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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Retrieved from www.ea-journals.org

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