MONETARY POLICY, INFLATION AND POVERTY IN NIGERIA BY OMOLE OLUWASEUN EBENEZER MATRICULATION NUMBER : 20162566 BEING A RESEARCH PROJECT TO BE SUBMITTED TO THE DEPARTMENT OF BANKING AND FINANCE, COLLEGE OF MANAGEMENT SCIENCE, FEDERAL UNIVERSITY OF AGRICULTURE, ABEOKUTA IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE BACHELOR OF SCIENCE (B. Sc. Hons) DEGREE IN BANKING AND FINANCE SUPERVISOR: DR. ADEDEJI SEPTEMBER, 2021 i DECLARATION I, Omole Oluwaseun Ebenezer with matriculation number 20162566 hereby declare that this research “Monetary Poverty, Inflation and Poverty in Nigeria (1989-2019)” was undertaken by me under the supervision of Dr. A. O. Adedeji, and that it has not been submitted anywhere for any award of degree. Idea and views of this work are products of the research undertaken by me, and the views of other researchers have been duly acknowledged. _________________________ Omole, Oluwaseun Ebenezer _____________________ Date ___________________ _________________ Omole, Oluwaseun Ebenezer Date ii CERTIFICATION This is to certify that this research work was carried out by OMOLE OLUWASEUN EBENEZER with matriculation number of 20162566 under the supervisor of DR. A.O ADEDEJI and has been approved for the award of Bachelor of Science in the Department of Banking and Finance (B. Sc.) in the Department of Banking and finance of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria. _________________ ________________ Dr A.O Adedeji Date (Project Supervisor) ____________________ _________________ Date Dr. O.J. Oyetayo (Head Of The Department) iii DEDICATION This project is dedicated to Almighty God for his divine wisdom, grace, protection and provision in the success of this project. iv ACKNNOWLEDGEMENTS I would like to express my special gratitude to my supervisor D.r A.O. ADEDEJI for their able guidance and support in completing my project. I would also like to extend my gratitude to head of the Department Dr. Mrs O.J. OYETAYO for her valuable guidance. I also acknowledge the great efforts of my wonderful lecturers in the department of banking and finance To my parent Mr and Mrs Omole, I thank you for your love, prayer, care, and financial support. Special thank to my brother, Olasanmi Oladipupo and my sister, Olasanmi Itunu . OMOLE OLUWASEUN EBENEZER v Abstract Using time series data from 1989 to 2019, this study examined the impact of monetary policy, inflation, and poverty in Nigeria. For the following variables, data was gathered from the Central Bank of Nigeria statistical bulletin (CBN): money supply, inflation rate, poverty level, and per capital income. The ARDL (auto regressive distributed lag model) was employed in this study. The results of the ARDL model show that a broad money supply has a positive impact on poverty reduction, whereas inflation has a negative impact, especially in the long run.With the exception of inflation, the short term parsimonious results demonstrated that the broad money supply and interest rate were inversely connected to poverty. Money supply granger causes poverty reduction, meaning that money supply and interest rate have an impact on poverty. As a result, the study advocated for an expansionary monetary policy as well as zero-interest financing capable of encouraging investment in the economy's real sector while also halting the inflationary trend linked to monetary policy. vi TABLE OF CONTENTS Contents Abstract ............................................................................................................................................ i TABLE OF CONTENTS .............................................................................................................. vii CHAPTER ONE ............................................................................................................................. 1 1.1 INTRODUCTION ............................................................................................................... 1 1.2 Statement of the Problem ..................................................................................................... 3 1.3 Research Questions .............................................................................................................. 4 1.4 Objective of the Study .............................................................................................................. 4 1.5 Research Hypothesis ............................................................................................................ 5 1.6 Justification of the Study .......................................................................................................... 5 1.7 Scope of the Study ............................................................................................................... 6 1.8 Organization of the Study .................................................................................................... 6 2.1 Introduction ............................................................................................................................... 7 2.2 Conceptual Review ................................................................................................................... 8 2.2.2 Inflation rate ....................................................................................................................... 9 2.2.3 Poverty ............................................................................................................................. 10 2.3 Theoretical Review ............................................................................................................ 13 2.3.1Classical and Neoclassical Theories of Poverty................................................................ 13 2.3.2 Marxian Theory of Poverty .............................................................................................. 14 2.3.3 The social Democratic Theory of Poverty .................................................................. 15 2.3.4 The social Darwinist Theory of Poverty..................................................................... 16 2.3.5 Situational Theory of Poverty..................................................................................... 17 2.3.6 Structural Theory of Poverty ...................................................................................... 18 2.3.7 The Membership Theory of Poverty .......................................................................... 18 2.3.8 Monetarist Theory of Inflation ......................................................................................... 19 2.3.9 Classical Theory of Inflation ............................................................................................ 20 2.3.10 the Phillips Curve ........................................................................................................... 20 2.4 Empirical Review.................................................................................................................... 21 vii CHAPTER THREE ...................................................................................................................... 45 RESEARCH METHODOLOGY.................................................................................................. 45 3.1 Introduction ........................................................................................................................ 45 3.2 Theoretical Framework .................................................................................................... 45 3.3 Model Specification ................................................................................................................ 46 3.3.1 Vector Auto-Regression Model (Objective2) .................................................................. 47 3.4 Estimation Techniques ............................................................................................................ 50 3.5 Source and Measurements of the data .................................................................................... 50 3.5 Post Estimation Technique ................................................................................................ 52 3.7 Scope and Source of the Variables ......................................................................................... 55 CHAPTER FOUR ......................................................................................................................... 57 DATA ANALYSIS AND DISCUSSION OF FINDINGS ........................................................... 57 4.1 INTRODUCTION .................................................................................................................. 57 4.2 Trends in Poverty, Inflation rate, and Broad money supply ................................................... 57 4.2.1 Trend Analysis ................................................................................................................. 57 4.3 Descriptive Statistics ............................................................................................................... 64 4.4 Unit Root Test ......................................................................................................................... 66 4.5 Pre-Estimation......................................................................................................................... 68 4.6 TEST OF HYPOTHESIS ....................................................................................................... 74 4.7 Discussion of Findings ............................................................................................................ 74 CHAPTER FIVE .......................................................................................................................... 77 SUMMARY, CONCLUSION AND RECOMMENDATIONS ................................................... 77 5.1 Summary of the Study ............................................................................................................ 77 5.2 Major Findings of the Study ................................................................................................... 78 5.3 Conclusions of the Study ........................................................................................................ 78 5.4 Policy Recommendations........................................................................................................ 79 5.5 Suggestions for Further Study ................................................................................................ 80 APPENDIX .................................................................................................................................................... 81 viii CHAPTER ONE 1.1 INTRODUCTION Poverty and inflation are dreadful global phenomena that affect people at all levels and depths at various times and stages of their lives. According to the National Bureau of Statistics, Nigeria is Africa's most populated country, with a population of almost 200 million people. Despite solid growth in Africa's second largest economy, poverty in Nigeria is growing, with nearly a 100 million people living on less than $1.9 per day (Daniel, 2011). The proportion of Nigerians living in absolute poverty, or those unable to afford the fundamental necessities of food, housing, and clothes, increased to 60.9 percent in 2019 from 54.7 percent in 2004. (National Bureau of Statistics, 2018). Despite the fact that Nigeria's economy is expected to grow further, poverty is predicted to worsen as the wealth gap between rich and poor continues to increase. It's no surprise that, despite the fact that Nigeria's economy has continued to grow, the number of Nigerians living in poverty has continued to rise year after year, according to Kale (2012). According to the National Bureau of Statistics' newest report 2020, 116.719 million Nigerians live in relative poverty out of a total population of 200 million. The term "relative poverty" refers to a comparison of people's living standards in a specific society over a period of time. Inflation has been a severe concern in Nigeria since the mid-1960s. In 1975, the Udoji committee, which quadrupled the basic minimum salary in the public sector, signaled the peak of inflationary pressures, resulting in massive strikes and turmoil in the private sector, where the Udoji recommendations were not binding. Even when the oil boom collapsed in 1980, the persistent 1 overvaluation of the Naira generated major economic distortions in production and consumption, as there was a high rate of import dependency, resulting in balance of payment deficits. A low inflation rate results in lower nominal and real interest rates, lowering borrowing costs. In a low-inflation economy, “households” will be encouraged to buy more durable products and invest at a faster rate. This will improve economic growth by increasing productivity and mass production of products and services. Low inflation is crucial for economic growth and, as a result, poverty reduction. (2012) (Hossain, Ghosh, and Islam). High inflation reduces the amount of available labor, resulting in lower productivity and, as a result, lower growth. The central bank and monetary authorities are in charge of monetary policy. It is the process of controlling the cost, value, and availability of money and credit in order to reach the intended level of price, employment, output, and other economic objectives, according to the Central Bank of Nigeria (CBN). Expansionary and contractionary monetary policies are used by governments to regulate the economy during periods of inflation and recession. The role of the monetary authorities is to harness mechanisms by establishing policies that promote economic growth and stability.As a result, economic theory and a number of empirical studies support the notion that monetary policy effects output, and therefore efficient monetary policy conduct is critical (ori, Perovi, andimi, 2012). The majority of research that examine monetary policy effects focus on policy measures against the whole economy, but this tends to obscure critical nuances that could have resulted in more stable and target-oriented policy designs. Excess money in circulation leads to inflation, which invariably leads to poverty. Monetary authorities regulate money in circulation through contractionary or expansionary policies. The proportion of food in relation to other commodities may differ between the rich and the poor. Food consumes a large portion of the income of poor households. A rise in the price of vital food 2 items reduces their purchasing power, making these items unaffordable for them at the same salary level. Food costs are erratic, resulting in famine and starvation, and hence contributing to the overall inflation rate.As a result, the cost of everyday products is a major source of anxiety in today's world. (Chaudhry et al., 2000) It is important to recognize that monetary policy and inflation are not the same thing. To the best of our knowledge, only Mbutor and Uba (2013) have looked into the relationship between inflation and monetary policy in Nigeria, and found that increasing financial inclusion could improve the effectiveness of monetary policy in Nigeria.However, when it comes to the relationship between financial inclusion and poverty, Ajide (2015), Onaolapo (2015), and Chibba (2009) believe that, given the current crisis, inclusive finance has a significant impact on poverty reduction, and that the need to scale up financial inclusion efforts has never been more pressing. These writers focused solely on the effects of inflation on poverty levels, ignoring the role of monetary policy in the relationship 1.2 Statement of the Problem The average Nigerian is a low-income individual. Nigeria is a country with great wealth in the hands of a few and extreme/abject poverty on the doorsteps of many. The disparity between Nigeria's economic metrics and macroeconomic variables and reality is concerning. People die as a result of their inability to afford three square meals each day and basic public healthcare. As bizarre as it may sound, this coexists with the affluent few's extravagant displays of riches. Poverty in Nigeria is caused by a variety of factors. This includes, but is not limited to, increasing disparities in resource distribution and a lack of an enabling environment. The high rate of unemployment, on the other hand, is a defining feature of poverty in Nigeria. It is an overstatement to say that unemployment equates to a loss of purchasing power. As a result, 3 fewer products and services are consumed. As a result, enterprises are forced to reduce production output or seek other customers. In the long run, these cyclical trends have an impact on economic growth. It is because of this fundamental knowledge that the celebration of Nigeria's continuous GDP growth is so curious.Between 1970 and 2013, the rate of inflation increased, resulting in various economic distortions, a situation in which the government of a country intervenes in the economy through policies such as fiscal and monetary policies. Some policies that resulted in economic distortions include the minimum wage, lump sum tax, taxation, and government subsidies. Also, after the oil boom faded, the overvaluation of the Nigerian currency contributed significantly to economic distortions in production and consumption, resulting in a high rate of reliance on imported goods from other countries, i.e., more imports than exports, resulting in a deficit balance of payment in the economy. 1.3 Research Questions This study seeks to investigate the effect of monetary policy and inflation on poverty level in Nigeria. To this end, this paper will provide answers to the following questions: I. What is the trend of monetary policy, inflation and poverty in Nigeria? ii. What is the direction of causation that exists among monetary policy, inflation and poverty level? iii. What effect does monetary policy and inflation have on poverty in Nigeria? 1.4 Objective of the Study The broad objective of this study is to investigate the relationship that exists among monetary policy, inflation and poverty in Nigeria, The specific objectives are to: i. Examine the trend of monetary policy and inflation and poverty 4 ii. Determine the direction of causality among the money supply, inflation and poverty iii. Analyze the effect of money supply and inflation on poverty 1.5 Research Hypothesis HO1: Monetary policy and inflation have no significant impact on poverty level HO2: There is a direction of causality that exists among monetary policy, inflation and poverty HO3: Monetary policy and inflation have no effects on poverty level 1.6 Justification of the Study Aneffective monetary policy will effectively lower inflation, resulting in a reduction in the country's poverty rate. This study appears to be not the first of its kind, although it has a broad scope. Adigwe (2015), Aminu Umaru (2013), and Onwuteaka (2019) are some of the past researches that looked at the effects of inflation and monetary policy on economic growth. However, Ogbonna and Uma (2015) did research in the case of Nigeria, however their work appears to focus more on monetary policy and inflation in Nigeria.As a result, this research would provide a significant contribution to knowledge by highlighting a special focus on one sort of monetary policy, namely interest rate reduction, as well as a comprehensive focus on the impact of inflation on poverty reduction. The difficult component of this study is that while the majority of these studies show monetary expansion as a growth booster and inflation as a growth stumbling block, a few others have presented evidence to the reverse. Most monetary experts have convincingly shown that inflation is solely a monetary phenomenon that occurs when the rate of increase of the money supply exceeds the rate of growth of production in the economy. 5 According to Precious and Palesa (2014), the main goal of monetary policy is to guarantee that money supply is at a dimension that is steady with the development focus of real income, to such an extent that non-inflationary development will be certain. In view of this, the study will consider some variables that will capture full effect of monetary policy and inflation rate in poverty reduction in Nigeria. 1.7 Scope of the Study The research study covers Nigeria using data of relevant variables from 1980-2019. It makes use of both the descriptive and analytical method of analysis. The descriptive method is used by appraising the results of the findings while the analytical method involves using both statistical and econometrics tools.The study made use of majorly secondary data which were gotten from journals, relevant textbooks, economic reviews as well as database such as Central Bank of Nigeria database, World Development Indicator. 1.8 Organization of the Study This research study is divided into five chapters. Chapter One consists of the background to the study, problem statement, research questions, objectives of the study, research hypotheses, justification of the study, scope and limitation of the study as well as the plan of the study. Chapter Two reviews related literatures and theoretical framework. The literature review is divided into the methodological review and empirical review. Chapter Three covers the methodology of the research and model specification. Chapter Four explains the empirical results gotten from the econometric analysis and the discussion of results. Chapter Five discusses and summarizes the major findings of study, the inferred conclusions and relevant policy recommendation. 6 CHAPTER TWO LITERATURE REVIEW 2.1 Introduction This study has attracted some basic conceptual and empirical discussions and methodological review concerning issues surrounding monetary policy, inflation rate and poverty reduction in Nigeria. Poverty is difficult to define in a concise and widely acknowledged way, owing to the fact that it impacts many elements of human life, including physical, moral, and psychological well-being. As a result, many criteria have been employed to define poverty. The majority of studies viewed poverty as a result of a lack of sufficient income to secure basic goods and services. Others see poverty as a result of factors such as education, health, life expectancy, child mortality, and so on. The poor were recognized by Blackwood and Lynch (1994) based on their consumption and expenditure levels.Sen (1983) also associates poverty with entitlements, which he defines as "the numerous bundles of goods and services over which one has command, taking into account the means by which such goods are purchased (for example, money and coupons, etc.) and the availability of the requisite goods." Others, on the other hand, define poverty as the inability to meet “basic needs requirements” – (physical: food, healthcare, education, shelter, and so on, as well as non-physical: participation, identity, and so on) for a meaningful life (World Bank, 2016). Attempts by economists and social scientists to conceptualize the issue of poverty abound in the social science literature. Broadly Poverty can be defined in four ways: a lack of fundamental needs/goods; a lack of or degraded access to productive resources; inefficient use of common resources; and as a result of exclusion mechanisms (Olayemi, 2012). Poverty is defined 7 as a lack of access to basic necessities and goods. It is primarily economic or consumptionoriented. It uses consumption-based categories to explain the scope and depth of poverty, as well as to determine who is and is not poor. As a result, the poor are defined as people who are unable to purchase a certain basket of fundamental goods and services in a particular society. Economists typically try to distinguish inflation from a one-time price increase or price increases in a small set of economic commodities or services, according to Piana (2001). According to studies in Nigeria, Fasanya (2013), monetary policy instruments have not played a significant role in improving macro-economic variables in light of economic stability, high unemployment rates in both rural and urban areas, poverty, inflation, and low living standards. 2.2 Conceptual Review 2.2.1 Monetary Policy Monetary policy aids to long-term economic growth and financial stability by ensuring that inflation is low and stable over time (Bernanke, 2011). The real economy is critical to the country's overall growth. It provides numerous benefits to the country because it has been determined to have the greatest influence on economic growth and job creation (Anyanwu, 2010). In many economies, the real sector's performance is used to judge the success of macroeconomic policies. Monetary policy is a macroeconomic management technique that is used to steer real-world outcomes in the desired direction.According to macroeconomic theory, monetary policy should have an impact on the real economy through changing interest rates, which would affect the cost of capital and investment in the productive sector. Monetary policy, according to Mishkin (1996 and 2007), influences the economy through a range of channels, including interest rates, credit and/or bank lending, asset values via exchange rates, equities and 8 housing prices. Because the channels via which shocks are communicated alter with developments in both the global and domestic economies, investigations into the effect of monetary policy on the economy have continued to generate significant scientific interest.The foundation of the quantity theory of money was laid by Irving Fisher (Diamond, 2015. P. 49), whose equation of exchange laid the groundwork for monetary policy. Money, according to him, has no effect on economic statistics other than pricing. However, (Keynes, 1930 P. 90) and other Cambridge economists claimed that money has an indirect effect on other economic variables by altering the interest rate, which affects economic actors' investment and cash holding.. The role of monetary policy in influencing the volume, cost, and direction of money supply has been effectively articulated by (Friedman, 1968), whose position is that inflation is always and everywhere a monetary phenomenon, while recognizing that an increase in money supply can reduce unemployment but also create inflation in the short run, and thus monetary authorities should increase the money supply. 2.2.2 Inflation rate Inflation is defined as a sustained increase in the general price level of a broad range of products and services in a country over a lengthy period of time.. Inflation has always been inextricably related to money, as the adage goes: "inflation is too much money chasing too little commodities." Inflation is defined as an economic scenario in which the rise in the money supply exceeds the new production of goods and services in the same economy, according to Hamilton (2001). Economists typically try to distinguish inflation from a one-time price increase or price increases in a small set of economic commodities or services, according to Piana (2001). Inflation is defined by Ojo (2000) and Melberg (1992) as a general and consistent increase in the prices of goods and services in an economy.The percentage change in the price index is used to 9 calculate the inflation rate (consumer price index, wholesale price index, producer price index). The consumer price index (CPI), for example, according to Essien (2002), assesses the price of a representative basket of products and services purchased by the average consumer and is generated on the basis of a periodic survey of consumer prices. In the aftermath of the global financial crisis in 2008, Nigerian inflation accelerated. Inflation remained high and stayed above the Central Bank of Nigeria's comfort zone.The argument over the growth-inflation trade-off and the function of monetary policy has resurfaced, taking center stage in recent policy discussions. The conventional view, driven mostly by the short run Phillips Curve, was that a higher inflation tolerance could lead to faster growth, as opposed to the idea that inflation represents a risk to growth above a certain point. Monetary policy, for example, helps to keep inflation low and consistent over time, which benefits to long-term economic growth and financial stability (Bernanke, 2011).Inflation that is low and consistent improves the functioning of markets and makes them more efficient at allocating resources. It also enables consumers and businesses to plan for the future without being too concerned about unpredictably fluctuating price levels. 2.2.3 Poverty Poverty can be defined in four ways: a lack of fundamental needs/goods, a lack of or degraded access to productive resources, inefficient use of common resources, and as a result of exclusion mechanisms (Olayemi, 2012). Poverty is defined as a lack of access to fundamental needs/goods that is primarily economic in nature. It uses consumption-based categories to explain the amount and depth of poverty, as well as to determine who is and is not poor. As a result, the poor are defined as members of a society who are unable to purchase a certain basket of essential goods and services.Poverty is explained by a lack of access to productive resources such as agricultural 10 land, physical capital, and financial assets. As a result, there is a severe lack of income, unemployment, and malnutrition. In general, limited access to resources focuses attention on poverty and limits an individual's ability to turn existing productive resources into a greater quality of life (Sen, 1997). Inefficient utilization of communal resources might also result in poverty. This could be due to a skewed policy environment, insufficient infrastructure, limited access to technology, credit, and so on. All of these factors contribute to low productivity, poverty, and a drop in economic growth.Finally, poverty can be caused by select groups exploiting systemic mechanisms to keep "problem groups" out of economic development, including the democratic process. The discomfort index, on the other hand, is a subjective measure that combines unemployment and inflation rates. The discomfort index, sometimes known as the misery index, is claimed to have little economic significance, but it is frequently used by politicians to demonstrate the success of their programs (or the failure of their opponents' policies) (Financial Dictionary). When looking at the discomfort index, the two primary components will be examined (i.e., unemployment rate and inflation rate).The true unemployment rate in Nigeria has been a source of contention. In 1992, the figure was given as 40 percent, while in 2010, it was given as 19.70 percent by people in government circles, which contradicts the figures given by other independent sources. As a result, one can state categorically that unemployment in Nigeria has been increasing. The millions of unemployed Nigerians are a stark contrast to the country's much-touted economic boom.Various Government Initiatives to Combat Poverty and Barriers Numerous policies and programs have been established to satisfy the unique requirements of the poor as a result of the government's interest for poverty alleviation. As a result of the continuous deterioration of living conditions in the 1980s, several poverty alleviation programs were established, including: 1986:Directorate of 11 Food, Roads, and Rural Infrastructure (DFRRI), 1993:Family Support Programme and the Family Economic Advancement Programme, 2000:Poverty alleviation Programme (PAP), 2001:National Poverty Eradication Programme (NPAP).Programme to Reduce Poverty (PAP) According to Ayaba (2012), PAP was implemented as a stopgap measure in early 2000 to address the challenges of rising unemployment and criminality, particularly among youngsters. Its ultimate goal was to improve Nigerians' well-being. The three main goals of PAP are as follows: (a) Lessen unemployment and hence increase effective demand in the economy; (b) Increase the economy's productivities (c) Significantly reduce the society's embarrassing crime wave. PAP's goals, in accordance with the stated aims, include, among others, the following: (a) Creating jobs for 200,000 people who are now unemployed. b) Establishing a credit delivery system via which farmers can obtain credit. c) By 2003, the adult literacy rate will have increased from 51% to 70%. (d)Increasing healthcare delivery system from its percent 40 percent to 70% by year 2003. (e)Embarking on training and settlement of at least 60% of tertiary institutions graduates. (f)developing small and medium scale industries.National Poverty Eradication Programme (NAPEP) Introduced early in 2001, NAPEP is the current programme which focuses on the provision of “strategies for the eradication of absolute poverty in Nigeria”. 12 2.3 Theoretical Review Several theoretical contributions have been made in the literature as regards monetary policy, inflation and poverty. These theories are of relevance to this study as they serve as bed rock to this research work. Nevertheless, no theory is sufficient in itself, an integrated approach is needed. 2.3.1Classical and Neoclassical Theories of Poverty Individuals, according to classical traditions, are mainly accountable for their own fate, choosing to become poor in effect (e.g. by forming lone-parent families). The notion of 'poor subcultures' argues that inadequacies may persist over time, due to a lack of adequate role models, and that government assistance should be confined to altering individual skills and attitudes (i.e., the laissez-faire tradition). Neoclassical theories are more comprehensive and acknowledge causes of poverty that are beyond the control of people.These include a lack of both social and private assets; market failures that exclude the poor from credit markets and make certain irrational choices rational; educational hurdles; immigrant status; poor health and advanced age; and employment barriers for lone-parent families. When comparing the classical and neoclassical approaches, the use of (quantifiable) monetary units to quantify poverty and the readiness with which policy prescriptions can be implemented are the primary differences.They also highlight the influence of incentives on individual behaviour as well as the relationship between productivity and income. Criticism of these approaches highlights their overemphasis on the individual (without, for instance, taking into account links with the community) and the focus on purely material means to eradicate poverty. 13 2.3.2 Marxian Theory of Poverty This is a hypothesis that states that poverty is caused by the circumstances in which a poor individual finds himself or herself. As a result, the poor individual is a victim of circumstances caused by a variety of variables, one of which is the production system. According to Karl Marx, the owners of means of production (capitalists)' entrepreneurial practices of moving away from labor-intensive to capital-intensive means of production in order to raise production and maximize profits leads to huge unemployment. In order to increase profitability, capital intensive production pushes the capitalist to retrench workers. Massive unemployment results from layoffs.Those who do not re-engineer end up as paupers at home, forming what Karl Marx refers to as a reserve army of laborers (Harvey and Reed). These paupers eventually become destitute. Continued austerity leads to an increase in the number of poor people in the economy, which raises poverty levels in the long run. A sequence of structural failures has resulted in an increase in the poor population. These structural failures, according to Gordon et al. (1982:), include racial and gender discrimination, as well as nepotism, which deny some groups of individuals access to jobs, education, and social assistance.Albrecht and Milford (2001) add to this hypothesis by stating that substantial economic restructuring leads to increased economic and social marginalization of a whole group of individuals. Due to a lack of access to opportunities, such populations end up impoverished. According to Marxist theory, poverty alleviation can be achieved through improving production structures and providing more education and training to individuals who have been rendered obsolete by technical advancements, allowing them to adapt to changes in their environment and change their profession. Education also helps that retrenched people accept and adapt to change (Winch, 1987).The idea also proposes for a government welfare program to assist individuals 14 who are unable to reengineer themselves through education in order to gain access to basic necessities like food rations, health care, and subsidies (Coser, 1969; Harvey & Reed, 1992) In order to alleviate poverty, Neo-Conservative theory of poverty recommends provision of moral education to curb over-population. Moral education results in sexual restraints, delay in marriage and practicing abstinence prior to marriage. Poverty can also be reduced through improved production technology to ensure that production of goods and services satisfy demand at affordable prices (Winch, 1987) 2.3.3 The social Democratic Theory of Poverty This theory was developed based on events that occurred in the United Kingdom in the 1920s. Poverty, according to the theory, is a class-based notion that arises through societal class fights rather than from a lack of resources. Piero Sraffa, the proponent of this theory, stated that class battles extended beyond production domains, and that so limiting poverty explanations to production means, as Marx did, would limit the scope needed to comprehend poverty. Poverty is influenced by the politics surrounding how products and services are created and distributed, just as it is by the means of production used (Sraffa, 1926).The politics of commodities and service distribution go a long way toward explaining why certain groups of society are poor. Poverty, according to the Social Democratic theory, is both a class issue and a market-based factor. Poverty alleviation necessitates distributive justice, which ensures that products and services generated are dispersed equally so that all classes of society are fairly involved in their enjoyment (Harvey & Reed, 1992). Sen (1981) comes to the conclusion that poverty is a result of entitlement, noting that “starvation...is a function of entitlement, not of food availability.” Entitlement is a legal claim on existing resources that is a result of a political process aimed at improving market dynamics or correcting market faults.In times of economic downturn, market 15 forces fail as a result of capitalists' fear of taking entrepreneurial risks, slowing production and causing unemployment, as John Maynard Keynes believed. When market forces fail, the poor get poorer as a result of greater unemployment or retrenchment, as well as low-income levels. When market forces fail, the government must intervene to assure sustained production and stable employment (Sen, 1984). Sen (1984) contends that when people's access to resources or income is limited, their own capacities lead to absolute deprivation, but market forces are powerless to intervene. While persons in positions of political power who are capable of producing should not be restricted from doing so, the government must also ensure that all of what is produced is distributed fairly in order to eradicate poverty. This theory is also a proxy for Marxism, which links poverty to the production and distribution of goods. 2.3.4 The social Darwinist Theory of Poverty According to the social Darwinist theory of poverty, poverty is a self-inflicted condition that evolves over time as a result of social evolution. The excellence or mediocrity of an individual will inevitably induce that person to be impoverished or otherwise. As a result, poverty is "both a final judgment and a purgative by which society selects the unfit." Poverty trends in any community are the outcome of natural selection, and any man-made attempt to reverse the trend's direction wreaks havoc on institutions' natural functioning (Harvey & Reed, 1992).Based on studies in metropolitan areas, the Social Darwinist theory of poverty distinguishes two forms of poverty. The first category is middle-class poverty, which is a reversible position brought on by social and ecological changes in urban areas. Physical disabilities, old age, or a female-headed home with dependent children are all signs of normal-class poverty. Because it focuses primarily 16 on income-based poverty, normal-class poverty is self-correcting. When a person reaches adulthood, moves from one economic class to another, or is assimilated, it can be removed.Other ways of eradication include education and training, as well as natural urban evolution (Harvey & Reed, 1992). This hypothesis is largely irrelevant because it focuses on urban or pre-urban poverty. The second sort of poverty is lower-class poverty, which is produced by poor people's behaviors or cultural practices and conventions. This type of poverty develops as a result of a way of life that prioritizes labor, self-improvement, and family service (Harvey & Reed, 1992). Lower-class poverty persists because educators and opinion leaders who are able to modify the normal-class poverty avoid issues of culture and habits passed down from generation to generation. Lowly class largely remains unchanged.Lower-class poverty therefore gradually evolves into a natural process through which society eliminates the unfit members (Harvey & Reed, 1992). This theory does apply given the fact that this study was based in the rural areas where the issue of culture cannot be underestimated. 2.3.5 Situational Theory of Poverty This idea explains why poor people are more likely to exhibit fatalism and desire for rapid fulfillment. This behavior, according to Jones (1984: 248), is “a sensible response to deprived conditions.... This behavior stems from the poor's opportunity structure rather than distinctive cultural values.....” The impoverished, according to this interpretation, exhibit impulsive behavior in order to maximize utility in order to ensure survival. The impoverished do not work because they are despairing due to a lack of optimism and a lack of a direct correlation between their efforts and the rewards they receive.The situation the poor find themselves in is one that does not allow them to gain much from hard work and a long-term view of issues. Consider a 17 child in a slum trying to study. Lack of supportive factors and an enabling environment such as school fees, career counselling, text books and the like will lead the child to give up and engage in immediate gratification such as street vending, theft, commercial sex activities and the like in order to satisfy immediate daily demands of food, shelter and clothing. 2.3.6 Structural Theory of Poverty The structural theories, in which poverty is blamed on circumstances and institutions in the social or economic systems, such as racism, sexism, and segregation barriers, rather than on the individual, are the second major category of theories (Gordon, Edwards & Reich, 1982). Poverty is thus caused by a lack of enough skills and work prospects to maintain acceptable living standards or quality of life (Cobb 1992 Duncan 1992 and Maril 1988). Albrecht et al. (2001) add to these theories by pointing out that large economic restructuring also leads to greater economic and social marginalization of a whole group of individuals.Structural theories absolve the poor from blame. Poverty is blamed on structural failures which include sexism, racism, and bad governance, wretched state of infrastructural development, poor development policies and even geographical placement. 2.3.7 The Membership Theory of Poverty According to S. N. Durlauf of the University of Wisconsin's Department of Economics, the importance of group memberships in shaping socioeconomic results should not be overlooked. He ascribed membership-based theory to this particular perspective on the origins of poverty, which he outlined in his work. The assumption behind this hypothesis is that during the course of a person's life, the organizations to which he or she is connected have a significant impact on his or her socioeconomic possibilities. Residential communities, schools, and businesses, for example, are examples of endogenous groups, according to the author.The idea behind this 18 theory is that during the course of a person's life, the organizations to which he or she is connected have a significant impact on his or her socioeconomic possibilities. Residential communities, schools, and businesses, for example, are examples of endogenous groups, according to the author. Other factors, such as ethnicity and gender, are exogenous. The membership theory of poverty is based on the assumption that an individual's socioeconomic result is determined by the composition of the many organizations in which he or she participates over the course of his or her life.In theory, such groupings can be defined along a variety of characteristics, including ethnicity, residential neighborhoods, schools, and workplaces. A variety of conditions can cause these affiliations to have causal effects on individual outcomes. Peer group effects, role model effects, social learning, and social complementarities are some of these aspects. 2.3.8 Monetarist Theory of Inflation The quantity theory of money was propounded by Milton Friedman (QTM). Money supply, according to monetarists, is the most important predictor of a country's price level. When the amount of money available in an economy changes, the price level changes directly and proportionally. The quantity theory of money can be expressed as follows, using Irving Fisher's equation for exchange: MV= PQ.................................(1) M= Money Supply in an economy V= Velocity of Money in Circulation Q= Volume of transactions P= General Price Level 19 Inflation in an economy is caused by a change in the supply of money or the quantity of money in circulation, which influences the price level but not the rate of development in the economy, according to monetarists. They felt that the degree of inflation has a significant impact on investments, exports, and capital accumulation, and thus on the long-term growth rate of an economy. They focused on the long-run dynamics of an economy rather than the short-run dynamics. 2.3.9 Classical Theory of Inflation Adam smith is the father of the classical economist; he came up with a supply side model of growth where he pointed out three important production factors, which are land, labour and capital. He propounded a production function where he expressed output is a function of land, capital and land that is: Y=f (L, K, T).............................(2) Y= Output K= Capital L= Labour T= Land Adam Smith argued that savings leads to investment which leads to economic growth. He stated that growth in output is as a result of investment growth, population increase, land and increase in productivity generally. (Gokal and Hanif, 2004) stated that the relationship between inflation and economic growth is negative by the reduction in firms profit level and saving through higher wage costs. This theory was criticized, as it does not give any direct reason of inflation and the tax effect on the level of profit and output. 2.3.10 the Phillips Curve This theory was propounded by A.W Phillips in 1958. His theory focused on the relationship that exists between inflation and unemployment. He estimated a curve known as the Phillips Curve, 20 this curve showed that there is an inverse relationship existing between wages and the rate of unemployment using data from United Kingdom from 1862-1957. He argued that wages and prices move in opposite direction thus showing that there is a relationship between prices and unemployment. The backbone of the Phillips Curve is that empirically it shows that there is an existing reliable correlation economically and statistically between inflation and unemployment, (Umaru and Zubairu, 2012). (Lucas R, 1973) argued that inflation is an important engine for economic growth, he stated that low inflation conquered adamant nominal prices and wages while relative prices can be adjusted to fit structural changes during production to aid modernization period. This to him speeds up economic growth. (Romer D, 2001) is of the opinion that high rate of inflation leads to “Shoe leather cost” i.e. inflation which is accompanied with extra effort by people to make them reduce holding money and “Menu cost” that is, inflation that leads to change of prices more often, this discourages investment and tax system in the long-run. 2.4 Empirical Review Dauda and Makinde (2009) examined the nexus between financial sector development and poverty reduction in Nigeria using annual time series from 1980 to 2010. The evidences from both the VAR and impulse response showed that theindirect effect of economic growth exerts the strongest influence on poverty reduction in the short run but could be detrimental to the poor in the long run due to the adverse effect of income inequality. The study concluded that the relationship between poverty and the financial deepening proxied by broad money supply (M2) is negative and significant. Hence, the McKinnonconduit effect is the likely main transmission channel through which the poor 21 benefit from the financial sector development in the long run. And also that credits to private sector, contrary to the general belief, have failed to cause a reduction in the incidence of poverty in Nigeria.Nwigwe, Omonona and Okoruwa(2012)argued that while microfinance has developed some innovative management and business strategies, its impact on poverty reduction remains in doubt. With a view to understanding how Islamic microfinance as a financial inclusion strategy can be applied in alleviating poverty and maintain sustainable development in Nigeria, Onakoya and Onakoya (2014) analysed the principles of Islamic finance and conceptualized its operational details to see the linkage between the real economies and sustainable development. The study employed triangulation method, which is the use of different data collection techniques within one study in order to achieve more accurate results. They employed a descriptive research method by collecting data from urban and rural areas; surveyquestionnaires coupled with semi structured interviews were adopted. With the understanding that microfinance is a sub-division of the financial sector, the survey conducted in Ogun State, a sub-national government of Nigeria revealed that Islamic microfinance in concert with the right fiscal and monetary policies framework, will contribute positively to poverty alleviation in Nigeria. Jeanneney and Kpodar (2008) investigated how financial development helps to reduce poverty directly through McKinnon conduit effect and indirectly through economic growth. The results obtained with data for a sample of developing countries from 1966 through 2000, using the system GMM estimator, suggest that the poorbenefit from the ability of the banking system to facilitate transactions and provide savingsopportunities but to some extent fail to reap the benefit from greater availability of credit. Also that 22 financial development is accompanied by financial instability which isdetrimental to the poor. Nevertheless, the benefits of financial development for the pooroutweigh the cost.Inoue and Hamori (2010) examined empirically whether financial deepening has contributed to poverty reduction using unbalanced panel data for 28 states and union territories between 1973 and 2004. Using dynamic generalized method of moments (GMM), they found that financial deepening and economic growth alleviate poverty, while international openness and inflation rate have the opposite effect. Odhiambo (2010) empirically analysed the causal relationship between financial development and poverty alleviation in Zambia from 1969 to 2006. She examined the effect of three proxies for financial development, namely: M2/GDP, private credit/GDP, and domestic money bank assets; on per capita consumption, a proxy for poverty levels. Using a bivariate causality test based on an Error Correction Model (ECM), she found that financial development seems to cause poverty reduction when private credit and domestic money bank assets are used, while the reverse causality is found when M2/GDP is used. Badebo and Mohammed (2015) examined the effectiveness of monetary policy as an anti –inflationary measure in Nigeria, using co-integration and error correction approach on quarterly time series data covering 1980 Q1 to 2012 Q4.They found a long run relationship between inflation and the vector of regressors employed. The study also revealed that interest rate, exchange rate, money supply and oil price are the major causes of inflation in Nigeria. Omeke and Ugwuanyi (2010) also carried out a study or better put tested the relationship between money, inflation and output in Nigeria, employing cointegration and Granger-causality test analysis. The findings revealed no existence of a co-integrating vector in the series used. However, Money supply was seen to Granger 23 causes both output and inflation. The result suggest that monetary stability can contribute towards price stability in Nigerian economy since the variation in price level is mainly caused by money supply and also conclude that inflation in Nigeria is too much extent a monetary phenomenon.Danjuma et al (2012), in their study on the assessment of the effectiveness of monetary policy in combating inflationary pressure on the Nigerian economy, found that liquidity ratio and interest rate are the dominant monetary policy tools that can be employed to combat inflation in Nigeria. Also, Emerenini and Eke(2014) investigated the determinants of inflation in Nigeria using a monthly data from 2007 to 2014, using OLS method found that,exchange rate and money supply influenced inflation. Apir (2015) studied the extent money supply can explain the inflationary phenomenon in Nigeria and discovered that money supply is the main determinant of inflation in Nigeria between 1999 and 2014. Olorunfemi and Adeleke (2013) also examined the effect of money supply on inflation and concluded that money supply and interest rate did influence inflation in Nigeria.Williams and Adedeji (2004) examined price dynamics in the Dominican Republic by exploring the joint effects of distortions in the money and traded-goods markets on inflation, holding other potential influences constant. The study captured the remarkable macroeconomic stability and growth for period 1991 to 2002. Using a parsimonious and empirically stable error-correction model, the paper found that the major determinants of inflation were changes in monetary aggregates, real output, foreign inflation, and the exchange rate. However, there was an incomplete pass-through of depreciation from the exchange rate to inflation.Mbongo et al (2014) examined the effects of money supply on inflation in Tanzania. Using OLS, VAR and Error Correction Model, 24 they found that money supply and exchange rate to have a significant impact on inflation in the short and long runs. Mubarik (2005) employed the Granger Causality test to analyse the threshold level of inflation for Pakistan for the period between 1973 and 2000. Annual data set was used. The result of the threshold model suggests that an inflation rate beyond 9-percent is harmful for the economic growth of Pakistan and inflation rate below the estimated level of 9-percent is favorable for the economic growth. ErTugcu and Coban (2014) investigated the short and long-run relationship between savings, inflation and economic growth in Turkey. The Autoregressive Distributed lag (ARDL) Approach was utilized for the analysis. The result showed that savings, inflation and economic growth are co-integrated and either inflation or economic growth has positive impacts on the savings in the Turkish economy. Kisu et al (2012) examined the relative importance of monetary factors in driving inflation in Malawi, using a stylized inflation model specification that included standard monetary variables, the exchange rate and supply side factors. They came up with the finding that money supply growth drives inflation with lags of about 3 to 6 months and that the exchange rate adjustments play a relatively more significant role in feeding costpush(supply side factors) inflation.Mahmoud (2015) examined the link between consumer price index (CPI) and Gross domestic product (GDP) in Mauritania. The result revealed a positive and significant relationship between the GDP and CPI. Khan et al. (2011) analyzed the relationship between financial sector development and poverty for different countries. The study divided financial sector into four sectors; Banking sector, Insurance companies, Stock market and Bond market, for the purpose of estimating effect of financial sector development on poverty. For banking sector, the 25 following variables were used; central bank assets to GDP, deposits money banks assets to GDP, bank deposits, concentration, overhead costs and net interest rate. For insurance company, non-life insurance was used as the variable; to capture the effect of stock market variable, stock market turnover ratio was used. For bond market, both market capitalization to GDP and public bond market capitalization to GDP were used. The results of the OLS estimation indicated that there is negative and highly significant relation between poverty and central bank assets, coefficient of Deposits Money Bank Fowowe and Abidoye (2012) concluded that measure of financial development does not significantly influence poverty in Sub-Saharan African countries. However, macroeconomicvariables such as low inflation and trade openness can help reduce the level of poverty after applying the Systems GMM estimatoron panel data for the selectedSub-Saharan African countries. Boukhatem (2015) provided an empirical assessment of the direct contribution of financial development to poverty reduction in 67 low and middle-income countries over the period 1986-2012. Using panel OLS and system GMM, the results showed the important contribution of financial development to the reduction of poverty independently of the econometric techniques used. The study also found that instability related to the financial development would worsen the condition of poor population and would vanish the positive effects of financial development. The study therefore suggested that pro-poor public investment policy in low and middle-income countries are required in tandem with financial development to ensure a reduction in the level of poverty. In (2017) analyzed the relationship between inclusive finance and poverty alleviation in a panel of 86 countries in Asian, African and Latin American countries from 2004 to 2013 by using generalized 26 method of moments. The results revealed that the impact of inclusive finance on poverty alleviation (proxied by Gini coefficient) was different in Asia, Africa and Latin America. For Asian countries, inclusive finance is negatively related to poverty alleviation which implied that the development of inclusive finance can be used to narrow the income gap between the rich and poor; for African and Latin American countries, there was a clear inverted U-shaped relationship between the development of inclusive finance and poverty alleviation, which indicated that the inclusive finance will first widen income gap, and when the financial development reaches a high stage, it can also be used to narrow the income gap and alleviate poverty. The study also found that export trade indicators in Asian countries were not statistically significant in achieving poverty alleviation. Though, the usage of natural resources had an impact on poverty alleviation in African countries, but its effect was positive which implied that the usage of natural resources cannot raise the standard of living or alleviate poverty in Africa. However, the industrial structures alleviated poverty and narrowed income gap in Latin American countries. Therefore, the study concluded that in order to narrow the income gap between the rich and the poor and alleviate poverty, the first is to promote the development of inclusive finance, improve the financial system, eliminate barriers and let middle and low income. Literature Review on Monetary Policy, Inflation and Poverty in Nigeria Literature Review on Monetary Policy, Inflation and Poverty in Nigeria Author(s) and Title Scope Methodology 27 Findings Comment Year /Objective Sani I Threshold 1986-2009 Doguwa relationship Nigeria 1980 Garch Inflation The null threshold is hypothesis between statistically cannot be inflation and significant accepted Inflation with Methodology economic focus on long growth has run issue economic growth Javier Andres Inflation and 1989-2011 and Ignacio economic OECD Hernando growth Panel not conclusiv Cordelia Study joint 2009-2018 OLS Money supply ARDL Onyinyechi and individual Nigeria has negative method of 2019 money supply and estimation on economic insignificant can also be growth with used. economic growth Barr and Money supply 1971-2010 Kantor and economic (1989) Khayroollo Panel ARDL influence long based on activities in economic panel South-Africa growth estimation Inflation ECM can also Inflation and South Africa Money supply Scope was 1980-2010 OLS 28 Sattarov economic (2011) growth Finland reduce be used for economic the estimation growth in Finland Chude Nkiru Relationship 1987-2010 Patricia between Nigeria (2016) OLS Positive and Interest rate significant and inflation money supply between rate are not and economic money supply mostly used growth and economic together. growth. Oluwagbenga Impact of 1980-2018 Anthony and inflation on Nigeria Dada ARDL Inflation and More exchange variables can economic have also be Oluwabunmi growth significant included. (2020) evidence from negative Nigeria impact on economic growth Literature Review on Monetary Policy, Inflation and Poverty in Nigeria (Cont) Author(s) and Title Year /Objective Scope Methodology 29 Findings Comment Akinola Impacts of 1973-2013 Abdulgafar and money Nigeria VECM Positive The results money supply was perfect Olarinde Olaiya supply and while based on the 2019 inflation rate analysis inflation was negative Foluso A Impact of 1987-2017 Akinsola and inflation on Nigeria Nicholas M 2017 VAR Negative Analysis was relationship not economic between compressive growth inflation and economic growth Phiri Andrew et Nonlinear 1970-1990 PANEL Inflation has Different al 2016 impact of South-Africa negative method of inflation on effect on estimation economic economic techniques growth growth used Positive and Other method significant of estimation Dingela Dynamic 1980-2016 Siyasanga and impact of South-Africa Khobai H money between can also be 2017 supply on money supply used economic and economic growth growth Mr TT Overview of ARDL August 2013 No 30 Review the Inconclusive Mboweni(2003) the South – South-Africa Estimation economy of Africa South-Africa economy as a whole Monaheng et al Inflation and 1980-2009 Panel ARDL (2015) economic South-Africa growth Inflation has Result from had the fixed detrimental effect was not effect to too good economic growth Iwedi Marshal To study the 1970-2014 (2016) link between Nigeria VAR Unidirectional ARDL causality method of money between estimation supply and money supply was economic and RGDP applicable growth Literature Review on Monetary Policy, Inflation and Economic Poverty in Nigeria (Cont) Author(s) and Title Year /Objective Nexhat and Impact of Scope Methodology Findings Comment 1997-2019 OLS Inflation has Panel data 31 Esat Durguti inflation on 2019 Kosovo positive supposed to be economic impact on used for the growth economic estimation growth Wiza To show Quarterly Munyesa relationship 2014 Panel ARDL Inflation pose Each variables data used a great effect has different between 1993-2011 on the growth effects on inflation and (South- of the economic economic Africa) economy growth It shows that The analysis inflation was not inflation and affect comprehensive economic economic growth in growth in Nigeria Nigeria growth Miftahu Idris Relationship 1981-2016 2017 between Nigeria OLS D Van Monetary 2001-2017 ARDL Long run and Wyngaard policy on South-Africa 2019 inflation and of money economic supply on growth economic Abstract was positive effect too much growth Astra Dimiti The influence 1970-2016 ECM 32 Money More variables Amassoma et of money al 2018 Nigeria supply does can still be supply on not included inflation in considerably Nigeria influence inflation both the short and long run Olorunfemi Money 1970-2008 Sola supply and Nigeria 2013 VAR Money ARDL can supply does also be used inflation in not really for the Nigeria influence estimation inflation Asuquo Money 1981-2015 OLS Inflation, Ekpeyong et supply, Nigeria al inflation and and interest 2018 economic rate had growth in positive effect Nigeria on growth Reserve labour force Summary of Literature Review on Monetary Policy, Inflation and Poverty in Nigeria (Cont) Author(s) and Title Year /Objective Scope Methodology 33 Findings Comment Anyanwu To investigate 1985-2000 Uchenna N and the effect of Nigeria Alexanda O.U money supply affects each on inflation other Bigben Examine post 1986-2008 Chukwuma SAP Nigeria Ogbonana 2015 VECM VAR Inflation and Data life span money supply was too short Exchange rate Inflation and is the most interest rate persistence of reliable for are not inflation in measuring Nigeria macro- included economic policy Ayad Hicham Relationship 1970-2018 2020 between Nigeria VAR There is a long Focus run attention on inflation rate, relationship Nigeria money supply among the and economic variables economy growth. Ogenyi,A.O et Determinants 1980-2010 ARCH AND Money supply, Only on al 2019 of inflation Nigeria GARCH Government working volatility in expenditure paper Nigeria and gross domestic product tends to favor inflation 34 Raymond, Econometric 1980-2012 Adegoyega R analysis of Nigeria 2014 ARDL Interest rate, Inflation and money supply interest rate effect of were influence were not used changes in by inflation interest rate on rate together inflation in Nigeria Feridun Mete Forecasting and Adebiyi Micheal 2005 1980-2003 ECM Exchange rate No specific inflation in and domestic comment on developing debt can be the impact of economies used to money supply forecast inflation Mathias Transmission 2000-2013 A.Cuba 2015 mechanism quarterly data VAR money supply Positive and No issue on significant interest rate transmission Summary of Literature Review on Monetary Policy, Inflation and Poverty in Nigeria (Cont) Author(s) and Title /Objective Scope Methodology Findings Comment Okoroafor To determine 1990-2011 Ordinary Human Other Micheal and impact of Nigeria Least Square development variables can Year 35 Nwaeze poverty on Chinweoke 2013 (OLS) index is still be economic statistically included in growth significant to this study influence economic growth Kwadwo Impact of 19767-2015 Ordinary Long run The author Ofori money supply Ghana Least Square effect of could not get Frimpon on inflation (OLS) money supply actual 2017 on inflation dependent rate variable for this study Nazima Food inflation 1990-2015 Auto There is a Poverty index Ellahi and and poverty Pakistan regressive link between was not Zaib Maroof distributed food inflation consider in 2013 lag model and poverty this study (ARDL) rate J.C Inflation and 1998-2003 Error Positive This study Vermeulen unemployment South Africa Correction relationship too focus on 2017 in South Africa Method between inflation and (ECM) inflation and not poverty employment Iwan Azis Macroeconomic E52-131 Panel Method Slower 36 Focus 2008 policy and Japan poverty growth and attention on higher Nigeria inflation economy worsen poverty Kalie Pauw Impact of Paper 07/126 Panel ARDL Poverty and Unavailability and Liberty growth on South Africa inequality of data Nncube redistribution of have been a 2014 poverty and major issue inequality on economic growth Adebayo Financial 1986-2015 Ajisafe and inclusion, Nigeria Solomon Okunade ARDL Financial Other method inclusion has of estimation monetary desirable can also be policy and effect on used for the poverty level poverty level study Literature Review on Money Supply, Inflation and Poverty in Nigeria (Cont) Author(s) and Title Scope Methodology Findings Year /Objective Dayo Benedict O Examine the 1970-2010 ECM Money supply Limited to relationship Nigeria has positive 37 Comment some and Kemi between relationship Funlayo A money with capital 2013 supply, accumulation variables only inflation and capital accumulation Awogbemi Causes and 1969-2009 Clement A effects of Nigeria and Taiwo Joseph K ARDL Money No specific supply, gross method of inflation in domestic estimation Nigeria product and technique inflation were mentioned 2012 all positive in the long run Mbutor O Inflation in 1970-2012 ECM Inflation does Limited Mbutor Nigeria: How Nigeria not really variable used 2013 much is the affect money function of supply as a money? result of recession Olalere, Examine the 1980-2009 Sunday Shina impact of Nigeria 2015 VECM Long run ARDL relationship method of money supply between estimation is on inflation in money supply also 38 Nigeria and inflation applicable Moses, K, Monetary Quarterly data OLS Existence CBN paper Tule and S.O growth and 1996Q1 And relationship work odediran et al inflation 2012Q4 between 2015 dynamics in Nigeria money Nigeria growth and inflation Oluremi Money supply 1970-1989 Ogun and mechanisms Adeola in Nigeria Panel ARDL Nigeria Adenikinju Money supply Variables and inflation used are not depends on specified each other 1995 Ezeibekwe, Monetary 1981-2018 Pane Data Show that Data Obinna policy and Nigeria investment invariable Franklin domestic depend on 2020 investment in inflation rate Nigeria Literature Review on Monetary Policy, Inflation and Poverty in Nigeria (Cont) Author(s) and Title Scope Methodology Findings Comment Year /Objective Mukytah Effect of 1981-2015 Vector Error Long run Causality Galadima money supply Nigeria Correction relationship among the 2017 on economic Model among the variables also 39 growth in (VECM) Nigeria variables, carried out money supply and interest rate are positive Gerald Monetary Working Epstein and policy and paper No 113 James heintz 2006 Panel method Financial Attention are sector focused on financial improves some area sector reform employment only for employ and poverty and poverty Siyan Peter To examine 1980-2014 Adegoriola implication of Nigeria and Adewale E.2016 VAR There is a Inflation and relationship poverty are unemployment between the major and inflation inflation focused in on poverty unemployment this study and poverty level Tokunbo Macro- 1960-2000 Error Economic This study is Simbowale economic Nigeria correction growth in not of recent Osinubi policies and Method Nigeria has data span 2005 pro-poor (ECM) been slightly used growth in pro-poor 40 Nigeria Mohammed Role of 1972-2008 Irfan and inflation and Pakistan Amjad Ali economic negative effect the current 2011 growth in in the short situation in explaining but inflation the country prevalence of has positive poverty effect Aphu Elvis Impact of AGD2014- 2018 Ghana 2017 ARDL Panel Economic The research growth has cannot give Government No specific spending role of government undermines government on poverty economic on poverty eradication growth by action displacing private sector activities Literature Review on Monetary Policy, Inflation and Poverty in Nigeria (Cont) Author(s) and Title Year /Objective Yakubu Musa Scope Methodology Findings Comment To investigate 1970-2010 Auto Government Data period is and Aminu long run regressive revenue has not of recent Bello effect of distributed lag significant 2014 money supply model Nigeria 41 effect on and (ARDL) money supply Panel Data There is No specific strong method of estimation government revenue Amedeo How much 1972-2002 Strano can money Ghana 2000 supply affect indication inflation rate between money supply and inflation Shahldur R Effect of 1981-2008 Talukdar inflation on Texas 2012 Panel data Relationship Observation between for each poverty in inflation and countries too developing poverty are low countries negative and insignificant Dimiti To investigate 1970-2016 Amassoma et influence of al 2018 ARDL Nigeria Money supply There are does not different money supply considerably economic on inflation influence condition inflation in long and short run Arne Bigsten Policies for 1990 Series 42 MDG Arrow and Abebe growth and Shimeles poverty 2006 reduction in Africa Zorobabel et Eliminating Abidjan 2015 Pane series al 2015 extreme can be poverty in reduced to Africa low Panel Poverty level Gary Moser Economic IMF PAPER Economic and Toshihiro growth and International growth not 2001 poverty Development necessarily reduction in influence sub-Saharan poverty in Africa Africa Paper work Voluminous Source: Author’s Compilation 2021 Literature Review on Monetary Policy, Inflation and Economic Poverty in Nigeria (Cont) Author(s) and Title Scope Methodology Findings Comment Year /Objective Javier Andres Inflation and 1989-2011 Panel Inflation with Methodology and Ignacio economic OECD economic focus on long Hernando growth growth has run issue 43 not conclusiv Iwedi To study the 1970-2014 Marshal link between Nigeria (2016) VAR Unidirectional More causality variables can money supply between still be and economic money supply included in growth and RGDP this study Ikechukwu, Nigeria Industrial output, Ordinary least- The result shows In appropriate Nwokoye and 1980-2013 exchange rate, square (OLS) that foreign method Ebele inflation, method direct (2015) population investment, growth and population foreign direct growth and real investment exchange rate are significant determinant of industrial output Abdallah and Ghana Exchange rate, Autoregressive There exists Ignore the Abdul 1986-2013 manufacturing distributed lag short and long major output, interest model run relationship (2016) objective rate and foreign between direct exchange rate investment and manufacturing sector performance. Source: Author’s Compilation 2021 44 Based on the empirical review of different authors, their study has been based on two variables: the impact of monetary policy on inflation rate, such as the study of Oseye(2011) who worked on the impact of monetary policy on inflation rate, and the research work of Kisu et al (2012) who examined the relative importance of monetary factors in driving inflation in Malawi. The goal of this study is to fill a gap in the literature by merging the three variables of monetary policy, inflation, and unemployment. In Nigeria, Dauda and Makinde (2009) looked at the relationship between banking sector development and poverty reduction. This study also aims to show the causation that exists among the three variables. Also, to increase the data coverage up till 2019 CHAPTER THREE RESEARCH METHODOLOGY 3.1 Introduction This chapter consists of theoretical framework which provides the theoretical basis of the study and the research methodology which illuminates the empirical investigation conducted. Also, to assess the impact of monetary policy and inflation on poverty using appropriate econometric technique, a model with dependent and explanatory variables to be estimated is specified, a priori expectation of the parameters, technique of estimation and method of data analysis are all treated. 3.2 Theoretical Framework The theoretical framework of this study is Marxism theory of poverty. This is a form of structural poverty school of thought that believes poverty is caused by vulnerable demographic situations and difficult labor market conditions, rather than an individual's incompetence. The works of German Karl Marx form the foundation of the Marxist school of thought, which 45 contends that inequality is an unavoidable part of a capitalist economy. The Marxists think that poverty is an intended result of the class struggle between capitalists and labor. Modern arrangements promote an imbalance of power and so provide inequality. To preserve control over the means of production, capitalists actively exploit their laborers and aim to prevent them from advancing socioeconomically as much as possible. 3.3 Model Specification The model to be estimated in this study are stated as follows POV= (M2, INFR, TROP) WHERE: POV= Poverty M2= Broad Money Supply INFR= Inflation rate TROP= Trade Openness The models are also specified in stochastic form: POVi,t = α0 + α1M2i,t + α2INFRi,t + α3TROPi,t + µ WHERE: µ is the error term αi = parameters Apriori Expectation: α2, α4 < 0 α0, α1, α3, >0 46 3.3.1 Vector Auto-Regression Model (Objective2) The Vector auto-regression (VAR) model is used for multivariable time series. The structure is that each of the variables is a linear function of past lags of itself and past lags of other variables and an error term. With the exclusion of restriction, these models don’t dichotomize variables into ‘endogenous’ and ‘exogenous’ (Eduardo), thus a Vector auto-regression (VAR) model is appropriate for establishing the dynamism of the relationship among public expenditure, infrastructure and economic growth. VAR modeling was and is commonly used for forecasting system of inter-related time series and for analyzing the dynamic impact of random disturbance on the system variables (Dr Wahab, Lawal FCIB A, 2011). VAR in other words describes the evolution of a set ‘k’ of variables (endogenous variables) over the same sample period (t=1…., T) as a linear function of only their past values. The mathematical representation of a VAR model is yt ο½ A1 yt ο1 ο« ... ο« ApYt ο p ο« Bxt ο« οt ....(3.00) Where; yt is a k vector of endogenous variables, xt is a d vector of exogenous variables, A1..., Ap and B are matrices of coefficients to be estimated οt is a vector of innovations that may be contemporaneously correlated but are uncorrelated with their own lagged values and uncorrelated with all of the right-hand side variables. 47 In the estimation of a VAR model, this study specifies the model as thus assuming the series are stationary at level and are cointegrated. π ππππ‘ π π = π + ∑ π1π ππππ‘−π + ∑ π2π π2π‘−π + ∑ π3π πΌππΉπ π‘−π + β π‘1 π π=1 π=1 π (3.01) π=1 π π π2π‘ = ππ + ∑ π1π ππππ‘−π + ∑ π2π π2 + ∑ π3π πΌππΉπ + β π‘2 π=1 π=1 π=1 π πΌππΉπ π‘ π π = πΌ + ∑ πΌ1π ππππ‘−π + ∑ πΌ2π π2π‘−π + ∑ π (3.02) π=1 π=1 πΌ3π πΌππΉπ π‘−π + βπ‘3 (3.03) π=1 Where: POV= Poverty M2= Broad Mone y Supply INFR=Inflation rate If all the series are non-stationary i.e. I(1) but are cointegrated based on the necessary cointegration tests. The study specifies the VECM model; π π π βππππ‘ = ππ + ∑ π1π βππππ‘−π + ∑ π2π π2 + ∑ π3π βπΌππΉπ π‘−π π=1 π=1 π π π βπ2π‘ = µπ + ∑ µ1π βππππ‘−π + ∑ µ2π π2π‘−π + ∑ µ3π πΌππΉπ π=1 π=1 (3.04) π=1 π=1 48 (3.05) π π π πΌππ π‘ = πΌπ + ∑ πΌ1π βππππ‘−π + ∑ πΌ2π βπ2π‘−π + ∑ πΌ3π βπΌππΉπ‘−π π=1 π=1 (3.06) π=1 ππ , ππ , πΌπ , π½π ππππΏπ ππππ‘βππ βπππ‘ππ’πππππ’π π‘ππππ‘πππππππππππ‘π However, if all the variables are co-integrated at I (1), the Vector Error Correction Model (VECM) is most appropriate. The dynamism of VECM makes it enjoy superiority over the previously considered models as it captures both short run and long run relationships among variables. It also indicates the direction of causality which is a major weakness of the cointegration tests, such as Granger-causality test (Granger, 1988). The model is given as: π βππππ‘ = πΌπ + ∑π=1 πΌ1π πΌππ + π2 + πΎ3 πΈπΆππ‘−1 + π1π‘ π π π π (3.7) βπ2π‘ = πΌπ + ∑π=1 πΌ1π πΌππ + ∑π=1 πΌ2π βπ2π‘−π + πΎ4 πΈπΆππ‘−1 + π2π‘ (3.8) βπΌππ π‘ = πΌπ + ∑π=1 πΌ1π πΌππ + ∑π=1 πΌ2π βπ2π‘−π + πΎ3 πΈπΆππ‘−1 + π3π‘ (3.9) ππ , ππ , πΌπ , π½π πππ πΏπ πππ π‘βπ π βπππ‘ ππ’π ππππ’π π‘ππππ‘ πππππππππππ‘π ECT= Error Correction Term Objective three is to show the effect POV=f (M2, INF, TROP) The ARDL model to capture the effect is therefore specified as follows: π π π π ππππ‘ = πΌπ + ∑ πΌ1 ππππ‘−π + ∑ πΌ2 π2π‘−π + ∑ πΌ3 πΌππΉπ π‘−π + ∑ πΌ4 ππ πππ‘−π + ππ‘ π=1 π=0 π=0 49 π=0 3.4 Estimation Techniques This study will adopt some pre-estimation test with a view to detect the appropriate econometrics techniques to use. 3.5 Source and Measurements of the data TABLE 2 Variables Definition Measurement Not having access to basic PHC essentials , or spend below 1.9$ per day considered to be poor WDI Poverty Money supply This is the measure of total money in CBN Naira /dollar the circulation Source STATISTICAL BULLETIN Percentage Inflation rate Trade openness CBN Persistence increase in the prices of goods and services Ratio of total trade to GDP STATISTICAL BULLETIN Index WDI Source: Author’s compilation 2021 The first objective of this study is to examine the trend of monetary policy, inflation and poverty in Nigeria. This will be evaluated using descriptive method, specifically graph. To evaluate the second and the third objectives, a series of pre estimation test will be carried out on the series of the study. Such pre estimation tests include: cointegration test, unit root test etc. Graphical analysis: This shows the trends in the variables under consideration, it shows the diagrammatical representation of variables. Graphical analysis further provides information about the movements as well as the description of the existence of structural breaks, trend component, discontinuities in series. 50 Descriptive method: Descriptive method is coefficients that summarize a given data set, this gives comprehensive information about the behavior and characteristics of the set of series under consideration. This includes mean, median, standard deviation, kurtosis, skewness, Jarque-Bera etc. a. Formal pre -tests: Formal preliminary tests are key in order to understand the stochastic processes that can cause problems in estimation and results are the unit root test and cointegration test. b. Unit root test This test is used to determine Stationarity of series. This test is to examine the stationarity of a series. A stationary series implies a series has a constant mean, constant variance and a constant co-variance. Hence, such series is predictable and hence stable over time. Unit root test is adopted in this study to ensure that series are not stationary at I (2) second difference, the series should be stationary at I(0), level and I(1), first difference. It examines the stability and reversion of the mean, covariance and auto- covariance off the variables. In this study, the unit root test is used to determine the order of integration - I(0) or I (1)- of the variables which helps with choosing the appropriate and suitable method of estimation. The test statistic employed here is the Augmented Dickey Fuller test statistic. The guiding hypothesis is stated below: H0: The series is not stationary H1: The series is stationary Pr<5% reject null, accept otherwise. c. Co-integration test 51 Ensuring the stationarity of series at level and first difference, co-integration test is used. Cointegration test is used to test for the long run relationship between variables. The result obtained from the unit root test is used to conduct the co-integration technique. If the series are significant at I(0) it means the variables are co-integrated, if otherwise that is if the series are significant at I(1), the approach of Engle-Granger co-integration test is adopted. If the series are significant at different orders i.e. level I(0) and difference I(1), we adopt Auto-regressive distributed lag bound co-integration test. 3.5 Post Estimation Technique The econometric model specified under this research work is a multiple linear regression model which has one dependent variable and two independent variables. Under this section, the econometric model will be estimated and the parameter estimates will be derived. The method/ technique to be used for estimation will be dependent on the outcome of the formal pre-test. Autoregressive Distributed lag (ARDL) model is use for estimating both longrun and short run when the series are of different order of integration. In this section, relevant diagnostics tests to be examined under this section include: a. Linearity Test This test is commonly used to test for general misspecifications propounded by Ramsey (1969) i.e. there is a linear relationship between the dependent variable (RGDP) and the independent variables (tax and interest rate). This test is popularly known as Regressions Specification Error Test (RESET). This test will thus be used to confirm if the model is mis-specified or not. This is because a model not properly specified will generate insignificant estimates and also a nonsignificant model. The violation of this assumption may imply that the model under 52 consideration is non-linear or incorrectly specified. The test statistic to be used for this purpose is the Ramsey Reset test. b. Normality test This test is a residual diagnostic test, that is, test on the stochastic variable. This test will be used to determine the normal distribution of the errors of the estimated regression model. This test is important as it is one of the underlining assumptions of the least square technique. Hence the violation of this assumption will generate unbiased estimates. Its violation may imply nonnormality of the error term. The test statistic to be used for this purpose is the Jarque-Bera test statistics. The hypothesis is given as: H0: The errors are normally distributed H1: The errors are not normally distributed Pr< 5% reject null i.e. not normally distributed, accept otherwise c. Heteroskedasticity test This test is to ascertain that the variance of the error term is constant overtime. It also tries to explain further the independence of the error term with respect to the explanatory variables of the regression model. This test is important to this research work as it is one of the assumptions of the classical linear regression model. Hence, this test will be carried out to ensure that the assumption of a constant variance is not violated. The violation of this assumption is an indication of the presence of heteroscedasticity in the model. The test statistic which will be used for this purpose is the Auto Regressive Lagrange Multiplier (ARCH-LM) test. The hypothesis is stated as: 53 H0: No heteroskedasticity H1: There is heteroskedasticity Pr (F-stat) < 5% reject null, that is, there is heteroskedasticity. Accept if otherwise d. Serial Correlation test This test is used to test for correlation among errors, that is, to ascertain whether the error terms are independent of one another or not. This is also one of the major assumptions of the classical linear regression model. The test statistic to be used for this purpose is the Breusch-Godfrey test. The hypothesis is stated below as: H0: No serial correlation H1: There is serial correlation Pr (F-stat) < 5% reject null, that is, there is serial correlation. Accept if otherwise e. Causality Test Causality in econometrics is somewhat different to the concept in everyday use; it refers more to the ability of one variable to predict (and therefore cause) the other. For instance, we have βπand k pair, it is possible to have that; (a) βππ‘ causes πΎπ‘, (b) πΎπ‘ causes βππ‘ , (c) there is a bi-directional feedback (causality among the variables), and finally (d) the two variables are independent. The problem is to find an appropriate procedure that allows us to test and statistically detect the cause and effect relationship among the variables. 54 3.7 Scope and Source of the Variables The variables used are: Economic Growth, foreign direct investment, public spending, and openness in Nigeria from 1989 to 2019. The data are annual and sourced from WDI, CBN statistical bulletin. 55 56 CHAPTER FOUR DATA ANALYSIS AND DISCUSSION OF FINDINGS 4.1 INTRODUCTION This chapter presents the results generated by the model specified in the previous chapter and afterwards, examines critically and analyses the results empirically. The results to be presented and analyzed include descriptive statistics and graphical analysis which belong to preliminary analysis. It also presents the regression analysis and post estimation (diagnostics) results. 4.2 Trends in Poverty, Inflation rate, and Broad money supply 4.2.1 Trend Analysis Graphical illustrations depict the movements, trend, fluctuation and discontinuities in the series. Likewise, it provides a qualitative assessment of possible relationship among series. The figures below show the graphical expressions of relevant variables. Figure 4.1 to 4.6 provided below depict movements and trends in Poverty, Money supply, Inflation rate as well as Poverty and inflation rate, Poverty and money supply and inflation rate and money supply. 57 TREND OF POVERTY REDUCTION IN PERCENTAGE Poverty 90 80 70 60 50 40 30 20 1980 1985 1990 1995 2000 2005 2010 2015 Source: Author’s Compilation 2021 The trend above shows the movement of poverty reduction in Nigeria between the periods of 1980 to 2019, there is a fluctuation in the movement of the poverty reduction over the time. The poverty level has not been stable there is reduction in poverty level between 2012 and 2013, it also increases from 2015 to 2017 as it reach peak in 2018, the poverty level in 2018 was so high as compare to the previous years. This increase in poverty level has made Nigeria to be the head quarter of poverty in the world as about 80millions Nigerians are living in extreme poverty, source from world development indicator (WDI). 58 M2 3.2E+13 2.8E+13 2.4E+13 2.0E+13 1.6E+13 1.2E+13 8.0E+12 4.0E+12 0.0E+00 1980 1985 1990 1995 2000 2005 2010 2015 Source: Author’s Compilation 2021 Figure 4.2 shown the trend of broad money supply of Nigeria from 1981to 2018. The trend exhibits an upward movement over the time in consideration. There has been an increase in money supplies which invariably help in industrial performance. The trend experienced constant movements from 1981 to 1998 and continues to rise. 59 InflationRate 80 70 60 50 40 30 20 10 0 1985 1990 1995 2000 2005 2010 2015 Figure 4.4 Trend in inflation rate for Nigeria from 1981 to 2018 Source: Author’s Compilation 2021 Figure 4.3 shows the trend of inflation rate in Nigeria from a period of 1981 to 2019. The trend depicted an oscillatory trend, meaning that there is an up and down movement in the trend. During the period inflation rate was at peak in 1995 and record a lowest inflation rate in 2007. Increase in inflation rate during this period may be as a result of increase in the volume of money in the circulation which invariably leads to increase in the price of industrial products. 60 FIGURE4.4 TRENDS OF POVERTY AND BROAD MONEY SUPPLY IN NIGERIA FROM 1980-2019 3.2E+13 2.8E+13 2.4E+13 2.0E+13 1.6E+13 1.2E+13 8.0E+12 4.0E+12 0.0E+00 1980 1985 1990 1995 2000 POV 2005 2010 2015 M2 Source: Author’s Compilation 2021 The graphs above show the trends movement in poverty and money supply in Nigeria during the periods of 1980 to 2019. From the trends it reveals that money supply rose above the money supply, the poverty level was constant through the period. With the level of poverty there was increase in money supply to suppress the level of poverty in the country that was why money supply rose above the poverty level. Money supply was constant during the periods 1980 till 61 1998, and it continues to rise as from year 2000 upward and it continues in that movement till 2019. FIGURE 4.5, TRENDS OF POVERTY AND INFLATION RATE IN NIGERIA FROM 19802019. 100 80 60 40 20 0 1980 1985 1990 1995 2000 POV 2005 2010 2015 INFR Source: Author’s Compilation 2021 The trends above depict movements in poverty and inflation rate from 1980 to 2019. It revels from the movements that poverty and inflation rate experienced sinusoidal movements which is unstable movements. This unstable may be as a result of the situation of things in the economy. Inflation cannot stop poverty also poverty cannot stop the inflation rate. Both inflation and poverty affects economy as a whole. 62 FIGURE 4.6 TRENDS OF INFLATION RATE AND MONEY SUPPLY IN NIGERIA FROM 1980-2019 3.2E+13 2.8E+13 2.4E+13 2.0E+13 1.6E+13 1.2E+13 8.0E+12 4.0E+12 0.0E+00 1980 1985 1990 1995 2000 INFR 2005 2010 2015 M2 Source: Author’s Compilation 2021 Graph above is the trends that show movements in inflation rate and broad money supply in Nigeria from 1980 to 2019. It shows from the trends that inflation rate was constant while money 63 supply rose above the inflation rate. There were upward movements in the movement of money supply, this may be as a result of government plan to expand the economy through money supply, and the money was used in a way that inflation was not raised. 4.3 Descriptive Statistics Descriptive statistics show the qualities of the data used for estimation, the knowledge of which assists in defining the appropriate methodology for estimation. The table below summarizes the descriptive statistics: Table below reveals some of the statistical properties of the selected variables for this study. The variables are Poverty (POV), Inflation rate (INFR), Money supply (M2), per capital index (PCI) and openness between 1980 and 2019. Table 4.1 Mean POV 56.61927 INFR 19.36212 M2 6.08E+12 PCI 108.1682 OPNS 13.03388 Median 55.86492 12.87658 8.68E+11 39.88000 12.9857 Maximum 88.29256 72.83550 3.04E+13 465.9600 22.81126 Minimum 22.77566 5.382224 1.52E+10 0.160000 3.029761 Std dev 18.16980 17.02816 9.05E+12 144.4240 5.349570 Skewness -0.16257 1.757736 1.338501 1.181604 -0.016634 Kurtosis 2.246459 4.946601 3.392150 2.911657 2.422370 Jargue- Bera 1.094521 26.24018 11.59018 9.087910 0.543991 0.060631 39 0.761858 39 Probability 0.048533 0.000002 Observations 39 39 Source: Author’s Compilation 2021 0.003042 39 Table 4.1 .above reveals some of the statistical properties of the selected variables for this study. The variables are Poverty (POV), Inflation rate (INFR), Money supply (M2), per capital index 64 (PCI) and Openness (OPN). Between 1980 and 2019, poverty averaged 56.61%, inflation rate (INFR) averaged 19.36%, openness (OPN), 13.03% while broad money supply recorded an average of β¦6.08E+12 billion, respectively. Between the periods considered, the highest values of INF, POV, M2, PCI and OPN, 13.0%, β¦10816789, β¦46596000 billion, 12.87% and 6.4% respectively. The lowest values however are 5.3%, 3.02%, 5.3%, 22.7% and 1.9% respectively. The standard deviation values show the extent at which the observations are dispersed around their respective means. The higher the standard deviation, the wider the dispersion. Skewness measures the asymmetry of the distribution of the series around its mean. A positive skewness means that the distribution has a long right tail and negative skewness implies that the distribution has a long left tail. The skewness of a normal distribution is zero. All variables are positively skewed except poverty and openness which are negatively skewed. Kurtosis measures the peakedness or flatness of the distribution of the series. For normal distribution the kurtosis is 3, but if it exceeds this value, the distribution is assumed to be peaked (leptokurtic) relative to the normal, but if it is less than 3, the distribution is flat (platykurtic) relative to the normal. POV,PCI and OPN are platykurtic while INFR and M2 are leptokurtic.The two tests of Skewness and Kurtosis however, are not individually sufficient in defining the distribution of the series, hence the need for Jarque-Bera normality test. Since the Jarque-Bera test combines skewness and kurtosis properties, it provides more comprehensive information. Following from the probability value of Jarque-Bera test, the null hypothesis of normality is rejected for poverty, inflation and money supply and at 5% critical level, but not rejected for PCI and OPN. However, at 1% critical level, we fail to reject the null hypothesis of normality for POV, M2, and INFR. 65 4.4 Unit Root Test The unit root test results reported in the tables below reveal that all the series are none- stationary except one as the null hypothesis that the series are non-stationary cannot be rejected at any of the chosen level of significance (1%, 5%, and 10%). This result implies that running a regression analysis on these variables in their levels using the Ordinary Least Square technique could generate spurious results as some of the fundamental least square assumptions have been violated. This study makes use of two different unit root tests, the Augmented Dickey-Fuller test (ADF) and the Phillip-Perron (PP) tests. The ADF unit root test is in table 4.while the PP unit root test is presented in table 5. From the ADF test result, all variables are non-stationary however after first differencing; the non-stationary variables are rendered stationary.POV, PCI and M2 are integrated of order one i.e. I(1) except for INF and OPN which are integrated of order zero I(0). From the PP test result in table 5, all variables are non-stationary in their level form except for poverty rate. All variables are integrated of order one i.e. I(1) except for poverty rate (POV). The decision criteria for the hypothesis states that if computed probability value exceeds the chosen significance level (in this case, 5%), we fail to reject the null hypothesis (that is we accept H0), and if the computed probability value is less than the chosen level of significance, the null hypothesis is rejected. 66 Table 4.2 Augmented Dickey-Fuller (ADF) Tests VARIABLE LEVEL FIRST DIFFERENCE I(d) Intercept Trend None Intercept Trend None and and intercept intercept POV 0.252129 -3.20328 2.284641 -5.758*** -5.75*** -5.021** I(1) M2 -2.885728 -2.74439 -0.24838 -2.57529 -2.72718 -2.594** I(1) PCI 0.644242 -2.16345 1.853643 -5.125*** -5.348** -4.706** I(1) INFR -2.884748 -4.3856* -1.897** ………… ………… ………… I(0) OPN -1.020655 -2.692** 0.286502 ………… ………… ………… I(0) *,**, *** represents 10%,5%,1% level of significance. Critical values are -3.626784, -4.234972, -3.626784, -1.951000, -3.225334 and -3.540328 at 1%, 5% and 10% significance level respectively. Source: Author’s Compilation 2021 From the unit root results in Table (ADF) it shows that (POV,M2 and PCI) are stationary at level meaning that null hypothesis cannot be rejected while (INFR and OPN) are all significant at first difference, in favour of alternative hypothesis. Table 4.3- Phillip-Perron (pp) Test VARIABLES LEVEL Intercept FIRST DIFFERENCE I(d) Trend None Intercept Trend None and and intercept intercept POV 0.296773 -3.20328 2.374896 -5.76884* -5.761** -5.0425* I(1) M2 -2.450940 -2.20408 -0.10974 -6.73127* -6.8680* -6.7896* I(0) PCI 1.270234 -1.79033 2.899179 -5.0076** -5.105** -4.7080* I(1) INFR -2.7563** -2.824** -1.7719* -9.44777* -10.340* -9.8312* I(0) OPN -5.4578* -8.457** -5.7312* ………… ………… ………… I(0) *,**, *** represents 10%,5%,1% level of significance. Critical values are -3.626784, -4.234972, -3.626784, -1.951000, -3.225334 and -3.540328 at 1%, 5% and 10% significance level respectively. Source: Author’s Compilation 2021 From the Phillip –Perron table only Poverty (POV) and per capital index (PCI) were stationary at level, while Money supply (M2), Inflation rate (INFR) and Openness (OPN) were stationary at first difference. 67 4.5 Pre-Estimation Correlation Matrix Table 4.4 INFR POV INFR POV 1 -0.18180 M2 M2 0.743839 -0.331280 1 OPN PCI 1 0.299926 1 1 OPN 0.718136 -0.354340 0.887469 PCI 0.411580 -0.98542 0.167360 Source: Author’s Computation 2021 From the results above there is a weak and negative correlation between Inflation rate and poverty level. Also there is a strong correlation between money supply and openness, inflation rate depicts a strong and strong correlation with poverty level. There is a weak and positive correlation between money supply rate and per capital index while openness shows a positive but weak correlation with poverty level. Lag Length Selection for Dependent Variable (FPI) Table 4.5 Lag LogL LR FPE AIC SC HQ 0 -150.8304 NA 269.6590 8.435021 8.479008 8.450374 1 -131.8386 35.87343 99.2525709 7.435476 7.523449 7.466181 2 -127.9846* 7.065608* 84.72685* 7.276922* 7.408882* 7.322980* 3 -127.8973 89.18138 7.327628 7.503575 7.389038 0.155189 Source: Author’s Compilation (2021) *indicates lag order selected the criterion 68 LR: Sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error. AIC: Akaike information criterion. SC: Schwarz information. HQ: Hanna-Quinn information criterion. According to LR, FPE, and AIC the optimum lag length for FPI is 2 lag period. This implies that in the ARDL equation, the optimal lag length for poverty in the equation is 2 using the AIC. 4.2.4 Cointegeration Test Before proceeding to the estimation proper, there is need to determine if there is long-run relationship among the variables. The ARDL bounds cointegration test result is presented in the table 6.below Following the mixed order of integration of the series as reported under the unit root section, the ARDL Bounds cointegration test proves most appropriate to determine if there is long-run relationship between food price inflation and the selected determinant variables. The test provides two critical values to be checked against the F-statistic value in order to make conclusion on either the rejection of the null hypothesis of no cointegration among the series, or otherwise. If the F-statistic exceeds the upper critical bound, i.e. I(1) bound, at the chosen significance level, then the null hypothesis is rejected. If the F-statistic gives a value below the lower critical bound, i.e. I(0) bound, the null hypothesis is accepted. Inconclusive is the decision if it fall between the I(0) and I(1) critical bounds. Table 4.1.6 presents the ARDL bounds test results , the F-statistic value which is approximately 5.6 is greater than the I(1) critical bound 69 hence, there is long-run relationship among the variables. long run estimate Following this cointegration test result, the study presents both the short run and of the ARDL technique. Table: 4.6. Result of Bounds Cointegration Test Test Statistic Value K F-statistic 5.567220 4 Significance I0 Bound I1 Bound 10% 2.75 3.79 5% 3.12 4.25 2.5% 3.49 4.67 1% 3.93 5.23 Critical Value Bounds Source: Author’s Compilation (2021) 70 4.3 Direction of Causality among POV, INFR, M2 Table: 4.7. VAR Causality Model Pairwise Granger Causality Tests Date: 01/02/10 Time: 18:38 Sample: 1980 2019 Lags: 2 Table 4.7 Null Hypothesis: LM2 does not Granger Cause LPOV LPOV does not Granger Cause LM2 INFR does not Granger Cause LPOV LPOV does not Granger Cause INFR INFR does not Granger Cause LM2 LM2 does not Granger Cause INFR Source: Author’s Computation 2021 Obs F-Statistic Prob. 38 1.21254 0.3104 0.45759 0.6368 0.08250 0.9210 0.41471 0.6639 1.11948 4.17581 0.3385 0.0242 38 38 Results of the granger causality above shows that money supply does not cause poverty, also inflation rate does not granger caused money supply but there was granger causality between money supply and inflation rate. Effect of Globalization, Institutional Quality on Poverty Reduction in Nigeria. This subsection presents the result obtained from estimating the ARDL short run dynamic and long-run models. 71 Table: 4.8.Short Run (Dynamic) and Long Run (Static) Model Result Variable Coefficient Std. Error T-Statistic Prob. D(INFR) 0.009378 0.049103 0.190996 0.8506 D(M2) -0.358784 0.098612 -3.638339 0.0017 D(PCI) -0.917523 0.431994 -2.123924 0.0470 D(OPN) 0.848671 0.392141 2.164197 0.0434 ECT(-1) -1.216224 0.211233 -5.757746 0.0000 Source: Author’s Computation 2021 Result of the short run model shows that inflation rate (INFR), is positive but insignificant to influence the level of poverty in Nigeria. Broad money supply was negative but significant to influence the level of poverty rate; this means that a unit changes in broad money supply will bring about a unit change in poverty. Also from the result per capital index was negative but significant to change the level of poverty in Nigeria. Openness was positive and significant to influence the level of poverty in Nigeria, this implies that if Nigeria trade with other countries the level of poverty will reduce. A unit changes in the degree of openness will bring about a unit change in the level of poverty in the country. 72 Table: 4.9 Long Run (Static) Model Result VARIABLES COEFFICIENT STD. T.STATISTICS PROBABILITY ERROR INFR -0.006630 0.057207 -0.115886 0.9090 M2 0.049855 0.029113 1.712451 0.1031 PCI -0.537253 0.0992214 5.826165 0.0000 OPN -0.754403 0.404924 -1.863072 0.0780 CONSTANT 11.310687 4.557790 2.481617 0.0226 Source: Author’s Computation 2021 R-square 0.917331 Fstatistic probability 14.05556(0.000000) Adjusted R-square 0.852067 Durbin Watson statistsics 1.99000 Results from the long run shows that only per capital income (PCI) was significant in the long run to influence the level of poverty, result shows that money supply was positive but insignificant in the long run. Money supply was only significant in the short run. The ARDL model has overall goodness of fit as the probability value of F-Statistic is less than 5% significance level, which informs rejection of the null hypothesis that model, has no goodness of fit. Durbin-Watson statistic of 1.99 is close to 2. It is a sign of absence of serial correlation. R-square of 0.852067 shows that 85.2% of total variation in unemployment is jointly explained by the model. 73 4.6 TEST OF HYPOTHESIS HYPOTHESIS I There is no significant relationship between money supply and poverty, result from the ARDL shows that money supply was significant in the short run, but insignificant in the long run. In this case the null hypothesis can be rejected in favour of alternative hypothesis. HYPOTHESISII Second Hypothesis states that there is no granger causality among money supply, inflation rate and poverty level. From the granger causality results it reveals that there was no causality among money supply, inflation rate and poverty, causality only runs from money supply to inflation rate. The null hypothesis cannot be rejected in this case. HYPOTHESIS III Hypothesis three states that there money supply and inflation rate do not affect poverty level. Results reveal that both money supply and inflation rate have positive but insignificant effect on poverty level. 4.7 Discussion of Findings Result of the short run model shows that inflation rate (INFR), is positive but insignificant to influence the level of poverty in Nigeria. Broad money supply was negative but significant to influence the level of poverty rate; this means that a unit changes in broad money supply will bring about a unit change in poverty. Also from the result per capital index was negative but significant to change the level of poverty in Nigeria. Openness was positive and significant to influence the level of poverty in Nigeria, this implies that if Nigeria trade with other countries 74 the level of poverty will reduce. A unit changes in the degree of openness will bring about a unit change in the level of poverty in the country. Also from the long run Results from the long run it shows that only per capital income (PCI) was significant in the long run to influence the level of poverty, result shows that money supply was positive but insignificant in the long run. Money supply was only significant in the short run. From the granger causality result, there was no causality between money supply and inflation, causality runs from money supply to inflation rate, meaning that increase in money supply will increase the level of inflation in the country. Causality also runs from per capital index to poverty level. If there is improve in per capital index it will reduce the level of poverty in the country. Post Estimation Diagnostic Tests Sequel to the adoption of the ARDL technique, for any estimated model to be valid, there are some certain assumptions that are needed to be verified. The table below shows the result of the test on these assumptions Table: 11. Diagnostic Test Result S/N TEST Test statistic(Prob) 1. Jarque-Bera Normality Test 1.059833(0.588654) 2. Breusch-Godfrey Serial Correlation LM Test 0.000838(0.9992) 3. Heteroskedasticity Test (Breusch- pagan -godfrey) 0.766702(0.0581) 4. Linearity test (Ramsey RESET) 1.202067(0.3483) Source: Author’s Compilation (2021) 75 4.4.1 Normality Test The Jarque-Bera normality test shows if the residual of the estimated ARDL model comes from a population that is normally distributed. As the probability value exceeds 5% significance level, we fail to reject the null hypothesis that residuals are normally distributed. 4.4.2 Serial correlation Test The LM test statistic seeks to investigate presence of serial correlation of the residuals. The null hypothesis of no serial correlation is not rejected as probability value exceeds 5% significance level. Hence residuals are not serially correlated. 4.4.3 Heteroskedasticity Test The ARCH-LM test statistic, whose probability value exceeds 5% significance level, indicates presence of homoscedasticity. Thus, the hypothesis of constant variance cannot be rejected. 4.4.4 Linearity Test The Linearity test suggests that ARDL model is well specified, and it follows an appropriate linear form, as the probability value exceeds the 5% critical level. Thus, the null hypothesis that model is well specified cannot be rejected. 76 CHAPTER FIVE SUMMARY, CONCLUSION AND RECOMMENDATIONS 5.1 Summary of the Study This paper examined the effect of monetary policy and inflation on poverty in Nigeria. The research was divided into five (5) chapters. Chapter one comprised of background to the study, statement of the research problem, research questions, research objectives, research hypothesis, and justification for the study, scope and limitation of the study, organization of the study as well as definition of terms; wherein key concepts of monetary policy and poverty were defined Chapter two was divided into three major sections: The conceptual framework, empirical framework and theoretical framework. Under the conceptual framework, reasons for increasing or decreasing in banks deposit were itemise among others. The advantages, disadvantages and effects of banks deposit were also elaborately explained. Thereafter was the empirical review in which works of past authors concerning the subject matter in developed countries, developing countries as well as in Nigeria were reviewed and critically appraised. The theoretical framework comprised of theories such as the Mundell-Fleming model, monetarist theory among others. Chapter three comprised of the research methodology which began with a restatement of the hypothesis, model specification, estimation technique, Nature and sources of data, Limitation of the methodology and a priori expectations Chapter four was dedicated to data analysis and discussion of the findings made. First, preliminary estimation analyses were carried out; including descriptive statistics, graphical 77 analysis, correlation analysis, unit root test as well as cointegration test. As the preliminary estimations would suggest, the autoregressive distributed lag (ARDL) model was adopted for the purpose of estimation. The results were interpreted and the research hypotheses were tested accordingly. The findings made were also linked to previous research works to see the extent to which findings were consistent. Chapter five comprised of summary, conclusion and policy recommendations. 5.2 Major Findings of the Study Having adopted the ECM-based ARDL for estimation, some major findings were made in this study, which include the following: i. Only per capital income was significant in the long run to influence or change the level of poverty in Nigeria ii. In the short run inflation rate was positive but insignificant while broad money supply was negative but significant iii. In the long run broad money supply was positive but insignificant but was significant in the short run only iv. From the granger causality test, there was causality between per capital index and poverty but there was also causality between money supply and inflation 5.3 Conclusions of the Study Based on the above findings made by the study, the following conclusions were surmised: i. Poverty is one of the most serious challenges faced by the developing countries like Nigeria. Reducing poverty is one of the most important targets of the Millennium 78 Development Goals of the United Nations. However for reducing poverty, it is imperative to understand the factors that cause poverty. ii. The long run relationship (cointegration) which exists among the variables implies that these macroeconomic variables will adjust to long-run equilibrium iii. Per capital income is an important factor in curbing poverty as its significant in the short and long run iv. Money supply is another factor that determines the level of poverty as it depicts a positive impact on the poverty level. 5.4 Policy Recommendations i. This paper recommended that inflation should be targeted, in other words double-digit inflation rate should be avoided. Although findings have revealed that inflation is of no significant effect on growth pattern, it should however be noted that unnecessarily high inflation rate could cause uncertainties to producers and investors, and could lead to economic instability. ii. The study recommends that the federal government through the monetary authorities should regulate monetary policy rate downwardly to encourage foreign and private investment in the country. This is because it will in turn boost productivity and reduced poverty level in Nigeria. iii. The government should channel its resources to the provision of basic amenities and infrastructures such as power, good roads etc., such that the citizens can benefit and the long-run effect being increased productivity and a higher standard of living. iv. The issue of corruption has to be tackled holistically in order to ensure that all efforts by government towards eradicating poverty in Nigeria are achieved 79 5.5 Suggestions for Further Study Findings and conclusions made in this study, however plausible they may seem, also may have their own limitations hence further research could improve upon them. The author therefore noted a few other ways through which findings could be improved: i. By expanding the scope of study up to 2019 data, further research could provide more information about the effect of monetary policy and inflation rate on poverty level in Nigeria. ii. Further research interests could also take asymmetry into consideration, since positive shocks to a variable could have different impact on other macroeconomic variables. In this wise, the non-linear ARDL technique was suggested iii. Further studies could also increase the sample size by making use of high frequency dataset, which could actually provide more valid results and might lead to better conclusions. 80 APPENDIX DATA YEARS POV INFR OPN M2 PCI IM EX GDP 1980 22.77566 20.81282 19.19614 1.44E+10 6.11E+10 19.19614 29.37517 6.42E+10 1981 25.16948 20.8128 9.581643 1.52E+10 5.95E+10 9.581643 8.590083 1.64E+11 1982 25.4806 7.69775 7.086126 1.67E+10 5.03E+10 7.086126 6.693707 1.43E+11 1983 28.70973 23.2123 4.511421 1.90E+10 3.48E+10 4.511421 5.533548 9.71E+10 1984 30.58066 17.8205 3.029761 2.12E+10 2.77E+10 3.029761 6.350781 7.35E+10 1985 26.35516 7.43535 3.295156 2.32E+10 2.79E+10 3.295156 7.096823 7.37E+10 1986 37.25208 5.71715 3.886755 2.36E+10 1.93E+10 3.886755 1987 50.22472 11.2903 6.647678 2.89E+10 2.17E+10 6.647678 12.84766 5.27E+10 1988 47.90396 54.5112 5.771463 3.84E+10 2.28E+10 5.771463 11.16915 4.96E+10 1989 52.02132 50.4667 8.931843 4.34E+10 2.21E+10 8.931843 25.25077 4.4E+10 1990 45.45457 7.3644 9.949967 5.76E+10 2.79E+10 9.949967 20.97477 5.4E+10 1991 46.57096 13.007 12.77474 7.91E+10 2.49E+10 12.77474 24.24687 4.91E+10 1992 44.44074 44.5888 14.25264 1.29E+11 2.64E+10 14.25264 23.97475 4.78E+10 1993 49.71078 57.1653 13.65321 1.98E+11 1.34E+10 13.65321 20.06654 2.78E+10 1994 56.84969 57.0317 1995 59.27368 72.8355 15.37256 3.19E+11 2.63E+10 15.37256 24.15582 4.41E+10 1996 55.86492 29.2683 17.23303 3.7E+11 3.28E+10 17.23303 1997 61.90011 8.52987 22.81126 4.3E+11 3.36E+10 22.81126 28.64975 5.45E+10 1998 64.67334 9.99638 21.13452 5.26E+11 2.92E+10 21.13452 18.14409 5.46E+10 1999 71.69717 6.61837 2000 74.26178 6.93329 12.97233 1.04E+12 4.02E+10 12.97233 36.02327 6.94E+10 2001 55.08743 18.8737 21.42954 1.31E+12 2002 57.78472 12.8766 16.79545 1.56E+12 5.3E+10 16.79545 23.23972 9.54E+10 2003 51.11944 14.0318 22.58358 1.77E+12 6E+10 22.58358 26.75138 1.05E+11 2004 50.97169 14.998 11.64207 2.13E+12 2005 50.00458 17.8635 2006 70.96248 8.23953 13.05043 3.56E+12 1.41E+11 13.05043 29.51613 2.36E+11 2007 52.75417 5.38222 18.10059 5.88E+12 1.55E+11 18.10059 21.23634 2.76E+11 2008 75.48682 11.578 15.12676 9.32E+12 1.93E+11 15.12676 25.67007 3.37E+11 2009 59.99067 11.5377 17.42837 1.09E+13 1.55E+11 17.42837 18.63034 2.92E+11 9.50999 2.67E+11 1.57E+10 13.1235 7E+11 3.44E+10 9.50999 13.54925 3.38E+10 23.0247 5.11E+10 13.1235 21.33433 5.94E+10 4E+10 21.42954 28.25096 7.8E+10 11.64207 12.0255 2.61E+12 9.89E+10 81 5.24909 5.48E+10 7.4E+10 20.2538 1.36E+11 12.0255 21.03396 1.76E+11 2010 76.88418 13.7202 17.66015 1.17E+13 2011 83.73758 10.8408 21.66102 1.32E+13 3.89E+11 21.66102 31.61694 2012 88.29256 12.217 12.98578 1.59E+13 4.39E+11 12.98578 31.54659 4.59E+11 2013 76.50933 8.47583 12.99895 1.74E+13 4.89E+11 12.99895 18.04991 5.15E+11 2014 79.13477 8.05738 12.45007 1.82E+13 2015 78.33146 9.01768 10.79023 1.87E+13 4.68E+11 10.79023 10.6567 4.95E+11 2016 70.96248 15.6969 11.50441 2.09E+13 3.96E+11 11.50441 9.21811 4.05E+11 2017 64.67334 3.5E+11 17.66015 25.66061 3.63E+11 4.1E+11 5.5E+11 12.45007 18.43513 5.68E+11 16.5 13.17604 2.59E+13 3.64E+11 13.17604 13.17156 3.76E+11 12.1 10.18645 3.04E+13 3.79E+11 1.02E+01 1.52E+01 3.97E+11 13.75 10.18906 3.05E+13 3.75E+11 10.18906 12.3471 3.93E+11 2018 88.29256 2019 89.3467 SOURCE: WORLD DEVELOPMENT INDICATOR AND CENTRAL BANK STATISTICAL BULLETIN 2019. Date: 01/02/10 Time: 18:09 Sample: 1980 2019 POV PCI OPN M2 INFR Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis 57.43745 56.35731 89.34670 22.77566 18.66692 -0.139352 2.224948 1.46E+11 5.17E+10 5.50E+11 1.34E+10 1.68E+11 1.109122 2.626532 12.91275 12.97906 22.81126 3.029761 5.316583 0.044860 2.423041 6.16E+12 8.68E+11 3.05E+13 1.44E+10 9.16E+12 1.403064 3.741637 19.22181 12.94178 72.83550 5.382224 16.83184 1.797076 5.105855 Jarque-Bera Probability 1.130637 0.568179 8.433475 0.014747 0.568220 0.752684 14.04063 0.000894 28.92092 0.000001 Sum Sum Sq. Dev. 2297.498 13589.70 5.82E+12 1.10E+24 516.5102 1102.376 2.46E+14 3.27E+27 768.8725 11049.13 Observations 40 40 40 40 40 82 Pairwise Granger Causality Tests Date: 01/02/10 Time: 18:38 Sample: 1980 2019 Lags: 2 Null Hypothesis: Obs F-Statistic Prob. LM2 does not Granger Cause LPOV LPOV does not Granger Cause LM2 38 1.21254 0.45759 0.3104 0.6368 INFR does not Granger Cause LPOV LPOV does not Granger Cause INFR 38 0.08250 0.41471 0.9210 0.6639 INFR does not Granger Cause LM2 LM2 does not Granger Cause INFR 38 1.11948 4.17581 0.3385 0.0242 LPOV LPCI LOPN LM2 INFR LPOV LPCI LOPN LM2 INFR 1.000000 0.584689 0.499548 0.855726 -0.122219 0.584689 1.000000 0.292637 0.848231 -0.454447 0.499548 0.292637 1.000000 0.523570 -0.038775 0.855726 0.848231 0.523570 1.000000 -0.303109 -0.122219 -0.454447 -0.038775 -0.303109 1.000000 ARDL Bounds Test Date: 01/02/10 Time: 18:33 Sample: 1981 2019 Included observations: 39 Null Hypothesis: No long-run relationships exist Test Statistic Value k F-statistic 2.694342 4 I0 Bound I1 Bound Critical Value Bounds Significance 83 10% 5% 2.5% 1% 2.45 2.86 3.25 3.74 3.52 4.01 4.49 5.06 Test Equation: Dependent Variable: D(LPOV) Method: Least Squares Date: 01/02/10 Time: 18:33 Sample: 1981 2019 Included observations: 39 Variable Coefficient Std. Error t-Statistic Prob. C LPCI(-1) LOPN(-1) LM2(-1) INFR(-1) LPOV(-1) 1.785005 -0.082117 -0.020380 0.088261 1.41E-05 -0.516297 0.835156 0.048400 0.058746 0.033324 0.001608 0.144284 2.137331 -1.696631 -0.346922 2.648567 0.008741 -3.578335 0.0401 0.0992 0.7309 0.0123 0.9931 0.0011 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.289891 0.182298 0.147358 0.716578 22.59958 2.694342 0.037822 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 0.035047 0.162959 -0.851261 -0.595328 -0.759434 2.229533 Dependent Variable: LPOV Method: ARDL Date: 01/02/10 Time: 18:32 Sample (adjusted): 1981 2019 Included observations: 39 after adjustments Maximum dependent lags: 4 (Automatic selection) Model selection method: Akaike info criterion (AIC) Dynamic regressors (4 lags, automatic): LPCI LOPN LM2 INFR Fixed regressors: C Number of models evalulated: 2500 Selected Model: ARDL(1, 0, 0, 0, 0) Note: final equation sample is larger than selection sample Variable Coefficient Std. Error t-Statistic Prob.* LPOV(-1) LPCI LOPN 0.524342 -0.058826 -0.031754 0.152304 0.054029 0.070558 3.442733 -1.088790 -0.450046 0.0016 0.2841 0.6556 84 LM2 INFR C R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.079259 0.000636 1.289453 0.840439 0.816264 0.149900 0.741509 21.93267 34.76359 0.000000 0.035555 0.001644 0.862401 2.229212 0.386969 1.495191 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 0.0327 0.7013 0.1444 4.011804 0.349706 -0.817060 -0.561127 -0.725233 2.328085 *Note: p-values and any subsequent tests do not account for model selection. Pairwise Granger Causality Tests Date: 01/02/10 Time: 18:38 Sample: 1980 2019 Lags: 2 Null Hypothesis: Obs F-Statistic Prob. LM2 does not Granger Cause LPOV LPOV does not Granger Cause LM2 38 1.21254 0.45759 0.3104 0.6368 INFR does not Granger Cause LPOV LPOV does not Granger Cause INFR 38 0.08250 0.41471 0.9210 0.6639 INFR does not Granger Cause LM2 LM2 does not Granger Cause INFR 38 1.11948 4.17581 0.3385 0.0242 85 7 Series: Residuals Sample 1981 2019 Observations 39 6 5 4 3 2 1 0 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 Dependent Variable: LPOV Method: ARDL Date: 01/02/10 Time: 18:32 Sample (adjusted): 1981 2019 Included observations: 39 after adjustments Maximum dependent lags: 4 (Automatic selection) Model selection method: Akaike info criterion (AIC) Dynamic regressors (4 lags, automatic): LPCI LOPN LM2 INFR Fixed regressors: C Number of models evalulated: 2500 Selected Model: ARDL(1, 0, 0, 0, 0) Note: final equation sample is larger than selection sample Variable Coefficient Std. Error t-Statistic Prob.* LPOV(-1) LPCI LOPN LM2 INFR C 0.524342 -0.058826 -0.031754 0.079259 0.000636 1.289453 0.152304 0.054029 0.070558 0.035555 0.001644 0.862401 3.442733 -1.088790 -0.450046 2.229212 0.386969 1.495191 0.0016 0.2841 0.6556 0.0327 0.7013 0.1444 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.840439 0.816264 0.149900 0.741509 21.93267 34.76359 0.000000 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 86 4.011804 0.349706 -0.817060 -0.561127 -0.725233 2.328085 Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis 4.26e-16 0.007807 0.274066 -0.284872 0.139690 -0.191580 2.326794 Jarque-Bera Probability 0.975027 0.614152 *Note: p-values and any subsequent tests do not account for model selection. Breusch-Godfrey Serial Correlation LM Test: F-statistic Obs*R-squared 1.335433 3.093588 Prob. F(2,31) Prob. Chi-Square(2) 0.2778 0.2129 Test Equation: Dependent Variable: RESID Method: ARDL Date: 01/02/10 Time: 18:34 Sample: 1981 2019 Included observations: 39 Presample missing value lagged residuals set to zero. Variable Coefficient Std. Error t-Statistic Prob. LPOV(-1) LPCI LOPN LM2 INFR C RESID(-1) RESID(-2) 0.264307 0.036149 -0.000467 -0.046471 -0.000101 -0.677629 -0.405879 0.057992 0.356286 0.074871 0.070507 0.070298 0.001670 1.277828 0.414578 0.266949 0.741840 0.482809 -0.006627 -0.661061 -0.060547 -0.530297 -0.979018 0.217238 0.4638 0.6326 0.9948 0.5135 0.9521 0.5997 0.3352 0.8294 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.079323 -0.128572 0.148399 0.682691 23.54426 0.381552 0.906063 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 4.26E-16 0.139690 -0.797142 -0.455898 -0.674706 1.938992 Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic Obs*R-squared Scaled explained SS 1.466234 7.089198 3.367204 Prob. F(5,33) Prob. Chi-Square(5) Prob. Chi-Square(5) Test Equation: Dependent Variable: RESID^2 Method: Least Squares 87 0.2273 0.2141 0.6436 Date: 01/02/10 Time: 18:35 Sample: 1981 2019 Included observations: 39 Variable Coefficient Std. Error t-Statistic Prob. C LPOV(-1) LPCI LOPN LM2 INFR 0.200206 -0.019869 -0.011289 -0.003775 0.007281 -0.000533 0.123901 0.021881 0.007762 0.010137 0.005108 0.000236 1.615862 -0.908029 -1.454316 -0.372377 1.425336 -2.255455 0.1156 0.3704 0.1553 0.7120 0.1635 0.0309 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.181774 0.057801 0.021536 0.015305 97.60204 1.466234 0.227331 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 88 0.019013 0.022187 -4.697540 -4.441608 -4.605714 1.864476 Reference A Policymaker’s Guide to the Literature. World Development Report, 1994, Vol. 22, Issue 4, pp. 567 –578.CBN Statistical Bulletins (Various). Adigwe, P. K, Echekoba F.N, Justus B.C Onyeagba (2015), Monetary Policy and Economic Agénor, P.R., 2005. The Macroeconomics of Poverty Reduction. Manchester School, 73(4): 369434.21. Aiyedogbon, J. O. and Ohwofasa, B. O. (2012). Poverty and youth Unemployment in Nigeria, 1987-2011. International Journal of Business and Social Science. Akcay et al (1996). Budget Deficit, Money Supply and Inflation: Evidence from Low and High Frequency Data for Turkey Bogazici University, Department of Economics. Akinboade, et al (2004), the determinants of Inflation in South Africa: An Econometric analysis. AERC Research paper 143. African Econolmic Research Consort ium, Nairobi. Alfandega, E. M. (2017). Theories Of Poverty Reduction As They Apply To The Gorongosa Case Study In Alleviating Poverty Through Local Resources And Initiatives. Catholic University of Mozambique. Amaechi, A. E. and Amara, T. C. 2005. Manual of Resource Methodology and Thesis Writing. Ker Experts Book Limited, Aba. Aminu U.V and Anono A.Z (2012) Effect of Inflation on the Growth and Development of the Nigerian Economy (An Empirical Analysis)International Journal of Business and Social Science Vol. 3 No. 10 Antai, A. S. 2007. In search for a corrupt free nation –a new paradigm for sustained development in Nigeria. Blackwood, D. L. and Lynch, R. G., 1994. The Measurement of Inequality Central Bank of Nigeria Statistical Bulletin, 1980-2012. www.cenbank.org Chimaobi, O. P. and Igwe, O. L. (2010): “Budget Deficit, Money Supply and Inflation in Nigeria. Europe a Journal of Economics, Finance and Administrative Science. 89 Chukwu, et al (2010). Cointegration and Structural Breaks in Nigerian Long-Run Money Demand Function. International Research Journal of Financeand Economics. ISSN 14502887 Issue 38 Daniel, A. 2011. Experimental Poverty Measures. Summary of a Workshop Paper presented at the Committee on National Statistics (CNSTAT). Dickey, D. A. and Fuller, W. A. (1979). “Distribution of the estimators for autoregressive times series with a unit root.” Journal of American Statistical Association,74:427-431. Gbadebo A.D and Mohammed N.U (2015).Monetary Policy and Inflation Control in Nigeria.Journal of Economics and Sustainable Development Vol.6, No.8, 2015. Iyeli, I. I., 2010. Empirical Econometrics: A guide to Policy Modeling. Pearl Publishers, Port Harcourt. Khan, H.G.A., Khan, A.D., Ahmad, A. and Siraj, A.E. (2011). Financial sector development and poverty reduction. Global Journal of Management and Business Research 11(5), 1-23. Kirkpatrick,C. and H. Jalilian, 2005. Can Financial Development Contribute to Poverty Reduction in Developing Countries?.Journal of Development Studies, 41(4): 636-356.22. Lawrence O.U, Odimgbe S.O, Ezeabalisi V.N and Alajekwu U.B, (2018) Effect of Monetary Policy on Economic Growth in Nigeria(AN EMPIRICAL INVESTIGATION) Vol 1 (590-591) Mahbub UL Itaq 1997. Speeches of Dr. Mahbub Ul Haq. Global Issues: Towards a More compassionate Society. State of the World Forum, 8 November, 1997.National Bureau of Statistics (2011) Bulletin. Mbutor, M.O.and Ibrahim A. U. (2013).The impact of financial inclusion on monetary policy in Nigeria. Journal of Economics and International Finance,5(8), 318-326 Mbutor, M.O.and Ibrahim A. U. (2013).The impact of financial inclusion on monetary policy in Nigeria. Journal of Economics and International Finance,5(8), 318-326 90 Musibau A.B and Muhammed I.S (2011) Money Supply, Inflation and Economic Growth in Nigeria Money Supply, Inflation and Economic Growth in Nigeria. Asian-African Journal of Economics and Econometrics, Vol. 11, No. 1, 2011: 221-223. Nwigwe, C.A., Omonona, B.T. and Okoruwa, V.O. (2012). Microfinance and poverty reduction in Nigeria: A critical assessment. Australian Journal of Business and Management Research, 2(4),33-40. Odhiambo, N.M. (2010).Financial deepening and poverty reduction in Zambia; An Empirical Investigation. International Journal of Social Economics, 37(1),41-53. Ogbonna, B. M and Uma, K. E (2017) Monetary Policy, Inflation and Economic Growth in Nigeria.International Journal of Research in Management, Economics and Commerce, Vol 07, Issue 10 (126-128) Onakoya, A.B. and Onakoya, A.O. (2014). Alternative financial inclusion strategy: Islamic expectations from Ogun sub-national government, Nigeria. Singaporean Journal of Business Economics and Management Studies 2(11), 11-20. Onaolapo, A. R. (2015). Effects of financial Inclusion on the economic growth of Nigeria. International Journal of Business and Management Review, 3,(8),11-28. Onwuteaka I.C, Okoye, P. V. C and Molokwu I.M (2019) Effect of Monetary Policy on Economic Growth in Nigeria. International Journal of Trend in Scientific Research and Developmntt (IJTSRD) Onwuteaka I.C, Okoye, P. V. C and Molokwu I.M (2019) Effect of Monetary Policy on Economic Growth in Nigeria. International Journal of Trend in Scientific Research and Developmntt (IJTSRD) Precious and Palesa (2014) The Game of Monetary Policy, Inflation and Economic GrowthOpen Journal of Social Sciences, 2019, No 1, 255-251 Rodriguez, R. A. (2015). Classical versus Keynesian Theory of Unemployment: An approach to the Spanish labor market. 91 Sarah, B. and Lloyd, S. (2008). Remittances, Poverty Reduction and Informalisation in Zimbabwe 2005-6: a political economy of dispossession? Brooks World Poverty Institute. Smith, N. (2008). Uneven Development: Nature Capital and the Production of Space. University of Georgia Press. Stephen, D., Paul, L. and Emanuela, L. (2003). The Labour Market Effects of remittances. Syed, T. J. and Syed, A. R. (2014). Effects of Workers’ Remittances and its Volatility on Economic Growth in South Asia. International organization for migration. Taylor, J. E., Mora, J.and Adams, R. (2005). Remittances, Inequality and Poverty: Evidence from Rural Mexico. American Agricultural Economics Association. Tehseen, J. and Syed, A. R. (2014). Effects of Workers' Remittances and its Volatility on Economic Growth in South Asia. international institute of migration World Bank, 2005. World Development Report 2005:A Better Investment Climate for Everyone. Washington DC: The World Bank.23.Bourguignon, F., 2006. From income to endowments: The difficult task of expanding the income poverty paradigm. 92