The Impact of Fiscal Policy Variables on Private Investment in Nigeria

Motivated by the need to avoid potential parameter bias associated with previous empirical researches, the current study conducted a disaggregated inquiry of the individual impact of scal policy variables on private investment in Nigeria. The empirical investigation adopted the Autoregressive Distributed Lag method which allows for the simultaneous estimation of the short and long-run relationships between variables, removing the problems associated with excluded variables and the existence of autocorrelation. The method was applied to time series data spanning the period 1980-2017, generated using the quantitative and ex- post facto research design. The bounds test results established a co-integrating relationship between private investment and its selected determinants. The empirical ndings conrmed that various components of direct taxes retarded the growth of private investment while indirect taxes stimulated the growth of private investment. Government capital spending had a favourable and statistically relevant impact on private investment while public external debt suggested a deleterious effect of inhibiting private investment both in the long and short run. The study recommended harmonizing tax policies to curb multiple taxes and high cost of doing business; and major investment in infrastructures to improve private investment and affect long-term growth positively.

The productive and effective use of private resource is a major determinant of sustainable growth in any economy. The revival of market tools as a basis for economic management and the speedy globalisation of economic activities led to a change in emphasis, from government to private sector-led growth strategies, particularly in developing countries. The new paradigm emphasises the hegemony of market forces in the economy, a decrease in public sector production activities and a rede ned role of the public sector in the development process under the guiding principle that the public sector should commit its resources to those areas that sustain private investment rather than substitute them (Hermes & Lensink, 2001). In recent decades, Nigeria's private investment has been poor. The policymakers have expressed signi cant concern that investment is a key variable affecting poverty reduction and sustainable growth.
Among other things, a publicly-led development policy was motivated by the oil boom of the 1970s. In order to guarantee government a growing degree of in uence over its own resources, public sector supremacy was also dominant. In conjunction with discontent with government enterprise e ciency, the decline in government revenues resulting from the economic crisis of the 1980s forced the country to implement the Structural Adjustment Programme (SAP) in 1986 (Duruechi & Ojiegbe, 2015). Since the need for a change of approach has been recognised, the country has shifted focus to growing the private sector. The much-needed private investment was driven by SAP and other policies. Privatization and commercialization policies have become the order of the day in an attempt to stimulate the private sector (Adejare & Akande, 2017). Until now, these policies have played a major role in rede ning the Nigerian economy.
Fiscal policy includes using taxes, government spending to control the trend of economic activities, aggregate demand, production, employment and growth (Ugwuanyi & Ugwunta, 2017). A country's scal policy encourages or impedes the growth of private investment depending on their design and execution.
In the economy. An expansionary scal policy will crowd-out private investment. Productive government spending acts as a stimulant to maximise pro t for investors, prompting them to expand their businesses (Barro & Salai-.Martin, 1992). Government spending on infrastructure, such as transport and communication networks, the provision of electricity and other energy sources facilitates the e cient access of private investor's to productive regions and acts as essential ingredient for growth. On the other hand, if funded by raising taxes or borrowing, public expenditure will crowd-out private investment. High tax burden lowers disposable income for individuals, leading to lower spending, lower savings and therefore lower investment. Therefore, it is important to establish an optimal income tax rate that maximises tax revenue and ensures optimal growth in private investment.
There is a crowding out impact on private investment when borrowing to fund government spending. The cost of borrowing rises as the public and private sectors compete for funds in the capital market, which serves as a deterrent for private investors. In addition, borrowing-funded government spending means that further taxes would be levied to liquidate the debt in the future, which poses an obstruction to private investors (Medee & Nembee, 2011). When government borrowing is expanded to fund higher government expenditure or tax cut, private investment is crowded out by higher interest rates. Long term growth of prospective output can be impaired by a decline in xed investment by corporations. While higher government expenditure can help in improving infrastructure for promoting private investment, the spike in government spending if not matched by increased government revenues and equivalent improvement in real GDP, can generate public debt and in ation. Moreover, the higher public spending may put an upward pressure on the interest rate and discourage private investment. The crowding out effect is weakened by the fact that government expenditure through the multiplier increases the demand for private sector goods and thus boosts xed investment through the accelerator effect (Kengdo et al., 2020).
Given the important role played by private investment both in contributing to GDP growth and in its ability to e ciently allocate and employ resources, Gitahi et al. (2013) argued that developing countries in pursuit of sustainable growth and poverty reduction should aim and maintain level of at least 25 percent of GDP for private investment. Bage (2003), writing on the Asian countries experiences found that investment rates of between 20 and 25 percent could yield growth rate of between 7 and 8 percent. While China has an average private investment as a percentage of GDP ratio of 46 percent between 1993 and 2014, Nigeria's average for the same period was less than 15 percent (Nigerian Investment Promotion Commission, 2018). This percentage is below the levels being experienced in most Sub-Saharan African economies and which is needed to achieve higher growth rates (World Bank, 2015). Despite the substantial increase in government scal operations in recent years aimed to achieving increased private sector-led growth, the stylized fact in Nigeria showed that the rate of growth of private investment has been decidedly unimpressive and has continued to stagnate (Ogunjimi, 2019).
The great depressions of the late 1930s and early 1940s brought with it a high degree of government involvement in economic management and scal policy instruments are among the policy choices readily employed. What remains open to dispute, however, is what kind of relationship exists between scal policy variables and private investment? This controversial eld of economic analysis has been explored in the present study by disaggregating scal policy variables into their respective components and evaluating their short and long-run impact on private investment in Nigeria using annual time series data from the1980-2017. Using data-driven economic models to describe the relationships between scal policy variables and private investment in Nigeria would allow policymakers implement their methodical analysis in a much more structured, informed and quanti ed manner for improved policy decisions. The remaining part of the paper is structured as follows: section two presents the theoretical links between investment and scal policy variables followed by section three which focuses on the methodological issues, model speci cation, estimation techniques and procedures that guided the study. Section four addresses the ndings and interpretation of the results followed by section ve which concludes the study and provides policy recommendations. assumes that government would prefer to raise as much tax revenue as possible, regardless of the tax-induced productivity losses. The curve describes the theoretical illustration of the relationship between tax-raised government revenue and all possible tax rate. It re ects the volume of tax revenue collected at zero percent and 100 percent severe tax rates. This theory believes that a 100 percent tax rate does not increase government revenue in the same way that zero percent rate of tax does not boost government revenue. This is because, a reasonable taxpayer is no longer motivated to earn more money at a 100 percent tax rate. Thus, government revenue would be 100 percent of nothing. Therefore, it follows that there must be at least one tax rate in-between where tax revenue is maximum (Fave & Dabari, 2017).
The Supply side economists opined that tax rates should generally be kept low and that policymakers will boost the economy in a way that produces more employment than regular government spending. By leaving more money in the free market, the expectation is that businesses will invest money more effectively and contribute more to economic growth. At a time, most economists adopted a Keynesian approach to solving the problem of low aggregate demand, recommending more government spending to increase aggregate demand for products, Laffer countered that the problem was not weak demand.
Rather, the burden of heavy taxes and government regulations created inhibitions to production, which depressingly impacts government revenue (Onyinyechi et al., 2016). Laffer contended that the greater the proportion of income or pro ts collected in the form of taxes from an individual or company, the lesser the willingness to work harder or invest more in the business. A corporation is more likely to nd ways to safeguard its capital from taxes or to move all or part of its activities broad. Investors are less likely to risk their capital if a larger proportion of their pro ts is taken in tax. When workers see increasing portion of their earnings due to increased efforts on their part, collected as taxes, they will lose the encouragement to work harder. For every type of tax, there is a threshold rate above which the motivation to produce more diminishes, thereby reducing the amount of revenue the government receives (Omodero & Alpheaus, 2019).

2.2: Investment Theories
The theoretical literature on investment maintains that scal policy can either crowd-in or crowd-out investment depending on how this policy is designed and implemented. Though various theories such as the acceleration theory, neoclassical theory, Tobin's Q theory, etc. explaining the determinants of investment exists in the literature, this paper is limited to a review of only the acceleration theory of investment. Clark (1917) explained that demand for capital uctuates, not with the size of demand for the nished products, but rather with the acceleration of that demand. The accelerator theory states that increasing a company's productivity rate will necessitate a corresponding increase in capital stock. The basic version of this theory proposes that transformation in capital stock is a multiplier function of a change in output.

2.2.1: Accelerator Theory of Investment
Thus, the basis of investment is adjustment in output. The theory advocates that the demand for machinery and factories is derived from the demand for products. Therefore, if the demand for products generated by capital equipment is to increase and the current capacity cannot accommodate this anticipated rise in demand, new investment in plant and machinery would be needed to increase production. Changes in production level therefore is positively correlated with the level of business investment as investment is presumed to respond instantaneously and totally to changing market conditions (Gitahi et al., 2013).
The accelerator theory advocates that as demand or pro ts rises in an economy, so does investment made by businesses. It implies that when demand echelons result in excess demand, companies have 2 options on how to satisfy demand. They either raise prices to cause demand to decrease or increase investment to balance demand (Chenery, 1952). The theory argues that most businesses elect to increase output and increase their pro ts. The theory further describes how this growth attracts more investors, which in turn accelerates growth (Treadway, 1971). But since the model overlooks the effects of volatility, business aspirations, pro ts, nancial factors and capital expenses on investment, it has been updated over time into the exible, crowding-in and crowding-out accelerator theory of investment.
The Keynesian crowding-in and Classical crowding-out acceleration theories are the major in uences relating scal policy variables to private investment in an economy. The Keynesian crowding-in theory presupposes the short-term, underemployment production level with uncertainty in an economy (with aggregate demand falling short of aggregate supply, that is, excess capacity). The theory also presumes that due to this excess capacity, savings and investment are interest rate inelastic. Keynes theorized that scal expansion (lowering of tax rates) would increase the disposable income of taxpayers and boost investment in the economy which could further lead to more growth in the economy. The Keynesian economists maintained that scal expansion have the proclivity to increase aggregate demand for private sector goods through the scal multiplier, thereby stimulating the growth of private investment (Omojolaibi et al, 2016).
The Classical crowding-out acceleration theory of investment supposes a long-term economy, functioning at full employment equilibrium level with no excess capacity, thus, investment and savings are highly interest rate elastic (Twine et al., 2015). The Classical economists reasoned that government active intervention in the management of the economy using expansionary scal policy, might result in increased interest rates, lower disposable income and higher wages all of which reduces the pro tability of businesses and by extension business investment. This may consequently discourage the growth of businesses and decrease the production level in an economy (Gitahi et al., 2013). The classical economists believed that while government involvement in economic management has an in uence on production, such impact is only momentary and in the long run. Its adverse side effect of discouraging private investment does more harm than good to the economy, thereby, rendering scal policy variables ine cient and counter-productive in promoting private investment (Omojolaibi et al., 2016).

3: Research Methodology
Page 7/20 The methodology for the study was discussed under the following sub-headings: research design, nature and sources of data, speci cation of the empirical model and estimation procedure.

Research Design
The purpose of a research design is to certify that the information gathered allows the researcher to effectively address the research problem as logically and unambiguously as possible. Acquiring information relevant to the research problem in social science research, typically includes determining the type of facts required to test a theory, to evaluate a programme, or accurately characterize and evaluate context related to an observable phenomenon. This study adopted the quantitative method and descriptive research design using already existing data to provide empirical answers to the research problems.

Nature and Sources of Data
The data for this study which are purely secondary were extracted from the Federal Inland Revenue

3.4: A Priori Expectation from the Model
The a priori expectations about the signs of the coe cients of the empirical model follow naturally from the analysis of the taxation and investment theories discussed in the theoretical framework. From theoretical literature, the study expects the signs of the coe cients of the various tax revenues to be positively or negatively related to GFCF. That is, β 1 , β 2, β 3 , and β 4 = > or < 0. β 5 and β 6 are the disaggregated coe cients of government expenditure while β 7 and β 8 are the disaggregated parameter coe cients of public debts. The study expects the sign of the coe cients of β 5 to be positive while β 6 is expected to be negatively related to GFCF. From theoretical literature, the coe cients of public debt are expected to be positively or negatively related to GFCF.

Estimation Procedure
The study uses the Autoregressive Distributed Lag (ARDL) approach to co-integration proposed by Pesaran & Shin (1999) and Pesaran, Shin & Smith (2001) to empirically analyse the long and short-run impact of scal policy variables on economic growth in Nigeria. This approach presents three signi cant advantages over the two alternatives commonly used in the empirical literature: the single-equation technique suggested by Engle & Granger (1987) and the maximum likelihood approach proposed by Johansen (1991Johansen ( , 1995 which are based on a system of equations. First, the ARDL bounds testing approach allows the analysis of long-term relationships between variables in a model to be achieved without the threat of producing false regressions, irrespective of whether they are stationary at levels, I(0), or stationary at rst difference, I(1), or mutually co-integrated. Second, the ARDL method allows for the simultaneous estimation of the short-run and long-run components, eliminating the problems associated with omitted variables and the presence of autocorrelation. Finally, the short and long-run parameters estimated using this approach are consistent in small samples. In addition, different optimal lags can be used for different variables as they enter the model, which is not applicable in the standard co-integration test. To use this approach, the study rst ensure that none of the variables in the model are I(2), as such data will invalidate the methodology. Then perform a bounds test to see if there is evidence of a long-run relationship between the variables and if the outcome is positive, then the study estimates a long-run levels model, as well as a separate unrestricted ECM. Following these, estimate the equation and ensure the errors of each model are serially independent and stable.

4: Results And Discussions
This empirical research aims to deliver fresh insights into the effect of scal policy variables on private investment based on a country-speci c context or background. This segment of the paper presents the results and addresses the research ndings.

Test of Stationarity of Study Variables
Prior to investigating co-integration, researchers effect unit root test on the series under study to examine the stationarity properties of time series variables. The conventional method of Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests were adopted to ascertain the stationarity status of the study variables. The results of the ADF and PP unit root tests are presented in table 1. Notes: a, b and c denotes the rejection of the null hypothesis at 1%, 5% and 10% signi cance levels respectively while n denotes Not Signi cant.
From the results presented in table 1, it is manifest that the ADF and PP unit root tests produced similar results with GFCF, Log of PPT, CIT, PIT, CED, GCE and GRE achieving stationarity only after rst difference while the Log of GDD and PED were stationary at levels. Based on these results, the study can correctly conclude that none of the study variables was integrated of order two. Moreover, the study variables have a mixed order of integration, that is, I(0) or I(1), which underlines the signi cance of using an ARDL bound testing approach to determine co-integration. Since all the study variables are a combination of I(0) and I(1) and no variable is I(2), the researcher is therefore certain that the co-integration analysis using the ARDL approach will not yield spurious regression results.

4.2: Bounds Test to Co-integration
The existence of co-integration between the regressand and regressors was assessed using the bounds testing approach. This required testing for the joint signi cance of lagged level variables involved in the model using the F-test at its optimal lag length since the procedure is very sensitive to the appropriate lag length. The observations in the study are annual and sample size is 38 with 9 parameters. As a result of the small number of observations and the need to save the degrees of freedom, the study selected a maximum lag length of 2 though the ARDL approach does not require symmetry of lag length. The results obtained from the ARDL bounds testing approach and the estimated F-test are summarised in   1, 0, 1, 1, 0, 0, 0, 0 Source: Researcher's E-Views 9.5 Computation. Table 2 indicated that the calculated F-statistic value of 6.9639 is greater than the upper bound critical value of 4.10 at one percent signi cance level, evidencing the fact that a long-run relationship exists between the study variables. This means that the null hypothesis of no co-integration between scal policy variables and private investment could be safely rejected at one percent level of signi cance suggesting that any short-run deviation in their relationships would return to equilibrium in the long-run. This conclusion appears consistent with the neoclassical theory which asserts that there is a long run relationship between the level of taxes and investment in an economy.

4.3: Long-run Effects of Fiscal Policy Variables on Private Investment
To determine the long-run effects of scal policy variables on private investment in Nigeria, the study estimated the conditional ARDL long-run model for equation 1 using the optimally determined lag length of (2, 1, 0, 1, 1, 0, 0, 0, 0). The estimated results of the long-run relationship between scal policy variables and private investment in Nigeria are contained in table 3.    The coe cient of the error correction term which measures the speed of adjustment to restore equilibrium in the dynamic model after a shock indicated that the lagged error term coe cient (ECT(-1)) as expected, was negative (-0.794746) and statistically signi cant at one percent level. This implies that the speed of adjustment was approximately 79.47 percent per year. The negative sign and signi cance level of the coe cient is an indication that co-integrating relationship exists between private investment and scal policy variables. The size of the coe cient of the ECT denotes that all things remaining equal, about 79.47 percent of the disequilibrium in the factor market caused by previous years' shocks converges back to long-run equilibrium in the current year. The pace of adjustment is reasonably fast and thus, any shock will take about 1.26 years to fully recover and restore the economy back to the long-run equilibrium path.

Short-Run Econometric Diagnostics Tests.
The study adopted various diagnostics tests such as the Jarque Bera, Breusch-Godfrey Serial Correlation LM and the Breusch-Pagan-Godfrey tests to check the adequacy of the estimated model. The results of the ARDL diagnostics checks are presented in table 6. The traditional assumptions of the dynamic model were tested, and the respective diagnostic checking statistics failed to reject the null hypothesis, thus indicating no evidence of non-normality, serial correlation and heteroscedasticity. Similarly, the parameters stability test conducted via CUSUM and CUSUM of squares tests reported in gures 1 and 2 indicated that both graphs lie between the upper and lower critical limits at 5 percent signi cance level. This con rmed the fact that the long and short-run estimated parameters of the ARDL model stated in equation 1 are dynamically stable over gradual and multiple structural changes. We therefore concluded that the ARDL model was desirable and well speci ed as it passes both the residual and stability diagnostic tests.

5: Conclusion And Recommendations
The mission to encourage private sector led growth requires a good understanding of the interaction between government scal operations and private investment. Low level of private investment in Nigeria has been of concern to policymakers, especially its implication on poverty reduction and sustainable growth. This study conducted a disaggregated analysis of the nexus between scal policy variables and private investment in Nigeria over a 38-year time frame using the ARDL methodology. It was based on the Laffer curve and Classical-Keynesian argument of whether government scal operations stimulate or discourage private sector investment in Nigeria. Fiscal policy variables were disaggregated into individual revenue, expenditure and debt components in order to evaluate their relative effects on private investment. The empirical results indicated that direct tax revenue were distortionary and retarded private