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THE IMPACT OF FISCAL DEFICIT ON THE CAPACITY UTILIZATION OF MANUFACTURING SECTOR IN NIGERIA
This chapter deals with the various methods, techniques and instruments used in the conduct of this research work. In addition it also includes the model specification and the various sources of data employed.
3.1 MODEL SPECIFICATION
The economic model employed in this project work intends to build the framework of analyzing the effect of fiscal deficit on capacity utilization and how they affect the manufacturing sector in Nigeria. Following the work of Abimbola, (2008), who made use of four variables, of which he used Gross domestic Product (GDP) as the dependent variable, Capacity utilization, index of manufacturing output, index of energy consumption as the independent variables. In addition, for this work, some variables were added, using Manufacturing output as the dependent variable while fiscal deficit, capacity utilization and government expenditure are the independent variable, in order to form the basis of this work.
Hence, the model is specified below:
The linear equation is specified as
LMOP= β0+ β1FD+ β2CU+ β3GEXP+U
Specifying the equation in an ECM Function
MOPt = β0 + β1MOPt-1 +β2FDt-1 + β3CUt-1 +β4GEXPt-1 + β5ECMt-1 + Ut
MOP = Manufacturing Output
FD = Fiscal Deficit
CU = Capital Utilization
GEXP = Government Expenditure
ECM = Error Correction Model
β0 = Intercept
β1 = Parameter Estimate of Fiscal Deficit
β2 = Parameter Estimate of Capital Utilization
β3 = Parameter Estimate of Government Expenditure
U = Stochastic Error Term
3.2 Description of Variables
Manufacturing activities have significant impact on the economy of a nation. It developed economies, for instance, they account for a substantial proportion of total economic activities. In Nigeria, the sub- sector is responsible for about 10% of total GDP annually. In terms of employment generation, manufacturing activities account for about 12 per cent of the labour force in the formal sector of the nation’s economy. This is why manufacturing statistics are relevant indices of the economic performance of a nation.
There are two basic roles of the government in any society; maintaining law and order (i.e. making and enforcing) as well as providing public goods such as good roads, education, health, defense, power and so on. Over time, scholars have argued that increase in government expenditure on socio–economic and physical infrastructure fosters economic growth. For example, expenditure on education and health raises the level of national output through improved quality of labour and productivity. Similarly, spending on infrastructure such as roads, communications, power and so on reduce production costs and increase profitability of firms, thus fostering economic growth.
Fiscal deficit could be seeing from many angles. It is the gap between the government’s total spending and the sum of its revenue receipts and non-debts capital receipts, (Buhari 1994). It represents the total amount of borrowed funds required by the government to completely meet its expenditure. It could also be defined as the excess of total expenditure including loans net of payments over revenue receipts and non-debt capital receipts. It also indicates the total borrowing of the government, and the increment to its outstanding debt. Despite the fact that realized revenues are often above budgeted estimates, extra budgetary expenditures have been rising so fast and result in fiscal deficit, Anyanwu (1997), and Robini (1991), shows that budget deficit in developing countries are heavily influenced by the degree of political instability as well as public finance considerations with no apparent direct effect of elections.
A metric used to measure the rate at which potential output levels are being met or used. Displayed as a percentage, capacity utilization levels give insight into the overall slack that is in the economy or a firm at a given point in time. If a company is running at a 70% capacity utilization rate, it has room to increase production up to a 100% utilization rate without incurring the expensive costs of building a new plant or facility.Capacity utilization rates can also be used to determine the level at which unit costs will raise.
Government Expenditure orgovernment spending on goods and servicesincludes all government consumption and investment but excludes transfer payments made by a state. Government acquisition of goods and services for current use to directly satisfy individual or collective needs of the members of the community is classed as government final consumption expenditure. Government acquisition of goods and services intended to create future benefits, such as infrastructure investment or research spending, is classed as government investment (government gross fixed capital formation). Government outlays that are not acquisition of goods and services, and instead represent transfers of money, such as social security payments, are called transfer payments and are not included in what the national income accounts refer to as government expenditure. The two types of government spending, on final consumption and on gross capital formation, together constitute one of the major components of gross domestic product.
John Maynard Keynes was one of the first economists to advocate government deficit spending as part of the fiscal policy response to an economic contraction. In Keynesian economics , increased government spending is thought to raise aggregate demand and increase consumption, which in turn leads to increased production. Keynesian economists argue that the Great Depression was ended by government spending programs such as the New Deal and military spending during World War II. According to the Keynesian view, a severe recession or depression may never end if the government does not intervene. Classical economists, on the other hand, believe that increased government spending exacerbates an economic contraction by shifting resources from the private sector, which they consider productive, to the public sector, which they consider unproductive.
3.3 A prior Expectation
This is a positive relationship between Fiscal deficit and the manufacturing output, which is shown by the higher the higher the fiscal deficit, the higher the investment towards manufacturing sector which will translate into a higher increase in manufacturing output. This relationship is shown below as:
From the model above, theoretically a positive relationship is expected between capacity utilization and manufacturing sector output and gross domestic product.
Capacity utilizationis the extent to which an enterprise or a nation actually uses its installed productive capacity. It is 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. If market demand grows, capacity utilization will rise. Therefore if fiscal deficit increases government expenditure, it also increases demand leading also to increased capacity utilization in other to meet with the increased demand which results to a positive relationship between capacity utilization and manufacturing sector output. This is shown below:
A positive relationship exists between government expenditure which could also be seen as government spending and manufacturing sector output.
In developing countries aspiring development, government tends to increase its expenditure in other to increase per capita income of the citizens in order to strengthen their demand capabilities.
This increased per capita income could therefore be channeled by the citizens either into two directions which could be increased consumption or savings.
When income is based on increased consumption, this in turn increases the demand of commodities from firm which pressures them to increase their scale in other to meet with the increased demand, this therefore causes a manufacturing output increase, while in the aspect of increased savings, it would lead into increased investment and also increased manufacturing output. Therefore, a positive relationship exists between government expenditure and manufacturing output. This is shown below as:
3.4 Technique of Analysis
This work uses the co-integration analyses and also the error correction model (ECM)
Co-integration test has been a useful tool used in tackling some economic analysis problem, which includes
- Testing rationality of expectation
- Testing market efficiency in different market
- Testing for permanent income hypothesis
- Testing for purchasing power parity.
The co-integration test is used in creating a way out to an inefficient and non sense or spurious result that is obtained by the ordinary least square (OLS) which could occur by regressing a non stationary series on another non stationary series which may be inconsistent (Engle and Yoo, 1987).
3.4.1 STAGES IN CO-INTEGRATION
A co-integration analysis technique comprises of various tests which includes the unit root test, the co-integration test and the error correction model.
Unit Root Test
The unit root test is considered as the most important factor in carrying out or testing for the stationary of a time series data.
Unit root test is a pre-test; it works hand in hand with co-integration, it is used to determine the type of co-integration test to be used, and basically it deals with the determination of the order in which a variable is integrated for the purpose of further analysis.
For instance, a time series Yt is said to be integrated of order 1 or I (1) of Yt is a stationary time series. A stationary time series is said to be I (0). A random walk is a special case of an I (1) series, because if Yt is a random walk, Yt is a random series or “White noise”. White noise is a special case of a stationary series. A stationary time series Yt is said to be integrated or order 2 or is I (2) if Yt is I (1) and so on.
Test for Co-integration
A co-integration model is used for carrying out tests of possible linear combination among economic variables. The concept of co-integration among variables is related with the fact that though economic variables may not be stationary when tested individually against the dependent variable but a mechanism could still exist that prevents some of the variable from diverging significantly from one another. Co-integration can therefore take place in a group of non stationary time series, if there is in existence a linear combination of stationary variables. . This means that the combination of variables does not possess long linear relationship or does not carry stochastic trends. The hypothesis of co-integration among the variables is rejected if the critical value is accepted and confirm the alternative hypothesis if otherwise. The various possible linear combinations among the variables is said to be “co integrating equation” which implies a long run equilibrium relationship.
The very well known method of co-integration among variables and to decide the number of co-integration test equation is known as Johansen’s co-integration test. The results obtained from this test is used in obtaining reports on the number of co-integration equation (rank) in the long run among the variables between one and five percent critical values. If therefore the result carried out from the co-integration test shows that a long run dynamic relationship among the variables exists, then we move on to bring up a parsimonious error correction model, which represents a short run dynamic model, and if otherwise, the need for error correction will not arise.
Advantages of Co-integration Test
- It establishes the long run relationship between economic variables that are stationary.
- It makes us understand if there is a linear combination among the variables
Error Correction Model (ECM)
The Johansen co-integration test carried is out in order to test and attain the existence of the long run linear relationship that exists among economic variables. This test therefore helps a person carrying out a research to know whether to proceed to an error correcting modeling or weather not to. If therefore variables are co-integrated, there would be a need for short run dynamic modeling (ECM) and if not, the use of error correction model will not be of use.
“Another way of explaining co-integration and error correction modeling is that it is an extension and generalization of the traditional approach to modeling short run disequilibrium by the use of partial adjustment model”, Abimbola (2008). The error correction model, that includes the previous periods disequilibrium, in the final equation can however be seen as a straight forward generalization of the partial adjustment model.
Abimbola (2008), however stated that the use of techniques of both co-integration and error correction adds more riches, flexibility and versatility to the econometrics modeling of dynamic systems and the integration of short run dynamic with long run equilibrium.
This error correction modeling (ECM) can be divided in two types, which are:
- The parsimonious error correction model, and
- The over-parameterized model
SOURCES OF DATA:
This study employed secondary data collected from CBN statistical Bulletin, World Bank, National Bureau of statistics and IMF
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