* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download ec4 - Caritas University
Survey
Document related concepts
Nouriel Roubini wikipedia , lookup
Foreign-exchange reserves wikipedia , lookup
Real bills doctrine wikipedia , lookup
Global financial system wikipedia , lookup
Fiscal multiplier wikipedia , lookup
Long Depression wikipedia , lookup
Inflation targeting wikipedia , lookup
Business cycle wikipedia , lookup
Fear of floating wikipedia , lookup
Modern Monetary Theory wikipedia , lookup
Quantitative easing wikipedia , lookup
Helicopter money wikipedia , lookup
Non-monetary economy wikipedia , lookup
Interest rate wikipedia , lookup
Money supply wikipedia , lookup
Transcript
AN ECONOMETRIC ANAYLSIS OF THE EFFECTS OF MONETARY POLICY ON NIGERIAN ECONOMY BY MBAMALU KINGSLEY KENECHUKWU EC/2006/238 DEPARTMENT OF ECONOMICS FACULTY OF SOCIAL SCIENCES CARITAS UNIVERSITY AMORJI NIKE ENUGU AUGUST 2010 TITTLE PAGE AN ECONOMETRIC ANALYSIS OF THE EFFECTS OF MONETARY POLICY IN NIGERIAN ECONOMY A PROJECT SUBMITTED IN PARTIAL FULLFILLMENT OF THE REQUIREMENT FOR THE AWARD OF BACHELOR OF SCIENCE (B.SC) DEGREE IN ECONOMICS BY MBAMALU KINGSLEY KENECHUKWU EC/2006/238 DEPARTMENT OF ECONOMICS FACULTY OF SOCIAL SCIENCES CARITAS UNIVERSITY AMORJI NIKE ENUGU AUGUST 2010 APPROVAL PAGE This is to certify that this research work was carried out by KinsleyMadumalu Kenechukwu with the registration number EC/2008/238 on the effects of monetary policy on Nigerian Economy and has been supervised and found worthy of acceptance in partial fulfillment of the requirement for the award of Bachelor of Science (B.Sc) degree in Economics department caritas University Amorji Nike Enugu. ……………...... Dr. F.O. Asogwa ............................ Date Supervisor …….................. Barr. P.C. Onwudinjo HOD Economics Department ….…………......... Date ………………….. Prof. Umeh Dean of Faculty …………………… Date ………………… External Examiner ……………………… Date DEDICATION This work is dedicated to the sacred heart of Jesus ever merciful and unbeatable for super abundant prosperity, protection and provision on the pursuit of my programme, also to my loving parents, relations, friends and well-wishers. ACKNOWLEDGEMENT I hereby pronounce my gratitude to all who on their own effort contributed to the success of this work. Indeed I lack words to appreciate my supervisor Dr. Asogwa who deductively gave me an appreciable supervision without grudges. Mr Ojike’s contribution towards this work is ever significant and appreciated. My propound gratitude goes to my parents Mr and Mrs Moses Mbamalu for their immeasurable assistance both financially and otherwise. To my sisters I say thank you. I will not fail to thank friends like Elizabeth Nwando Mokwe for contributing to this research work. To my well wishers i say thank you all. Mbamalu Kingsley Kenechukwu Economics Department ABSTRACT This study aimed at analyzing through econometric methodology the effects of monetary policy in Nigeria economy. To meet the above objective, output growth was chosen as the dependent variable while real exchange rate, real interest rate and inflation was chosen as the independent variable. The ordinary least square was used in the regression estimation. From the empirical result, we realized that the entire explanatory variables are insignificant in the t-test, but in f-test we rejected the null hypothesis and conclude that the slope coefficient are not simultaneously equal to zero. We realizes from the battery test that there is a co integration between the explanatory band the dependent variables since its level of stationarity are the same. The policy implication of the result is that if monetary and banking policies are effectively applied, it will be consistent with determining the level of output growth in the economy CHAPTER ONE 1.0 INTRODUCTION One of the ways taken by all economy to make the banking sector effective is the use of the monetary policy introduced by the federal government and carried out by the apex bank of the country. Apparently, the existence of an effective banking industry is vital to every economy and it encourages economic growth and development via its role in financial interdiction of funds supplies to deficit economic units .This stimulates international trade, investment economic growth as well employment growth as well as employment. Monetary policy is one of the steps taken by every economy to make the banking sector effective. Monetary and banking policies are the sole responsibilities of monetary authority, which comprises of The CBN for the initiation, implementation and articulation of monetary system. The CBN carried out these duties on behalf of the federal government according to CBN decree 21 of 1991 and the banks and other financial institution BOFIA A4, of 1991 as amended. The banks proposal on monetary policy is subjective to the federal government. The policies to be pursued is usually out in form of ‘’Audience’’ to all banks and other financial institutions. The guideline are general in operation within a fiscal year but could be amended on the course of the year. The CBN is equally empowered to direct the activities of the financial institutions in other to carry out certain duties in pursuit of approved monetary policy of which penalties are prescribed for non-compliance with specific provision of the guidelines. 1.1 BACKGROUND OF THE STUDY Monetary policy affects financial and economic activities over the year. In other to appreciate the effects of monetary policy on the banking industry, it would be wise to move a review of changing views of monetary influence. Usually when the quantity of money changes in relation to financial activities as viewed by FISHER (1932). Fisher, take other neoclassical writer who held the view that in short run, money influences real cash balances. According to him, when the money stock increases, example; An increase commodity prices since output and velocity were fixes initially. He assumed that a rise in commodity prices would exceed the increase in interest rate which was regarded as a component of a firms operating cost. In the whole analysis, rise in commodity prices will lead to an increase in a firms profit, demand, money stock and deposit which will eventually lead to a further rise in investment and commodity price. The excess reserved for lending will decline with interest rate, which was stocky earlier. In the analysis of long-term transmission of monetary influence, Fisher replaced ‘’Interest-Investment’’ channel with ‘’Real Cash Balance’’. He noted that when wealth rises due to rise in money stock, people tend to reduce their cash balances by purchasing goods and service. Since the velocity (v) and output (y) in Fishers equation of exchange (MVPT) is fixed, the risen money stock (M) cannot lead to increased holding of goods and services but will lead to decline in prices level (P). Keynes (1936) accepted the change in money supply relative has both substitution and effect and considered investment to be quite responsive to interest rates. Keynes recommended price induce wealth effects, (i.e. change in wealth due to change in yields). There are ranging accounts by his interpreters about the extent he integrate them in his general theory. Hence subsequent write to Keynes (i.e. Keynesian or post Keynesian regards the cost of capital (interest rate) as the main process by which changes in money stock influence the economy. Thus the change in volume of money alters the rate of interest. Usually approximated by the long-term government bound rate, which affects investment and consumption. Thus the link between wealth of private sector and real sectors and consumption was analyzed by Piguo (1974) and Patikin (1951) in form of ‘’real cash balance effect’’ According to them changes in quantities of money would affect aggregate demand even if they did not alter interest rate. On the other hand, credit rationing channel of monetary influence explained how financial interdiction, would be controlled by the market forces so as to ration the supply of credit by non-price mechanism. Thus an expansionary monetary policy would raise the force of equity (i.e. reduce the yield on equities). The margin between the market evaluation and cost of reproducing the existing capital goods will stimulate new investment over those goods. The non-monetarist argued that monetary policy is as effective as fiscal policy as to determine total spending in the economy in spite of their differences. It holds the following views: 1. Movement in quantity of money is the most reliable measure of monetary value. 2. Monetary authority can detect the movement in the stock of money over time and business cycle. 3. Changes in stock of money are the primary determination of total spending as emphasized on owen’s economic stabilization program. 4. Monetary impulse are transmitted to real economy through an active price process or profit adjustment process which affect many financial and real antes. 1.2 STATEMENT OF PROBLEM Despite the establishment of Central Bank of Nigeria (CBN) in 1958, banking industry remained both poor, inadequate in terms of number, quality and variety of service rendered. The establishment of CBN paved way for adoption of monetary management by the banking industry. Just incase any analyst is waiting in the wings to strike CBN for its poor monetary policy performance. Ogwuma (1994:362) offers a defense which says “A less than objective appraisal of the CBN role in the Nigerian economy could interpret the adverse macro-economic trend as evidence of failure on the part of CBN. The key constraint are as follows: 1.3 AIMS AND OBJECTIVES OF THE STUDY The following issues are the main aims and objectives of carrying out this study; a. To identify the basic effects of monetary policy in order to Achieve a sound financial system. b. To examine CBN monetary policy strategies c. To identify the best policy measure for economic stability. 1.4 SIGNIFICANT OF THE STUDY The important of this study cannot be over emphasizes. It will serve as a useful material to the monetary authority, bank management and staff, customers, depositors, students and indeed the entire economy. Never the less, it will add to the volume of studies on the regards. The report shall be useful in ensuring both monetary stability and a sound, safe and profitable banking environment which will facilitate the pace for the economic growth and development in Nigeria. 1.4 HYPOTHESIS / RESEARCH QUESTION The following hypothesis has been formulated as a guide to the conduct of the study. They should be tested based on the result obtained from the regression coordinated. The hypotheses are; b. Ho: Variation in monetary policy does not significantly affect output growth. c. H1: Variation in monetary policy significantly affect output growth i.e. Ho= Null Hypothesis Hi= Alternative Hypothesis 1.5 SCOPE OF THE STUDY Although there exist many factors affecting the operation of or the performance of the banking industry, this study focuses on the impacts of monetary policy on the performance of the banking industry. 1.6 LIMITATION OF THE STUDY It is quite believed that the study of nature needs sufficient time, finance and materials. The inadequacy of those factors poses enough limitations to this study. The limitations in general include; a. Financial and monetary constraint b. Material constraint c. Time constraint d. Physical and Geographical constraint 1.8 DEFINITION OF TERMS 1.8.1 BANKING INDUSTRY These refers to the total number of banks and other financial institution who performs banking function such as acceptance of deposits,. Issuing of credits/loan and keeping of valuables. Such banks include; Merchant Banks and Development Banks etc. The banking industry also consists of the monetary authorities such as Central Bank of Nigeria and other federal bodies whose duty includes the regulation of the economy. 1.8.2 INSURANCE BANK This implies those banks whose risk are insured with Nigeria Deposit Insurance Commission ( NDIC) 1.8.3 BANK DISTRESS This is the period in the banking industry when they cannot be able to meet up its target such as; objectives, dividends, staff remuneration in the economy as a whole. In this period, a bank is said to be in the period of solvency, i.e. a period when its debt ratio are high. CHAPTER TWO 2.0 LITERATURE REVIEW 2.1 CONCEPTUAL FRAMEWORK The concept and definition of monetary policy in the previous year has no universal acceptability but however, the term monetary policy according to CBN release on monetary policy concept (2006) was defined as “Any policy measure designed by the Federal Government through the CBN to control cost availability and supply of credit. It also referred to as the regulation of monetary supply and interest rate by the CBN in order to control inflation and to stabilize the currency flow in an economy. However, in the CBN Briefs (Series No 97/03 June 1997).Monetary policy was defined as follows; The combination of measures designed to regulate the value, supply and cost of money on an economy in consonance with the expected levels of the economic activities These imply that the excess supply of money would result in excess demand for goods and services, which would in turn cause a rise in price and determination of balance of payment position. Monetary policy is one of the available tools of macroeconomic objectives. The primary goals of macroeconomic policy are price stability, external stability and a satisfactory rate of output growth. 2.2 THEORITICAL LITERATURE The effect of monetary policy is a central issue and has attracted a lot of comments both in and out of the country. The theories of monetary policy became success during 1930’s and 1940’s. It was believed that the well being of monetary policy in stimulating recovery from depression was severely limited than in controlling a boom and inflation. These views emerged from the experience of Keynes in his theory. Keynes general view holds that during depression, the CBN can increase the reserve of commercial banks through a cheap monetary policy. They can do so by buying securities and reducing the interest rate. As a result of these, the ability of extending credit facilities to borrowers increases. But the great depression tells us that in a serious depression when there is pessimism among economic actors, the success of such a policy is practically zero. In this situation economic actors have no incentives to borrow even at a reduced interest rate. In this case, the question of borrowing for long-term capital needs does not arise in a depression when the business activities are already at a low level. The classical view of monetary policy is based on the quantity theory of money. According to this theory, an increase in the quantity of money leads to a proportional increase in price level. The quantity theory of money is usually discussed in terms of ‘’Equation Of Exchange’’ which is given by the expression. P, denotes price level and Y denotes the level of current real GDP. Hence, PY represents current; ’’NORMINAL GDP’’ M denotes the supply of money over which the fed has some control and v denotes the “Velocity Circulation’’ which is the average number of time a naira is spent on final goods and services over the cause of the year. The equation of exchange is an identity which states that the current market value of all final goods and services… nominal GDP must equal the supply of money multiplied by the average number. Monetarist view of monetary policy dates back in 1950’s, a new view of monetary policy called monetarism, has emerged that disputes the Keynesian view that monetary policy is relatively ineffective. Adherent of monetary argue that the demand for money is stable and not sensible to change the interest rates. 2.2.1 TYPES OF MONETARY POLICY There are basically two kinds of monetary policy, they are: a. EXPANSIONARY MONETARY POLICY An expansionary monetary policy is used to overcome depression, recession and deflationary gap. When there is fall in consumer goods and services, and in business investment goods, a deflationary gap emerges. The Central Banks starts an expansionary policy that eases the credit market conditions and leads to an upward shift in aggregate demand. For this the CBN purchases the government securities in the open market, lowers the reserve requirements of member banks, lowers the discount rate and encourages consumer and business credit through selective credit measures. b. RESTRICTIVE MONETARY POLICY This is the kind of monetary policy designed to reduce aggregate demand (AD) and inflationary gap. Inflationary pressure takes place as a result of risen consumer demand for goods and services and there is also boom in business investment. The CBN introduces the restrictive policy in order to lower aggregate consumption and investment by increasing the cost availability of bank credit. 2.2.2 AIMS AND OBJECTIVES OF MONETARY POLICY There appear to be a general consensus that the single most important objectives of monetary policy are the pursuit of price stability. These recognition is perhaps derived from the increasing rate at which many central banks around the world are been given the exclusive power to control inflation and stabilize domestic prices. The perspective which recognizes a focus on inflation as the right approach to macroeconomic stability receives a strong support from the analytical research summarized in Fisher (1996) The study concludes that the fundamental task of the currency and the following; a. Achievement of domestic price and exchange rate stability b. To control inflation c. Maintenance of healthy balance of payment position d. Promotion of rapid and sustainable rate of economic growth and development e. f. Maintenance of macroeconomic stability Development of a sound financial system g. To stabilize the naira exchange rate h. To maintain a high level of employment 2.2.3 INSTRUMENTS OF MONETARY POLICY The policy instruments are of two kinds, they are; i. Indirect Quantitative or General ii. Direct Quantitative or Selective These affect the levels of aggregate demand and through the supply of money cost and availability of credit. The first category includes the bank rate variations, open market operation and changing reserve requirement. They are meant to regulate the overall level of credit in the economy through commercial banks. The selective credit control aims at controlling specific kinds of credit. They are discussed under the following; a. BANK RATE POLICY: The bank rate is the minimum lending rate of the Central Bank at which it rediscounts first class bill of exchange and government securities held by the commercial bank. When they notice an inflationary pressure in the economy, it raises the bank rate. In this period, borrowing from the CBN becomes difficult and the commercial banks borrow less from it. Also the commercial banks borrowers such as the individual and industries borrow less from it due to an increase in its lending rate. On the contrary when prices are depressed, the central bank lowers their bank rate making it cheaper to borrow from them. The commercial banks also lower its lending rate making it easy for businessmen to borrow money. In this case, investment, output, employment, income and demand starts rising. b. CHANGES IN RESERVE RATIO: This system was first adopted in USA as suggestion by the Keynes ‘’Treatise on Money’’ as a monetary devise. In every organized financial economy, certain percentage of its total deposit is kept in form of reserve fund its vaults and also a certain percentage with the central bank. When prices are rising, the central bank raises the reserve ratio. Bank is required by law to keep more to the central bank. They lend less when their reserve is reduced and they lend less. The volume of investment, output and employment are adversely affected. On the contrary when the reserve ratio is lowered, the commercial banks reserves rises, thereby lending more and the economic activities are favored. C. OPEN MARKET OPERATION: This refers to the sell and purchase of securities by the central bank in the money market. When prices are rising and there is a need of controlling them, the central banks sell securities. The reserves of commercial banks are reduced and they are not in a position to lend money to individual and corporations. Further investments discouraged and the rise in price are checked. On the contrary, when recessionary forces starts in an economy, the central bank by securities from business communities and commercial banks, their by increasing their reserve. Investment, output, income and aggregate demand rises. D. CREDIT CONTROLS: Credit control are used to control specific types of credit for particular Purposes. They usually take the form of changing margin to control speculative activities in the economy or in particular sectors in certain commodities and prices will start rising. The central bank raises the margin requirement on them. The result is that the borrowers are given less money is loans against specified securities. 2.2.4 FISCAL POLICY Fiscal policy which is national in scope, is a government policy related to taxation and policy, which is concerned with money supply, are the two most important components of a government overall economic growth. Keynesians considered fiscal policy the steeling wheel for aggregate economy. They said classical economists with their Laissez-Faire policy were trying to drive an economy without any steering wheel. Fiscal policy can be either expansionary, concretionary. It is expansionary or loose when taxation is reduced or public spending is increased with the aim of stimulating total spending in the economy known as aggregate demand. On the other hand, fiscal policy is contraction or tight when taxation is increased or public spending is reduced in order to restrict demand and slow down the economy. In Nigeria, the major fiscal policy instrument includes changes in tax rate (on personal income, company income, petroleum profits, capital gain, import duties as well as mining rents, royalties etc) and government expenditure (recurrent and capital). 2.2.5 DIFFERENCES BETWEEN MONETARY AND FISCAL POLICY Monetary and fiscal policy is both instrument of macroeconomic stability but they have the following difference; a. Monetary policy is typically implemented by a central bank, while fiscal policy decision are set by the national government b. Both monetary and fiscal policy may be used to influence the performance of the economy in the short run c. Monetary policy uses instruments such as open market Operation, Reserve ratio and moral Suasion etc for economic stability while Fiscal policy uses taxation as the instrument of economic stability. d. Fiscal policy decisions undergo stages before a [approval in the house while monetary policy decisions are approved by the decisions of the CBN. 2.3 EMPIRICAL LITERATURE The effects of monetary policy is a central issue in macroeconomics, it has attracted comments from different scholars both in developed and developing countries. Ojo (1999) regards monetary policy during much of the 90’s as generally restrictive, yet money supply (in this case M2) increased persistently and well beyond the established growth rate target. Sanusi (2001) goes further back to a period (1959-1969) when Nigeria’s monetary policy was deliberately expansionary during this period. As the Treasury bill rate was reduced from 5% in 1960 to 3, 5% in 1964, M2 rose at an annual rate of 44% between 1960 1994 and to 84% during 1968-1970. 2.3.1 MONETARY POLICY STRATEGY IN NIGERIA Monetary policy strategy refers to how the central bank carries out monetary policy actions (Mish kin, 2001). A central feature of the difference forms of monetary policy strategy is the choice of the numerical anchor. Thus each of the three basic types of monetary policy strategy uses a different nominal anchor. Monetary targeting involves the use of information conveyed by the monetary aggregate to conduct monetary policy. Monetary targeting occurs in at least two forms, first is the rigid Friedman-type in which the chosen monetary aggregate is kept on a constant growth rate path as the forces of monetary policy. Second is the flexibility variety, which may involve a set of monetary aggregate, each of which is allowed to grow at different rate. According to ‘’Odozi’’ the conduct of monetary policy goes on three inter-related stages, namely: a. Policy Formulation Stage b. Implementation Stage c. Review Stage The frame work of this exercise is usually provided by law as follows; 1. The relationship between the central bank and the federal Government 2. Which arm of the government has the financial authority on the policies initiated by the central bank? CHAPTER THREE 3.1 THE MODEL The information used in this economic phenomenon empirically can be analyze in functional relationship between output growth as the dependent variable while the independent variable such as ;real interest rate, inflation and real exchange rate. Yg = F (RIR, INF, RER)…………………….(1.0) Equation 1.0 shows a functional relationship between output growth and other independent variables such as; interest rate, inflation rate and real exchange rate. 3.2. BATTERY TEST: This involves Augmented Dickey Fuller test and cointegrated test of error correction. Co-integration is an econometric property of time series variables. If two or more series are individual integrated in the time series sense but some linear combination of them has a lower order of integration then the series are first order integrated. If residuals are random walk, we say that the two variables are not cointegrated. Static regression of Xt or Yt, the test for cointegration is a test of null hypothesis that p=1 in the residual and may be tested using Dickey-fuller statics. Regression using the error correction form of the system, followed by a test of the null hypothesis. 3.3 MODEL SPECIFICATION The specification of econometric model is based on economic theory and on any valuable information relating to the phenomenon being studied. In doing this, there are three specific steps involved. i Determination of dependent and independent variables ii Theoretical a prior expectation about the size and signs of parameters of the function and; iii The determination of the mathematical form of model. The model to be adopted will specifically be based on the following functional relationship. Yg = F(INT, INF, RER)……………………(3.0) Equation 3.0 reads that output growth is a function of interest rate, inflation rate and exchange rate. However, to hold firm the influence of random variable, the equation is explicitly transformed in to the following: Yg=Bo+B1INT+B2INF+B3RER+Ui……………………. (3.1) Where; RIR: Real Interest Rate INF: Inflation Rate RER: Exchange Rate BO: parameter Constant Ui :Error Term B1, B2, B3= Parameter Estimates In equation 3.1 output growth is the dependent variable while interest rate, inflation and exchange rate are the independent variable. 3.4 METHOD OF ESTIMATION: We estimate the parameters of the model after obtaining the data. We use the statistical techniques of regression analysis to obtain the parameter estimates. The techniques to be used in analysis are; co-efficient of multiple determinations, F-test, T-test and Durbin-Watson etc. 3.4.1 CO-EFFICIENCE OF MULTIPLE DETERMINATION (R2) The R2 is used to test for the goodness of fit of the model in the economy that is to say that the percentage of total variation in dependent variable explained by the regression plane. The R2 is expressed mathematically as R2= B1∑1Y+B2∑2Y+B3∑3Y 3.4.2 T-TEST The t-test is used to test for the significance or reliability of the estimates regression co-efficient. If the probability at which t-cal is significant in our regression result for any independent variable is less or equal to our chosen level of significant (0.05), we reject null hypothesis (Ho) which states that the independent variable is not singular. This means accepting the alternative hypothesis (Hi) 3.4.3 F-TEST This is a test of the overall significance of the entire regression plane. It will be used to find out whether the joint impact of the explanatory variable actually has a significance influence on the dependent variable. 3.4.4 STANDARD ERROR TEST This is used to test for the presence of auto-correlation that is the serial dependent of successive error term in regression. Auto-correlation usually indicates that an important part of the variation of the dependent variable has not been explained, the problem of auto-correlation are usually detected by Durbin-Watson (DW) statistics. It is mathematically giving as: DW=∑ (et (et-1)2) (et)2 Where: DW= Durbin-Watson ∑= Summation et= present period error et-1= Previous period error 3.4.5 TEST FOR MULTICOLLINEARITY It is used to check for multicollinearity among the explanatory variable the basis for the test being the correlation matrix result using the correlation co-efficiencies between bases of regression. 3.4.6 HETEROSKEDASTICITY It is conducted to ascertain whether the error term Ui, in the model of regression has a common or constant variance while the heteroskedesticity test will be adopted. 3.5 SOURCES OF DATA The sets of data used in this research where the time series data obtained from the annual abstract of statistics of the Nigeria Bureau of Statistics. Secondly, the sources of data involved the empirical exploration of the study which is made from the secondary data obtained from relevant government institutional publication such as: Central Bank of Nigeria Bulletin. CHAPTER FOUR 4.1 BATTERY TEST 4.1.1 UNIT ROOT TEST Variable ADF* 1% 5% 10% Yg 2.4432 -3.4758 -2.8811 -2.5771 Yg(D) -5-4350 -3.4761 -2.8812 -2.5772 RIP -2.4346 -3.4758 -2.8811 -2.5771 RIP (D) -4.6402 -3.4761 -2.8812 -2.5772 RER -1.9357 -3.4758 -2.8811 -2.5771 RER (D) -3.9119 -3.4761 -2.8812 -2.5772 -2.8% -3.4758 -2.8811 -2.5771 -4.1585 -3.4761 -2.8812 -2.5772 INF WF(D) FOR OUTPUT GROWTH (YG) Hence ADF* is less than the critical value at 1%, 5% and 10%, therefore Yg is not stationary but ADF* first difference (YgD) is stationary because it is greater than the critical value at 1%, 5% and 10% at first difference of Yg. i.e ADF* < 1%, 5% and 10% at level form ADF* > 1%, 5% and 10% at first difference. FOR REAL INTEREST RATE (RIR) Since ADF* is less than the critical value at 1%, 5% and 1% therefore ADF* (RIR) is not stationary at level form of but ADF* (RIRD) is stationary because it is greater than the critical value at 1%, 5% and 10% at first difference i.e ADF* < 1%, 5% and 10% at level form ADF* > 1%, 5% and 10% at first difference. FOR REAL EXCHANGE RATE (RER) Since ADF* is less than the critical value at 1%, 5% and 10% therefore (RER) ADF* is not stationary but ADF* (RERD) is stationary because, it is greater than the critical value at 1%, 5% and 10% i.e ADF* < 1%, 5% and 10% at level form ADF* > 1%, 5% and 10% at first difference. FOR INFLATION (INF) Since ADF* is less than the critical value at 1%, 5% and 10% therefore (INF) ADF* is not stationary but in first difference of inflation, the (INF) is stationary because ADF* is greater than the critical value. i.e ADF* < 1%, 5% and 10% at level form ADF* > 1%, 5% and 10% at first difference. IN SUMMARY: Since the co-efficient of dependent variable (Yg) conforms with the explanatory variable (RIP, RER and INF), we assume that there is a co-integration between them. (Dependent and Independent Variable). 4.1.2 JOHAMSON CO-INTEGRATION Because the dependent variable and explanatory variable are of the same level of stationality, by rule thumb, we suspect and assumed that there is a co-integration between the explanatory and dependent variable. For the reason above, the error correction model (ECM-1) lag 1 is added as one of the explanatory variable. 4.2 PRESENTATION OF REGRESSION RESULT Dependent Variable : Dyg Method : Ordinary least square Sample : 3-152 Included Observation Variable : 150 Co-efficient Std Error t-Statistics Prob C - 1.8164 2.4640 -0.737 0.4622 DRIR - 0.94313 0.57882 -1.629 0.1054 DEF - 0.47543 0.55997 -0.849 0.3973 DRER 0.0022846 0.057581 -0.040 0.9684 ECM 0.33128 0.053734 6.165 0.0000 R- Squared = 0.233869 F- Statistics = 6.1924 DW 2.71 = RSS = 127820.7022 for 8 variables and 150 observations. 4.2.1 EVALUATION OF RESULT Evaluation Based on Economic criteria 1. Real Interest Rate (RIR): The coefficient of the variable is -0.94313. This shows that a unit change in real interest rate will bring about a 94% decrease in output growth. 2. Inflation (INF): The Coefficient of the variable is 0.47543. This shows that a unit change in inflation rate will bring about a 47.5% decrease in output growth. 3. Real Exchange Rate (RER): The coefficient of the variable is -0.0022848 which shows that a unit change in real exchange rate will bring about a 0% change in output growth. 4.2.2 EXPECTED AND OBTAINED SIGN OF OUR PARAMETER ESTIMATE From the regression data the obtained result is expected to follow and conform to economic aprior expectations of signs and magnitude. Hence, the table is a summary of the outcome of our parameters. Variable RIR Expected Obtained Conclusion Positive Negative Do not conform INF Positive Negative Do not conform RER Positive Negative Do not conform 4.3 EVALUATION OF STATISTICAL CRITERIA Coefficient of determination R2: The R2 is 0.233869 on approximately 23%. This shows that in the Longrun, the Independent Variables were able to explain the variations in output growth to the time of 23%. Therefore, the regression line is poorly fitted. 4.3.1 TEST OF SIGNIFICANCE OF THE PARAMETER A student t-test is used to determine the significance of the individual parameter estimate in doing this, we compare the calculated t-value in the regression result with the T-tabulated at n-k degree of freedom (df) and at 5% level of significance. The test will be carried out under the following hypothesis: Ho: B = 0 not statistically significant H1: B ≠ 0 statistically significant Where B = coefficient of the parameter Ho = Null hypothesis H1 = Alternative hypothesis Decision Rule: reject Ho if T-calculated > T – tabulated on accept if otherwise. n= 150, k = 8 n- k = 150 – 8 = 142 df, at 5% of significance. Variable T- T-tabulated Decision Conclusion Calculated RIR - 1.629 - 1.960 Accept Ho Not significance INF - 0.849 - 1.960 Accept Ho Not significance RER - 0.040 - 1.960 Accept Ho Not significance The result shows that real interest rate, inflation rate and real exchange rate are statistically insignificant using the t-test. 4.3.2 F-test Statistics This analysis shall be carried out under the following hypothesis: Ho: x1 = x2 : xk = 0 (all slope coefficient are zero) Ho: x1 ≠ x2 ≠ xk ≠ 0 (all slope coefficient are not zero) Decision Rule: Reject Ho if F-calculated is greater than Ftabulated, for the numeration degree of freedom is k-1 = 8 – 1 = 7 For the denomination: Degree of freedom is n-k = 150 – 8 = 142 at 5% - level of significance. F- Calculated F- Tabulated 6.1924 2.01 Decision Reject Ho From the result, we’ll observe that f- calculated exceed our ttabulated that is 6.1924 > 2.01. Thus, we reject the null hypothesis and conclude that all slope coefficients are not simultaneously equal to zero. ECONOMETRIC TEST Test for Autocorrelation The underlying assumption is that the succession values of the random variable (VI) are temporarily independent. The problem is usually dictated with Durblin – Watson (DW) statistics. Decision Rule 5 d* < dc reject Ho, presence of positive autocorrelation of first order. d* > (4-dl) reject Ho presence of negative autocorrelation of first order du < d* <du (4-du) < d* < (4-dl), test is inconclusive. Where dl = Lower limit du = Upper limit d* = durblin – Watson dh = 1.637; 4-dl = 4 – 1.637 = 2.363 du = 1.832 d* = 2.71 2.71 > 2.63 That is d* > (4.dl) reject Ho, presence of negative autocorrelation of first order. CHAPTER FIVE SUMMARY, CONCLUSION AND POLICY RECOMMENDATION 5.1 SUMMARY The empirical result shows that the real interest rate, real exchange rate and inflation are not statistically significant using the t-test which implies that it impacts in determining the rate of economic growth to that monetary policy help in the growth of total domestic output through varying the magnitude of interest rate, real exchange rate and inflation. The explanatory variables from the model is not significant from the t-test. This means that it has minimal impact in determining the output growth. 5.2 CONCLUSION This study has been concerned with finding the effects of monetary and banking policies on the economic growth. It is necessitated by the fact that since the financial liberalization, Nigeria has come to rely heavily on the use of monetary and banking policy for stabilization of the economy. 5.3 POLICY RECOMMENDATION The empirical result revealed that an effective monetary policy is necessary for macro-economic stability for attainment of economic growth and development. The following policy idea is necessary: * Stabilizing the Naira Exchange Rate: Considering the failure of various market oriented measure aimed at stabilizing the naira exchange rate since the introduction of SFEMFEM there is need for another approach as well as modification of the easily manipulated method of foreign exchange allocation. * Need for Effective Monetary Policy in order to take adequate measures instability and in order streamlining economic macroeconomic impediment that jeopardizes growth and development. * Need for restrictive monetary policy to overcome inflationary gap. Restrictive monetary policy is one designed to curtail aggregate demand: The economy experiences inflationary presume due to rising consumer demand for goods and services. * The government and institutions charged with economic development strategies and policy function should evolvement to impact move on GDP by conceptuality on the use of exchange rate, interest rate in order to raise the level of investment. BIBLIOGRAPHY Akatu, O.(1963). Reflection on Macroeconomic: Otta: Papers and Proceedings Press. Anyanwakoro, M. (1999). Theory and Policies of Money and Banking. Uwani Enug:Hosanna Publication. Attamah, N. (1999). Basic Principles of Economics. Coal Camp Enugu: Marydan Publishers. Campbel, (1982). Nigerian Economic Policy and Performance. Oxford: OxfordUniversity Press. Ezeduji, F.O. (1994). Conduct of Monetary Management In Nigeria. Onitsha: Wema Publishers. Friedman, (1963). The Role of Monetary Policy. Binmighan: Wiglass Publishers Inc. Jhinghan, M.C. (1970). Advanced Economic Theory. Mayan Vinan Phase 1 Delhi: Vindu Publication. Julius, A.A. (2004). Facing New Challenges In Akume: Jobies Press. Banking. Keynes, J.M. (1936).The General Theory of Employment Interest and Money. New York: Harcourt Brace Company. Nwagbara, C.P. (2004). An Introduction Approach to Statistics. Ogui Road Enugu: J.F.C and Company Publication. Ogikhonon H. and Dimowo F.A. (1997). The Structure of the Nigerian Economy (1960-1997). Awka: Joanne Educational Publishers Ltd. Pandey, I.M. (1992). Monetary Policy Effects. London: MC Graw Hill Companies Inc. Uchendu O.A. (1996). The Transmission of Monetary Policy in Nigeria. Central Bank of Nigeria Economic and Financial Review, Vol. 34. No 2, p. 608. Udeabah, S.I. (2002). Economic Development and Planning Ogui New Layout Enugu: Lincon Press Nig. JOURNALS Ezeudoji, F.U. (1994). The effects Monetary Policy on the Performance of Banking Industry In Nigeria. CBN Economic and Financial Review. Vol. 32, Pp 3-10. Million, F.C. (1971). A Monetary Theory of Income. Journal of Political Economy. Vol. 2, PP3-8. Odozi, V.A. (1997). The Management of Monetary and Banking Politics. CBN Billion. Vol. 21, PP 2-13. Ojo,M.O. (1999). A review and Appraisal of the Monetary and other financials sector policy measures in the Federal Government budget for 1999.CBN Bullion. Vol.24,pp2-8 Kingsley Mbamalu Pre-Estimation Tests Yg in Level form ADF Test Statistic 2.443255 1% Critical Value* 5% Critical Value 10% Critical Value -3.4758 -2.8811 -2.5771 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(YG) Method: Least Squares Date: 07/02/08 Time: 05:32 Sample(adjusted): 1971:2 2007:4 Included observations: 147 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. YG(-1) D(YG(-1)) D(YG(-2)) D(YG(-3)) D(YG(-4)) C 0.139647 -0.682706 -0.283627 0.107745 -0.209351 -5.799682 0.057156 0.105475 0.120342 0.114792 0.091720 2.445852 2.443255 -6.472677 -2.356831 0.938611 -2.282502 -2.371232 0.0158 0.0000 0.0198 0.3495 0.0240 0.0191 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.438157 0.418233 25.76599 93607.96 -683.1322 2.046108 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -2.078707 33.78100 9.375948 9.498006 21.99196 0.000000 Yg first diff ADF Test Statistic -5.434964 1% Critical Value* 5% Critical Value 10% Critical Value -3.4761 -2.8812 -2.5772 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(YG,2) Method: Least Squares Date: 07/02/08 Time: 05:06 Sample(adjusted): 1971:3 2007:4 Included observations: 146 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. D(YG(-1)) D(YG(-1),2) -1.508504 -0.017261 0.277556 0.249365 -5.434964 -0.069220 0.0000 0.9449 D(YG(-2),2) D(YG(-3),2) D(YG(-4),2) C R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat -0.105450 0.162517 0.028634 -3.144329 0.805909 0.798978 26.36822 97339.63 -681.8369 1.986671 0.217713 0.160931 0.086912 2.225676 -0.484354 1.009855 0.329464 -1.412753 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) 0.6289 0.3143 0.7423 0.1599 -0.246164 58.81102 9.422424 9.545038 116.2626 0.000000 RIR in Level form ADF Test Statistic -2.436351 1% Critical Value* 5% Critical Value 10% Critical Value -3.4758 -2.8811 -2.5771 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(RIR) Method: Least Squares Date: 07/02/08 Time: 06:23 Sample(adjusted): 1971:2 2007:4 Included observations: 147 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. RIR(-1) D(RIR(-1)) D(RIR(-2)) D(RIR(-3)) D(RIR(-4)) C -0.131051 -0.427578 -0.095073 0.117919 0.202999 -0.846172 0.053790 0.090773 0.097613 0.095683 0.083064 0.838656 -2.436351 -4.710395 -0.973984 1.232399 2.443891 -1.008962 0.0161 0.0000 0.3317 0.2199 0.0158 0.3147 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.275264 0.249564 8.666040 10589.14 -522.9546 2.074885 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) 0.146122 10.00378 7.196661 7.318719 10.71073 0.000000 RIR first Diff ADF Test Statistic -4.640216 1% Critical Value* 5% Critical Value 10% Critical Value -3.4761 -2.8812 -2.5772 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(RIR,2) Method: Least Squares Date: 07/02/08 Time: 06:26 Sample(adjusted): 1971:3 2007:4 Included observations: 146 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. D(RIR(-1)) D(RIR(-1),2) D(RIR(-2),2) D(RIR(-3),2) D(RIR(-4),2) C -1.274227 -0.275005 -0.457409 -0.378222 -0.140832 0.145146 0.274605 0.248422 0.207007 0.151740 0.083501 0.726718 -4.640216 -1.107007 -2.209628 -2.492566 -1.686597 0.199728 0.0000 0.2702 0.0288 0.0138 0.0939 0.8420 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.744050 0.734909 8.769329 10766.16 -521.1056 2.014765 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -0.036507 17.03211 7.220625 7.343239 81.39623 0.000000 RER in level form ADF Test Statistic -1.935670 1% Critical Value* 5% Critical Value 10% Critical Value -3.4758 -2.8811 -2.5771 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(RER) Method: Least Squares Date: 07/02/08 Time: 06:15 Sample(adjusted): 1971:2 2007:4 Included observations: 147 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. RER(-1) D(RER(-1)) D(RER(-2)) D(RER(-3)) D(RER(-4)) C -0.059402 -0.454578 -0.083051 0.124708 0.245808 11.18332 0.030688 0.083475 0.092002 0.091881 0.081823 7.124801 -1.935670 -5.445646 -0.902716 1.357269 3.004141 1.569633 0.0549 0.0000 0.3682 0.1769 0.0032 0.1187 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.265850 0.239816 42.34452 252821.2 -756.1594 2.104725 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) -0.713878 48.56663 10.36952 10.49157 10.21177 0.000000 RER first diff ADF Test Statistic -3.911900 1% Critical Value* 5% Critical Value 10% Critical Value -3.4761 -2.8812 -2.5772 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(RER,2) Method: Least Squares Date: 07/02/08 Time: 06:20 Sample(adjusted): 1971:3 2007:4 Included observations: 146 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. D(RER(-1)) D(RER(-1),2) D(RER(-2),2) D(RER(-3),2) D(RER(-4),2) C -1.013373 -0.523197 -0.651157 -0.523952 -0.194341 -0.478337 0.259049 0.237127 0.200730 0.150007 0.083647 3.509024 -3.911900 -2.206397 -3.243941 -3.492853 -2.323342 -0.136316 0.0001 0.0290 0.0015 0.0006 0.0216 0.8918 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.746868 0.737827 42.24881 249894.7 -750.6638 2.026644 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) 0.133836 82.51272 10.36526 10.48787 82.61418 0.000000 INF in Level form ADF Test Statistic -2.889871 1% Critical Value* 5% Critical Value 10% Critical Value -3.4758 -2.8811 -2.5771 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(INF) Method: Least Squares Date: 07/02/08 Time: 05:40 Sample(adjusted): 1971:2 2007:4 Included observations: 147 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. INF(-1) D(INF(-1)) D(INF(-2)) D(INF(-3)) D(INF(-4)) C -0.159010 -0.431646 -0.055416 0.178571 0.231637 3.206346 0.055023 0.089500 0.096661 0.095059 0.082139 1.278776 -2.889871 -4.822875 -0.573304 1.878531 2.820062 2.507355 0.0045 0.0000 0.5674 0.0624 0.0055 0.0133 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.306057 0.281449 8.862487 11074.66 -526.2496 2.122901 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) 0.124014 10.45506 7.241492 7.363550 12.43732 0.000000 INF first Diff ADF Test Statistic -4.158461 1% Critical Value* 5% Critical Value 10% Critical Value -3.4761 -2.8812 -2.5772 *MacKinnon critical values for rejection of hypothesis of a unit root. Augmented Dickey-Fuller Test Equation Dependent Variable: D(INF,2) Method: Least Squares Date: 07/02/08 Time: 05:06 Sample(adjusted): 1971:3 2007:4 Included observations: 146 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. D(INF(-1)) D(INF(-1),2) D(INF(-2),2) D(INF(-3),2) D(INF(-4),2) C -1.116252 -0.465840 -0.630752 -0.493846 -0.198782 0.199372 0.268429 0.244289 0.205992 0.152264 0.082994 0.742116 -4.158461 -1.906923 -3.062029 -3.243355 -2.395129 0.268653 0.0001 0.0586 0.0026 0.0015 0.0179 0.7886 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat 0.758801 0.750187 8.964538 11250.81 -524.3200 2.041916 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion F-statistic Prob(F-statistic) 0.040068 17.93578 7.264658 7.387272 88.08672 0.000000 ---- PcGive 8.00, copy for meuller ---- ---- session started at 9:59:10 on 2nd July 2010 ---Data loaded from: kingsl~1.wks DYg = diff(Yg, 1); DRIR = diff(RIR, 1); DINF = diff(INF, 1); DRER = diff(RER, 1); EQ( 1) Modelling Yg by OLS The present sample is: 2 to 152 Variable Coefficient Std.Error t-value t-prob 75.298 14.297 5.267 0.0000 -4.1188 0.81245 -5.070 0.0000 -1.8433 0.87806 -2.099 0.0375 -3.4756 0.78810 -4.410 0.0000 PartRý Constant 0.1615 RIR 0.1514 RIR_1 0.0297 INF 0.1190 INF_1 -1.3272 0.84293 -1.574 0.1176 -0.16278 0.083619 -1.947 0.0535 0.070684 0.084248 0.839 0.4029 0.0169 RER 0.0256 RER_1 0.0049 Rý = 0.420829 F(6, 144) = 17.439 [0.0000] å = 47.2574 DW = 0.645 RSS = 321589.6766 for 7 variables and 151 observations ECM added to database ECM = Residual values of equation 1 EQ( 2) Modelling DYg by OLS The present sample is: 3 to 152 Variable Coefficient Std.Error -1.8164 2.4640 t-value t-prob PartRý Constant 0.0038 -0.737 0.4622 DRIR -0.94313 0.57882 -1.629 0.1054 -0.10830 0.58233 -0.186 0.8527 -0.47543 0.55997 -0.849 0.3973 -0.054925 0.56078 -0.098 0.9221 -0.0022848 0.057581 -0.040 0.9684 0.028962 0.058141 0.498 0.6192 0.33128 0.053734 6.165 0.0000 0.0184 DRIR_1 0.0002 DINF 0.0051 DINF_1 0.0001 DRER 0.0000 DRER_1 0.0017 ECM 0.2111 Rý = 0.233869 F(7, 142) = 6.1924 [0.0000] å = 30.0024 DW = 2.71 RSS = 127820.7022 for 8 variables and 150 observations Testing for Error Autocorrelation from lags 1 to 2 Chiý(2) = 22.091 [0.0000] ** and 12.089 [0.0000] ** F-Form(2, 140) = Error Autocorrelation Coefficients: Lag 1 Coeff. Lag 2 -0.4394 -0.09951 Normality test for Residual The present sample is: 3 to 152 Sample Size 150 Mean 0.000000 Std.Devn. 29.191403 Skewness -1.201842 Excess Kurtosis 4.377773 Minimum -139.326914 Maximum 83.302943 Normality Chiý(2)= 28.817 [0.0000] ** Testing for Heteroscedastic errors Chiý(14) = 9.9004 [0.7694] and F-Form(14, 127) = 0.64105 [0.8262] V01=DRIR V02=DRIR_1 V03=DINF V04=DINF_1 V05=DRER V06=DRER_1 V07=ECM Heteroscedasticity Coefficients: Constant V05 V01 V02 V03 V04 Coeff. 602.4 -1.352 -39.1 -1.382 -54.72 0.6238 t-value 0.846 3.351 -0.02723 -0.619 -0.02764 - 0.1186 V06 V07 V01ý V02ý V03ý V04ý Coeff. 0.9564 -0.7571 1.493 -1.232 - 0.2156 0.897 -0.6802 - 0.4957 t-value 0.6409 0.9463 -0.122 0.3046 V05ý Coeff. V06ý V07ý 0.04762 -0.004178 t-value 1.814 -0.1378 RSS = 6.48822e+008 0.0861 1.26 å = 2260.27 Test of Functional Form Chiý(35) = 30.033 [0.7066] and F-Form(35, 106) = 0.75817 [0.8238] V01=DRIR V02=DRIR_1 V04=DINF_1 V05=DRER V06=DRER_1 V07=ECM V03=DINF Heteroscedasticity Coefficients: Constant V01 V02 V03 V04 607.3 118.7 -13.48 121.5 -29.26 V05 Coeff. -3.054 t-value 0.2801 2.763 1.678 -0.1344 1.648 - -0.436 V06 V07 V01ý V02ý V03ý V04ý Coeff. 11.12 -1.621 -9.83 -0.1758 - 0.2374 -0.3008 -1.333 -0.02697 - -1.773 t-value 1.692 2.011 -0.2808 V05ý V06ý V07ý V02 * V01 V03 * V01 V03 * V02 Coeff. 19.37 0.02008 0.1525 -14.79 - 0.7401 0.4523 1.717 -1.238 - -9.02 t-value 1.631 0.07008 -0.6706 V04 * V01 V04 * V02 V04 * V03 V05 * V01 V05 * V02 V05 * V03 Coeff. -14.03 -1.261 -10.75 1.39 1.498 1.53 t-value 0.2316 -0.8743 -0.1248 -0.9605 0.4243 0.4615 V05 * V04 V06 * V01 V06 * V02 V06 * V03 V06 * V04 V06 * V05 Coeff. 0.8547 4.616 -0.5509 5.417 - 0.1509 0.6532 -0.2152 0.7434 - 0.08071 t-value 0.3304 1.01 0.4705 V07 * V01 V07 * V02 V07 * V03 V07 * V04 V07 * V05 V07 * V06 Coeff. 0.2592 0.6311 3.536 0.9924 1.57 0.3617 2.497 0.5632 0.1139 t-value 1.876 2.165 0.4805 RSS = 5.55587e+008 å = 2289.41