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Domestic Macroeconomic Policies and Private Fixed Capital Formation in Nigeria: A VAR Approach By Okoli, R. Obioraa Onah, F. E. b Amalaha, R. Obinnac and Nwosu, O. Christiand June, 2007 Domestic Macroeconomic Policies and Private Fixed Capital Formation in Nigeria: A VAR Approach Abstract The study has as its objectives, to determine the impact of macroeconomic policies on private capital formation in Nigeria. In addition, the study sought to evaluate ipso facto the pattern of responses of private investment to shocks on macroeconomic Policies. And finally, to determine the causal ordering of the mediating variables connecting private investment and macroeconomic variables. The study applied the co- integrated vector autoregressive framework. The first objective of the model was resolve by estimating the short run dynamic error correction model. For the second objective, VAR model was estimated to determine the impulse response functions and variance decomposition using Cholesky decomposition so as to determine the response of private investment to shocks on macroeconomic policies. The third objective was resolved by conducting a granger causality test. Empirical investigation reveal that macroeconomic policies like, interest rate policy, exchange rate policy, the size of the public sector, domestic credit policy and the real GDP growth plays a prominent role in the performance of private investment in Nigeria. The results of both the dynamic short run model, impulse response and pair wise Granger causality test revealed that domestic credit to the private sector exerts a more significant influencing on the performance of the private investment. The study recommends that the expansion of the banking sector loanable fund to the private sector should be at the heart of the monetary policy design in Nigeria. In addition, the terms on which banking sector advances are extended to private investors should be reviewed and efforts should be intensified to wipe off all unofficial parallel markets or the so-called black market since they facilitate not only faster depreciation of the Naira through round tripping there by facilitating facilitate huge capital flight and illegal transfer of funds. Keywords: Domestic Macroeconomic Policies; Private Fixed Capital Formation; VAR Model ____________________ a Department of Economics, University of Nigeria, Nsukka. Tel: +234-803-094-5881. E-mail: [email protected] b Prof. Onah, F.E is the Head of Department, Department of Economics, University of Nigeria, Nsukka c Development Economics Unit, Department of Economics, University of Nigeria, Nsukka. Tel: +234-803-362-8283, 802-373-6892. E-mail: [email protected] d Department of Statistics, University of Nigeria, Nsukka. Tel: +234-805-324-1950. E-mail: [email protected] ii List of Tables Table 4.1: Table 4.2: Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7: Unit Root Statistics Johanson Co- integration Test Statistics Impulse Response for Private Investment Variance Decomposition for Private Investment Impulse Responses for GDP Variance Decomposition for GDP Result of Granger Causality Test iii Table of contents Abstract………………………………………………………………………………... ii List of Tables…………………………………………………………………………….iii Chapter one: Introduction 1.1Background…………………………………………………………………………...1 1.2 Problem Statement………………………………………………………………….3 1.3 Objective of the Study……………………………………………………………....7 1.4 Hypothesis…………………………………………………………………………...7 1.5 Scientific Contribution……………………………………………………………...7 1.6 Significance of Study 1.7 Scope of the Study…………………………………………………………………...8 Chapter two: A Review of Literature…………………………………….9 2.1 Theoretical Underpinnings………………………………………………………….9 2.2 Empirical Literature……………………………………………………………….15 2.3 Limitations of Previous Study……………………………………………………..19 Chapter three: Methodology……………………………………………..20 3.1 The Model…………………………………………………………………………..20 3.2Model Justification…………………………………………………………………..23 3.3 Estimation Procedure………………………………………………………………24 3.4 Method of Results Evaluation……………………………………………………...25 3.5 The Data……………………………………………………………………………..26 Chapter Four: Presentation and Interpretation of Empirical Results……..................................................................................................27 4.1 Result Presentation…………………………………………………………………27 4.2 Unit Root Analysis………………………………………………………………….27 4.3 Co Integration Analysis…………………………………………………………….28 4.4.1 Short-Run Dynamic VAR Model………………………………………………..29 4.4.2 Impulse Response and Variance Decomposition……………………………….31 4.4.3 Granger Causality Test…………………………………………………………..37 4.5 Evaluation of Hypothesis…………………………………………………………...40 4.6 Police Implications of Findings…………………………………………………….41 Chapter five: Summary, Policy Recommendation and Conclusion.......42 5.1 Summary of Findings………………………………………………………………42 5.2 Policy Recommendations…………………………………………………………...43 5.3 Conclusion…………………………………………………………………………..44 iv Chapter one Introduction 1.1 Background The impact of macroeconomic policies on private capital formation, a topic of obvious concern to policy makers, has attracted considerable interest in the analytical and empirical literature. Economic theory has paid considerable attention to this debate. Taken as a whole, however, the theoretical predictions are ambiguous. Depending on their underlying assumptions, some approaches predict a negative relationship, while others predict a positive one. Empirical literature on growth has consistently showed that the rate of accumulation of physical capital or investment is an important determinant of economic growth. Results provide evidence that public capital investments are a key input in the private sector producion process for they affect both the steady state level of income per capita and the rate of economic growth on the transition paths towards the equilibrium (Nair, 2005). Furthermore, there are other important empirical evidences why private investment should be at the centre of the debate on how to promote growth and raise employment. Ndikuman (2005), while accepting that investment is a robust determinant of growth, especially equipment investment, believe that private investment is a key determinant of cross-country difference in long run economic growth. This has led observers to identify low investment as one of the leading causes of the slow growth in developing countries in general and in African countries in particular. The UN Millennium Project (2005) has reemphasized the need for a big push strategy in investment to help poor countries break out of their poverty trap and achieve the Millennium Development Goals (MDGs). The report argues further that, to enable all countries achieve the MDGs, there should be identification of priority private investments to empower poor people, and these should be built into MDG-based strategies that anchor the scaling-up of private investment.. In more than 40 years since independence, Nigeria has never grown at 7 percent or more for more than three consecutive years (NEEDS, 2004). Between 1975 and 2000, Nigeria’s broad based macroeconomic aggregate-growth, the terms of trade, the exchange 1 rates, government revenue and spending – were among the most volatile in the developing world. The economy has been caught in a low growth trap, characterized by a low savings – investment equilibrium (at less than 20 percent). With an average annual investment rate of barely 16 percent of GDP, Nigeria is far below the minimum investment rate of about 30 percent of GDP required to unleash a poverty reduction growth rate of at least 7 – 8 percent per year (NEEDS, 2004). A fairly large and growing literature has developed around attempts to explain this poor growth performance. In providing what is perhaps one of the best reviews of literature, Collier and Gunning (1999) zero in on several important factors whose impact on African growth performance is mediated through their negative implications for investment, particularly private investment. In their view, “cumulatively” the variables have contributed to a capital hostile environment. This in turn has reduced the rate of return on private investment. These factors include: high risk, capital hostile environment, poor finance and low savings In Nigeria, unsurprisingly, the policy orientation has been akin to that of other developing countries in manifesting an increasing reorganization of the potential role the private sector could play in mobilizing the country’s formidable and copious natural and human resources. These concern, however, do not seem to have been matched by an appropriate and consistent blend of policies to bolster private sector investment. The reported performance of private investment in Nigeria has been less than satisfactory, and slightly less than the average for Sub-Sahara Africa (SSA). The Nigerian private sector spent only around 21 percent of the countries national income over the period 1970-1980. The period 1981-1991 marked a notable low performance with private investment/GDP ratio of only 11 percent (The corresponding average for SSA was around 14 percent). By 1992-2003, it fell further to 7 percent (CBN, 2004). Not only has private investment been diluted over the 1980s and has remained so over the period 1990 – 2000, it has also been volatile. To use the 1980s as an example, private investment as a percentage of GDP dropped from 21 percent to 19 percent from what it was in 1970-1980 representing a drop of 47 percent. Between 1991- 2003, it further dropped by 36 percent from 11 percent to 7 percent CBN (2004). This poor performance is attributed to successive attempts to 2 sustain fiscal balances and external balances by a pursuit of credit restraints to galloping inflation, and to a continual devaluation of domestic currency to correct price distortion and accumulate foreign resources. Prescription of solutions to the poor performance of private investment that characterized a growing economy like Nigeria is of great policy concern. To what extent is there really a relationship between private capital formation and macroeconomic policy? Particularly, there are unresolved questions regarding the powers of a country’s domestic monetary and fiscal policies in bolstering private capital formation. Ndicumana (2005) stated that it is largely within the power of developing countries to boost private capital formation by adopting appropriate blend of domestic policies on domestic credit to the private sector, the exchange rate, interest rate and fiscal policies. But this has not been fully supported by the country’s experience as shown in the poor performance of private investment. This further casts doubts on the ability of the country to induce “investment transition” which is required to meet the MDGs of reducing poverty by scaling up private investment. 1.2 Problem Statement Investment is key to economic growth. Empirical studies like (Khan and Reinhart, 1990; Kormendi and Mcquire, 1985; Lucas, 1988; Barro and Lee, 1994; Barro, 1995; Ghura and Hadjimichael, 1996; Kehoe and McGrattan, 1999; Hernandez, 2000; Elenog and Jayaraman, 2001; Ndikumana, 2000; and 2005) conducted in Africa have established beyond doubt, the critical linkage between investment and the rate of growth. These researchers further posit that private investment has a stronger more favourable effect on growth than government investment. According to Hermandez – Cata (2000), the ratio of private investment to GDP in sub-Saharan African countries had experienced poor rate of growth between 1980s – 1990s. He stated further that private investment GDP/ratio was less than 10 percent, compared with 16 percent in Latin America, 18 percent in advanced countries and 16.5 percent in newly industrialized countries in Asia. Viewed against the background of growing evidence of a strong link between high investment and sustainable growth, a steady decline since 1980s of private fixed 3 investment in Nigeria has been a matter of considerable concern to policy makers. The poor performance as experienced in Nigeria is akin to other countries in the region of Sub-Saharan Africa. The private investment as a percentage of GDP, which was 19.1 percent in 1970, dropped to an average of 18.4 percent by 1980. By 1981-1990, it dropped further to 11 percent and to 7 percent of GDP between 1991-2003 (CBN, 2004). This poor performance has persisted despite efforts made in the past to change the trend. The performance of private sector capital expansion over the last three decades dropped as a result of weak relationship between the banking sector and private capital expansion. This issue has remained one of the most complicated in the policy-making process and design in Nigeria. This is due to the fact that expanding banking sector loanable funds and their potential effect on domestic credits are at the heart of the concern of monetary policy as designed and implemented in developing countries (Badawi, 2004). Mostly guided by the central objective of curbing inflation and lack of variety in monetary tools and instruments, monetary policy in Nigeria adopt tight measures in the process of constraining credit by setting administered controls on the direction and terms of credit to the private sector. Nigeria experienced a markedly low credit to GDP ratio: banking sector advances to the private sector fell from around 19.8 percent in 1980s to 12.7 percent in 1990s (CBN, 2004). This performance seems quite alarming, especially when compared to the needs of a typical Sub-Saharan African country of at least 15 percent credit/GDP ratio in order to achieve private investment/GDP ratio of as high as 26 percent (ADB, 2004). This poor performance of the financial sector in easing credit constraint is attributed to the failure of the monetary authorities in Nigeria to design a comprehensive framework that incorporates a complete set of monetary, institutional and prudential objectives which strike at the same time an appropriate balance between inflation targets and expansion in bank advances to the private sector. Inflation rate measured in terms of percentage in consumer price index (CPI) escalated from an average of 20.5 percent in 1980-1994 to an average of 25.4 percent in 1995-1999 and fall to an average of 12.9 percent, between 2000-2003 (Asogwa, 2005). This was attributed to the weakness in Nigerian fiscal policy framework or what can be termed fiscal procyclicality (Batin, 2004). 4 While the debate on the right monetary approach to adopt is still going on, policy analysts are yet to come to a consensus regarding the impact of fiscal policy on private capital formation. The differences in outcome may at least partly be explained by methodological weakness of these studies. A large number of studies focus on aggregate variables of fiscal policy, such as consumption, overall taxes or budget deficits. Thus, they disregarded the importance of the composition of fiscal policies and thereby overlooked the possibility that different policies may have different effects on private capital formation. In some cases, it is not entirely clear whether any empirical association between fiscal variables and private capital formation operates through third – variables relevant to private investment. These have implications for policy advice for countries currently struggling with structural imbalance. This point seems intuitive enough, but it is still a point of contention in the literature. In particular, Ndikumana (2005) claims that it is largely within the power of the country concerned to adopt appropriate domestic policies (monetary, fiscal and exchange rate) to bolster private capital formation. However, despite efforts made in the past to bolster private investment, private fixed capital formation in Nigeria is still below the average for SSA. Is this effort worth it? This research believes it does. Having recognized the role of private capital formation in the growth process and the fact that no work known to us has made attempt to answer the question of whether domestic macroeconomic policy simulate private capital formation in Nigeria? The researcher believes that investigating this is indeed expedient owing to the fact that Nigeria is currently mobilizing for the second phase of it developmental program termed NEEDS II. The few existing studies on capital formation in Nigeria are not comprehensive. The study by Ekpo (1999) is on public expenditure and growth. The work failed to look at the role of monetary and exchange rate policies on private capital formation in Nigeria. Badawi (2004) stated that the exchange rate policy of a country is very crucial especial to 5 the import dependent industries. Furthermore, the work failed to look at impulse responses. Even at that, there is an urgent need to extend this study because of emerging trends in Nigeria’s macroeconomic environment. .Iyoko (2006) investigated the relationship between public and private investment in Nigeria. This work tends to reinforce the findings by Ndikumana (2005) that public investment those not crowd out private investment in Africa. The study failed to look at the present level of private capital formation in Nigeria and the macroeconomic fundamentals responsible for this dismal performance. The works by Akpokodje (2000), Ahmet and Gaobo (2005) are not country specific, hence, the need to carryout a country specific assessment. These works also did not investigate the magnitude of shocks transmitted from one variable to the by testing for impulse responses and variance decomposition. The research lacuna is derived from this gap. This work will depart from existing studies (known to us) by assessing the impact of macroeconomic policy on private capital formation in Nigeria using an econometric framework encompassing other conventional determinants of investment, and applying a range of estimation techniques that control for issues such as simultaneity, countryspecific effects and parameter heterogeneity, while investigating both the short run and long rung effects of policies as neglected by past studies. In doing this, the mediating variables responsible for the transmission of policies will be determined, while impulse responses will be identified and variance decomposition will also be investigated using Choleski decomposition. The research question arising from the above issues are as follows: 1) What are the impacts of macroeconomic policies on private capital formation? 2) What is the pattern of responses of private investment to shocks on Macroeconomic policies? 3) What is the direction of the causal ordering of the mediating variables connecting Private investment and Macroeconomic policies? 6 1.3 Objectives of the Study The objectives include 1) To determine the impact of macroeconomic policies on private capital formation in Nigeria. 2) To investigate the pattern of responses of private investment to shocks on macroeconomic Policies. 3) To determine the causal ordering of the mediating variables connecting private investment and Macroeconomic policies. 1.4 Research Hypotheses 1) Macroeconomic policies have no impact on private capital formation in Nigeria. 2) Private investment has no significant impulse responses in Nigeria. 3) The mediating variables connecting private investment and macroeconomic Policies have no causal ordering in Nigeria. 1.5 Expected Scientific Contribution By using a VAR model to test the stated hypothesis, this work would have build a model of private capital formation and macroeconomic policies for Nigeria by extending the neoclassical accelerator model, taking into account some specific constraints faced by the developing world. In doing so, the study presents four novelties: 1) The work will provide deeper understanding of the relationship between macroeconomic policies and Private capital formation in Nigeria and expose the impediments to investment growth in Nigeria. 2) A VAR model will be used to assess the performance of private investment in Nigeria. 3) The impulse response will indicate the magnitude of the shocks transmitted from one variable to another (among the explanatory variables) and will serve as a guide on Policy formulation as regards to investment in Nigeria. 4) The relationship between macroeconomic variables and private capital formation will be tested in a Country specific approach method as opposed to the usual cross-country analysis 7 1.6) Significance of Study This work set to determine the impact of macroeconomic policies on private capital formation in Nigeria. Since economic literature has established that private investment is an elixir to economic growth, a work of this nature is indeed expedient. This work by providing a deeper understanding of the relationship between macroeconomic policies and private capital formation in Nigeria will expose impediments o investment growth in Nigeria. 1.7) Scope of the Study This study will cover the period 1970-2004; a sample size of 35 years is necessary in order to have enough observation for the computing of VARS 8 Chapter Two A review of Literature 2.1 Theoretical Underpinnings A number of theories have emerged to explain private investment behaviour in developed countries. Though literatures are inconclusive in their assessment of the impact of macroeconomic policies on investment, the majority does find a negative association between both variable (Seven, 1998). Economic theory has paid considerable attention to this debate, taken as a whole, the theoretical predictions are ambiguous. Depending on their underlying assumptions some approaches predict a negative relationship, while some predict a positive one. Literature on private investment behavior in industrialized countries has distinguished a set of factors determining firm’s investment decision. The basic of the majority of these approaches and the simplest among them is the accelerator theory of investment, also known as “acceleration principal”. It says that, other things being equal, an increase in a firm’s output will require a proportionate increase in its stock of capital equipment. The implication of acceleration theory is that, the level of output or the changes in aggregate demand determines investment or the change in capital stock. That firm’s output required would induce the firm to instantly increase its stock of fixed assets provided that it has been operating at full capacity (clark, 1917; Manne, 1945; Timbergen, 1938). The assumption of full capacity and instantaneous adjustment underlying the naive accelerator principal were modified and a more realistic model termed the flexible accelerator model or capacity utilization model was developed (Godwin, 1948, Chanery, 1952, Koyck, 1954). The concept of flexible accelerator says that, the adjustment of the capital stock to the desired level is not instantaneous because of delivery lags and delayed response to changes in the level of demand. As argued by Eisner (1963), the relationship between current investment and current income or output is an oversimplification because the current changes in the demand, output or Sales is not enough to sustain an increase in investment. Thus the firms will opt for other ways of meeting the demand like running down the inventories in fixing their investment. 9 The neoclassical theory of investment-founded by Jorgenson (1963)-provided another explanation for investment expenditure in addition to changes in output. Inducement to invest may also be simulated by favorable changes in relative prices where downward shifts in the real user cost of capital services imply that the firm has to restore equilibrium by cutting down the marginal productivity of capital stock (Jorgensen, 1963). Jorgensen model is based on theory of optimal capital allocation. The theory of profit maximization firm, subject to a production function through which a technical relationship between inputs and outputs get defined is central in neoclassical model. Jorgenson’s basic assumptions for a firm to maximize its present value are the rate of changes of the input of capital services is equal to the rate of net investment; the relationship between level of output and inputs of labour and capital services is constrained by a production function. The production function also connects the capital stock to the relative price between capital and output. The model assumes flexible accelerator princes and perfect capital and other markets. It implies that, there are no liquidity constraints to adjust capital stock and a general equilibrium situation with full employment. Empirical evidence is consistent with this accelerator effect and shows that high output growth is associated with high investment rates (Greene and Villanueva, 1991; wai and Wong, 1982). The decision by the firm to invest is too complex to be determined only by output and relative prices as the accelerator-- neoclassical framework suggest (Badawi, 2004). The cash theories of investment built on the assumption that external funds are more expansive than internal funds-argued that financial conditions internal to the firm in the form of liquidity constraints and profit availability determine investment outlay in a given firm (Eisner, 1963; Grunfeld, 1960; Meyer and Glauber, 1964). This theory hinges on total profits or profit rates earned by business unit and industries instead of output. This analysis has several variants. The profit theory states that “greater the gross profits, greater will be the level of internally generated funds and in turn greater will the rate of investment” Meyer and Kuh (1958) observed that the recognition of the institutional changes led the theory of investment to changes from profit maximization to utility maximization’ Firms decision is not only internally determined, external factors responsive to the firm’s assets relative to replacement cost. In response to this, Tobin introduced the Tobin’s q, which 10 transmits the impact of fluctuations in capital and financial market on private sector investment. The theory is the addition to the market value of the firm resulting from a unit increase in fixed capital, or the capital valuation of the extra unit of the firms fixed assets (Tobin, 1969;Brainard and Tobin, 1968). In a volatile, uncertain world the firm may not be interested in expected or actual values of the rate of returns, output, relative prices, or internally generated funds. It may rather make investment decisions with a view to the degree of variability of investment determinants from perceived expected value (Badawi, 2004). Much of the theoretical work on uncertainty and investment has been developed in the framework of riskneutrality. However, unlike the neoclassical framework with certainty, the firm maximizes expected utility or profit function, resulting in a marginal condition for optional capital where the expected marginal revenue product of capital is a function of random distribution of factor and prices. It is the variance of the density function of probability distribution of each factor that determines the degree of uncertainty about that factor. These degrees of uncertainty about different factors may be assumed independent from each other by assuming an independent distribution of factors affecting expected marginal revenue function or assumed correlated by assuming joint distribution and analyzing uncertainty in a multivariate context (Hartman, 1972; Nickell, 1977; Serven, 1998). In support of this proposition, Abel (1983) states that price shocks causes firm to alter the optional capital/labour mix, thus making marginal revenue product of capital rise more (or fall less) than relative output prices. Consequently, marginal profitability is a convex function of output prices, and Jensen’s inequality then implies that price uncertainty raises the expected profitability of capital, hereby increasing investment. In literature, focus has been shifted to the adjustment costs which is implied by the acquisition and installation of capital, emphasizing the irreversibility nature of most fixed investment projects (Dixi and Pindyck, 1994). The above models reflect uncertainty about the appropriate form of the private investment model for developing countries. Though the empirical test of the various models including the most widely accepted neoclassical flexible accelerator model, have 11 been quite successful, its application in the developing countries context is rather difficult due to the inherent assumptions of the model and non availability or inadequacy of data for certain variables. In recognition of the above limitations, developing countries moved from traditional theories to the role of economic policies in determining private investment and try to identity and quantify the relevant policies for private investment as well as bridge the gap between pure, investment theory and unique structural and institutional characteristics of developing economies (Mckinnon, 1973; Fry, 1988; Badawi, 2004). The theories synthesized a framework, which feature a new set of factors that seems to be left out in conventional investment theories. Based on this fact, Bhattacharaya et al (2004), and Badawi (2004) observed that banking sector credit and depth or size of financial intermediation came out as an important factors in investment equation: The relationship between the banking sector institutions and private sector capital expansion remains one of the most complicated issues in the policy making process and design in developing countries. This due to the fact that expanding banking sector loanable funds and their potential effect on domestic credit are at the heart of the concern of monetary policy designed and implemented in developing country. Nair, (2005) observed that real bank credit to the private sector act as an explicator to capture the credit constraints in the economy. He further observed that asymmetric information and incomplete contracts implies that availability of finance especially bank credit may constraint investment decisions of private firms. Since the fundamental market problems centered on asymmetric information between buyers and sellers, this will frustrate the efficient exchanges that would occur in equilibrium if all agents were fully informed. Consequently, the assumption of the neo-liberal view that individuals and firms can costlessly write and enforce richly detailed financial contracts can be questioned since the completeness of financial contract is not possible if information or ability to enforce contract is not possible (Gertler and Rose, 1994). Until the early 1970s, it was generally believed that low interest rates on bank loans and deposits would promote private investment spending – a notion consistent with the Keynessian and neo-classical analyses. But McKinnon and Shaw (1973) challenged this 12 conventional wisdom. They argued that raising interest rates increase the amount people are willing to hold as financial assets by decreasing the holdings of foreign assets and non-financial assets. Thereby, the mostic financial system is able to extend more loans to the investors. They argued further that the existence of very low or negative real interest rate would result in the support and expansion of unproductive non-viable projects and the channeling of funds into consumption rather than investment, which would be detrimental to private capital formation. They advanced the hypothesis that private investment in developing countries is positively related to the accumulation of real money balances. In another perspective, the “new-structuralize” economist argued that high bank interest rates lead to high bank deposits simply due to transfer of funds away from alternative asset holdings (Taylor, 1983), such as the informal credit markets (Edward, 1988). As a result of the above,stiglitz and Uyo (1996) argued against unbridled financial liberalization and instead, supported, “Mild financial repression. In support of this statement is the work by (King and Levine, 1997). Ndikumana (2005) observed that the effect of the exchange rate on private investment is theoretically ambiguous. He argued that real exchange rate depreciation increases profitability in export-oriented sectors and therefore promotes investment in these sectors. Conversely, depreciation of the exchange rate increases the cost of imported capital goods, and thus decreases investment in import dependent sectors. Badawi (2004) also observed that real exchange rate appears to have a significant positive short-run impact on private fixed investment, while it reports a negative long-run impact on private sector investment in fixed assets. He further observed that the deleterious impact of depreciation in the domestic currency on private sector investment has contributed to the debate on the appropriateness and relevance of devaluation policy, a debate he contended can be widened by adding a neoclassical dimension (as far as investment literature is concerned), considering the potential impacts of devaluation on the real user cost of capital, and thereby on investment and growth. This dimension may stand in conflict with the conventional view that devaluation has a favorable effect on growth, and development through correcting distortions and generating incentives for the private sector (particularly in the tradable goods sector) 13 The theoretical literature on the relationship between fiscal policy and growth has grown substantially since the mid-1980s, when the endogenous growth models emerged. According to these models, the process of economic growth is endogenously determined. A crucial difference with neo-classical growth models is that these new growth models do not assume diminishing marginal productivity of capital. Consequently, (changes in) the capital stock can affect the long run per capital growth rate, either via a quantity (i.e. more investment) or a quality (i.e. more efficient investment) effect. These new growth models, therefore, conclude that economic policy-among which is also fiscal policy-can increase the steady-state economic growth rate, if policies are aim at influencing the quantity and/or quality of the capital stock. Among the endogenous growth models incorporating the role of fiscal policy are Barro (1990,) king and Rebelo (1990), Rebelo (1991) and Barro and Sala-i-Martin (1992). The exact nature of the impact of fiscal policy on economic growth according to these models depends on the type of fiscal policy instruments used. In particular, the growth effects of fiscal policy can be divided into productive and non-productive expenditures,(distortionary and non-distortionary) taxes (Kneller, et al. 1999; Gemmell, 2000; Hermes and Lensink, 2001). When government expenditures create positive production externalities, focus on enhancing innovation and research and development and/or stimulate the accumulation of private capital, these expenditures are seen as productive. Aschauer (1999), Kneller el. at (1999) posit that public investment in infrastructure, education and health belong to productive expenditure and is said to crowd-in private investment. However if financial recourses are scarce, public investment may reduce the possibilities of the private sector to obtain credit to finance investment. Moreover, if public investment is financed through monetary financing, private investment may be seriously discouraged (Ramirez, 1996). In this case public investment is said to crowd-out private investment opportunities (Buiter, 2004) Locking at fiscal policy instruments, budget deficit are assumed to have a negative impact on economic growth (Hermes and Lensink, 2001). First, high deficits may signal a 14 high tax burden in the future. This may discourage current aggregate expenditures, and thus also private investment. Other works in support of the above include :( Bertola and Drazen, 1993; Giavazzi and Pagano, 1990; 1996, Sutherland 1997; Guimaraes and Olaf 2000; Ndikumana 2005). It was further observed by Alesing and Perotti (1997) that high budget deficit may lead to higher interest rates in financial markets, which may reduce investment and growth. Moreover, high budget deficits may increase risk premiums on interest rates, in particular raising inflation risk and the default risk premium. High interest rate risk premium may discourage private investment finally when high deficits are financed with financial market loan; this may decrease the opportunities of the private sector to borrowing (Hermes and Lensink, 2001). In addition to testing the impact of fiscal policy on private investment, the impact of capital and trade flows have been reported to have had a positive effect on private capital formation by increasing exchange base and private sectors access to imported capital goods and foreign markets (FitzGerald et al, 1994). 2.2 Empirical Literature Blejer and Khan (1984b) using a framework, which is an extension of flexible accelerator type, associated with Jorgenson (1967, 1971) and Hall (1977) tested an explicit functional relationship between principal policy instruments and private capital formation in developing countries. Their findings were a challenge of the traditional view that standard investment theory is not relevant for developing countries. They were also able to establish a direct empirical link between government policy variables and private capital formation. Asante (1993) estimated a private investment equation for Ghana. In estimating the determinants of private investment, the independent variables employed include incremental capital output ratio, the lending rate, the exchange rate, credit to the private sector and public investment. His preliminary result showed among other things a “crowding out” effect of public investment. 15 Ariyo and Raheem’s (1991) estimated the effect of fiscal deficit on macroeconomic aggregate in Nigeria. Employing the following independent variables: public investment, rate of growth of GDP, domestic credit to the private sector and interest rate. Their results show that all the variables were statistically significant and evidence of “crowding in” was arrived at. Moshi and Kilindo (1999) estimated the impact of government policy on macroeconomic variables in Tanzani using ordinary least square (OLS). The work which was an extension of Khan and Blejer (1984) was able to establish a direct empirical link between government policy and private capital formation. The result indicates that public investment crowd out private investment, but the effect depends on the way in which public investment is introduced into the model. Elenoa and Jayaraman (2001) carried out a study on the determinants of private investment in Fiji. Employing an econometric extension of the work of Goldsborough et al. (1996) and Ndikumana (2000) tried to avoid simultaneity problems by lagging certain variables, constraining the causality to run in one direction. Augmented Dickey fuller test (ADF) and the Phillips Perron test were used to examine the stationarity properties of the time series data. The empirical investigation show that changes in real private investment in Fiji are best explained by changes in terms of trade and by a dummy variable representing a coup and its effects. It was further observed that changes in other economic variables examined have an insignificant effect on the variations of private investment. Nair (2005) analyze the determinants of fixed investment in India Private Corporate using Annual Survey of Industries data. In caring out this investigation, a reduced form equation derived from the neoclassical investment theory was used for the empirical analysis. Empirical results show that, the traditional determinants like output and profit still plays a major role in determinant corporate investment rather than the policy variables. It was also observed that the only index that shows strong positive association with corporate investment is index of money market liberalization. It was further observed that there is significant negative association between index of capital account 16 liberalization and corporate investment. Hermes and Lensink (2001) investigated the impact of fiscal policy on private investment in less developed countries. This work main contribution is that it is the first attempt to analyses the existence of a non-linear relationship between fiscal policy variables and investment. The researchers employed a panel estimate for a set of LDCS, using observations of variable that have been averaged over three periods: 1970-1979, 19801989 and 1990-1998. The result of the investigation show that a reduction of budget deficits as such is not a panacea and can be even harmful and that the combination of specific expenditure and revenue reforms may be of crucial importance. Badawi (2003) in an attempt to address the issue of complementarily and substitutability of state capital to private sector investment in a neoclassical growth framework employed a co-integrated vector autoregressive model to account for potential endogeniety and nonstationarity problems. Results suggest that both private and public capital spending have simulated economic growth in Sudan over the period 1970-98. It was observed that the impact of private investment on real growth has been more pronounced than that of public sector investment. Iyoko (2006) tested the relationship between public and private investment in Nigeria. Her result reinforced the findings by Ndikumana that public investment does not crowed out private investment in Africa. Lutfi (1999) estimated the effects of financial markets on private capital formation in Turkey covering the period 1968-1998 periods. This study modified the neoclassical investment model by including credit availability, GARCH process of interest rate. While reinforcing the findings of previous studies that the quantity of credits significantly affects private investment, the result go on to indicate that cost uncertainty, but not the level, has an adverse impact on private investment in turkey Badawi, (2005) using a blend of co integration, vector autoregressive and error correction techniques to estimate long and short-run coefficients. The empirical result suggests that 17 public sector investment had a negative crowd out impact on private investment over the period of study. Devaluation policy contributed to discouraging private sector capital expansion. He observed further that monetary policy in the form of restrictive domestic credit appears to have a significant impact on private investment, suggesting that a restrictive monetary policy may lead to shrinking private capital formation by tightening financial contract private firms. Ahmet and Gaobo (2005) analyze the determinants of unsatisfying private investment growth in the Middct le East and North African (MENA) throughout the 1980s and 1990. The researcher employed a panel of 40 developing economies. Extending the neoclassical accelerator model and taking account of the various constraints faced by the investors in developing countries into account, the research came to the conclusion that insufficient structural reforms, deficient trade openness, economic uncertainty and external debt burden have been a crucial factor for the deficit in private capital formation in the developing world and in MENA countries in particular. Seven (1998) estimated the impact of uncertainty on investment using a large panel data set of developing countries. The researcher draws a distinction between sample variability and uncertainty, and constructed alternative measures of the volatility of five key macroeconomic variables- inflation, growth, the terms of trade, the real exchange rate and the price of capital goods and examined their association with, aggregate private investment. The method the method employed allowed for simultaneity, country specific effects and parameter heterogeneity, across country. The result abstain underscore the robustness of the investment uncertainty. Akpokodje (2000) explored the association between export earning fluctuations and capital formation in Nigeria using a reduced form equation built around the flexible accelerator model and adopting a cointegration technique. Result reveals that the current level of export earnings fluctuations adversely impinges on investment (that is the change in capital stock in the short-run. 18 2.3 Limitation of Studies Although the importance of private capital formation has been widely developed in the literature, title is known-both theoretically and empirically about what induces private investment in developing country like Nigeria. It has been observed that developing countries do not always operate in a competitive environment and also faces constraints that are not accounted for in the neoclassical model. This partly explains why most economists do not agree on the subject of the determinants of investment in the developing countries (see Greene and Villanueva, 1991, Blejer and Khan, 1984, serven, 1998, Ahmet and Gaobo, 2005, Naira, 2005, Badawi, 2005). This phenomenon is also the case with Nigeria, for which empirical literature is very deficient (See Ekpo, 1990) Akpokoje, 2000, Ahmet and Gavbo 2005). Most of these studies are not country specific but rather a cross-country analysis. The study by Akpokoje (2000) is based on the relationship between export and gross capital formation and that of Ekpo (1999) is on public expenditure and economic growth. No work known to us has carried out an investigation on the impact of macroeconomic policies on private capital formation in Nigeria. The big question of can macroeconomic policy stimulates private capital formation in Nigeria has remained unanswered. This work is a novelty in that it is the first time this research question is to be answered in Nigeria. This question forms the nucleus of this research work. 19 Chapter three Methodology 3.1 The Model In modeling the determinants of investment, five broad approaches are generally considered. These major strands of investment behaviour include the accelerator model, the liquidity theory, the expected profit theory, the Tobin’s Q theory, and the neoclassical flexible accelerator theory. The flexible accelerator model appears to be the most popular of these theories used in applied work. However, in the context of developing countries, due to data limitations and structural constraints, a variant of the flexible accelerator model has often been used in empirical literature, including the literature on the determinants of private investment in these countries. According to the neoclassical model originally developed by Jorgensen (1963), solving the profit maximization problem of a representative firm yields the demand for capital as a function of output and the cost of capital under certainty (Ram, 1993). K*pt = F (GDPt, Ct) ……………………………………………………………………….. (1) Where K*pt is optimum or desired capital stock by private sector in period t; GDPt is the output, and Ct is the cost of capital proxied by interest rate. In addition, in the light of the arguments that the quantity constraints coming from the financial markets may be more binding than the cost of capital in a developing country like Nigeria, the flow of credits to the private sector is added. It has also been observed that the exchange rate plays a significant role in the growth of the private sector. Though the theoretical prediction are ambiguous. The inclusion of exchange rate into the model is indeed expedient. Also, the role of public investment on private sector growth process is still an ongoing debate in literature .Drawing a conclusion on its impact in the private sector growth process is indeed difficult owing to the fact that empirical result conducted in other developing countries reported divergent result on it impact on private sector 20 growth process. While some report a crowding in relationship, others reported a crowding out effect. The inclusion of this variable into the private investment equation in is indeed important. Thus the equation becomes, K*pt = H (GDPt, RIRt, DCRPt, REXCHt, PUINVt) ………………………………….... (2) Because there is no data on capital stock available for Nigeria, one can use definition of the gross private investment given by, PIt = (Kpt - Kpt – 1) + Kpt – 1 …………………………………………………………. (3) Where is the depreciation rate of the private capital stock and P1t is gross private investment. In the steady state, this equation becomes, PI*t = K* pt …………………………………………………………………………... (4) Inserting (3) into (2), obtain PI*t = H (GDPt, RIRt, DCRPt, REXCHt, PUINVt) ………………………………….. (5) The actual stock of private capital may not adjust completely to reach the desired level due to technical constraints, and the time it takes to plan, decide, build and install new capital. Such dynamic structure in private capital behaviour can be introduce through a practical adjustment mechanism like the following, Kpt – Kpt – 1 = B (K*pt –Kpt-1) O ≤ ≤ 1 …………………………………………….. (6) Where is the coefficient of adjustment. In this difference between desired private capital in the time t and actual private capital in the previous period. For practical purposes, on can express equation (6) in terms of gross private investment as 21 IPt-Pt –1 = (IP*t – IPt –1) ……………………………………. …………………… (7) Rearranging equation (7), obtain. IPt = IP*t – (1 - ) IPt – 1……………………………………………………..……. (8) Extending the above theoretical model and previous studies like Badawi (2003 and 2004), Aschauer’s (1989), Monadjemi’s (1996), Ndikumana (2005), Ouattara, (2005) and based on economic theory, Private Investment model can be specified as follows: It 0 1 It 1 2 RGDPt 3 PUINVt 4 RIRt 5 EXRCHt 6 DCRPt t …………………. .(3.9) All variables in natural logarithm except real interest rate The unrestricted VAR model of equation (3.9) may be written as Vt = GoDt + G1Vt-1 + G2Vt-2 + ………. + GKVt-k + t………………………….. ..(3.10) Where Vt is (6 x 1) vector containing the endogenous variables, D is the vector of intercept term and trend, t is a (6x1) vector of white noise errors that are uncorrelated with all the right hand side variables and their own lagged values but may be contemporaneously correlated with own lagged value. The corresponding vector error correction model (VECM) of equation (3.10) may be specified as Vt Go Dt 1Vt 1 2 Vt 2 ... k 1Vt k 1 Vt k ...(3.11) Where is a (6 x 6) matrix and t is a (6 x 1) vector of error term. The matrix contains information on the long run adjustment, while i contains information on the 22 short run adjustment to changes in Vt. The matrix is decomposed into = ; where is the adjustment matrix, representing the speed of adjustment to equilibrium, while contains long run coefficients or elasticities. The above equation can be transformed into a matrix form as follow: ln I t ln RGDP t ln PUINVt k 1 i 1 RIRt ln EXCH t ln DCRPt i11 i 21 i 31 i 41 i 51 i 61 i12 i 22 i 32 i 42 i 52 i 62 i13 i 23 i 33 i 43 i 53 i 63 i14 i 24 i 34 i 44 i 54 i 64 i15 i 25 i 35 i 45 i 55 i 65 i16 (ln I )t i 1 ln I t k 1i ln RGDP i 26 (ln RGDP)t i 2 t k 2i ln PUINVt k 3i i 36 (ln PUINV )t i 3 i 46 ( RIR)t i 4 1 2 3 4 5 6 RIRt k 4i ln EXCH i 56 (ln EXCH )t i 5 t k 5i i 66 (ln DCRP)t i 6 ln DCRPt k 6i Where It=Private Investment RGDP=Real GDP PUINV=Public Investment PIR=Real interest rate REEXC=Real exchange rate DCRP=Domestic Credit to the private sector 3.2 Model Justification In assessing the relationship between macroeconomic policies and private capital formation in Nigeria, we opted to use a VAR approach. The choice of a VAR model will help us obtain quality economic properties, strong statistical inference and sound economic postulates of the specified model. In developing countries in general, it has proved difficult to estimator robust structural models of private investment (see Agenor, 2004). VAR models offer a way of analyzing the dynamic relationship between two main variables without having to specify a structural model of private capital formation. The model allow us take into account-delayed responses with a parsimonious lag structure. VAR model obviates a decision as to what contemporaneous variables are exogenous with only lagged variables on the right hand side, and all variables are endogenous 23 (Green, 2000). The model takes all variables as dependent to avoid lead back effects of two variables. The central feature characterizing the VAR technique is that it poses strong restrictive structural modeling, as it imposes no a priori end-exogenous divisions of variables. Furthermore, no zero restrictions are imposed on individual variables to attain identification, which is the case under simultaneous equation modeling. VAR model when supplemented with co integration account for problems of non-stationarity and exogeneity in order to estimate relevant parameters that describe both short and long run equilibrium or stationary relationship, VAR models provide a convenient common framework for examining private investment behavior in a country of this nature. Using a uniform single regression model would amount to imposing strong restrictions on specification and the direction of causality among the variables, thus the need for VAR model,The use of VAR models to study the impact of macroeconomic variables on private capital formation is by no means new. For instance, Mittnik and Neumanna (2001) in a study of six industrial countries and Ghali (1998) used a VAR model in investigating public investment and private investment; Belloc and Vertova (2002) in HIPC used VAR to test complementary relationship. voss (2002) for united state and Canada, Badawi (2003 and 2004) for Sudan and Ndikumana (2005) for South Africa used VAR to test macroeconomic policies and private capital performance. 3.3 Estimation Procedure Investigating the time series properties of data is a precondition to establishing the VAR mode. To test the order of integration of variables, standard tests for unit root such as the Augmented Dickey – Fuller (ADF).Johanson (1991) cointegration test based on the maxeigenvalue test or trace test is used to establish the existence of a long term relationship between macroeconomic policies and private capital formation in Nigeria. Because all the right-hand- side variables in the VAR contain lagged variables, the simultaneity bias is not a concern, and the OLS estimates are as good as GLS estimate. Based on the AIC and SIC (Akaike, 1981) we shall chose the optimal lag length for the VAR estimation. A vector error correction model (VECM) is applied to estimate short run dynamic 24 relationships. VECM is a restricted VAR designed for nonstationary time series that are cointegrated. The VECM has cointegrated facilities built into the model so that it restrict the long term behaviuor of the endogenous variables to converge to their cointegrating relationships while allowing for short term dynamic adjustments. 3.4 Method of Results Evaluation To achieve the first objective of this study, the short-run dynamic VAR result will be used to determine the impact of macroeconomic policies on private capital formation in Nigeria. Effort will be made to interpret the estimated coefficients for the short run dynamic VAR model. For the second objective, the impulse response functions and variance decompositions of the system will be used to draw implications about a VAR. Based on Sim (1980), the impulse response depicts how an endogenous variable responds over time to a single surprise change in itself or in another variable, thereby suggesting evolutionary effects for each variable. If the error terms are uncorrelated, then each depicts the surprise movement (or innovation) in the corresponding dependent variable. But since they are correlated to some degree we shall use the Choleski decomposition, in which the errors are orthogonalzed so that the covariance matrix of the resulting surprise movements is lower triangular, to attribute common effects. This implies a recursive chain of causality among the surprise movements in any given year, so that effects flow only downward, from variables earlier in the causal chain to those later (Todd, 1990).Also, the impulse response function test shall be complimented by the variance decomposition test. The test suggests that forces associated with one variable are major influences on the evolution of another variable. .This test will be used to give vent to the impulse response test The third objective will be accomplished by conducting the granger causality test. The granger causality test sets to determine the causal ordaining of the mediating variables connecting private investment and macroeconomic policies. Granger (1969) starts from the premise that the future cannot cause the present or the past. Note that the direction of 25 causality may depend critically on the number of lagged terms included in the regression. The test is very sensitive to the number of lags used in the analysis. 3.5 The Data The sample consists of annual data from 1970 – 2004 extracted from the central bank of Nigeria statistical bulletin various years, AERC 2005, CBN Annual Reports and Statement of Account for various years. 26 Chapter Four Presentation and Interpretation of Empirical Results 4.1 Result Presentation Most time series data tend to contain infinite variances that are not mean- reverting and lie on the unit circle. Equation estimated from such series result in spurious regression that makes little economic sense. Indeed the loading of the endogenous variable is minuscule when in fact a long -run relationship exists between it and the economic fundamentals driving it. Thus each of the variables would be examined for unit root and co integration. Consequently, the Augmented Dickey – Fuller (ADF), defines the equations for these tests. 4.2 Unit Root Analysis The test for unit root using the Augmented Dickey – Fuller (ADF) indicated that real gross domestic product, private investment, public investment and real exchange rate are non-stationary with one as the order of integration. Domestic credit to the private sector and real interest rate were shown to be stationary series. All tests were significant at both 5% and 1%. The lag length criteria (AIC) did not improve with further increases in the lag length. See table 4.1 below Table 4.1: Unit Root Statistics Variable Adf Critical McKinnon Lag statistic Order integration RGDP -4.928986** -3.639407 0 1 PRIV -9.645069** -3639407 0 1 PUINV -5.798530** -3639407 0 1 DCRP -5.127062* -3.711457 0 0 REXCH -5.395782** -3.63907 0 1 RIR -3.901355* -3.63907 0 0 1** Adf stationary at first difference 1*Adf stationary at level 27 of 4.3 Co-integration Analysis The unit root results conducted above have significant implications for the co integration analysis. The standard Johanson approach, which requires the variables to be integrated of order one, can be implemented. This involves testing whether the matrix has reduced rank. That is to find whether r = (n-1) co integration vectors exist in Here Johansen maximum eigenvalue and trace test is used to determine the number of co integrating vectors for the specification suggested by the selection criteria. The null hypothesis that there is no co integrating vector in the system (Ho: r = 0) is rejected, but the alternative that there exists at most one co integrating vector (Ho: r = 1) is not. From the table below, the estimated eigenvalue and trace test indicated that there are three co integrating vector. There are, therefore three long –run relationships between the variables. See table 4.2 below. Table 4.2: Johanson Co- integration Test Statistics HO:rank = r Maximum Trace 5% critical 5% critical No. of CE(s) Eigenvalue statistic value for max value for eigenvalue trace status HO: r = 0 115.9645 230.19 40.08 95.75 None* HO: r = 1 60.695 114.22 33.877 69.81 At most 1* HO: r = 2 30.71 53.52 27.58 47.856 At most 2* HO: r = 3 15.528 22.81 21.13 29.797 At most 3 HO: r = 4 5.857594 7.288 14.26 15.49 At most 4 HO: r = 5 1.430 1.430 3.84 3.84 At most 5 An asterisk indicates rejection of the null hypothesis at 5% level. 28 Model Results and Discussion 4.4.1 Short-Run Dynamic VAR Result The estimated model (see appendix) shows that private investment at the one period and two period lags were not significant at five percent level of significance. This means that changes in the past does not always trail changes in the actual value of private investment. Private investment is found to respond to gross domestic product at the past period, as real gross domestic product at the one lag was significant at the 5 percent level. This is an indication that past performance of real GDP in is fundamental in determining the performance of private investment in Nigeria. Similarly, public investment at the one lag period has significant influence on private capital formation in Nigeria. Meanwhile, real interest rate at both one period and the second period lags were statistically significant at 5 percent level of significance suggesting the short-run impact of interest rate in desired long-run private capital formation in Nigeria. The estimated real exchange rate and domestic credit to the private sector lagged by one is also significant at the 5 percent level of significance. From the results therefore, if real GDP rose in the previous period by 1 base point it would result in a net effect of 0.971 base points in the current private investment in Nigeria. The above magnitude is large compared to related results found for developing countries. For example, real GDP coefficient appears to be close to unity in Blejer and Khan (1984), equal to 0.46 in fry (1980), between 0.01-0.08 in Ndikumana (2000), 0.002 in Sioum (2002) and nearly 0.9 for Badawi (2004). While a 1 percent rise in one lag period of public investment will contemporaneously lead to approximately 0.63 base points rise in private investment. This result reinforced the findings by Mlambo and Nell (2000) for South Africa that a 10 percent increase in government expenditure results in a 0.24 percent increase in private investment. These results suggest that public investment crowd in private investment in the two countries. Furthermore, Reinikka and Svensson (2002) finds out that a 1 percent increase in public investment result in 0.43 percent increase in private investment in Uganda. 29 Also, interest rate coefficient both for one and two lagged period reported a different result. The result of one lag of interest rate is not consistent with a priori expectation but the estimated coefficient for second lag period of interest produced result that is consistent with conventional economic theory. From the estimated result, interest rate differential would lead to 0.445 base point increases in contemporaneous private investment if the interest rate lagged by one period changes by 1 unit. This result appears to be interesting in light of the considerable theoretical and empirical evidence advocating a positive relationship between investment and interest rate in LDCs. While many researches made significant empirical contributions to establish such a positive relationship there seems to be no lack of an opposite position. With a highly significant negative long-run coefficient of nearly 0.45 for interest rate lagged by two, Nigeria seems to exhibit an interest rate investment nexus similar to those at work in Sudan, Indonesia and Chile. Badawi (2004) reported a long-run coefficient of – 0.10 for Sudan, Chhibber and Shafik (1990) report a long-run coefficient of –2.3 for Indonesia, Solimano(1980) also report a negative long-run coefficient for Chile. Revealing another intriguing result is real exchange rate for Nigeria. The estimated coefficient suggests that a unit increase in exchange rate brings about a contemporaneous increase in private investment by 0.92 base points. The exchange rate and private investment pass through in Nigeria is not in tandem with conventional theory of an inverse relationship between the two. However, this result seems not to be consistent – qualitatively as well as quantitatively – with that reported by Solimano (1980) for the case of Chile over the 1980s. What the above result is implying is that the size of the Nigerian traded goods sector has expanded and depended on imported capital goods. Furthermore, domestic real credit to the private sector reports a positive long-run effect of private investment. This long-run elasticity is highly significant at 5 percent level of significance reporting a large t statistic of around 6.85. With a magnitude of 0.76, real credit seems to have exerted a large impact on private investment in Nigeria than in other developing countries suggesting that credit rationing right have been more severe in Nigeria in comparison to other less developing country's average. Blejer and Khan 30 (1984), using various specifications for the investment equation for a panel of 61 developing countries, estimate a similar result in the range 0.197 – 0.257. Ndikuman (2000), employing a sample of 30 Sub-Saharan. African countries got a result of 0.363, while Badawi (2004) for Sudan came up with, elasticity of 7.14. 4.4.2 Impulse Response and Variance Decomposition The second objective of this study is to determine the responses of private investment to shocks on macroeconomic variables. We shall look at impulse response and variance decomposition under the vector autoregressive model. This will enable us ascertain how the variables under study respond to innovations and to determine the percentage of forecast error decomposition of the dependent variable as accounted for by the lagged endogenous variables. We restrict our interpretations to the impulse response for, and variance decomposition of private investment and real GDP. These are presented in tables’ 4.3, 4.4, 4.5and 4.6 below. Table 4.3 Impulse Response for Private Investment Period PRINV DCRP GDP PUINV REXCH RIR 1. 124146.3 0.0000 0.0000 0.0000 0.0000 0.0000 2. -10243.40 18215.07 7651.54 16005.45 -14581.47 -24105.84 3. 9532.7 17193.64 17524.14 10476.93 -21518.28 -16996.16 4 22522.86 16306.68 22270.64 21758.09 -24458.54 13922.91 5 -1426928 16754.32 22647.32 26027.17 -26660.99 12819.85 6 -3880.72 7304.189 24791.77 31060.12 -19502.65 819.1022 7 15476.35 3051.36 25862.04 38213.43 -13217.32 -352.0971 8 10648.46 4267.09 27330.80 39780.12 -1237213 -1641.492 9 8551.419 4684.837 30496.54 39951.94 -12996.53 -4071.742 10 11874.46 6435.33 33551.37 41625.16 -14506.25 -3189.268 The results suggest that private investment, responds negatively to one standard innovation to its own lagged values in the 2nd, 5th, and 6th year of innovation, but respond 31 positively to domestic credit to private sector, real GDP and public investment both in the short and long run. The result further reveals that private investment responded negatively to one standard innovation on real exchange rate from the 2nd year to the 10th year, with real interest rate responding negatively in the long-run. The result shows thatl real exchange rate and real interest rate does not reflect an effective macroeconomic policy pass through on private investment in Nigeria. The implication of the above analysis is that domestic credit to private sector, real GDP and public investment is an effective medium of shock transmission to private investment in Nigeria. The result is reinforced by the variance decomposition for private investment shown in table 4.4 below 32 Response to Cholesky One S.D. Innov ations ± 2 S.E. Response of PRINV to PRINV Response of PRINV to DCRP Response of PRINV to GDP Response of PRINV to PUINV Response of PRINV to REXCH Response of PRINV to RIR 160000 160000 160000 160000 160000 160000 120000 120000 120000 120000 120000 120000 80000 80000 80000 80000 80000 80000 40000 40000 40000 40000 40000 0 0 0 0 0 0 -40000 -40000 -40000 -40000 -40000 -40000 -80000 -80000 1 2 3 4 5 6 7 8 9 10 -80000 1 Response of DCRP to PRINV 2 3 4 5 6 7 8 9 10 -80000 1 Response of DCRP to DCRP 2 3 4 5 6 7 8 9 10 -80000 1 Response of DCRP to GDP 40000 2 3 4 5 6 7 8 9 10 -80000 1 Response of DCRP to PUINV 2 3 4 5 6 7 8 9 10 1 Response of DCRP to REXCH 300000 300000 300000 300000 300000 300000 200000 200000 200000 200000 200000 200000 100000 100000 100000 100000 100000 100000 0 0 0 0 0 0 -100000 -100000 -100000 -100000 -100000 -100000 -200000 -200000 1 2 3 4 5 6 7 8 9 10 -200000 1 Response of GDP to PRINV 2 3 4 5 6 7 8 9 10 -200000 1 Response of GDP to DCRP 2 3 4 5 6 7 8 9 10 -200000 1 Response of GDP to GDP 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 1 Response of GDP to REXCH 16000 16000 16000 16000 16000 12000 12000 12000 12000 12000 12000 8000 8000 8000 8000 8000 8000 4000 4000 4000 4000 4000 0 0 0 0 0 0 -4000 -4000 -4000 -4000 -4000 -4000 -8000 -8000 -8000 -8000 -8000 -8000 -12000 1 2 3 4 5 6 7 8 9 10 -12000 1 Response of PUINV to PRINV 2 3 4 5 6 7 8 9 10 -12000 1 Response of PUINV to DCRP 2 3 4 5 6 7 8 9 10 Response of PUINV to GDP 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 1 Response of PUINV to REXCH 6000 6000 6000 6000 6000 4000 4000 4000 4000 4000 4000 2000 2000 2000 2000 2000 2000 0 0 0 0 0 0 -2000 -2000 -2000 -2000 -2000 -2000 -4000 1 2 3 4 5 6 7 8 9 10 -4000 1 Response of REXCH to PRINV 2 3 4 5 6 7 8 9 10 -4000 1 Response of REXCH to DCRP 2 3 4 5 6 7 8 9 10 -4000 1 Response of REXCH to GDP 2 3 4 5 6 7 8 9 10 Response of REXCH to PUINV 2 3 4 5 6 7 8 9 10 1 Response of REXCH to REXCH 100 100 100 100 100 50 50 50 50 50 0 0 0 0 0 0 -50 -50 -50 -50 -50 -50 -100 2 3 4 5 6 7 8 9 10 -100 1 Response of RIR to PRINV 2 3 4 5 6 7 8 9 10 -100 1 Response of RIR to DCRP 2 3 4 5 6 7 8 9 10 -100 1 Response of RIR to GDP 2 3 4 5 6 7 8 9 10 Response of RIR to PUINV 2 3 4 5 6 7 8 9 10 1 Response of RIR to REXCH 15 15 15 15 15 10 10 10 10 10 5 5 5 5 5 0 0 0 0 0 0 -5 -5 -5 -5 -5 -5 -10 -10 -10 -10 -10 -10 -15 -15 -20 1 2 3 4 5 6 7 8 9 10 -15 -20 1 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 -15 -20 1 3 5 -15 -20 1 2 Response of RIR to RIR 10 -20 10 -100 1 15 -15 9 Response of REXCH to RIR 50 1 8 -4000 1 100 -100 7 Response of PUINV to RIR 6000 -4000 6 -12000 1 Response of PUINV to PUINV 5 4000 -12000 1 4 Response of GDP to RIR 16000 -12000 3 -200000 1 Response of GDP to PUINV 2 Response of DCRP to RIR -20 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 Table 4.4 Variance Decomposition for Private Investment Period S.E PRINV DCRP GDP PUINV REXCH RIP 1. 124146.3 100.00 0.0000 0.0000 0.0000 0.0000 0.0000 2. 130220.7 91.5069 1.9565 0.3452 1.5107 1.2538 3.4268 3. 130220.7 84.31018 3.38907 1.97508 1.9767 3.6497 4.6993 4. 145077.1 96.56722 4.0937 4.0937 3.9879 6.05243 5.0544 5. 153613.6 63.74027 4.9752 5.8249 6.4277 8.4107 5.2047 6. 160081.1 63.74027 4.3887 9.4326 9.6835 9.229 4.7953 7. 16786.1 58.8159 4.3887 9.4326 13.9885 9.0129 4.3613 33 7 8 9 10 8. 1754865 54.1863 4.0749 11.0567 17.9384 8.7441 3.9994 9. 191999.0 45.8475 3.5760 14.8133 24.01564 8.3338 3.4137 Obviously, the variance decomposition shows that private investment explains 100 percent of its variance in the first period while other lagged endogenous variables explain zero percent. But with the passage of time, the influence of private investment decreases while that of domestic credit to private sector, real GDP, public investment, real exchange rate and interest rate starts to increase. This suggests that domestic credit is very effective in the medium term, but decreases in the 9th and 10th period. Real GDP and public investment explains more of its variance in the long-run as the values maintained an upward trend, while real exchange rate and interest rate becomes more effective in the medium term as more of the variance is explained in 4th to 7th year for both variables. The implication of the above result is that domestic credit; real GDP and pubic investment do explain significant part of private investment in the long run with exchange rate and interest rate showing no significant impact. This result still reinforces our findings on the short run dynamic VAR estimate conducted above. Going by the long run relationship established by the neoclassical flexible accelerator model that there exist a significant long run relationship between output and investment; we next examine the impulse response function and variance decomposition for real GDP in tables 4.5 and 4.6 Table 4.5 Impulse Responses for GDP Period PRINV DCRP GDP PUINV REXCH RIR 1. -792.908 -2842.079 6558.862 0.0000 0.0000 0.0000 2. -707.549 2796.014 5322.02 1165.934 -2094.895 -379.6621 3. 761.229 5212.156 3997.829 246.1080 -2898.851 -844.8999 4. 1327.150 4317.241 3227.683 2343.696 -3282.852 -373.7757 5. 594.6124 3040.100 3059.980 4253.373 -3736.149 465.7742 6. 594.7096 1643.302 3574.802 5607.642 -3556.694 954.8808 34 7. 810.822 729.4939 4223.745 6620.312 -2967.109 769.1336 8. 1313.666 423.4418 4803.117 7177.602 -2388.695 100.654 9. 1910.387 549.2653 5333.940 7491.106 -2116.413 -477.7156 10. 2192.062 972.3175 5848.947 7745.336 -2273.113 -695.2243 The response function shows that the response of real GDP to an innovation in private investment is negative between the 1st and second period but became positive with an increasing influence over the long run. The response of real GDP to innovation in domestic credit to the private sector is negative in the first period but assumed a positive value afterward. The positive influence was more in the long run. The response to innovation in lagged GDP was positive all through the period with an increasing influence over the long run. The first two periods impacted more on real GDP. The result is in tandem with economic a priori expectation of a positive relationship between real GDP and private investment. The response of real GDP to innovation in public investment shows a positive impact both in the short and long run with an increasing influence over the long run. That of GDP to innovation in real exchange rate and real interest has a negative impact both in the short and long run. These findings are supported the result of variance decomposition in table 4.7 below. Table 4.6 Variance Decomposition for GDP S.C PRINV DCRP RGDP PUINV REXCH RIR 1. 7191.994 1.215477 15.61614 83.1684 0.0000 0.0000 0.0000 2. 9708.716 1.198110 16.86320 75.68771 1.4422 4.6558 0.01529 3. 1213.18 1.161140 29.26069 59.3381 0.09648 8.6922 0.5830 4. 13942.50 1.785707 31.7399 50.2812 3.5561 12.1244 0.5132 5. 15672.25 1.556754 28.8831 43.6068 10.1800 15.2788 0.4945 6. 17502.95 1.328666 24.03856 39.1332 18.4264 1637910 0.69411 35 7. 19457.82 1.248748 19.59156 36.3770 26.4861 15.5786 0.7179 8. 21466.62 1.400465 16.13538 34.8938 32.9408 14.0376 0.5920 9. 23538.10 1.823534 13.47480 34.1575 37.5266 12.4840 0.5336 10. 25683.52 2.260052 11.46096 33.8754 40.6133 11.2688 0.5214 The result of variance decomposition in the table above shows that private investment explains a significant proportion of real GDP. Domestic credit to the private sector also explains a significant proportion of GDP both in the short and long run, while real exchange rate do not explains any significant proportion of real GDP in the short run, but reveal a significant long run impact on GDP. The result also reveals that domestic credit to the private sector and lagged real GDP have a significant impact on private capital formation in Nigeria. 36 Variance Decomposition Percent PRINV variance due to PRINV Percent PRINV variance due to DCRP Percent PRINV variance due to GDP Percent PRINV variance due to PUINVPercent PRINV variance due to REXCH Percent PRINV variance due to RIR 100 100 100 100 100 100 80 80 80 80 80 80 60 60 60 60 60 60 40 40 40 40 40 40 20 20 20 20 20 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 20 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Percent DCRP variance due to PRINV Percent DCRP variance due to DCRP Percent DCRP variance due to GDP Percent DCRP variance due to PUINVPercent DCRP variance due to REXCH Percent DCRP variance due to RIR 100 100 100 100 100 100 80 80 80 80 80 80 60 60 60 60 60 60 40 40 40 40 40 40 20 20 20 20 20 0 0 1 2 3 4 5 6 7 8 9 10 Percent GDP variance due to PRINV 0 1 2 3 4 5 6 7 8 9 10 Percent GDP variance due to DCRP 0 1 2 3 4 5 6 7 8 9 10 Percent GDP variance due to GDP 20 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Percent GDP variance due to PUINV Percent GDP variance due to REXCH 1 90 90 90 90 90 90 80 80 80 80 80 80 70 70 70 70 70 70 60 60 60 60 60 60 50 50 50 50 50 50 40 40 40 40 40 40 30 30 30 30 30 30 20 20 20 20 20 20 10 10 10 10 10 0 0 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 Percent GDP variance due to RIR 10 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Percent PUINV variance due to PRINV Percent PUINV variance due to DCRP Percent PUINV variance due to GDP Percent PUINV variance due to PUINVPercent PUINV variance due to REXCH Percent PUINV variance due to RIR 80 80 80 80 80 80 70 70 70 70 70 70 60 60 60 60 60 60 50 50 50 50 50 50 40 40 40 40 40 40 30 30 30 30 30 30 20 20 20 20 20 10 10 10 10 10 0 0 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 20 10 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Percent REXCH variance due to PRINVPercent REXCH variance due to DCRP Percent REXCH variance due to GDPPercent REXCH variance due to PUINV Percent REXCH variance due to REXCHPercent REXCH variance due to RIR 100 100 100 100 100 100 80 80 80 80 80 80 60 60 60 60 60 60 40 40 40 40 40 40 20 20 20 20 20 0 0 1 2 3 4 5 6 7 8 9 10 Percent RIR variance due to PRINV 0 1 2 3 4 5 6 7 8 9 10 Percent RIR variance due to DCRP 0 1 2 3 4 5 6 7 8 9 10 Percent RIR variance due to GDP 20 0 1 2 3 4 5 6 7 8 9 10 Percent RIR variance due to PUINV 0 1 2 3 4 5 6 7 8 9 10 Percent RIR variance due to REXCH 1 80 80 80 80 80 80 70 70 70 70 70 70 60 60 60 60 60 60 50 50 50 50 50 50 40 40 40 40 40 40 30 30 30 30 30 30 20 20 20 20 20 10 10 10 10 10 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 3 4 5 6 7 8 9 10 20 10 0 1 2 Percent RIR variance due to RIR 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 4.4.4 Granger Causality Test The third objective of this study is to determine the causal ordaining of the mediating variables connecting private investment and macroeconomic policies. To achieve the above objective, Granger causality test is indeed expedient. Granger (1969) starts from the premise that the future cannot cause the present or the past. Note that the direction of causality may depend critically on the number of lagged terms included in the regression. The test is very sensitive to the number of lags used in the analysis. The Grange causality test is guided by the following decision rule: 37 Hypothesis Ho: Bj =0 Against Hi: Bj =o Decision Rule Reject the null if the computed F-value s greater than critical F-value at 5% level of significance otherwise accept the null. Based on the above criteria, we present the result of Granger causality test in table 4.7 below Table 4.7: Result of Granger Causality Test Direction of causality Computed F Critical F value Decision value RGDP PRINV at 5% PRINV 1.32941 3.63 Do not reject the null hypothesis 072133 3.63 Do not reject the null hypothesis 1.12226 3.63 Do not reject the null hypothesis RGDP PUIN PRINV PUINV 1.20891 3.63 Do not reject the null hypothesis REXCH PRINV 0.78644 3.63 Do not reject the null hypothesis PRINV REXCH 0.63599 3.63 Do not reject the null hypothesis PRINV RIP PRINV 2.74570 3.63 Do not reject the null hypothesis PRINV RIP 2.72907 3.63 Do not reject the null hypothesis PRINV 1.35649 3.63 Do not reject the null hypothesis DCRP PRINV DCRP PUINV PUINV 4.46975 9.07287 Reject the null hypothesis 3.63 Reject the null hypothesis RGDP PUINV 0.73414 REXCH RGDP 0.29435 3.63 Do not reject the null hypothesis RGDP REXCH 1.73260 3.63 Do not reject the null hypothesis Do not reject the null hypothesis 38 RIR RGDP 0.35234 3.63 Do not reject the null hypothesis RGDP RIP 1.63784 3.63 Do not reject the null hypothesis RGDP 6.8569 3.63 Reject the null hypotheses DCRP 0.77867 3.63 Do not reject the null hypotheses 1.44289 3.63 Do not reject the null hypothesis REXCH 0.203.5 3.63 Do not reject the null hypothesis PUINV 3.99620 3.63 Reject the null hypothesis RIR 1.21362 3.63 Do not reject the null hypothesis PUINV 2.52475 3.63 Do not reject the null hypothesis DCRP 16.7718 3.63 Reject the null hypothesis REXCH 0.74274 3.63 Do not reject the null hypothesis DCRP RGDP REXCH PUINV RIR PUINV DCRP PUINV RIR PUINV REXCH DCRP 1.83286 3.63 Do not reject the null hypothesis DCRP REXCH 0.33069 3.63 Do not reject the null hypotheses REXCH DCRP 0.37299 3.63 Do not reject the null hypothesis DCRP RIR 0.70438 3.63 Do not reject the null hypotheses RIR DCRP 2.69912 3.63 Do not reject the null hypotheses Granger causality test result conducted above indicates that there is a unidirectional causality between private investment and domestic credit to private sector, public investment and real GDP, real interest rate and public investment, public investment and domestic credit to the private sector. The unidirectional causality among these variables is based on the rejection of the null hypothesis that their exist no causality among the variables. The result further reveled that the unidirectional causality between these variables is an indication of mutual relationship between them. The result further shows that the null hypotheses are not rejected at 5% level of significance for the other variables indicating the absence of mutual relationship between them. The implications of the causality test conducted above include that: (1) domestic credit to private sector has been established to be the main linkage variable between private investment and the other macroeconomic variables: (ii) that the channel of transmission 39 DCRP is: PINV PUIN RGDP REXCH RIR The current study gives support to the arguing for credit expansion to the private sector. Literature on private investment in the developing countries has also established that their exist a positive relationship between domestic credit and private capital formation. 4.5 Evaluation of Hypothesis Based on the estimated result, we now evaluate the hypothesis of this study. Test of Hypothesis one Ho: Macroeconomic policies have no impact on private capital formation in Nigeria Hi: Macroeconomic policies have a significant impact on private capital formation in Nigeria CONCLUSION Based on the result of short run dynamic model investigated above, we reject the null hypothesis and conclude that macroeconomic policy variables have significant impact on private capital formation in Nigeria Test of Hypothesis Two Ho: Private investment has no significant impulse from macroeconomic variables in Nigeria Hi: Private investment has a significant impulse response from macroeconomic variables in Nigeria CONCLUSION Result of impulse responses conduct in table 4.4 shows that there is a significant impulse response among three variables and private investment. These variables include Private investment lag by one, domestic credit to the private sector and real GDP. The result further reveals a partial response between real exchange rate and real interest rate. Base on findings, we reject the null hypothesis and uphold the alternative hypothesis. 40 Test of hypothesis three Ho: The mediating variables connecting private investment and macroeconomic policies have no causal ordering in Nigeria. CONCLUSION The result of the pair wise Granger causality test conducted in table 4.7 above leads to the rejection of the null hypothesis since there exist a significant causal ordering of macroeconomic variables and private capital formation in Nigeria. 4.6 Policy Implications of Findings The result of the various test conducted above revealed an interesting outcome for policy prescription in Nigeria. Domestic credit to the private has proved to have a more significant impact on private investment in Nigeria than the other macroeconomic policy variables. Based on the various test conduct, the variable plays an outstanding role in influencing private investment in Nigeria. This brings us to the negative impact of credit rationing on investment. Real GDP also play an important role in private capital formation in Nigeria. Results showed that real GDP reports a significant direct long run effect on private investment over the period of the study. This finding provides evidence to the validity of the hypothesis that the accelerator principle does explain private investment in Nigeria. Result of public investment on the various parameters of assessment showed that public investment crowd in private investment in Nigeria. This lends support for rapid growth of public investment for they play a significant role in the private sector production process. Results based on exchange rate revealed that the concept of devaluation does not bring about the much-expected growth in private investment in Nigeria. Findings from this study lend support to the debate on the appropriateness and relevance of devaluation policy on investment growth. These findings are incongruous with the conventional view that devaluation helps in correcting distortions and generate incentives for the growth of the private sector. Results on real interest rate showed that the variable does not play a prominent role in private capital formation in Nigeria but has been a disincentive to the growth of the private sector. 41 Chapter Five Summary, Policy Recommendation and Conclusion 5.1 Summary of Findings This work is an attempt to empirically investigate the impact of macroeconomic policies on private fixed capital formation in Nigeria within a co integrated vector autoregressive framework. As earlier stated, private investment has been established to be a key to economic growth through sound macroeconomic policies. To achieve the target of achieving economic growth of about 7-8 percent, a good understanding of the impact of macroeconomic polices on the growth of private sector is very expedient owing to the fact that Nigeria economy has been experiencing serious structural imbalance, low growth trap, characterized by a low savings – investment equilibrium. The result of short run dynamic model shows that some of the macroeconomic variables like real GDP, domestic credit to the private sector, public investment, real interest rate lagged by two years and real exchange rate were statistically significant at the 5 percent level of significance. Real GDP is statistically significant and impact positively on private capital formation in Nigeria over the study period. The result upholds the validity of the accelerator principle that there exist a positive long run relationship between real GDP and private investment in Nigeria. Domestic credit to the private sector also reports a significant positive effect on private investment. Public investment reports a crowd in effect on private investment in Nigeria. This finding is not in tandem with literature that public investment crowd out private investments in LDC. Rather it bolsters the performance of private sector in Nigeria. The real interest rate reported an interesting result. The variable reported a significant negative impact on private capital formation in Nigeria. This shows the deleterious impact of high user cost of capital on investment growth in Nigeria. The real exchange rate also reports a negative long run impact on private investment. Depreciation of Nigeria currency has impacted negatively the formation of private capital over the study period by increasing the imported capital requirements of private investors. The deleterious impact of depreciation in the domestic currency on private sector investment contributes to the debate on the appropriateness 42 and relevance of devaluation policy a debate that may be widened by adding a neoclassical dimension (as far as investment literature is concerned), considering the potential impacts of devaluation on the real user cost of capital, and thereby on investment and growth. This dimension may stand in conflict with the conventional view that devaluation brings about the growth of private capital formation through correcting distortions and generating incentives for the private sector (particularly in the tradable goods sector). To achieve the third objective of this study which is the determination of the causal ordering of the mediating variables connecting private investment and macroeconomic policies, the granger causality test was conducted. The result reveals a unidirectional causality between private investment and domestic credit to the private sector, between public investment and real GDP, between real interest rate and public investment and between public investment and domestic credit to the private sector. The unidirectional causality among these variables is an indication of significant mutual relationship between the variables and private capital formation. The result of the finding reveals further that domestic credit to the private is a more effective policy variable than the other variables on private capital formation in Nigeria. 5.2 Policy Recommendations The empirical results and the analysis conducted revealed the best approach to improving the performance of private investment in Nigeria. Domestic credit to the private sector has been reported to play a prominent role in the growth of the private sector in Nigeria. This provides the platform for arguing for credit expansion to the private sector. The expansion of the banking sector loanable fund to the private sector should be at the heart of the monetary policy design in Nigeria. The idea of exercising tight measures in the process of constraining domestic credit should be given attention and the conflict of curbing inflation and credit expansion to the domestic economy can be resolved by introducing varieties of monetary tools and instruments. Furthermore, the ratio of credit to GDP should be reviewed upwards to boost economic growth. 43 The growth of the public investment has been reported to play a complimentary role on the growth of the private sector in Nigeria. In light of these findings, effort should be made to boost the development of public sector especially in the sectors that act as catalyst to the growth of the private sector. Policy prescription could be widened to include, in addition to targeting the volume of credit to private sector the terms on which banking sector advances are extended to private investors. This is directly related to the cost of funds dilemma in the sense that governments in developing countries pursue policies with a view to make loans expensive in the process of restricting domestic credit. The negative impact of real interest rate on private investment poses very important qualitative implications for financial sector efficiency. The monetary authority needs to be proactive in the management of interest rate since user cost of capital has been established to be on the high side in Nigeria in comparison to other developing countries. Efforts should be made to see that interest rate do not derail the target of increasing investment to about 30 percent of GDP required to unleash a poverty reduction of at least 7 – 8 percent by 2015. The stability of exchange rate is very expedient if the expected growth of the economy through the private sector is to be achieved. To achieve exchange rate stability, efforts should be intensified to wipe off all unofficial parallel markets or the so-called black market since they facilitate not only faster depreciation of the Naira through round tripping but also facilitate huge capital flight and illegal transfer of funds. 5.3 Conclusion Empirical investigation reveals that macroeconomic policies like, interest rate policy, exchange rate policy, the size of the public sector, domestic credit policy and the real GDP growth plays a prominent role in the performance of private capital formation in Nigeria. The results of both the dynamic short run model, impulse response and pair wise Granger causality test revealed that domestic credit to the private sector plays a more prominent role in influencing the growth of the private sector in Nigeria. This study revealed that Nigeria’s private sector is still inertia and below the average for sub- 44 Saharan Africa and also below the 30 percent GDP growth ratio needed to reduce poverty by half in Nigeria by 2015. Base on our findings, we agree that studies on private investment in Nigeria still remain open for future researcher. One major limitation of this work is its inability to incorporate investment under conditions of uncertainty. It is recommended that further researchers in this area should look at this area. In addition, carrying out the study under a structural vector autoregressive framework would necessitate long run restrictions that would completely reflect the systemic behaviour of the data generating process. So alternative model should be considered 45 REFERENCES Abel, A.B. 1983. “Optimal Investment under Uncertainty”. The American Economic Review, No1.73. 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