ABSTRACT
In the past 3 decades (1981-2017), the Nigerian government has set out various policies targeted at stimulating the macroeconomic variables and consequently affecting the agricultural outputs positively in the economy, but have inadequately achieved these goals. This is evidenced in the annual agricultural outputs which are always insufficient to cater to the rising population of the country. Hence, this study examined the impact of selected macroeconomic variables onNigeria’s agricultural outputs (aggregate and dis-aggregated) over the time under review(1981-2017). The Cobb-Douglas Production theory formed the theoretical framework for the study. After reviewing relevant works of literature, the suitable analytical techniques (Johansen cointegration(long-run relationship), Fully Modified OLS(FMOLS(long-run impacts) and Error Correction Model (ECM)(short-run impact)) were chosen and employed. The five (One aggregate and four disaggregated) estimated Johansen results all indicated a long-run equilibrium relationship
Furthermore, the coefficients of the FMOLS results for aggregate agricultural output, in the long run, reveals that credit and Non-oil importsaresuitable macroeconomic variables that can be used to positively and negatively impact the aggregate agricultural outputs in Nigeria respectively. In the short run, non-oil exports impact much positively with a 24.6% increase for any 10% increase
While Non-Oil Imports impact much negatively to aggregate agricultural output with -20.6% for any 10% increase. For the sub-sectors, the FMOLS results for crop production suggested credit to be a more suitable variable to use to rapidly increase the sub-sector’s outputs with a 2.07% increase to the output for a 10% increase; while Non-Oil imports can impose the most negative impact with -0.41% reduction the sub-sector’s output for any 10% increase. And in the short run, Non-oil exports impact much positively with 0.804% for any 10% increase; while non-oil imports impact much negatively to the sub-sector with -0. 8.15% for any 10% increase. Again for a quick and much positive response in fish production, in the long run, the result suggests credit be the most suitable variable with a 2.323% increase in fish output for any 10% increase; while Non-Oil exports can impose the most negative impact with -1.996% reduction of fish output for any 10% increase. And in the short run, Non-oil imports impact much positively with a 0.990% increase in fish output for any 10% increase. While non-oil export impacts much negatively with -1.013%
reduction for any 10% increase. Considering the result obtained from the FMOLS estimation for the forestry sub-sector, to achieve the quickest and positive response in forestry production, in the long run, the result suggests Non-Oil export as the most suitable variable with a 0.616% increase to the forestry output for any 10% increase; while credit can impose the most negative impact with – 0.716% reduction of forestry output for any 10% increase. In the short run, Non-oil exports impact much positively with a 0.322% increase in forest output for any 10% increase; while Non-Oil imports impact much negatively with a -0.255% reduction for any 10% increase. Finally, to achieve a fast and much positive response in livestock production, in the long run, the FMOLS result suggests labour as the most suitable variable with a 0.514% increase to the livestock output for any 10% increase; while public debt servicing can impose a quick and more negative impact on livestock output with -0.140% reduction in the output for any 10% increase. In the short run, labour impacts more positively with a 0.307% increase in the output for any 10% increase. Thus, the results obtained suggest that macroeconomic variables still affect the sector’s outputs; and practical policy recommendations by policymakers to help and rapidly boost the sector output’s growth is by helping farmers via the good provision of credit and helping them to market their produce at the international markets which can help them earn foreign currencies and thus, stimulate them to produce more and consequently lead to expansion of the whole sector vis-à-vis the Nigerian economy
TABLE OF CONTENTS
Page
Title Page ————————————————————————————————— i
Declaration————————————————————————————————— ii
Certification————————————————————————————————– iii
Dedication—————————————————————————————————- iv
Acknowledgement ——————————————————————————————- v
Abstract ——————————————————————————————————- vi
Table of Contents ——————————————————————————————- vii
List of Tables ————————————————————————————————- x
List of Figures ———————————————————————————————— xii
List of Abbreviations and Acronyms ——————————————————————— xiii
CHAPTER ONE
GENERAL INTRODUCTION
1.1 Background of the Study ——————————————————————————– 1
1.2 Problem of the Study ———————————————————————————— 4
1.3 Research Questions ————————————————————————————– 7
1.4 Research Objectives ————————————————————————————- 8
1.5 Justification of the Study ——————————————————————————– 8
1.6 Scope of the Study—————————————————————————————- 10
1.7 Organization of the Work ——————————————————————————- 11
viii
CHAPTER TWO—————————————————————————————— 12
LITERATURE REVIEW ———————————————————————————- 12
2.0 Introduction ——————————————————————————————— 12
2.1 Conceptual Literature ——————————————————————————– 12
2.1.1 Agricultural Output ————————————————————————— 12
2.1.2Macroeconomic Variables——————————————————————- 14
2.2 Theoretical Literature Review———————————————————————– 17
2.2.1 Stylised Facts———————————————————————————– 21
2.2.1.1Why Nigeria Needs to Focus More on Agricultural Sector ————————– 22
2.2.1.2Why Nigeria‘s Agricultural Sector is not Yielding Optimum Output ————— 24
2.2.1.3Review of Some Previous Reforms in the Sector (1981– 2020)——————- 27
2.3Empirical Literature Review ————————————————————————- 30
2.6 Gaps Identified from the literature reviewed——————————————————- 33
CHAPTER THREE ————————————————————————————- 35
RESEARCH METHODOLOGY ———————————————————————– 35
3.0 Introduction ——————————————————————————————- 35
3.1 Theoretical Framework——————————————————————————- 35
3.2 Empirical Model Specification———————————————————————- 38
3.3 Apriori Expectation———————————————————————————– 39
3.4 Estimation Techniques——————————————————————————- 40
3.4.1.1 Stationarity Test————————————————————————- 40
3.4.1.2 The Johansen Cointegration Test—————————————————— 41
ix
3.4.1.3 Fully Modified Ordinary Least Squares (FMOLS)——————————— 43
3.4.1.4 Error Correction Mechanism (ECM) ———————————————– 44
3.5 Sources of Data ————————————————————————————– 45
CHAPTER FOUR ————————————————————————————— 46
DATA PRESENTATION, INTERPRETATION AND ANALYSES OF RESULTS———– 46
4.0 Introduction ——————————————————————————————– 46
4.1 The trend of Agricultural Sector‘s Output And Some Macroeconomic Variables In Nigeria 46
4.1.1 The Relative Share Of Agricultural Output in the Nigerian Economy————— 46
4.1.2 Share of Agricultural output and Inflation ———————————————- 48
4.1.3 Share of Agricultural Output and Interest Rate.(Maximum Lending Rate) ——– 49
4.1.4 Share of Agricultural Output and Public Debt —————————————– 50
4.1.5 Share of Agricultural Output and Credit Availability (ACGFS) ——————– 52
4.2 Descriptive Statistics———————————————————————————- 52
4.3 Stationarity Test————————————————————————————— 54
4.4 Johansen Cointegration test for the five equations———————————————— 55
4.5 The FMOLS, ECM and Diagnostic Tests and interpretations for Aggregate Agricultural
Output Equation. ————————————————————————————– 62
4.6 The Fully Modified OLS, ECM and Diagnostic Tests and interpretations for the Four Disaggregated
Sub-sectors of Agricultural————————————————————- 69
4.7 Key Findings——————————— ———————————————————- 86
x
CHAPTER FIVE —————————————————————————————– 90
SUMMARY, CONCLUSION AND POLICY RECOMMENDATIONS———————- 90
5.1 Summary ——————————————————————————————- 90
5.2 Conclusion —————————————————————————————– 93
5.3 Policy Recommendation ———————————————————————— 93
REFERENCES——————————————————————————————- 96
APPENDICES——————————————————————————————— 107
Appendix I Matrix table of empirical review of literature——————————————-109
LIST OF TABLES
Table 2.2 List of few earlier Studies and their theoretical Framework —————————— 17
Table 3.3 A-priori Expectations —————————————————————————— 40
Table 3.5 Sources is Data. ———————————————————————————- 45
Table 4.2.a Descriptive Statistics for the Endogenous Variables———————————– 53
Table 4.2.b Descriptive Statistics for the Exogenous Variables ———————————- 54
Table 4.3 Unit Roots Test- Phillip Perron —————————————————————- 55
Table 4.4.1 Lag Length Criteria for Aggregate Agricultural Output in Nigeria ——————— 56
Table 4.4.1.2 Johansen Cointegration Test for Aggregate Agricultural Output in Nigeria ——– 56
Table 4.4.2.1 Lag Length Criteria for Crop Production Output in Nigeria.————————– 57
Table 4.4.2.2 Johansen Cointegration Test for Crop Production Output in Nigeria ————- 57
Table 4.4.3.1 Lag Length Criteria for Fishery Production Output in Nigeria———————– 58
Table 4.4.3.2 Johansen Cointegration Test for Fishery Production Output in Nigeria ———- 59
xi
Table 4.4.4.1 Lag Length Criteria for Forestry Production Output in Nigeria——————— 59
Table 4.4.4.2 Johansen Cointegration Test for Forestry Production Output in Nigeria ———– 60
Table 4.4.5.1 Lag Length Criteria for Livestock Production Output in Nigeria——————— 61
Table 4.4.5.2 Johansen Cointegration Test for Livestock Production Output in Nigeria ———– 61
Table 4.5.1 FMOLS Result For Aggregate Agricultural Output In Nigeria.————————– 62
Table 4.5.2 Parsimonious Error Correction Model For Aggregate Agricultural Output In Nigeria. 67
Table 4.5.3 Serial Correlation Test———————————————————————– 68
Table 4.5.4 Heteroscedasticity Test ——————————————————————— 68
Table 4.6.1.1 FMOLS Result For Crop Production Output In Nigeria————————— 70
Table 4.6.1.2. Parsimonious Error Correction Model for Crop production in Nigeria ———– 72
Table 4.6.1.3 Breusch-Godfrey Serial Correlation LM Test: —————————————- 73
Table 4.6.1.4 Breusch-Pagan Heteroscedasticity Test ———————————————- 73
Table 4.6.2.1 FMOLS Result For Fishery Production Output In Nigeria ————————— 74
Table 4.6.2.2 Parsimonious Error Correction Model For Fishery Output In Nigeria ———– 76
Table 4.6.2.3 Breusch-Godfrey Serial Correlation LM Test ————————————– 76
Table 4.6.2.4 Breusch-Pagan Heteroscedasticity Test ———————————————- 77
Table 4.6.3.1 FMOLS Result For Forestry Production Output In Nigeria ———————– 78
Table 4.6.3.2. Parsimonious Error Correction Model For Forestry Output In Nigeria. ———— 80
Table 4.6.3.3 Breusch-Godfrey Serial Correlation LM Test —————————————- 81
Table 4.6.3.4 Breusch-Pagan Heteroscedasticity Test: ———————————————— 81
Table 4.6.4.1 FMOLS Result for Livestock Output in Nigeria.—————————————-` 82
Table 4.6.4.2. Parsimonious Error Correction Model. ————————————————– 84
xii
Table 4.6.4.3 Breusch-Godfrey Serial Correlation Test ———————————————— 85
Table 4.6.4.4 Breusch-Pagan heteroscedasticity Test ————————————————– 85
LIST OF FIGURES
Figure 2.2.4 Total Agricultural Output in Nigeria from 1981-2016 ———————————- 27
Figure 3.1 Variables in equation 3.1 that can affect the Total Agricultural Output in Nigeria—- 37
Figure 4.1.1 The Relative Share Of Agricultural Output To Nigeria‘s Real GDP From 1981 –
2017.———————————————————————————————————– 47
Figure 4.1.2. Showing the graphical representation of Relative Agricultural Output Share and
Inflation Rate in Nigeria from 2007 to 2017————————————————————- 48
Figure 4.1.3 Relative Contribution of Agricultural sector‘s Output Versus Interest rate. ———- 50
Figure 4.1.4 Trend analysis of Public debt servicing————————————————– 51
Figure 4.5.1 Trend analysis between agricultural output and Public debt servicing—————- 66
figure 4.5.5 The CUSUM graph for Aggregate Agricultural Output———————————- 69
Figure.4.6.1.1 Trend analysis of Crop Production and Public Debt Servicing from 1981Q1 to
2017Q4. ———————————————————————————— 71
Figure 4.6.1.5 The CUSUM graph for crop production ———————————————– 73
Figure 4.6.2.5 The CUSUM graph for fishery production ——————————————– 77
Figure 4.6.3.5 The CUSUM graph for forestry Production——————————————- 81
Figure 4.6.4.5 The CUSUM graph for livestock Production—————————————– 85
xiii
LIST OF ABBREVIATIONS AND ACRONYMS
ACGSF Agricultural Credit Guaranteed Scheme Funds
AU African Union
CAADP Comprehensive Africa Agriculture Development Programme
CBN Central Bank of Nigeria
ECM Error Correction Model
FMARD Federal Ministry of Agriculture and Rural Development
FMOLS Fully Modified Ordinary Least Squares
FAO Food and Agricultural Organisation
IFAD International Fund for Agricultural Development
NAB National Agricultural Bank
NAIC Nigerian Agricultural Insurance Corporation
NBS National Bureau of Statistics
SAP Structural Adjustment Programme
USD United State Dollar
WFP World Food Programme
CHAPTER ONE
INTRODUCTION
1.1 General Background of the Study: Macroeconomic goals in every country are to increase the general output level with a minimal level of idle labour, a constant favourable balance of payments, price stability and a good standard of living of her citizens. For any economy to achieve these goals, it must be actively involved in the high production of its basic primary and secondary needs via a good relationship between macroeconomic fundamentals and real sectors of the economy (Sloman and Wride, 2009). Sometimes this relationship can be indirect; for instance, macroeconomic variables like interest rate and investment are capable of boosting the output level of an economy by linking the money and goods markets together. Again this indirect link may take a longer time, as several channels exist through which these variables have to penetrate and adjust for the markets to arrive at equilibrium level; thereby leading to positive output growth in the economy. At equilibrium, a high possibility for positive output growth is experienced, and this affects the volume of external trades (exports and imports) whose proceeds are used for continuous increase in growth and development of other sectors‘ capacity (McConnell & Brue, 2005). The World Food Programme (WFP) understood this in 2008, as it kicked against imposing export prohibitions or restrictions on agricultural foodstuffs purchased for non-commercial purposes, with the aim of achieving zero hunger by 2030 (Action Against Hunger, 2018)
Regionally, within the Sub-Saharan countries, the report by the Food and Agricultural Organization (FAO) revealed how agricultural output has helped the countries in the region to reduce the level of poverty and food insecurity (FAO, 2009). Despite the commendation by the FAO, most countries in the region to date have not reached the desired level of food production
2 Hence, they cannot depend much on agriculture for products and export returns. This is because of poor management of some macroeconomic variables, combined with inconsistency in maintaining and adhering to good agricultural policies by some regional countries
In Asia, available information revealed that China with 35 percent of its labour force in agriculture (425million agricultural farmers), can feed 22 percent of the world‘s population based on its different agricultural produce and products which are outcomes of modern technology and good management of some macroeconomic variables1. China was able to achieve this feat because the government played a major role in building and developing the sector to its present level via sound macroeconomic policies. For instance, the government raised loan balance from $43 billion to $ 127 billion from 2002 to 2005, adopted the use of micro-loans and joint guarantee group lending programme and practiced the land leasing method of agriculture which involves giving farmers land for as long as 30 years without any product nor financial costs (Hay, 2008 and Gale & Collander, 2006). Apart from China, some other countries(the United States of America(U.S.A); in the world are economically buoyant and rich in agricultural output not based on the large labour force, but rather, they invest massively in the sector through capital and labour, and shield the sector from the negative impacts of some macroeconomic variables
In Nigeria, for the past two decades, the agricultural sector‘s output and value addition per capita have not adequately satisfied the demands of the people and the domestic industries; despite the large labour force which the sector accommodates. This could be attributed to the fast annual growth in the population of the country, while research works that have been carried out revealed 1 Agriculture is a major source of income to most Chinese, as it was stated by Lauren Keane in Washington post, China has a long standing policy of food – self – sufficiency, growing about 95% of the grains required to feed its people. Any lower output can have a negative impact on the world food supply
3 some factors like change in climate condition, other(Eyo (2008); Adama and Bobai (2010); Rebecca and Ogunbadejo (2014) among others) were of the views that macroeconomic variables like inflation, interest rate and lack of credit have been the major cause inhibiting the output growth in the agricultural sector over the years also play some part in the sector‘s inadequate outputs growth, while other studies‘ results revealed lack of public investment in the sectors as a challenge (Abel and Anoriode, 2015; Rebecca and Ogunbadejo, 2014; Sunday, Ini-Mfon, Glory, & Daniel, 2012 among others)
A report by the FAO through the Ministry of Agriculture and Rural Development (FMARD) in 2008 revealed that Nigeria lost an estimated 10 billion USD for the past 20 years due to poor post-harvest storage and inadequate value addition to produce. Furthermore, other studies by Adeoti and Sinh (2009), Anyawu and Adesope (2010) and Adesope and Okoruwa (2013) argued, that the poor performance of the agricultural sector can partly be attributed to the poor application of modern technology by most farmers which helps in adding value to the raw produce and low amount of expenditure (less than 4%) sunk into the sector which was evidenced from the National Bureau of Statistics (2018). Whereas Eyo(2008); Adama and Bobai (2010); Rebecca and Ogunbadejo (2014) among others revealed that some macroeconomic variables like inflation, interest rate and lack of credit have been the major cause inhibiting the output growth in the agricultural sector over the years(p 5,7 & 8)
Finally, Nigeria with its large heterogeneous population and abundance of fertile arable land that is suitable for the cultivation of different crops, ought to have lead other African countries if not compete at the global level in terms of good agricultural output. However, the negative effects of some macroeconomic variables (monetary and fiscal) may have deprived the country of this feat
4 Hence, there is a need to examine some of these macroeconomic variables (inflation rate, interest rate, public debts servicing, total non-oil exports and imports) to determine the nature of their impacts to correct the negative effects they may have caused in the agricultural sector. ( World Bank, 2016 and Abel & Onoriode, 2015) 1.2 Problem Of The Study: The agricultural sector in Nigeria had the largest share of the labour force and output; and was massively engaged before the discovery and exploration of oil in 1956 and 1958 respectively (Olarinde and Abdullahi, 2014). After the discovery of crude oil, the sector was relegated to the background which led to some technical challenges especially in boosting its output capacity
Thus, making the impact of government policies on the sector to be ineffective coupled with the negative impact of some macroeconomic variables as identified and empirically proven by Adama and Bobai (2010); Okidim and Albert (2012); Ajudua, Davis, & Osmond, (2015); Oyetade, Shri and Abdulrazak (2016); among others that some macroeconomic variables like money supply, savings, inflation rate, unemployment rate, exchange rate, among others have affected the output rate of this sector in time past and probably till now
Furthermore, some previous studies(Adama and Bobai(2010, Olarinde and Abdullahi, 2014 among others ) and national statistical publications revealed and relate the problem to the meager amount of the total government expenditure injected into the sector compared to other sectors of the economy. For instance, the 2016 annual report by the Central Bank of Nigeria (CBN) revealed that for the past 7 years (2010 – 2016), the budgetary allocation to the sector has not exceeded 2%. For instance, in 2010, the budgeted figure stood at 1.32%, it increased to 1.47% in 2011; 1.67% in 2012 and 2013. The figure then reduced to 1.43% in 2014 and 0.90% in 2015 (CBN, 2016)
5 Furthermore, official data analyzed and presented in 2018 by the Nigerian Ministry of Budget and Planning, revealed that the central and state governments only budgeted 360.1 billion for agriculture. This represents only 2% of the 17.5trillion of Nigeria‘s cumulative spending of these two tiers of government in 2018; N254 billion (1.8%) in 2017 out of the cumulative spending of N13.5 trillion and N196.3 billion (1.6%) in 2016 out of the total budget of N12.5 trillion). This contradicts the 2003 Maputo African Union (AU) agreement which Nigeria is a signatory for because these figures do not show a substantial move by the Federal government to diversify the economy by moving away from the oil sector to a sector like agriculture. Considering the 2003 Maputo Declaration on Comprehensive Africa Agriculture Development Programme (CAADP), which requires all African Union member countries to allocate at least 10% of their National annual budgets to the Agricultural sector, in which some African countries like Burkina Faso (18%), Niger and Mali (15%) Malawi (13.8%), Ethiopia (11.9%), Senegal (10.8%) and Zambia (11.5%) have complied. However, the Nigerian government over the years has not implemented the terms of this agreement (CAADP, 2003)
In terms of good management of macroeconomic variables and policies consistency and Programmes in the economy, Nigeria has witnessed series of economic retardation because of some incompetency in line with these. Evidenced from the macroeconomic literature like Akpan (2015), Oyakhilomen and Rekwot (2014) and Udeaja and Elijah (2014), the inflation rate is still a variable of concern in Nigeria. For instance, from November 2014 to the third quarter of 2016 the inflation rate rose increasingly from 8% to more than 16.54% respectively. However, the Federal Ministry of Finance attributed the hike to be an exchange rate pass-through due to our import dependency, while the Central Bank viewed it as an outcome of the fall in global crude oil price and depletion of the foreign reserve that contributed to the high demand of foreign 6 currencies, which brought about the rise in inflation. This showed how porous and weak the Nigerian foreign exchange system is, which allows for many fluctuations in the market. During those periods, the exchange rate (Naira to U.S. Dollar) appreciated from N188.45 (0.8%) per Dollar as of December 2014 to N366.19 (41.1%) per Dollar in 2016. Hence, the effect of this problem can spread, affecting other macroeconomic variables like real government expenditures, inflation rate, real money supply, public debt servicing, Unemployment rate, interest rate, external sector and the general output growth in the economy (Ibrahim, 2018)
Furthermore, the poor management of some macroeconomic variables and inconsistency in the implementation of national policies have also affected the agricultural output (Adama & Bobai, 2010; Rebecca & Ogunbaejo, 2014; Olarinde & Abdullahi (2014). For instance, policies ranging from the fourth National Development Plan (1981 – 1985) to policy on trade like the export boom (1984 – 1990). Furthermore, policy on foreign direct investment, which contributed to about 49.6% of the economy‘s growth in Nigeria in the early 1980s; to policy on structural development – Structural Adjustment Policy (SAP) introduced in the Mid –1980s, the Green Revolution Programme (1979 – 1983). Other policies include National Agricultural Land Development Authority (1992), National Fadama Development Project (1992), Roots and Tuber Expansion Programme (2003), the Agricultural Transformation Agenda (2016); export diversification in 2016 and most other reforms were not effectively implemented. The effects of these policies do not mirror agricultural output based on poor policy implementations. That may be the reason for the poor output growth in the sector for some time now especially from 2013 to 2016 as the 2016 World Bank Survey‘s report revealed. The report showed the average growth rate of the agricultural sector from 2006 to 2016 stood at 5.20%, which is not a good output rating for a country whose population is acutely rising daily
7 This report (2016 World Bank Survey) and other evidence from the literature revealed the instability of the sector‘s output, which is worthy of note that, some macroeconomic variables can still affect the agricultural sector positively or negatively. Thus, there is a need for the investigation of the impact of other macroeconomic variables (Inflation rate, Interest rate, Public debts servicing, non-oil exports and imports) on the aggregate and disaggregated agricultural sector outputs, to proffer proper policy guides for the growth and development of the sector and its sub-sectors, vis-à-vis the Nigerian Economy. Hence, to address these problems, these questions were asked: 1.3 Research Questions: a. What has been the trend of agricultural output and these selected Macroeconomic variables (inflation rate, interest rate, public debt servicing and non-oil external trade) in Nigeria? b. What is the impact (long and short-run) of these selected macroeconomic variables (inflation rate, interest rate, public debt servicing and non-oil external trade) on the aggregate agricultural output in Nigeria? c. What is the impact (long and short-run) of these selected macroeconomic variables (Inflation rate, Interest rate, public debt servicing and non-oil external trade) on the disaggregated agricultural output (Crop, Fisheries, Forestry and Livestock) in Nigeria? 8 1.4 Research Objectives: The research questions stated above outlined the ways on how to achieve the objectives of the study, which are: a. To examine the trend of agricultural output and some selected macroeconomic variables in Nigeria
b. To determine the impact (long and short-run) of some selected macroeconomic variables (inflation rate, interest rate, public debt servicing and non-oil exports and imports) on aggregate agricultural output in Nigeria
c. To investigate the impacts (long and short-run) of some selected macroeconomic variables (inflation rate, interest rate, public debt servicing and non-oil exports and imports) on disaggregated (Crop, Fishery, Forestry and Livestock) agricultural output in Nigeria
1.5 Justification for the Study
The justification for this study is underpinned by the observed gaps in the literature. These gaps are two folds: Empirical and methodological. First, is the measurement of the dependent variable (agricultural output), unlike Eyo (2008); Olarinde and Abdullahi (2014); Oyetade, et al. (2016) among others that considered the absolute monetary value, agricultural growth rate and index of agricultural production to measure agricultural sector‘s output in their models, this study considered both the disaggregated sub-sectors output (Crop Production, fishery, Forestry and livestock and Poultry) and the real aggregate share of agricultural sector‘s output (in relative terms) to Nigeria‘s real GDP
The motivation for dis-aggregating the sector is for policy purpose. That is, to determine which of the macroeconomic variables in terms of government policy implementation can be used to yield greater growth in any of the sub-sector. In other words, if the government wants to 9 encourage the cultivation of fish within the sector, which of these macroeconomic variables(inflation rate, interest rate, public debt servicing and non-oil exports and imports) would she stimulate more to achieve more output of fish. While the justification for using the relative share of real agricultural output and not absolute monetary value nor growth rate nor index of agricultural production is because there exists some degree of positive correlation between the real share of agricultural output to human lives in Nigeria. Unlike the absolute monetary value(share of nominal agricultural output) which measures agricultural outputs at current market prices without considering inflation, the real share of agricultural output considers the effect of inflation since it is measured at constant prices. Thus the more it increases the more it affects people’s lives positively and vice-versa. Furthermore, works like Oyakhilomen and Rekwot (2014) and Akpaeti (2015) attempted to maintain only the fiscal and monetary variables impact on agricultural output in Nigeria respectively, however, this work will combine both monetary (Credit, inflation rate and interest rate) and fiscal (Non-Oil External Trade and Public debt services) variables to determine their impacts on the agricultural Output
Second, the selected variables that were chosen and included in the model of this study and analyzed are much more different from previous studies. For instance, only Sunday, et al. (2012); Okoye and Clement (2015) and Lawrence and Clement (2017) had attempted to include and investigate the impact of external but not public debts servicing (domestic and foreign) on agricultural output and they used annual and not quarterly data. Hence, this study used quarterly data of public debt servicing as one of its variables to ascertain the impact of the agricultural sacrifice that is made when the government services public debts. Furthermore, this study includes a more related agricultural variable known as Non-oil trade (non-oil imports and exports) into its estimation model and investigate its impact on the agricultural sector‘s output in 10 the Nigerian economy as most of the reviewed studies did not incorporate the variable into their model. Since previous studies did not attempt to adequately investigate the impact of these selected macroeconomic variables on the real agricultural output in Nigeria thus, this study will add to the existing works of literature differently by including these variables. No doubt, these variables also may have positive or negative effects on the sector‘s output
On methodology, most of the previous studies used descriptive statistics, Ordinary Least Squares (OLS) (Multivariate and Two-Stage), seemingly unrelated regression, VAR and one-step dynamic forecasting. Few works like Olarinde and Abdullahi (2014); Udeaja and Elijah (2014); Oyakhilomen and Rekwot (2014); Oyetade, et al. (2016); Aniekan (2015); Eze (2017) among others have reported this subject matter via the use of VAR and cointegration. These estimation techniques were used by these studies without correcting for the serial correlation, endogeneity and low convergence of large finite samples. Thus, the coefficients from such estimations may not be biased, but the t-statistics used to make inference may not be consistent and a type 1 error may be made (Kao 1999, as cited in Studenmund, 2016). It is on these notes that the researcher opted to exploit the fully modified Ordinary Least Squares (FMOLS) for long-run impact coefficients and the Error Correction Model (ECM) for short-run impact and to determine the speed of adjustment to equilibrium using quarterly data. The choice for the use of quarterly data is because annual data does not give a good account of lead/lag relationships; furthermore, quarterly data gives a quick reaction to level shifts and changes in trends more than annual data since it is modeled quarterly and not annually (Tom, 2018)
1.6 Scope Of The Study: The study empirically determined the impact of selected macroeconomic variables (inflation, interest rate, public debt servicing, non-oil exports and non-oil imports) on agricultural output in 11 Nigeria using quarterly Nigerian time-series data from 1981 to 2017. The selection of the period in question (1981 – 2017) is to determine the extent to which some macroeconomic variables affect the agricultural sector‘s output despite several attempts by the government to boost the sector‘s output via different policy reforms. Furthermore, the period culminates in the vast accumulation of external reserves and the Structural Adjustment Policy, which comes with the abolition of the agricultural marketing board, and several other institutional and pricing policies
Finally, this is a period where some financial reforms with the view of stimulating the agricultural sector were initiated and implemented. For instance, the early initiation of the Agricultural Credit Guarantee Scheme Fund(ACGSF) that was established by Decree number 20 of 1977, and fully started in 1978 is one among many policies that we need to determine its impacts on Nigeria‘s real agricultural output. Besides, the 1994 – adoption of pegged exchange rate system, 1996- the liberation of the utilization and disbursement of exports proceeds by exporters, the creation of risk department for a micro guideline for farmers in 2010 and other financial policy reforms (Ajibola, Udoette, Omotosho, & Rabia, 2015 and Alex, 2012)
1.7 Organisation of the Study: The study was structured into five chapters; Chapter 1 contains the general introduction, which comprises the background of the study, the research problem, research questions, research objectives, justification for the study, the scope of the study and organization of the study
Chapter 2 has the review of related works of literature by presenting the conceptual, theoretical and empirical issues and stylized facts. While chapter 3 has the theoretical framework and methodology of the study; Chapter 4 focused on the trend analysis, estimations, presentation and interpretation of empirical results and key findings; and finally chapter 5 encompasses the summary, conclusion and policy recommendations of the study
HOW TO ORDER FOR COMPLETE PROJECT MATERIALSTEP 1
» Bank Branch Deposits, ATM/online transfers (Amount: ₦3,000 NGN)
 |
Bank: FIRST BANK Account Name: OMOOGUN TAIYE Account Number: 3116913871 Account Type: SAVINGS Amount: ₦3,000 AFTER PAYMENT, TEXT YOUR TOPIC AND VALID EMAIL ADDRESS TO 07064961036 OR 08068355992 OR Click Here |
 |
Bank: ACCESS BANK Account Name: OMOOGUN TAIYE Account Number: 0766765735 Account Type: SAVINGS Amount: ₦3,000 AFTER PAYMENT, TEXT YOUR TOPIC AND VALID EMAIL ADDRESS TO 07064961036 OR 08068355992 Click Here |
 |
Bank: HERITAGE BANK Account Name: OMOOGUN TAIYE Account Number: 1909068248 Account Type: SAVINGS Amount: ₦3,000 AFTER PAYMENT, TEXT YOUR TOPIC AND VALID EMAIL ADDRESS TO 07064961036 OR 08068355992 Click Here |