effects of phillips curve on the nigerian economy

CHAPTER ONE
INTRODUCTION
1.1 Background of the Study In Nigeria, there have been problems in achieving macroeconomics objectives. The problem inherent in achieving the macroeconomics objectives are inflation, unemployment, low investment, poverty, low foreign reserve (i.e. deficit balance of trade). After the independence of Nigeria in 1960, Agriculture was the livewire of Nigerian economy, Nigeria being an agrarian nation can’t de-emphasize the importance of agriculture not only to her economy but also to general well being of the populace. The basic importance of agriculture in Nigeria include but not restricted to provision of food for all, provides employment for about 70% of the populace, source of family and national income, generate savings both external and internal revenue among others. Agriculture which was the livewire of Nigerian economy has suffered from mismanagement, inconsistent and poorly conceives government policies, neglect and the lack of basic infrastructure. Nigerian is no longer a major exporter of cocoa, groundnuts, rubber and palm oil. The agriculture sector failed in meeting the adequacy in foreign exchange reserve due to high imports and prevalence of oil export which led to massive unemployment in Nigeria. The oil boom of the 1970s led Nigeria to ignoring its agricultural products and highly dependent on oil. Due to the prevalence of oil, the foreign exchange reduced drastically hence leading to the federal government earning most of its income from oil export. In light of the high expansionary public sector fiscal policies in 2001, the government sought ways to head of higher inflation thus leading to the implementation of stronger monetary policies.
The decline in agricultural export, decline in industrialization, dependence on oil are causes for slow economic growth in Nigeria. From the research on agriculture and oil boom, it reveal that unemployment and inflation are the two major pests eating deep into the macro economics objectives. “Inflation is the general increase in prices of goods and services in an economy” (CBN 2008), inflation is also an economic parasites caused by high demand for goods in relation to supply thereby raising to prices of the few goods, weak monetary policy hence inflation sucks the economy of Nigeria as it reduces the value of money. Unemployment on the other hand could be defined as the economic situation when people are having no work or are seeking for active work to involve themselves in. This economic parasite could be caused by high level of literacy, low investment, weak monetary policy and fiscal policy, low foreign direct investment (Batini,2004). Over the years, the problem of inflation and unemployment has been concurrent. These two economic problems affect the growth of any economy in the world. Some scholars see them as so correlated or related that the occurrence of one variable affects or reduces the other. This led to Phillips curve
1.2 Statement of the Problem According to Phillips, there is a negative relationship between inflation and unemployment, this relationship is referred to as ‘Phillips Curve’. This study shall examine the theories of Phillips Curve whether truly there is a negative relationship between unemployment and inflation in Nigeria. This study shall also examine the shifting of Phillips Curve as postulated by Keynes. According to the study by Keynes ‘There is bound to be shocks in an economy whereby one of unemployment and inflation would be affected without necessarily affecting the other.

YEAR
UNEMPLOYMENT RATE
INFLATION RATE
2000
6.9
18.1
2001
18.9
13.7
2002
12.9
12.2
2003
14.0
14.8
2004
15.0
11.8
2005
17.8
11.9
2006
8.2
13.7
2007
5.4
14.6
2008
11.6
14.9
2009
12.4
19.9
Source: CBN Statistical Bulletin
Evidence from Nigeria shows the relationship between unemployment and inflation rate from 2000 - 2009 .

From the above, it is clearly seen there seems to be no relationship between unemployment and inflation rate which tries to negate the Philips position. Bearing the foregoing in mind, the study will therefore test whether there is a relationship between unemployment and inflation. From the study, the following research questions will be asked
1. What is the relationship between inflation and unemployment in Nigeria
2. What macroeconomics policies could be adopted to control inflation and unemployment

1.3 Objective of the Study The main objective of this study is to test the existence of Phillips curve in Nigeria. The other objectives to be examined in the study are ;
1. To examine the causes and consequences of unemployment in Nigeria
2. To examine the relationship between unemployment and inflation in Nigeria

1.4 Justification of the Study This study will be relevant to the government, students, and other microeconomics units. The study would assist government in getting insight into the prevention of inflation and unemployment. The recommendation in this study would pinpoint area of balance between inflation and unemployment through defined models. This study would assist students of Economics in knowing the impart or effect of Phillips curve, its applicability in Nigerian economy, the study would give insight to consumers, companies as to the effects of inflation in the Nigerian economy on consumption and savings.

1.5 Scope of the Study This study shall be limited to some specific areas. These areas are inflation, recession, unemployment, the effect of inflation and unemployment in Nigeria, oil boom in Nigeria, control against inflation, relationship existing between inflation and output gap in Nigeria. Thus this study shall examine the importance of Phillips curve in Nigeria and review of Phillips curve as related to Nigeria.

1.6 Organization of the Study This study will be made up of five (5) chapters and they are outlined below
Chapter one will be the introduction of the study
Chapter two will be conceptual framework and review of related literature
Chapter three will be the research methodology
Chapter four will be the data presentation and analysis finding
Chapter five will be conclusion and recommendation.

1.7 Definition of Terms
(a) Agrarian : Promoting the interest of farmers especially by seeking a more equitable basis of landownership
(b) Macroeconomics : Study of large scale economics system, a branch of economics that focuses on the general features and processes that make up a national economy and the ways in which different segments of the economy are connected
(c) Parasites : a plant or animal that lives on or in another, usually larger, host organism in a way that harms or is of no advantage to the host
(d) Microeconomics : the study of particular aspects of an economy
(e) Inflation : an increase in the supply of currency or credit relative to the availability of goods and services, resulting in higher prices and a decrease in the purchasing power of money
(f) Unemployment : the number of people who are unemployed in an area, often given as a percentage of the total labor force
(g) Phillips Curve : a hypothetical relationship between the rate of wage increases and the rate of unemployment according to which the one rises as the other falls
(h) Monetary policy : a government 's or central bank 's policy for control of the amount of currency available and the rate at which people can borrow money
(i) Fiscal policy : the way a government attempts to manage the economy through taxation, spending, and borrowing
(j) Nairu : non-accelerating inflation rate of unemployment
(k) Agriculture: the occupation, business, or science of cultivating the land, producing crops, and raising livestock
(l ) Exports : to send goods for sale or exchange to other countries
(m) Import: to bring something or cause something to be brought in from another country, usually for commercial or industrial purposes
(n) Balance of trade: the difference between the value of the total imports and total exports of a country as assessed over a fixed period
(o ) Deficit : the amount by which expenditures exceed income or budget
(p) Poverty: the state of not having enough money to take care of basic needs such as food, clothing, and housing

CHAPTER TWO
CONCEPTUAL FRAMEWORK AND REVIEW OF LITERATURE

2.1. Introduction This chapter is detailed examination of papers studies and work carried out previously by different authors in relation to testing the existence of Phillips curve in Nigeria and other related topics. In view of this, this chapter will be further broken down into different sub-headings for the sake of understanding and in-depth knowledge about the subject matter.
2.2 Conceptual Framework
Inflation is a problem in all facets of life and in all economic entities. The government of any nation is concerned with the responsibility of ensuring that her plans and programs are not frustrated by unpredictable and galloping prices. Every firm desires a stable macro-economic environment that is devoid of unrepentant price change that can bring about reliable forecast and planning. An individual also strives that he is not worse off by unexpected price increase. All these bring home the need to explore the study of inflation so as to form a timeless and dependable model of its tendency (Taiwo, 2011). Inflation has been seen by the classical economist as fundamentally a monetary phenomenon and can be produced only by a more rapid increase in the quantity of money than output. Johnson defines inflation as a sustained rise in prices. Broeman defines inflation as a continuing increase in the general price level. Shagnre defines it as a persistent and appreciable rise in the general price level. Dernberg and Macdougall are more explicit when they write that the term usually refers to a continuing rise in prices as measured by the index such as the consumer price index (CPI) or by implicit price deflator for gross national product.
2.2.1 TYPES OF INFLATION There are four main types of inflation
1. Demand Pull or Excess Demand The most important inflation is called demand-pull or excess demand inflation. It occurs when the total demand for goods and services in an economy exceeds the available supply, so the prices for them rise in a market economy. Historically this has been the most common type and at times the most serious. Every war produces this type of inflation because demand for war materials and manpower grows rapidly without comparable shrinkage elsewhere. Other types of inflation occur more readily in conjunction with demand-pull inflation.
2. Cost-Push Inflation Another type of inflation is called cost-push inflation. The name suggests the cause--costs of production rise, for one reason or another, and force up the prices of finished goods and services. Often a rise in wages in excess of any gains in labor productivity is what raises unit costs of production and thus raises prices. This is less common than demand-pull, but can occur independently as well as in conjunction with it.
3. Administered Price Inflation A third type of inflation could be called pricing power inflation, but is more frequently called administered price inflation. It occurs whenever businesses in general decide to boost their prices to increase their profit margins. This does not occur normally in recessions but when the economy is booming and sales are strong. It might be called oligopolistic inflation, because it is oligopolies that have the power to set their own prices and raise them when they decide the time is ripe. One can at such times read in the newspapers that business is just waiting a bit to see how soon they might raise their prices. An oligopolistic firm often realizes that if it raises its prices, the other major firms in the industry will likely see that as a good time to widen their profit margins too without suffering much from price competition from the few other firms in the industry.
4. Sectoral Inflation The fourth type is called sectoral inflation. The term applies whenever any of the other three factors hits a basic industry causing inflation there, and since the industry hit is a major supplier of many other industries, as for example steel is, or oil is, that raises costs of the industries using say steel or oil, and forces up prices there also, so inflation becomes more widespread throughout the economy, although it originated in just one basic sector. 2.2.2 What Sorts Of Policies Might Each Type of Inflation Call For? For oligopolistic inflation, make sure there is no collusion which antitrust law makes illegal. It is likely not possible to induce oligopolies to be more price competitive with each other, so the only way to get the benefit os price competition to restrain oligopolistic inflation is to increase import competition if that is a possibility.
Since cost-push inflation is often wage increases exceeding increases in labor productivity, the problem is whether it is possible or desirable to restrain such wage increases. The fact of the matter is, many wage rates now leave the worker or the worker & family in poverty. It would be difficult to argue that those wages should not rise to what is called a living wage level even though that may cause price increases for all who already have higher incomes. But what about other wage earners. Should all of them, or all whose wages are above average (but still below that of others) be restrained somehow from wage increases that exceed the gains in their own labor productivity? If nobody else is restrained and profits are ballooning, would that be fair?
Some European economies have wrestled with this problem more than others. They have sometimes come up with what is called an incomes policy, essentially a bargain between business and labor that neither wages nor profits shall gain more than the other for some agreed period, and that both shall be relatively restrained. University of Minnesota economist Walter Heller at one time proposed what he called wage-price guidelines for the same purpose, and others have suggested tax policies to enforce such bargains between labor and business. Europe’s bargains often broke down because business conditions improved and profits grew more than was in the bargain and labor refused to restrain itself as much as originally agreed to. There is presently no agreed upon policy to deal with cost-push inflation. Demand pull inflation can appropriately and successfully be dealt with by a sufficiently aggressive macro-economic policy: tight monetary and fiscal policies to cut out the excess demand. Tight money & high interest rates to cut borrowing and slow or stop increases in the money supply, and running a government budget surplus if necessary to reduce incomes and purchasing power. It is usually not employed vigorously enough to do the job, but it always could be and stop this type of inflation. But if applied to any of the other types of inflation it would likely create or increase unemployment and would not get at the root cause of that inflation.
Another angle to be mentioned is that these several types of inflation can all work at the same time. A familiar term is a wage-price spiral, where demand pull likely starts inflation, labor demands and gets wage increases to catch up to the rising cost of living, which increase their incomes and adds more demand-pull. That is a good time for oligopolies to raise prices, and any of these hitting key sectors ads further inflation. Such an inflation can become cumulative and produces what is called hyperinflation or run-away inflation. Prices may rise so fast that when labor gets paid it quits work and rushes to the stores to buy things needed before their prices rise even further. At the extreme some countries with such inflation have in the end had to repudiate their currency and start anew with another money which they issue more sparingly to stop the inflation. No one in their right mind would ever risk hyperinflation, so the problem is to know how much inflation can be allowed without running the risk of hyperinflation. That will vary country by country and situation by situation, and no one knows the answer anytime. So the risk should not be run.
But slow inflation does not pose the risk for this country. Inflation of 3% a year even increases business profits and stimulates business because it buys materials and labor at one price level and by the time its products are on the market they can be sold at a slightly higher price level. The problem is to keep inflation from creeping upwards from that rate. And if it is continuous for a lifetime, people who struggle to save as much as they can for retirement find that the purchasing power of their savings is being reduced by 3% a year.

2.2.3 Causes of Inflation
1. The Money Supply
Inflation is primarily caused by an increase in the money supply that outpaces economic growth. Ever since industrialized nations moved away from the gold standard during the past century, the value of money is determined by the amount of currency that is in circulation and the public’s perception of the value of that money. When the Federal Reserve decides to put more money into circulation at a rate higher than the economy’s growth rate, the value of money can fall because of the changing public perception of the value of the underlying currency. As a result, this devaluation will force prices to rise due to the fact that each unit of currency is now worth less. One way of looking at the money supply effect on inflation is the same way collectors value items. The rarer a specific item is, the more valuable it must be. The same logic works for currency; the less currency there is in the money supply, the more valuable that currency will be. When a government decides to print new currency, they essentially water down the value of the money already in circulation. A more macroeconomic way of looking at the negative effects of an increased money supply is that there will be more dollars chasing the same amount of goods in an economy, which will inevitably lead to increased demand and therefore higher prices.
2. The National Debt
We all know that high national debt in the U.S. is a bad thing, but did you know that it can actually drive inflation to higher levels over time? The reason for this is that as a country’s debt increases, the government has two options: they can either raise taxes or print more money to pay off the debt. A rise in taxes will cause businesses to react by raising their prices to offset the increased corporate tax rate. Alternatively, should the government choose the latter option, printing more money will lead directly to an increase in the money supply, which will in turn lead to the devaluation of the currency and increased prices (as discussed above).

3. Demand-Pull Effect
The demand-pull effect states that as wages increase within an economic system (often the case in a growing economy with low unemployment), people will have more money to spend on consumer goods. This increase in liquidity and demand for consumer goods results in an increase in demand for products. As a result of the increased demand, companies will raise prices to the level the consumer will bear in order to balance supply and demand.
An example would be a huge increase in consumer demand for a product or service that the public determines to be cheap. For instance, when hourly wages increase, many people may determine to undertake home improvement projects. This increased demand for home improvement goods and services will result in price increases by house-painters, electricians, and other general contractors in order to offset the increased demand. This will in turn drive up prices across the board.
4. Cost-Push Effect
Another factor in driving up prices of consumer goods and services is explained by an economic theory known as the cost-push effect. Essentially, this theory states that when companies are faced with increased input costs like raw goods and materials or wages, they will preserve their profitability by passing this increased cost of production onto the consumer in the form of higher prices.
A simple example would be an increase in milk prices, which would undoubtedly drive up the price of a cappuccino at your local Starbucks since each cup of coffee is now more expensive for Starbucks to make.
5. Exchange Rates
Inflation can be made worse by our increasing exposure to foreign marketplaces. In America, we function on a basis of the value of the dollar. On a day-to-day basis, we as consumers may not care what the exchange rates between our foreign trade partners are, but in an increasingly global economy, exchange rates are one of the most important factors in determining our rate of inflation.
When the exchange rate suffers such that the U.S. currency has become less valuable relative to foreign currency, this makes foreign commodities and goods more expensive to American consumers while simultaneously making U.S. goods, services, and exports cheaper to consumers overseas.
This exchange rate differential between our economy and that of our trade partners can stimulate the sales and profitability of American corporations by increasing their profitability and competitiveness in overseas markets. But it also has the simultaneous effect of making imported goods (which make up the majority of consumer products in America), more expensive to consumers in the United States.
2.2.4 Determinants and Effects of Inflation in Nigeria The causes of Nigerian inflation for some time period could be traced to several studies such as Tegene (1989), Baro (1995), Moser (1995), Bruno and Easterly (1998), Erbaykal and Okuyan (2008), Awogbemi and Ajao (2011) among others. Changes in money supply, credit to government by banking system, government deficit expenditure, industrial production and food price indices are underlined factors that contribute to inflationary tendencies in Nigeria. Increase in government expenditure financed by monetization of oil revenue and credit from banking system could also be responsible for the expansion of money supply which in turn (with lagged effect) contributes to inflationary tendencies.
Growth in the money supply is another determinant of inflation. When money supply growth increases substantially, inflation also increases and when there is a decline in monetary growth rate, there is a strong relationship between increase in money supply and inflation. Rising cost of goods are often taken to be counter-productive and negative to an economy. The most significant effect of inflation is its impact on the revenues of the government. When it is higher than previously planned and thought, the revenues of the government will increase. Inflation is also responsible for inefficiencies and non-performance of an economy. It makes budgeting and future planning difficult for economic agents and imposes a drag on productivity, particularly when firms are forced to shift resources away from products and services thereby discouraging investment and retarding growth (Orubu,2009).

2.2.5 Ways to Combat Inflation
1. Spend Money on Long-term Investments.
We all love to save. But when it comes to long-term investments, sometimes spending money now can allow you to benefit from inflation down the road. As an example, let’s say you are looking to take out a mortgage to purchase a home and economists project significant inflation over the next 50 years. When you consider you can repay the mortgage down the line with inflated dollars that are worth less than they are now, then you are using inflation to your benefit. Other areas where you can take advantage of inflation include home improvement projects, capital expenditures for a business, or other major investments.

2. Invest in Commodities.
Commodities, like oil, have an inherent worth that is resilient to inflation. Unlike money, commodities will always remain in demand and can act as an excellent hedge against inflation. For most of us, however, purchasing commodities in the open marketplace is probably too much of a daunting task. In that case, you can consider commodity-based Exchange Traded Funds (ETFs) which offer the liquidity of stocks with the inflation hedging power of commodity investment. Just be careful of and watch out for the problems of ETFs.
3. Invest in Gold and Precious Metals.
Gold, silver, and other precious metals, like commodities, have an inherent value that allows them to remain immune to inflation. In fact, gold used to be the preferred form of currency before the move to paper currency took place. With that said, even precious metals are liable to being a part of speculative bubbles.
4. Invest in Real Estate.
Real estate has also historically offered an inflationary hedge. The old saying goes: “land is the one thing they aren’t making any more of.” Investing in real estate provides a real asset. In addition, rental property can offer the landlord the option of increasing rent prices over time to keep pace with inflation. Plus, there’s the added alternative of the ability to sell the real assets in the open market for what normally amounts to a return that generally keeps pace with or outstrips inflation. However, just like with precious metals, we all know that real estate bubbles can and do exist.

5. Consider TIPS.
Treasury Inflation Protected Securities (TIPS) are guaranteed to return your original investment along with whatever inflation was during the lifetime of the TIPS. But TIPS do not offer the opportunity for significant capital appreciation, and therefore should only make up a portion of your personal investment portfolio allocation.
6. Stick with Equities.
Although investing in bonds may feel safer, historically, bonds have failed to outpace inflation, and have at times been crushed during hyper-inflationary periods. Over the long term, the only source of inflation-beating returns has been the stock market. Equities have historically beat bonds because of the ability of corporations to pass price increases along to their consumers, resulting in higher income and returns for both the company and its investors.
7. Consider Dividend-Paying Stocks.
Exhaustive research by Wharton School of Business economist Jeremy Siegel reveals that large cap, dividend paying stocks have provided an inflation-adjusted 7% per year return in every period greater than 20 years since 1800. If you have the investment risk tolerance for the volatility and a time horizon of greater than 20 years until retirement, consider dividend-paying securities. Dividend stocks offer a hedge against inflation because dividends normally increase on an annual basis at a rate which outpaces that of inflation. This almost guarantees stock price appreciation at a similar pace, while offering the further benefit of compounding when dividends are reinvested.

8. Save More.
The fact is that you are probably going to need a lot more money for retirement than you think you will. There are two ways to get to your new benchmark: Save more, or invest more aggressively. Saving more is probably the easiest and most proactive thing you can do to ensure your ability to fund a comfortable retirement. If you are saving $250 a month, could you save $500 a month if you ate out a few less times and carpooled to work? Chances are, you could and this will help protect you from future inflation. See some of these planning strategies for how much to save for retirement based on age.
9. Invest in Collectibles.
Who would have believed the return on investment you could have gotten from the purchase of a Mark McGwire rookie card during his first year in Major League Baseball, or a Limited-Edition G.I. Joe in its original packaging? Buying and selling collectibles can actually offer great inflation-adjusted returns, while also being a fun and interesting hobby.
10. Become a Patron of the Arts.
The strategic acquisition of photography, paintings, sculptures and other art can often provide inflation-beating returns, though certainly not always. My suggestion would be to find the best of both worlds, a valuable piece of fine art that you truly appreciate and will not be in a hurry to sell.
2.3.1 Unemployment Unemployment is defined as a situation where someone of working age is not able to get a job but would like to be in full time employment. Unemployment occurs when a person who is actively searching for employment is unable to find work. Unemployment is often used as a measure of the health of the economy. The most frequently cited measure of unemployment is the unemployment rate. This is the number of unemployed persons divided by the number of people in the labor force
Economists distinguish between various overlapping types of and theories of unemployment, including cyclical or Keynesian unemployment, frictional unemployment, structural unemployment and classical unemployment. Some additional types of unemployment that are occasionally mentioned are seasonal unemployment, hardcore unemployment, and hidden unemployment. Though there have been several definitions of "voluntary" and "involuntary unemployment" in the economics literature, a simple distinction is often applied. Voluntary unemployment is attributed to the individual 's decisions, whereas involuntary unemployment exists because of the socio-economic environment (including the market structure, government intervention, and the level of aggregate demand) in which individuals operate. In these terms, much or most of frictional unemployment is voluntary, since it reflects individual search behavior. Voluntary unemployment includes workers who reject low wage jobs whereas involuntary unemployment includes workers fired due to an economic crisis, industrial decline, company bankruptcy, or organizational restructuring. On the other hand, cyclical unemployment, structural unemployment, and classical unemployment are largely involuntary in nature. However, the existence of structural unemployment may reflect choices made by the unemployed in the past, while classical (natural) unemployment may result from the legislative and economic choices made by labour unions or political parties. So, in practice, the distinction between voluntary and involuntary unemployment is hard to draw. The clearest cases of involuntary unemployment are those where there are fewer job vacancies than unemployed workers even when wages are allowed to adjust, so that even if all vacancies were to be filled, some unemployed workers would still remain. This happens with cyclical unemployment, as macroeconomic forces cause microeconomic unemployment which can boomerang back and exacerbate these macroeconomic forces.
1. Classical Unemployment
Classical or real-wage unemployment occurs when real wages for a job are set above the market-clearing level, causing the number of job-seekers to exceed the number of vacancies. Many economists have argued that unemployment increases the more the government intervenes into the economy to try to improve the conditions of those without jobs. For example, minimum wage laws raise the cost of laborers with few skills to above the market equilibrium, resulting in people who wish to work at the going rate but cannot as wage enforced is greater than their value as workers becoming unemployed. Laws restricting layoffs made businesses less likely to hire in the first place, as hiring becomes more risky, leaving many young people unemployed and unable to find work.
However, this argument is criticized for ignoring numerous external factors and overly simplifying the relationship between wage rates and unemployment. In other words, that other factors may also affect unemployment. Some, such as Murray Rothbard, suggest that even social taboos can prevent wages from falling to the market clearing level.

2. Cyclical Unemployment Cyclical or Keynesian unemployment, also known as deficient-demand unemployment, occurs when there is not enough aggregate demand in the economy to provide jobs for everyone who wants to work. Demand for most goods and services falls, less production is needed and consequently fewer workers are needed, wages are sticky and do not fall to meet the equilibrium level, and mass unemployment results. Its name is derived from the frequent shifts in the business cycle although unemployment can also be persistent as occurred during the Great Depression of the 1930s. With cyclical unemployment, the number of unemployed workers exceeds the number of job vacancies, so that even if full employment were attained and all open jobs were filled, some workers would still remain unemployed. Some associate cyclical unemployment with frictional unemployment because the factors that cause the friction are partially caused by cyclical variables. For example, a surprise decrease in the money supply may shock rational economic factors and suddenly inhibit aggregate demand. Keynesian economists on the other hand see the lack of demand for jobs as potentially resolvable by government intervention. One suggested interventions involves deficit spending to boost employment and demand. Another intervention involves an expansionary monetary policy that increases the supply of money which should reduce interest rates which should lead to an increase in non-governmental spending.
3. Marxian Theory of Unemployment
It is in the very nature of the capitalist mode of production to overwork some workers while keeping the rest as a reserve army of unemployed paupers. — Marx, Theory of Surplus Value, Marxists also share the Keynesian viewpoint of the relationship between economic demand and employment, but with the caveat that the market system 's propensity to slash wages and reduce labor participation on an enterprise level causes a requisite decrease in aggregate demand in the economy as a whole, causing crises of unemployment and periods of low economic activity before the capital accumulation (investment) phase of economic growth can continue.
According to Karl Marx, unemployment is inherent within the unstable capitalist system and periodic crises of mass unemployment are to be expected. The function of the proletariat within the capitalist system is to provide a "reserve army of labor" that creates downward pressure on wages. This is accomplished by dividing the proletariat into surplus labor (employees) and under-employment (unemployed). This reserve army of labor fights among themselves for scarce jobs at lower and lower wages. At first glance, unemployment seems inefficient since unemployed workers do not increase profits. However, unemployment is profitable within the global capitalist system because unemployment lowers wages which are costs from the perspective of the owners. From this perspective low wages benefit the system by reducing economic rents. Yet, it does not benefit workers. Capitalist systems unfairly manipulate the market for labour by perpetuating unemployment which lowers laborers ' demands for fair wages. Workers are pitted against one another at the service of increasing profits for owners. According to Marx, the only way to permanently eliminate unemployment would be to abolish capitalism and the system of forced competition for wages and then shift to a socialist or communist economic system. For contemporary Marxists, the existence of persistent unemployment is proof of the inability of capitalism to ensure full employment.
4. Structural Unemployment Okun 's Law is known as ‘The gap version’ and it states that for every one percent increase in the unemployment rate,a country’s GDP will be roughly an additional two percent lower than its potential GDP which interprets unemployment as a function of the rate of growth in GDP.
Structural unemployment occurs when a labour market is unable to provide jobs for everyone who wants one because there is a mismatch between the skills of the unemployed workers and the skills needed for the available jobs. Structural unemployment is hard to separate empirically from frictional unemployment, except to say that it lasts longer. As with frictional unemployment, simple demand-side stimulus will not work to easily abolish this type of unemployment. Structural unemployment may also be encouraged to rise by persistent cyclical unemployment: if an economy suffers from long-lasting low aggregate demand, it means that many of the unemployed become disheartened, while their skills (including job-searching skills) become "rusty" and obsolete. Problems with debt may lead to homelessness and a fall into the vicious circle of poverty. This means that they may not fit the job vacancies that are created when the economy recovers. The implication is that sustained high demand may lower structural unemployment. This theory of persistence in structural unemployment has been referred to as an example of path dependence or "hysteresis". Much technological unemployment, due to the replacement of workers by machines, might be counted as structural unemployment. Alternatively, technological unemployment might refer to the way in which steady increases in labor productivity mean that fewer workers are needed to produce the same level of output every year. The fact that aggregate demand can be raised to deal with this problem suggests that this problem is instead one of cyclical unemployment. As indicated by Okun 's Law, the demand side must grow sufficiently quickly to absorb not only the growing labor force but also the workers made redundant by increased labor productivity.
5. Seasonal Unemployment Seasonal unemployment may be seen as a kind of structural unemployment, since it is a type of unemployment that is linked to certain kinds of jobs (construction work, migratory farm work). The most-cited official unemployment measures erase this kind of unemployment from the statistics using "seasonal adjustment" techniques. The resulting in substantial, permanent structural unemployment. 6. Frictional Unemployment Frictional unemployment is the time period between jobs when a worker is searching for, or transitioning from one job to another. It is sometimes called search unemployment and can be voluntary based on the circumstances of the unemployed individual. Frictional unemployment is always present in an economy, so the level of involuntary unemployment is properly the unemployment rate minus the rate of frictional unemployment, which means that increases or decreases in unemployment are normally under-represented in the simple statistics. Frictional unemployment exists because both jobs and workers are heterogeneous, and a mismatch can result between the characteristics of supply and demand. Such a mismatch can be related to skills, payment, work-time, location, seasonal industries, attitude, taste, and a multitude of other factors. New entrants (such as graduating students) and re-entrants (such as former homemakers) can also suffer a spell of frictional unemployment. Workers as well as employers accept a certain level of imperfection, risk or compromise, but usually not right away; they will invest some time and effort to find a better match. This is in fact beneficial to the economy since it results in a better allocation of resources. However, if the search takes too long and mismatches are too frequent, the economy suffers, since some work will not get done. Therefore, governments will seek ways to reduce unnecessary frictional unemployment through multiple means including providing education, advice, training, and assistance such as daycare centers.
The frictions in the labour market are sometimes illustrated graphically with a Beveridge curve, a downward-sloping, convex curve that shows a correlation between the unemployment rate on one axis and the vacancy rate on the other. Changes in the supply of or demand for labor cause movements along this curve. An increase (decrease) in labor market frictions will shift the curve outwards (inwards).
7. Hidden Unemployment Hidden, or covered, unemployment is the unemployment of potential workers that is not reflected in official unemployment statistics, due to the way the statistics are collected. In many countries only those who have no work but are actively looking for work (and/or qualifying for social security benefits) are counted as unemployed. Those who have given up looking for work (and sometimes those who are on Government "retraining" programs) are not officially counted among the unemployed, even though they are not employed. The same applies to those who have taken early retirement to avoid being laid off, but would prefer to be working. As well, persons on disability benefits do not count as unemployed. The statistic also does not count the "underemployed" — those working fewer hours than they would prefer or in a job that doesn 't make good use of their capabilities. In addition, those who are of working age but are currently in full-time education are usually not considered unemployed in government statistics. Traditional unemployed native societies, who survive by gathering, hunting, herding, and farming in wilderness areas, may or may not be counted in unemployment statistics. Official statistics often underestimate unemployment rates because of hidden unemployment.
8.Long-term unemployment This is normally defined, for instance in European Union statistics, as unemployment lasting for longer than one year. It is an important indicator of social exclusion. The United States Bureau of Labor Statistics (BLS) reports this as 27 weeks or longer. Long-term unemployment can result in older workers taking early retirement; in the United States, taking reduced social security benefits at age 62.
2.3.2 Ways To Measure Unemployment There are also different ways national statistical agencies measure unemployment. These differences may limit the validity of international comparisons of unemployment data. To some degree these differences remain despite national statistical agencies increasingly adopting the definition of unemployment by the International Labor Organization. To facilitate international comparisons, some organizations, such as the OECD, Eurostat, and International Labor Comparisons Program, adjust data on unemployment for comparability across countries. Though many people care about the number of unemployed individuals, economists typically focus on the unemployment rate. This corrects for the normal increase in the number of people employed due to increases in population and increases in the labor force relative to the population. The unemployment rate is expressed as a percentage, and is calculated as follows: As defined by the International Labor Organization, "unemployed workers" are those who are currently not working but are willing and able to work for pay, currently available to work, and have actively searched for work. Individuals who are actively seeking job placement must make the effort to: be in contact with an employer, have job interviews, contact job placement agencies, send out resumes, submit applications, respond to advertisements, or some other means of active job searching within the prior four weeks. Simply looking at advertisements and not responding will not count as actively seeking job placement. Since not all unemployment may be "open" and counted by government agencies, official statistics on unemployment may not be accurate. In the United States, for example, the unemployment rate does not take into consideration those individuals who are not actively looking for employment, such as those still attending college.
The ILO describes 4 different methods to calculate the unemployment rate:
1. Labour Force Sample Surveys are the most preferred method of unemployment rate calculation since they give the most comprehensive results and enables calculation of unemployment by different group categories such as race and gender. This method is the most internationally comparable.
2. Official Estimates are determined by a combination of information from one or more of the other three methods. The use of this method has been declining in favor of Labour Surveys.
3. Social Insurance Statistics such as unemployment benefits, are computed base on the number of persons insured representing the total labour force and the number of persons who are insured that are collecting benefits. This method has been heavily criticized due to the expiration of benefits before the person finds work.
4. Employment Office Statistics are the least effective being that they only include a monthly tally of unemployed persons who enter employment offices. This method also includes unemployed who are not unemployed per the ILO definition.
The primary measure of unemployment allows for comparisons between countries. Unemployment differs from country to country and across different time periods. For example, during the 1990s and 2000s, the United States had lower unemployment levels than many countries in the European Union, which had significant internal variation, with countries like the UK and Denmark outperforming Italy and France. However, large economic events such as the Great Depression can lead to similar unemployment rates across the globe. Eurostat, the statistical office of the European Union, defines unemployed as those persons age 15 to 74 who are not working, have looked for work in the last four weeks, and ready to start work within two weeks, which conform to ILO standards. Both the actual count and rate of unemployment are reported. Statistical data are available by member state, for the European Union as a whole (EU27) as well as for the euro area (EA16). Eurostat also includes a long-term unemployment rate. This is defined as part of the unemployed who have been unemployed for an excess of 1 year.
The main source used is the European Union Labour Force Survey (EU-LFS). The EU-LFS collects data on all member states each quarter. For monthly calculations, national surveys or national registers from employment offices are used in conjunction with quarterly EU-LFS data. The exact calculation for individual countries, resulting in harmonized monthly data, depend on the availability of the data.
The Bureau of Labor Statistics measures employment and unemployment (of those over 15 years of age) using two different labour force surveys conducted by the United States Census Bureau (within the United States Department of Commerce) and/or the Bureau of Labor Statistics (within the United States Department of Labor) that gather employment statistics monthly. The Current Population Survey (CPS), or "Household Survey", conducts a survey based on a sample of 60,000 households. This Survey measures the unemployment rate based on the ILO definition. The Current Employment Statistics survey (CES), or "Payroll Survey", conducts a survey based on a sample of 160,000 businesses and government agencies that represent 400,000 individual employers. This survey measures only civilian nonagricultural employment; thus, it does not calculate an unemployment rate, and it differs from the ILO unemployment rate definition. These two sources have different classification criteria, and usually produce differing results. Additional data are also available from the government, such as the unemployment insurance weekly claims report available from the Office of Workforce Security, within the U.S. Department of Labor Employment & Training Administration. The Bureau of Labor Statistics provides up-to-date number. The BLS also provides a readable concise current Employment Situation Summary, updated monthly.
U1–U6 from 1950–2010, as reported by the Bureau of Labor Statistics
The Bureau of Labor Statistics also calculates six alternate measures of unemployment, U1 through U6, that measure different aspects of unemployment
U1: Percentage of labor force unemployed 15 weeks or longer.
U2: Percentage of labor force who lost jobs or completed temporary work.
U3: Official unemployment rate per the ILO definition occurs when people are without jobs and they have actively looked for work within the past four weeks.
U4: U3 + "discouraged workers", or those who have stopped looking for work because current economic conditions make them believe that no work is available for them.
U5: U4 + other "marginally attached workers", or "loosely attached workers", or those who "would like" and are able to work, but have not looked for work recently.
U6: U5 + Part-time workers who want to work full-time, but cannot due to economic reasons (underemployment).
Note: "Marginally attached workers" are added to the total labour force for unemployment rate calculation for U4, U5, and U6. The BLS revised the CPS in 1994 and among the changes the measure representing the official unemployment rate was renamed U3 instead of U5. The unemployment rate is included in a number of major economic indexes including the United States ' Conference Board 's Index of Leading Indicators a macroeconomic measure of the state of the economy

2.3.3 Limitations Of The Unemployment Definition
Some critics believe that current methods of measuring unemployment are inaccurate in terms of the impact of unemployment on people as these methods do not take into account the 1.5% of the available working population incarcerated in U.S. prisons (who may or may not be working while incarcerated), those who have lost their jobs and have become discouraged over time from actively looking for work, those who are self-employed or wish to become self-employed, such as tradesmen or building contractors or IT consultants, those who have retired before the official retirement age but would still like to work (involuntary early retirees), those on disability pensions who, while not possessing full health, still wish to work in occupations suitable for their medical conditions, those who work for payment for as little as one-hour per week but would like to work full-time.
These people are "involuntary part-time" workers, those who are underemployed, e.g., a computer programmer who is working in a retail store until he can find a permanent job, involuntary stay-at-home mothers who would prefer to work, and graduate and Professional school students who were unable to find worthwhile jobs after they graduated with their Bachelor 's degrees.
2.4 Phillips Curve In economics, the Phillips curve is a historical inverse relationship between the rate of unemployment and the rate of inflation in an economy. Stated simply, lower unemployment is correlated with higher rate of inflation. While there is a short run tradeoff between unemployment and inflation, it has been observed in the long run. Accordingly the Phillip curve is now seen as too simplistic with the unemployment rate supplanted by more accurate predictors of inflation based on velocity of money supply measure such as the ‘MONEY ZERO MATURITY’ which is affected by unemployment in the short run but not in the long term. William Phillip ‘the relation between unemployment and the rate of change of money wage rates in the united kingdom (1861-1957) which was published in the quarterly journal Economica. In the paper Phillips describes how he observed an inverse relationship between money wage changes and unemployment in the British economy over the period examined. Similar patterns were found in other countries and in 1960 Paul Samuelsson and Robert Solow took Phillips’ work and made explicit the link between inflation and unemployment; when inflation is high, unemployment was low and vice versa. In the years following Phillips’1958 paper, many economists in the advanced industrial countries believed that his result showed that there was a permanently stable relationship between inflation and unemployment.

2.5 Inflation And Unemployment The concept of inflation has been define as a persistence rise in the general price level of broad spectrum of goods and services in a country over a long period of time. Inflation has been intrinsically linked to money, as captured by the often heard maxim, inflation is too much money chasing too few goods. Hamilton (2001) inflation has been widely described as an economic situation when the increase in money supply is faster than the new production of goods and services in the same economy. Piana (2001) economists usually try to distinguish inflation from an economic phenomenon of a onetime increase in prices or when there are price increases in a narrow group of economic goods or services. Ojo (2000) and Mel berg (1992) the term inflation describes a general and persistent increase in the prices of goods and services in an economy. According to the classical view of inflation, inflation is caused by the alterations in the supply of money. When the money supply goes up the price level of various commodities goes up as well. The increase in the level of prices is known as inflation. According to the classical economists there is a natural rate of unemployment, which may also be called the equilibrium level of unemployment in a particular economy. This is known as the long term Phillips curve. The long term Phillips curve is basically vertical as inflation is not meant to have any relationship with unemployment in the long term. It is therefore assumed that unemployment would stay at a fixed point irrespective of the status of inflation. The Keynesians have a different point of view compared to the Classics. The Keynesians regard inflation to be an aftermath of money supply that keeps on increasing. They deal primarily with the institutional crises that are encountered by people when they increase their price levels. As per their argument the owners of the companies keep on increasing the salaries of their employees in order to appease them. They make their profit by increasing the prices of the services that are provided by them. This means there has to be an increase in the money supply so that the economy may keep on functioning. In order to meet this demand the government keeps on providing more money so that it can keep up with the rate of inflation. Inflation is defined as a generalized increase in the level of price sustained over a long period in an economy (Adebayo, 1997). Unemployment has been categorized as one of the serious impediments to social progress. Apart from representing a colossal waste of a country’s manpower resources, it generates welfare loss in terms of lower output thereby leading to lower income and well-being (Raheem, 1993). Unemployment is a very serious issue in Africa (Bello, 2003) and particularly in Nigeria (Oladeji, 1994 and Umo, 1996).
2.6 Literature Review
Two major goals of interest to economic policy makers are low inflation and low unemployment, but quite often, these goals conflict. This trade-off between inflation and unemployment is described as the Phillips curve. This was an empirical discovery by Phillips (1958), which showed an inverse relationship between wage and unemployment rates. The discovery is strengthened by the fact that movement in the money wages could be explained by the level and changes of unemployment. An argument in favor of the Phillips curve is the extension that establishes a relationship between prices and unemployment. This rests on the assumption that wages and prices move in the same direction. The strength of the Phillips curve is that it captures an economically important and statistically reliable empirical relationship between inflation and unemployment
Gokal and Subrina (2004) say like many countries, industrialized and developing, one of the most fundamental objectives of macroeconomic policies in Fiji is to sustain high economic growth together with low inflation. However, there has been considerable debate on the nature of the inflation and growth relationship. This paper reviewed several different economic theories to ascertain consensus on the inflation – growth relationship. Classical economics recalls supply-side theories, which emphasize the need for incentives to save and invest if the nation 's economy is to grow. Keynesian theory provided the AD-AS framework, a more comprehensive model for linking inflation to growth. Monetarism reemphasized the critical role of monetary growth in determining inflation, while Neoclassical and Endogenous Growth theories sought to account for the effects of inflation on growth through its impact on investment and capital accumulation. The paper also reviews recent empirical literature. This includes Studies by Sarel (1996), Andres & Hernando (1997) and Ghosh & Phillips (1998) and Khan & Senhadji (2001) amongst others. Ultimately, we tested whether a meaningful relationship held in Fiji’s case. The tests revealed that a weak negative correlation exists between inflation and growth, while the change in output gap bears significant bearing. The causality between the two variables ran one-way from GDP growth to inflation. Sani (2006) re-examines the issue of the existence and the level of inflation threshold in the relationship between inflation and growth in Nigeria, using three different approaches that provide appropriate procedures for estimating the threshold level and inference. While Sarel’s (1996) approach provides a threshold point estimate of 9.9 per cent that was not well identified by the data, the technique of Khan and Senhadji (2001) identifies a 10.5 per cent inflation threshold as statistically significant to explain the inflation-growth nexus in Nigeria. Also, the approach of Drukker et al (2005) suggests a two threshold point model with 11.2 and 12.0 per cent as the appropriate inflation threshold points. These results suggest that the threshold level of inflation above which inflation is inimical to growth is estimated at 10.5 to 12 per cent for Nigeria. Using the estimated two threshold point model, this paper did not find enough reasons to accept the null hypothesis of the super-neutrality of money, and therefore, suggest that there is a threshold level of inflation above which money is not super-neutral.

Nwaobi (2009) says at present, the world economy is at a cross road. The Nigerian economy is therefore undergoing it most severe economic crisis since the Biafra war of the sixties. Currently, she is experiencing a staggering rate of inflation (well up to the double digit) as well as experiencing a severe recession (as the unemployment rate has risen astronomically).
Consequently, a basic thesis of this proposal is that stagflation has caused and will continue to cause considerable hardship for many Nigerian families and poses a serious threat to the mental health of a substantial proportion of the population. It is therefore the aim of this research to document in a systematic way how families that have experienced varying degrees of “inflation crunch” have adjusted to or tried to adapt to this pressure. In other words, this phased research project proposes to provide information that will be useful to policy makers (government) who must weigh the costs and benefits of the current inflationary pressures as well as severe recession. Essentially, the result will be an emergence and evolution of corrective policy measures and strategies (as adequate and functional). Carlos (2010) tries to determine if the Phillips curve is a relevant tool to conduct monetary policy in African countries wishing to adopt an inflation-targeting regime. I choose Nigeria as a case of study because it is in the early stage of the implementation of this regime. I estimate a medium-sized model for monetary policy analysis. The model reflects a synthesis between the New Keynesian and the Real Business Cycle (RBC) approaches. Then I estimate the model by using Bayesian econometric technique in order to overcome the shortage of data availability. The study concludes that there is evidence that central banks can control the inflation rate through a Phillips curve, a Taylor rule that includes the exchange rate, and the sterilization of the resources from oil exports. Nevertheless, there are limits to the stabilization program. The same evidence suggests that it is important to implement a credible inflation-targeting regime to reduce inflation gradually, instead of abrupt stabilization attempts with high costs in lost output. Chimobi (2010) in his work ‘Inflation and Economic Growth in Nigeria’ purpose of his study is to ascertain the existence (or not) of a relationship between Inflation and economic growth in Nigeria. The methodology employed in this study is the cointegration and Granger causality test. Consumer price index (CPI) was used as a proxy for Inflation and the GDP as a perfect proxy for economic growth to examine the relationship. The scope of the study spanned from 1970 to 2005. A stationarity test was carried out using the Augmented Dickey-Fuller test (ADF) and Phillip-Perron test (PP). and stationarity found at first difference at 1% and 5% level of significance. The Johansen Juselius co-integration technique employed in this study proved to be superior to the Engle and Granger (1987) approach in assessing the co-integrating properties of variables, especially in a multivariate context. The result of the test showed that for the periods, 1970-2005, there was no co-integrating relationship between Inflation and economic growth for Nigeria data. Further effort was made to check the causality relationship that exists between the two variables by employing the VAR-Granger causality at two different lag periods. The results showed the same at different lags. The first test was conducted using lag two (2) and in the result unidirectional causality was seen running from Inflation to economic growth. Further test at lag four (4) was carried out and it only supported the first by also indicating a unidirectional causality running from Inflation to economic growth. Various studies as reviewed in the literature came out with the result that high inflation is and has never been favourable to economic growth. Hence, the study through the empirical findings maintain the fact that the causality that run from inflation to economic growth is an indication of relationship showing that Inflation indeed has an impact on growth

Stephen (2011) examined the trade-off between inflation and economic growth in Nigeria using the Philips relation approach. The study employed experimental research design approach for the data analysis, which combined theoretical consideration (a priori criteria) with empirical observations and extracted maximum information from the available data. The Nigeria’s secondary data were processed using e-view for windows econometric packages. The results of the regression showed that there is a positive relationship between inflation and output growth in Nigeria. It indicated that a 1 percent rise in inflation in the current period leads to 6.4 percent increase in output. This is in consonance with the Philip’s curves theory, which proposes a trade-off between inflation and economic growth. This suggested that a creeping inflation is a necessary concomitant to economic growth and development of any nation and Nigeria in particular. This finding has some policy implications. For an economy to grow, the policy maker should permit a little bit of inflation. The inflationary rate of Nigeria in the current period, which is in single digit, and the economic growth rate, which is 6.5 percent, are a great manifestation of the Philip’s theory of inflation. Aminu and Zubairu(2012) investigates the relationship between unemployment and inflation in the Nigerian economy between 1977 and 2009 through the application of Augmented Dickey-Fuller techniques to examine the unit root property of the series after which Granger causality test was conducted to determine causation between unemployment and inflation, then cointegration test was conducted through the application of Johansen cointegration technique to examine the long-run relationship between the two phenomenon, lastly ARCH and GARCH technique was conducted to examine the existence of volatility in the series. The results indicate that inflation impacted negatively on unemployment. The causality test reveals that there is no causation between unemployment and inflation in Nigeria during the period of study and a long-run relationship exists between them as confirmed by the cointegration test.ARCH and GARCH results reveals that the time series data for the period under review exhibit a high volatility clustering. The paper recommends the use of inflation/unemployment theory that is drawn from data sourced within the country and also improvement in the existing theories in order to ensure their applicability in the Nigerian context, so as to achieve a desire reduction in unemployment and inflation which in turn boost economic growth and development. Asuquo (2012) in his study evaluate Inflation accounting and control through monetary policy measures in Nigeria from 1973 to 2010. Secondary data were used empirically to do the assessment. Aggregate data on independent variables (monetary policy measures) that affect inflation were collected and analyzed using multiple regression model and the ordinary least squares estimation techniques. From the analysis carried out, it was found that some of the variables (money supply, interest rate and exchange rate) were statistically significant, which means that the studied variable could be used to predict inflation. Furthermore, domestic credit was not statistically significant, even though it could be used as a policy variable to account for inflation. Based on these findings, it was recommended that monetary supply, interest rates and exchange rates should be the principal policy variables to be manipulated in controlling inflation in Nigeria Adeyeye and kola (2012) examined the causes and effects of inflation in Nigeria between 1969 and 2009 and what could be done to ameliorate the negative effects on the economy. The time series variables properties on some selected variables were examined using Augmented Dickey Fuller (ADF) Unit root test and co-integration analysis. The result revealed that the explanatory variables (money supply, growth rates, gross domestic product growth rates and expenditure revenue ratio) are not spurious but exchange rate of dollar to naira was non stationary. The study also revealed that the gross domestic product growth rate is counter inflationary as against inflationary factors. David and Anyiwe (2013) examined the dynamics of inflation and unemployment in Nigeria using the vector error correction methodology over a period of twenty seven years. The study finds evidence of stagflation in the Nigerian economy over the period of study. In fact, the Nigerian economy is managing a shocking rate of inflation together with a severe recession as the unemployment rate has risen astronomically. Consequently, the Nigerian economy is at a cross road. Based on these findings, it is recommended that the CBN maintains a stance of gradual reduction of the benchmark inflation rate to a single digit as the excessive contraction of the monetary policy rate seems to have become counterproductive in recent times. Single digit inflation rate can be achieved if the CBN could increase GDP growth above money supply and increase lending to the real sector of the

CHAPTER THREE
METHODOLOGY AND DATA
3.0 Introduction Chapter three of this research work contains the methodology that will be used. It also contains the model specification, the type of estimation technique used, sources of data obtained etc.
3.1 Research Design This is the plan and structure of investigating that drives a researcher. It is a logical mode of proof that permits the research to draw reference about the casual relationship between the variables under study and also to define the extent of generalization of the research findings. This study involves quantitative analysis of the variables used in this study, adopting the econometric technique of co integration and error correction modelto assess the interaction between non-oil export and economic growth in Nigeria. This study made use of secondary data and there include annual series data on interest rate, exchange rate, gross domestic product figures, non-oil export and oil export.
3.2 Sources of Data Data is a very important aspect of any econometric research work and very indispensable to the field of econometrics. Gigariti (2003) asserted that the success of any econometric analysis ultimately depends on the availability of appropriate and accurate data. For the purpose of this research work we will make use of secondary data. The data been obtained from the Central Bank of Nigeria statistical bulletin 2010, National Bureau of Statistics. The econometric software used for the analysis of this work is Econometric view (E-view), while the Microsoft excel 2010 is used to enter the data. The test statistic to be employed will be the parametric test.
3.3 Research Technique The technique of research for a study is the way in which the data used for the analysis are arranged , presented and interpreted. Some technique make use of tables, graph, percentages and some statistical test like Chi-square, Analysis of Variance, Spearman’s rank correlation and a host of other parametric and non parametric tests. Other studies make use of econometric technique like Ordinary Least Square (OLS), Cointegration and Error Correction Model (VECM), Vector Autoregression (VAR) and a host of other econometric techniques. This study however has adopted the use of Cointegration and Error Model in the analysis of the data used for the study. The technique was adopted based on the fact that the study makes use of time series data, the type of data that is prone to serial or auto-correlation in econometric analysis. The cointegration technique involves determination of the stationary or otherwise of a variable before the OLS is estimated on such data. The imperative of the determination of the stationary property of the variable used may have nonsense result or spurious result and the conclusion therefore will be invalid.
3.3.1 Cointegration Cointegration provides a powerful way of detecting the presence of economic structures. It is an over-riding requirement for any economic model using non-stationary time series data. If the variables do not cointegrate, we have a problem s of spurious regression and econometric work becomes almost meaningless. Economically speaking two variables will be cointegrated if they have a long term or equilibrium relationship between them. If there is a genuine long-run relationship between Yand X, although the variables will rise over time (because they are trended), there will be a common trend that links them together. Cointegration implies that Yand X share similar stochastic trends. For an equilibrium, or long-run relationship to exist, what we require is a linear combination of Y and X that is a stationary variable . Eviews provides two tests of cointegration in the singlr equation setting. Both are residual-based tests
(1) Engle-Granger test
(2) Phillips-Quliaris test The two tests simply apply unit root test to the residuals obtained from static OLS (SOLS) estimation pf linear model. The two tests differ in the method of accounting for serial correlation in the residuals series. Engle-Granger test uses a parametric augmented Dickey-Fuller (ADF) approach. Phillips-Quliaris test uses the non parametric Phillips-Perron (PP) methodology.
3.4 Model Specification Based on theoretical findings in the factors affecting the non-oil sector, a number of specified models were discovered and the model below has being modified to fit desired objectives.

UMR = f(UMP t-1,GDP,CU,INF)
Where:
UMR = UNEMPLOYMENT RATE
UMPt-1 = UNMPLOYMENT RATE LAGGED 1
GDP = GROSS DOMESTIC PRODUCT
CU = CAPACITY UTILIZATION
INF = INFLATION RATE
Justification of the variables in the model;
Unemployment Rate - The unemployment rate is calculated by dividing the number of unemployed persons by the size of the workforce and multiplying that number by 100, where an unemployed person is defined as a person not currently employed but actively seeking work. The size of the workforce is defined as those employed plus those unemployed
Capacity Utilization - refers to the extent to which an enterprise or a nation actually uses its installed productive capacity. Thus, it refers to the relationship between actual output that 'is ' actually produced with the installed equipment, and the potential output which 'could ' be produced with it, if capacity was fully used.
Gross Domestic Product (GDP) - this is the total market value of all final goods and services produced in a country within a specific time period. A functional relationship is specified showing GDP as a function of non-oil export. A country with high GDP will mean that there is the availability of funds to diversify the economy towards non-oil ventures e.g Nigeria which will enhance its export.
Inflation rate ; an increase in the supply of currency or credit relative to the availability of goods and services, resulting in higher prices and a decrease in the purchasing power of money.
The regression form of the model is specified thus:
LogUMR= β0+ β1logUMPt-1+ β2logGDP+ β3logCU+ β4logINF+ Ut
Where:
Ut = Error Term AND β0 β1β2 β3 β4ARE COEFFICIENTS. The above model specifies the relationship between inflation and unemployment in Nigeria
3.5 Evaluation Criterion This criterion consists of testing the estimates of the parameter if they are theoretically meaningful and statistically significant. For this to be satisfied three criterions will be used; economic/a priori criteria, statistical criteria and econometric criteria.
3.5.1 A priori Expectation The a priori expectation of the model is such that: β10, +Ut
3.5.2 Economic Criterion This is based on economic theory and is used to refer to the sign and magnitude of parameter of any economic relationship. It has to do with the a priori expectation of the coefficients of the parameter that our model conforms to. It is expected that an increase in the independent variables will lead to a corresponding increase in the dependent variable.
3.5.3 Statistical Criterion A crucial question to be answered here is if the model conforms to statistical specification ie if the t statistics are in support of the model. Common t statistics are t ratio, f statistics, Durbin Watson, R and adjusted R square.
R2 and adjusted R2: the R2 test statistics measures the goodness of fit and it is the predictive power of a given model. The closer the R2 to 1 the better the result. An R2 of 0.92 means the given model can be 92% relied upon while the remaining 8% can be explained by the error term. The adjusted R2 is not much different from the R square and it can seeks to further reveal the predictive power of a model by taking into consideration the degree of freedom used in the data. The adjusted R2 gives room for determining the one to one relationship between the R2 and the residual variable.
T ratio: this is a test statistics that confirms reliability of a particular model. It also tests whether a particular independent variable belongs in the model. If the calculated t ratio is greater than tabulated t ratio at any given level of significance then the particular variable belongs to the model under consideration.
F-Statistics : virtually everything that must be said on the f-statistics has been said under the t-ratio. It is sufficient condition for testing that all the independent variables put together belong to a particular model. The procedure for testing it is similar to that of t-ratio in that appropriate levels of significance say 5% or 1% is always chosen. The decision rule is similar to that of the t-ratio in that if the observe f-ratio is greater than the critical f-ratio, the overall independent variables are significant and belong to the model in question. If otherwise then the reverse is the case.
The Standard Error of Regression (SER) : this is another test of overall goodness of fit and more importantly of the reliability in prediction. The lower the SER the better the prediction power of the equation. One important note is that econometricians have not agreed on the relative size of the SER. They only suggest ratio of the SER to the mean of the dependent variable, if the ratio is small it is considered acceptable. An SER in the neighborhood of 10% or less is considered small reasonably to confirm acceptability on the result of a model.
Durbin Watson statistics: this is a test for serial or auto correlation. A model observed to having a serial correlation problem according to the OLS technique is biased and therefore the result cannot be entirely relied upon. Therefore DW is needed to test for the seriality of the data. Serial or auto correlation is a problem of time series data.

CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS OF FINDINGS
4.1. Objective of the Study Restated
Data presentation and analysis of findings are best achieved with a recall of the broad objective of a study. This will provide a platform on which the data analysis will be built. The broad object of this study is to empirically examine the existence of Phillips Curve in Nigeria. This will enable us to know the size, the magnitude and the direction of the relationship between inflation and unemployment.
4.2. The Model
As stated in the previous chapter, the model adopted for this study is specified as follows:
LogUMR= β0+ β1logUMPt-1+ β2logGDP+ β3logCU+ β4logINF+ Ut.................(4)
Where:
UMR = UNEMPLOYMENT RATE
UMPt-1 = UNMPLOYMENT RATE LAGGED 1
GDP = GROSS DOMESTIC PRODUCT
CU = CAPACITY UTILIZATION
INF = INFLATION RATE

4.3. Testing for the Stationarity Property of the Time Series
The study choses the options of graphical approach and the estimation of AR(1) of the time series in order to confirm the stationarity nature of the time series. The results as obtained from E-Views and attached as appendices at the back of the project is presented as follows:

Nb Fig 4.3.1 Trend of Unemployment rate (1985-2010)

The above diagram appears to follow a random walk, as the trend revolves around mean 30. This is suggestive of stationarity of the data. This can further be confirmed by the estimation of the AR(1) of the series which is presented in the table below.

Table 4.3.1. AR(1) of the series UME

Dependent Variable: UME

Method: Least Squares

Date: 06/10/13 Time: 12:45

Sample (adjusted): 1986 2010

Included observations: 25 after adjustments

Variable
Coefficient
Std. Error t-Statistic Prob.

UME(-1)
0.825241
0.116087
7.108808
0.0000

R-squared
0.273371
Mean dependent var
22.49120
Adjusted R-squared
0.273371
S.D. dependent var
20.47724
S.E. of regression
17.45531
Akaike info criterion
8.596343
Sum squared resid
7312.512
Schwarz criterion
8.645098
Log likelihood
-106.4543
Hannan-Quinn criter.
8.609866
Durbin-Watson stat
1.696364

From the table the coeffiecient of the UME(-1) is approximately 0.83, which is less than 1and which suggests that the series is stationary. Fig 4.3.2. Trend of Gross Domestic Product (GDP)

.
This trend of the series is suggestive of the one with non-stationarity. This can be further confirmed using the AR(1) result as shown below.
4.3.2 AR(1) of the series GDP
5.
Dependent Variable: GDP

Method: Least Squares

Date: 06/10/13 Time: 13:10

Sample (adjusted): 1986 2010

Included observations: 25 after adjustments

Variable
Coefficient
Std. Error t-Statistic Prob.

GDP(-1)
1.152739
0.020039
57.52377
0.0000

R-squared
0.987901
Mean dependent var
7390914.
Adjusted R-squared
0.987901
S.D. dependent var
9146064.
S.E. of regression
1006023.
Akaike info criterion
30.52009
Sum squared resid
2.43E+13
Schwarz criterion
30.56884
Log likelihood
-380.5011
Hannan-Quinn criter.
30.53361
Durbin-Watson stat
1.946877

The coefficient of the series is approximately 1.15, which is more than 1, which suggest the presence of a unit root, therefore the series is non stationary.
Fig 4.3.2. Trend of Capacity Utility (CU)

This trend follows the same pattern as that of GDP, and obviously the trend of the series is suggestive of the one with non-stationarity. This can be further confirmed using the AR(1) result as shown below:

Table 4.3.3 AR(1) of the series CU

Dependent Variable: CU

Method: Least Squares

Date: 06/10/13 Time: 13:21

Sample (adjusted): 1986 2010

Included observations: 25 after adjustments

Variable
Coefficient
Std. Error t-Statistic Prob.

CU(-1)
1.011825
0.016449
61.51175
0.0000

R-squared
0.856281
Mean dependent var
43.26040
Adjusted R-squared
0.856281
S.D. dependent var
9.456087
S.E. of regression
3.584825
Akaike info criterion
5.430474
Sum squared resid
308.4233
Schwarz criterion
5.479229
Log likelihood
-66.88093
Hannan-Quinn criter.
5.443997
Durbin-Watson stat
1.352438

The coefficient of CU(-1) is approximately 1.01, which suggest the presence of a unit root, therefore the series is non stationary. For the remaining variable of INF. he graph and the AR(1) follow the same pattern of interpretation with the three explained above.
4.4. Unit Root Test
This study in addition to the graphical approach and the estimation of AR(-1) of all the variables conducted the unit root test using the Augmented Dickey Fuller and the Phillips-Perron and the result obtained from the test is as presented in the table below:
Table 4.4.1. Augmented Dickey Fuller for Unit Root Test
Critical values 1%, 5% and 10% are -3.7241, -2.9862 and -2.6325 respectively
Variables
At levels
1st Difference
2nd Difference
Order of Integration
UME
-2.4301
-4.3325*
-4.8819
I(1)
UMPt-1
-2.4301
-4.3325* -4.8819
I(1)
GDP
-0.2803
-0.6811
-11.9902**
I(2)
CU
-1.1388
-3.3443
-6.8258**
I(2)
INF
-2.4301
-4.3334*
-4.9184
I(1)
Source: Own Computation using E-Views 7
*Significant at 1%, **Significant at 5%
From the table, there exist the presence of unit root test in all the variables .

Table 4.4.2: Johansen Co-integration Test
Sample: 1985- 2010
Included Observation: 39 after adjustment
Test Assumption: Linear Deterministic Trend in the Data
Series: UME,GDP,CU,INF
Lag Interval: 1 to1
Eigenvalues
Trace Statistics
5% Critical Value
Probabilities
Hypothesised No of CEs
0.8297
75.5802
47.8561
0.0000 None *
0.5483
33.0972
29.7971
0.0201 At most 1 *
0.4172
14.0255
15.4947
0.0822 At most 2
0.0435
1.0683
3.8415
0.3013 At most 3 Source: Own Computation
Note: Trace test indicates 4 cointegrating equations at 5% level. *Denotes rejection of the hypothesis at the 5% level.
From the above result, it can be confirmed that Phillips Curve and its determinants are subject to an equilibrating relationship. Some of the determinants are positively related to the output in the long run, while some are negatively related in the long run.
Following the above the regression result that shows the estimate of the parameters of the model is as shown in the table below:
Table 4: Ordinary Least Square Regression Result for the model
Dependent Variable (Md/P)
Variable
Coefficient
Std Error t- statistic
Prob
Constant
0.033516
0.053657
0.624625
0.5405
UME

R- Squared

Adjusted R-Squared

S.E. of regression

Sum squared resid

Log Likelihood

Durbin-Watson Stat

The above result can be expressed in a linear form as follows:
Md/P= -35.23-1.633rb -1.336re +0.016P -25.909/P(dp/dt) +0.0467W-237.09w + 10. 844u (-2.22) (-2.25) (-1.68) (5.51) (-1.81) (7.05) (-4.36) (1.19)

The above is a product of time-series data concerning the values of demand for money represented by Md/P, return on bond (rb), return on equity (re), the price level (P), change in price level over time (1/P dp/dt), human wealth (W), ratio of human to non human wealth (w) and taste and preferences (u). With a priori expectation as stated previously, it is observed all the signs came out as expected with the exception of the sign of w which is negative contrary to the expected positive sign. The signs are not just as expected but also significant judging the t statistics reported in parenthesis above.
From the result a 1% increase in returns on bond will depreciate demand for money by 1.633million naira. Likewise a 1% increase in return on equity reduces demand for money 1.336million naira. A #1 change in the price level bring about #0.0161million change in money demand, while a #1 change in price over time about #25.91 negative change in money demand. A naira increase in human wealth increases money demand by #0.0466million, while a 1% increase in the ratio of human to non human assets reduces money demand by #237.088. Taste and preferences show that people prefer to hold more money by as much as #10.844million when their taste is in favour of activities within the economy.
It is noted R2, which is a measure of overall goodness of fit in the analysis is very high. At a high level of 0.85 or what can be regarded as 85%, it means that the proportion explained by the independent variable is 85% while the remaining 15% was explained by error term. We equally see that the adjusted R2 that allows for degree of freedom is equally high. This R2 allows to compare equations with different explanatory variables and equally to determine that one-to-one relation between R2 and the residual variance. The R2 is most useful in a simultaneous equation with the best predictive ability.
Reported in parenthesis are t-values. The t-values are obtained by the ratio of the estimated parameters to the standard error of the parameters. Therefore the t test is a test to determine whether or not a given independent variable belongs to a particular equation. It is a good or reliable indicator of the dependent variable. From the result, it is seen that t –ratio of rb, re, P, 1/P(dp/dt), W, w and u are (-2.22), (-2.25), (-1.68), (5.51), (-1.81), (7.05), (-4.36) and (1.19) respectively. Using the rules of thumb that gives significance to the t-value higher than 2 at 5%, we may be forced to conclude that the t-values of all the explanatory variables with the exception of that of taste and preferences (u) are significant. at 5%. However a proof of this is found that the t tabulated t values at 5% i.e. t5%,39 = 1.68. Since the t value of 1.68 is greater than on the t-calculated of 1.19, it shows that the t value is significant for all the variables except that of u.
The F ratio is an improvement over the t-ratio is a test of significant linear relationship between the independent variables taken together and the dependent variables. Whereas the t –ratio tests variable by variable in the equation, the F-ratio takes the whole independent variables in bulk and test. Using the F test, the tabulated F is equal to F31,39,5% is 3.34. Since our F calculated of 24.91 is greater than 3.34, the test is significant and the independent variables put together are good and reliable indicators of the dependent variables.
The Durbin-Watson test statistics is used to test for serial correlation or auto-correlation in the data used to run a regression. The result which can be interpreted to mean that any regression with significance of autocorrelation means that the successive data in the series are dependent on one another. From the result the DW is 1.81 and the tabulated DW 0.8152 for lower value and 1.579 for upper value. It therefore suggests that the data used is devoid of serial correlation and that the the regression estimates are unbiased..
5.2. Error Correction Model
In order to establish the long run relationship between the dependent variable and the independent variables of the model, equation 2 can be transformed into an econometric model under the ECM framework as follows: dUME=π0+π1+π2-π3+π4+π5ECM(-1)+εt d in the equations stand for first differencing, while ECM is the error correction mechanism for the model. The significance of the ECM in the model is to indicate how disequilibrium in demand for money can be adjusted in the short run. The result of the ECM for the model is presented in the table below:
Table 5: Parsimonious Error Correction Model
Dependent variable is d(Md/P(-1),2)
Variables
Coefficient
Std Error t- Statistic
Prob
UME(-1)
-0.003822
0.002199
-1.738286
0.1002
CU
0.000649
0.011244
0.011244
0.9547
GDP
0.9547
2.82E-08
-1.617557
0.1242
INF
0.999355
0.002297
435.1561
0.0000
ECM
-0.646366
0.331973
-1.947045
0.0682
Source: Author’s Computation
As stated earlier, the significance of ECM is to indicate how the departure from the long run disequilibrium is corrected in the short run. To do this, the coefficient of the ECM comes handy. As shown in table 4, the coefficient of ECM is -0.64, which is a reasonably good adjustment process. The speed of adjustment which is significant at both 5% and 1% suggests that about 64% of the disequilibrium in the previous year’s shock adjusts back to the long run equilibrium in the current year.

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References: Amemiya, T. (1985), “Advanced Econometrics” Cambridge, Massachusetts: Harvard University Press Antonio, R Caporale, G. M., and L. A. Gil-Alana (2006), Modeling structural breaks in the US, UK and Japanese Unemployment rates, CESIFO Working Paper, 1734 Central Bank of Nigeria (2006) “Inflation Targeting in Nigeria” Proceeding of the Fifteenth Annual Conference of the Research and Statistics Offices, Bauchi, Nigeria Central Bank of Nigeria (2012a), Origin and Development of Inflationary Trend in African Countries (Impact on Their Growth)” Central Bank of Nigeria (2012b), The Dynamics of Inflation in Nigeria, Abuja CBN. Chatterjee, S. (2001), “Why Does Countercyclical Monetary Policy Matter?” Federal Reserve Bank of Philadelphia, Business Review, Second Quarter CIA World Fact Book National Bureau of Statistics (2012), Labour Policies and the Nigerian Work Force Davidson, R., and J De Veirman, E. (2007). Which Nonlinearity in the Phillips Curve? The Absence of Accelerating Deflation in Japan, Reserve Bank of New Zealand, January 14, 2007 Dua, P. (2006), “Inflation-Unemployment Trade-off in Asia,” presented in the Project Link Meeting, United Nations, Geneva. Dumlao, L. (2005), “Capacity Utilization, Aggregate Supply and Phillips Curve in the Philippines,” Ateneo De Manila University. Esguerra, E. (2010). “Job Creation: What’s Labour Policy Got to do with it?” Presented During the 10th AC-UPSE Economic Forum, 21 July Friedman, M. (1968), “The Role of Monetary Policy,” American Economic Review, 58, March, pp. 1-17. Feyzioğlu, T., and L. Willard (2006), Does Inflation in China Affect the United States and Japan? IMF Working paper, WP/06/36 Gambetti, L. (2004), “Policy Matters: The Long-run Effects of Aggregate Demand and Mark-up Shocks on the Italian Unemployment Rate” Empirical Economics 29:209–226 Ariga, K., and K. Matsui (2002), Mis-measurement of CPI.ac.jp/~seido/output/Ariga/ariga029.pdf Bureau of Labor Statistic, (2007). Foreign Labor