between monetary and fiscal policies and aggregate demand using different theories, variables, time frame, methods, and countries.

 between monetary and fiscal policies and aggregate demand using different theories, variables, time frame, methods, and countries.

Many studies have explored the relationship between monetary and fiscal policies and aggregate demand using different theories, variables, time frame, methods, and countries. They realised various results depending on the country, method, variables and time of study. This section presents the various studies, methods, variables, the countries of research and the results obtained..

                                                Sesay and Abdulai (2017) examine the rate at which changes in monetary policy in Sierra Leone has affected the behavior of private sector investments for the period spanning 1980 – 2014 using vector autoregressive model and the results suggest that money supply and gross domestic saving exert positive and statistically significant effect on private sector investments whereas Treasury bill rate, inflation and gross domestic debt exert a negative effect.

Joab and Daney (2017) examine the impulse on the aggregate demand in Bolivia through the coordination of the monetary and fiscal policy in crisis time. The structure of a Dynamic Stochastic General Equilibrium Model (DSGE) helps us to understand the transmission channels of shocks (in Taylor rule, Phillips curve and public investment) and how the monetary and fiscal policy reacts to these shocks. The coordination of fiscal – monetary policy is evidenced in the impulse response functions of cost push inflation, given that for exogenous inflationary effects, the monetary authorities’ response is to raise the interest rate and by the fiscal policy with maintaining a public investment Contractive to avoid even greater inflationary effects.

Khaysy and Gang (2017) examine the impact of monetary policy on the economic development by using annual time series data for the period 1989-2016. The unit root testing result suggests that all variables are stationary at first difference and Johansen Co-integration and Error Correction Model were employed to analyze the association between variables. The finding shows that money supply; interest rate and inflation rate negatively affect the real GDP per capita in the long run while only the real exchange rate has a positive sign. The error correction model result indicates the existence of short run causality between money supply, real exchange rate and real GDP per capita.                                                                                                                      Emad (2017) investigates the short – term effects of fiscal policy shocks including government spending and tax revenue on real gross domestic product in Egypt. He applied Structural vector autoregressive model (SVAR) model and impulse response function (IRF) using annual data for the period 1985-2015. His main findings are: 1) Government spending shock has a negative impact on real gross domestic product. 2) The impact of taxation seems to be less efficient as it has a positive but weak impact on real gross domestic product (GDP). Nevertheless, the impulse response functions were statistically insignificant.                                   Nursini (2017) examines the effect of fiscal policy and trade openness on economic growth in Indonesia for the period 1990-2015 using vector auto-regressive model. The study shows that government spending on infrastructure and human resources have positive and significant effect on economic growth if they are financed by tax revenue and insignificant if they are financed by foreign loans. Routine government spending has negative and insignificant effect on economic growth for both financed by taxes and foreign loans. Trade openness has positive and significant effect on economic growth. The implication is that the proportion of spending on infrastructure and human resources should be increased by taxes financing rather than foreign loans. Competitiveness of domestic industries should be improved to achieve a positive impact of free trade.                                                                                                     Nwankwo, Kalu, and Chiekezie (2017) investigate the impact of fiscal policy on economic growth in Nigeria from the period of 1970 to 2014 using data sourced from Central Bank of Nigeria Statistical Bulletin (various issues) and World Bank Development Indicator (WDI), while co-integration and error correction (ECM) approaches were utilized in analyzing the data. The result of the unit root test shows that government capital expenditure, oil revenue, gross domestic product and tax revenue were stationary at first difference I(1), while government recurrent expenditure was stationary at levels at levels I(0). The co-integration result shows that there are 3 co integrating equations at 5 per cent level of significance. This shows that there exists a long-run relationship between fiscal policy and economic growth. The estimated ECM has the required negative sign of -0.447 (45%) and lies within the accepted region of less than unity although, government capital and recurrent expenditures at lagged two years was insignificant and therefore has no impact on economic growth.                                                Wissem (2016) analyses the threshold effect of fiscal policy on private consumption in Tunisia using a threshold regression model over the 1975-2010 period. Their empirical results reveal that public expenditure and tax revenues have Keynesian effects on consumption, when private debt/GDP ratio is below 48 %. This effect becomes non-Keynesian once this threshold is exceeded. The study indicates that private consumption reacts in non-linear fashion to changes in fiscal policy.                                                                                                                                        Joseph, Tochi-Nze, and Ekundayo (2016) examine the nexus between fiscal policy and private investment in five selected West African countries using annual data for the period 1993 to 2014 employing fixed effect model for panel data ordinary least square approach, the results shows the existence of a significant crowding-in effect of government capital expenditure and tax revenue while non-tax revenue shows a crowding out effect. Recurrent expenditure and external debt also shows crowding-out effects but were insignificant. The accelerator effect of output growth was also found to be insignificant across the countries over the time period. The study calls for concerted efforts from these countries to channel funds towards capital projects and also restructure the tax systems to prevent the negative effects of public debt on private investment.                      Abdulazeez (2016) examines the impact of monetary policy on economic growth in Nigeria. The study uses time-series data covering the range of 1990 to 2010. Multiple regressions were employed to analyze data on variables such as money supply, interest rate, financial deepening and gross domestic product. They were all found to have marginal impact on economic growth in Nigeria. The study further shows the aims and objectives of monetary policy, which includes price stability, maintenance of balance of payment equilibrium, full employment and economic growth. In summary, the study finds marginal impact on growth due to change in monetary policy application.                                                                              Adigwe, Echekoba and Justus (2015) examine the impact of monetary policy on the Nigerian economy. In doing this, the ordinary least square method (OLS) was used to analyse the data between 1980 and 2010. The result of the analysis shows that monetary policy represented by money supply exerts a positive impact on GDP growth but has negative impact on the rate of inflation. The recommendations of the study are that monetary policy should facilitate a favourable investment climate through appropriate interest rates, exchange rate and liquidity management mechanism while the money market should provide more financial instruments that satisfy the requirements of the ever-green sophistication of operators.                            Ejuvbekpokpo, Sallahuddin and Clark (2015) study “the impact of fiscal policy on investment expenditure in Nigeria covering the period of 1970 to 2010 and using a multiple regression model. The estimation technique employed was the ordinary least squares (OLS) method. The study reveals that fiscal policy has a significant impact on investment expenditure in Nigeria while government expenditure and gross domestic product have significant impact on investment, but corporate income tax has a positive, instead of a negative, impact on investment expenditure in Nigeria.                                                                                                                     Sylvia, Ifeoma, Okelue and Adeline (2015) determine the impact of various components of fiscal policy on the Nigerian economy. They used descriptive statistics to show the contribution of government fiscal policy to economic growth, and to ascertain and explain growth rates, while an ordinary least square (OLS) in a multiple form was used to ascertain the relationship between economic growth and government expenditure components after ensuring data stationarity. The findings of the study reveal that total government expenditures had tended to increase with government revenue, with expenditures peaking faster than revenue. Investment expenditures were much lower than recurrent expenditures evidencing the poor growth of the country’s economy. Hence, there is some evidence of positive correlation between government expenditure on economic services and economic growth. Therefore, in public spending, it is important to note that the effectiveness of the private sector depends on the stability and predictability of the public incentive framework, which promotes or crowds out private investment.                                                                                                                                Abdurrauf (2015) examines the short and long run impact of fiscal policy on economic development in Nigeria between a period of 1981 and 2013 using annual time series data sourced from World Development Indicators (2014) and the Central Bank of Nigeria (2014). He used government recurrent expenditure, government capital expenditure, government investment and tax revenue to indicate fiscal policy while economic development was proxy by real per capita income. The model was estimated using Pair-wise Correlation to ascertain the relationship and then Co-integration and error correction mechanism for impact after confirming the data’s stationarity using Unit Root. The result shows that government recurrent expenditure and government investment have significant positive impact on economic development in both the short and long run within the period under consideration. Capital expenditure appeared to have a short run positive impact but not in the long run. Tax revenue had an inverse significant impact in both short and long run. The speed of adjustment to equilibrium was found to be high. The results are all in line with theories and previous studies such as Charles (2012).                                               Ghulam (2014) analyses the role of fiscal policy for private investment in Pakistan. The data used the study span 1979-2012. After finding the integration order of all variables by Augmented Dicky Fuller Test, the impact of variables was analyzed by utilizing the Auto Regressive Distributed Lag approach of Co-integration which is a better estimation technique for small sample size. Error correction model was applied for short run dynamics. The results reveal that fiscal deficit, rate of interest, inflation and external debt negatively affect private investment in Pakistan while exchange rate and exports have a positive impact on private investment.                                   Zhu (2014) analyses the effect of fiscal policy on private consumption in China through the linear regression model and the VAR model while controlling the monetary policy. Fiscal policy taken into consideration include: government expenditure, taxation and transfer payment. The study discovers that, an expansionary government spending, a cut in taxation or an increase in transfer will lead to an increase in household consumption. Furthermore, it find out that local government plays a more important role in stimulating private consumption than central government.                                                                                                                                            Juan, Christian, Pablo and Francisco (2014) effects of fiscal policy on private consumption: Evidence from structural-balance fiscal rule deviations. They used a new narrative measure of fiscal shocks to study how private consumption reacts to increase in government spending. Their fiscal shocks arise from three announcements of expansionary fiscal rule deviations in a small and open economy where fiscal policy follows a structural-balance fiscal rule. All those deviations were announced to be mainly on the spending side. They find a negative response of private consumption in the face of those announcements. Their findings are consistent with the existence of consumers expecting some irreversibility in government spending increases and, as a consequence, a rise in future taxes to make the newly announced fiscal spending path consistent with the inter-temporal government budget constraint.                               Osasohan (2014) investigates the impact of monetary policy on economic growth in the United Kingdom. The study uses time-series data over a period spanning 1940-2012. The impacts of each of the endogenous variables were investigated using the vector error correction model (VECM). The study shows that a long run relationship exists among the monetary variables. Specifically, it finds that the inflationary rate and money supply are significant monetary policy instruments that drive growth in the United Kingdom. It, therefore, recommends that the UK policy makers should focus on boosting macroeconomic performance by ensuring that growth in money supply is proportional to the growth in real gross domestic product.                                   Chipote and Makhetha (2014) explore the role played by monetary policy in promoting economic growth in the South African economy over the period 2000-2010. The study employs the Augmented Dickey-Fuller and Phillips Perron unit root tests to test for stationarity in the time series. The Johansen co-integration and the error correction mechanism were employed to identify the long-run and short-run dynamics among the variables. The study shows that a long run relationship exists among the variables. Also, the core finding of this study is that money supply, interest rate and exchange rate are insignificant monetary policy instruments that drive growth in South Africa whilst inflation is significant. The study, therefore, recommends that monetary policies should be used to create a favourable investment climate that attracts both domestic and foreign investments thereby promoting a sustainable economic growth. It further suggests that government should also increase spending on the productive sectors of the economy so as to promote economic growth as monetary policy alone is unable to effectively spur economic growth.                                                                                                              Corazon (2014) measures the effect of monetary policy on economic growth in Kenya.  Vector Auto-regressive model was used to analyse the data. Findings from this study indicates that one standard deviation monetary policy shock proxy by the CBR has a negative and insignificant effect on the output in the first two months which then becomes positive and insignificant in the next four months. However, a one standard deviation shock of the interbank rate to inflation is positive and significant for the first two and a half months. The effect continues to be positive but insignificant up to the sixth month.                                                            Ogar, Nkamare and Emori (2014) examine the empirical link of the effect of fiscal and monetary policy on the economic growth in Nigeria (1986-2010). The objectives were to determine fiscal and monetary policy factors that contribute to the growth of Nigerian economy. They used secondary data, from Central Bank of Nigeria Statistical Bulletin, and employed the ordinary least squares method to analyse the date. They find that government revenue had a positive and statistically significant impact on gross domestic product. The study also shows that government expenditure was positively significant on the growth of Nigeria Economy. The second model depicts that money supply had a positive impact on gross domestic product and it discovers that this variable was statistically significant. Exchange rate variable had a positive impact on the performance of Nigeria economy. The finding reveals that inflation had a positive impact but there was no significant relationship between inflation and gross domestic product. It therefore suggests that government should increase the number of fiscal policy instruments over and above the ones currently in use.                                                                                        Michael and Ebibai (2014) examine the impact of monetary policy on selected macroeconomics variables such as gross domestic product, inflation, and balance of payments in Nigeria from (1980-2011). Data were extracted from the Central Bank Statistical Bulletin. The study was designed in such a way that it is an econometric investigation of the impact of monetary policy on economic growth in Nigeria using such econometric tools like the ordinary least square (OLS) regression analysis. The error correction method was used to ascertain if there is a static long run equilibrium relationship among the explanatory variables and to subsequently derive an adequate dynamic model of the short run relationship. The study shows that the provision of investment friendly environment in Nigerian will increase the growth rate of GDP.                Udude (2014) examines the impact of monetary policy on the growth of Nigeria’s economy between the period of 1981 and 2012 with the objective of finding out the impact of various monetary policy instruments (money supply, interest rate, exchange rate and liquidity ratio) in enhancing economic growth of the country within the period considered. To identify the stationarity characteristics of the data employed in the study, various advanced econometric techniques like augmented dickey fuller unit root test, Johansen co-integration test and vector error correction mechanism (VECM) were employed and the following outcomes were obtained: None of the variables was stationary at level meaning they all have unit roots but all the variables became stationary after first difference with the exclusion of money supply. However, all the variables became stationary after second difference. Hence they were integrated of order two. The co-integration result indicates that there is long run relationship among the variables with two co-integrating vectors, while the result of the vector error correction mechanism (VECM) test indicates that only exchange rate exerted significant impact on economic growth in Nigeria while other variables did not. Equally, only money supply though statistically insignificant possessed the expected sign while others contradicted the expectation. The study concludes that monetary policy did not impact significantly on economic growth of Nigeria within the period under review and that the inability of monetary policies to effectively maximize its objectives or targets most times is as a result of the shortcomings of the types of policy instruments used in Nigeria which limits the contribution monetary policy to economic growth.                                       Ismail, Adegbemi and Mariam (2013) examine the impact of monetary policy on economic growth in Nigeria. The study used time-series data covering the period 1975 – 2010. The effects of stochastic shocks of each of the endogenous variables were explored using Error Correction Model (ECM). The study shows that Long run relationship exists among the variables. Also, the core finding of this study is that inflation rate, exchange rate and external reserve are significant monetary policy instruments that drive growth in Nigeria. The study, therefore, recommends that the establishment of primary and secondary government bond markets that will help to increase the efficiency of monetary policy and reduce government’s reliance on the central bank for direct financing.                                                                               Asogwa and Chetachukwu (2013) evaluate the impact of budget deficits on private investment in Nigeria for the period 1980 – 2011 using ordinary least square regression model. They find that budget deficits crowds out private investments and that private investments granger cause budget deficit with feedback.                                                                                           Afia (2013) examines linear as well as non-linear impact of fiscal policy variables on private investment in Pakistan. The results imply that it’s better to examine different aspects of fiscal policy instead of fiscal policy variables in aggregate form as the impact of fiscal policy variables in aggregate and disaggregate form do not comply with each other. Different categories of expenditures and revenues have different impact on private investment. Secondly, in most of the cases there exists a non-linear relationship, which implies the significance of certain threshold level for the different fiscal policy instruments to encourage private investment.                                Sineviciene andVasiliauskaite (2012) analyse the relationship between fiscal policy and private investment in the Baltic States of Estonia, Latvia and Lithuania using vector error correction model. The study shows that from the tax revenue side, the strongest relationship exists between the current taxes on income, wealth and private investment. Analysis of fiscal policy indicators interaction with private investment from the government expenditure side shows the existence of strongest relationship between public and private investment thereby leading to the conclusion that fiscal policy indicators explain fluctuations in private investment in the Baltic States.                                                                                                                                  Menjo and Kotut (2012) investigate the effects of fiscal policy on private investment and economic growth in Kenya using time series data spanning 1973 to 2009. They adopted two stage instrumental variable estimation methods to perform the regression analysis because of its adaptability. The results indicate that fiscal policy impacts on investment and investment plays a major role in the determination of the economic growth in Kenya.                                          Stephen (2012) analyses the effects of fiscal policy on private investment in Kenya from 1964 – 2010. The study adopted modified flexible accelerator model to evaluate the economic relationship between private investment and the other variables. Vector auto–regression modeling technique and error correction model were applied to estimate the effects of fiscal policy variables on private investment. The study also used semi–annual time series data for the period 1964 – 2010. Since some of the variables were stationary at levels while others became stationary at first difference, the study used Johansen co-integration tests to determine long–run relationship between private investment and the aforementioned fiscal variables. Furthermore, the Granger–Causality test was undertaken to determine the economic relationship between the variables. The results of the study reveal that fiscal policy design and implementation matters to private investment levels in Kenya. The study finds that taxes, government expenditure, government debt servicing and fiscal reforms could either promote or deter private investment both in the short–run and in the long–run.                                                                                                            Jeevan (2012) estimates the impact of monetary policy on aggregate demand in India using a structural VAR model on quarterly data from 2000Q1 to 2011Q. The overall impact on aggregate demand was decomposed to observe the differential impact among the various components. The study finds that an interest rate hike has a significant negative impact on the growth of aggregate demand. However, the maximum impact was borne by investment demand growth and imports growth. Impact on private consumption growth and exports growth were relatively far more subdued, while there is hardly any cumulative impact on government consumption growth as it increases after some marginal fall initially. Variance decomposition analysis indicates that interest rate accounts for a significant percentage of the fluctuation in the growth of all the components of aggregate demand, except government consumption. Furthermore, interest rate channel completely dominates exchange rate channel in monetary transmission, though the latter channel has non-negligible impact on investment and imports                       Tobias and Mambo (2012) explore the relationship between monetary policy and private sector investment in Kenya by tracing the effects of monetary policy through the transmission mechanism to explain how investment responded to changes in monetary. The study utilises quarterly macroeconomic data from 1996 to 2009 and the methodology draws upon unit roots and co-integration testing using a vector error correction model to explore the dynamic relationship of short run and long run effects of the variables due to an exogenous shock. The variables were stationary in first differences and using ordinary least squares the estimated long run relationship indicates that government domestic debt and Treasury bill rate are inversely related to private sector investment, while money supply and domestic savings have positive relationship with private sector investment consistent with the IS-LM model. Based on the empirical results the study suggests that tightening of monetary policy by -1 percent has the effect of reducing investment by -2.63 while loosening monetary policy tends to increase investment by 2.63. The error correction term (ECT) of -0.55 is negatively signed indicating a move back to equilibrium suggesting that following an exogenous shock, 55 percent of the disequilibrium is corrected after one quarter.                                                                                      Charles (2012) examines the impact of monetary policy on Nigerian economy. In doing this, the Ordinary Least Squares Method (OLS) was used to analyse the data spanning the period 1981 – 2008. Ordinary least square (OLS) was used in the analysis. The result of the analysis shows that monetary policy represented by money supply exerts a positive impact on GDP growth and balance of payment but negative impact on rate of inflation.                                  Onouorah, Shaib, Oyathelemi and Friday (2011) critically evaluate the impact of monetary policy on micro-economy in relation to private investment in Nigeria. The data were obtained from the CBN Statistical Bulletin, while correlation analysis was performed and shows the relationship between private investment (PI) and money supply (Ms), interest rate (IR), credit (CD), inflation (INF), exchange rate (EXR) and GDP is significant at 0.01 level. Ms was significant at 0.01 with (PI), (CD) and GDP but not significant with (IR), (INF) and (EXR). The interest Rate (IR) was only significant with (INF). (CD) is significant at 0.01 level of significance with (PI), (Ms), exchange rate (EXR) and GDP. Inflation rate (INF) was significant with interest rate (IR). Money supply was found to be the effective monetary policy instrument than the interest rate. This is based on the fact that private investment react more to changes in money supply than the interest rate in Nigeria. However, the correlation result shows that private investment increase as money supply increases.  This is because of the direct relationship that exists between both variables.                                                                                                                   Ogbole, Ogbole, Amadi and Isaac (2011) study fiscal policy and economic growth in Nigeria. They used time series data spanning 1970-2006 in respect of the independent/explanatory variable which is fiscal policy and dependent variable which is economic growth proxy by gross domestic product (GDP) were sourced from Central Bank of Nigeria Statistical Bulletin, and were tested and found to be stationary using augmented dickey-fuller test and co-integrated (using Johansen’s Co-integration test). Granger causality test was further employed to test for causal relationship between these variables. The result of the analysis shows the existence of causal relationship between them with a unidirectional causality running from (GE) to GDP, which is in line with the a priori expectation. They conclude that in the period under study, fiscal operations in Nigeria, to some extent, caused some economic growth in the country, though the precise extent is a subject of further study.          Fatima, Ahmad and Rehman (2011) explore the impact of fiscal deficit on investment and economic growth in Pakistan over the period 1980 to 2009. The two stage least square method was adopted to estimate the simultaneous equation model. GDP growth and investment are the dependent variables while fiscal deficit, investment, exports, imports, foreign aid, inflation, real interest rate and population growth the independent variables. They conclude that fiscal deficit affects economic growth of the country adversely because of poor tax collection, inelastic tax system, complex tax laws, and heavy reliance on foreign trade taxes, large tax exemptions and incentives. Results of the study also show that there is persistence deficit in balance of payments that creates fiscal deficit.                   Marratin and Salotti (2010) conduct a study on the relationship between fiscal policy and private investment of 14 EU countries and find that state expenditure shocks have positive effect on private investment. The study suggests that remuneration-related public expenditure has a relatively higher stimulating effect, whereas government investment has no stimulating effect on private investment. Traum and Yang (2010) find limited relationship among public debt, real interest rate, and private investment. They observe that in the short run, government debt can either crowd in or crowd out private investment depending on the cause of the debt as a percentage of GDP. If reduction in distortionary taxes is responsible, private investment is crowded in, but if it is increase in government consumption spending and transfer payments, private investment will be crowded-out.                                                                                  Adefeso (2010) examine the impact of fiscal policy on economic growth in Nigeria from 1970 to 2005, using the error-correction technique to test the predictive ability of the endogenous growth model. The findings of the study are consistent with earlier empirical findings in other countries, which reveal that productive government expenditure has positive effect on economic growth.                                                                                                                                              Central Bank of Nigeria (2010a) constructed a medium macro econometric model for the Nigerian economy that is capable of incorporating the essential features of the economy, while making extensive use of economic theory. The model, which was highly aggregated, reflected activities of four sectors (i.e. the external, the fiscal, the monetary and the real sectors). It comprised six blocks, namely: supply, private demand, government, external, monetary/financial and price blocks. Specifically, in the fiscal/government block, Government expenditure was broken down into recurrent and capital expenditure, but only recurrent expenditure was endogenized; capital expenditure was treated as a policy variable. Variations in size and components of capital expenditure were important fiscal policy tools in terms of complementing private investment as well as determining deficits and financing options.                                           Lawrence and Victor (2008) explore the impact of the monetary policy and credit guidelines of the Central Bank of Nigeria on private domestic spending (defined in terms of business fixed investments). To this end, the study relies on recent developments in co-integration and error correction modelling techniques. The results of the analysis show that greater reliance could be placed on monetary policy as a veritable instrument for correcting some of the major macro-economic ills facing the economy. The study recommends, amongst others, that monetary policy should be made much more effective in terms of doses and frequencies while at the same time, avoiding sharp and wide swings in policy initiations.                                    The study of Berument and Dincer (2008) examine the effects of monetary policy on economic growth in Turkey spanning the period 1986-2000 through structural VAR (SVAR) technique. They find that a tight monetary policy has a temporary effect on output, causing output to decline for three months in a statistically significant fashion. The findings confirm the work of previous studies (Sousa and Zaghini, 2008; Sims, 1992; Eichenbaum and Evans, 1995). Employing the same estimation technique, Bhuiyan (2008) examined the effects of monetary policy shock in Canada by using the overnight target rate as the monetary policy instrument. Using monthly data from 1994-2007, findings of the study indicate that the transmission of the monetary policy shock to real output operates through both the interest rate and the exchange rate.                                                                                                                                                     Rafiq and Mallick (2008) examine the effects of monetary policy on output in the three largest euro are a economies (Germany, France and Italy) using time series data spanning period 1981-2005 using the new VAR identification procedure. They find that monetary policy innovations are at their most potent only in Germany. Apart from Germany, it remains ambiguous as to whether a rise in interest rates concludes with a fall in output, thereby showing a lack of homogeneity in the responses.                                                                                           Parikh, Booth and Sundrum (2007) developed an econometric model of the Indonesian monetary sector to quantify the relationship between money income and prices in a macroeconomic context using a simple ordinary least square technique. In the model, the components of money supply were separated, permitting part of the money supply to be endogenously determined. The model had an aggregate demand function for money balances, three components of money supply government budget receipts and expenditure and different price components. The estimation of money supply was found to be influenced by government domestic expenditure and revenue, foreign expenditure and different price components. The demand for money on the part of the public was found to be the demand for real balances.           Mzgyar (2006) assesses the effect of monetary policy on major components of aggregate demand using three different macro models, all estimated on Hungarian data for a period of 10 years. Three models indicate that after an unexpected monetary policy tightening, investments decrease quickly. The response of consumption is more ambiguous, but it is most likely to increase for several years, which may be explained by the slow adjustment of nominal wages. On the other hand, the study could not detect any significant change in net exports during the first couple of years after the shock. The weak response of net exports could be due to the drop in exports coupled with a fall in imports of almost the same magnitude, highlighting the relative             Kimani (2005) studies the relationship between budget deficit financing and private investment in Kenya using a vector–auto–regressions analysis. The study finds that domestic borrowing crowds-out private investment in Kenya. This could imply that the government does not use the resources from domestic borrowing for investment in public utilities like infrastructure. On the contrary, the results imply that the government resorted to domestic borrowings thereby competing for scarce resources from financial sector with the private investors. With this competition, the interest rate goes up making cost of borrowing unbearable for the prospecting investors.                                                                                                              Kiptui (2005) examines Kenya’s fiscal adjustment process and its effect on private investment in Kenya from 1972–1999. Error correction model and co– integration analysis were used in the study. The approach of the study was to analyze the determinants of private investment and then concentrate on the fiscal variables in the results interpretations. The fiscal variables identified included budget deficits, government consumption expenditure, tax burden and public debt. The findings of the study suggest that debt servicing problem crowded–out private investment. The econometric analysis demonstrates that budget deficits had statistically significant lagged effects on private investment, suggesting that the benefits of fiscal restraint are not realized immediately. The study further asserts that benefits of fiscal restraint were even larger considering that domestic and foreign debt service, total debt stock and tax burden all had negative effects on private investment. The results also indicate that public investment had negative effects on private investment. Lastly, it was revealed that government consumption expenditure had positive effects on private investment. Use of error correction model in the study illuminates on the relative effects or elasticities of independent variables without providing information on how long the effect will last. In addition, the study assumes that private investment was the dependent variable arbitrarily. Some of the variables in the model could be influenced by private investment. This assumption definitely affects the outcome of the model estimation negatively.                                                                                                                    Amanja and Morrissey (2005) analyse the relationship between fiscal policy and growth in Kenya between 1964 -2002 using autoregressive distributed lag (ARDL) model and ordinary least square methods on time series data. The study reveals that productive expenditure has strong adverse effect on growth while there was no evidence of distortionary effects on growth of taxes. Government investment was found to be beneficial to growth in the long run.                             Yaacov and Michel (2004) analyse the impact of fiscal policy on private consumption in Israel with emphasis on the fiscal expectations approach. The method of estimation was based on the approach of Engel and Granger, according to which the basic test for determining the specification of a long run relation is the stationarity of the residual. Stationarity was tested using the ADF statistic. They find that there is substitution between private and public consumption but of a very limited magnitude (approximately 20 percent). The study also finds that, in contrast to the Ricardian approach, the method of financing of public expenditure has effect on private consumption. Thus, an increase in the direct taxation of wages has a negative effect on consumption that is equal to the full amount of the tax increase while bond financing has a positive effect as long as the increase in public debt is small.                                               Hossain and Razzaque (2003) modeled the government sector of the Bangladesh economy within an open economy framework. Government revenue endogenously entered the model and was disaggregated into tax and non-tax sources. Based on the import dependent nature of the economy, the taxes were further decomposed into trade and internal taxes. The internal and non-tax revenues were taken as functions of the nominal GDP, while the trade related taxes were depended on related import bases including custom duties, VAT and supplementary duty on imports.                                                                                                                                   Alesina, Ardagna and Perotti (2002) evaluate the effects of fiscal policy on private investment using a panel of 18 OECD countries over the period 1960- 1996. The investigation was based on Tobin model, which highlights the central role of profits as a determinant of investment. The study made a breakdown of spending into the government wage bill, purchases of goods by the government and transfers. On the revenue side, in addition to total taxes, the study considered separately taxes on labor income, indirect taxes and business taxes. Such aggregation was justified on the basis that the main emphasis was on the channel through which fiscal policy affects investment through labor-market. The focus of the study was not on the differences between government investment and consumption of goods and services, and thus they were lumped together. Business and labour income taxes were separated to check their possible direct effects on profits and capital formation. The investigation find the following: First, increases in public spending increased labor costs and reduced profits, and as a result, investment declined. Second, increases in taxes reduced profits and investment, however, the magnitude of these effects on the revenue side was smaller than those on the expenditure side. Labor taxes had the largest negative effect on profits and investment. Third, the size of the coefficients suggested that there was nothing special in the behavior of investment during periods of large or small fiscal adjustments. Lastly, the different composition of the stabilization package could account for the observed difference in private investment growth rates. Thus, to understand properly the effect of fiscal policy on private investment, it is imperative to disaggregate different revenue and expenditure components.                                                                                               Mlambo and Oshikoya (2001) did a research on the relationship between macroeconomic policy factors and private investment in Africa covering the period 1970 – 1996. The study used panel data regressions for a sample of forty developing countries from Africa, East Asia, Latin America and South Asia. The study yielded some imperative results on how macroeconomic policies affected investment. First, investment behavior was affected by the economic environment in which entrepreneurs operate. This indicates the importance of providing an appropriate macroeconomic environment, mainly by following sound fiscal, monetary, trade and competition policy. Secondly, public sector reforms had an influence on private investment behaviour. Thirdly, financial reforms were found to reduce financial repression by limiting the monetization of fiscal deficit, liberalizing interest rates and eliminating credit controls. The study, however, assumes that the data for all variables were stationary at level, which is a farfetched assumption for time series data. The results could have improved if the time series properties of the data were tested, and instead of static OLS, error–correction model (ECM) could have been employed.

2.6 Gap in Literature                                                                                                                          This study is important because, most of the recent studies concentrate on the effect of monetary policy on either private consumption, private investment, consumption expenditure or unemployment and effects of fiscal policy on either private consumption, private investment, consumption expenditure or unemployment. This study focuses on the impact of monetary and fiscal policies on aggregate demand.  From the literature reviewed so far none of the reviewed studies used macro econometric models and simulation exercises as tools of estimation.

CHAPTER THREE

METHODOLOGY

3.1 Introduction

The chapter presents both the theoretical and empirical model adopted for the study. The variables used in the study are defined. The data, the sources and the methods used in analysis are explained.

3.2 Empirical Frameworks of the Model

The macro-econometric model (MEM) in this study is ideal, because it provides information on the dynamics of the adjustment process which in turn is useful for short-term and medium-term forecasting and policy analysis. It is also structural in the sense that it allows the formal use of econometrics as the best tool for policy analysis at the macro level. It stresses the crucial role played by monetary and fiscal variables in the behaviour of key aggregate demand like private consumption, private investment, government consumption and net export. This macro-econometric model is a set of equations designed to explain the economy or some part of the economy. There are two types of equations: The behavioural equations which are estimated from the historical data and the identities equations that hold by definition and are always true.

The model has 12 equations, of which 8 are of stochastic relationship and 4 are identities. The model was adapted from the works of Ojo (1973), Ajayi (1978), Khan and Knight (1981), Soludo (1998), Olofin and Poloamina (1984) and Ikhide (1998).

The model is broadly classified into three blocks: consumption, investment, and net export sector blocks. This classification is doubly important because it allows the study to capture the crucial role played by monetary and fiscal variables in the behaviour of macroeconomic aggregates.

In the consumption block, the study specifies equations that show private consumption, disposable income equation, government (Public) consumption equations. Investment block is divided into Private investment equation and government investment equation. The net export sector block is open with identity equation and consists of three behavioural equations: export equation, import equation and exchange rate equation.

Figure 13: Macroeconomic Models of Monetary

Source:  Author’s Compilation, 2018

Figure 14: Macroeconomic Model of Fiscal policy

Source:  Author’s Compilation, 2018

Figure 13 shows the routes through which monetary policy of the Central Bank of Nigeria affects aggregate demand and macroeconomic activity in general. The goal of monetary policy is to induce changes in aggregate expenditures, which results in changes in aggregate production, price level, inflation, employment, and unemployment. The route between monetary policy and aggregate demand works through a variety of channels. The main key channel is money supply. Expansionary monetary policy; specifically open market operations, affects bank reserves, which then affects interest rates and business expansion. Changes in interest rates induce changes in investment expenditures on capital goods by business sector and consumption expenditures on durable goods by household sector. Lower interest rates induce greater investment and aggregate expenditures. On the other hand, positive changes in business activities induce changes in net export, employment opportunity, household income which in turn induce consumption expenditure and aggregate demand.

Figure 14 shows how Fiscal policy affects aggregate demand through changes in government spending and taxation. Government spending and taxation influence employment and household income, which dictates consumer spending and investment. Expansionary fiscal policy usually enacted in response to recessions or employment shocks, increases government spending in areas such as infrastructure, education and unemployment benefits. According to Keynesian economics, these programs prevent a negative shift in aggregate demand by stabilizing employment among government employees and people involved in stimulated industries

3.3 Model Specification

The study constructs a model with three blocks, consumption block, investment block, and Net export block which contains 21 variables. The variables are linked to one another through 8 behavioural equations and 4 identities, considering Nigeria as a market economy. All behavioural equations are modeled based on economic theories for model building). General structure of the model is briefly explained here.

The aggregate demand for goods and services is the sum of domestic absorption and the trade balance Zerfu (2002) and Basdevant and Kaasik (2003)

Y_t = A_t + (X_t – M_t) ……………………………………………………………………………2

Where

A is domestic absorption refers to consumption (C), investment (I) and government expenditures (G) respectively. Whereas, X and M denotes exports and imports of goods and services respectively. The national income now is defined as:

AD_t = C_t + I_t + G_t + (X_t – M_t)…………………………………………………………………3

This relationship always holds as an identity. In estimating the impact of monetary and fiscal policies on aggregate demand, the following blocks equations are specified:

3.3.1 Consumption Sector Block

Total consumption of goods and services comprises of private consumption and government consumption

C = P^C + G^C…………………………………………………………………………………….4

P^C= a₀ + a₁Y^d + a₂INT + a₃MS + a₄GE + a₅Tax + μ₁……………………………………………..5

G^C= b₀ + b₁GR + b₂MS + b₃INT + a₄RDEGDP + μ₂ ………………………………………………6

Y^d = c₀ + c₁GDP + c₂DT + c₃IT + c₄WR_t + c₅CPI + μ₃………………………………………7

Where C = Total consumption

P^C = Private Consumption

G^C = Government Consumption

G^R = Government Revenue

GE = Government Expenditure

Tax = Taxation

INT = Interest rate

MS = Money Supply

RDEGDP = Ratio of development expenditure to GDP

WR = Worker’s remittances

CPI = consumer price index

A priory expectation for consumption sector block parameters is:

Positive parameters: α_1, α_3, α_4, b_1, b_2, b_4, and c₁

Negative parameters:  α_2, α_5, b_3, c_2, c_3, c_4, c₅

3.3.2 Investment Sector Block

Aggregate investment is disaggregated into private investment (P^I_t), government investment (G^I_t) and increase in stocks (Dstocks). Increases in stocks may be an important component of business cycle. It can be thought that increase in stocks may be heavily dependent on the fluctuations in agricultural production, which in turn affected by exogenous factors such as climate. Hence, increase in stocks is assumed to be exogenous (Ra & Rhee, 2005).                                                             Private investment continuously plays a key role in sustaining development process by promoting economic growth. Private investment decisions depend on investment in long-lived capital assets and expectations about the future (Guru-Gharsns, 2000). In this study, we pay attention to only private investment and government investment only.

I = PI + GI …………………………………………………………………………………………………………………….8

P^I= a₀ + a₁INT + a₂MS + a₃Y^d + a₄GE + a₅Tax + a₆PD + a₇RPSC + μ1……………………..9

G^I = b₀ + b₁INT + b₂MS + b₃PD + b₄GE + b₅GI^-1 + μ₂……………………………………………10

Where I = Total investment

P^I = Private Investment

INT = Interest rate

MS = Money Supply

Yd = Disposable income

GE = Government expenditure

Tax = Taxation

PD = Public debt

RPSC = Ratio of private sector credit to GDP

GI= Government Investment

A priory expectation for consumption sector block parameters is:

Positive parameters: α_1, α_5, α_6, b_1, b_3,

Negative parameters:  α_2, α_4, α_7, b_2, b_4, b₅

The accelerator theory suggests that as income increases, investment also increases. Therefore, real income (disposable income) is included to capture the effect of accelerator principle. The real interest rate is another important variable that determines the level of private investment. The neoclassical theory predicts negative relationship between interest rate and investment. However, McKinnon (1973) and Shaw (1973) argue that interest rate could exert positive impact on the level of investment because real interest rate could increase savings, which led to increase investment (Khan & Khan, 2007). Furthermore, interest rate can also be used as a measure of cost of borrowings that may affect the cost of capital and debt-equity ratio (Guru-Gharsns, 2000). Availability of credit to private sector is another important determinant of private investment and influences the investment behaviour positively (Jongwanich & Kohpaiboon, 2008). It also provides a link between real and monetary sectors (Guru-Gharsns, 2000). Furthermore, government investment that concentrates mostly on infrastructure exerts an important influence on private investment. It is often suggested that government investment complements private investment instead of crowding-out in developing countries (Hossain & Razzaque, 2003).Therefore, government investment is included in the specification to capture the ‘crowding-out’ or ‘crowding-in’ effects (Jongwanich & Kohpaiboon, 2008).

3.3.3 Export-Import (NEX) Sector Block

Nigeria’s external sector reflects the economic transactions between the residents of Nigeria and the rest of the world. The sector can be in equilibrium or disequilibrium (surplus or deficit). A deficit outcome represents a situation where receipts are inadequate to accommodate the payments, while a surplus position reflects a situation where receipts are in excess of the payments. An ideal external sector is one that is stable and in equilibrium over time. Equilibrium is achieved when external receipts and payments are equal, the exchange rate is stable and external reserves are adequate. However, in more practical terms, such a perfect system hardly exists.

Within macroeconomic models, different techniques have been employed in the modeling of the external sector arising from theoretical underpinnings, accounting systems and definition of variables (Matlanyane, 2005). In principle, the estimation of the external sector should reflect trade flows, services flows, transfers as well as direct and portfolio capital flows (Pauly, 2000). Pandit (2000) is of the view that the discussion of the external sector should focus on the analysis of the disequilibrium in the sector and how it impacts on the economy. This can be achieved by integrating the demand and supply analysis in the trade flows. The external sector model is specified as:

NEX = XP – MP……………………………………………………………………………11

XP= β₀ + β₁INT + β₂ EXR + β₃ MS + β₄ GE + β₅PD + U_1..………………………………..12

MP = ϰ₀ + ϰ₁MS + ϰ₂ EXR + ϰ₃INT + ϰ₄PD + ϰ₅GE + U₂…………….…………….………13

EXR = ơ₀ + ơ₁MS + ơ₂INT + ơ₃PD + ơ₄GE +U₃……………………………………………14

Where

NEX = Net Export

XP = Export

MP = Import

INT = Interest rate

GE = Government Expenditure

MS = Money Supply

EXR = Exchange Rate

PD = Public Debt

A priory expectation for external sector block parameters

Positive parameters: β_3, β_4, ϰ_1, ϰ_5, ơ_1, ơ₄

Negative parameters: β_1, β_2, β_5, ϰ_2, ϰ_3, ϰ_4, ơ₃

3.4 Sources of Data

Annual time series data spanning the period 1986-2017 were used for the estimation. The detail of data description with respect to variables, signs and source are presented in table 1.

Table 1:  Data Description

Source: Author’s Compilation, 2019

3.5 Techniques of Data Analysis

This study investigates the impact of monetary and fiscal policies on aggregate demand in Nigeria. Quantitative data are used in the study to answer the research questions posed in the previous section. The study uses time series data for the period between 1986 – 2017. Data were obtained from Central Bank of Nigeria Statistical Bulletin, National Bureau of Statistics, National Population Commission and other financial documents. Two stage least square techniques are used in the estimation of all the 8 behavioural equations in the macro econometric models. This is because the structure of the model is such that some independent variables appear in other equations as dependent variables. Therefore, the use of Ordinary Least Square (OLS) techniques to estimate the equations would give biased and inconsistent estimates of the parameters (Dauda, 2009). Simulation exercise was followed after estimation of the macro econometric model

3.6 Simulation Experiment

The study carries out a set of simulation experiments. The major objective of the simulation exercise is to derive an appropriate set of policy to achieve specific improvement in key macroeconomic aggregates. There are basically two types of simulation: historical simulation and policy simulation. Historical simulation allows for the validation, evaluation of, and counter–factual analysis of the model.

The importance of the historical stimulation is clear and straightforward. It enables the model builder to compare the simulated and the actual series in order to determine how well the macro-econometric model tracks the economy (Iyoha, 2002). If the simulated values for all or most endogenous variables are very close to the actual values, then one is forced to conclude that the econometric model suitably describes the structure of the Nigerian economy.

The purpose of policy simulation is to enable the study to predict the response of key endogenous variables to changes in identified policy instruments like government expenditure and money supply. As Iyoha (2002) points out, that predicting policy response is more or less indispensable for effective macroeconomic management and policy analysis.

CHAPTER FOUR

DATA PRESENTATION, ANALYSIS AND DISCUSSION OF RESULTS

4.1 Introduction

The purpose of this chapter is to empirically estimate the behavioural equations of Nigeria’s macroeconomic model developed in chapter three with the aim of analyzing the impact of monetary and fiscal policies on aggregate demand in Nigeria. However, before the macroeconomic model is estimated, it is important to perform trend analysis of the structure and pattern of monetary and fiscal policy variables in Nigeria within the period under review. This chapter conducts numerical simulations to analyse possible macroeconomic effects on Nigeria’s economy arising from exogenous shocks from increase and decrease in money supply, interest rate, government expenditure and tax.

4.2 Trend of Monetary, Fiscal and Aggregate Demand Variables in Nigeria 1986-2017

Table 2: Structure of Selected Monetary, Fiscal and Aggregate Demand Variables in Nigeria

Source: Central Bank of Nigeria Statistical Bulletin, 2018

Figure 15: Trend of MS, INT, PC, PI (1986-2017)

                          Figure 16: Trend of GE, PD, PC, PI (1986-2017)

Figure 15 shows the trend of money supply (MS), interest rate (INT), private consumption (PC) and private investment (PI) within the period of 1986-2017. Nigeria’s annual growth in money Supply (MS) was reported at 19.5% in 1986. This records an increase in the following years to 22.41% in 1987 and 32.91% in 1988. With increase in money supply, private consumption (PC) also increases in marginal rate. The floatation in interest rate also affected the trend movement of private investment in the country. This trend is a clear indication that interest rate and money supply have significant impact of private consumption and private investment in Nigeria.                        As seen in the figure 16, government expenditure (GE) as a percentage to nominal GDP reached 23.5% in 1986, dropped to 19.7% in 1989, 18.4% in 1992, and 13.1% in 1996. Government expenditure (GE) as a percentage to nominal GDP stood at 29.7% in 1999 and continues to drop to 10.4% in 2006. 19.2% in 2010, and 29.3% in 2017. During the period, as government expenditure (GE) as a percentage to nominal GDP is increasing and decreasing, private consumption (PC) as a percentage to nominal GDP is also increasing and decreasing at marginal rate. It is expected that, increase in government expenditure will stimulate private consumption. Public debt (PD) as a percentage to nominal GDP and private investment (PD) as a percentage to nominal GDP also show an inverse relationship during the period under investigation as public debt (PD) is increasing, private investment (PI) as a percentage to nominal GDP is decreasing. In 1986, public debt (PD) as a percentage to nominal GDP reached 35.8% while private investment (PI) as a percentage to nominal GDP and private consumption (PC) as a percentage to nominal GDP reached 54.4% and 1.9% respectively. As public debt (PD) start increasing to 57.2% in 1987, 58.1% in 1988, 69.2% in 1989, 77.9% in 1990, private investment (PI) as a percentage to nominal GDP begin to drop to 52.1% in 1987, 44.5% in 1988 and private consumption (PC) as a percentage to nominal GDP to 1.8% in 1987, 1.7% in 1988, 1.6% in 1989 and 1.5% in 1990. The factors behind the raise in public debt (PD) as a percentage to nominal GDP that slow the growth of private investment and public consumption (PC) as a percentage to nominal GDP during this period was due to global oil glut of the 1980 were Nigeria lacked the financial resources to generate adequate foreign exchange earnings to provide basic service. The trend of public debt (PD) reached 80% in 1992 and begins to drop to as low as 24.3% in 1998. This dropped in public debt (PD) as a percentage to nominal GDP was as a result of revenue from the oil sector within the period. The public debt (PD) as a percentage to nominal GDP later rose in 1999 to 62.1% and dropped to 7.1% in 2008 and 15.4% in 2017.

4.3 Estimation Results of the Structural Model and Analysis

The behavioural equations in the model specified in chapter three of this study have been estimated using two stages least squared regression model and the results are presented below:

4.3.1 Consumption Sector Block Result

Equations 3, 6 and 7 are equations for the consumption sector which shows the impact of monetary and fiscal policies variables on private consumption, government consumption and disposable income (aggregate demand components) and the equations were estimated and the result presented in equation 15, 16 and 17:

PC =   0.63Yd + 0.03INT + 0.96MS + 0.53GE – 0.12TAX……………………………………15

(3.03)        (-3.31)        (3.35)         (2.58)    (2.12)

R² = 0.88,  R^-2 = 0.79. DW = 2.65

GC= 0.284GR + 0.572MS – 0.218INT + 0.727RDEGDP………………………………………16                                         (3.32)           (2.53)       (-1.38)            (2.58)                                                                                                                               R² = 0.74,  R^-2 = 0.71. DW = 1.93

Y^d= 0.847GDP + 0.979DT – 0.17IT – 0.36WR – 0.111CPI…………………………………………………17                                                            (2.20)        (-1.44)       (-2.05)    (3.47)        (-0.42)                                                                              R² = 0.46, R^-2 = 0. 41. DW = 1.42.

The estimated equation 15 show a good fit as the adjusted coefficient of determination (R²) is high.  The R^-2 value of 0.79 showed that over 79 percent of the variability in the dependent variable is explained by the joint independent variables in the model. This is a representation of goodness of fit for the regression line. The estimated coefficients of the variables in equation 15 were also very impressive as they fall within a-priori expectation of the study. The disposable income (Yd) variable showed a positive coefficient (0.63). This is an indication that disposable income (Yd) impacted positively on the private consumption (PC). A one percent increase in disposable income (Yd) will impact positively on private consumption (PC) by 0.63 percent. Other variables that showed positive signs include MS (0.96) and GE (0.53).  The coefficient of INT (-0.04) and TAX (-0.12) shows an inverse relationship with private consumption (PC). The values of t-statistics of all the explanatory variables Yd (3.03), INT (-3.31), MS (3.35), GE (2.58) and TAX (2.12) were statistically significant at 5% level. The Durbin Watson statistic of 2.17 shows that there no autocorrelation among the variables.

Equation 16 is the estimated result for government consumption (GC). The adjusted coefficient of determination which measure the goodness of fit is very high (0.71%), this implies that the function explains 71 percent linear movements in the dependent variable of GC. The result shows that ratio of development expenditure to GDP (RDEGDP), government revenue (GR) and money supply (MS) have positive and significant relationship with government consumption (G^C).  The coefficient of ratio of development expenditure to GDP (RDEGDP) is 0.72, government revenue (GR) is 0.28 and money supply (MS) is 0.57. This means that a percentage increase in ratios of development expenditure to GDP (RDEGDP), government revenue (GR) and money supply (MS) will lead to 0.72%, 0.28% and 0.57% increase in government consumption (GC) respectively. Their respective t-values are greater than 2 in absolute terms. The coefficient of interest rate (IN) is -0.281 which means a percentage increase in interest rate (INT) will result to 0.281% decrease in government consumption (G^C). Interest rate (INT) is statistically insignificant as indicated by its t-value (-1.38).

Equation 17 show the coefficient of gross domestic product (GDP) is 0.85 which show a positive relationship with disposable income (Y^D) and is statistically significant as indicated by its t-value which is greater than 2 (2.20). Direct tax (DT) indicated correct sign as it show an inverse relationship with disposable income (Y^D). An increase in direct tax (DT) by 1% would lead to a decrease in disposable income (Y^D) by 0.98%. Indirect tax (IT) has coefficient of -0.17 which means that any increase in indirect tax (IT) by 1% will lead to decrease in disposable income by 0.17%. Workers’ remittances (WR) coefficient is -0.37 and that of consumer price index (CPI) is -0.11. This means that an increase in workers’ remittances (WR) and consumer price index (CPI) by 1% would lead to decrease in disposable income (Y^D) by 0.37% and 0.11% respectively. The R² which measures the goodness of fit of the regression model is 0.47. This means that 47% of the variation in disposable income (Y^D) is explained by the explanatory variables (GDP, DT, IT, WR & CPI).

4.3.2 Investment Sector Block Result

Equations 9 and 10 are equations for investment sector which shows the impact of monetary and fiscal policies variables on private investment and government investment (aggregate demand components) and the equations were estimated and the result presented in equation 18 and 19.

PI = -2.240INT + 0.814MS – 2.67Yd + 0.1814GE – 0.520TAX – 0.014PD + 0.107RPSC……………18

(-2.96)        (3.46)       (-5.14)      (4.19)         (2.43)       (-2.29)      (2.84)

R² = 0.90,  R^-2 = 0.86. DW = 1.98

GI= -0.018INT + 0.312MS – 0.013PD + 0.926GE……………………………………………19                                                            (-3.53)           (2.54)       (-1.17)     (4.43)            (1.96)                                                                                                              R² = 0.57,  R^-2 = 0.52. DW = 1.53

Equation 18 showed that the adjusted R^-2 which is 0.86 explains that the goodness of fit of the regression line is very high. The R^-2 implies that the function explains 86 percent linear movements in the dependent variable of PI. Private investment (P^I) equation indicates that the model is a good fit as 90% of the variation in private investment (P^I) is explained by the explanatory variables (INT, MS, YD, GE, TAX, PD & RPSC). All the explanatory variables are statistically significant as their t-values are up to 2 in absolute terms. A percentage increase in MS, GE, and RPSC would result to an increase in Private investment (P^I) by 0.81%, 0.18%, and 0.11% respectively while a percentage increase in INT, YD, TAX and PD would lead to decrease in PI by 2.24%, 2.67%, 0.52% and O.014% respectively. The DW statistics of 1.98 fall within the rejection region. Therefore, there is absence of autocorrelation among the variables.              Equation 19 represents the government investment (GI) sector in Nigeria. The estimated result showed that R^-2 adjusted was 0.52 and this is an indication of goodness of fit for the regression line. As expected, some of the coefficients exerted high positive significance impact on macroeconomic aggregate of government investment (GI). The coefficients of MS (0.31) and GE (0.92) exert positive influence on the government investment (GI). The coefficient of INT (-0.016) and PD (0.013) exert negative influence on the government investment (GI). All the variables except ND (-1.17) are statistically significant at 5 percent level.

4.3.3 Export-Import Sector Block Result

Equations 12, 13 and 14 are equations for export-import sector which shows the impact of monetary and fiscal policies variables on export, import and exchange rate (aggregate demand components) and the equations were estimated and the result presented in equation 20, 21 and 22.

XP = -0.148INT – 0.085EXR + 0.168MS + 0.115GE – 0.373PD……………………………..20

(-2.19)          (-2.42)        (0.42)         (4.28)         (-2.29)

R² = 0.46,  R^-2 = 0.41. DW = 1.56

MP= 0.322MS – 0.045EXR – 0.102INT – 0.104PD + 0.139GE………………………………21                                                          (3.09)        (1.90)         (1.03)          (-2.54)            (1.53)                                                                                                              R² = 0.58,  R^-2 = 0.56. DW = 1.99

EXR= 0.374MS – 0.6231INT – 0.526PD + 0.829GE…………………………………………………………22                                                            (2.67)        (-2.43)            (2.01)      (1.99)                                                                                           R² = 0.76, R^-2 = 0. 71. DW = 1.93

Equation 20 revealed that interest rate (INT), exchange rate (EXR), money supply (MS), government expenditure (GE) and national debt (PD) are the variables that determine export (XP) in Nigeria. The Durbin-Watson statistics test showed no presence of autocorrelation. The adjusted R^-2 which measure the goodness of fit was high (0.41%). This implies that the function explains 41% variability in the dependent variable. The estimated coefficients of equation 20 indicate that INT, MS and GE have a positive influence on the XP. The coefficients of EXR and PD have significant negative influence on XP. The result indicated that a 1% increase in EXR and PD will decrease XP by 0.085% and 0.373% respectively. The t-values of all the variables show that they are statistically significant at 5 percent level except MS.

Equation 21 shows the relationship between import (MP) and Money supply (MS), Interest rate (INT), public debt (PD), exchange rate (EXR) and government expenditure (GE).  The coefficient of MS and GE indicates positive relationship with MP while INT and PD show negative relationship. The t-statistics indicates that MS and PD are statistically significant as their respective t-values of 3.09 and -2.54 are greater than 2 in absolute terms. The coefficient of determination R² is 0.56. This implies that, 56% behaviour of import (MP) is explained by the explanatory variables.                                                                                                                                  The equation for the relationship between exchange rate (EXR) as dependent variable and money supply (MS), interest rate (INT), public debt (PD) and government expenditure (GE) as explanatory variables is estimated and presented in equation 21. The result reveals that money supply (MS) has negative relationship with exchange rate (EXR) while has positive relationship with exchange rate (EXR). All the explanatory variables except government expenditure (GE) are statistically significant as their respective t-values are greater than 2 in absolute terms. The R² which measure the goodness of fit of the regression model is 0.76. This means that 76% of variation in exchange rate (EXR) is explained by money supply (MS), interest rate (INT), public debt (PD) and government expenditure (GE).

4.4 Simulation Experiment 

4.4.1 Model Appraisal

Within-sample simulations are conducted to test the reliability of the model in predicting the movement of the endogenous variables. While assessment of the examination of the goodness of fit of the models and coefficient estimates of individual variables were important for good macro-econometric modeling, good statistical properties in individual equations do not necessarily implied a good performance of the model as a whole. Rather, good forecasting performance of the model depends on the quality of data, how well the behavioral equations are linked and how economically meaningful the coefficient estimates are. Figure 17 -21, which show the actual and simulated values of endogenous variables, provides evidence for the good performance of the model.

In figure 17 – 21, the horizontal axis contains the time period and the vertical axis indicates the number of deviation of that variable from baseline.  The graphs show the stochastic dynamic actual and baseline simulation. Government expenditure (GE), private consumption (PC) and disposable income (Yd), private investment (PI) and government consumption track their historical path well.

A cursory examination of the graphs indicates that the model tracks the time paths and turning points of the endogenous variables reasonably well. This is a good indication that the model captures the workings of Nigeria’s economy with respect to the behaviour of the variables of interest thus, suggesting its suitability for policy simulation.

Presentation of Graphs of the Stochastic Dynamic Baseline Simulation

   Figure 17: Government Expenditure                                       Figure 18: Private Consumption

Figure 19: Disposable Income                                                        Figure 20: Private Investment

Figure 21: Government Expenditure

4.4.2 Model Simulation

Given the appraisal and validity tests and the level of satisfactory performance observed in all the variables and equations, this section attempts to provide simulation on possible outcomes of changes in some selected variables. The process is to introduce shocks in selected policy variables and trace their impact given the relationships in the model. The aim is to examine what would happen to selected macroeconomic variables if a particular policy instrument is altered.

The study uses historical simulation which is the conventional approach in the evaluation of forecasting performance of a macro model with the aim to determine the forecasting performance of the estimated model. If the magnitude of difference between the forecasted and actual value is low then the model has a good forecasting power (Ikhide, 1988).

4.4.3 Simulation Results

The study uses four policy variables for the simulation: interest rate (INT), money supply (MS), capital government expenditure and direct tax with the following scenarios:

Scenario 1:- A decrease in interest rate by 5%

Scenario 2: An increase in money supply by 5%.

Scenario 3: An increase in government expenditure by 5%.

Scenario 4:– A decrease in direct tax by 5%.

Table 3: Results and Analysis of the Simulation Experiments for Scenario 1 and 2

Source: E-views 7 output, 2019

In scenario 1, the study performs a simulation experiment of 5% decrease in interest rate. From the result in table 3, the respective values of the dynamic baseline simulation and scenario solution are presented. With decrease in interest rate by 5%, government capital expenditure (GCE) and government recurrent expenditure (GRE) increase with 4.03% and 2.01% respectively. Also, disposable income (Yd) increase by 1.1%, private consumption (PC) by 0.34%, private investment (PI) by 5.34% and government investment by 0.02%. Export and import also increase significantly as a result of decrease in interest rate by 5% to 3.34% and 2.74% respectively. The result indicated positive shocks all the variables which imply that financial shocks from the interest rate have impact on aggregate demand components.

The result from scenario 2 of the simulation forecast indicates that an increased in money supply by 5% helps to boost private consumption (PC) in the economy by 0.1%. From the result, private investment (PI) increases by 6.7% points while government consumption (GC) and government investment (GI) increases by 0.7% and 0.08% respectively. The shock also pushes the government capital expenditure (GCE) up by 2.44%. The model shows that government recurrent expenditure (GRE), export (XP) and import (MP) also responded to the shock by 2.3%, 3.2% and 3.03% increase respectively.

Table 4:Results and Analysis of the Simulation Experiments for Scenario 3 and 4

Source: E-views 7 output

Scenario 3 examines the increase in government expenditure by 5%. The result shows that government capital expenditure (GCE) appreciates by 12.2% points, government recurrent expenditure (GRE) by 0.5% while export (XP) rise by 0.6% points.  Also, private consumption (PC) and private investment (PI) appreciate by 0.2% and 0.3% respectively. The increase in government expenditure (GE) by 5% also stimulates disposable income (Yd) by 1.1%, money supply (MS) by 0.47% and increases import (MP) by 0.3%. However, the shocks have impact on the aggregate demand components in the economy.

In scenario 4, a decrease in direct tax (DT) by 5% points results in an increase in both government capital expenditure (GCE) and government recurrent expenditure (GRE) by 9.3% and 0.9% respectively. Similarly, a reduction in direct tax (DT) by 5% increases private consumption by 0.1% and private investment by 0.7%. It also increases money supply (MS) by 0.11% export (XP) by 0.2% and import (MP) by 0.1%. This result shows a strong relationship between fiscal policy variables (government expenditure and tax) and aggregate demand components of Nigeria’s economy.

4.5 Discussion of Results

The results from the estimated equations on the impact of monetary and fiscal policies on aggregate demand indicates that money supply (MS) and interest rate (INT) as monetary policy variables are statistically significant in influencing aggregated demand (private consumption, private investment, government consumption and export-import). Money supply is positively related with aggregate demand while interest rate (INT) is inversely related with aggregate demand (private consumption, private investment, government consumption and export-import) in Nigeria during the period under review. The findings are in line with the works of Michael and Ebibai (2014). Similarly, the result indicates that the instruments of fiscal policy (government expenditure) have positive and significant influence on aggregated demand (private consumption, private investment, government consumption and export-import), taxation has negative and significant influence on aggregate demand (private consumption, private investment, government consumption and export-import) and public debt increase affects aggregate demand (private consumption, private investment, government consumption and export-import) negatively in Nigeria during the period under review. These findings are in line with the works of Wissem (2016) and Zhu (2014).

The Simulation results performed on 5% decrease in interest rate (INT), 5% increase in money supply (MS), 5% increase in government expenditure (GE) and 5% decrease in direct tax (DT) show that with 5% decrease in interest rate, private consumption (PC), private investment (PI) and government consumption (GC) increase at 0.34%, 5.34% and 0.5% respectively. Money supply increase leads to private consumption to increase by 0.1% points while government consumption (GC) and private investment (PI) increase by 0.7% and 6.7% respectively. The shock also pushes the disposable income (Yd), export (XP) and import (MP) up by 1.04%, 3.2% and 3.03% respectively. Increase in government expenditure (GE) by 5% shows that export (XP) appreciates by 0.6% points while import (MP) rises by 0.3% points.  Also, private consumption (PC) and private investment (PI) appreciate by 0.2% and 0.3% respectively. The increase in government expenditure (GE) by 5% also stimulates government consumption (GC) by 0.14%, money supply (MS) by 0.47% and government investment (GI) by 0.04%.                                                     Similarly, a decrease in direct tax (DT) by 5% points results in an increase in government capital expenditure (GCE) by 9.3% without any impact on government recurrent expenditure (GRE. Similarly, a reduction in direct tax (DT) by 5% increases private consumption by 0.1% and private investment by 0.7%. It also increases money supply (MS) by 0.11%. Finally, the baseline simulation demonstrates good tracking power of the actual from the baseline simulation as the nature of the oscillation suggested.

4.6 Test of Hypotheses

From the regression analysis, the study reject null hypothesis that monetary policy has no significant impact on aggregate demand in Nigeria and accept the alternative that monetary policy has significant impact on aggregate demand in Nigeria. This is because monetary policy variables (money supply and interest rate) are statistically significant as their t-values are greater than 2 in absolute terms.

In the same vein, the study rejects null hypothesis that fiscal policy instruments has no significant impact on aggregate demand in Nigeria and accepts the alternative hypothesis that fiscal policy instruments has significant impact on aggregate demand in Nigeria. This is because fiscal policy variables are statistically significance in influencing aggregate demand as their t-values are greater than 2 in absolute terms. Government expenditure has a positive and significant influence on aggregate demand, tax is statistically significant and has impact on aggregate demand and public debt has impact on aggregate demand in Nigeria.

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATION

5.1 Summary

Based on reviews of theoretical literature and empirical studies, monetary and fiscal policies are very important policies that are used to influence economic activity of a nation. To influence economics activities using monetary policy, the central bank can use money supply and interest rate. Since money is important in all economic transactions while interest rate is a tool that can be used to motivate investors, having control over them makes central bank, to some extent, have influence over economic decisions, which in turn affect economic output of a country. In the same vein, the economic activities can be influence through the manipulation of fiscal policy instruments such as government expenditure and taxation.

Expansionary fiscal policy increases the level of aggregate demand, through either increases in government spending or reductions in taxes. Expansionary fiscal policy does this by increasing consumption and raising disposable income through cuts in personal income taxes or payroll taxes; increasing investments by raising after-tax profits through cuts in business taxes; and increasing government purchases through increased federal government spending on final goods and services, and raising federal grants to state and local governments to increase their expenditures on final goods and services. Contractionary, fiscal policy does the reverse: it decreases the level of aggregate demand by decreasing consumption, decreasing investments, and decreasing government spending, either through cuts in government spending or increases in taxes.

This study on “the impact of monetary and fiscal policies on aggregate demand in Nigeria is a very elaborate study, since it covers the period between 1986 – 2017. Macro econometric model is specified in the study to assess the impact of monetary and fiscal policies on aggregate demand in Nigeria. The study constructed a model with four structural sector blocks: monetary, fiscal, aggregate demand and external sector block that contains 21 variables. The variables are linked to one another through 8 behavioural equations and 4 identities, considering Nigeria as a market economy. All behavioural equations are modeled based on economic theories for model building.

In this study, some relevant literatures were discussed. This was done under three sub-headings, theoretical review, empirical review and methodological review. The data used in the study were obtained from the CBN statistical bulletin, NBS annual publication, National Population Commission, World Bank publications and other related sources. The two stages least squares (2LS) technique is used to estimate all the behavioural equations specified in the study. The study reveals that money supply (MS) and interest rate (INT) as monetary policy variables are statistically significant in influencing aggregated demand. Money supply is positively related with aggregate demand while interest rate (INT) is inversely related with aggregate demand in Nigeria during the period under review. The findings are in consonance with the works of Michael and Ebibai (2014).

The result also indicates that the instruments of fiscal policy as such government expenditure have positive and significant influence on aggregated demand while taxation has negative and significant influence on aggregate demand in Nigeria during the period under review. The result also shows that public debt (PD) influences aggregate demand. The findings are in tandem with the works of Wissem (2016) and Zhu (2014).

The Simulation results performed on 5% decrease in interest rate (INT), 5% government expenditure, 5% money supply and 5% direct tax influences private consumption, private investment, government consumption and export-import significantly. Finally, the baseline simulation demonstrates good tracking power of the actual from the baseline simulation as the nature of the oscillation suggests in the simulation graphs.

5.2 Conclusion

Monetary and fiscal policies are two major strategies of managing resources and demand pressures in the economy. The major tools of monetary policy that influence the economy are money supply and interest rate. The first tool of fiscal policy is taxation which presents the revenue side of the government’s budget. The second tool of fiscal policy is government spending which presents the expenses side of government’s budget. The debate between economists regarding the impact of monetary and fiscal policies on economic activity is still unsolved so far. This study aims to contribute to this debate by examining the effects of monetary and fiscal policies including money supply, interest rate, and government spending and tax revenue on aggregate demand in Nigeria spanning the period 1986-2017.

To achieve the objective of the study, the study applied macro-econometric model with multiple structural equations which were estimated using two stages least square method (2SLS) and simulation experiment was also performed. The main findings of the study shows that both monetary policy and fiscal policy influence aggregate demand. The study concludes that monetary and fiscal policies are statistically significant in influencing aggregate demand in Nigeria during the period under investigation. Finally, simulation experiment was performed and a cursory examination of the graphs indicated that the model tracked the time paths and turning points of the endogenous variables reasonably well. This was a good indication that the model captured the workings of the Nigerian economy with respect to the behaviour of the variables of interest thus, suggesting its suitability for policy simulation.

• Recommendation

Based on the results and findings in the previous chapter, the study suggests the implementation of the following recommendations:

Low interest rate should be charged through reduction in monetary policy rate by the monetary authority which will lower the cost of borrowing, encourage investors to borrow more for investment which increases the demand for investment and thereby increases aggregate demand.                                                                                                                                        The monetary authority should increase the supply of money in the economy through open market operation and sales of treasury bill to create a favourable investment climate, create jobs, promote non-oil export and revive industries that are currently operation far below their installed capacity.                                                                                                                                  The study suggest that since government expenditure is found to be an aggregate demand stimulant, the government should consider restructuring its expenditure pattern by allocating more towards productive expenditure such as capital projects especially in the area of infrastructural development; this will have the effect of both stimulating private consumption and private investment consumption (aggregate demand) and consequently output growth.              Estimation results in this study also revealed that taxation has a negative impact on aggregate demand (private consumption and investment consumption). Therefore, to fight the problem of low aggregate demand, tax rates should be lowered. Reduction in both direct and indirect taxes improve the purchasing power of the people which stimulate private consumption (aggregate demand) and consequently economic growth.                                                                  Both domestic debt and external debt crowd-out private investment in the short run, government should strive to reduce her debt profile by improving its revenue base.

• Suggestions for Further Studies

It is essential to recognize that there are further features or policy options, such as monetary and fiscal policies instruments such as selective credit control, moral suasion, subsidy etc which might be valuable to improve aggregate demand and economic performance in the future. But due to the limitation of accurate and reliable data availability, time devoted to this study on the one hand and complexity of the model in order accomplish policy analysis on the other, these features have been left for further studies.

The macro econometric model developed in this thesis analyses the impact of monetary and fiscal policies variables on aggregate demand components: consumption sector, investment sector and export-import sector and does not take into account key sub-sector that can improve the quality of this study such as domestic investment sub-sector and foreign direct investment sub-sector.

• Limitation of the Study

The study analyses the impact of monetary and fiscal policies on aggregate demand in Nigeria for the period 1986-2017. The study was constrained by lack of adequate, reliable and inconsistency of data from different sources which affected the study but the outcomes of the study were not invalidated.