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1.1 Background to the Study In any country economy, the real sector which also known as the manufacturing sector is often refers to as the backbone of the economy due to its crucial role in enhancing wide and efficient backward and forward linkages among the different sectors which made up the country economy. (Adeyemi Olufemi, 2016). The manufacturing sector of any economy can therefore be describes as the engine growth because It is an avenue for increasing productivity in relation to import substitution and export expansion, creating foreign exchange earning capacity, raising employment and per capita income, which widen the scope of consumption in dynamic patterns. Furthermore, it promotes the growth of investment at a faster rate than any other sector as well as wider and more efficient linkage among different sectors (Ogwuma, 1995). In recent years, there have being a growing interest in the study of capacity utilization in the manufacturing sector as result of the realization of positive relationship between capacity utilization and output growth in the manufacturing sector. According to Fabayo(1981) a manufacturing firm level of capacity level does not only determine the volume of manufactured output that can be derived from a full utilization of their existing capacity, but also define the required expansion of capacity for a targeted volume output. He further stated that there exists a positive correlation also between capacity utilization and employment via shift work operation, price stability and industrial growth, on the other hand. Capacity utilization is an important determinant of economic development and growth and a priori reason for its (Capacity utilization) analysis in a developing economy becomes evident. In a developing economy, the economic resources (especially capital and skilled labour) which are needed for rapid economic development are both scarce and expensive and cannot easily be augmented of financial resources, technical know-how and element of time factor. They are also paradoxically grossly underutilized (Fabayo, 1981) The Nigerian manufacturing sector has continued to witness reducing capacity utilization. For example According to Akingbola, 1992, from the report of meeting of the Manufacturing Association of Nigeria (MAN) held in May, 1992 between 1975-1979, the capacity utilization of the manufacturing sector reduced drastically from 75.4percent to a record low of 30percent . It was also discovered the capacity utilization of the manufacturing sector fell from 57percent in 1988 to an estimates of 40 percent in 1998 and 30 percent . Manufacturing capacity utilization has therefore reduced from over 70 percent in the past to just above 44 percent at the end of the second quarter of 2006, the fall still continues till date. This under utilization of capacity can be attributed to the lack of the following factors in the Nigerian manufacturing sector Employment Rate Unemployment is one of the economic problem facing Nigeria. This therefore indicates that there is an under-utilization of human resources in the country economy connotes the fact that there is low level of human resource utilization in the countrys manufacturing sector. Effective monetary policy Monetary policy can simply be defined as monetary measures implemented by the apex or central bank to influence macro-economic variables such as price stabilization (factor price and consumer price), full employment, sustainable balance of payment, exchange rate stability among others. Although the country apex bank implemented several monetary policies in the past years but most if these implemented policies are often seen to be ineffective to achieve the desired outcome which is often to increase output of the manufacturing sector and price stability. Effective Fiscal Policy A good fiscal policy plays an important role in the economic development of a country such role as maintaining an economy at full employment so that the savings capacity of the economy is not impaired and also raise marginal propensity to save by the community as far as above as the propensity as possible without discouraging workforce. The country implement fiscal policy in the past years can also be said be ineffective as marginal propensity to consume have always being high relative to marginal propensity to save due to persistent inflation in the past years. Upgrading and Development of Natural Resources Endowment In economics, natural resources are categorized under land which is one of the factors of production. Although the country is blessed several natural resources but the productivity of these natural resources can be said to be underutilization resulting from poor management. Epileptic Power Supply This is a major issue causing under-utilization in the capacity of the Nigerian manufacturing industry. This has forced many industries to either relocate to neighbouring countries in Africa where power supply is much stable relatively to Nigeria or closed down. 1.2 Statement of Study Nigerian manufacturing sectors comprises of four different players namely multinational, national, regional and local. In the last two decades most of other players apart from the multinational companies have left the country manufacturing sector to neighboring countries due to unpredictable government policies, lack of basic raw materials, most of which are imported. In recent time too, some of these multinationals are leaving the country also due to exchange rate instability. The manufacturing sector of the country accounts for a lower percentage of the countrys GDP compare to sectors like agriculture and oil sector which are the mainstay of the country economy and the capacity utilization of the countrys manufacturing have been continuously declining since the last decades due to some factors stated earlier. Although the Nigerian manufacturing sector can be said to prospective , with a large market of over 180 million people, endowment of natural and mineral resources as well as availability of cheap labour compare to developed countries. The development of the country manufacturing sector with therefore requires a concentrated efforts of the government in creating enabling business environment that will encourage and sustain investment of both local and foreign investors in the manufacturing sector because a well-developed manufacturing sector will stimulate economic growth and development sector. This research work will be solely based on assessing the benefits of derived from determining the capacity utilization in the Nigerian manufacturing sector ranging 1980-2009. 1.3 Objectives The objectives of the study include the following Identify the main determinants of capacity utilization in the Nigerian manufacturing sector, To analyse the operational relationship among raw materials, machinery, spare parts and the operators performance of selected firms To access the adequacy of operation maintenance and replacement cost in the selected firms Finally, to recommend policies that can improve the rate of capacity utilization in Nigeria manufacturing sector and consequently accelerate the growth of manufacturing output in the country. 1.4 Research Questions The research questions that will be answered in the study to achieve the stated objectives include the following What are the determinants of capacity utilization in the Nigerian manufacturing sector What of operational relationship exist among raw-material, machinery, spare parts and the performance of the selected firms Is the operation maintenance and replacement cost in selected firms adequate 1.5 Test of Hypothesis The hypotheses that will be tested in this study to achieve the state objective include the following HYPOTHESIS 1 H0 There is no significant relationship between raw materials, machinery and spare part and the operators performance of the selected firms. HI There is significant relationship between raw materials, machinery and spare part and the operators performance of the selected firms. HYPOTHESIS 2 H0 There is no significant difference between the cost of production and performance of the selected firms. HI There is significant difference between the cost of production and performance of the selected firms Significance of the Study Manufacturing sector is a very crucial sector to any country (either developed or developing economy) because of its contribution to economic growth and development in terms of investment, employment and price stability. Several research have been carried out to decipher the determinants of capacity of manufacturing firms in the Nigeria manufacturing sector basically on its contributory role to economic growth and development. This study is very important for development and growth in potential input and output in the manufacturing sector of the economy, it is very important for policy and project identification, preparing, appraisal, implementation and evaluation which will in turn aid and foster the rate of capacity utilization in the manufacturing sector of Nigeria. 1.6 SCOPE AND LIMITATIONS OF THE STUDY The scope of the study will simply specify both the period of analysis and years that will be covered by the study. The period of years and analysis will between 1980 and 2015.. Some practical limitations that are likely to be experienced in the course of analysis and gathering of necessary information are lack of adequate data, information, difficulties encountered in collecting and arranging the datas, this research work also had to contend with time and other resources constraint like finance, cost consideration also posed a serious problem. CHAPTER TWO LITERATURE REVIEW 2.0 Concept of Capacity Utilization Cassels (1937) is one of the earliest scholars to carry out a detailed study in the economic concept of firms capacity. This concept takes an explicit account of economics factors such as cost, price, revenue and profit. It can thus be defined from the economic perspective as the optimum output a firm can produced from a given factors of production. It should be noted that this economic approach to a firms capacity utilization considers a manufacturing firms capital as a quasi-fixed input, and also provide a basis to distinguish between short and long-run cost curves. In the long-run, the firm capacity can be adjusted in order to achieve optimal output (cost-minimizing, profit-maximizing) level. In the short-run, capital is fixed and only the variable inputs can be varied. Hickman (1964) defined economic capacity of a firm as that output level at which the short run average total cost curve is at its minimum while Klein (1960) and Friedman (1963) defined economic capacity as the output level at which the long-run and short-run average total cost curves are tangent. Capacity utilization is also defined as a concept in Economics, which simply refers to the extent to which a manufacturing firm or industry actually uses its installed capacity. Thus, it refers to the relationship between actual output produced and potential output that could be produced with installed equipment if capacity was fully used. Capacity utilization in industry is described as the level of utilization of an industrys installed productive capacity (Okpaleye, 1988). An industry would be said to be performing optimally when its installed production capacity is fully utilized. By contrast, in the cost approach, capacity output is an optimum level of output at which an additional unit of output would well exceed the output range. This capacity stock and the level of production inputs (Hanis and Taylor, 1988). Given capacity output as that maximum attainable level of output at any given time period, if an inputs available are fully utilized, capacity utilization is expressed as the ratio of actual output (A0) to capacity output (C0) multiplied by 100 i.e ( A0/C0 X 100) . Lund (1981) once called for the distinction between capital utilization and capacity utilization. He argued that while capacity utilization is a measured of a realized output relative to potential output, capital utilization ratio is a measured of utilized inputs of capital relative to available inputs of capital. Berndt (1990) defined capital utilization as the ratio of the desired stock of capital (given output quantity and input prices) to the actual stock of capital. Fa Berndt and Fuss (1989) pointed out that two measured of utilization coincide only if there is one fixed input (capital) and if production is characterized by constant returns to scale. The concept output is essentially a production concept in an industrial process. It refers to the production flow that is associated with the input of fully utilized manpower, capital and other relevant factors of production. The difference between capacity output and the actual output flow is regarded as the output gap while the ratio of the latter to the former is an index measure of the rate of capacity utilization (Fabayo, 1979). 2.1 NIGERIA MANUFACTURING INDUSTRY Before the independence in 1960 till mid-century, Nigerias industry sectors were dominated by agricultural production which was largely in subsistence scale. This is as result of the countrys fertile land and abundant mineral resources drove the economy. However, there was a shift from Agriculture sector to oil sector due to the oil boom in 1970. Thus, oil sector became the mainstay of the economy and made the highest contribution to the countrys Gross Domestic Product (GDP). The oil sector is also the major earner of the countrys foreign exchange which made the other sectors (agriculture and non-oil industrial sector) to be neglected by the government. 2.1.1 Major Nigeria Industry Sectors The mining sector, including the oil and natural gas segment, is the largest Nigeria industry sector. According to the 2015 figures, it accounts for more than 90 of the annual national production and generates more than 80 of the government revenues. The country produces 2.169 million barrels per day (2015 statistics). In terms of oil export volumes, the country ranks 8thin the world. The Nigerian oil sector is regulated by the Nigerian National Oil Corporation (NNOC). It is a member country of the Organization of Petroleum Exporting Countries (OPEC). Although major reforms have been undertaken to liberalize the countrys economy, the oil sector is still under the close scrutiny of the government. While, the oil sector is the major source of revenue for Nigeria, it is also central to civil unrest and border disputes. For long-term growth, the government has to strategically plan to develop the non-oil industries in the region. Other major industrial sectors in Nigeria are Telecommunication In the economic reforms of 2005, the government laid huge emphasis on improving the telecommunication sector. The Nigeria Communications Commission has the responsibility to develop mobile and internet communication facilities in the country. Mining The non-oil mining sector is yet to be developed completely to contribute towards national production. The country has significant reserves of coal, iron, gold, uranium and tantalum. The manufacturing, construction and chemical sectors are also gradually shaping up after the 2005 economic reforms. CHAPTER THREE RESEARCH METHODOLOGY 3.1 INTRODUCTION This chapter shall focus on ways in which data necessary to achieve the stated research objectives as well as answering the research questions will be collected and also the model that will be used to analyze the data will also described in this section. 3.2 Restatement of Research Questions The research questions that will be answered in the study to achieve the stated objectives include the following What are the determinants of capacity utilization in the Nigerian manufacturing sector What of operational relationship exist among raw-material, machinery, spare parts and the performance of the selected firms Is the operation maintenance and replacement cost in selected firms adequate 3.3 Research Methodology The study will therefore made use of both primary and secondary data. The primary data will used to capture the assessment of operators performance in the Nigerian Manufacturing sector while secondary data was employed to analyze the relationship between the key determinants of capacity utilization in Nigerias Manufacturing sector. The survey method presents research design, population, sample and sampling technique, research instrument, validity of the instrument, and reliability of the instrument, and data analysis. The sample for this study comprises of three states (Oyo state, Ogun State and Osun State) in the South West of Nigeria. Two firms will be selected from each of the three states giving a total of six firms for this study and 10 respondents from each of these firms. The firms are UP Printing Press and Gaso Furniture Company in Ibadan were sampled in Oyo State, Alumax Industries LTD and Twinstar Industries Ltd were sampled in Ogun state While International Breweries Ltd and Harvest field INDUSTIRES ltd were sampled in Osun State. Stratified and simple random sampling techniques were employed as the sampling techniques. The major instrument used for this study is questionnaire. The questionnaire was titled capacity utilization and its determinants in Nigerian manufacturing sector. The research instrument is subject to content and face validity. The instrument was presented to experts in Economics and industries respectively for refinement and suitability. The reliability of the instrument employed was Half-split reliability method for internal consistency. The reliability coefficient was determined using pearson product moment correlation coefficient. The data were analyzed using descriptive and inferential statistics. The statistical tools that were employed for data analysis are chi-square ( ) and ANOVA method. Frequency counts and percentage were used to analyze a Bio-data and general questions of this study. Secondly, the empirical investigation in this section focuses on model specification, a prior expectation, estimating techniques and sources of data 3.4 Model Specification The model for this study follows the work of Ukoha (2000) and Fabayo (1998), which took its roots from the theory of Berndit and Morrison. Therefore, rate of electricity generation in Nigeria (proxy for energy) is included in the determinants as a modified factor in the model. Therefore, the model for this study is specified below CU f (MGDP, INTR, CPI, CPF, ELEGR) CU b0 b1MGDP b2 INTR b3 CPI b4 CPF b5 ELEGR ut Where CU Capacity utilization in the Nigerian Manufacturing Sector MGDP Real Manufacturing Output Growth INTR Interest Rate CPI Consumers Price Index CPF Fixed Capital Formation in manufacturing sector ELEGR Electricity Generation Rate (proxy for energy) ut Stochastic Variables 3.4.1 A priori expectation A positive relationship is expected among all the variables except interest rate with negative expectation. 3.4.2 Model Estimation Technique The estimation procedures employed in this empirical investigation is based on co-integration analysis and the Error Correction Model. The choice of this technique is informed by the need to determine the time series characteristics of the variables that are used in the study. The first step is to determine and test the stationarity of the data. The second step after testing for stationarity is the establishment of long-run relationship among the variables. After the order of integration of the variables are ascertained, that the long-run relationship among the variables can be determined. Therefore, Co-integration Analysis and Error correction Model (ECM) would be formulated and estimated. 3.4.3 SOURCES OF DATA Data needed for this research work were secondary in nature. It was sourced from the various versions of the Central Bank of Nigeria statistical bulletins and National Bureau of Statistics. CHAPTER FOUR DATA PRESENTATION AND ANALYSIS 4.1 Introduction In this chapter of the , The socio- economic characteristics such as the age distribution, gender distribution, marital status and educational qualification distribution, of the respondents whom questionnaire were administered to will be analyzed and presented using frequency count and percentage. 4.2.1 Analysis of Information Concerning Respondents The information about the respondent will be analysed and presented in tabular form. These information include their age distribution, gender distribution, marital status and educational qualification distribution TABLE 1-4 Distribution of the socio-economic characteristics Table 1 Age Distribution Age DistributionCategoriesFrequencyPercentageABelow 18-NILB18-241830C25-402236.67D41-601525E61 and above58.33Total60100 Source Field work 2018 The table above indicate that workers between the age bracket (18-24) are 18 (30), workers between the age bracket (25-40) are 22 (36.67), workers between the age bracket (41-60) are 15(25), workers above 60 are 5(8.33).This indicates that majority of these workers are adult and mature. TABLE 2 Gender Distribution Gender DistributionFrequencyPercentage AMale3965BFemale2135Total60100 Source Field Study 2018 The table above indicate that 39 (65) are male while 21 (35) are female. This implies that the majority of the workers in the firms under review are male TABLE 3 Educational Level Educational LevelCategoriesFrequencyPercentage AInformal Education 58.33BPrimary Education1220CSecondary Education1525DTertiary Education2440EOther46.67Total60100Source Field Study 2018 The table above indicates that the informal education is 5(8.33), the primary Education is 12(20), the secondary Education is 15 (25), and the tertiary Education is 24 (40). This implies that majority of staff in these firms are literate. TABLE 4 Marital Status CategoryFrequencyPercentage Single3558.33Married1535Widow/Widower58.33Divorce35Other23.33Total60100Source Field Study 2018 The table above indicates that 58.33 are married, 35 are single, and both widow and divorce are 8.33 respectively. This table confirms that most of the workers are married people and they are mature and responsible 4.2.2 ANALYSIS OF INFORMATION CONCERNING FIRM In this sub-section, the following information were analyzed concerning the firms category of sub-sectors of the firms, ownership of the firm, location of the firm and the proportion of skilled labour to total employees of the firms. Table 5-8 Information concerning Firm Table5 Category of sub-sectors Group ItemsFrequencyPercentageCategories of Sub-sectorsAFood Beverage1220BChemical Pharmaceutical1830CPlastic Rubber Products915DPaper/Printing/Furniture2135ETextiles–FOthers Specify–Total60100Source Field Study 2018 The table above indicates that most of the sub-sectors of the manufacturing firms are paper/printing and furniture which is above 35, while chemical and pharmaceutics is 30, food/beverage is 20 and plastics and rubbers products in 15 respectively, none is Textile because almost all textile industries in Nigeria are moribund due to preference for imported clothing material Table 6 Ownership of firms Ownership of FirmsItemsFrequency Percentage APrivate60100B Public–Total60100Source Field Study 2018 Table 6 shows that all of these firms under review are private firms whose main motive is profit maximization. Table 7 Location of firms Location FirmsItemsFrequencyPercentage ARural Area–BUrban Area60100Total60100Source Field Study 2018 Tables 7 indicates that majority of these firms under review are located in urban areas which is in conformity with one of the features of manufacturing firms in Nigeria. Table 7 Firms Age in years The variables to be deemed appropriate to dealt with in respect to production and cost of production are cost of raw materials, cost of fuel per month, cost of the spare parts, cost of maintenance per month and cost of depreciation of machines. The following questions would be equally discussed Is supply of raw material adequate How is the maintenance of firms machinery Does the firm make spare parts available when necessary Table 10-13 Information on Production and the cost of production Table 10 costs of production SNVARIABLEHIGH PERCENTAGELOW PERCENTAGEACost of Raw-Materials4020BCost of Fuel per Month4515CCost per Spare Parts3525DCost of Maintenance per Month4614ECost of Depreciation of Machine2040Total186114Source Field survey 2018 Table10 indicates that there is high cost of raw materials, spare parts, fuel and maintenance which may be as a result of inflation and increased foreign exchange rate. Table 11 Is supply of raw material adequate RespondentsFrequencyPercentage Yes2541.67No3558.33Total60100Source Field survey 2018 Table 11 revealed that 58.33 of the respondents indicate that the supply of raw materials is inadequate against 41.67 of respondents that agreed on adequate supply of raw materials. This is therefore implies that most firms under the review import some, if not all, of their raw-materials Table 12 How is the maintenance of firms machinery RespondentsFrequencyPercentage Very Regular1525Fairly Regular2541.7Occasionally1016.7Not Regular1016.7Source Field survey 2018 The table 12 above indicates that most of the firm under review maintenance of their machinery is fairly regular in order to maintain effective and steady production Table 13 Does the firm make spare parts available when necessary RespondentsFrequencyPercentage Yes2440No3660Total60100Source Field survey 2018 The response of respondents is a little bit negative which indicates that there is difficulty in getting some of the spare parts. This is attributed to the fact that there are import-oriented spare parts which are not easily available in Nigeria 4.3 Test of Hypothesis In this section, the hypothesis specified in chapter one will be tested using statistical tools which comprises chi-square (X2) and ANOVA methods. 4.3.1. RE-STATEMENT OF HYPOTHESES HYPOTHESIS 1 H0 There is no significant relationship between raw materials, machinery and spare part and the operators performance of the selected firms. HI There is significant relationship between raw materials, machinery and spare part and the operators performance of the selected firms. HYPOTHESIS 2 H0 There is no significant difference between the cost of production and performance of the selected firms. HI There is significant difference between the cost of production and performance of the selected firms For hypothesis 1, responses of questions in table 11, 12 and 13 was used to analyze the ANOVA ANOVA Table VariableDFSSMSF-ratio calF-ratio tabOperational Materials2354012700.30034.74Error7296004228.57Total9331405498.57Source Field survey 2018 DECISION RULE The rule of thumb here is that if F-cal. is greater than F-tab., the null hypothesis is rejected and vice versa. From the analysis above, it was discovered that F-cal is less than F-tab., therefore, the null hypothesis is accepted and alternative is rejected. This implies that there is no significant relationship between operational materials and operational performance of the firms. For hypothesis 2, responses of questions in table 10 and Chi-square table in the appendix was used to analyze chi-square(X2 ) Decision rule Reject H0 if X2 cal X2 tab , Accept if X2 cal X2 tab The rule of thumb here is that if X2 cal is greater than X2 tab , the null hypothesis is rejected and vice versa. From the analysis above, it was discovered X2 cal that is greater than X2 tab therefore, the null hypothesis is rejected and alternative is accepted. This shows that there is significant difference between the cost of production and operational performance of the selected firms. The implication is that there is high cost of production which mitigates the performance of the selected firms and as well, the capacity utilization. Secondly, from the empirical analysis dimension, this chapter concentrates on the presentation of the empirical results which comprise of the unit root test, co-integration analysis and error correction mechanism test. 4.4 TIME SERIES PROPERTIES OF THE VARIABLE To ascertain that the study is free from problem of spurious regression, the study examines the time series properties of the variables. In economic literature, most time series variables are non-stationary and including non-stationary variables in the model can lead to spurious regression co-efficient estimate (Granger Newbold, 1977). Table 4.4.1 Augmented Dickey- Fuller Test Result Variables ADF Statistics Critical Value @ 5Order of IntegrationRemarksCU-3.350811-2.957001I(0)StationaryELEGR-6.477039-2.957110I(0)StationaryMGDP-3.734618-2.957110I(0)StationaryCPI-3.279473-2.960411I(0)StationaryCPF-6.343130-2.957110I(0)StationaryINT-5.900700-2.957110I(0)StationaryECM-3.297297-22.957710I(0)StationarySource Own Computation Using SPSS The table 4.4.1 above presents the results of the Augmented Dickey-Fuller test. The test however, shows that all the variables were stationary at levels. This means all the variables such as CU, ELEGR, MGDP,CPI, CPF and INT are integrated of order zero. The implication of this is that the variables considered in the model for the purpose of this study do not contain a unit root and it permits to proceed to co-integration test and also meet the condition for Johansen co-integration. Johansen co-Integration Result The results emanating from the unit root test indicates that the variables were stationary at levels. The implication of this is that parameter estimates using ordinary least square regression may be misleading and therefore may not serve the purpose of the study. To determine the number of co-integrating vectors from the results we consider the maximum eigen value test using the more critical values of Mackinnon Haug Michelis (1999). Table 4.4.2 Johansson Co-interaction Result Hypothesized No of CE (s)Eigen ValueTrace StatisticsCritical Value @ 5ProbNone0.761688127.110495.753660.0001At most 10.66010882.6510769.818890.0034At most 20.56363249.1981447.856130.0372At most 30.30948423.4907829.797070.2228At most 40.18425012.0108915.49471 0.1564At most 50.167901 5.6979063.8414660.0170Source Own Computation Using SPSS N.B Denotes rejection of the Hypothesis at the 0.05 level Mackinnon Haug Michel is (1999) P-values. The table 4.2.2 above presents the results of the Johansen co- integration estimates. The long run test identifies three (3) integrating equations at 5 critical value. From the estimates of this study, the normalized co-integrating co- efficient with the highest log-likehood ratio in absolute term is chosen as the long-run equilibrium equation. The equation is thus presented as follows CU -102.2242ELEGR 79.45698 MGDP 152.651141CPI 3.696358 CPF 40.37311 INT (29.7335) (18.9281) (19.0929) (2.00720) (16.5263) N B Standard Errors are in parenthesis The normalized equation above represents the long-run equilibrium equation. The equation revealed that exogenous variables of ELEGR and MGDP maintained negative long-run relationship with the dependent variable, capacity utilization (CU). This implies that in the long-run, the level of electricity generated in Nigeria (ELEGR) will pull down the capacity utilization (CU) in Nigeria by about 102. Also going by the level of manufacturing share of the GDP in (MGDP) in Nigeria today, the level of capacity utilization in the country will be pulled down by about 79. While on the other hand, the consumer price index (CPI), and interest rates (INT) maintained positive long-run relationship with level of capacity utilization in Nigeria. The results showed that the CPI, CPF and INT will improve the level of capacity utilization in the country by about 152.65, 3.7 and 40.4 respectively in the long-run. Thus, CU, ELE, MGDP, CPI, CPF, INT co-integrate in the long-run which implies that capacity utilization and the functional components of the determinants of capacity utilization maintained a long run relationship. CHAPTER FIVE CONCLUSION AND RECOMMENDATION 5.1 Introduction In this chapter, the conclusion based on analysis done in the previous chapter will be discussed and appropriate recommendations will be made on how the capacity utilization in the Nigerian manufacturing will be enhanced. 5.2 Conclusion The study was set out to examine the determinants of capacity utilization in the Nigerian manufacturing sector. From the analysis done so far, it was concluded from the survey analysis that there is low production in the manufacturing sector in Nigeria as a result of high cost of imported raw materials, machinery, and spare parts owing to increased interest rate and exchanged rate. It was deduced from the analysis that poor performance of infrastructural facilities mainly frequent distortion in electric power rendered a reduction in capacity utilization. The empirical study found that some of the determinants of capacity utilization such as CPF and CPI have positive long-run relationship with capacity utilization which implies that CPF and CPI are promoting capacity utilization. There is negative relationship between electricity generation (ELE) and real manufacturing output growth which inferred that there is low power generation and low manufacturing productivity growth rate in Nigeria respectively. This verifies the result obtained in the test of hypothesis. There is a positive long run relationship between interest rate and capacity utilization but statistically insignificant. This has resulted to high cost of production as inconformity with the field survey results. Policy Recommendations Based on the findings from this study, the following recommendations are suggested. Putting the economy back to the trajectory of growth and development, government should make adequate provision of infrastructural facilities especially electricity generation. Relevant measures to enhance policy coordination and structural institutions among the various arms of government should be put in place. This would proffer solutions to the policy inconsistencies that result to macro-economic instability which is creating high interest rate. Y, dXiJ(x(I_TS1EZBmU/xYy5g/GMGeD3Vqq8K)fw9
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