Monetary and Fiscal Policies Interactions on Stock Returns in Nigeria

The research examined the effects of monetary and fiscal policies on stock returns in Nigeria. The researchers utilized ex-post facto research design using the time series data of the annual market values of All Share Index (ASI) of the Nigerian Stock Exchange (NSE). It was yearly data on the various monetary policy and fiscal policy variables obtained from the Central Bank of Nigeria Statistical Bulletins covering from 1985 to 2017. The result of the cointegration test reveals a long-run relationship between monetary variables and stock returns. Meanwhile, the overall result shows that monetary policy has a significant effect on stock return. However, there is no long-run relationship between fiscal policy variables and stock returns. Meanwhile, the result of the Unrestricted Vector Autoregression model shows that fiscal policy has a significant effect on stock prices in Nigeria. On the other hand, a long-run relationship exists between monetary policy, fiscal policy, and stock returns. It has a significant effect on stock returns in Nigeria. This implies that monetary and fiscal policies have a significant effect on stock returns in Nigeria. It is recommended that there is a need for the federal government to harmonize fiscal and monetary policies in the same direction and to equally design policies that promote a free market for the growth of the Nigerian economy.


INTRODUCTION
The nexus between fiscal and monetary policies and stock market performance has been the front burner of discourse among several researchers. It is because the achievement of desirable macroeconomic objectives cannot be separately effective compared to a policy mix of suitable levels of monetary and fiscal policies. Fiscal and monetary policies are interrelated main drivers of economic policies of a country as the ineffectiveness of one may cause the federal government of that country to review the other. The policies set up the aim to regulate the affairs of a country to facilitate growth and stability of some vital aggregate economic variables of the price level, real Gross Domestic Product (GDP), real investment, and real consumption. Abata, Kehinde, and Bolarinwa (2012) stated that fiscal and monetary policies were inextricably linked in macro-economic management. The developments in one sector directly affected developments in the other. They further concluded that fiscal policy was central to the health of any economy since the government's power to tax and to spend affected the disposable income of citizens and corporations and the general business climate.
According to Chatziantoniou, Duffy, and Filis (2013), there is a need for government policymakers to have a deep understanding of monetary and fiscal shocks in combination with stock markets. It cannot be underestimated as both policies play a significant role in the economic and financial activities of the economy. It invariably translates into stock market performance. Sede and Omorokunwa (2015) and Gowriah, Seetanah, John, and Keshav (2014) found no significant relationship between fiscal deficit ratio (fiscal policy proxy) and stock returns. They concluded that monetary policy through the money supply and interbank rates exerted more impacts on stock returns than the fiscal deficit ratio. Nwakoby and Alajekwu (2016) indicated that monetary policy had the potential (53%) to influence the stock market.
There are divergences as to which variables of monetary policy (exchange rate, interest rate, inflation rate, rediscount rate, or money supply) and fiscal policy (either tax rate, government expenditure, budget deficit, domestic debt outstanding, or non-oil revenue) are more important. Guérin and Leiva-Leon (2017) found that a highly interconnected stock market was more likely to respond to monetary policy.
Several researchers have studied the effects of fiscal policy on stock return (Ogbulu, Torbira, & Umezinwa, 2015;Anghelache, Jakova, & Oanea, 2016) as well as monetary policy on stock returns (Uwubanmwen & Eghosa, 2015). However, few researchers studied the combined effects of the two policies on stock returns especially in the Nigeria context (Abata et al., 2012;Gowriah et al., 2014;Nwaogwugwu & Evans, 2016;Nwakoby & Alajekwu, 2016;Lawal, Somoye, Babajide, & Nwanji, 2018;Nwaogwugwu, 2018) Researchers are equally divided, whether expansionary or contractionary, inflationary, or disinflationary fiscal and monetary policies have a negative, positive, or non-statistically significant relationship with stock market performance. Also, the recent events in the country depicted by government bail-out funds to various state governments, the devaluation of the Naira occasioned by the rise in the exchange rate, and the fall in the price of Nigerians crude oil, have impacted significantly on the stock market performance.
Using event study analysis and Nonlinear Seemingly Unrelated Regression (NSUR), Thorbecke (1997) found that a significant large relationship existed between stock returns and monetary policy. However, Ekene (2016) stated that the monetary policy variables had no significant impact on stock prices. The researcher concluded that the Nigerian stock market was not yet an efficient mechanism of monetary policy implementation.
Suhaibu, Harvey, and Amidu (2017) investigated monetary policy and stock market dynamics from the African perspective. They used five indicators, namely S&P global equity indices, inflation rate, money, and quasi growth (M2), real interest rate, and GDP growth in a panel Vector Autoregression (VAR) model in 1979-2013. The result showed that the stock markets of the 12 African countries were positively affected contemporaneously by their respective monetary policies through the interest rate. However, they could not find evidence for the reverse reaction. Galí and Gambetti (2015) estimated the response of stock prices to monetary policy shocks using time-varying coefficients VAR. Evidence pointed to protracted episodes in which stock prices ended up increasing persistently in response to an exogenous tightening of monetary policy. That response was at odds with the conventional view on the effects of monetary policy on bubbles and the predictions of bubbleless models. They argued that it was unlikely that the evidence could be accounted for by an endogenous response of the equity premium to the monetary policy shock.
Lütkepohl and Netšunajev (2018) employed a co-integrated Structural Vector Autoregressive (SVAR) model to investigate the relationship between monetary policy in the euro area and the stock market. They found a plausible identification scheme for the stock market and monetary policy shocks, which was consistent with the second-order moment structure of the variables. The model indicates that contractionary monetary policy shocks led to a long-lasting downturn of real stock prices.
In a panel study of European countries, Lee (2007) revealed that the Belgium stock market did not fully capture and reflect all publicly available information on fiscal policy proxied by government budget deficits. However, the other countries did as fiscal policy significantly affected aggregate stock prices, most notably France, Germany, the United Kingdom, and USA stock markets concerning money supply.
There was a long-run relationship between fiscal policy and stock market returns, as confirmed by Ogbulu et al. (2015) in Nigeria. The public expenditure exerted a significantly negative impact on stock prices. Meanwhile, domestic government debt outstanding and non-oil revenue had a significant positive impact. Next, Using Ordinary Least Square (OLS) and Augmented Dickey-Fuller and Phillips-Perron tests on quarter data on six European Union countries Hungary, Romania, Czech Republic, Slovakia, Bulgaria and Poland, Anghelache et al. (2016) found no significant relationship between fiscal policy and capital market performance as well as capital market performance on fiscal policy in both Hungary and Poland. However, bilateral relationships occurred in the Czech Republic and Slovakia. Chunming and Ruo (2015) examined the impact of policy transmission as induced by the interaction between fiscal policy, monetary policy, exchange rates, and external balances. They affected economic growth and inflation for the economies of Brazil, Russia, India, China, and South Africa (BRICS). The results from a panel VAR estimation showed that monetary policy shocks significantly impacted the real economic activity even though the effect from fiscal policy shocks was relatively weak, especially from across country point of view. The impact of policy interaction between fiscal and monetary policies on stock market behavior was seen from the positive interaction between inflation and interest rates channel.
In the research conducted by Bhatti, Ziaei, and Rehman (2015), fiscal policy tools were best used in boosting economic activities in Malaysia. In another empirical analysis carried out by Sede and Omorokunwa (2015) in Nigeria, they used firstorder differences, Autoregressive Distributed Large (ARDL) approach to Error Correction Model (ECM), Granger Causality test, and cointegration. They found out that a long-run relationship existed among all the fiscal and monetary variables and stock returns with more monetary policy instruments tending to Granger cause stock returns more than the fiscal policy ones. It implied that the fiscal deficit ratio was institutionally determined in most cases.
Next, Laopodis (2007) concluded that US fiscal deficits were important to their stock market. It was with taxes having a higher sensitivity than government expenditure. However, there was a general absence of short-run linkages in the case of taxes and federal funds rate equations. Chatziantoniou et al. (2013) did cross-country research of the USA, UK, and Germany. They revealed that both fiscal and monetary policies were very vital in stock market development. They both influenced the different stock markets directly or indirectly.
Consequently, analysts and investors should consider the policies jointly rather than individually in their bid to understanding the relationship between the policies and stock market performance. Gowriah et al. (2014) indicated that fiscal policy did not have a short or long-run effect on stock prices in Mauritius, while monetary policy variables did. Money supply and GDP both exerted significant positive short-and long-run relationships with the stock price. Similarly, interest rates had a highly significant positive one in the long run. Meanwhile, both the effective exchange rate and Consumer Price Index (CPI) had a significant negative relationship. They concluded that the Mauritius stock exchange was not affected by changes in the fiscal policy because it was a developing economy with limited investors. Onyema (2017) investigated the stock market response to fiscal policy shocks in Nigeria by using Structural VAR (SVAR) methods. The data used consisted of 31 yearly observations on total government revenue, total expenditure, and the Nigerian stock market price index from 1985 to 2015. The research found evidence that although stock prices responded positively to fiscal policy shocks, the effect of these shocks on the stock market was insignificant. The observed variation in stock prices was primarily caused by shock. Thus, fiscal policy had very little or no influence on the stock market in Nigeria.
Prukumpai and Sethapramote (2019) examined the impact of monetary and fiscal policy on the Thailand stock market using the SVAR model. The empirical results showed that the Thailand stock market significantly responded to both monetary policy and fiscal policy. However, monetary policy had stronger effects on both real output and stock prices than those in fiscal policy. Also, sector indices were used in place of the overall stock market. The results revealed that different sectors appeared to react heterogeneously to shocks in monetary policy and fiscal policy.
Thanh, Thuy, Anh, Thi, and Truong (2017) concluded that monetary and fiscal policy did not only affect the Vietnam stock market individually but also impacted the Vietnam stock market through their interaction. In addition, Hu, Han, and Zhang (2018) pointed out that the interaction between monetary and fiscal policies had played a significant role in explaining the development of Chinese stock markets.
In Nigeria, Lawal et al. (2018) examined the impact of the interactions between fiscal and monetary policies on stock market behavior and the impact of the volatility of these interactions on the Nigerian stock market. The researchers analyzed monthly data using the ARDL and Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) models. The results showed that the interaction between monetary and fiscal policies influenced stock market returns in Nigeria. The ARDL results showed the evidence of a long-run relationship between All Share Index (ASI) and monetary-fiscal policies. The results from the volatility estimates stated that the ASI volatility was largely sensitive to volatility in the interactions between the two policy instruments.
Nwaogwugwu (2018) empirically examined the impact of macroeconomic policy and stock market behavior in Nigeria. Broad money, interest rate, government expenditure, tax revenue, and GDP were chosen as indicators of macroeconomic policy. Meanwhile, the stock price was used to represent the stock market behavior. The empirical findings showed that money supply and interest rate had statistically significant effects on the stock market in the short-and long-run. Similarly, government spending and taxation had statistically significant effects on the stock market in the short-and long-run. Therefore, it suggested that macroeconomic policy actions had significant effects on the stock market in Nigeria in the short-and longrun. Nwokoye and Emmanuel (2018) investigated the impact of monetary policy on the development of the stock market in Nigeria. The period of the research was from 1981 to 2015. Cointegration and Vector Error Correction Modelling (VECM) were used for the analysis. The cointegration test indicated that there was a long-run equilibrium relationship among the variables of the model. VECM result showed that monetary policy, through the growth rate of the money supply had impacted the development of the stock market positively and significantly in Nigeria. Moreover, the findings further indicated that the prime lending rate had a negative impact on the development of the stock market in Nigeria. Jonathan and Oghenebrume (2017) investigated the relationship between monetary policy and stock market prices in Nigeria. It was to see whether monetary policy influenced stock market prices for the period of 1985 to 2015. A long-run equilibrium relationship was found among the variables used.
The empirical results indicated that monetary policy rate, credit to the private sector, exchange rate, and broad money supply were positively related to stock market prices captured by the all-share index. The exchange rate and broad money supply were found to have a statistically significant impact on stock market prices. The estimated ECM equations showed that the short-run determinants of stock prices were largely from credit to private sector, exchange rate, and one period lagged exchange rate. Meanwhile, the monetary policy rate and broad money supply had a negative relationship with stock market prices in the short-run. Therefore, the results of this research that some monetary policy instruments could be a better predictor of stock market prices in Nigeria.
Empirical literature investigated shows that there are few studies on the impact of both monetary and fiscal policy (macroeconomic policies) on stock market performance (Sede & Omorokunwa, 2015;Bhatti et al., 2015;Gowriah et al., 2014;Nwaogwugwu, 2018). Meanwhile, several researchers have examined the effect of fiscal policy on stock performance (Ogbulu et al., 2015;Onyema, 2017) and monetary policy on stock market performance (Nwokoye & Emmanuel, 2018;Jonathan & Oghenebrume, 2017). In Nigeria, the research has been carried out, but the researchers do not investigate beyond 2007 (Sede & Omorokunwa, 2015). However, there are few studies and empirical evidence that show the effect of fiscal and monetary policies on the Nigerian stock market returns. Therefore, the researchers intend to address the gaps, extend the scope from 1985 to 2017 and previous literature by empirically analyzing the relationship between fiscal and monetary policies and stock returns. It includes other macroeconomic variables such as inflation, exchange rate, cash reserve ratio, and private sector credit growth. Hence, it will improve the existing knowledge on this. The need for this research cannot be overemphasized by considering the major recent events. So, the researchers seek to examine the effects of monetary and fiscal policies on Nigerian stock market returns.

METHODS
This research utilizes ex-post facto research design using the time-series data of the yearly values of All Share Index (ASI) of Nigeria Stock Exchange (NSE). The yearly data on various monetary policy and fiscal policy variables cover the period of 1985 to 2017. Ex-post facto research relies on secondary data obtained after the event has occurred, so there is no interference from the researcher. Descriptive and inferential statistics, presented in tables, are used to analyze the results and findings from the data analysis. In evaluating the effects of monetary and fiscal policies on stock returns in Nigeria, the researchers adapt an earlier model used by Sede and Omorokunwa (2015) in modeling the variables used. All variables are in the natural log. The econometric models are given as follows: ASI t = f (M2 t , EXR t , MPR t , GR/GDP t , GS/GDP t , BB/ GDP t ) (1) ASI t = 0 + 1 M2 + 2 EXR + 3 MPR + 4 GR/GDP t + 5 GS/GDP t + 6 BB/GDP t + Where: M2 t = M2 growth in broad money supply at t time, EXR t = Exchange rate at t time, MPR t = Monetary policy rate at t time GR/GDP t = Government revenue/GDP (ratio of total government revenue to GDP per year) at t time; GS/GDP t = Government spending/GDP (ratio of total government spending to GDP per year) at t time BB/GDP t = Budget balance (government budget balance relative to GDP) at t time 0 = Intercept of the model 1 -3 = The coefficients of monetary policy parameters 4 -6 = The coefficient of fiscal policy parameters = error term

RESULTS AND DISCUSSIONS
The mean, median, standard deviation, skewness, and kurtosis are presented in Table 1. It shows the descriptive statistics of the variables used. The mean value shows that all variables have positive values except for BB_GDP. It has a negative mean value of -2,66. It is also revealed that EXR has the highest mean value (79,9), followed by GR_GDP (19,2). Then, MPR, GS_GDP, LNASI, and LNM2 rank the third (13,6), the fourth (11,04), the fifth (8,5), and the sixth (6,6) respectively. For virtually all the data series, the researchers observed that the values of mean and median and mode are very close. It suggests that the distribution is near symmetry. The minimum and maximum changes range from positive to positive in all the case variables except for BB_GDP that ranges from negative to positive. It implies that the budget has remained negative. There may be instances of no change in BB_GDP, or the changes are approximately zero.
Moreover, from Table 1, it is evident that EXR has the highest standard deviation (63,77), while other variables are relatively low. It implies that EXR is the most volatile factor among these variables considered in this study. The results also show that LNASI, EXR, BB_GDP, and LNM2 are negatively skewed. Meanwhile, GR _GDP, GS_GDP, and MPR are positively skewed. It also indicates that LNASI, EXR, BB_GDP, GR-GDP, and LNM2 are platykurtic since the value is less than three. It implies that the variables produce fewer and less extreme outliers than those in the normal distribution. Then, GS_GDP and MPR are higher than three, so it is leptokurtic.
The unit root test is carried out to determine the order of integration of each of the variables. It is to see whether the variables contain a unit root, so it is nonstationary using the Augmented Dickey-Fuller (ADF) test. The result is presented in Table 2. It shows that all the variables considered are not stationary at the level of their probability value, however, they are stationary at the first difference. Therefore, it means that the variables considered in this research are multileveled integrated. Then, these variables are integrated of order one, so a long-run linear combination is suspected amongst them. Therefore, a cointegration test is conducted to ascertain if the long-run relationships exist or not. From Table 3, both the Trace statistics and Max-Eigen test results are given. The Trace statistics shows that the null hypothesis of at most one cointegrating equation is rejected because of the alternative hypothesis at 5% level of significance. It is greater than the critical values at a 5% level of significance. It means that there is a long-run relationship between the variables. The Trace test indicates two cointegrating equations.
Similarly, the Max-Eigen test also indicates two cointegrating equations. Moreover, the result of the Johansen cointegration test strongly rejects the null hypothesis of no cointegration among the five variables. It provides evidence of two cointegrating vectors at a 5% significance level. Since the result of the Johansen cointegration indicates that the variables are integrated, the VECM is used.
The result of VECM is in Table 4. The coefficient of the ECM is correctly signed and statistically significant. The value shows that the speed of adjustment of long-run equilibrium is approximately 52%. Therefore, it suggests that long-run causality exists between monetary policy, fiscal policy, and stock returns in Nigeria. Both independent variables have any significant influence on the dependent variable (LNASI) in the long run.   The result shows that the one-year period lagged LNASI is positively related to the LNASI. It suggests some inertia response of LNASI to its lag. Thus, the stock returns, as measured by ASI last year, can significantly and systematically impact on ASI in this year. Its coefficient value of 0,46 implies that 1% of the increase in ASI in the previous year will lead to 46% of the increase in ASI in the current year, which is also significant at 5%. In the case of a period lag of M2, which is used as a proxy for monetary policy, it has a negative sign with a relatively high coefficient value of 0,62. It implies that 1% of the increase in the money supply in the previous year will lead to 62% of the decrease in LNASI. It probably suggests that the high level of money supply impacts their potentials to contribute to stock performance largely and negatively. A similar result is obtained in MPR. It is negatively reflected by the low level of MPR contribution to stock performance in Nigeria. However, a period lag of EXR reveals a positive coefficient of 0,02, which is also statistically significant at 5%. It implies that 1% of the increase in the exchange rate led to 2% of the increase in stock returns.
On the other hand, a period lag of GS_GDP, GR_GDP, and BB_GDP reveals a negative and insignificant effect on stock returns. Moreover, a period lag of GS_GDP shows a negative coefficient of 0,022. Then, GR _GDP has a negative coefficient of 0,023. Meanwhile, BB_GDP coefficient shows that 1% of the increase in BB_GDP leads to 2,3% of the decrease in stock returns. It can be inferred from the statement that government activities (fiscal policy) do not contribute positively to stock returns.
In the result of the R-squared, the explanatory variables explain 56,1% of changes in the dependent variable. It implies that about 43,9% variation in the independent variable is caused by other factors that are not considered in this research. It is reduced slightly after adjusting for the degrees of freedom to 35,4% (Adjusted R-Squared). Moreover, the F-statistics shows that the result is statistically significant as the probability value of F-statistics is lower than 5%. Thus, this research rejects the null hypothesis that there is no significant effect of monetary policy and fiscal policy (macroeconomics policy) on stock returns. Furthermore, the error correction term has the expected negative sign. It is highly significant at 5% level. This further lends credence to the good model specification of the model. The coefficient of the error correction term is 0,542. It shows that 54,2% of the disequilibrium in stock returns is corrected in the following year. This value appears to be considerable enough to ensure speedy stock returns.
The results are in line with Laopodis (2007) and  Sede and Omorokunwa (2015). They also agreed that a long-run relationship exists between monetary policy, fiscal policy, and stock returns. It is also validated by previous researchers such as Chatziantoniou et al. (2013), Bhatti et al. (2015), and Sede and Omorokunwa (2015). As suggested by Chatziantoniou et al. (2013), there is a need for government policymakers to have a deep understanding of monetary and fiscal shocks in combination with stock markets. It cannot be underestimated as both policies play a significant role in the economic and financial activities of the economy, which is invariably translated into stock market performance. Based on the findings of this research, it is recommended that there is a need for the federal government to harmonize fiscal and monetary policies in the same direction and to equally design policies that promote free entrepreneurs for the growth of the Nigerian economy. Also, there is a need for a framework to ensure that the liquidity of the foreign exchange market should be in place to restore investors' confidence, enhance foreign exchange inflows, boost foreign direct and portfolio investments, and reduce the level of uncertainty in the economy. There is also a need to increase the manufacturing activities in the country to boost the economy through the provision of infrastructure, access to foreign exchange, and improve the ease of conducting business in the sector.

CONCLUSIONS
There is a common belief that monetary policy should not be examined in isolation from fiscal policy and vice versa, as they both individually and collectively play important roles in economic growth. They also influence stock performance. The stock market is the focal point in the country's economy. Hence, this research examines the effects of monetary and fiscal policies on stock returns in Nigeria.
The monetary and fiscal policy variables applied are monetary policy rate, broad money supply, exchange rate, government revenue relative to GDP, government spending relative to GDP, and government budget balance relative to GDP. The researchers develop an econometric model using cointegration to estimate the effects of the monetary and fiscal policy variables on the stock return. The researchers find that a long-run relationship exists between monetary policy, fiscal policy, and stock returns. It has a significant effect on stock returns in Nigeria. Thus, it suggests that fiscal and monetary policy have a significant effect on stock returns in Nigeria. Finally, future researchers need to consider countries with significantly different monetary policy regimes and fiscal policies. They can also extend the scope beyond 2017. Moreover, the future researchers should also consider adopting quantitative easing as a money policy and other measurements of stock performance.