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THE IMPACT OF INTEREST RATE LIBERALIZATION ON INVESTMENT IN NIGERIA BY HITLAR, INEDU (PG/M.Sc/12/62808) [email protected] Phone: 07081022293, 08032122813 DEPARTMENT OF ECONOMICS UNIVERSITY OF NIGERIA, NSUKKA SUPERVISOR: REV. FR. (PROF) H.E ICHOKU AUGUST, 2015.

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THE IMPACT OF INTEREST RATE LIBERALIZATION ON

INVESTMENT IN NIGERIA

BY

HITLAR, INEDU

(PG/M.Sc/12/62808)

[email protected]

Phone: 07081022293, 08032122813

DEPARTMENT OF ECONOMICS

UNIVERSITY OF NIGERIA, NSUKKA

SUPERVISOR: REV. FR. (PROF) H.E ICHOKU

AUGUST, 2015.

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THE IMPACT OF INTEREST RATE LIBERALIZATION ON

INVESTMENT IN NIGERIA

BY

HITLAR, INEDU

(PG/M.Sc/12/62808)

[email protected]

Phone: 07081022293, 08032122813

An M.Sc dissertation submitted to the Department of Economics

Faculty of the Social Sciences, University of Nigeria, Nsukka

In Partial Fulfilment of the Requirements

For the Award of Master of Science

(M.Sc) Degree in Economics

SUPERVISOR

REV. FR. (PROF) H.E ICHOKU

AUGUST, 2015

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CERTIFICATION

This is to certify that Hitlar,Inedu an M.Sc student of the University of Nigeria, Nsukka

with registration number PG/M.Sc/2012/62808 has successfully completed the research required

for the Award of Master of Science Degree in Economics in the afore mentioned institution.

The work covered in this project is original and has not been submitted in part or full for

any other degree of this University or any other University.

…………………………………….. Date…………………………..

Rev. Fr. (Prof) H.E Ichoku

Supervisor

…………………………………….............. Date…………………………..

Professor S. I.Madueme

Head of Department

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APPROVAL

This research work titled: “The Impact of Interest Rate Liberalization on Investment in Nigeria”

has followed due process and has been approved to have met the requirement for the award of

the Master of Science degree in Economics, University of Nigeria, Nsukka.

Approved

………………………………… Date…………………………..

Rev. Fr. (Prof) H.E Ichoku

Supervisor

………………………………… Date…………………………..

Professor S. I. Madueme

Head of Department

………………………………….. Date…………………………..

Dean Faculty of Social Sciences

Professor I. A. MADU

……………………………….

External Examiner

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DEDICATION

To GODAlmighty, My wife Joy,Ojoneand wonderful Kids Jessica,Chubiyojo and

Jose-Franklyn,Eyiojo.

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ACKNOWLEDGEMENT

I am greatly indebted to my supervisor, Rev. fr. (Prof) H.E. Ichoku whose rigorous

scrutiny and material contributions enhanced the quality of this work. I commend his useful and

objective advice and criticisms towards the successful completion of this thesis. I pay homage to

him for his useful comment.

I am so grateful to all the lecturers in the department most especially; Dr. Eze B, Dr.

NwosuE, Dr. Edeme R, Dr. Innocent (SPG), Mr. Johnson N, and all the lecturers that taught me

during the course work sessionand contribute to the knowledge which I acquire today, for their

friendly relationship is what made the university environment a place worth living for me

Thanks to my parents Elder and Deaconess Hitlar, J.E for their moralencouragement of

which without them I wouldn‟t have being where I am today. Also to my beloved siblings, Dr.

Chuba, M.A, Major (Elder) Agada J.A & family, Daniel Agada (USA), Cletus Sam (Canada),

Dr. Okpanachi, S. S, Dr. Ene I. O, and Mr. Simon Sule& family (Nsukka) for their support in the

course of this program.

Special thanks to Innocent Chile (Prof), Henry Asogwa, KarimoTari Moses, Emmanuel

Asuquo,Susan Fachano (Hajia) and my entire roommate for their assistance in one form or the

other to keep me going.

Finally, I thank the Almighty God who gives me the idea. When Pythagoras was praised

for being wise, he said “I am not wise, only God is wisdom; I am only a lover of wisdom”.

May God Bless You All.

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TABLE OF CONTENTS

Title page … … … … … … … … … …… … i

Cover page … … … … … … … … … …… … ii

Certification page … … … … … … … …… … … iii

Approval page … … … … … … … …… … … iv

Dedication … … … … … … … … … … v

Acknowledgement … … … … … … … … …vi

Abstract … … … … … … … … …… vii

CHAPTER ONE

INTRODUCTION

1.1 Background to the study… … … … … … … … 1

1.2 Statement of the problem… … … … … … … … 3

1.3 Research Questions… … … … … … … … … 5

1.4 Research Objectives… … … … … … … 5

1.5 Research Hypotheses… … … … … … … … 5

1.6 Policy Relevance of the study... … … … … … … 6

1.7 Scope of the study… … … … … … … … … 6

CHAPTER TWO

POLICY CONTEXT OF INTEREST RATE LIBERALIZATION IN NIGERIA

2.1 Management of Interest Rate prior to 1986 … … … … … … 7

2.2Management of Interest Rate since 1987 … … … … … … 8

CHAPTER THREE

REVIEW OF RELATED LITERATURE

3.1 Conceptual framework … … … … … … … … 11

3.2Theoretical framework … … … … … … … … 12

3.2.1 Theories of Interest Rate… … … … … … … … 12

3.2.2 Theories of Investment … … … … … … … … 14

3.3 Empirical Literature… … … … … … … … … 17

3.4 Limitation of previous studies … … … … … … … 23

CHAPTER FOUR

METHODOLOGY

4.1 Theoretical framework … … … … … … … … 25

4.2 Model specification … … … … … … … … 27

4.3 Method of estimation … … … … … … … … 29

4.4 Justification of the model … … … … … … … … 30

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4.5 source of data … … … … … … … … … 31

CHAPTER FIVE

PRESENTATION AND ANALYSIS OF RESULTS.

5.1 Descriptive analysis of variable … … … … … … … 32

5.2 Pre-Diagnostic tests … … … … … … … … 33

5.2.1 Unit root test result … … … … … … … … 33

5.2.2 Co-integration test … … … … … … … … 34

5.3 Presentations of regression result and interpretation … … … … 35

5.3.1 Error correction model … … … … … … … … 35

5.3.2 Innovation accounting … … … … … … … … 37

5.4 Evaluation of research Hypothesis … … … … … … 38

5.4.1 Test of working Hypothesis i … … … … … … … 38

5.4.2 Test of working Hypothesis ii … … … … … … … 39

5.4.3 Test of working Hypothesis iii … … … … … … … 39

5.5 Chapter summary and prospects … … … … … … … 40

CHAPTER SIX

SUMMARY, POLICY RECOMMENDATIONS AND CONCLUSION

6.1 Summary of research finding … … … … … … … 41

6.2 Policy recommendation … … … … … … … … 42

6.3 Conclusion … … … … … … … … … 43

6.4 Recommendation for further studies … … … … … … 44

Appendix A … … … … … … … … … … 46

Appendix B … … … … … … … … … … 47

Appendix C … … … … … … … … … … 55

Reference … … … … … … … … … … 60

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ABSTRACT

The importance of investment in economic growth cannot be overemphasized. This has led to an

upsurge in the study of its determinants. This research therefore, seeks to investigate the impact

of interest rate liberalization on investment in Nigeria from 1970-2012. Using the Error

Correction Model (ECM), the result indicates that a long run relationship exists among the

variables. The result further reveals that all the variables have significant impact on investment.

The study equally shows that there is no differential impact of interest rate liberalization on

investment in Nigeria during the pre and post-liberalization regimes. Also, the impulse responses

of these variables to shocks in theextraneous variables were verified; using the Multiple-

Equation VAR models. In addition, the variance decomposition result shows thatPeriod 2 shows

a standard deviation value of 97.23 in investment resulting from own shock, 2.44 to a response

to a shock from interest rate, 0.0186 to a response from market capitalization rate,0.205900 to a

response to public expenditure and 0.101933 to response to trade openness. In period 10,

investment responds positively with a standard deviation of 18.77 originated from own shock

and standard deviation values of 8.05, 7.94, 12.43 and 15.59 arising from a shock from interest

rate, market capitalization rate, public expenditure and trade openness respectively. It is

recommended that polices to make interest rate attractive to investors as well as improve trade

should be encouraged. Also broadening the capital market and improving infrastructure through

increased capital expenditure should be pursued. In addition to these, there should be

consistency in policies so that policy summersaults does not affect investment.

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CHAPTER ONE

INTRODUCTION

1.1 Background of the Study

The Nigerian economy has at different times witnessed enormous interest rate swings in different

sectors of the economy since the 1970s and mid 1980s under a regulated regime. The preferential

interest rates were based on the premise that the market, if freely applied would exclude some

priority sectors. Thus, interest rates were adjusted through the market forces in order to promote

increased level of investment in the various preferred sectors of the economy. Prominent among the

preferred sectors were the agricultural, manufacturing and solid mineral sectors which were

accorded priority and deposit money banks were directed to charge preferential interest rates on all

loans to encourage the upsurge of small-scale industrialization which is a catalyst for economic

development (Udoka, 2000). According to Mckinnon (1973) and Shaw (1973), this situation can

ignite financial repression which occurs mostly when a country imposes ceiling on deposit and

lending nominal interest rate at a low level relative to inflation. The resulting low or negative

interest rates discourage savings mobilization and the channelling of mobilized savings through the

financial system. This has a negative effect on the quantity and quality of investment and hence

economic growth.

Closely followed by the regulated interest rate regime was the interest rate reform, a policy evolved

under the financial sector liberalization. The policy was put in place to achieve efficiency in the

financial sector, thus, engendering financial deepening. In Nigeria, financial sector reforms started

with the deregulation of interest rate in August, 1987 (Ikhide & Alawade, 2001). Since then, the

Nigerian government has been pursuing a market determined interest rate which does not permit a

direct state intervention in the general direction of the economy (Nyong, 2007).

Since the introduction of the interest rate liberalization concept in the 1980s, many countries such as

Angola, Burundi, Congo, Ivory Coast, Ghana, Malawi, Nigeria, China, India etc. have made

attempts at liberalizing their financial sectors by deregulating interest rate, eliminating or reducing

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credit controls, allowing free entry into the banking sector, giving autonomy to commercial banks,

permitting private ownership of banks and liberalizing international capital flows financial

repression has retarded the development process as envisaged by Shaw (1973). Undoubtedly,

government past efforts to promote economic development by controlling interest rate and

securing inexpensive funding for their own activities have undermined financial development.

(Arturo, Fabio, & Andrew, 2003).

The liberalization of the interest rate system, mainly by raising interest rates, was a policy measure

adopted by the Nigerian Government to increase private saving. The objective was to make and

maintain positively in real terms as the upsurge in inflation in the 1970s had rendered them negative

and there were rigid exchange and interest rate controls resulting in low direct investment. Funds

were inadequate as there was a general lull in the economy. Monetary and credit aggregates moved

rather sluggishly. Consequently, there was a persistent pressure on the financial sector, which in

turn necessitated a liberalization of the financial system (Soyibo & Olayiwola, 2000).

In response to these developments, the government deregulated interest rate in 1987 as part of the

Structural Adjustment Program (SAP). The official position then was that interest rate liberalization

would, among other things, enhance the provision of sufficient funds for investors, especially

manufacturers (a priority sector), who are considered to be the prime agents of investment, and by

implication, promotes economic growth (Odhiambo, 2009). However, in a dramatic policy

reversal, the government in January, 1994 out-rightly introduces some measures of regulation into

interest rate management. It was claimed that there are more wide variations and unnecessarily high

interest rate under the complete deregulation of interest rate immediately, deposit rate were once

again set at 12% - 15% per annum while a ceiling of 21% per annum was fixed for lending (CBN

2012).

The high interest rate observed in Nigeria during the era of interest rates deregulation has been

frequently blamed for the country‟s slow growth and pointed out as a major failing of the

Adjustment Program initiated in August, 1986. The believe is premised on the assumption that the

demand for funds is for the purpose of investment and that investment demand will be larger at a

lower lending rate. This study regards that such blame is largely for obvious reasons. First interest

rate deregulation lead to an increase in saving mobilization in Nigeria (Chuba, 1997). While it is

impossible to achieve economic growth without adequate investment, saving generates investment.

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Secondly, investment does not depend upon interest rate alone, for instance investors may be

prepared to borrow more and invest more, even if interest rate are high provided they anticipate a

higher margin of profits. On the other hand, investors are not tempted to borrow even if interest rate

are very low, or even zero if they are afraid that they may lose even their capital. In other words,

investment depends upon risk and the prospects of profits in a particular industry-or what Keynes

(1936) calls the marginal efficiency of capital rather than upon interest rates. Thirdly, interest rate

is just one among many factors that have negative effects on investment. For example, the

deregulation of Nigerian economy went beyond interest rates reform policies rather than interest

rate deregulation to be the major obstacle to investment expansion in Nigeria.

The policy on interest rate introduced in 1994 was retained in 1995 with a minor modification to

allow for flexibility. The policy stayed in place until it was lifted in October 1996. The lifting

remained in force till date, thus enabling the pursuit of a flexible interest rate regime in which bank

deposit and lending rate were largely determined by the forces of demand and supply for funds

(Omole & Falokun, 1999).

1.2 Statement of the problems

Prior to the deregulation of interest rate in Nigeria, the prevailing rates of interest were regulated

by government through the Central Bank of Nigeria (CBN). This was meant to guide the economy

to follow the desired direction. However, it was soon realized that, the low rates of interest that

prevailed could not be sustained (for example the real lending rates were 3.60, -4.40,-13.20,-9.40,-

6.93,-2.63,-1.40 and -11.73 percent in 1973, 1974, 1977, 1978, 1979, 1980 and 1981 respectively

(Chuba, 2005). This very low and sometimes negative real interest rates discouraged savings. Also,

the low rates did not only increase the demand for loanable funds but also misdirected credit.

Consequently, the demand for credit soon exceeded the supply of funds while essential sectors of

the economy were starved of funds. It was against this background that the Nigerian interest rate

system was deregulated in the second half of the 1980. A major objective of the deregulation

exercise was to increase savings for investment and economic growth. But despite this effort,

investment is still in the doldrums because the deposit rate is low and that discouraged savings

which translate into higher interest rate and therefore low investment. The deregulation exercise has

been met with mixed feelings in Nigeria, while some believe it would enhance economic

performance, others have contrary opinion. Nwankwo (1989) opine that interest rate deregulation

will definitely lead to more efficient allocation of financial market resources. His position is in line

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with the arguments of Mckinnon (1973) and Shaw (1973). Abiodun (1988), on the other hand holds

that deregulation of interest rate is like a double-edged sword, which will either stimulate or mar the

economy. He asserts that the deregulation of interest rate will lead to an increase in interest rate,

which will increase savings. This high cost of borrowing might bring about cost-push inflation as

borrowers of funds will pass the high cost of borrowing to the customers by pushing up prices.

Ojo (1988) & Ani (1988) are both of the opinion that interest rate deregulation would mar the

Nigerian economy. In their separate studies, they flawed the deregulation exercise, claiming it

would discourage investment and hence economic growth, by pushing up interest rates. They

believe that since domestic financial markets are to some extent structurally oligopolistic, if interest

rate is left uncontrolled, it might lead to a sharp increase in lending rate which will translate to

increase in cost of capital and discourages investment. This position is supported by Soyibo &

Olayiwola (2000) and Akpan (2004) who all pointed out the low positive impact of deposit rate on

investment after interest rate liberalization in Nigeria.

Okogo & Osafo-Kwaako (2006), believe that, with the Structural Adjustment Programme in 1986,

market based reforms were to ensure that true cost of capital would be achieved in Nigeria.

However, the initial attempt at interest rate liberalization yielded poor results. A poorly supervised

and inefficient financial sector, weak institutions and poor governance created opportunities for

arbitrage, patronage and rent-seeking behaviour.

The high interest rate observed in Nigeria during the era of interest rate liberalization (17.5%,

26.8%, 20.18%, 24.85%, 17.59% and 16.79% in 1987, 1989, 1995, 2002, 2010 and 2012

respectively) have been frequently blamed for the country‟s slow growth and therefore a major

failure of Structural Adjustment Programme (SAP) initiated in August 1987. This belief is premised

on the assumption that, the demand for funds is for the purpose of investment and that investment

demand will be lower at higher lending rate ( for example, investment was at 19.835%, 19.879%,

15.145%, 30.472%, 25.842% and 22.139% in 1987, 1989, 1995, 2002, 2010 and 2012). (CBN

2012).

This change of interest rate policy is a problem because of two main reasons, first, investment

contraction in Nigeria may not have any connection with the increase in lending rate that

accompanied interest rate liberalization. Just as it was in 1987 when interest rate is 17.5% and

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investment was 19.835%, an increase in interest rate in 1989 (i.e. from 17.5% to 26.8%) was also

accompanied by increase in investment (i.e. from 19.835% to 19.879%). Secondly, low interest rate

policy, which the regulation of interest rate implies could discourage saving mobilization. However,

it is impossible to achieve economic growth without adequate investment, saving generates

investment. (Chuba,2005). These problems give raise to this study to find out the structural changes

that have taken place in the economy during the pre-liberalization and the post-liberalization

regime. Although many works have not compare the two periods to see how investment response to

the changes in interest rate over time in Nigeria.

There is therefore the need for a comparative analysis of the impact of interest rate liberalization in

promoting investment in Nigeria. This forms bedrock of the present study, in line with this

therefore, the study will address the following question. Equally, answers to these questions would

enable us to access the desirability or otherwise of the occasional resort to financial system

regulation and control as practiced between 197 -2012.

1.3 Research Question

i. To what extent has interest rate affected investment in Nigeria?

ii. What is the differential impact of interest rate liberalization on investment in Nigeria

during the pre and post-liberalization regimes?

iii. What is the difference in the structural response of investment to changes in interest rate

in Nigeria overtime?

1.4 Objectives of the Study

The major objective of this research is to analyze the impact of interest rate regulation and

deregulation on investment in Nigeria. The specific objectives are:-

i. To examine the impact of interest rate on investment in Nigeria.

ii. To determine the differential impact of interest rate liberalization on investment in

Nigeria during the pre and post-liberalization regimes

iii. To examine the structural responses of investment to changes in interest rate in Nigeria

overtime.

1.5 Research Hypotheses

Based on the objective of the study, the following null hypotheses are proposed.

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Ho1: Interest rate has no significant impact on investment in Nigeria.

Ho2: There is no differential impact of interest rate liberalization on investment in Nigeria

during the pre and post-liberalization regimes

Ho3: There are no structural responses of investment to changes in interest rate in Nigeria

overtime.

1.6 Policy Relevance of the Study

This study will be helpful in analyzing how the impact of interest rate liberalization on

investment in Nigeria has been before the regime of interest rate deregulation and after the

regime. It also investigates the interest rate deregulation and investment relationship by taking

into consideration the transmission mechanism through which interest rate affect investment.

The study is also relevant because it will make a comparative analysis between the impact of

deregulated interest rate on investment and that of regulated interest rates on investment. As a

result, the outcome of this study shed more light on the role of interest rate in economic

development in Nigeria. Consequently, this work will be useful to Government and monetary

policy makers in their quest to improve financial intermediation in the economy. Also, by

raising specific issues concerning the link between interest rate and economic performance

(investment) in Nigeria, this study provides a basis for further in-depth investigation in this area.

1.7 Scope of the Study

This study is a macro level analysis which will involve time series elements, thus the

econometric analysis of the impact of interest rate liberalization on investment is based on the

Nigeria economy for the period 1970-2012. These years are chosen owing to the availability of

time series data for the variable of interest indicator. The main variables of interest in this study

are investment which is proxy by Gross Domestic Investment (dependent variable); and interest

rate, market capitalization rate, public expenditure, and trade openness as explanatory variables.

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CHAPTER TWO

POLICY CONTEXT OF INTEREST RATE LIBERALIZATION IN NIGERIA

Interest rate in Nigeria over the years has played a pivotal/dominant role as one of the

instruments used by the Federal Government in managing Monetary Policy. The use of Interest

rate as an instrument of monetary policy was based on two main assumption on Interest rate

regulation; more so that, interest rate has since remained one of the instrument of managing

monetary policy of the Federal Government of Nigeria, Interest rate guidelines/regulations have

always been contained either in the Federal Government Annual Budget document or the

monetary/credit policy circular of the Central Bank of Nigeria (CBN) from time to time.

(Akingunola 2012) As the positive relationship between investment and economic development

is well established, it therefore becomes expedient for any economy that wishes to grow to pay

proper attention to changes in interest rate. Nigeria being a country in dire need of development

cannot overlook the important role interest rate could play in this direction. Interest rate

liberalization policy in Nigeria is discussed along the dividing period of pre-liberalization (1970-

1986) and post liberalization (1987-2012) periods.

2.1 Management of Interest Rate Prior to 1986

Prior to the Structural Adjustment Programme in 1986, the level and structure of interest rate

were administratively determined by the central bank of Nigeria. Both deposit and lending rates

were fixed by the Bank based on policy decision, at that time, the major reason for administering

interest rate were the desire to obtain the social optimum in resource allocation, promote orderly

growth of the financial market, combat inflation and lessen the burden of internal debt servicing

on the government. In implementing credit policy, the sector of the economy were classified into

three categories; preferred, less preferred, and other. The preferred category included

Agriculture, Manufacturing, and Residential housing; while the less preferred sectors consist of

important and general commerce. In the group of “others” were Credit and Financial institutions,

Government and “Personal and Professional” sectors. Such a classification enabled government

to direct financial resources at concessionary interest rate to sector considered as priority areas.

The concessionary rate were typically below the minimum rediscount rate (MRR) which was

itself quite low, averaging about 7.25% below 1978 and 1985. The prevailing rates were unable

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to keep pace with inflation, resulting in negative real interest rates. Moreover, the demand for

credit soon exceeded the rate of saving and a large proportion of government borrowing had to

be financed by the central bank.

Other implication of low interest rate policy was that even “preferred sector” could not get

access to funds partly because financial institutions were unable to raise sufficient loanable funds

through savings or from the money market at the favoured/concessionary rate of interest. A case

in point was the directive to the banks to lend to Agriculture at 7% in 1984 when the average

saving deposit rate was 9.80%. Over all, the low interest rate regime resulted in inefficient

production and excessive demand for credit. (CBN Briefs 1996). The pre-liberalization period

(1970-1986) is considered as a period of financial repression and was characterized by a highly

regulated monetary policy environment in which policies of directed credits; interest rate ceiling

and restrictive monetary expansion were the rule rather than the exception (Soyibo & Olayiwola,

2000). Although, the interest rate policy instruments remained fixed, there were marginal

increases for instance; the deposit rate was increased from 4.5% in 1975 to 10% in 1986, while

the lending rate rose from 6% to 10.25% within the same period. (CBN 2012)

2.2 Management of Interest Rates Since 1987

Within the general framework of liberalizing the economy in 1986 to enhance competition and

efficient allocation of resource, the Central Bank of Nigeria introduced a market-based interest

rate policy in August, 1987. The policy decision was not without controversy while it was

generally agreed that low interest rate did not encourage saving, it was feared that high interest

rate, which were likely to accompany liberalization of interest rate, might stifle investment. The

liberalization of interest rates allowed banks to determine their deposit and lending rate

according to market conditions through negotiations with their customers. However, the

Minimum Rediscount Rate (MRR) which influences other interest rate continue to be determined

by the central bank in line with changes in overall economic conditions. The MRR which was

15% in December 1987 was reduced to 12.5% in August 1987 with the objective of stimulating

investment in the economy. During the same period, the saving deposit of commercial banks on

the average was 11.5% and interest rate paid by merchant banks on 90-days fund was 15%. The

prime lending rates of commercial and merchant banks were, on the other average, 18.0% and

20.5% respectively. While their corresponding maximum lending rate were 19.2% and 22.0%.

Following the need to moderate monetary expansion in 1989, the MRR was raised to 13.25%. it

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was also observed that there were wide disparities in the interest rate structure of the various

banks. (CBN brief 2012). The lack of responsiveness of the structure of deposit and lending rates

to market fundamentals, particularly the decline in inflation in 1990 and the increase in domestic

liquidity, compelled the authorities in 1991 to fix a maximum spread of 4% points between the

cost of funds of commercial and merchant banks, and their maximum lending rates. The banks

were therefore, directed to a maximum lending rate of 21% and the minimum deposit rate of

13.5%. the banking community was highly critical of the new policy measure claiming that it

was against the deregulatory posture of the government. While the reported figures showed that

the rates charged were within the guidelines, there was sufficient evidence that actual rates were

higher.(Acha & Acha 2011). As it were, the benefit of the policy were largely marginal, hence

the ceiling on interest rate were removed in January 1992. Interest rate in 2002 was volatile and

rose to unprecedented level (24.85%).

For the liberalization period, lending was allowed to be determined by market forces and the

interest rates actually increased as envisaged. For instance, the nominal deposit and lending rate

rose from 9.5% and 12% in 1986 to 14% and 19.2% respectively in 1987, as a result of the

interest rate liberalization policy in Nigeria. By 1990, the deposit and lending rate have risen to

18.8% and 27.7% respectively. The government intervened in 1991 and pegged the deposit and

lending rate at 14% and 21% respectively. Also, the deposit and lending rate falls from 2.21%

and 22.51% in 2010 to 1.44% and 22.39% in 2011 respectively. This shows that there is a fall

in investment because depositors are discouraged from saving as a result of the low interest rate

(CBN, 2011). It should be remarked, however, that the changes in interest rate management are

significantly different from what prevailed during the era of regulation. The new policy allows

for a band within which deposit rates can be negotiated, while lending rates are no longer

specified for activity sectors. It also allows room for negotiation up to a limit of 21%per annum.

The 2012 monetary policy circular retains the 2011 interest rate policy measure with indication

that efforts would be made to create an enabling environment for investors to invest in the

economy.(CBN 2012). The implication of the tunnel-like structure of interest rate and low

deposit rate are that savings will likely be discouraged, and this will negatively affect fund

mobilization by banks. This will in turn affect the amount of funds available for investment with

retarded influence on economic growth. On the other hand the high lending rate is detrimental to

productive investment and hence economic growth. As Soyibo & Olayinola (2000) observe,

borrowers with worthwhile investment may be discouraged from seeking loans and the quality of

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the mix applicants could change adversely. Again, high lending interest rate could create moral

hazard where loan seekers borrow to escape bankrupting rather than invest or finance working

capital. Generally, the behaviour of the interest rate structure is such that there is a wide spread

margin between deposit and lending rates which may encourage speculative financial

transaction.

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CHAPTER THREE

REVIEW OF RELATED LITERATURE

3.1 Conceptual Framework

Interest rate: According to Keynes, interest rate is the reward for not hoarding but for parting

with liquidity for a specific period of time. Keynes' definition of interest rate focuses more on the

lending rate. Adebiyi (2002) defines interest rate as the return or yield on equity or opportunity

cost of deferring current consumption into future. Some examples of interest rate include the

Saving rate, Lending rates, Treasury bill rate and the Discount rate.

Prof. Learner, in Jhingan (2003), defines interest rate as the price which equates the supply of

credit or saving plus the net increase in the amount of money in the period, to the demand for

credit or investment plus net hoarding in the period. This definition implies that interest rate is

the price of credit which like other prices is determined by the forces of demand and supply of

loanable funds. Apart from this, interest rate can also be categorized as nominal or real. This

categorization credited to Irvin Fisher accommodates the influence of inflation on interest rate.

Nominal interest rate in the observed rate of interest incorporating monetary effects while real

interest rate is arrived at by considering the implication of inflation on nominal interest rate

(Uchendu, 1993, Essia 2005).

Investment: This refers to real capital formation that will produce a stream of goods and

services for present and future consumption (Bannock, Baxter & Rees, 2003). In common terms,

investment is defined as the capital formation in the production. Stiglitz (1993) defines

investment as the acquisition of an asset with the aim of receiving a return. It could also mean

the production of capital goods; goods which are not consumed but instead used in future

production. An example includes building of rail road‟s, or factory. There are several motive for

investment, the basic motive is profit/return. According to Keynes theory, this motive depends

on the expected marginal efficiency of capital (MEC) in relation to the expected rate of interest.

Investment is categories into public and private investment (induced and autonomous). Public

investments are the investment which are being carried out by the government in order to

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provide social amenities to her citizens such as the provision of electricity, housing, good roads,

and so on. While private investments are carried out by the individuals in the economy, they

source for funds from the financial institutions to establish industries in the economy

3.2 THEORETICAL LITERATURE

3.2.1 Theories of Interest rate

Anyanwu (1995), Jorg, G.H (2002), Rasheed, O.A (2010); and Chris,U.O & Anyingang R.O

(2012) explicated the following interest rate theories: (a) the classical theory, (b) the loanable

funds theory, and (c) the Keynesian theory.

(a) The classical theory of interest rate

The rate of interest according to the classical is determined by the supply and demand for capital.

The supply of capital is governed by the time preference while the demand for capital is

determined by the expected productivity of capital. Time preference and productivity of capital

depend upon waiting or saving. The demand for capital is determined by the investors because it

is productive. While the productivity of capital is subject to the law of variable proportions.

Additional units of capital are not as productive as the earlier units. That is, the rate of interest is

just equal to the marginal productivity of capital and it means that at a higher rate of interest, the

demand for capital is low and it is high at a lower rate of interest. Thus, the demand for capital is

inversely related to the rate of interest and the demand schedule for capital or investment curve

slope downward from left to right. The supply of capital depends on saving, rather than the will

to save and the power to save of the individual or community. Some individuals save irrespective

of the rate of interest. Classical economists are of the view that, the higher the rate of interest, the

larger will be the individual saving and the supply of funds.

(b) The loanable funds theory of interest rate

The neo-classical or the loanable fund theory examines interest rate in terms of demand and

supply of loanble funds or credit. According to this theory, the rate of interest is the price of

credit which is determined by the demand and supply for lonable funds. In the words of Prof

Lerner in Jhingan (1992); it is the price which equates the supply of credit, or saving plus the net

increase in the amount of money in a period, to the demand for credit, or investment plus net

hoarding in the period. The demand for loanble fund has primarily three source; government,

businessmen and consumers who need them for purpose of investment, hoarding and

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consumption. The government borrows funds for constructing public works or for war

preparations. The businessmen borrow for the purpose of capital goods and for starting

investment projects. Such borrowings are interest elastic and depend mostly on the expected rate

of profit as compared with the interest rates. The demand of loanable fund on the part of

consumers is for the purchase of durable consumer goods like scooters, houses etc. individuals

borrowings are also interest elastic. The tendency to borrow is more at a lower rate of interest at

a higher rate.

(c) Keynes liquidity of preference theory of interest rate

Keynes defines the rate of interest as the reward of not hoarding but the reward for parting with

liquidity further specified period. It is not the price which brings into equilibrium the demand for

resources to invest with the readiness to abstain from consumption. It is the price which

equilibrates the desire to hold wealth in the form of cash with the available quantity of cash. In

other words, the rate of interest in the Keynesian sense is determined by the demand for and the

supply of money. This theory is therefore characterized as the monetary theory of interest as

district from the real theory of the classical.

Supply of money refers to the total quantity of money in the country for all purpose at any time.

Though the supply of money is a function of the rate of interest to a degree, yet it is considered

to be fixed by the monetary authorities. The demand for money according to Keynes is the

liquidity preference by which his theory of interest rate is commonly known. The liquidity

preference is the desire to hold cash. The rate of interest in Keynes word is the premium which

has to be offered to induce people to hold the wealth in some form other than hoarded money.

The higher the liquidity preference, the higher will be rate of interest that will have to be paid to

the holders of cash to induce them to part with their liquid assets. The lower the liquidity

preference, the lower will be the rate of interest that will be paid to cash-holders.

Keynes gives three reasons why individuals and businessmen hold money, which are the

transactions, precautionary and speculative motive. He holds that the transactions and

precautionary motive of holding money has nothing to do with the rate of interest. But the

speculative motive of holding money is to make gain by investing in bonds. Money held for

speculative purposes is a liquid store of value which can be invested at an opportune moment in

interest-bearing bonds or securities. Bonds and the rate of interest are inversely related to each

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other low bond price are indicative of high interest rates, and high bond price reflect low interest

rates.

(d) The Wicksell theory of interest rate

He examines the relation between the natural interest rate and market interest rate. The natural

interest rate is rate of interest at which the demand for loan capital and supply of savings exactly

agree, and which more or less corresponds to the expected yield on the newly created capital,

will then be the normal or natural real rate. It is the rate consistent with a stable money supply

and stable prices. On the other hand, the market rate of interest is the money prevailing in the

loan market. It is the rate of interest charged by banks or lenders. It depends upon the demand

and supply of money. According to wicksell, the natural rate of interest is essentially variable. It

is partly determined by the demand for loans which, in turn, depends on the expected

profitability of new investment. All factors which affect the expected profitability of investment

bring changes in the natural rate of interest. He pointed out that, the natural rate is not the same

as the market rate. There are disparities between the two rates during the short run which

produce changes in the price level. The market rate of interest tends to be sticky and responds

slowly to changes in the demand for loanable funds. In the long-run, disparities between the two

rates automatically generate forces which bring their equality.(Jhingan, 2010 )

3.2.2 Theories of Investment

Dale, W.J (1967), Jhingan (2010), and Johan, E.E (2013), explicated the following Investment

theories: (a) Accelerator theory, (b) Financial theory (c) Tobin‟s q theory, (d) Neo-classical

theory, (e) Classical theory, and (f) Keynesian theory

(a)The accelerator theory of Investment

The accelerator theory states that an increase in the rate of output of a firm will require a

proportionate increase in the capital stock. The capital stock refers to the desired or optimum

capital stocks, K*. Assuring that capital-output ratio is some fixed constant, V, the optimum

capital stock is a constant proportion of output so that in any period t,

Kt = v Yt

Where Kt is the optimal capital stock in period t, v (the accelerator) is a positive constant, and Yt

is the output in period t.

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Any change in output will lead to a change in the capital stock, thus;

Kt - Kt-1 = v (Yt - Yt-1)

Int = v (Yt - Yt-1) [Int = Kt - Kt-1]

= v D Yt

Where DYt = Yt - Yt-1 and Int is net investment

This equation represents the naïve accelerator.

In the above equation, the level of net-investment is proportional to change in output. If the level

of output remains constants (Y = 0), net investment would be zero. For net investment to be a

positive constant, output must increase. When output starts declining, net investment becomes

negative. This based on the assumption that, there is symmetrical reaction for increase and

decrease of output.

(b)The financial theory of investment

The theory was developed by James Duesenbery. It is known as the cost of capital theory of

investment. The accelerator theories ignore the role of cost of capital in investment decision by

the firm. They assume that the market rate of interest represents the cost of capital to the firm

which does not change with the amount of investment it makes. It means that unlimited funds are

available to the firm at the market rate of interest. In other words, the supply of funds to the firm

is very elastic. In reality, an unlimited supply of funds is not available to the firm in any time

period at the market rate of interest. As more and more funds are required by it for investment

spending, the cost of funds (rate of interest) rises. To finance investment spending, the firm may

borrow in the market at whatever interest rate funds are available.

(c)Tobin’s q theory

James Tobin has proposed the q theory of investment which links a firm‟s investment decision to

fluctuation in the stock market. When a firm finances it capital for investment by issuing share in

the market, its share prices reflect the investment decisions of the firm. Firm‟s investment

decision depends on the following ratio, called Tobin‟s q

capital ofcost t replacemen

stock capital of uemarket valq

The market value of firm‟s capital stock in the numerator is the value of its capital as determined

by the stock market. The replacement cost of firm‟s capital in the denominator is the actual cost

of existing capital stock if it is purchased at today‟s price. Tobin‟s q theory examines investment

by relating the market value of firm‟s financial assets (the market value of its shares) to the

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replacement cost of its real capital (share). According to Tobin, net investment would depend on

whether q is greater than 1 (q > 1) or less than 1 (q < 1). If q > 1, the market value of the firm

share in stock market is more than the replacement cost of it real capital, machinery etc. The firm

can buy more capital and issue additional shares in the stock market. In this way, by selling new

shares, the firm can earn profit and finance new investment. Conversely, if q < 1, the market

value of its shares is less than its replacement cost and the firm will not replace capital

(machinery) as it wears out. The theory provides an incentive to invest for firms on the basis of

the stock market. It does not only reflect the current profitability of capital but also its expected

future profitability. Investment is expected to be higher in the future when the value of q is larger

than 1. Tobin‟s q theory of investment induces firms to undertake net investment even when q is

less than 1 in the present. They may adopt such economic policies which brings future

profitability by raising the market value of their shares.

(d) Neo-Classical Theory of Investment

This theory is developed by Jorgenson (1963) and followed by its 1967 and 1971 versions,

combines the users cost of capital and the accelerator effect to explain investment behaviour. In

this model, the firm is assumed to own most of the capital stock and it can either sell the stock or

make use of it. But if the firm uses its stock, some costs are inevitable to be incurrent. The cost

includes the forgone interest income that the firm generates had it sold the stock, the depreciation

cost that comes with time, and the charges in the market value (price) of capital overtime (this

take negative if the value of capital appreciates and positive otherwise). In such model,

investment tax credit.

(e) Classical theory of investment

They regard the rate of invest as the factor which bring the demand for investment and the

willingness to save into equilibrium with one another. Investment represents the demand for

investable resources and saving represents the supply, whilst the rate of interest is the price of

investable resources at which the two equate (investment and saving). Just as the price of a

commodity is necessarily fixed at that point when the demand for it is equal the supply, so the

rate of interest necessarily comes to rest under the amount of investment at that rate of interest.

(f) Keynesian theory of investment

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The theory emphasised the importance of interest rate in investment decision. But other factors

also enter into the model not least the expected profitability of an investment project. Changes in

interest rate should have an effect on the level of planned investment undertaken by private

sector businesses in the economy. A fall in interest rate should decrease the cost of investment

relative to the potential yield and as result planned capital investment projects on the margin may

become worthwhile. A firm will only invest if the discounted yield exceeds the cost as the

project. The inverse relationship between investment and the rate of interest is represented by

using the marginal efficiency of capital investment (MEC). A fall in the rate of interest causes an

expansion of planned investment. Planned investment can change at each rate of interest. The

MEC is the expected rate of return over cost of new capital goods. In order to find whether it is

worthwhile to purchase capital goods, it is essential to compare the present value of the capital

asset with its cost or supply price (interest rate). If the present value of a capital project exceeds

it cost of buying, it pays to buy it. On the contrary, if its present value is less than it cost, it is not

worthwhile in investing in the capital project.

From the above theories of interest rate and investment, this research work is based on the

Keynesian theory of interest rate and investment. This is because the Keynesian explain the

behaviour of investment toward interest rate, which is in relation to the situation of Nigeria,

when the interest rate is regulated, investment is negative because the rate of interest is very high

but when deregulated, the rate of interest is left into the hands of demand and supply to decide.

3.3 Empirical Literature

Several empirical studies have proved that increased real interest rates raise the quantity and

quality of investment. Such that two channels for the effect have been postulated. First, is that

the higher interest rates increase the availability of domestic credit to finance investment,

although the theory here is hard to distinguish from the effect of interest rate on savings. Second,

that potential channel through McKinnon (1973) hypothesis on the complementarily of money

and capital indicating that investment project are lumpy, and that investors must accumulate their

investment balances in the form of deposits until the required amount of principal is reached.

The study by in Fry (1981a)have shown that credit availability mechanism has been reported for

12 Asian developing countries which showed that the ratio of domestic credit to nominal gross

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national product (GNP) is positively and significantly related to real interest rates. Fry (1981b)

gives similar results for seven pacific basin developing countries. Fry (1980) found strong

positive and significant relationship between the availability of domestic credit and investment in

a pooled time-series study of 61 developing countries, while Fry (1986) reached similar

conclusion from a study of 14 Asian developing countries. He employs the OLS technique in his

work.

The complementarily hypothesis has been investigated extensively and with conflicting results.

One group of studies tests the hypothesis by including real money balance in investment or

savings functions. A positive and significant co-efficient has been identified, for example by Abe

et al (1975), Fischer (1981), and Jao (1976).

A second group of studies has tested the complementarily hypothesis by including either an

investment variable or a saving variable in demand for money function. Akhtar (1974) rejected

the hypothesis in a study of Pakistan using the investment rate. Similarly, Harries (1979) found

that out of tests our 5 Asian developing countries, only the results for one (Taiwan) supported the

hypothesis. In a test using the saving rate Fry (1978) found a negative and significant coefficient

in a pooled time-series study for 10 Asian developing countries and rejected the hypothesis.

However, in time series tests for India and Nnanna (2001), Thornton (1990), found a positive

and significant coefficient for the savings rate in a demand for money function and a positive and

significant coefficient for the real money balances in a savings function, and concluded that the

complementarily hypothesis was relevant for the poorest developing countries.

Majed & Ahmed (2010) investigate the impact of real interest rate liberalization on investment in

Jordan over the period 1990-2005. the result were found to be in line with the economic theory

and some other studies in the sense that interest rate liberalization has a negative impact on

investment, where it is found that an increase in interest rate by 1% reduces the investment level

by 44% on the other hand the income level has a positive impact.

There have been few studies relating directly to the efficiency of investment. In a study of

Turkey, Fry (1979) found a positive and significant relationship between real interest rates and

the incremental capital-output ratio. A similar result was achieved in a pooled time-series. Study

of 11 Asian developing countries by the Asian Development Bank (1985).

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Eregha (2010) examined variations in interest rate and investment determination in Nigeria

between the periods of 1970-2002 and deduced that investment has an indirect relationship with

interest rate variation and other variables that he used. These variables such as debt burden,

economic stability, foreign exchange, shortage and lack of infrastructure affect gross investment

and the OLS technique was employed.

Government have attempted to raise private savings through interest rates liberalization. In the

development economic literature, the theory of high interest rate policy was popularized by

McKinnon (1973) and Shaw (1973) who argued that, in countries characterized by financial

repression, raising nominal interest rates relative to inflation would increase saving and the

supply of investable resources in an economy. According to the McKinnon and Shaw doctrine,

financial repression arises mostly when a country imposes ceilings on nominal deposit and

lending interest rates at a low level relative to inflation the resulting low or negative real interest

rates discourage saving mobilization and the channelling of the mobilized saving through the

financial system.

Country and cross-country studies for OECD (Organisation for Economic Cooperation and

Development) countries tend to show that saving is not much influenced by interest rates

(Deaton 1992). Increasing evidence for developing countries (Giovanini, 1983, 1985, Corbo &

Schmidt-Hebbel 1991; Scmidt-Hebbel, Webb & Corsetti 1992) suggests that private savings (or

consumption) typically does not respond to the real interest rates. Edwards (1994) confirms that

insensitivity of private savings to the real interest rate for a cross-country sample of OECD and

developing economies. In those exceptional cases where a positive response of saving to the

interest rates is found (Gupta 1997, Fry 1988), it is quantitatively very small.

There is little evidence that domestic savings in developing countries are interest-elastic (Fitz

Gerald, 1989; Jansey, 1989; Taylor, 1988) and it is widely held that sustained increases in the

real interest rates generally dampens the response of investment expansion. Further, empirical

evidence has shown that a significant portion of the private sectors savings is used to finance

capital flight rather than investment (Fitz Gerald & Sermad, 1990). Hence, they conclude that the

suggestion that the removal of distortions in the savings market will yield higher savings

investment and growth does not coincide with the facts.

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The findings by Deaton (1992), Giovannini (1983, 1985) Corbo & Schmidt-Hebbel (1992),

Schmidt-Hebbel, Webb & Corsetti (1992) and Edwards (1994) that savings is insensitive to real

interest rates are in direct contradiction to real life experience and empirical evidence in Nigeria.

Soyibo & Adekanye (1992), in their investigation of the relationship between aggregate savings

and real interest rates in Nigeria use OLS regression model but in a log form and find aggregate

savings to be positively and significantly correlated with real interest rates.

Turtelboom (1991) has provided reasons for one to be sceptical about the impact of interest rates

on saving in Africa. He examines the experience of five African countries (Gambia, Ghana,

Kenya, Malawi, and Nigeria) with interest rate liberalization. It was revealed that despite

substantial progress made in reforming their financial systems, liberalization only partially

affected the level and variability of interest rate in these countries. This behaviour of interest

rates was attributed to the underdevelopment of financial markets and the oligopolistic structure

of the banking industry which kept interest rate spreads wide through the collusive behaviour of

the dominating banks.

Fry (1978) found that although higher interest rate in Nepal following liberalization triggered a

change in the composition of many stock-currency fell relative to deposits; there was a sharp

contraction in both private sector demand for credit and the volume of investment. However,

using pooled time-series data to estimate national savings functions for fourteen (14) Asian

developing countries, Fry (1988) found that the real deposit rate of interest exerts a positive and

significant effect on national savings.

Giovannini (1983) estimated regressions similar to Fry‟s (1988), coming up with contrasting

results, using data from the 1960s and 1970s for seven Asian countries, he found no real interest

rate effect on savings. On the argument that traditional savings equation may not reveal the

response of aggregate saving to the interest rate, Giovannini (1985) supplement Keynesian type

saving functions with estimates of the inter-temporal elasticity of substitution in consumption.

Using annual data for 18 developing countries, it was found that only in 5 cases did consumption

respond significantly to changes in interest rates.

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Since the seminar work by McKinnon (1973) and Shaw (1973), there has been a considerable

amount of empirical research into the workings of financially repressed economies and the

beneficial effects of financial liberalization. The McKinnon-Shaw claim is that a repressed

financial system interferes with development in a number of ways: saving vehicles are

underdeveloped and/or the return on savings is negative or unstable; financial intermediaries that

collect savings do not allocate them efficiently among competing uses, and firms are discouraged

from investing because poor financial policies reduce the returns to investment or make them

excessively unstable. In contrast, liberalization on the financial sector from interest rate ceiling

and other restrictions facilitate economic development and growth because higher interest rates

lead to increased savings and a more efficient allocation of capital. The empirical proposition is

that increased real interest rate promotes economic growth. In a model which captured interest

rates on economic growth in 7 Asian countries, Fry (1980) concludes that around half a

percentage point in economic growth was foregone for everyone percentage point by which the

real rate of interest is set below its equilibrium level. The Lanyi & Saracoglu (1983) study also

found a positive and significant relationship between interest rate and the rate of growth of real

GDP.

Phylaktis (1997) however notes that despite the trauma associated with liberalization, by the

early 1990s, Chile was at the most advanced stage in the process compared to other Latin

American countries and was poised to resume sustainable growth. Nominal and real interest rates

were however at high level despite substantial capital inflows, as the demand for credit remained

high.

Robert and Ross (1992) demonstrate that 119 countries sampled, both developed and developing

countries with average real interest rate below -0.5 over the 1974-1989 period tended to grow

more slowly than countries with average real interest rates greater than -0.5. This generally

supports the findings of Gelb (1989), Easterly (1990); and Roubini & Sala-Martin (1991) that

severely repressed interest rates are associated with slow growing countries. Furthermore, Robert

& Ross (1992) find that countries with severely depressed interest rates tend to have low

investment rates and low efficiency of investment measures. Less favourable results have been

found in other studies however. A paper by Khatkhate (1988) found no difference in average real

GDP growth rate between countries having below average and above-average real interest rates

in a sample of 64 developing countries. In addition, Gupta (1984) found conflicting results in

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two studies. Thus, the Gupta cross-section study of 25 Asian and Latin American countries

found an unfavourable effect of higher interest rates on the rate of economic growth. In a study

of India and Korea, however, Gupta found evidence that higher real interest rate raised

economic growth (John Thornton 1991).

Fry (1988) stated that interest rate liberalization increase the supply and allocation of resources

for investment. Financial intermediation was found to have an affirmative shock on economic

growth for a sample of 74 countries Levine and Beck (2000). Similarly, Bekaert & Harvey

(2001) found that interest rate liberalization contributing 30% to the process of economic

growth. Mattoo et al (2006) found interest rate liberalization having an affirmative and

momentous effect on economic growth in a sample of 59 countries. Ozdemir & Erbril (2008)

empirically investigated the impact of interest rate liberalization on economic growth in 10 new

European Union countries and Turkey between 1995 and 2007. Their findings take cognizance

of interest rate liberalization as a policy tool because of its possibility to promote economic

growth.

Asamoah (2008) assessed the interest rate liberalization and its impact on saving, investment,

and the growth of GDP in Ghana. The empirical estimation of 42 observations that is, January

2000 to June 2003 was evaluated using OLS and the result show that the rise in interest rate

over the years after liberalization has led to a corresponding increase in saving which has a

positive impact on the growth of GDP.

Obamuyi (2009) studied the relationship between interest rate and economic growth in Nigeria.

The study employed co integration and error correction modelling techniques and reveal that

lending rate has significant effect on economic growth. The study then postulated that

investment friendly interest rate policies necessary for promoting economic growth needs to be

formulated and properly implemented. Akintoye & Olowlaju (2008) examine optimum

macroeconomic investment decision in Nigeria. The study employed OLS and VAR framework

to stimulate and project inter-temporarily private investment response to its principal shock

namely public investment, domestic credit and output shock. The study found low interest rate to

have constrained investment growth. The study resolve that only government policies produce

sustainable output, steady public investment and encourage domestic credit to the private sector

will promote private investment. Obute, C. et al (2012) assess the impact of interest rate

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deregulation on economic growth of Nigeria, their findings reveal that real deposit rate has no

significant impact on saving before and after deregulation (liberalization); and also, real lending

rate has no significant impact on investment before and after liberalization but that investment

has a positive and significant impact on economic growth.

Onwumere, Okore & Imo (2012) were of the view that interest rate liberalization causes interest

rate to rise, thereby increasing saving and investment. It covers the period 1976 to 1999 and

adopts OLS technique using SPSS statistical software. The study reveals that interest rate

liberalization has a negative significant impact on investment in Nigeria; only real lending rate

was use in the estimation of investment. Thus, interest rate liberalization, though a good policy,

was counterproductive in Nigeria. This might be as a result of improper pace and sequencing.

The result did not give room for comparative analysis of what happen during the pre-

liberalization and post –liberalization periods.

Akiri & Adofu (2007); investigate the effect of interest rate deregulation on investment in

Nigeria between 1986-2002 and uses OLS regression model to authenticate the proficiency of

interest rate deregulation on gross domestic investment in Nigeria. The study also identified

other factors which impede investment in Nigeria namely, political instability, exchange rate

inflation rate, unawareness of investment opportunities and corruption in other to bring out the

level of influence of exchange rate and inflation rate into investment.

Chuba (2005) investigate the validity of the proposition that the high interest rate observed

during the era of post liberalization of interest rate have been frequently blamed for the

investment contraction in Nigeria. The study makes use of descriptive and analytical tools, the

finding shows that real lending rate have a negative but insignificant impact on gross domestic

investment (GDI) and that interest rate liberalization does not have negative impact on GDI as

usually claimed.

3.4 Limitations of Previous Studies

From the empirical review above, it is clear that, the previous literature have been done to

investigate the impact of Interest rate liberalization on savings and investment in Nigeria. For

instance the work of Akiri & Adofu (2007) uses real lending rate, exchange rate and inflationary

rate to estimate the behaviour of interest rate deregulation towards investment by using OLS but

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fail to do a comparative analysis. Chuba (2005) uses gross domestic product, real lending rate

and foreign capital to estimate the interest rate policy and investment behaviour in Nigeria

between 1973-2002. Furthermore, Onwumere, Okore & Imo (2012) estimate the impact of

interest rate liberalization on savings and investment in Nigeria by using real lending rate to

estimate the investment function but fail to do an indebt comparative analysis of what happen

during the pre-liberalization and post-liberalization regime. None of the works clearly compare

the periods before and after liberalizations to show if really interest rate liberalization has any

impact on investment. This work therefore departed from other works by comparing the two

periods to establish the impact of interest rate liberalization on investment and to test for the

structural break. In addition, this work include market capitalization rate to show the amount of

capital available to investors.

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CHAPTER FOUR

METHODOLOGY

4.1 Theoretical Framework

The framework for the analysis is based on the Financial Liberalization Theory put forth by

McKinnon (1973) and Shaw (1973) which postulates that financial liberalization in financially

repressed developing countries would induce higher savings, especially financial savings,

increase credit supply, stimulate investment and hence help to boost economic growth. They

both claim that interest rate regulations usually lead to low and sometimes negative real interest

rates, which is the cause of unsatisfactory growth performance of developing countries. They

claim that financial repression through interest rates ceiling keeps real interest rates low and thus

discourages savings and consequently, stifles investment. Thus investment is constrained as a

result of low savings resulting from financial repression. The quality of investment will also be

low because the projects that would be undertaken under a regime of repression would have a

low rate of yield. With interest rate deregulation, real interest rates would rise thereby increasing

both savings and investment. The increased investment results in the rationing out of low-

yielding projects and subsequent undertaking of high-yielding projects would therefore boost

economic growth.

Though both Mackinnon and Shaw advocated that interest rates deregulation was needed to

remedy the problems caused by financial repressive policy of developing countries as established

by Kar and Pentecost (2001). They further assert that the implication of the theory is that the

demand for real money balances (M/P) depends positively upon real income, Y, the own real rate

of interest on bank deposits, R, and the real average return on capital, r. Critically, the positive

association between the average real return on capital and the demand for money balances

represents the complementarity between capital and money. This, however, is only one leg of the

complementarity hypothesis.

According to McKinnon, the investment ratio, I/Y, must also be positively related, inter alia, to

the real rate of return on money balances. This is because a rise in the real return on bank

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deposits, R, if it raises the demand for money and real money balances are complementary to

investment, it must also lead to a rise in the investment ratio. The researcher hereby adopts this

theory as the main theoretical framework of this research and following Bouzid (2012), the

McKinnon-Shaw theory therefore gives a demand for money function and a demand for

investment function as:

, ,m i

f y dp y

…………………………………………..1

Equation (1) is the standard long-run real money demand function.

With Y = Real income

i

y = Investment rate

d

= Real interest rate

d = Nominal interest rate

= Anticipated inflation rate

])(

)(

Y

P

M

: represents the money demand for transaction. An increase in the income generates

a strong monetary detention.

]

)(

)(

Y

I

P

M

: This partial derivative represents the money demand for investment. An increase in

investment rate allows a strong money detention. In other words, the investment increases the

monetary saving. It is an important condition of success of financial reform policies for the

transmission of the investment to the saving.

])-d(

)(

a

P

M

A positive real interest rate allows a greater money demand. However,

McKinnon complementary theory appears in the following investment function:

,i

f r dy

…………………………………………………2

Equation (2) is an investment function.

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27

r: the physical capital average current rate.

])(

)(

r

Y

I

and ])-d(

)(

a

Y

I

Thus, the complementarity‟s theory seen in the partial derivatives following:

]

)(

)(

Y

I

P

M

........................................................................................................3

])-d(

)(

a

Y

I

....................................................................................................4

Equations (3) and (4) suggest that it is not the cost of capital but the availability of finance that

constrains investment in financially repressed economies. When the real deposit rate increases,

investment increases as well because the financial constraint is relaxed. However, the traditional

theory suggests the reverse, that is, that an increase in interest rate reduces investment.

For Shaw, the investment (I) is a decreasing function of real interest rate (r) and the saving is an

increasing function of investment rate (g) and real interest rate (r). The above investment and

saving functions are express as:

I I r 0)(

)(

r

I

.................................5

,S S r g 0)(

)(

r

S

0

)(

)(

g

S

........6

4.2 Model Specification

Based on the framework above and following the Obamuyi (2009) approach in estimating the

relationship between interest rate and economic growth in the regulated and deregulated era in

Nigeria. The functional form of the model is specified thus:

Invt =f(ir, mkcp, pubexp, trop,)..........................................................................7

where;

invt = proxy for Gross Domestic Investment;

i r = Interest Rate;

mkcp =Market Capitalization Rate;

exppub = Public Expenditure;

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trop = Trade openness

MODEL 1:

To estimate objective one which is to examine the impact of interest rate on investment in

Nigeria, equation (7) is rewritten in an econometric form thus:

∆ invtt = α0 + α1∆irt + α2∆mkcpt + α3∆pubexpt + α4∆tropt + µt………………….8

where

αo = the intercept of the model

α1..α4 = the slope coefficient of explanatory variable

∆ = refers to a first difference

µt = error term

ir, mkcp, pubexp and trop are already being explained above.

MODEL 2:

To estimate objective two, which is to determine the differential impact of interest rate

liberalization on investment in Nigeria during the pre and post liberalization regimes, the study

transform equation 7 with the introduction of dummy variables as specified below:

Invtt = λ0 + λ1irt + λ2mkcpt + λ3pubexpt + λ4tropt + ψ0di + ψ1 diirt + ψ2 dimkcpt +

ψ3dipubexpt + ψ4ditropt + µt .......................................................................................9

where;

di = (Dummy variable to control for changes in the pre and post liberalization regimes, (1987-

2012=1, and 0 otherwise) ;

λ0 and ψ0 = the intercept of the model

λ1.... λ4 and ψ1 and ψ4 = the slope coefficient of explanatory variable.

All other variables as defined above.

MODEL 3

In order to estimate Objective three which is to examine the structural responses of investment to

changes in interest rate in Nigeria, Vector Autoregression(VAR) estimation technique is

employed. The specification is as follows:

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𝑖𝑛𝑣𝑡𝑡 = 𝛼0 + 𝛼1 𝑖𝑛𝑣𝑡𝑡−𝑖 +

𝑘

𝑗=𝑖

𝛼2 𝑖𝑟𝑡−𝑖 + 𝛼3 𝑚𝑘𝑐𝑝𝑡−𝑖 + 𝛼4 𝑝𝑢𝑏𝑒𝑥𝑝𝑡−𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

+ 𝛼5 𝑡𝑟𝑜𝑝𝑡−𝑖

𝑘

𝑗=𝑖

+ 𝜇𝑡 ………………………………………………………… 10

𝑖𝑟𝑡 = 𝛿0 + 𝛿1 𝑖𝑛𝑣𝑡𝑡−𝑖

𝑘

𝑗=𝑖

+ 𝛿2 𝑖𝑟𝑡−𝑖 + 𝛿3 𝑚𝑘𝑐𝑝𝑡−𝑖 + 𝛿4 𝑝𝑢𝑏𝑒𝑥𝑝𝑡−𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

+ 𝛿5 𝑡𝑟𝑜𝑝𝑡−𝑖

𝑘

𝑗=𝑖

+ 휀𝑡 …………………………………………………………11

𝑚𝑘𝑐𝑝𝑡 = 𝛽0 + 𝛽1 𝑖𝑛𝑣𝑡𝑡−𝑖 +

𝑘

𝑗=𝑖

𝛽2 𝑖𝑟𝑡−𝑖 + 𝛽3 𝑚𝑘𝑐𝑝𝑡−𝑖 + 𝛽4 𝑝𝑢𝑏𝑒𝑥𝑝𝑡−𝑖

𝑘

𝑗=1

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

+ 𝛽5 𝑡𝑟𝑜𝑝𝑡−𝑖

𝑘

𝑗=1

+ 𝜑𝑡 ………………………………………………………… 12

𝑝𝑢𝑏𝑒𝑥𝑝𝑡 = 𝛾0 + 𝛾1 𝑖𝑛𝑣𝑡𝑡−𝑖

𝑘

𝑗=𝑖

+ 𝛾2 𝑖𝑟𝑡−𝑖 + 𝛾3 𝑚𝑘𝑐𝑝𝑡−1 + 𝛾4 𝑝𝑢𝑏𝑒𝑥𝑝𝑡−𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

+ 𝛾5 𝑡𝑟𝑜𝑝𝑡−𝑖

𝑘

𝑗=𝑖

+ 𝜌𝑡 ………………………………………………………… 13

𝑡𝑟𝑜𝑝𝑡 = 𝜃0 + 𝜃1 𝑖𝑛𝑣𝑡𝑡−𝑖

𝑘

𝑗=𝑖

+ 𝜃2 𝑖𝑟𝑡−𝑖 + 𝜃3 𝑚𝑘𝑐𝑝𝑡−𝑖 + 𝜃4 𝑝𝑢𝑏𝑒𝑥𝑝𝑡−𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=𝑖

𝑘

𝑗=1

+ 𝜃5 𝑡𝑟𝑜𝑝𝑡−𝑖

𝑘

𝑗=𝑖

+∞𝑡 ………………………………………………………… 14

where:

All the variables are as defined above

k = lag order/length

𝛼, 𝛿,𝛽, 𝛾,𝜃, = parameters

𝜇, 휀,𝜑, 𝜌,∞, = structural innovations (error term)

4.3. Method of Estimation

In order to estimate objective one and two, the study uses multiple regression and employs

ordinary least squares (OLS) estimation technique. The OLS technique is favoured because of its

BLUE property. The OLS estimator is said to be Best Linear Unbiased Estimator (BLUE) in the

class of all available estimators if the following assumptions are satisfied:

1. It is linear, that is, a linear function of a random variable, such as the dependent variable,

Y in a regression model.

2. It is unbiased, that is, its average or expected value E(âi) is equal to the true value ai.

3. It has minimum variance in the class of all such linear unbiased estimators; an unbiased

estimator with the least variance is known as an efficient estimator.

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However, there is no guarantee that economic time series (variables) will always satisfy these

assumptions and so the estimation shall proceed as follow. First the models shall be estimated,

after which the variance inflation factors (VIF) shall be examined for linear relationship among

the explanatory variables.

To estimate objective two, dummy variable technique is employ to determine the differential

impact of interest rate liberalization on investment during the pre and post liberalization regime.

The dummy technique provides valuable information about the existence of a regime.

To estimate objective three, VAR estimation technique is employed. Before the VAR equations

are estimated, the maximum lag length will be selected. This is to avoid degree of freedom

problem and the possibility of introducing multicollinearity, as well as specification errors. For

the selection of the maximum lag length, the Akaike information criterion (AIC) and the

Schwartz Bayesian information Criterion (SBIC) are chosen. Of the two criterions, the Bayesian

approach is especially attractive (that is, preferable). SVARs are proliferative parameterized.

The study shall also examine the time series properties of the data by checking the stationarity

properties of the data and the evidence of cointegration. It shall also employ Zivot and

Andrews‟s unit roots tests which are more robust in the presence of structural breaks

Impulse responses and variances decompositions shall be used to interpret the model results

since the VAR coefficients are not directly interpretable. In order to ensure that the results are

reliable, the study shall conduct diagnostics tests such as eigen-value stability test, normality and

autocorrelation tests, lag exclusion tests, and portmanteau tests. It is when the basic tests, such as

the stability tests, are satisfied that the impulse response functions and variance decompositions

will have meaningful interpretation.

4.4 Justification of the Model

In this study, which aim at analysing the impact of interest rate liberalization on investment in

Nigeria has been before the regime of interest rate deregulation and after the regime. And with

the motivation to investigates the interest rate deregulation and investment relationship by taking

into consideration the transmission mechanism through which interest rate affect investment.

Therefore, borrow from the methodology of the Mckinnon complementarity hypothesis by

adopting the impulse responses and variances decompositions to pursue the established research

objectives given the well acknowledge frictions in the literature.

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Having established these, the motivations for this methodology is the findings in the literatures

that indicate nature of the model to advance efficiency in estimation by combining information

on both the real money demand and investment equations.

The second motivation is to impose and/or test restrictions that involve parameters in different

equations. The model uses several variables, such as inflation rate, gross fixed capital formation

and political stability proxy by corruption perception index and market capitalization rate

designed to measure the cross correlations of interest rate, and trade openness.

4.5 Source of data

The study employed secondary data collected from the following sources: The Central Bank of

Nigeria Statistical Bulletin (2012), The National Bureau of Statistics Bulletin (2012) and Central

Bank of Nigeria Annual Report and Statement of Accounts. The study will employ the

Statistics/Data Analysis software (Eview 7.0) for the estimation of the various models

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CHAPTER FIVE

PRESENTATION AND ANALYSIS OF RESULTS

5.1 DESCRIPTIVE ANALYSIS OF VARIABLES

Table1 below shows the descriptive statistics of the variables used in the analysis. According to

the table, the mean value of investment (LOG_INVT) in the period was 29.296, and that of

interest rate (IR) was 15.11 which range from 6.00 to 31.65 with a standard deviation of 6.62.

Also, the market capitalization (LOG_MKCP) ranges from 21.659 to 30.326 with a mean and

standard deviation of 24.975 and 2.996 respectively. More so, the logarithm value of public

expenditure (LOG_PUBEXP) has the minimum value of 19.32 with a maximum value of 28.978.

The trade openness (TROP) ranges from 0.072 to 30.045 with the mean of 6.284 and standard

deviation of 8.605 respectively.

Table 1: Descriptive table

LOG_INVT IR LOG_MKCP LOG_PUBEXP TROP

Mean 29.29575 15.11112 24.97493 24.51328 6.283531

Median 29.00264 16.79250 23.86310 24.01998 0.795171

Maximum 31.08487 31.65000 30.32571 28.97778 30.04527

Minimum 27.99502 6.000000 21.65936 19.32679 0.072361

Std. Dev. 0.918081 6.623125 2.995657 2.787700 8.605110

Observations 43 43 43 43 43

Source: E-Views Output (2015)

Figure below shows the trends of the variables used in the regression analysis. It is shown that

the investment returns fell sharply in the initial period of pre liberalization regimes after which

the fall has been gradual and it began to gradually rise from 2005. Interest rate was low prior to

the 1986 (SAP period) after which it began to rise sharply, reaching its peak between 1990 to

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1995, but is now falling in the recent period. Public Expenditure and Market capitalization were

low at the early years and began to rise sharply around the year 2000.

5.2 PRE-DIAGNOSTIC TESTS

5.2.1 Unit Root Test Result

The time series behaviour of each of the series is presented in Tables 4.2 and 4.3 below, using

the ADF and P – P tests at both level and first difference of the series. The computer output is

presented in appendix B, but these have been extracted into the two tables below.

0.0E+00

4.0E+12

8.0E+12

1.2E+13

1.6E+13

2.0E+13

2.4E+13

2.8E+13

3.2E+13

1970 1975 1980 1985 1990 1995 2000 2005 2010

INVT

4

8

12

16

20

24

28

32

1970 1975 1980 1985 1990 1995 2000 2005 2010

IR

0.00E+00

2.50E+12

5.00E+12

7.50E+12

1.00E+13

1.25E+13

1.50E+13

1970 1975 1980 1985 1990 1995 2000 2005 2010

MKCP

0

1,000,000

2,000,000

3,000,000

4,000,000

1970 1975 1980 1985 1990 1995 2000 2005 2010

PUBEXP

0

4

8

12

16

20

24

28

32

1970 1975 1980 1985 1990 1995 2000 2005 2010

TROP

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The ADF test results presented in table 4.2 shows that all the variables are non-stationary at level

which are cointegrated at the order of 1 except for investment which is cointegrated at order 2.

This justifies the number of times they are to be differenced to achieve stationarity.

Table 4.3 of the Phillip Perron test depicts that all the variables are homogenous of order one.

Therefore, they are made stationary by first difference prior to subsequent estimations to forestall

spurious regressions.

Table 2: Augmented Dickey Fuller (ADF) Test

LEVEL FIRST DIFFERENCE Order of

Cointegration

Interpretation

Variables Intercept Trend Intercept Trend

LOG(INVT) -2.2746

(0.1849)

-1.4980

(0.8133)

-1.8400

(0.3563)

-2.5652

(0.2973)

I(2) Non-Stationary

IR -1.6689

(0.4393)

-1.7546

(0.7086)

-7.1624

(0.0000)

-7.1592

(0.0000)

I(1) Non-Stationary

LOG(MKCP) 1.5474

(0.9992)

-1.8163

(0.6790)

-4.6257

(0.0006)

-4.9907

(0.0012)

I(1) Non-Stationary

LOG(PUBEXP) -0.6267

(0.8534)

-2.3019

(0.4235)

-4.3538

(0.0013)

-4.2976

(0.0078)

I(1) Non-Stationary

TROP 3.5640

(1.0000)

2.6939

(1.0000)

-7.1896

(0.0000)

-7.7509

(0.0000)

I(1) Non-Stationary

Source: Authors’ Computation (2015)

Table 3: Phillip-Perron (PP) Test

LEVEL FIRST DIFFERENCE Order of

Cointegration

Interpretation

Variables Intercept Trend Intercept Trend

LOG(INVT) -1.9754

(0.2961)

-0.7129

(0.9654)

-4.8040

(0.0003)

-5.4622

(0.0003)

I(1) Non-Stationary

IR -1.6309

(0.4583)

-1.8171

(0.6786)

-7.1770

(0.0000)

-7.1852

(0.0000)

I(1) Non-Stationary

LOG(MKCP) 1.3352

(0.9984)

-1.8163

(0.6790)

-4.6419

(0.0005)

-5.0135

(0.0011)

I(1) Non-Stationary

LOG(PUBEXP) -1.0296

(0.7340)

-2.0924

(0.5349)

-4.1748

(0.0021)

-4.1109

(0.0125)

I(1) Non-Stationary

TROP 1.0761

(0.9967)

-1.0667

(0.9227)

-7.1953

(0.0000)

-10.0520

(0.0000)

I(1) Non-Stationary

Source: Authors’ Computation (2015)

5.2.2. Co-integration Test

The results of the co-integration tests are extracted into the table below. The computer output is

contained in appendix C. The table shows that the variables converge in the long run, thereby

depicting the existence of long run relationship among the variables. The long run relationship

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exists at 5% level of significance according to the Trace test statistics and the Eigen value. There

exists three (3) co-integrating relationship among the variables based on the Trace statistics

result and two (2) co-integrating vectors among the variables based on the Eigen value. Since the

variables are co-integrated, there is, therefore, a long run relationship among the variables. It

means that the study can proceed to estimating the Error Correction Model.

Table 4: Co-Integration Testing

No. of

CE(s)

Eigen

value

Trace

Statistic

0.05

Critical

Value

Prob.** No. of

CE(s)

Eigen

value Max Eigen

0.05 Critical

Value Prob.**

None * 0.7080 114.504

0 69.8189 0.0000 None * 0.7080 48.0036 33.87687 0.0006

At most 1 * 0.6058 66.5004 47.8561 0.0004 At most 1 * 0.6058 36.3056 27.58434 0.0030

At most 2 * 0.3837 30.1948 29.7971 0.0450 At most 2 0.3837 18.8783 21.13162 0.1004

At most 3 0.2495 11.3166 15.4947 0.1928 At most 3 0.2495 11.1941 14.26460 0.1448

At most 4 0.0031 0.1225 3.8415 0.7263 At most 4 0.0031 0.1225 3.841466 0.7263

Source: Authors’ Computation (2015) Trace and Max-eigenvalue test indicates 2 cointegratingeqn(s) at the 0.05 level

* denotes rejection of the hypothesis at the 0.05 level

**MacKinnon-Haug-Michelis (1999) p-values

5.3 PRESENTATIONS OF REGRESSION RESULTS AND INTERPRETATION

The results of the regressions for the various models are presented below. In the models, the

dependent variable is investment, while the independent variables are interest rate, market

capitalisation rate, public expenditure and trade openness. The results of the error correction

model and innovation accounting (variance decomposition and impulse response) that will guide

our interpretation are as follows:

5.3.1 Error Correction Model

The Error Correction Modelling involves three steps. The first is to estimate a long-run model;

the second is to include the error term from the long model in a dynamic over-parameterised

model and the third is to work on this model until one obtains the parsimonious model which is

then interpreted. The results of the long run models and over-parameterised models are contained

in appendix C and D respectively. What are normally interpreted are the parsimonious results

which are given below. Therefore, based on the result from tables 4, an over-parameterised

model was estimated. Every variable was set at 3 lag. The parsimonious interaction involves

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dropping insignificant variables. Therefore, the size of the model was reduced by imposing zero

coefficients on those lags where„t‟ statistic is low.

The parsimonious result is shown in the table below. According to the result, R2 value of 0.806

shows that all the variables can explain about 80.6% of investment. F-statistic of 7.128 (P<0.05)

shows that they are jointly significant and the Durbin Watson value of 2.017 implies that the

model does not suffer from autocorrelation problem. The ECM has the correct sign of negative

meaning that about 20.4% of the errors are corrected yearly. Precisely, this speed of adjustment

shows that about 20.4% percent of errors generated in each period is automatically corrected by

the system in the subsequent period and is statistically significant.

In terms of the significance of the individual variables, it is observed that all the variables were

significant. This implies that they are the significant determinants of investment in Nigeria.

Precisely, the results show that both current and past period public expenditure has positive

effect on investment. The first, second and third lags of market capitalisation rate are significant

and are positively related to investment. Also, both first and third lags of interest rate are

significant and positively related to investment at 1% and 5% level respectively. Finally, both

second and third lags of trade openness are significant and positively related to investment at

10% and 5% level respectively.

The result shows that period dummy of pre and post liberalization regimes with a value of -0.074

and standard error of 0.102 is not significant, implying that the impact of interest rate

liberalization on investment is not justified by the pre or post liberalization regimes. Hence, there

is no differential impact of interest rate liberalization on investment in Nigeria during the pre and

post-liberalization regimes.

Table 5: Error Correction Mechanism (ECM) Result

Dependent Variable: D(INVT)

Variable Coefficient

D(PUBEXP) 0.127(0.09)

D(INVT(-1)) 0.549***(0.162)

D(IR(-1)) 0.017**(0.008)

D(MKCP(-1)) -0.099(0.106)

D(INVT(-2)) -0.461***(0.15)

D(MKCP(-2)) 0.3**(0.121)

D(PUBEXP(-2)) 0.24**(0.111)

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D(TROP(-2)) 0.03*(0.016)

D(INVT(-3)) 0.626***(0.141)

D(IR(-3)) 0.028***(0.009)

D(MKCP(-3)) -0.125(0.129)

D(TROP(-3)) 0.059**(0.021)

ECM(-1) -0.204**(0.078)

PERIOD_DUMMY -0.074(0.102)

C -0.117(0.076) R-Squared 0.8061 Adjusted R-Squared 0.6930 F-Statistics 7.1284 (0.000) Durbin Watson 2.0167

Source: Authors’ Computation (2015)

Note: *, **, *** represents significance level of 10%, 5% and 1% respectively and Standard error in

parenthesis.

5.3.2 INNOVATION ACCOUNTING

This section presents the results of the impulse response function and the variance decomposition

that will aid the interpretation of the structural responses of investment to changes in interest rate

in Nigeria overtime.

The results of the variance decomposition and impulse response function of variables considered

in this study, using the cholesky - dof ordering are presented here. Explicitly the result shows the

effect of one standard deviation shock or innovation on self and other variables. Specifically,

period 1 of the table indicates that a shock to INVT causes a positive standard deviation value of

100.00 in INVT (own shock). The table also shows that INVT does not respond to innovations

from IR, MKCP, PUBEXP and TROP in period 1. Period 2 shows a standard deviation value of

97.23 in INVT resulting from own shock, 2.44 to a response to a shock from IR, 0.0186 to a

response from MKCP, 0.205900 to a response to public expenditure and 0.101933 to response to

trade openness.

In period 10, INVT responds positively with a standard deviation of 18.77 originated from own

shock and standard deviation values of 8.05, 7.94, 12.43 and 15.59 arising from a shock from IR,

MKCP, PUBEXP and TROP respectively. Furthermore, IR responds positively to shocks from

INVT and own shock in period 1 with standard deviation values of 4.591 and 4.591 respectively.

The standard deviation values of 4.903 and 8.623 indicate positive responses in IR due to shock

from INVT and own shock in Period 2. In the long run, IR respond positively to innovations

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from INVT, own shock, market capitalization, public expenditure and trade openness in period

10 with standard deviations of 15.2359, 15.4114, 5.03372, 6.88330 and9.98708 respectively.

For the impulse response function, the results show that a one-period standard deviation shock to

IR, MKCP, PUBEXP and TROP do not have significant impact on INVT. However, a one-

period standard deviation shock to INVT marginally appreciates IR by less than 1 percent in 2

years before depreciating. A one-period shock to INVT does not have significant impact on

MKCP, PUBEXP and TROP.

Table 6: Variance Decomposition of Investment Result

Period INVT IR MKCP PUBEXP TROP

1 100.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)

2 97.23 (6.14) 2.44 (5.27) 0.02 (1.94) 0.21 (1.52) 0.10 (1.82)

10 62.60 (18.70) 2.84 (8.05) 8.30 (7.94) 11.11 (12.43) 15.16 (15.59)

Source: Authors’ Computation (2015)

Table 7: Variance Decomposition of Interest Rate Result

Period INVT IR MKCP PUBEXP TROP

1 2.25 (4.59) 97.75 (4.59) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)

2 2.93 (4.90) 90.74 (8.62) 0.34 (3.23) 5.57 (6.46) 0.42 (2.73)

10 32.97 (15.24) 58.27 (15.41) 1.07 (5.03) 6.45 (6.88) 1.24 (9.99)

Source: Authors’ Computation (2015)

5.4 EVALUATION OF RESEARCH HYPOTHESES

Having subjected these models to various economic, statistical and econometric tests, the study

hereby presents the conclusions on the hypotheses stated in section 1.5 as evaluated thus:

5.4.1 Test of Working Hypothesis I

The hypothesis of this study can be evaluated from the results of our model.

As evident in the result of the study in append C, the p-value for interest rate is 0.0486 which

was less than 0.05 at 95% confidence interval. Also, other control variables such as public

expenditure, market capitalisation rate and trade openness have significant impact on investment.

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The t-values of all the independent variables are statistically significant. This implies that interest

rate in addition to other control variables do really have significant impact on investment in

Nigeria. The F-statistic of the model is highly statistically significant which indicates that the

overall performance of the model is pretty significant.

For the first hypothesis, we reject the null hypothesis that there is no

significant impact of interest rate on investment in Nigeria and accept

the alternative hypothesis.

5.4.2 Test of Working Hypothesis II

Furthermore, the regression results obtained provide the basis for testing the second hypothesis.

As the regression result shows, the probability value of the dummy is 0.4756 which is greater

than 0. 05 and the standard error is 0.102. On the basis of this, there exists no differential impact

of interest rate liberalization on investment in Nigeria during the pre and post-liberalization

regimes.

For the second hypothesis, we accept the null hypothesis that there is no differential impact of

interest rate liberalization on investment in Nigeria during the pre and post-liberalization

regime in Nigeria and reject the alternative hypothesis.

5.4.3 Test of Working Hypothesis III

The results of the innovation accounting show that after period one, INVT responds positively

from shocks arising from IR, MKCP, PUBEXP and TROP respectively.

For the third hypothesis, we reject the null hypothesis that there are no structural responses of

investment to changes in interest rate in Nigeria overtime and accept the alternative

hypothesis.

5.5 CHAPTER SUMMARY AND PROSPECTS

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In this chapter, the regression results of the postulated models were presented. These results were

economically interpreted, statistically analysed and econometrically evaluated. The various tests

carried out all confirmed the robustness and reliability of the regression results of the model. We

finally evaluated the working hypotheses of this study based on the results obtained. We reject

the null hypotheses one and three, but accept the null hypothesis two. The implications of these

results are that interest rate impacts on investment in Nigeria and also investment responds

positively to changes in interest rate overtime. However, there exists no differential impact of

interest rate liberalization on investment in Nigeria during the pre and post-liberalization

regimes. We shall dedicate the next chapter to the summarize f all the findings of this research

work, proffer policy prescription and finally make conclusion.

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CHAPTER SIX

CONCLUSION AND POLICY RECOMMENDATIONS

6.1 SUMMARY OF RESEARCH FINDINGS

This research work investigated the impact of interest rate liberalisation on investment in

Nigeria from 1970 to 2012. Thus, the study modelled investment against interest rate and other

control variables such as public expenditure, market capitalisation rate and trade openness to

establish a long run relationship among the variables. It further used the Error Correction Model

(ECM) and innovation accounting technique to test the objectives of the study. The ECM has the

correct sign of negative meaning that about 20.4% of the errors are corrected yearly. Precisely,

this speed of adjustment shows that about 20.4% percent of errors generated in each period is

automatically corrected by the system in the subsequent period and is statistically significant.

The study found that interest rate is a significant determinant of investment in Nigeria. This

should be expected as the cost on capital plays major role in investment decisions and the

prospects of investment in most economies. Also, the finding of the study revealed that public

expenditure exerts significant impact on investment in Nigeria. The impact of public expenditure

on investment stems from its role in financing critical infrastructure that improves investment

climate in the economy.

In addition to this, the study revealed that market capitalisation rate plays significant role on

investment in Nigeria. The Nigerian capital market has been showing signs of expansion over the

years. This has the propensity to attract investors to the economy. Also through the capital

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market, funds can be raised by investors. In another vein, the study show that trade openness has

significant impact on investment in Nigeria. Trade openness leads to capital mobility that

encourages investment.

The study examined the differential impact of interest rate liberalization on investment in Nigeria

during the pre and post-liberalization regimes. The finding shows that there exists no differential

impact of interest rate liberalization on investment in Nigeria during the pre and post-

liberalization regimes. Hence, there is no difference in the impact of interest rate liberalisation

during the pre SAP and post SAP period. Finally, the result of the innovation accounting shows

that investment responds positively to shocks arising from interest rate and other control

variables used in the study. Hence, any change in these variables exerts positive influence on

investment.

6.2 POLICY RECOMMENDATIONS

With respect to the research findings, the following policy recommendations were suggested:

The government should use her monetary policies to influence interest rate in a way that it will

not serve as disincentive to investment. The high cost of borrowing in Nigeria has been

complained about by investors in the country. The spread between borrowing and lending rates

in very high and it is skewed in favour of borrowing rate. We are mindful of the relationship

between inflation rate and interest rate that is that, in a regime of high inflation rate, interest rate

is usually high due to the positive relationship between the two variables. On account of this,

effort should be geared towards reducing inflation rate to a lower single digit level so as to bring

down interest rate.

The budget should be structured in a way that capital expenditure is increased. The tradition in

the country is that recurrent expenditure takes a larger chunk of government expenditure, thereby

stifling the financing of capital projects. In her expenditure on capital projects, emphasis should

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be laid on basic critical infrastructure that impact heavily on investment such as energy, roads

and the others.

The capital market should be broadened to make it more attractive to investors with the

introduction of more financial instruments and improvement on the regulatory framework that

gives confidence to investors. The political system should also be stabilised since it also

influences investors‟ confidence. It is also recommended that listing conditions should be made

simpler in order to attract new firms on the stock market.

Policies on external trade should be carefully crafted so that they will not have adverse effect on

the domestic economy. Much as trade liberalisation should be encouraged in order to boost

capital movement, effort should be made to protect domestic investors from stiff competition

arising from products from foreign companies. Incentives should be given to domestic producers

to cushion the effect of high cost of production in the country and, hence make their products

attractive in international market.

Any new policy on interest rate, capital market and trade should be made public before they are

implemented so that investors can gauge the likely implications of these policies on investment

and therefore, take appropriate measures. This is necessary as it has been revealed in the study

that shocks to these variables exert positive influence on investment. Since there is no

differential impact of interest rate liberalisation between the pre and post liberalisation period,

we recommend that monetary authorities should continue to manipulate this rate through

monetary policy committee meetings that is held periodically and the rates should be fine-tuned

in a way that it can boost investment without jeopardising other macroeconomic objectives.

6.3 CONCLUSION

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This research has provided reliable evidence of the impact of interest rate on investment in

Nigeria. The conclusion to be drawn from this study is that interest rate exerts significant

influence on investment in Nigeria. In order to boost investment in Nigeria, certain

recommendations have been made in this study which when considered hold the key to

unlocking the investment potentials in the country.

Owing to the role played by interest rate in investment, making this rate affordable will go a long

way in boosting investment in Nigeria. In addition to interest rate, other control variables as used

in this study also impact on investment. They include government expenditure, market

capitalisation rate and trade openness. Infrastructural facilities such as electricity, roads and

others are germane to investment; therefore, government should improve its capital project in

order to finance these critical infrastructures. Without an efficient and effective capital market,

investment will be retarded. Owing to the importance of the capital market, policies should be

directed at broadening it through effective institutional framework.

Trade policies should be crafted to ensure that they do not hurt domestic investment. Since

Nigeria thrives on importing most of her needs, incentives should be given to domestic investors

to cushion the negative effect of dumping in the country. Also the monetary authorities should

continue to manipulate the interest rate in line macroeconomic realities in the economy. Finally,

policy changes on interest rate, trade and the capital market should be made public so that

investors can take appropriate measures to guide against unpleasant shocks that may arise from

the implementation of such policies.

6.4 RECOMMENDATIONS FOR FURTHER STUDIES

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This research work as could be seen from all our hypotheses and analyses is limited to

investigating the impact of interest rate on investment in Nigeria. It is worthy to note that this

study did not consider some variables that may affect investment in Nigeria. These variables

include fiscal deficit which has the tendency to crowd out private investment and it is pertinent to

note that Nigeria embarks more on fiscal deficit in her budget execution due to short fall in

revenue. Another variable is exchange rate which is very important in influencing investment

through its impact on portfolio investment and the importation of production inputs by domestic

investors. In subsequent studies, we also recommend that focus should be placed on investigating

the determinants of the three types of investment in Nigeria viz: foreign direct investment,

private investment and public investment. In summary, we recommend the following for further

studies:

I. The inclusion of fiscal deficit as a control variable in analysing the determinants of

investment in Nigeria

II. The inclusion of exchange rate as another important control variable.

III. Placing a focus on foreign direct investment, private investment and public investment thier

determinants in Nigeria.

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APPENDIX A

DATA PRESENTATION

YEAR INVT IR MKCP PUBEXP TROP

1970 3.16219E+13 7 2550000000 247.5 0.3892126

1971 2.95221E+13 7 2770000000 444.0 0.5030856

1972 2.74223E+13 7 2990000000 594.0 0.4954832

1973 2.53224E+13 7 3210000000 729.8 0.6597363

1974 2.32226E+13 7 3430000000 1,353.5 0.4731308

1975 2.11227E+13 6.25 3650000000 3,059.3 0.3182318

1976 1.90229E+13 6.5 3870000000 4,657.6 0.4082684

1977 1.69231E+13 6 4090000000 6,339.9 0.4671396

1978 1.48232E+13 6.75 4310000000 4,213.9 0.4887008

1979 1.27234E+13 7.7875 4530000000 4,342.4 0.6113699

1980 1.06236E+13 8.4316667 4750000000 7,233.8 0.7380251

1981 8.65792E+12 8.9166667 5000000000 10,990.9 0.1162784

1982 6.29859E+12 9.5375 5000000000 10,680.5 0.0950341

1983 4.17214E+12 9.9766667 5700000000 11,090.9 0.0883964

1984 2.36728E+12 10.241667 5500000000 7,064.9 0.0886143

1985 2.58311E+12 9.4333333 6600000000 5,857.1 0.0934329

1986 2.60227E+12 9.9591667 6800000000 5,774.7 0.0723605

1987 1.67929E+12 13.961667 8200000000 8,263.5 0.2354529

1988 1.43907E+12 16.616667 10000000000 10,778.5 0.2394012

1989 1.94941E+12 20.441667 12800000000 12,974.7 0.3752442

1990 2.73549E+12 25.3 16300000000 20,049.3 0.5815885

1991 2.71815E+12 20.041667 23100000000 27,023.7 0.7951714

1992 2.65247E+12 24.758333 31200000000 37,060.6 1.2852145

1993 3.0695E+12 31.65 47500000000 44,180.7 1.3987771

1994 2.73698E+12 20.483333 66300000000 55,916.2 1.3390715

1995 2.01907E+12 20.233333 1.804E+11 77,895.1 6.0616356

1996 2.38114E+12 19.836667 2.858E+11 83,987.6 6.3734449

1997 2.59143E+12 17.795 2.819E+11 92,686.2 6.9113379

1998 2.46212E+12 18.184167 2.626E+11 143,168.0 5.1120182

1999 2.39154E+12 20.29 3E+11 167,896.1 6.5715559

2000 2.79685E+12 21.274167 4.723E+11 359,670.6 8.9032047

2001 2.18327E+12 23.438333 6.625E+11 596,956.4 9.0369357

2002 2.62663E+12 24.770833 7.649E+11 724,537.2 7.5181132

2003 3.94171E+12 20.714167 1.3593E+12 921,159.7 10.822544

2004 2.99637E+12 19.180833 2.1125E+12 1,125,057.0 12.490762

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2005 2.68397E+12 17.948333 2.90006E+12 1,478,585.4 17.880103

2006 4.27559E+12 16.9 5.1209E+12 1,586,796.6 17.51061

2007 6.05865E+12 16.939167 1.31817E+13 2,116,138.9 19.269513

2008 6.01503E+12 15.479833 9.56297E+12 3,021,602.24 22.839743

2009 8.10499E+12 18.361667 7.03084E+12 2,776,912.95 18.802556

2010 9.59106E+12 17.585 9.91821E+12 3,266,234.72 24.888056

2011 6.75696E+12 16.016667 9.67265E+12 3,542,001.15 30.045269

2012 6.92655E+12 16.7925 1.48009E+13 3,844,925.84 26.798002

Descriptive Statistics

INVT IR MKCP PUBEXP TROP

Mean 8.25E+12 15.11112 1.84E+12 609933.3 6.283531

Median 3.94E+12 16.79250 2.31E+10 27023.70 0.795171

Maximum 3.16E+13 31.65000 1.48E+13 3844926. 30.04527

Minimum 1.44E+12 6.000000 2.55E+09 247.5000 0.072361

Std. Dev. 8.57E+12 6.623125 3.85E+12 1104408. 8.605110

Skewness 1.446221 0.196137 2.153904 1.809700 1.346579

Kurtosis 3.826860 2.158639 6.379887 4.904454 3.594810

Jarque-Bera 16.21443 1.544000 53.71568 29.96920 13.62902

Probability 0.000301 0.462088 0.000000 0.000000 0.001098

Sum 3.55E+14 649.7782 7.92E+13 26227134 270.1918

Sum Sq. Dev. 3.09E+27 1842.363 6.22E+26 5.12E+13 3110.013

Observations 43 43 43 43 43

Descriptive Statistics

LOG_INVT IR LOG_MKCP LOG_PUBEXP TROP

Mean 29.29575 15.11112 24.97493 24.51328 6.283531

Median 29.00264 16.79250 23.86310 24.01998 0.795171

Maximum 31.08487 31.65000 30.32571 28.97778 30.04527

Minimum 27.99502 6.000000 21.65936 19.32679 0.072361

Std. Dev. 0.918081 6.623125 2.995657 2.787700 8.605110

Skewness 0.605895 0.196137 0.517177 0.135840 1.346579

Kurtosis 2.010128 2.158639 1.754934 1.924502 3.594810

Jarque-Bera 4.386508 1.544000 4.694303 2.204655 13.62902

Probability 0.111553 0.462088 0.095641 0.332097 0.001098

Sum 1259.717 649.7782 1073.922 1054.071 270.1918

Sum Sq. Dev. 35.40066 1842.363 376.9064 326.3935 3110.013

Observations 43 43 43 43 43

APPENDIX B

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Unit Root Test: Augmented Dickey Fuller Test

At Level

LOG_INVT @ Intercept

Null Hypothesis: LOG_INVT has a unit root Exogenous: Constant Lag Length: 3 (Automatic - based on SIC, maxlag=9)

t-Statistic Prob.* Augmented Dickey-Fuller test statistic -2.274637 0.1849

Test critical values: 1% level -3.610453 5% level -2.938987 10% level -2.607932 *MacKinnon (1996) one-sided p-values.

LOG_INVT @ Trend

Null Hypothesis: LOG_INVT has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 3 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -1.498026 0.8133

Test critical values: 1% level -4.211868

5% level -3.529758

10% level -3.196411

At First Difference

D(LOG_INVT) @ Intercept

Null Hypothesis: D(LOG_INVT) has a unit root

Exogenous: Constant

Lag Length: 2 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -1.839962 0.3563

Test critical values: 1% level -3.610453

5% level -2.938987

10% level -2.607932

*MacKinnon (1996) one-sided p-values.

D(LOG_INVT) @ Trend

Null Hypothesis: D(LOG_INVT) has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 2 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.*

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Augmented Dickey-Fuller test statistic -2.565233 0.2973

Test critical values: 1% level -4.211868

5% level -3.529758

10% level -3.196411

*MacKinnon (1996) one-sided p-values.

Unit Root Test: Phillip Perron (PP)Test

At Level

LOG_INVT @ Intercept

Null Hypothesis: LOG_INVT has a unit root

Exogenous: Constant

Bandwidth: 4 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -1.975422 0.2961

Test critical values: 1% level -3.596616

5% level -2.933158

10% level -2.604867

*MacKinnon (1996) one-sided p-values.

LOG_INVT @ Trend

Null Hypothesis: LOG_INVT has a unit root

Exogenous: Constant, Linear Trend

Bandwidth: 2 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -0.712931 0.9654

Test critical values: 1% level -4.192337

5% level -3.520787

10% level -3.191277

*MacKinnon (1996) one-sided p-values.

At First Difference

D(LOG_INVT) @ Intercept

Null Hypothesis: D(LOG_INVT) has a unit root

Exogenous: Constant

Bandwidth: 3 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -4.803956 0.0003

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

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*MacKinnon (1996) one-sided p-values.

D(LOG_INVT) @ Trend

Null Hypothesis: D(LOG_INVT) has a unit root

Exogenous: Constant, Linear Trend

Bandwidth: 0 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -5.462225 0.0003

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

*MacKinnon (1996) one-sided p-values.

Unit Root Test: Augmented Dickey Fuller (ADF) Test

At Level

Market Capitalization @ Intercept

Null Hypothesis: LOG_MKCP has a unit root

Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic 1.547435 0.9992

Test critical values: 1% level -3.596616

5% level -2.933158

10% level -2.604867

*MacKinnon (1996) one-sided p-values.

Market Capitalization @ Trend

Null Hypothesis: LOG_MKCP has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -1.816263 0.6790

Test critical values: 1% level -4.192337

5% level -3.520787

10% level -3.191277

*MacKinnon (1996) one-sided p-values.

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At First Difference

Market Capitalization @ Intercept

Null Hypothesis: D(LOG_MKCP) has a unit root

Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -4.625669 0.0006

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

*MacKinnon (1996) one-sided p-values.

Market Capitalization @ Trend

Null Hypothesis: D(LOG_MKCP) has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -4.990688 0.0012

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

*MacKinnon (1996) one-sided p-values.

Unit Root Test: Phillip Perron (PP) Test

At Level

Market Capitalization @ Intercept

Null Hypothesis: LOG_MKCP has a unit root

Exogenous: Constant

Bandwidth: 1 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic 1.335216 0.9984

Test critical values: 1% level -3.596616

5% level -2.933158

10% level -2.604867

*MacKinnon (1996) one-sided p-values.

Market Capitalization @ Trend

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Null Hypothesis: LOG_MKCP has a unit root

Exogenous: Constant, Linear Trend

Bandwidth: 0 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -1.816263 0.6790

Test critical values: 1% level -4.192337

5% level -3.520787

10% level -3.191277

*MacKinnon (1996) one-sided p-values.

At First Difference

Market Capitalization @ Intercept

Null Hypothesis: D(LOG_MKCP) has a unit root

Exogenous: Constant

Bandwidth: 1 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -4.641867 0.0005

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

*MacKinnon (1996) one-sided p-values.

Market Capitalization @ Trend

Null Hypothesis: D(LOG_MKCP) has a unit root

Exogenous: Constant, Linear Trend

Bandwidth: 1 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -5.013509 0.0011

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

*MacKinnon (1996) one-sided p-values.

Unit Root Test: Augmented Dickey Fuller (ADF) Test

At Level

Public Expenditure @ Intercept

Null Hypothesis: LOG_PUBEXP has a unit root

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Exogenous: Constant

Lag Length: 1 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -0.626670 0.8534

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

*MacKinnon (1996) one-sided p-values.

Public Expenditure @ Trend

Null Hypothesis: LOG_PUBEXP has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 1 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -2.301933 0.4235

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

*MacKinnon (1996) one-sided p-values.

At First Difference

Public Expenditure @ Intercept

Null Hypothesis: D(LOG_PUBEXP) has a unit root

Exogenous: Constant

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -4.353849 0.0013

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

*MacKinnon (1996) one-sided p-values.

Public Expenditure @ Trend

Null Hypothesis: D(LOG_PUBEXP) has a unit root

Exogenous: Constant, Linear Trend

Lag Length: 0 (Automatic - based on SIC, maxlag=9) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -4.297590 0.0078

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

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*MacKinnon (1996) one-sided p-values.

Unit Root Test: Phillip Perron (PP) Test

At Level

Public Expenditure @ Intercept

Null Hypothesis: LOG_PUBEXP has a unit root

Exogenous: Constant

Bandwidth: 1 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -1.029646 0.7340

Test critical values: 1% level -3.596616

5% level -2.933158

10% level -2.604867

*MacKinnon (1996) one-sided p-values.

Public Expenditure @ Trend

Null Hypothesis: LOG_PUBEXP has a unit root

Exogenous: Constant, Linear Trend

Bandwidth: 2 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -2.092437 0.5349

Test critical values: 1% level -4.192337

5% level -3.520787

10% level -3.191277

*MacKinnon (1996) one-sided p-values.

At First Difference

Public Expenditure @ Intercept

Null Hypothesis: D(LOG_PUBEXP) has a unit root

Exogenous: Constant

Bandwidth: 5 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -4.174763 0.0021

Test critical values: 1% level -3.600987

5% level -2.935001

10% level -2.605836

*MacKinnon (1996) one-sided p-values.

Public Expenditure @ Trend

Null Hypothesis: D(LOG_PUBEXP) has a unit root

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Vector Autoregression Estimates

Date: 06/11/15 Time: 16:14

Sample (adjusted): 1972 2012

Included observations: 41 after adjustments

Standard errors in ( ) & t-statistics in [ ] INVT IR MKCP PUBEXP TROP INVT(-1) 0.931885 -1.687193 -0.069354 0.224175 0.996317

(0.19010) (2.30490) (0.20278) (0.20362) (1.49929)

[ 4.90221] [-0.73200] [-0.34202] [ 1.10096] [ 0.66453]

INVT(-2) -0.045668 -1.261092 0.049462 -0.230645 0.094564

(0.19807) (2.40165) (0.21129) (0.21216) (1.56222)

[-0.23056] [-0.52509] [ 0.23410] [-1.08711] [ 0.06053]

IR(-1) 0.019280 0.561908 -0.008945 0.005472 -0.080811

(0.01454) (0.17636) (0.01552) (0.01558) (0.11472)

[ 1.32558] [ 3.18623] [-0.57655] [ 0.35124] [-0.70445]

IR(-2) -0.015957 0.120510 0.043271 -0.000159 0.089682

(0.01452) (0.17609) (0.01549) (0.01556) (0.11454)

[-1.09877] [ 0.68436] [ 2.79312] [-0.01019] [ 0.78295]

MKCP(-1) 0.016063 -2.274995 1.090617 0.053654 3.244828

(0.17703) (2.14654) (0.18885) (0.18963) (1.39627)

[ 0.09073] [-1.05984] [ 5.77519] [ 0.28294] [ 2.32392]

MKCP(-2) 0.087960 1.937221 -0.251942 0.111769 -2.764423

(0.19281) (2.33784) (0.20568) (0.20653) (1.52071)

[ 0.45619] [ 0.82864] [-1.22495] [ 0.54118] [-1.81784]

PUBEXP(-1) -0.059693 3.347299 -0.003423 1.132858 -1.389933

(0.16641) (2.01778) (0.17752) (0.17825) (1.31252)

[-0.35870] [ 1.65890] [-0.01928] [ 6.35534] [-1.05898]

PUBEXP(-2) -0.063648 -3.560055 0.049364 -0.296626 1.831314

(0.15156) (1.83772) (0.16168) (0.16235) (1.19540)

[-0.41994] [-1.93721] [ 0.30532] [-1.82712] [ 1.53197]

TROP(-1) -0.006313 0.132256 -0.014544 -0.009977 0.382184

(0.02420) (0.29348) (0.02582) (0.02593) (0.19090)

[-0.26081] [ 0.45064] [-0.56327] [-0.38480] [ 2.00197]

TROP(-2) 0.018065 0.070013 0.052253 -0.003804 0.419052

(0.03215) (0.38978) (0.03429) (0.03443) (0.25355)

[ 0.56196] [ 0.17962] [ 1.52377] [-0.11049] [ 1.65276]

C 3.618867 103.4342 2.943959 0.264197 -52.83010

(3.36208) (40.7652) (3.58639) (3.60125) (26.5169)

[ 1.07638] [ 2.53731] [ 0.82087] [ 0.07336] [-1.99232] R-squared 0.948793 0.872172 0.995242 0.993839 0.969662

Adj. R-squared 0.931723 0.829563 0.993656 0.991786 0.959549

Sum sq. Resids 1.481920 217.8651 1.686252 1.700257 92.18329

S.E. equation 0.222255 2.694841 0.237083 0.238066 1.752934

F-statistic 55.58519 20.46907 627.5401 483.9482 95.88555

Log likelihood 9.888307 -92.41771 7.240331 7.070765 -74.78572

Akaike AIC 0.054229 5.044766 0.183398 0.191670 4.184669

Schwarz SC 0.513968 5.504505 0.643137 0.651409 4.644408

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Exogenous: Constant, Linear Trend

Mean dependent 29.21016 15.50678 25.13465 24.75202 6.568281

S.D. dependent 0.850581 6.527564 2.976644 2.626686 8.715692 Determinant resid covariance (dof adj.) 0.002297

Determinant resid covariance 0.000482

Log likelihood -134.3013

Akaike information criterion 9.234212

Schwarz criterion 11.53291

Bandwidth: 5 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Prob.* Phillips-Perron test statistic -4.110891 0.0125

Test critical values: 1% level -4.198503

5% level -3.523623

10% level -3.192902

*MacKinnon (1996) one-sided p-values.

APPENDIX C

ERROR CORRECTION MODEL

Dependent Variable: D(INVT)

Method: Least Squares

Date: 06/10/15 Time: 17:40

Sample (adjusted): 1974 2012

Included observations: 39 after adjustments Variable Coefficient Std. Error t-Statistic Prob. D(PUBEXP) 0.126523 0.090359 1.400235 0.1742

D(INVT(-1)) 0.549405 0.161942 3.392606 0.0024

D(IR(-1)) 0.016917 0.008141 2.078009 0.0486

D(MKCP(-1)) -0.099170 0.105605 -0.939063 0.3571

D(INVT(-2)) -0.460641 0.149850 -3.074008 0.0052

D(MKCP(-2)) 0.300151 0.121245 2.475573 0.0208

D(PUBEXP(-2)) 0.240345 0.111446 2.156594 0.0413

D(TROP(-2)) 0.030419 0.016465 1.847468 0.0770

D(INVT(-3)) 0.625582 0.141274 4.428160 0.0002

D(IR(-3)) 0.027970 0.009411 2.972156 0.0066

D(MKCP(-3)) -0.125134 0.128748 -0.971930 0.3408

D(TROP(-3)) 0.059035 0.021257 2.777255 0.0105

ECM(-1) -0.204457 0.078361 -2.609176 0.0154

PERIOD_DUMMY -0.073670 0.101637 -0.724837 0.4756

C -0.116900 0.075790 -1.542420 0.1361 R-squared 0.806135 Mean dependent var -0.033239

Adjusted R-squared 0.693047 S.D. dependent var 0.243446

S.E. of regression 0.134877 Akaike info criterion -0.885179

Sum squared resid 0.436606 Schwarz criterion -0.245347

Log likelihood 32.26098 Hannan-Quinn criter. -0.655613

F-statistic 7.128395 Durbin-Watson stat 2.016659

Prob(F-statistic) 0.000016

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APPENDIX D

Variance Decomposition

Variance Decomposition of INVT: Period S.E. INVT IR MKCP PUBEXP TROP

1 0.222255 100.0000 0.000000 0.000000 0.000000 0.000000 (0.00000) (0.00000) (0.00000) (0.00000) (0.00000)

2 0.316437 97.22985 2.443667 0.018645 0.205900 0.101933 (6.14111) (5.26869) (1.94219) (1.52424) (1.81610)

3 0.364583 96.38232 2.556814 0.099581 0.574585 0.386696 (8.57027) (5.72052) (3.18353) (3.66588) (3.23944)

4 0.401555 93.50485 2.182808 0.886679 2.553589 0.872073 (11.3203) (5.77538) (4.38422) (6.77492) (5.52589)

5 0.433265 88.40230 1.876294 2.243202 5.715594 1.762608 (13.5646) (6.06436) (5.20228) (9.50031) (7.98525)

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of INVT to INVT

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of INVT to IR

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of INVT to MKCP

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of INVT to PUBEXP

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of INVT to TROP

-4

-2

0

2

4

2 4 6 8 10

Response of IR to INVT

-4

-2

0

2

4

2 4 6 8 10

Response of IR to IR

-4

-2

0

2

4

2 4 6 8 10

Response of IR to MKCP

-4

-2

0

2

4

2 4 6 8 10

Response of IR to PUBEXP

-4

-2

0

2

4

2 4 6 8 10

Response of IR to TROP

- .4

.0

.4

.8

2 4 6 8 10

Response of MKCP to INVT

- .4

.0

.4

.8

2 4 6 8 10

Response of MKCP to IR

- .4

.0

.4

.8

2 4 6 8 10

Response of MKCP to MKCP

- .4

.0

.4

.8

2 4 6 8 10

Response of MKCP to PUBEXP

- .4

.0

.4

.8

2 4 6 8 10

Response of MKCP to TROP

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of PUBEXP to INVT

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of PUBEXP to IR

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of PUBEXP to MKCP

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of PUBEXP to PUBEXP

- .4

-.2

.0

.2

.4

.6

2 4 6 8 10

Response of PUBEXP to TROP

-2

-1

0

1

2

3

4

2 4 6 8 10

Response of TROP to INVT

-2

-1

0

1

2

3

4

2 4 6 8 10

Response of TROP to IR

-2

-1

0

1

2

3

4

2 4 6 8 10

Response of TROP to MKCP

-2

-1

0

1

2

3

4

2 4 6 8 10

Response of TROP to PUBEXP

-2

-1

0

1

2

3

4

2 4 6 8 10

Response of TROP to TROP

Response to Cholesky One S.D. Innovations ± 2 S.E.

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6 0.462854 82.43824 1.647531 3.780517 8.802206 3.331507 (15.4334) (6.68289) (5.85700) (11.3379) (10.3361)

7 0.490450 76.78700 1.566919 5.192035 10.83613 5.617923 (16.8201) (7.12780) (6.46057) (12.3430) (12.2234)

8 0.516694 71.64450 1.764034 6.380657 11.66333 8.547475 (17.7471) (7.50750) (7.02393) (12.6499) (13.5932)

9 0.542382 66.93084 2.231632 7.386768 11.61964 11.83112 (18.3605) (7.75975) (7.49538) (12.5945) (14.6990)

10 0.567863 62.59629 2.839074 8.295521 11.11120 15.15791 (18.7693) (8.05320) (7.94182) (12.4280) (15.5903)

Variance Decomposition of IR: Period S.E. INVT IR MKCP PUBEXP TROP

1 2.694841 2.247212 97.75279 0.000000 0.000000 0.000000 (4.59079) (4.59079) (0.00000) (0.00000) (0.00000)

2 3.269561 2.925026 90.74103 0.343339 5.571510 0.419092 (4.90275) (8.62288) (3.22969) (5.65347) (2.72678)

3 3.593631 5.412227 86.65959 0.285759 6.460262 1.182165 (7.14904) (9.96320) (3.58343) (6.61179) (3.68006)

4 3.747968 10.24925 81.95981 0.324252 6.253599 1.213088 (9.67896) (11.6220) (3.82243) (7.01270) (4.12205)

5 3.898316 16.42787 76.19197 0.381241 5.793406 1.205510 (11.9337) (12.9675) (3.88343) (7.01633) (5.31568)

6 4.038571 21.98740 71.09134 0.379118 5.402179 1.139969 (13.3278) (13.9998) (4.01665) (6.99162) (6.83668)

7 4.163908 26.43151 66.95302 0.364563 5.177219 1.073694 (14.3238) (14.6021) (4.25635) (6.94800) (8.00128)

8 4.274438 29.59986 63.62667 0.453435 5.292383 1.027660 (14.8650) (15.0238) (4.46475) (6.84006) (8.78241)

9 4.375536 31.68558 60.78774 0.697718 5.775669 1.053293 (15.1650) (15.2619) (4.71093) (6.75887) (9.41982)

10 4.469760 32.97117 58.26962 1.073017 6.448865 1.237328 (15.2359) (15.4114) (5.03372) (6.88330) (9.98708)

Variance Decomposition of MKCP: Period S.E. INVT IR MKCP PUBEXP TROP

1 0.237083 9.677499 0.136251 90.18625 0.000000 0.000000 (9.08047) (3.93267) (9.82620) (0.00000) (0.00000)

2 0.344501 8.420559 1.020106 90.09547 0.007387 0.456473 (9.31146) (4.89754) (10.7313) (1.88597) (2.11597)

3 0.422261 6.769272 3.341337 88.18734 0.094848 1.607206 (9.38502) (6.45149) (11.2789) (3.57179) (2.70159)

4 0.500810 5.290066 9.209725 80.84039 0.832718 3.827098 (9.12499) (9.96407) (13.0331) (4.49711) (5.09834)

5 0.584520 3.926685 15.31539 71.64695 2.161507 6.949471 (8.44245) (12.9275) (15.2453) (5.12781) (7.46156)

6 0.667887 3.028130 19.54645 64.19354 3.425478 9.806394 (8.00721) (14.7773) (16.7826) (5.60689) (9.12141)

7 0.747264 2.608560 21.92386 58.85056 4.408364 12.20865 (7.98913) (15.7997) (17.6702) (5.97925) (10.4064)

8 0.822065 2.567983 23.10789 55.03103 5.141838 14.15126 (8.60198) (16.5442) (18.0929) (6.34468) (11.4935)

9 0.892818 2.775676 23.64325 52.14333 5.753838 15.68391 (9.57645) (17.1918) (18.2315) (6.71629) (12.4565)

10 0.960237 3.112395 23.87171 49.79797 6.353085 16.86484 (10.6443) (17.7023) (18.2162) (7.11054) (13.2884)

Variance Decomposition of PUBEXP: Period S.E. INVT IR MKCP PUBEXP TROP

1 0.238066 0.039138 1.390176 9.560830 89.00986 0.000000 (3.04281) (4.93222) (7.90266) (10.1664) (0.00000)

2 0.366176 2.257222 2.149995 10.06490 85.33776 0.190129 (4.95131) (6.65055) (9.18726) (12.2523) (2.05872)

3 0.452427 3.861929 3.344183 12.01060 80.13844 0.644843 (7.36434) (8.84694) (10.9205) (14.0921) (3.86873)

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4 0.510286 4.222772 4.060143 15.35319 75.40907 0.954824 (8.93637) (10.7199) (12.4949) (15.2504) (5.75265)

5 0.551600 3.987607 4.697837 19.77318 70.46948 1.071892 (10.0237) (12.0892) (13.9783) (16.1890) (7.46271)

6 0.585446 3.558833 5.518499 24.41971 65.49614 1.006823 (10.4245) (13.0924) (14.9707) (16.8585) (9.03607)

7 0.617613 3.273155 6.757326 28.46506 60.59023 0.914232 (10.3964) (13.9400) (15.5055) (17.2459) (10.2738)

8 0.651277 3.311380 8.465177 31.38560 55.84102 0.996828 (10.1341) (14.7082) (15.7426) (17.4004) (11.2923)

9 0.687713 3.713399 10.47421 33.06209 51.39428 1.356029 (9.83238) (15.3247) (15.7804) (17.4003) (12.0516)

10 0.726709 4.428921 12.48856 33.69891 47.43134 1.952269 (9.68990) (15.8131) (15.7004) (17.3168) (12.5588)

Variance Decomposition of TROP: Period S.E. INVT IR MKCP PUBEXP TROP

1 1.752934 5.647738 0.006278 10.25286 0.739384 83.35374 (7.38990) (3.45202) (8.75361) (2.62970) (9.71100)

2 2.091600 5.701093 1.763536 23.43686 2.000754 67.09776 (7.23920) (5.95149) (10.9060) (3.62617) (11.3103)

3 2.369224 4.944055 1.402389 27.64121 1.624886 64.38746 (7.34784) (5.84948) (11.4612) (4.29378) (12.2443)

4 2.645371 5.767450 2.113143 29.47929 1.390037 61.25008 (8.15431) (6.12315) (11.6171) (4.89144) (12.4661)

5 2.930909 6.784639 3.836574 29.68619 1.782961 57.90964 (8.88922) (6.97964) (11.9842) (5.22821) (12.9540)

6 3.225805 7.565673 5.791490 29.58528 2.391246 54.66632 (9.78039) (8.03188) (12.2851) (5.61598) (13.6347)

7 3.509771 7.982370 7.295428 29.98165 2.827005 51.91354 (10.3790) (9.32416) (12.7149) (5.97081) (14.2326)

8 3.781997 8.017775 8.374371 30.87311 3.012399 49.72234 (10.9280) (10.3826) (13.1685) (6.27178) (14.8803)

9 4.047784 7.771567 9.210205 32.03453 3.031716 47.95198 (11.1850) (11.3996) (13.5646) (6.57787) (15.3719)

10 4.313535 7.339414 9.969342 33.20320 2.987981 46.50006 (11.3643) (12.2225) (13.8461) (6.90504) (15.7942)

Cholesky Ordering: INVT IR MKCP PUBEXP TROP Standard Errors: Monte Carlo (100 repetitions)

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REFERENCES

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Finance and Accounting. ISSN 2222. 2 (3) 71-82

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