the impact of lending rate on manufacturing industry in nigeria (final)
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THE IMPACT OF LENDING RATE ON MANUFACTURING INDUSTRY IN NIGERIA
BY
SOYEBO KOLADE ABIODUN
120205211
A RESEARCH PROJECT SUBMITTED TO THE DEPARTMEN OF FINANCE,
FACULTY OF BUSINESS ADMINISTRATION, UNIVERSITY OF LAGOS, IN
PARTIAL FUFILMENT OF THE REQUIREMENTS FOR THE AWARD OF
BARCHELOR OF SCIENCE DEGREE IN FINANCE
JUNE 2016
CERTIFICATION
This is to certify that this project titled “The impact of lending rate on manufacturing industry in
Nigeria” was carried out by SOYEBO, KOLADE ABIODUN with Matric number 120205211 of
the department of Finance, University of Lagos under my supervision.
………………………….. ……………………..
MR. S. O. OJOGBO DATE
PROJECT SUPERVISOR
…………………………… ……………………..
PROFESSOR (MRS.) E.O. ADEGBITE DATE
HEAD OF DEPARTMENT
DEDICATION
I dedicate this research work to the God Almighty for granting me wisdom and strength for my
course of study and this research work. To him be all glory and honour.
ACKNOWLEDGEMENTS
I thank God Almighty for his guidance and protection from the beginning of my journey in
University of Lagos up to this point and for making this research work a success All glory and
honour be unto His name.
I am equally grateful to my indefatigable project supervisor Mr. S.O. Ojogbo for his constructive
guidance and fatherly support, I remain forever indebted to him.
My gratitude goes to my Wonderful parents The Revd. and Mrs. S.O. Soyebo for their love, care,
prayers, support and understanding. May you reap the fruits of your labour in Jesus’ name,
Amen. I also appreciate all my siblings for their encouragement, God bless you.
Special thanks to Very Revd. D.F. Adekoya for his prayers, assistance and support, may God
take him to greater height.
To all my friends who immensely contributed both morally and academically to this research
work especially Azeez, Dare, Deola, Seun, Innocent, Bolaji, Dayo, I feel elated to have you as
my companion. These are my words to you—I am not the best but I know I have good friends
like you, I may not be liked by all but I know I am loved by God for having you. I thank you all
for standing by me; I will never forget you all. God bless you.
ABSTRACT
This study examines the impact of lending rate on manufacturing industry in Nigeria over the
period of (1990-2014). The study used data sourced from the Central Bank of Nigeria (CBN). E-
views 7 was used for analysis of the data. Augmented Dickey-Fuller test statistics was used to
conduct unit root test for stationarity of data. The result was that the series of data were
stationary. The ordinary least square technique (OLS) was used to specify and examine the
relationship between the variables lending rate (LR), Government expenditure (GOVEX) and
inflation rate (IFR) which were considered as independent variables and the manufacturing
sector output (MSO) which was considered as the dependent variable.
In conclusion it was found out that there is no significant relationship between lending rate (LR)
and manufacturing sector output (MSO), manufacturing industries does not enjoy enough credit
facilities from commercial banks in Nigeria owing to the fact that lending rate of commercial
banks in Nigeria due to the fact that the lending rate seems to be too high. Recommendation
where made for learners and further research works.
TABLE OF CONTENT
Title page ……………………………………………………………………………………. i
Certification page …………………………………………………………………………… ii
Dedication …………………………………………………………………………………... iii
Acknowledgements …………………………………………………………………………. iv
Abstract ……………………………………………………………………………………… v
Table of contents ……………………………………………………………………………. vi
List of tables ………………………………………………………………………………… ix
CHAPTER ONE: INTRODUCTION
1.1 BACKGROUND TO THE STUDY……………………………………………….. 1
1.2 STATEMENT OF PROBLEM …………………………………………........ 3
1.3 OBJECTIVES OF THE STUDY ..................................................................... 4
1.4 RESEARCH QUESTION ........................................................................... 4
1.5 RESEARCH HYPOTHESIS ............................................................................ 4
1.6 SCOPE AND LIMITATION OF THE STUDY .................................................. 5
1.7 SIGNIFICANCE AND RELEVANCE OF THE STUDY .................................... 5
1.8 OPERATIONAL DEFINITION OF TERMS ..................................................... 6
REFERENCES
CHAPTER TWO: LITERATURE REVIEW AND THEORETICAL FRAMEWORK
2.1 REVIEW OF EMPIRICAL LITERATURE………………………………………... 9
2.2 CONCEPTUAL FRAMEWORK …………………………………………………... 13
2.2.1 THE MANUFACTURING INDUSTRY …………………………………………… 13
2.2.2 LENDING RATE ……………………………………………………………………19
2.2.3 INFLATION ……………………………………………………………………….. 28
2.3 THEORETICAL FRAMEWORK ………………………………………………….. 30
2.3.1 THEORIES OF INTEREST RATE ………………………………………………… 30
REFERENCE
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN ……………………………………………………….......... 38
3.2 POPULATION OF THE STUDY …………………………………………………. 38
3.3 TYPES AND SOURCES OF DATA ……………………………………………… 38
3.4 SAMPLING TECHNIQUE AND SAMPLE SIZE ………………………………... 38
3.5 MODEL SPECIFICATION ……………………………………………………...39
3.6 A-PRIORI EXPECTATION ……………………………………………….……… 39
3.7 DATA ANALYSIS TECHNIQUE ………………………………………………..40
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
4.1 DESCRIPTIVE STATISTICS
………………………………………………………………………….. 41
4.2 UNIT ROOT TEST RESULT AND INTERPRETATION
……………………………….. 42
4.3.1 INTERPRETATION OF RESULTS
………………………………………………………………… 44
4.3.2 MULTICOLLINEARITY TEST
…………………………………………………………………….. 46
4.3.3 TEST OF HYPOTHESES
……………………………………………………………………………….. 47
4.4 REFERENCE
…………………………………………………………………………………………………. 50
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSON AND
RECOMMEENDATIONS
5.1 SUMMARY OF FINDINGS ......................................................................... 51
5.2 CONCLUSION BASED ON FIDINGS ………………………………………... 52
5.3 RECOMMENDATIONS ……………………………………………………...... 52
5.4 SUGGESTIONS FOR FURTHER STUDIES ………………………………..... 53
BIBLIOGRAPHY
APPENDIX
LIST OF TABLES
Table Titles Pages
4.1 Descriptive Statistics 41
4.2 Result of unit root test 43
4.3.1 Ordinary Least square Regression Result 44
4.3.2 Summary of A Priori Expectation 46
4.3.3 Variance Inflation Factors 47
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND TO THE STUDY
With the recent trend in the sharp switch from the oil and gas driven economy as a result of
reduction in the price of crude oil, the Nigerian economy will be on the brink of relying on key
real industries like the manufacturing industry to sustain the growth of the Nigerian economy as
the leading economy in Africa. The Nigerian economy comprise of several industries, which
constitute the key industrial sectors responsible for sustaining the growth and expansion of the
entire Nigerian economy (Abdulahi, 2008).
The industry under examination, manufacturing industry, is responsible for transforming all
forms of numerous raw materials into marketable finished or partly finished products that are
required for daily needs and existence of people in the society. It constitutes a major fraction of
the real industry in any growing economy. The industry is also expectedly responsible for
generating foreign exchange earnings for the economy through the exportation of its finished or
partly finished products.
However, it is worthy of note that the manufacturing industry of the Nigerian economy suffer for
lack of funds which is caused by high lending rate and remains the most unfortunate and hardest
hit by the high lending rates of banks, given that the major problem facing the Nigeria
manufacturing industry is the inability of actors in the industry to access cheap and adequate
finance for investment purposes in the industry (Dikko, 2004).
While banks constitute the primary source of capital for industrialists, the performance of the
manufacturing industry in Nigeria has been constrained due to inadequate funding culture of the
Nigerian banks. In this light, it has become obvious that the banks, especially the commercial
banks, have not been effectively contributing their expected economic quota to the output of the
manufacturing industry of the Nigerian economy. It is also discovered that even when banks
choose to lend, they do so at high interest rates that greatly inhibit manufacturers’ comfort to
offset (Nzotta, 1999).
The manufacturing industry of the economy is considered one of the most important industries of
the economy, and for obvious reasons, it is affected by the unprecedented increase of banks high
lending rate to borrowers. Therefore, this study is poised at ensuring that banks who are the
ultimate source of loan to the industry would be made to realize that manufacturers are quality
customers, and lending rates should be a dialogue between the two industries so that the
manufacturing industry could survive.
To appraise the effect of this situation prompted this study so as to provide research evidence on
how and why lending rate affect the manufacturing industry of the Nigerian economy.
1.2 STATEMENT OF PROBLEM
The Manufacturing industry in Nigeria has been experiencing stunted growth in times past, while
its contribution to gross domestic product has remained very low, and according to the rebased
Gross Domestic Product (GDP) value of 2014, Nigeria has been named the 1st and 27th largest
economy in Africa and the world respectively.
In the views of Olorunsola (2001), the Nigerian Banks are predominantly highly liquid, but carry
on with the policy that lending to the manufacturing industry is very risky and increasing credit
facilities to the manufacturing industry is not justified in terms of risk and cost frameworks of
banks.
Consequently, banks charge high interest rates, make demands for high level of collateral and
provide fewer loans advancement for more than a year’s duration to the manufacturing industry.
Coupled with the above, high lending rate in the Nigerian financial system becomes a reflection
of extremely poor infrastructural facilities and inefficient institutional framework necessary to
bring about substantial reduction in the risk associated with financing such an important industry
in the economy.
Prominent among the obstacles facing the performance of manufacturing industry in Nigeria is
the lack of adequate bank credits to the manufacturing industry of the economy. The banks
especially the commercial banks have not been contributing effectively to the output of
manufacturing industry of the economy.
1.3 OBJECTIVES OF THE STUDY
The main objective is to examine the impact of Bank lending rate on manufacturing sector output
in Nigeria. However, the following specific objective will be reviewed:-
1. To investigate the relationship between inflation rate and manufacturing sector output in
Nigeria.
2. To investigate the relationship between government expenditure and manufacturing
sector output in Nigeria.
1.4 RESEARCH QUESTIONS
1. What is the inpact of bank lending rate on manufacturing sector output in Nigeria?
2. Is there relationship between bank inflation rate and manufacturing sector output in
Nigeria?
3. Is there relationship between bank Government expenditure and manufacturing sector
output in Nigeria?
1.5 RESEARCH HYPOTHESES
1. Hθ: Lending rate has no significant impact on manufacturing sector output in Nigeria.
H1: Lending rate has significant impact on manufacturing sector output in Nigeria
2. Hθ: There is no significant relationship between inflation rate and manufacturing sector
output in Nigeria.
H1: There is significant relationship between inflation rate and manufacturing sector output
in Nigeria.
3. Hθ: There is no significant relationship between government expenditure and manufacturing
sector output in Nigeria.
H1: There is significant relationship between government expenditure and manufacturing
sector output in Nigeria.
1.6 SCOPE AND LIMITATION OF THE STUDY
The data fot this study will be collected from the Central Bank of Nigeria statistical bulletin to
cover the time frame of 1990 to 2014.
Limited time is a factors militating against the quest for sourcing more information that would
enable deeper penetration into the study.
1.7 SIGNIFICANCE AND RELEVANCE OF THE STUDY
A number of benefits is attached to the relevance of this study which are:
The study will help in investigating the relationship between bank lending rate, inflation rate,
governmennt expenditure and manufacturing sector output
The study will also help to bridge the weak link between the financial and real industries of the
Nigerian economy, in which much of banking industry resources have only been channelled to
the services industry, effectively crowding out the manufacturing industry of the economy.
This will also amout to high reduction in importation of finished products, due to better and
enhanced support for the industry. Also, improved foreign direct investment may likely occur
due to the involvement of the government support in the affairs of the industry, granting
foreigners the expected confidence to operate effectively in the Nigerian manufacturing business
environment. This study will be beneficial to the manufacturers , as it will help in possibe
expansion in their scope of business and operations through access to improved lending rate
options.
The government will also have the opportunity to reduce unemployment rate in the economy,
given that the industry will effectively engage the services of more manpower resources towards
the effective production of goods and services.
1.8 OPERATIONAL DEFINITION OF TERMS
Lending Rate: This is the percentage of the borrowed funds a customer must pay to the bank for
use of loan.
Inflation: it is a persist tendency for prices and money wages to increase. The dictionary of
economics said “inflation is measured by the proportional changes over time in some appropriate
price index, commonly a consumer price index or a GDP deflator” inflation occurs when the
general price level is rising.
Manufacturing industry: Its refers to those industries which are involved in the manufacturing
and processing of items. They indugle in either creation of new commodities or in value
addition.
1.9 REFERENCES
Abdullahi, S. A. (2008). Nigeria Vision 2020: The Recommendations of the Nigeria
Economic Submit Group. Retrieved from file: //E: Nigeria’s %20 Vision 202020 on
December 19, 2008.
Dikko, L.M.,(2005) “The Role of Banks in Improving Socio-Economic Growth” The
Nigerian Banker April-June 2005 pps 10-23
Nzotta, S. M. (1999). Money, banking and finance: Theory and Practice (2nd Ed). Owerri:
Hudson Jude Nigerian Publishers.
CHAPTER TWO
LITERATURE REVIEW AND THEORETICAL FRAMEWOWK
2.1 REVIEW OF EMPIRICAL LITERATURE
It becomes imperative for this study to discuss the concept of manufacturing in Nigeria and
challenges and prospects facing the sector before the raised questions are addressed. Relevant
literature of some researchers are reviewed to give insight into the work.
Muhammad Auwala Haruna (1990) empirically investigates the impact of interest rates and other
macro-economic factors on the manufacturing performance in Nigeria using co-integration and
an error correction mechanism (ECM) technique with annual time series address the interest rate
spread and government deficit financing which has a negative impact on the growth
manufacturing sector in Nigeria.
Amassoma et al. (2011) examined the nexus of interest rate deregulation, lending rate and
manufacturing industry in Nigeria by employing co-integration and error correction techniques
on annual data spanning 1986 to 2009. The findings showed that interest rate deregulation has a
positive and significant effect on manufacturing industry.
Central bank statement issued in (1989) set some guidelines on the speeds of banks average cost
funds their maximum lending rates as well as minimum level of saving deposit rates. This
prescription was necessitated by the rapid increase in bank lending rates.
Recently, the government approved vision 20-2020 for the world by 2020 (the times of Nigeria
2008). The objective of the vision 20-2020is in line with the various studies and projections by
Goldman Sachs that Nigeria will be the 20th and 12th largest economy of the world by 2025 and
2050 respectively ahead of Italy, Canada, Korea among others and Africa's biggest economy by
2050.The vision is to be realised through the growth of the private sector.
Accordingly, the Nigerian government has also adopted the Public Private Partnership (PPP)
strategy which is designed to lead to dramatic improvement in quality, availability and cost-
effectiveness of service.
Soyibo and Olayiwola (2000) suggested and studied the vector Error Correction model (VECM)
which was employed after going through a sort of stepwise procedure with many transformation
s of data and testing the number of co-integrating vectors to curb set a balance on the interest rate
and reduce inflation.
Akpan (2004) conducted a study to empirically explore the effect of financial liberalization in the
form of an increase in the real interest rates and financial deepening on the rate of economic
growth in Nigeria using the endogenous growth model; he used the Error model (ECM) to
capture both short and long run impact of the variables in the model. Overall, the results show a
positive impact of financial liberalization on the conduct of the economy and its growth.
World bank(2002) reveal that high interest rate in the Nigerian financial system is a reflection of
the extremely poor infrastructural facilities and inefficient institutional framework necessary to
bring about a substantial reduction in the risk associated with financing an extremely traumatized
economy.
Olokoyo (2011) examined the determinants of commercial banks’ lending behavior in Nigeria.
From her findings, commercial banks’ deposits have the greatest impact on their lending
behaviour.
Felicia (2011) used regression analysis to investigate the determinants of commercial banks
lending behaviour in Nigeria. The study discovered that commercial banks deposits have the
greatest impacts on their lending behavior
Victor and Eze (2013) examined the effect of Bank lending rate on the performance of Nigeria
deposit Money Banks. His research shows that lending rate and monetary policy rate has a
significant and positive effects on the performance of Nigerian deposit banks.
Odior (2013) empirically investigates the impact of macroeconomic factors on manufacturing
productivity in Nigeria over the period 1975 to 2011. The analysis starts with examining
stochastic characteristics of each time series by testing their stationarity using Augmented
Dickey Fuller (ADF) test and estimate error correction mechanism model. The findings were
reinforced by the presence of a long-term equilibrium relationship, as evidenced by the
cointegrating equation of the VECM. The study showed that credit to the manufacturing sector in
the form of loans and advances and foreign direct investment have the capacity to sharply
increase the level of manufacturing productivity in Nigeria, while broad money supply has less
impact and concluded that expansionary policies are vital for the growth of the manufacturing
sector in Nigeria which in turn would lead to economic growth.
Nneka (2013) examined the performance of monetary policy on manufacturing sector in Nigeria
for time frame 1986 to 2009. She noted that the main focus of monetary policy in relation to the
manufacturing sector has always been the stimulation of output, employment and the promotion
of domestic and external stability, while that of fiscal policy has been the generation of revenue
for the government and the protection of domestic infant industries against unfair competition
from import and dumping. Vector Error Correction (VEC) and Ordinary Least Square (OLS)
estimation were used to study the models for significance, magnitude, direction and relationship.
The study revealed that money supply positively affect manufacturing output index while
company lending rate, Company income tax rate, Inflation rate, Exchange rate has a negative
impact to the performance of the manufacturing sector over the years. They recommended that
expansionary policies are vital for the growth of the manufacturing sector in Nigeria which in
turn would lead to economic growth.
GLOBAL ECONOMIC DOWNTURN AND THE MANUFACTURING SECTOR
PERFORMANCE ON THE NIGERIAN ECONONMY
This research analysis the position of the manufacturing sector of the Nigerian economy both the
descriptively and empirically before the global met down and during the period of the global
melt down. It was discovered that before the melt down, all indicators of performance used
shows a down reward trend. The period during the melt down shows some little insignificant
improvement on some of the performance indicators such as manufacturing GPP, Capacity
authorization. Generally speaking, the manufacturing sector plays a catalytic role in a modern
economy and has many dynamic benefits crucial for economic transformation. In any advanced
economy or even growing economy the manufacturing sector as a leading sector in many
respect. It is an avenue for increasing productivity in relation to import replacement and export
expansion, creating foreign exchange earning capacity rising employment and per capital
income, which causes unique consumption patterns. Furthermore it creates investment capital at
a faster rate than any other sector of the economy while promoting wider and more effective
linkages among different sectors (Ogwuma 1986).
The world global melt down affected the world economy. The degree of the of the impact varied
form economy. This impact depends on the movement of what incomes, prices inflation and the
terms of trade. The global economy without any doubt experience serious turmoil especially in
the year 2007, 2008, 2009 and even now. World inflation rates was on the increase caused by the
surge in food and fuel prices. Global decline in 2008 while the foreign exchange market
experience instability as major currencies experienced weakness (Ogwuma 1986).
2.2 CONCEPTUAL FRAMEWORK
2.2.1 The Manufacturing industry
Manufacturing is defined as the “production of goods by industrial processes” Raw (2004).
Though Nigeria is blessed with abundant raw materials still Nigeria is nowhere in world market
in terms of manufacturing products. While some industrialized countries that are poorly endowed
with natural resources have become affluent societies through the execution of sound
manufacturing production development through the application of science and technology.
Before independence, agricultural products dominated Nigeria’s economy and accounted for the
major share of its foreign exchange earnings. Initially, inadequate capital investment permitted
only modest expansion of manufacturing activities. Early efforts in the manufacturing sector
were oriented towards the adoption of an import substitution strategy in which light industry and
assembly related manufacturing ventures were embarked upon by the formal trading companies
up to about 1970, where the prime mover in manufacturing activities was the private sector,
which established some agro-based light manufacturing units such as vegetable oil extraction
plants, turneries tobacco processing, textiles, beverages and petroleum products.
Arising from the foregoing affirmed centrality of industrialization as the pivot of economic
growth and development, industrialization process seems to be the main hope of most developing
countries such as Nigeria with large population and large labour force. In spite of these aspiration
which ought to have favoured effective industrialization process in an economically conducive
manufacturing environment, most of these results as reflected in the performance of the
manufacturing sector remain socio-economically undesirable and below minimal expectations.
Against this backdrop of realizing the vision 202020, current economic planning and policy
instruments may be diverted at the development of the key productive sectors, particularly
manufacturing and commerce for the promotion of an increasing pace of industrialization in
Nigeria. The major problem facing the Nigerian manufacturing sector, however, is having
adequate and cheap finance resource for investment decision making.
In recognition of this potential roles of the sector, it is claimed that successive governments in
Nigeria are continuing to articulate policy measures and programmes to achieve industrial
growth incentive and adequate finance for the real sector. The central goal of government policy
was to foster growth in the manufacturing sector. Over the years, and largely in response to some
of the previous policy strategies, the main features of the Nigerian manufacturing sector had
emerged.
Hence, the role of bank credits in the growth of manufacturing sector cannot be over-
emphasized. For instance, the Federal Government’s Appropriation Bill for the year 2005 has as
one of its broad policy objectives to achieve a high economic growth rate (i.e GDP of at least
5%) through a better mobilization and prudent use of economic resources. This objective was not
achievable due to insignificant levels of resources from the financial sectors that should be
mobilized and deployed to finance business expansion and growth in the sector at hand. Banks,
by default, have to be effective intermediaries for mobilizing and channeling deposits to the
productive sectors of the economy, especially, the manufacturing sector that is being discussed in
the course of this study.
In spite of continuous policy strategies to attract credits to the manufacturing sector, most
Nigerian manufacturing enterprises have remained unattractive for bank credits. For instance, as
indicated in central Bank of Nigeria (CBN) reports, almost throughout the regulatory era,
commercial banks’ loans and advances to the manufacturing sector deviated persistently from
prescribed minimal. Furthermore, the enhanced financial intermediation in the economy
following the financial reforms of the 1990s, notwithstanding, credits to manufacturing as a
proportion of total banking credits has not improved significantly averaging 15.7 percent
between 1990 and 1994 and 25.8% between 1995 and 2010. Consequently, many manufacturing
firms in the country have continued to rely heavily on internally generated funds, which have
tended to limit their scope of operations.
Despite the various national development plans put in place in Nigeria to enhance
industrialization the country still remain a mono-resource (crude oil) based economy. Growth in
manufacturing sector is also in a down ward trend and industrial capacity utilization is low.
The poor performance of the sector has been attributed to a number of the factors which include
amongst others: inflation, high cost of production due to high exchange rate and the epileptically
nature of power weak demand for manufactures (products) due to declining purchases power of
the populace high expenditure on spare parts repairs/maintenance legal and illegal influx of
cheap imported goods (globalization of trade) and political instability, especially during the
military regime (Burda 1997).
For the country to improve its manufacturing sector to evolve to a manufacturing based economy
and be relevant in the globalization of production and trade, it should pursue a combination of
those approaches and moves be able to monitor and manage its inflationary trend well,
generation and application of science and technology knowledge relevant to manufacturing
through in country research and development science and technology and innovation efforts
encouragement of foreign direct investment adoption of continuous improvements and
innovations programmes and a better and steadier power supply.
This is only possible in a national innovation system with the following enabling environments: a
well-founded 13 education system good and well maintained physical infrastructural; favorable
environment for research and development and innovations and stable and favorable economic,
legal and political conditions.
THE ROLE OF THE MANUFACTURING SECTOR ON THE NIGERIA ECONOMY
Lambo (1987) noted that "the manufacturing sector in Nigeria is similar to that of any
developing country that has pursued import substitution industrialization behind high protective
barriers"
The above as pointed by Bankole (2005) recorded that the role of the manufacturing sector in
economic development of Nigeria cannot be over emphasized. He claimed that a manufacturer is
an innovator who requires both our national corporation and support while trying to change the
economy's status of the nation for better.
Embracing the wonderful idea, Schumpeter (1996) wrote that "the manufacturer is an innovator
and he who undertake new combination of factors of production. This combination opens the
way for profit in a stationary state or during a down turn which then leads to upswing".
Based on this innovativeness of the entrepreneur, Schumpeter noted that over years, Nigerian
government have series of policies aimed at enhancing self-reliance especially through the
sector.
Following this discoveries, Bankole strongly stated that it can conveniently be said or claimed
that the industrial or manufacturing sector plays major roles in the economic development of
Nigeria.
He further opined that among the roles the manufacturing sector plays towards contributing to
and enhancing the economic development of Nigeria are:-
Provision of the essential finished goods required by Nigerians.
Earning of foreign reserves for Nigerian economy.
Creation of employment opportunities for Nigerian citizens.
Reducing the importation of the finished goods they produce.
Contributing further, a national publication captioned "Nigeria a viable black power" (1996)
noted that the back bone of the Nigerian economy is the industrial sector. In order to realize this,
the national publication recorded that Nigeria has adopted an industrial policy which places the
responsibility for creating an enabling environment for the government and makes the private
sector the main actor in the industrial scene.
Following the policy thrust and the realization of the fact that the private sector is making
encouraging effort as expected, this publication then wrote that "Government has further
restrained itself from going into fresh ventures especially in areas that the private sector has been
found to be better disposed to handle. The publication then observed that this development from
the manufacturing sector has reduced the unemployment stigma of the economy and more so, the
country-demands. In response to this national need, the manufacturing sector showed
commitment to reduce the huge spending on fertilizer importation.
In this regard, the publication opined that the country established fertilizer companies such as
federal superphosphate fertilizer company(FSFC) with installed capacity of 1,200.00 metric tons
of SSP-type of fertilizer and the national fertilizer company of Nigeria (NAFCON) limited
Onne,Port-harcourt with installed capacity of 700,000 metric tons,thus,the nation banned the
importation of fertilizer.
This remarkable fact according to Iwuoha (2000) presents a plus mark for the manufacturing
sector towards reviving the agricultural sector and thereby paves way for economic growth.
Furthermore the national publication noted that, the contribution of certain manufacturing
industries in Nigeria like the Anambra motor manufacturing company (ANAMMCO) which is a
joint venture between the federal government and the Mercedes Benz AG of Germany.
ANAMMCO has currently diversified to the production of water tankers, fire fighting vehicles,
mobile clinic vans, refuse disposal, vehicles and buses. The firm, despite its problems has been
able to achieve 55% local integration.
The above, according to this source, helps to facilitate the acquisition of appropriate technology
in the country's automobile. Sub-sector.
Soludo(2005) stated that "hopefully, with the privatization of key public parastatals like Nigeria
electrical power authority, now power holding company of Nigeria(PHCN)etc. and the continued
growth of private sector, the character of governance and politics will change in Nigeria.
Soludo (2005) adds that "more fundamentally, the results for the economy since 2000 and
especially under the national economic empowerment and development strategy (NEEDS)
Agenda have been better than under any other regime in our history".
2.2.2 LENDING RATE
PRIME LENDING RATE
According to Investopedia, it is a rate that commercial bank charge their most credit worthy
customers. Generally a bank’s best customers consist of large corporations. The prime lending
rate or prime interest rate is largely determined by the Federal funds rate which is the Overnight
rate which bank lend to one another. The prime rate is also important for retail customers, as the
prime rate directly affects the lending rate which are available for mortgage, small business and
personal loans.
FACTORS THAT INFLUENCE CHANGES IN LENDING RATES
Rates can change over time. A few factors that affect them according to (Loto, 2012) are:
Prevailing economic conditions in the country: This considers the effects of boom and
downturns in the economic conditions of the nation, which correspondingly dictates the
behaviour and reactions of lending institutions’ rates on funds and the expectations from their
public customers alike. During boom periods, interest expectations are likely to be relatively
low from both parties, while lending rates are expected to be generally high during economic
downturn situation.
How risky the borrower is: This portrays how good alternatively risky the credit seem to the
lending bank. How risky the loan is (especially with short term loans and loans with collateral
is it something of value, an asset or property that borrowing manufacturers pledge
when getting a loan, so that If they default with the repayment of the loan as agreed, the lender
can take collateral and sell it). Hence, banks (lenders) want manufacturers to have some skin
in the game. They are taking a risk so they want them to risk something too. Large loans and
borrowers without a solid credit history are most likely to need collateral. Bank lenders
usually define collateral requirements; that if manufacturers cannot meet them they may have
to pay higher rates or find another lender.
Eagerness of Lender: How eager the lender is to make loans or gather deposits is another
major factor to the availability of disbursable funds for real sectors of the economy to
gainfully utilize.
Low Level of Technology: This is perhaps the greatest obstacle constraining productivity. It
alludes to frequent breakdown of machines, leading to reduction in capacity utilization rates of
installed capacity in the organization. Low technology is therefore responsible for the inability
of local industry to produce capital goods such as raw materials, spare parts and heavy duty
machinery.
Policy Instability: Investment in Manufacturing requires long range planning. However, the
increasing policies inconsistency resulting in instability in the macroeconomic environment
adversely affects corporate planning. Hence, stable and consistent macroeconomic policies are
a pre-requisite for high performance in the sector.
Low Investment: Lack of cheap accessible funds has made it difficult for manufacturing
companies to make investments in modern machines, information technology and quality
human resource development which are critical for raising productivity and increasing global
competitiveness
High cost of Production: Increased cost, traced largely to poor performing infrastructural
facilities, high interest and exchange rates have all resulted to increased unit price of
manufactures, low effective demand for goods, liquidity squeeze and fallen capacity
utilization rates.
Lack of Funding: Funding challenge has made it difficult for manufacturing firms to to invest
in modern machines and equipment, information technology and human resource of their
organization. Also, high interest rates and the reluctance of financial institutions to comply
with laid down lending guidelines tend to frustrate corporate investments and fail to ensure
protection and growth of local industries.
LENDING OBJECTIVES OF COMMERCIAL BANKS
The commercial objective of commercial banks’ lending is to maximize profit, although other
social and economic functions tend to deflect banks from profit maximization as their primary
objective. Since banks are acknowledged agents of social, economic and political development,
they have a social responsibility. The extent of this expanded responsibility varies from country
to country and the social situation is a major determining factor, hence the role of commercial
banks as agents of development appears greater in developing countries of which Nigeria is one.
Nevertheless, the principal objectives of a bank are to provide growth, profitability and liquidity.
1. Growth
For any lending decision and activity to be worth the effort, there must be enough assurance that
it will lead to the bank’s business growth in terms of an additional variety of services, yielding
good income to the bank. It should also increase the available quality of bank’s loan resources. If
from the onset the lending carries far greater risks than are considered reasonable, it is likely that
it could turn bad at a future date and therefore fail to contribute to the bank’s loan resource
quality wise.
2. Profitability
As profit is necessary for the long term survival of the firm and as profitability is used as an
index for measuring managerial performance, it is natural that most company management
would consider and evolve a definite policy for maximizing return on investment as a prime
objective. In lending activity, commercial banks are concerned with safety of their loans since
they represent a chunk of depositor’s money and a source of income is less than the average cost
of borrowed funds. In Nigerian situation, where there is still competition for deposits,
particularly among corporate clients, sometimes at incredible rates, lending decisions must
achieve a reasonable degree of return and therefore lending officers normally prefer proposals
which have a variety of income sources
Like foreign business or local transfers. The end result is to enhance the profitability of the
bank’s loan resources.
3. Liquidity
There are existing safety measures to ensure that banks’ liquidity is reasonably maintained.
These are derived from the various traditional central bank control mechanism such as cash
reserve ratio and liquidity ratio. However, even within the available loanable funds, a bank
should maintain a prudent balance between its deposit funds and overall lending, such that the
maturity consideration is given prominence. For a commercial bank, it will be desirable to
provide short term facilities to individuals, commerce and industry by way of overdraft, which
can be recalled on demand or short term loans with maturities of between six and twelve months.
If the source of funds are essentially short, it will be imprudent and likely cause of illiquidity to
tie funds down perpetually on long term loan. This appears to be the greatest test problem for
most commercial banks in Nigeria. Commercial banks’ traditional role as providers of short term
finance notably overdrafts has changed. In its place they now wear the tag of “development
banks” involved in long term loans, mainly to the agricultural and manufacturing sectors so as to
contribute to industrialization, economic development process which the country is yearning for.
How this unique role is to be achieved from source of deposit funds that remain basically short
term and volatile is the difficult question which banks’ managements are continually finding
answers for.
THE IMPACT OF LENDING ON THE ECONOMY
Commercial banks in playing their intermediation role give out deposits mobilized to the deficit
unit of the economy in the form of loan which may be on short, medium or long term basis. This
loan can be private or public loan. Private loan is a loan or credit used by individuals and
businesses in order to carry on exchanges in the private sector of the economy, while the public
loan or credit is loan extended or used directly by a level of government such as local, state and
federal. Government borrows money primarily through the sale of bonds and other securities, if
tax revenues are not sufficient to cover current spending needs. Therefore loan facility has
become an inescapable part of everyday life. It can be good or bad, depending on the reason for
its need and the ability of the borrower to repay. The impact of lending therefore on the economy
is hereby stated below.
1. Raising of standard of living
Generally, consumers benefit from using loan facility because they are able to use future income
to pay for the needed goods and services, thus they can raise their current standard of living
based on their ability to earn or obtain funds in the future.
2. Handling Emergencies
The means of loan facilities have made it possible to deal with important emergencies and crisis
such as unexpected automobile repairs, medical problem and casualty losses which must often be
paid for immediately. As a result of loans, people are able to pay for these emergencies.
3. Expansion of Markets
Mostly, businesses rely on loan facilities to expand their market and find customers. The means
of loan facility enable most entrepreneurship to expand and to bring forth their businesses. The
use of loan facility is very significant in business expansion most especially for small and
medium scale entrepreneurship.
4. Acquisition of Financial Capital
Many businesses acquire capital to begin, maintain and expand their operations. Many firms
experience uneven cash flows where expenditures are refunded before cash arrives from sale of
products and services. New locations, new employees and marketing expenditures would often
not be possible without the availability of big loans.
5. Economic Growth and Stabilization
Loans has sometimes been referred to as oil for economic machinery. It enhances the flow of
money and the factors of production within the economic system. Therefore, there is no country
or nation that can survive without obtaining loan or borrowing to sustain her economic growth
and development by using funds for economic and social development. Furthermore, loan
facility has also provided a means to stabilize the level of economic activity by working to vary
the interest rates charged for using the loan facility. As a result of this, government i.e. central
bank have made use of monetary and fiscal policies to regulate and stabilize the economy since
the role of credit and loan facility is especially important in monetary policy because the goal is
to affect spending by controlling interest rates and also the expansion and contractions of bank
loans alter the nation’s money supply. However, the type of economic activities which are
supported by the extension of bank loans influences what is produced and how much of each
product is produced.
PRINCIPLES (CANONS) OF GOOD LENDING
The economic growth, business and commercial development of any nation is achieved through
the enviable lending role performed by its banking financial and quasi-financial institutions. In
most developing countries of the world, the lending function has become so paramount that is
has persistently been integrated into government policy formation in the National economic
development process.
A bank which aimed to be successful in the administration of its lending and credit facilities and
the implementation of its policies as well as remaining in business, should take into
consideration the following factors before lending. The factors are stated below:
Safety
The safety of any loan/advances is of paramount importance to the bank. Hence, banks lay great
emphasis on the 5c’s of the borrower which are :-( character, capacity, capital, collateral and
condition)and purpose of the loan. There must be reasonable certainty that the amount granted
can be repaid from profits and cash flow generated from the operations of the company. If the
advance is granted to a personal borrower, the source of repayment must not be doubtful. In
support of the safety requirement, the borrower must be able to provide acceptable security
which will serve as something to fall back on if the expected source of repayment should fail.
Emphasis laid by banks in ensuring safety of any loans are explained below:
Character
This is the willingness of the customer to repay, the customer must be
honest with good integrity and highly responsible.
Capacity
The success of the borrower’s business must have reflected the
customer’s financial condition and ability to repay through cash flow and earnings.
Capital
The borrower’s stake in business as also his intrinsic financial strength as reflected in his equity
capital or net worth.
Collateral
The borrower’s ability to offer quality assets to provide adequate
protection to the bank against default in repayment.
Conditions
Recent trends in borrower’s line of activity and changing economic
conditions that might impact his financial conditions and thereby the ability to repay.
Purpose of the loan
Customers should always indicate in their loan applications and clear
terms the purpose for which they require the bank advance. Purposes should be sent in accord
with customer’s type of business, trade or profession and without any legal barriers. The purpose
for which bank credit is sought must be viable, profitable and self-liquidating so as to ensure
evident and feasible source of loan and overdraft repayments. The credit officers should avoid
lending for speculative reasons. Customers advance proposal must be thoroughly scrutinized and
appraised to confirm their viability, profitability and that they fall in line with the current lending
policies. All the critical accounting ratios should be applied to ensure that there would be cost
benefits trade off in banking lending. There should be good marketing outlets for borrower’s
product lines.
1. Suitability
The bank worker should also satisfy himself about the suitability of an advance. Even where the
requirements of a borrower satisfy all safety and risk considerations, it is absolutely necessary
for the bank worker to ensure that the purpose of the loan is not in conflict with the economic
and monetary policies of the Government. In Nigeria bank lending is highly regulated and
controlled by the Central Bank. This is done through the issue of annual credit allocation
guidelines and the imposition of quantitative and qualitative limitations on bank lending. The
guidelines vary from year to year depending on the monetary policy being pursued by the
Federal Government. The purpose of the advance and its implications on economy are therefore
given due consideration when granting an advance.
2. Profitability
It is well fact that banks are businesses established mainly to make profits and not charitable
organization. Therefore, any facilities granted are expected to yield some profit to the bank.
What determines the amount of profit is the rate of interest charged.
2.2.3 INFLATION
In economics “inflation is a rise in the general level, of prices of goods and services in an
economy over a period of time” (Blanchard 2000). Inflation means a sharp upward movement in
the price level
Inflation means “too much changing too few goods”. Keynes says “any rise in the price level
after the level of full employment has been achieved”. When output is unresponsive to change in
money supply then we know that inflation has set in inflation generally \associated with the
abnormal increase in the quality of money resulting in the abnormal rise in the prices.
TYPES OF INFLATION
There are three major types of inflation as part of what Robert J. Gordon calls the ‘triangle
model. These types are classified based on their causes;
Demand pull inflation: Inflation caused by increase in aggregate demand due to increased private
and government spending etc. demand inflation is constructive to a faster rate of economic
growth since the excess demand and favourable market conditions will stimulate investment and
expansion. The failing value of money however, may encourage spending rather than saving and
so reduce the funds available for investment.
Cost-push inflation: presently termed “supply shock inflation” caused by drops in aggregate
supply due to increased prices of inputs for example. Take for instance a sudden decrease in the
supply of oil which would increase oil prices production for which oil is a part of their costs
could then pass this on to consumers in the form of increased prices.
Built-in inflation: Induced by adaptive expectations often linked to the “price/wage spiral
because it involves workers trying to keep their wages up (gross wage have to increase above the
CPI rate to net CPI after tax) with prices and then employers passing higher cost on to consumers
as higher prices as part of a “vicious cycle” built –in inflation reflects events in the past and so
might be seen as hangover inflation.
A major demand-pull theory centres on the supply of money. Inflation may be caused by an
increase in the quantity of money in circulation relative to the ability of the economy to supply
(its potential output). This is most obvious when government finance spending in a crises such as
civil war by printing money excessively often leading to hyperinflation a conduction where
prices can double in a month or less. Another cause can be a rapid decline in the demand for
money. As happened in Europe during the black plague.
We have some other types of inflation which are classified based on their behaviour.
Hyper-inflation: Hyper-inflation is also known as runaway inflation or galloping inflation. This
can usually lead to the complete breakdown of a country’s monetary system. However, this type
of inflation is short lived. In 1923, in Germany, inflation rate touched approximately 32 percent
per month with October being the month of height inflation (Blanchard 2000).
Creeping inflation: This is the type of inflation that proceeds for a long time at a moderate and
fairly steady rate of price. It can be explained as slow but unalterable continuing inflation that,
however it appears tolerable in the short run, never the less leads to important long-run cost
increases.
Sectoral inflation: The sectoral inflation takes place when there is an increase in the price of
goods and services produced by a certain sector of the industry usually primary goods or
services. For instance an increase in the cost of crude oil would directly affect all other sectors
which are directly related to the oil industry. Thus the ever increasing price of fuel has become
an important issue related to the economy all over the world.
2.3 THEORETICAL FRAMEWORK
2.3.1 THEORIES OF INTEREST RATE
The theory of interest rate is very controversial. This is indicated by the diverse attempts made
by economists over the last one hundred years to develop an acceptable theory of interest rate.
The various theories that have been developed are difficult to classify although it is possible to
trace the chronological order of the development of these theories from pre-classical to the
classical through the neo-classical. (Loanable funds). The Keynesian version and finally heading
to the Hick general equilibrium approach and the monetarist view on interest rates.
The classical theory of interest rate
This theory is associated with the name of David Ricardo, Piggon, Cassels, Walras, Tansing and
Knight. According to the classical theory, rate of interest is determined by the interaction of
demand and supply of capital or to be more accurate, by the intersection of the investment
demand schedule and the savings schedule. It is also be stated that the interest rate is determined
by the equality of savings and investment under the condition of perfect competition. The rate of
interest is constructed be the balancing factor, which equates the volume of savings with the
volume of investment. There is inverse relationship between the rates of interest rises, the
demand declines. In the same manner, if the rate of interest falls, the demand curves for capital
rises. That is why the demand curve for capital slopes downward from left to right.
The supply of capital on the other hand, at any particular time depends on a number of factors.
An important factor influencing the supply according to the classical economists is the rate of
interest. The public saves more at a higher rate than a lower rate. This is why the supply curves
of capital slopes downwards.
The classical economist believed that the rate of interest must be high enough to induce the saver
to forego consumption. If the public saves less, the total supply of capital will fall short of the
total demand and intimately the rate of interest will have to rise high enough to compensate the
saver.
The Neo-classical or the loanable funds theory of interest rate
The neo-classical or the loanable funds theory of interest was first propounded by the Swedish
economist Wicksell and later developed and supported by several leading American and Swedish
economist including Professor Robertson, Bertil, Lindhal and Mydal Seth. However, the theory
in its present form is associated with Professor Robertson. According to the theory, the rate of
interest determined by the demand and supply of loanable funds and those who borrow them the
rate of interest will be such as shall bring about equilibrium between, the demand and supply of
loanable funds. The loanable funds are wide in scope and include not only savings out of current
income but also bank credit, dis-hoarding and dis-investment. The classical theory of interest rate
refers only to savings out of investment and current income, they do not include bank loans,
wealth or disinvested assets actually; bank loans represent important funds which are available
on payment of interest to the borrowers. Likewise, hoarded wealth can also become available for
the purpose of investment. Dis-invested wealth is also another source of funds available to
borrowers since the loanable fund theory is more comprehensive, it is often referred to as
monetary theory of interest. This theory is one of the two general approaches that have been
followed in developing the modern monetary theory of the rate of interest.
Keynes liquidity preference theory of interest
As opposed to the classical theory, which might be termed as the real theory of interest, Keynes
after criticizing the classical theory propounded his own theory of interest. This theory is also
called the monetary theory of interest because according to this theory, the rate of interest can be
controlled through variations in the supply of money. According to Keynes, interest is purely a
monetary phenomenon because the rate of interest is calculated in terms of money. It is also a
monetary phenomenon in the sense that it is determined by the demand for and supply of money.
Keynes defined interest as the reward paid for parting with liquidity for a specified time. He was
further to state that money is the most liquid asset and people generally like to keep their assets
in cash. Therefore, if they are asked to surrender this liquidity, they must be paid a reward. This
is paid in the form of interest. The greater the desire for the liquidity, the higher shall be the rate
of interest demanded for parting with liquidity.
Like the price of an ordinary commodity, the rate of interest is determined by the supply and
demand of money. According to Keynes, the rate of interest governed by the liquidity preference
of the commodity. The liquidity preference arises due to necessity of keeping adequate cash for
meeting curtaining requirements. Keynes discussed these requirements under the namely:
a) The transaction motives
b) The precautionary motives
c) The speculative motives
The demand for money arising under these motives constitutes the aggregate demand for money.
It should however be remembered that the demand for money in the Keynesian sense is the
demand to hold money.
Transactions motives.
The transactions motive for demanding money arises from the fact that most transactions involve
an exchange of money. Because it is necessary to have money available for transactions, money
will be demanded. The total number of transactions made in an economy tends to increase over
time as income arises. Hence, as income or GDP rises, the transactions demand for money also
rises.
Precautionary motives.
People often demand money as precaution against an uncertain future. Unexpected expenses,
such as medical or car repair bills, often require immediate payment. The need to have money
available in such situations is referred to as the precautionary motive for demanding money.
Speculative motives.
Money, like other stores of value is an asset. The demand for an asset
depends on both its rate of return and its opportunity cost. Typically, money holdings provide no
rate of return and often depreciate in value due to inflation. The opportunity cost of holding
money is the interest rate that can be earned by lending or investing one’s money holdings. The
speculative motive for demanding money arises in situations where holding money is perceived
to be less risky than the alternative of lending the money or investing it in some other asset. For
example, if a stock market crashed seemed imminent, the speculative motive for demanding
money would come into play; those expecting the marketing to crash would sell their stocks and
hold the proceeds as money. The presence of a speculative motive for demanding money is
affected by expectations of future interest rates and inflation. If interest rates are expected to rise,
the opportunity cost of holding money will become greater, which in turn diminishes the
speculative motive for demanding money. Similarly, expectations of higher inflation presage a
greater depreciation in the purchasing power of money and therefore lessen the speculative
motive for demanding money.
Loan Pricing Theory
Banks cannot always set high interest rates, e.g. trying to earn maximum interest income. Banks
should consider the problems of adverse selection and moral hazard since it is very difficult to
forecast the borrower type at the start of the banking relationship (Stiglitz & Weiss, 1981). If
banks set interest rates too high, they may induce adverse selection problems because high-risk
borrowers are willing to accept these high rates. Once these borrowers receive the loans, they
may develop moral hazard behaviour or so called borrower moral hazard since they are likely to
take on highly risky projects or investments (Chodechai, 2004). From the reasoning of Stiglitz
and Weiss, it is usual that in some cases we may not find that the interest rate set by banks is
commensurate with the risk of the borrowers.
Firm Characteristics Theories
These theories predict that the number of borrowing relationships will be decreasing for small,
high-quality, informationally opaque and constraint firms, all other things been equal (Godlewski
& Ziane, 2008).
Credit Market Theory
A model of the neoclassical credit market postulates that the terms of credits clear the market. If
collateral and other restrictions (covenants) remain constant, the interest rate is the only price
mechanism. With an increasing demand for credit and a given customer supply, the interest rate
rises, and vice versa. It is thus believed that the higher the failure risk of the borrower, the higher
the interest premium (Ewert et al., 2000).
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Retrieved from www.ea-journals.org
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN
This is regarded as the plan structure and strategy of investigation conceived so as to obtain
answers to research problems. It ensures that the required data are collected and that they are
accurate. The research for this study is Ex-post facto research design being that the study is
based on historical gotten from a secondary source without attempting to manipulate them. The
research work covers periods between 1990 to 2014.
3.2 POPULATION OF THE STUDY
The population of the study cut across 21 commercial banks in Nigeria and over 200
manufacturing industries in Nigeria.
3.3 TYPES AND SOURCES OF DATA
The type of data used is a time series data which means the data is time dimensional. The data to
be used will be sourced from secondary source, this is known as secondary data and will be
obtained from central bank of Nigeria statistical bulletin over the period 1990 to 2014.The data
required for this study is manufacturing sector output, Lending rate to manufacturing industry,
inflation rate and Government expenditure.
3.4 SAMPLING TECHNIQUE AND SAMPLE SIZE
Sampling technique for this study is Convenience sampling technique and Judgmental sampling
technique. Convenience sampling because the data collection from the population is
conveniently available in the C.B.N. statistical bulletin. Judgmental sampling because the
members of the population and conclusion relies on my reasoning and my personal judgment.
The sample size is twenty four years ranging from 1990-2014.
3.5 MODEL SPECIFICATION
The model that will be used in the study is as follows:
MSO= (LR, INF, GOVEX, µ)…………………………………………………….. (1)
This will be exemplified in more complex form equation below.
MSO= β0 + β1LR t + β2INF t + β3GOVEX t + µt ………………………………… (2)
MSO= Manufacturing sector output
LR= Lending rate
INF= Inflation rate
GOVEX= Government expenditure
µ = Error Term
In the above equation, β0 represent the constant term, β1, β2, β3 are slopes of the regression lines,
the subscript (t ) shows that the data used is a time series data.
3.6 A-PRIORI EXPECTATION
1. It is expected that lending rate will have a positive effect on manufacturing sector output in
Nigeria
2. It is expected that inflation rate will have a positive effect on manufacturing sector output in
Nigeria
3. It is expected that government expenditure will have a positive effect on manufacturing sector
output in Nigeria
3.7 DATA ANALYSIS TECHNIQUE
Multiple regression of Ordinary least square technique (O.L.S) will be adopted. E-views (7)
software statistical package will be used for the computation of the analysis in the study. The
choice of OLS is based on its Best Linear Unbiased Estimators (B.L.U.E.) compared to other
estimators.
CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS
4.1 Descriptive Statistics
The objective of this section is to analyze and interpret all the variables used for the study, stated
as follows: Manufacturing Sector Output (MSO), Government Expenditure (GOVEX), Inflation
Rate (IFR) and Lending Rate (LR) using the descriptive statistics.
MSO GOVEX IFR LR
Mean 452.7744 545.2948 19.37600 19.14600
Median 465.8100 351.2500 12.00000 18.29000
Maximum 943.1200 2681.080 76.80000 29.80000
Minimum 40.82000 24.05000 0.200000 13.54000
Std. Dev. 224.5697 570.0583 19.12763 3.478396
Skewness 0.151640 2.179880 1.819018 1.345440
Kurtosis 2.658676 8.842637 5.211572 5.073826
Jarque-Bera 0.217167 55.35825 18.88162 12.02249
Probability 0.897104 0.000000 0.000079 0.002451
Sum 11319.36 13632.37 484.4000 478.6500
Sum Sq. Dev. 1210358. 7799195. 8780.786 290.3818
Observations 25 25 25 25
Source: Researcher’s own computation, E-views 7
From the results obtained it is shown that all the mean values of all variables used were positive.
The mean and the standard deviation value of Manufacturing Sector Output for the study period
(1990-2014) are N452.7744 and N224.5697 respectively. The maximum and minimum values
are N943.12 and N40.82 respectively. While 0.217167 and 0.897104 represent the Jarque-Bera
statistic value (the absence of outliers in the data) and p-values respectively.
Government expenditure (GOVEX) has a mean and standard deviation values of N545.2948 and
N570.0583 respectively. A maximum value of N2681.080, minimum value of N24.05 with a
Jarque-Bera value of 55.35825 which shows the normality of the data.
The mean value of Inflation Rate for the period under review stood at 19.37600 while the
standard deviation is at 19.12763 from the analysis obtained above. The maximum and minimum
are 76.8 and 0.2 respectively. The p-value and Jarque-Bera (shows the normality of the data) are
0.000079 and 18.88162 respectively.
The mean value for lending rate (LR) for the period under review stood at 19.14600 with a
standard deviation value of 3.478396. The highest and smallest value from the analyze are 29.8
and 13.54 respectively. Like in the others, the Jarque-Bera statistic value of 12.02249 and p-
value of 0.002451 also indicates that the data is normal and there are outliers in the data.
In terms of skewness, all the variables were shown to be positively skewed.
4.2 UNIT ROOT TEST RESULT AND INTERPRETATION
The properties of the time series data for the period of the study covering 1990-2014 was
investigated in order to test its stationarity using the Augmented Dickey-Fuller (ADF) test
statistics. To avoid getting a spurious regression, it is important to test the stationary of the
individual variables using Unit Root Test. Regression of a non-stationary time series on another
non-stationary time series may produce a spurious regression (Gujarati, 1995). The hypothesis
tested was;
Variable ADF Critical Value
(5%)
P-Value Order of
Integration
At Conclusion
MSO -4.930311 -3.622033 0.0034 I(1) 1st Diff Stationary
GE -4.869208 -3.622033 0.0038 I(1) 1st Diff Stationary
IFR -4.007381 -3.644963 0.0250 I(0) Level Stationary
LR -3.946328
-3.673616 0.0303 I(0) Level Stationary
H0: It is non-stationary i.e. it has a unit root
H1: It is stationary i.e. it has no unit root
Decision rule: Taking the absolute value of both the ADF test statistic and the critical value,
reject the null hypothesis of non-stationarity if the ADF test statistic is greater than the critical
value and if the probability value (p-value) is less than 5%.
The unit root results which indicate the order of integration of each of the variables is presented
in table 4.2.
TABLE 4.2 RESULTS OF UNIT ROOT TESTS
Source: Researcher’s own computation, E-views 7
The results suggested that the Null hypothesis (H0) of unit root i.e. Non-stationary is rejected at
level for IFR & LR which means it is integrated of order 0 i.e. I(0) while it is rejected at first(1st)
difference for MSO & GOVEX which means integrated of order 1 i.e. I(1). This implies that all
the series are stationary (at 5% level of Critical Value) and their null hypothesis of non-
stationarity is rejected and therefore their regression will not be spurious.
4.3 INTERPRETATION OF RESULTS
Table 4.3.1 Ordinary Least square Regression Result
Dependent Variable: D(LNMSO)Method: Least SquaresDate: 05/29/16 Time: 19:06Sample (adjusted): 1991 2014Included observations: 24 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
C 0.092260 0.033376 2.764277 0.0123D(LNGE) 0.228783 0.088618 2.581674 0.0183
D(IFR) 0.005626 0.002263 2.486142 0.0224D(LR) -0.001682 0.006687 -0.251472 0.8041U(-1) -0.633029 0.139859 -4.526212 0.0002
R-squared 0.628633 Mean dependent var 0.130834Adjusted R-squared 0.550451 S.D. dependent var 0.206054S.E. of regression 0.138156 Akaike info criterion -0.937815Sum squared resid 0.362654 Schwarz criterion -0.692387Log likelihood 16.25378 Hannan-Quinn criter. -0.872703F-statistic 8.040595 Durbin-Watson stat 0.688324Prob(F-statistic) 0.000571
Source: Researcher’s own computation, E-views 7
Table 4.3.1 shows the result of the ordinary least square regression. From the table, the
coefficient of determination (R2) which measures how the variation in the dependent variable is
being accounted for by the variation in the independent variables. From the result, the R2 is
0.628633. This implies that approximately 63% variation in MSO is being explained by variation
in GE, IFR and PLR. While the adjusted R2 gives a value of 0.550451 i.e. approximately 55%.
The Prob(F-statistic) is used to test the joint impact of the independent variables on the
dependent variable. It measures the simultaneous significance of all the estimated parameters. It
tests the hypothesis that;
H0: β1 =0, β2 =0, β3 =0 (there is no joint impact)
H1: β1 ≠0, β2 ≠0, β3 ≠0 (there is joint impact)
Decision rule: if the Prob(F-statistic) value is less than the significance level of 0.05, reject the
null hypothesis that all parameters equal to zero.
Conclusion: The Prob(F-statistic) from the result is 0.000571, so the null hypothesis that all
parameters equal to zero is rejected. This means that all the variables used has joint impact.
The value of the intercept which is 0.092260 shows that MSO will experience 0.092260 increase
when all other variables are held constant.
A negative relationship is observed to exist between lending rate (LR) and manufacturing sector
output (MSO) shown by its coefficient of -0.001682. This means that a percent increase in
lending rate will reduce manufacturing sector output by 0.001682%. The relationship is also
observed to be statistically insignificant as the p-value of 0.8041 is greater than 0.05 which is the
level of significance. The relationship between inflation rate (IFR) and manufacturing sector
output (MSO) is observed to be positive given its coefficient of 0.005626. This means that an
increase in inflation rate will lead to a 0.005626% increase in MSO. The relationship is also
observed to be statistically significant given its p-value of 0.0224 which is less than the 0.05
level of significance. Government Expenditure (GOVEX) was found to have a direct relationship
with manufacturing sector output. Its coefficient of 0.228783 implies that a unit increase in
government expenditure will lead to a 22.8783% increase in MSO. The relationship is also found
to be statistically significant as its p-value of 0.0183 is less than 0.05 which is the level of
significance.
Table 4.3.2 Summary of A Priori Expectation
Independent
Variables
Expected
Signs
Observed
Signs
Remarks
Government
Expenditure
_ + Conform
Inflation rate _ + Does not
conform
Lending rate + - Does not
Conform
Source: Researcher’s own computation, E-views 7
4.3.2 MULTICOLLINEARITY TEST
Table 4.3.3 Variance Inflation Factors
Variance Inflation Factors
Date: 05/29/16 Time: 19:07Sample: 1990 2014Included observations: 24
Coefficient Uncentered CenteredVariable Variance VIF VIF
C 0.001114 1.400676 NAD(LNGE) 0.007853 1.520388 1.139460
D(IFR) 5.12E-06 1.150707 1.150491D(PLR) 4.47E-05 1.018701 1.010882U(-1) 0.019560 1.043154 1.039206
Source: Researcher’s own computation, E-views 7
Table 4.3.3 shows the Variance Inflation Factors (VIF) for the variables which measures the
level of collinearity between the regressors in an equation. The VIF test shows how much of the
variance of a coefficient estimate of a regressor has been inflated due to collinearity with other
regressors. Basically, VIFs above 10 indicate the presence of collinearity. Therefore, VIFs below
10 are desirable. Thus, with VIF values all less than 10 for GOVEX, IFR and LR respectively,
we conclude that there is no multicollinearity among the independent variables.
4.3.3 TEST OF HYPOTHESES
Hypothesis I
H0: Lending rate has no significant impact on manufacturing sector output.
H1: Lending rate has significant impact on manufacturing sector output.
Decision rule: reject the null hypothesis (H0) at 5% level of significance when the p-value is less
than 5% and accept the alternative hypothesis (H1). Do not reject the null hypothesis when p-
value is greater than 5%.
Conclusion: The null hypothesis was not rejected based on the fact that the p-value of 0.8041 is
greater than 0.05 with a negative coefficient of -0.001682. Therefore, the null hypothesis which
states that lending rate has no impact on manufacturing sector output in Nigeria is thereby
accepted.
Hypothesis II
H0: There is no significant relationship between inflation rate and manufacturing sector output in
Nigeria.
H1: There is a significant relationship between inflation rate and manufacturing sector output in
Nigeria.
Decision rule: reject the null hypothesis (H0) at 5% level of significance when the p-value is less
than 5% and accept the alternative hypothesis (H1). Do not reject the null hypothesis when p-
value is greater than 5%.
Conclusion: The null hypothesis was rejected based on the fact that the p-value of 0.0224 is less
than 0.05, with a coefficient 0.005626. This implies that a change in inflation rate has a positive
relationship with manufacturing sector output in Nigeria. Therefore, the alternative hypothesis
which states a significant relationship exist between inflation rate and manufacturing sector
output in Nigeria is thereby accepted.
Hypothesis III
H0: There is no significant relationship between government expenditure and manufacturing
sector output in Nigeria.
H1: There is a significant relationship between government expenditure and manufacturing sector
output in Nigeria.
Decision rule: reject the null hypothesis (H0) at 5% level of significance when the p-value is less
than 5% and accept the alternative hypothesis (H1). Do not reject the null hypothesis when p-
value is greater than 5%.
Conclusion: The null hypothesis was rejected based on the fact that the p-value of 0.0183 is less
than 0.05, with a coefficient of 22.8783%. This implies that a change in government expenditure
has a positive impact on manufacturing sector output in Nigeria. Therefore, the alternative
hypothesis which states that Government expenditure has impact on manufacturing sector output
in Nigeria is thereby accepted.
REFERENCE
Gujarati, D.N. 1995. Basic Econometrics. New York, USA, McGraw-Hill Book Company.
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSON AND RECOMMEENDATIONS
5.1 SUMMARY OF FINDINGS
1. Negative relationship is observed to exist between Lending rate (LR) and Manufacturing
sector output (MSO) given its negative slope coefficient of -0.001682. It indicates that
1% increase in lending rate will result into 0.1982% reduction in manufacturing sector
output. The relationship is also observed to be statistically insignificant as the p-value
which is 0.8041 is greater than 0.05 which is the level of significance.
2. The relationship between Inflation rate (IFR) and Manufacturing sector output (MSO) is
observed to be positive and also statistically significant given its slope coefficient of
0.005626 and p-value of 0.0224 which is lesser than 0.05 i.e. 5% level of significance.
This means that 1% increase in inflation rate (IFR) will lead to a rise in manufacturing
sector output by 0.005626%.
3. The relationship between Government expenditure (GOVEX) and Manufacturing sector
output (MSO) is observed to be positive. Its slope coefficient of 0.228783 implies that a
unit increase in government expenditure will lead to a 22.8783% increase in MSO. The
relationship is also found to be statistically significant as its p-value of 0.0183 is less than
0.05 which is the level of significance.
5.2 CONCLUSION BASED ON FIDINGS
The study reveals that government expenditure and inflation rate significantly affect
manufacturing sector output in Nigeria. However lending rate which according to Apriori
expectation should affect manufacturing sector output in Nigeria does not have significant
relationship with one another. This result may be accepted because the manufacturing industry in
Nigeria has not enjoyed enough credit facilities from the lending institutions in Nigeria which
has affected their ability to maximize within their production possibility frontier. This again has
resulted to downward slope of their production possibility curve.
The lending institutions should therefore make their lending rates reasonable so as to allow
manufacturing industry lend more thereby increasing manufacturing sector output. The
government should also increase their expenditure on social amenities so as to create enabling
environment for the manufacturing industryto operate effeciently.
5.3 RECOMMENDATIONS
1. The government should endeavor to ensure that there are available and sufficient credit
facilities allocated to the manufacturing sector in Nigeria with reasonable or affordable lending
rates by the lending institutions. This will enable the manufacturing sector in Nigeria to
maximize production and operate on their production possibility curves, which is full capacity.
In the long run it will lead to development of the Nigerian economy, through employment
generation, innovation, competition, economic dynamism and promotion of indigenous
technology.
2. For Nigeria to meet her millennium developmental goals and objectives, the nation should
depend mostly on products and services produced within her boundaries, hence the need to
encourage the manufacturing sector. It will afford her the privileges of enjoying favourable
balance of payments, as well as favourable terms of trade, which are the fundamentals for
economic growth and development in the 21st century.
5.4 SUGGESTIONS FOR FURTHER STUDIES
For better and broader knowledge on the study interested researchers should
1. Look into the behavioralal attitudes of commercial banks towards lending to
manufacturing industry.
2. Examine the strength of Government expenditure on the performance of Manufacturing
industry in Nigeria.
3. Not restrict their knowledge to Nigeria alone, their knowledge should be extended to the
whole West Africa states.
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APPENDIX
Year Prime Lending rate
Manufacturing sector output
Inflation rate Government expenditure
1990 25.50 40.82 3.6 24.05
1991 20.01 98.65 23.0 28.34
1992 29.80 144.37 48.8 39.76
1993 18.32 165.89 61.2 54.50
1994 21.00 219.85 76.8 70.92
1995 20.18 295.80 51.6 121.14
1996 19.74 350.60 14.3 212.93
1997 13.54 382.62 10.2 269.65
1998 18.29 395.77 11.9 309.02
1999 21.31 426.21 0.2 498.03
2000 17.98 468.03 14.5 239.45
2001 18.29 535.80 16.5 438.70
2002 24.85 507.84 12.2 321.38
2003 20.71 465.81 23.8 241.69
2004 19.18 349.32 10.0 351.25
2005 17.95 408.37 11.6 519.47
2006 17.26 478.52 8.5 552.39
2007 16.94 520.88 6.6 759.28
2008 15.14 585.57 15.1 960.89
2009 18.99 612.31 13.9 1152.80
2010 17.59 643.07 11.8 883.87
2011 16.02 694.81 10.3 918.55
2012 16.79 761.47 12.0 874.84
2013 16.72 823.86 8.0 1108.39
2014 16.55 943.12 8.0 2681.08
Source: CBN Statistical Bulletin 2014
GDP CPS M2 MCAP TLS TVS Mean 17646.12 3300.591 3654.097 3855.149 749285.0 355040.8 Median 5696.393 480.7708 753.7047 386.1500 190016.0 21112.55 Maximum 89043.62 17128.98 17680.52 19077.42 3535631. 2350876. Minimum 134.5856 13.07034 22.29924 6.600000 20525.00 225.4000 Std. Dev. 26096.98 5270.729 5315.497 5822.270 994532.3 588414.2 Skewness 1.662918 1.546089 1.395164 1.358914 1.464166 1.906407
Kurtosis 4.376818 3.946041 3.540639 3.474663 4.259655 6.098016
Jarque-Bera 16.19602 13.07070 10.09777 9.514861 12.70232 30.16907 Probability 0.000304 0.001451 0.006416 0.008588 0.001745 0.000000
Sum 529383.7 99017.74 109622.9 115654.5 22478550 10651223 Sum Sq. Dev. 1.98E+10 8.06E+08 8.19E+08 9.83E+08 2.87E+13 1.00E+13
Observations 30 30 30 30 30 30
Null Hypothesis: LNCPS has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.003719 0.1489Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: D(LNCPS) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.232064 0.0123Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: LNMCAP has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -1.681563 0.7336Test critical values: 1% level -4.309824
5% level -3.57424410% level -3.221728
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: D(LNMCAP) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.210761 0.0129Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: LNGDP has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -1.879932 0.6389Test critical values: 1% level -4.309824
5% level -3.57424410% level -3.221728
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: D(LNGDP) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.649370 0.0004Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: LNM2 has a unit rootExogenous: Constant, Linear Trend
Lag Length: 2 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -2.085062 0.5306Test critical values: 1% level -4.339330
5% level -3.58752710% level -3.229230
Null Hypothesis: D(LNM2) has a unit rootExogenous: Constant, Linear TrendLag Length: 3 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.567109 0.0537Test critical values: 1% level -4.374307
5% level -3.60320210% level -3.238054
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: LNTLS has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -1.648891 0.7478Test critical values: 1% level -4.309824
5% level -3.57424410% level -3.221728
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: D(LNTLS) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.177163 0.0014Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: LNTVS has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -1.855817 0.6511Test critical values: 1% level -4.309824
5% level -3.57424410% level -3.221728
*MacKinnon (1996) one-sided p-values.
Null Hypothesis: D(LNTVS) has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.563036 0.0058Test critical values: 1% level -4.323979
5% level -3.58062310% level -3.225334
*MacKinnon (1996) one-sided p-values.
Dependent Variable: LNGDPMethod: Least SquaresDate: 03/22/16 Time: 12:59Sample: 1985 2014Included observations: 30
Variable Coefficient Std. Error t-Statistic Prob.
C 5.706361 0.656403 8.693383 0.0000LNM2 1.167785 0.311385 3.750298 0.0010
LNCPS -0.347291 0.242475 -1.432277 0.1650LNMCAP 0.359020 0.129605 2.770116 0.0106LNTLS -0.385350 0.091009 -4.234199 0.0003LNTVS -0.026938 0.070878 -0.380059 0.7072
R-squared 0.993331 Mean dependent var 8.399100Adjusted R-squared 0.991941 S.D. dependent var 2.001333S.E. of regression 0.179659 Akaike info criterion -0.418653Sum squared resid 0.774659 Schwarz criterion -0.138413Log likelihood 12.27979 Hannan-Quinn criter. -0.329001F-statistic 714.9265 Durbin-Watson stat 1.597051Prob(F-statistic) 0.000000
Dependent Variable: D(LNGDP)Method: Least SquaresDate: 03/22/16 Time: 13:03
Sample (adjusted): 1986 2014Included observations: 29 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
C 0.120742 0.061007 1.979158 0.0604D(LNM2) 0.700844 0.299664 2.338768 0.0288
D(LNCPS) -0.464981 0.200118 -2.323534 0.0298D(LNMCAP) 0.328017 0.097142 3.376682 0.0027D(LNTLS) -0.123189 0.078166 -1.575997 0.1293D(LNTVS) -0.046821 0.064249 -0.728746 0.4738
Z(-1) -0.731833 0.159820 -4.579101 0.0001
R-squared 0.638878 Mean dependent var 0.223955Adjusted R-squared 0.540390 S.D. dependent var 0.193243S.E. of regression 0.131008 Akaike info criterion -1.020612Sum squared resid 0.377588 Schwarz criterion -0.690576Log likelihood 21.79888 Hannan-Quinn criter. -0.917249F-statistic 6.486867 Durbin-Watson stat 2.193954Prob(F-statistic) 0.000476
Variance Inflation FactorsDate: 03/22/16 Time: 13:06Sample: 1985 2014Included observations: 29
Coefficient Uncentered CenteredVariable Variance VIF VIF
C 0.003722 6.288641 NAD(LNM2) 0.089798 9.769306 1.729150
D(LNCPS) 0.040047 5.882795 1.736988D(LNMCAP) 0.009437 2.553778 1.386504D(LNTLS) 0.006110 1.860757 1.670253D(LNTVS) 0.004128 2.580456 2.002675
Z(-1) 0.025542 1.147136 1.146938
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 0.771262 Prob. F(2,20) 0.4757Obs*R-squared 2.076506 Prob. Chi-Square(2) 0.3541
Heteroskedasticity Test: Breusch-Pagan-Godfrey
F-statistic 1.664276 Prob. F(6,22) 0.1771Obs*R-squared 9.053558 Prob. Chi-Square(6) 0.1706Scaled explained SS 5.118954 Prob. Chi-Square(6) 0.5286
Date: 03/22/16 Time: 13:09Sample (adjusted): 1987 2014Included observations: 28 after adjustmentsTrend assumption: Linear deterministic trendSeries: LNGDP LNM2 LNCPS LNMCAP LNTLS LNTVS Lags interval (in first differences): 1 to 1
Unrestricted Cointegration Rank Test (Trace)
Hypothesized Trace 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.832920 110.0567 95.75366 0.0036At most 1 0.607130 59.95678 69.81889 0.2367At most 2 0.391908 33.79705 47.85613 0.5130At most 3 0.302894 19.86902 29.79707 0.4317At most 4 0.211841 9.766123 15.49471 0.2992At most 5 0.104824 3.100573 3.841466 0.0783
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values