However there were few exception particularly

variable PUEXPRE on access to farm roads The resultants effect of the insignificance of PUEXPRE in the

mangroveswamp zone is due to the neutralizing negative effects associated with the recurrent spending 25

Conclusions

The study established significant causality between public spending and agricultural growth however size

quality of spending and appropriation of fund to capital spending than recurrent expenditure play a

significant role Also results from the regression analyses established significant causality it could be

positive or negative depending on the government schemes Public spending on education access to health

services and rural roads enhanced agricultural productivity and reduced poverty

The study revealed that public spending can be effectively used to stimulate economic growth and enhanced

agricultural productivity However the size and channel of distributions by different governments make the

difference in agricultural productivity enhancement Thus African governments need to increase quality

spending on agriculture and rural roads direct complementary spending to certain sectors such as education

and health Unfortunately rising government spending has not translated to meaningful growth and poverty

reduction as Nigeria ranks among the poorest countries in the world In addition many Nigerians have

continued to wallow in abject poverty while more than 50 percent live on less than US$2 per day Couple

with this is dilapidated infrastructure (especially roads and power supply) that has led to the collapse of

many industries

Important drivers of economic development indicators like access to quality health care facilities education

and ruralfarm roads influenced agricultural productivity In Nigeria these drivers were not effectively

motivated and were poorly funded In addition low budget appropriated to agriculture in the years under

review was low Hence the study recommends that governments should improve on the existing public

expenditure in agriculture and drivers of economic development indicators to make agricultural productivity

returns effective Also government must put in place a comprehensive monitoring and evaluation system

that will enable the government to assess the effect of its grants programs

References

Alexiou C (2009) Government Spending and Economic Growth Econometric Evidence from

the South Eastern Europe (SEE) Journal of Economic and Social Research 11(1) 1ndash16

Alshahrani S A Alsadiq A J (2014) Economic Growth and Government Spending in Saudi

Arabia an Empirical Investigation IMF Working Papers 14(3) 1-38

Anisimova E (2016) Public expenditure in agriculture trends ldquoblack boxesrdquo and more

International food policy research institute (IFPRI) publication

Ansari MI Gordon DV Akuamoah C (1997) Keynes versus Wagner public expenditure and

National income for three African countries Applied Economics 29543-550

Arndt C Pauw K and Thurlow J (2015) ldquoThe Economy-wide Impacts and Risks of Malawirsquos Farm Input

Subsidy Programrdquo American Journal of Agricultural Economics 98 (3) 962ndash980Aparajita G and John N (2017) Reaping Richer Returns Public Spending Priorities for African

Agriculture Productivity Growth A copublication of the Agence Franccedilaise de Deacuteveloppement and the World Bank

Aschauer D (2000) Public Capital and Economic Growth Issues of Quantity Finance and Efficiencylsquo Economic Development and Cultural Change 48 (2) 391ndash406

Attari M I Javed A Y (2013) Inflation Economic Growth and Government Expenditure

of Pakistan 1980-2010 Procedia Economics and Finance 5 58ndash67

Benin S Mogues T Cudjoe G Randriamamonjy J (2009) Public Expenditures and Agricultural

Productivity Growth in Ghana Contributed Paper IAAE Beijing 2009

Breisinger C Diao X Thurlow J Al-Hassan RM (2008) Agriculture for Development

in Ghana New Opportunities and Challenges Regional Strategic Analysis and Knowledge

Support System ReSAKSS Working Paper No 16 November 2008

Central Bank of Nigeria (CBN) (2016) Statistical Bulletin

Diao X S Fan S Kanyarukiga B (2010) Agricultural Growth and Investment Options for Poverty

Reduction in Rwanda IFPRI Research Monograph Washington DC International Food

Policy Research Institute

Emerenini F M Ihugba O A (2014) ldquoNigerians total government expenditure its relationship with

economic growth (1980-2012)rdquo Mediterranean Journal of Social Sciences 5(17) 36-47

Fan S Hazell P Thorat S (2000) Government Spending Agricultural Growth and Poverty Reduction in

India American Journal of African Economics 5(4) 133-165

Fan S Zhang X (2008) ldquoPublic Expenditure Growth and Poverty Reduction in Rural Ugandardquo

African Development Review 20 (3) 466ndash496

Ghura D (1995) ldquoMacro policies external forces and economic growth in Sub-Saharan Africardquo

Economic

Development and Cultural Change 43(4) 759-78

Greene WH (1993) Econometric analysis New York USA Macmillan Publishing Company

Guseh J S (1997) Government Size and Economic Growth in Developing Countries A Political-

Economy Framework Journal of Macroeconomics 19(1) 175ndash192

Hsieh E Lai K (1994) Government Spending and Economic Growth The G-7 Experience

Journal of Applied Economics 26 535ndash 542

Karamba R W and Winters P (2015) ldquoGender and Agricultural Productivity Implications of the Farm Input Subsidy Program in Malawirdquo Agricultural Economics 46 (3) 357ndash74

Kareem R O Bakare H A Ademoyewa G R Ologunla S E Arije A R (2015) Nexus between

Federal Government Spending on Agriculture Agricultural Output Response and Economic Growth

of Nigeria (1979-2013) American Journal of Business Economics and Management 3(6)359ndash366

Knoop T A (1999) ldquoGrowth welfare and the size of governmentrdquo Journal of Economic Inquiry 37(1)

103-119Makhtar D(2017) Efficiency of Public Spending will Enhance Agriculture Productivity for

Poverty Reduction in Africa World Bank publicationManyong VMIkpi A Olayemi JYusuf S Omonona B Okoruwa V Idachaba F (2005)

Agriculture in Nigeria Identifying opportunities for increased commercialization and investment

International Institute of Tropical Agriculture (IITA) Ibadan Nigeria

Mogues T Morris M Freinkman L Adubi A Ehui S Nwoko C Taiwo O Nege C Okonji P

Chete L (2008) Agricultural Public Spending in Nigeria IFPRI Discussion Paper 00789

September

Ojiako F Chianu F Johm K Ojukwu C (2016) Drivers of human capital development an analysis

of primary and secondary education outcomes in Nigeria International journal of current research

8(6) 3285-3229

Otsuka K Hayami Y (1988) Theories of share tenancy A critical survey Economic

Development and Cultural Change 37(1)31-68

Oxford Policy Management (2005) A Joint Evaluation of Ugandarsquos Plan for the Modernization

of Agriculture

Takeshima H and Liverpool-Tasie L(2015) ldquoFertilizer Subsidies Political Influence and Local Food Prices in Sub-Saharan Africa Evidence from Nigeriardquo Food Policy 54 11ndash24

Wagner A (1893) ldquoGrundlegung der politischen okonomie (3rd ed)rdquo Leipzig C F Winter

Wu S-Y Tang J-H Lin E S (2010) The Impact of Government Expenditure on Economic

Growth How Sensitive to the Level of Development Journal of Policy Modeling 32(6) 34-45

Yasin M (2000) Public Spending and Economic Growth Empirical Investigation of Sub-Saharan

Africa Southwestern Economic Review 4(1) 59ndash68

Zhang X and S Fan 2004 ldquoPublic Investment and Regional Inequality in Rural Chinardquo

Agricultural Economics 30 (2) 89ndash100

2402

3421

2281

2982

4505

5215

4129

4803

3507

4259

1785

2546

3232


Subsidy Programrdquo American Journal of Agricultural Economics 98 (3) 962ndash980

Aparajita G and John N (2017) Reaping Richer Returns Public Spending Priorities for African

Agriculture Productivity Growth A copublication of the Agence Franccedilaise de

Deacuteveloppement and the World Bank

Aschauer D (2000) Public Capital and Economic Growth Issues of Quantity Finance and Efficiencylsquo

Economic Development and Cultural Change 48 (2) 391ndash406

Karamba R W and Winters P (2015) ldquoGender and Agricultural Productivity Implications

of the Farm Input Subsidy Program in Malawirdquo Agricultural Economics 46 (3) 357ndash74

Makhtar D(2017) Efficiency of Public Spending will Enhance Agriculture Productivity for

Poverty Reduction in Africa World Bank publication

Takeshima H and Liverpool-Tasie L(2015) ldquoFertilizer Subsidies Political Influence and

Local Food Prices in Sub-Saharan Africa Evidence from Nigeriardquo Food Policy 54 11ndash24