Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: IMPACT OF CURRENCY INTERVENTION ON EXCHANGE RATE IN NIGERIA Hamisu Ali1 Department of Economics, Faculty of Social and Management Sciences, Adamawa State University, Mubi Email: hamisu006@gmail.com James Tumba Henry2 Email: henry723@adsu.edu.ng Department of Economics, Faculty of Social and Management Sciences, Adamawa State University, Mubi Abstract The Central Bank of Nigeria has expanded her monetary policy toolkits to include currency intervention so as to ensure that the exchange rate of the naira relative to other currencies is stable. However, whether this intervention has an impact on exchange rate of the naira and sterilized is still under contention. Thus, this study was undertaken to understand what currency intervention means, the theoretical foundation of currency intervention and empirically study it impact on exchange rate in Nigeria. The study employed Error Correction Model (ECM) and time series data from 1980 to 2018. The result obtain revealed that currency intervention has no significant impact on exchange rate in Nigeria in the short run and it is non-sterilized. It was therefore recommended that the CBN should strictly monitor the foreign exchange market to ensure that the monies released as intervention are used for the purpose they are meant for and therefore avoid speculative tendencies inherent in the Nigerian Foreign Exchange Market. Keywords: monetary policy, currency intervention, exchange rate 1.0 INTRODUCTION One of the main reasons for establishing the Central Bank of Nigeria is to conduct monetary policy so as to preserve the value of the domestic currency. According to the International Monetary Fund (IMF) factsheet (2017), central banks in recent times have expanded their toolkits to deal with risks associated with financial instability and to manage volatile exchange rates. One of the monetary policy tools employed especially to maintain exchange rate stability by the central banks of developing countries (including Nigeria) is currency intervention or foreign exchange market intervention. Conceptually, currency intervention sometimes called currency manipulation occurs when the government through the central bank buys or sells �hard currency� in exchange for their own local currency with the aim of influencing the exchange rate and trade policy. In other words, the Central Bank of Nigeria (CBN, 2016) explained that currency intervention occurs when the central bank or monetary authority sells or buys foreign currency to ease volatility and bring calmness to the forex market. The essence of currency intervention is to ensure that the exchange rate is stable over a period of time to aid and boost economic activities. In literature, some of the motives that have been advanced for currency intervention as highlighted by Chutasripanich and Yetman (2015) are: leaning against the wind; reduce exchange rate misalignment; managing or accumulating foreign reserves and ensure adequate liquidity in the foreign exchange market. Thus, when the price of foreign exchange increases, the central bank intervenes by selling foreign exchange to the market to boost supply. This will bring down the price of foreign exchange. Similarly, when the price of foreign currency decreases, it buys foreign exchange from the market. This will eliminate the over-supply of foreign exchange to the market and the price will increase to the desired level. However, before a central bank intervenes, there must have been a detailed analysis of the factors affecting the market (CBN, 2016). To support this assertion, Moreno (2005) opined that central banks intervene in foreign exchange markets in order to achieve a variety of overall macroeconomic objectives, such as controlling inflation, maintaining competitiveness or maintaining financial stability. However, the precise policy objectives and how it is reflected in the currency intervention framework will depend on the development stage a country is in, the level of financial development and integration of the country, and the vulnerability of a country to external shocks. Intervention in the foreign exchange market is to ensure balance in the short- run and to prevent wide swings from taking place on a day-to-day basis. The number of times a central bank intervenes in a market at a particular period is determined by the severity of the situation (CBN, 2016). Empirically, when discussing the theories of currency intervention and how it affects the exchange rate in developing countries, distinction is always made between sterilized and non-sterilized intervention. Sterilized intervention is a policy that attempts to influence the exchange rate without changing the monetary base while the non-sterilized intervention is a policy that alters the monetary base. In Nigeria, few studies that have been conducted have shown mixed conclusions about whether the CBN currency intervention policy is sterilized (Adebiyi, 2007; ) or non-sterilized (Akinkunmi, 2017; Omojolaibi & Gbadebo, 2014; Dayyabu, Adnan & Sulong, 2016). Hence, this study seeks to investigate the impact of currency intervention on the value of the naira and to also know whether the CBN�s intervention in the foreign exchange market is sterilized or not. This means to know whether Forex intervention has an impact on the growth of money supply (M2) in Nigeria. 2.0 EXCHANGE RATE MANAGEMENT AND INTERVENTIONS IN NIGERIA In Nigeria, prior to 1986, the authorization of foreign exchange disbursement was a shared responsibility between the Federal Ministry of Finance and the CBN and the exchange rate of the naira was pegged against the US dollars and other reference currencies. Shortly after adopting the International Monetary Fund (IMF) and World Bank Structural Adjustment Programme (SAP), the modalities for managing foreign exchange market changed to reflect a market-oriented approach to price determination. Thus, the Second-tier Foreign Exchange Market (SFEM) was established (in 1986) when the determination of the Naira exchange rate was made to reflect the forces of demand and supply. In a bid to achieve a realistic exchange rate for the Naira, the first and second-tier exchange rate markets were integrated into one big Foreign Exchange Market (in 1987) and different pricing methods like weighted average, marginal and Dutch Systems were adopted. As part of the policy reform, the Bureau de Change foreign exchange market was introduced in 1989 to deal with privately sourced foreign exchange (Oyinlola, 2018). Ever since then, the CBN has always intervened in the foreign exchange market although with a policy change from free-floating exchange rate to guided deregulation (in 1995) that led to the institutionalization of the Autonomous Foreign Exchange Market (AFEM). In 1999 however, the AFEM was changed into a daily, two-way quote Inter-bank Foreign Exchange Market (IFEM) which is expected to broaden and deepen the foreign exchange market on daily basis and discourage speculative tendencies (CBN, 2016). The exchange rate policy adopted between 2002 and 2013 were the Retail Dutch Auction System and the Wholesale Dutch Auction System. Consequently, the interbank foreign exchange market with CBN interventions was introduced from November 2013 to June 2016 (Oyinlola, 2018). In early 1995, the CBN initiated a substantial liberalization of the country�s exchange rate system. The exchange rate policy adopted in 1995 represented a major turnaround from the abandonment of market-based mechanisms that had occurred between 1993 and 1994, and they were accompanied by strong efforts to restore fiscal and monetary discipline [International Monetary Fund (IMF), 1998]. From early 1995 to 2018, the policies have resulted in a fairly stable market-oriented exchange rate for the naira. The IMF (1998) asserted that six (6) AFEM intervention exercises took place in 1995, with total funding of $1,741 million at rates of N80 to N85 per U.S dollar, as compared with 15 allocations the previous year at the official rate totaling $1,961 million. In 1996 however, the policies initiated in 1995 remained in effect but a few modifications were introduced. One of the modifications made was that the requirements that visitors pay hotel bills and official service fees such as airport taxes in foreign currency were abolished (IMF, 1998). In February 1996, the CBN reinstated the AFEM rules and announced that foreign exchange intervention will be monthly. Thus, in May 1996, the intervention was changed to weekly. In 1996 alone, 35 intervention exercises were conducted totaling $1,846 million resulting in the appreciation of the naira from N85 per U.S dollar to N80 per U.S dollar (IMF, 1998). In early 1997, the Nigerian foreign exchange market was further liberalized with the same AFEM system and the CBN started conducting interventions every Wednesday of each week. According to IMF (1998), this intervention rate is what is known as the AFEM rate, rather than the interbank rates. Similarly, in early 1998, the AFEM system remained unchanged and the interventions conducted during this period were exceptionally high, reaching $4770 million in January, three-and-a-half the year-earlier and 11 times that of January 1996 (IMF, 1998). This made the exchange rate of the naira relative to the U.S dollar to depreciate from N81 in January 1998 to N84 in late February 1998. In October 1999, the foreign exchange market was further liberalized and the inter-bank foreign exchange market (IFEM) replaced the AFEM (Essien, Stephen & Omotosho, 2017). The AFEM intervention rate continues to depreciate from N84 per dollar in 1998 to N91.83 in 1999. However, subsequent reforms and interventions led to a further depreciation of the naira between 1999 and 2004 when it reached N132 per U.S dollar (Oyinlola, 2018). Between 2004 and 2008 the Nigerian currency appreciated for the first time after the 1995 liberalization policy. Ever since then, the value of the naira against the U.S dollar keeps depreciating, reaching N192 per U.S dollar in 2015 and N253 per U.S dollar in 2016 in spite of the CBN�s intervention. The official exchange further depreciated to N305 per U.S dollar in 2017 and N306 in 2018. The CBN�s intervention in the foreign exchange market has led to numerous exchange rates for the naira against the U.S dollars. There is government budget exchange rate, bureau de change rate, interbank rate, fuel merchant rate, black market rate, western union rate, foreign medical trips rate, and pilgrimage rate. 3.0 THEORETICAL BACKGROUND The sterilized intervention procedure is a combination of two transactions. First, the central bank conducts a non-sterilized intervention by buying (selling) foreign currency bonds using the domestic currency. Then the central bank �sterilizes� the effects on the monetary base by selling (buying) a corresponding quantity of domestic currency-denominated bonds to soak up the initial increase (decrease) of the domestic currency. The net effect of the two operations is the same as a swap of domestic-currency bonds for foreign-currency bonds with no change in the money supply (Maurice, 1996). With sterilization, any purchase of foreign exchange is accompanied by an equal-valued sale of domestic bonds. For example, desiring to decrease the exchange rate, expressed as the price of domestic currency, without changing the monetary base, the monetary authority purchase foreign currency bonds. After this action, in order to keep the monetary base unchanged; the monetary authority conducts a new transaction, selling an equal amount of domestic-currency bonds so that the total money supply is back to it original level. On the other hand, in the non-sterilized intervention, authorities affect the exchange rate through purchasing or selling foreign money or bonds with domestic currency. For example, aiming at decreasing the exchange rate or price of the domestic currency, authorities could purchase foreign currency bonds. During this transaction, the extra supply of domestic currency will drag down domestic currency prices, and the extra demand for foreign currency will push up foreign currency prices. As a result, the exchange rate will drop. 3.1 Sterilized Theories of Currency Intervention 3.1.1 Signaling/Expectation Approach The signaling approach works on the assumption of information asymmetry where the central bank has an information advantage over market agents with regard to future monetary policy or the long-run equilibrium value of the exchange rate (Chipili, 2014). By intervening in the foreign exchange market, the central bank changes market agents' expectations of future fundamentals by providing information about future monetary policy. When the central bank buys domestic currency, a contractionary future monetary policy is signaled to the market. This induces agents to revise their expectations of the future exchange rate, given that the exchange rate is forward-looking, resulting in an appreciation. The signaling theory predicts that the exchange rate will depreciate following a sterilized purchase of foreign currency by the central bank if the purchase is assumed to signal a more expansionary domestic monetary policy. A depreciation of the exchange rate occurs because the central bank does not alter the domestic monetary base to avoid the agents misconstruing it as a change in the monetary policy stance. Intervention in this context is effective if and only if the signal about future monetary policy arising from intervention is credible. 3.1.2 Portfolio-Balance Approach According to Chipili (2014) the portfolio-balance channel, investors diversify their holdings among domestic and foreign assets as a function of both expected returns and the variance of returns. Intervention, therefore, affects the level of the exchange rate through the portfolio-balance channel by altering the relative supply of foreign and domestic securities, compensating investors by a risk premium for holding foreign securities, provided that these securities are imperfect substitutes. This creates disequilibrium in the investors� portfolio. Equilibrium is restored through a change in the risk premium, which causes a change in asset returns imbedded in capital gains, thereby producing changes in the spot exchange rate. In an event that intervention increases the supply of domestic assets relative to foreign assets held by the market, a higher expected return on domestic assets will be demanded on domestic assets for the market to willingly hold them, resulting in the depreciation of the domestic currency. However, if these securities are perceived to be perfect substitutes, intervention is predicted to have no effect on the exchange rate. 3.1.3 Noise-Trading Approach In this approach, the exchange rate is allowed to move away from its fundamental value due to a rational bubble, which reflects the behavior of �noise traders�. Noise traders (chartists) are those traders whose demand for currencies or other assets is influenced by beliefs or sentiments that are not fully consistent with economic fundamentals. They base their expectations of future changes in the exchange rates on the behavior of past values of the exchange rates (Chipili, 2014). Noise traders can, therefore, move asset prices away from their fundamental equilibrium when induced by the central bank through intervention to either buy or sell currency. This affects the noise traders� perception of the trend in the exchange rate changes. Intervention in this case either increases or reduces exchange rate volatility by leaning with or against the wind, respectively, when noise traders move the exchange rate away or towards its fundamental value. The theory is ambiguous on the effects of central bank intervention on exchange rate volatility. Central bank intervention can reduce exchange rate volatility if it helps resolve market uncertainty about future fundamentals and policies, or if it reduces the likelihood of speculative attacks on the currency and vice versa. 3.1.4 Liquidity Approach This approach presupposes that intervention might have a direct impact on the exchange rate volatility, but not the level. Intervention is expected to have a short term, flow-driven impact on the exchange rate if the size of intervention is large relative to the market turnover within a brief period of time. The size of the intervention influences fundamentals, which, in turn, affect the nominal exchange rate. In addition, intervention reduces the risk of market-making through the provision of more liquidity on the market, which induces dealers to provide additional liquidity, thereby affecting fundamentals and, ultimately, the exchange rate. 3.2 Non-Sterilized Theory of Currency Intervention 3.2.1 Monetary Approach This is the only currency intervention theory under the non-sterilized intervention approach to exchange rate determination. This approach tries to explain how the value of a domestic currency is directly or indirectly affected due to the changes in the foreign and domestic supply of and demand for money (Dayyabu et al., 2016). This theory presumed that in the short-run, prices are flexible. Dominguez (1998) as cited in Dayyabu et al. (2016) opined that the monetary approach to foreign exchange market intervention indicates a situation where non-sterilized intervention affects the value of domestic currency exchange rate equal to the changes in the relative amount of supplies of domestic and foreign exchanges. 4. LITERATURE REVIEW The bulk of literature on currency intervention has focused on whether such foreign exchange policy is sterilized or non-sterilized. The study of Disyatat and Galati (2005) surveyed the literature on the efficacy of foreign exchange market intervention in emerging market countries with evidence from the Czech koruna using daily data from 2001 to 2002. The study used dynamic OLS to estimate the data obtained for this study. The result revealed that central bank intervention had weak-statistical significant impact on the spot rate and the risk reversal but the magnitude of the impact was small. It was therefore concluded that currency intervention has no influence on short-term exchange rate volatility. Similarly, Miyajima and Montoro (2012) investigated the impact of foreign exchange interventions on exchange rate expectations in four selected emerging economies (Brazil, Korea, Malaysia, and Peru). The study employed panel regression model to analyze monthly data from 2002 to 2012. The result obtained revealed that sterilized central bank foreign exchange intervention has little systematic influence on near-term nominal exchange rate expectations in the direction intended by the central banks. It was concluded that intervention may not change near-term exchange rate expectations. In Japan, Fatum and Hutchison (2003) investigated the effectiveness of foreign exchange market intervention using official daily data from April 1, 1991, to December 31, 2000. The study used non-parametric sign test and matched-sample test. The result revealed that there is strong evidence that sterilized intervention systematically affects the exchange rate in the short-run. It was therefore recommended that the Bank of Japan could indeed engineer exchange rate depreciation even though interest rate cannot be moved further downwards. Contrary to the finding of Fatum and Hutchison (2003), Pontines (2018) evaluates the effectiveness of official foreign exchange intervention on the movement of the exchange rate in Japan using daily data from 1999:M1 to 2011:M12. The study employed a Tobit regression model and the self-selection bias technique. The result obtained revealed that the period of intervention is characterized by large, infrequent and sporadic interventions are effective in moving the changes in the exchange rate in the desired direction. The study also showed that once the exchange rate moves in the desired direction, the effect is not long-lasting but slightly longer. It was concluded that in spite the fact that intervention is an effective tool, it cannot be regarded as a panacea that can move exchange rates at every point in time. Using a two-stage IV-panel approach Adler and Tovar (2014) examined the effectiveness of sterilized interventions in influencing the exchange rate of 15 Latin American countries from 2004 to 2010. The result revealed that interventions slow the pace of appreciation, but the effects decrease rapidly with the degree of capital account openness. It was therefore concluded that interventions are more effective in the context of an already overvalued exchange rate. Using Analysis of Variance (ANOVA), Kembe (2013) investigated the impact of central bank intervention on foreign exchange rate volatility in Kenya using annual data from 2008 to 2011. The result revealed that intervention operations generally reduce exchange rate volatility and that it is more effective when the intervention is made public. The result also showed that the Central Bank of Kenya intervention is felt in the market immediately. It was concluded that the central bank and other players in the Kenyan financial sector should develop hedging instruments to minimize speculative tendencies prevalent in the foreign exchange market. In Zambia, contrary to Kembe (2013), Chipili (2014) analyses the impact of central bank intervention on exchange rate volatility using weekly data from 1996 to 2010. The study employed a GARCH framework as its estimation technique. The result obtained revealed that foreign exchange intervention has statistical weak-negative impact on exchange rate volatility. It was, therefore, suggested that the Central Bank of Zambia should not rely entirely on intervention to dampen exchange rate volatility and that domestic changes are required to reinforce intervention. In Nigeria, Adebiyi (2007) investigated the impact of foreign exchange intervention in the Nigerian foreign exchange market. The study employed the Autoregressive Distributed Lag (ARDL) model to analyze quarterly data from 1986:Q1 to 2003:Q4. The study revealed that foreign exchange intervention in Nigeria is sterilized because cumulative aid, which constitutes part of foreign exchange inflows, and net foreign assets variables, which are proxies for intervention, are significant. It was therefore concluded that the use of the stock of external reserves to support the exchange rate through increased funding of the foreign exchange market should be encouraged. Contrary to the findings of Adebiyi (2007), Omojolaibi and Gbadebo (2014) examined the impact of foreign exchange rate intervention on monetary aggregates in Nigeria using time series data from 1970 to 2006. This study also used the Autoregressive Distributed Lag (ARDL) model as its estimation technique. The result revealed that all explanatory variables (net foreign private capital, real gross domestic product and dummy variable) except cumulative net foreign assets are significant at 5% level of significance. This implies that there is an incomplete sterilized intervention in the Nigerian Forex market since all the variables are not significant. It was concluded that given the adverse effects of the non-sterilized intervention, the Nigerian government should allow intervention to be economically motivated rather than being politically executed. To support the findings of Omojolaibi and Gbadebo (2014), Dayyabu et al. (2016) investigated the effectiveness of foreign exchange market intervention in Nigeria using time series data from 1970 to 2013. The study employed cointegration, error correction model and granger causality to estimate the data obtained for the study. The result granger causality result revealed that the CBN intervention is non-sterilized. It was concluded that the CBN should provide an effective way through which its FEM intervention could be efficient and sterilized so as to ensure stability in the exchange rate and the price level. Using the Panel Data framework, Akinkunmi (2017) examined the exchange rate rebound effects of the Central Bank intervention in selected ECOWAS countries (Ghana, Senegal, Nigeria, Sierra Leone, and Ghana) from 1992 to 2016. The result showed that the impact of the central bank intervention on exchange rate is insignificant and it does not lead to the exchange rate rebound effect. Based on this finding, the study recommended a reduction in the rate of intervention in the exchange rate market and allowing the market mechanisms to operate the market. 4.1 SUMMARY OF RELATED LITERATURE AND RESEARCH GAP There are strands of literature that tries to investigate the relationship between currency intervention and exchange rate movement in different countries, but a few of them focused on Nigeria. The literature reviewed above showed some interesting findings but sometimes contradictory. Few of these studies especially the ones done on Nigeria are summarized below: Table 1: Summary of Related Literature and Research Gap Author(s)/Year of Study Title and Scope Variables Method Major Findings Weakness Adebiyi (2007) A Study of Foreign Exchange Intervention and Monetary Aggregates in the Nigerian financial sector (1986:Q1-2003: Q4) Cumulative net foreign assets, cumulative aid, broad money supply, and gross domestic product Autoregressive Distributed Lag (ARDL) model The study revealed that foreign exchange intervention in Nigeria is sterilized This study only centers whether currency intervention is sterilized or not Omojolaibi and Gbadebo (2014) Foreign Exchange Intervention and Monetary Aggregates: Nigerian Evidence (1970-2006) Broad Money supply (M2), cumulative net foreign asset, cumulative net foreign private capital, real gross domestic product, and dummy variable for years of intervention Autoregressive Distributed Lag (ARDL) model There is an incomplete sterilized intervention in the Nigerian Forex market since all the variables are not significant The basis for judging whether intervention is incomplete is not known Dayyabu et al. (2016) Effectiveness of Foreign Exchange Market Intervention in Nigeria (1970-2013) Exchange rate, money supply, net foreign asset, and the lending rate Johansen Juselius cointegration, Error Correction Model and Granger Causality Test Intervention is non-sterilized This study only centers on whether currency intervention is sterilized or not Akinkunmi (2017) Rebound Effects of Exchange Rate and Central Bank Interventions in Selected ECOWAS Countries (1992-2016) Exchange rate, intervention variable, and monetary policy rate Fixed and Random Effects Models Central bank intervention on the exchange rate is insignificant. This implies it is non-sterilized This is not country-specific Source: Compiled by the Author From Table 1 above, it is obvious that most of the studies only concentrated on whether currency intervention is sterilized or non-sterilized without looking at whether it has an impact on exchange rate of the naira. Thus, this study added to existing literature by investigating the impact of currency intervention on exchange rate in Nigeria from 1980 to 2018. 5. METHODS AND DATA 5.1 Methods To empirically investigate the impact of currency intervention on the exchange rate and to know whether the Central Bank of Nigeria foreign exchange interventions is sterilized or non-sterilized, this study adopted descriptive research design. This is appropriate for this study because it is theory-based created by gathering, analyzing and presenting data collected. The theory that underpins this study is the portfolio balance approach. The major concern of this approach is that investors strive to invest their portfolio either in domestic assets or foreign assets given their expected returns and the risk associated with these returns. According to Dayyabu et al. (2016), after the central banks have intervened in the foreign exchange market, the amount of currency released as intervention operation is offset by the domestic open market purchase of the local currency. This is done so that the intervention will not affect the monetary base of the economy that is capable of resulting in inflation due to excess money in circulation. What happens is that the central bank keeps rebalancing its portfolio through buying and selling of domestic and foreign assets. Thus, this study adopted the model used in the study of Dayyabu et al. (2016) where exchange rate is expressed as a function of cumulative net foreign asset (proxy for intervention), money supply and interest rate. ?EXR?_t = f (NFA, M2, LR) 1 In this study, the foreign exchange reserve is used to augment the model because a country cannot defend the value of her local currency without accumulating enough foreign exchange reserves. In this light, Ryan (2017) opined that foreign exchange reserve serves as formal backing for domestic currency. Similarly, to avoid strong serial correlation in the model, this study removed lending interest rate from the model and replaces it with one period lag of exchange rate (LAGEXR). Thus the exchange rate and currency intervention model used in this study become: ?EXR?_t = f (LNFA, M2, RES, LAGEXR) 2 Stating the linear form of equation 2, it becomes: Model 1: Exchange Rate and Currency Intervention ?EXR?_t = ?_0 + ?_1 ?LNFA?_t + ?_2 ?LM2?_t + ?_3 L?RES?_t+ ?_4 ?LAGEXR?_t + ?_t 3 In equation 3, ?EXR?_t is the nominal exchange rate at time t, ?LNFA?_t is natural log of net foreign asset proxy for currency intervention because most studies (Adebiyi, 2007; Omojolaibi & Gbadebo, 2014; Dayyabu et al., 2016 among others) used it due to unavailability of data on intervention in some countries like Nigeria, LM2 natural log of broad money supply at time t, ?RES?_t is foreign exchange reserve at time t, ?LAGEXR?_t is a one-period lag of exchange rate at time t and ?_t is the stochastic error term at time t. To determine whether the central bank of Nigeria's currency intervention policy is sterilized or non-sterilized, this study adopted the model of Adebiyi (2007) where broad money supply (M2) is expressed as a function of cumulative aid, cumulative net foreign assets, gross domestic product, and a dummy variable. ?M2?_t = f (cNFA, cAID, GDP, DUM) 4 In this study, cumulative aid (cAID), gross domestic product (GDP), dummy (DUM) variables were removed because they are not core determinants of money supply. According to Fry (1985), as cited by Bakare (2011), some of the factors that influence the growth of money supply are domestic credit expansion to private sector, domestic credit to public sector, interest rate, and net foreign assets. However, this study used domestic credit to the private sector and lending interest rate as a control variable due to the unavailability of data on domestic credit to the public sector. Thus the money supply and currency intervention model used in this study become: ?M2?_t = f (NFA, LR, DCP) 5 Stating the linear form of equation 2, it becomes: Model 2: Money Supply and Currency Intervention ?M2?_t = ?_0 + ?_1 ?LNFA?_t + ?_2 ?LR?_t+ ?_3 ?LDCP?_t+ u_t 6 In equation 6, ?M2?_t is the broad money supply at time t, ?LNFA?_t is cumulative net foreign asset used as a proxy for intervention, LR is lending interest rate, LDCP natural log of domestic credit to the private sector at time t, and u_t is the stochastic error term at time t. 5.2 Data This study used annual time series data from 1980 to 2018 to examine the relationship between the variables in the two models above. This period was chosen so as to avoid micronumerosity and because Nigeria switched from a pegged exchange rate regime shortly after adopting the IMF/World Bank Structural Adjustment Programme (SAP) in 1986 to different versions of the free-floating exchange rate regime. Within this period, the Central Bank of Nigeria intervened severally with the aim of achieving a realistic exchange rate for the naira. Table 2: Description of Variables, Sources and A priori Expectation VARIABLE DESCRIPTION SOURCE A PRIORI EXPECTATION Nominal Exchange Rate (EXR) The official exchange rate refers local currency units relative to the U.S. dollar. World Bank, World Development Indicators Dependent Variable Broad Money Supply (LM2) Broad money is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler�s checks; and other securities such as certificates of deposit and commercial paper in millions of naira. World Bank, World Development Indicators Dependent Variable + Cumulative Net Foreign Asset (CNFA) Net foreign assets are the sum of foreign assets held by monetary authorities and deposit money banks, less their foreign liabilities in millions of current local currency. World Bank, World Development Indicators + Lending Interest Rate (LR) Lending rate is the bank rate that usually meets the short- and medium-term financing needs of the private sector. World Bank, World Development Indicators _ Foreign Exchange Reserve (RES) Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities in millions of naira. World Bank, World Development Indicators + Domestic Credit to the Private Sector (DCP) Domestic credit to the private sector refers to financial resources provided to the private sector by financial corporations in millions of naira. World Bank, World Development Indicators + Source: Compiled by the Author 5.3 Estimation Techniques Estimating the relationship between the variables in the two equations above, this study employed the cointegration and error correction modeling technique. To do this, three fundamental tests are required: test for stationarity of the data, conduct the cointegration test and finally, the error correction estimate. Unit Root Test The unit root test procedure employed for this study is the Augmented Dickey-Fuller (ADF) test developed by Dickey and Fuller (1979, 1981). The ADF test requires rejecting a null hypothesis of unit root, that is, the series are non-stationary in favour of the alternative hypotheses of stationarity (Omoke, 2010). The tests were conducted without a deterministic trend for each of the series. The general form of the ADF test is stated as: ??y?_t = ?_0 + ?_1 y_(t-1) + ?_(i=1)^n????y_i ? + ?_t 7 Where: y is a time series, t is a linear time trend, ? is the difference operator, ?_0 is a constant, n is the optimum number of lags in the dependent variable and ?_t is the error term at time t. Cointegration Test This involves testing for long-run relationship among variables that are integrated of the same order, that is I(1). A lack of cointegration implies that the variables in the model have no long-run relationship and can wander away arbitrarily from each other. Thus, the Johansen�s approach takes its starting point from estimated a vector autoregressive (VAR) of order P. this is expressed as: y_t = u + ?_1 y_(t-1) + ----+ ?_p y_(t-1) + ?_t 8 Where: y_t is an nx1 vector of variables that are integrated of order commonly denoted as I(1) and t is an nx1 vector of innovations. This VAR model can be written as: ??y?_t = u + ?_(yt-1) + ?_(i-1)^(p-1)??_i ??y?_(t-1) + ?_t 9 Error Correction Model This is done when there is evidence of a long run relationship among the variables in the model. It requires the estimation of Ordinary Least Square (OLS) model with an error correction term to capture the dynamic relationship among the variables. The purpose of the ECM is to indicate the speed of adjustment from the short run disequilibrium to the long-run equilibrium. ??y?_t = ?_0 + ?_(t-1)^(n-1)??_1t ??y?_(t-1)+ ??ECM?_(t-1) + ?_t 10 Where: ? is the difference operator and ? is the error correction coefficient. 6. ANALYSIS AND RESULTS Unit Root Test of Stationarity Table 3: Augmented Dickey-Fuller (ADF) Unit Roots Results Variables At Level Prob. At First Difference Prob. Order of Integration EXR -1.813620 0.9996 -4.254008 0.0019 I(1) LCNFA -1.324006 0.6078 -5.386228 0.0001 I(1) LM2 -0.668523 �0.8421 -3.304695 0.0218 I(1) LR -2.424698 �0.1420 -5.398049 0.0001 I(1) LRES -0.305688 �0.9147 -5.415829 0.0001 I(1) LDCP -1.806618 �0.3718 -4.732552 0.0005 I(1) Critical Value at 5% -2.941145 -2.943427 Source: Computed by the Author The unit root results presented in Table 3 show that the variables are stationary after first difference. This implies the test statistic at first difference is greater than the critical value at 5% level of significance, thus, the variables are integrated of order I(1). This is also evidence from the probability values obtained after differencing the variables. These values are all less than 0.05%. Consequently, Johansen Cointegration test will be appropriate to check for long-run relationship among the variables. This is because this test requires that all the variables must be stationary at order I(1). Cointegration Tests Since all the variables are integrated of order I(1), this study went further to test for the long-run relationship among the variables. The result obtained is presented in Table 4 below. Table 4: Johansen Cointegration Test Result for Exchange Rate and Currency Intervention Model H0 Eigen-value Trace Statistics 5% critical value Max-eigen Statistics 5% Critical Value r=0 �0.620341 �71.02538 �69.81889* �35.83383 �33.87687* r?1 �0.368876 �35.19155 �47.85613 �17.02935 �27.58434 r?2 �0.242036 �18.16220 �29.79707 �10.25340 �21.13162 r?3 �0.148525 �7.908807 �15.49471 �5.949035 �14.26460 r?4 �0.051589 �1.959772 �3.841466 �1.959772 �3.841466 r indicates the number of cointegrating vector. * indicates 1 cointegrating eqn at the 5% level Source: Computed by the Author The cointegration test for exchange rate and currency intervention model revealed that there is one cointegration equation using the trace statistics and the Maximum-Eigen statistics at 5% level of significance. Thus, it was concluded that long-run relationships exist among the variables in the exchange rate and currency intervention model. Table 5: Johansen Cointegration Test Result for Money Supply and Currency Intervention Model H0 Eigen-value Trace Statistics 5% critical value Max-Eigen Statistics 5% Critical Value r=0 �0.526189 �51.64513 �47.85613* �27.63700 �27.58434* r?1 �0.297073 �24.00813 �29.79707 �13.04259 �21.13162 r?2 �0.208977 �10.96554 �15.49471 �8.673866 �14.26460 r?3 �0.060058 �2.291670 �3.841466 �2.291670 �3.841466 r indicates the number of cointegrating vector. * indicates 1 cointegrating eqn(s) at the 5% level Source: Computed by the Author Similarly, the cointegration test for money supply and currency intervention model revealed that there is one cointegration equation using the trace statistics and the maximum-eigen statistics at 5% level of significance. Thus, it was concluded that long-run relationships exist among the variables in the money supply and currency intervention model. Error Correction Results After testing for long-run relationship among the model, the study went further to estimate the specific impacts of the independent variables on the dependents variables in the models above. The results obtained are presented in Tables 6 and 7 below. Table 6: ECM: Exchange Rate and Currency Intervention Model Variables Coefficients Standard Error T-value Prob. Value C 6.050999 5.298679 1.141983 0.2622 D(LNFA) -8.142886 7.388155 -1.102154 0.2789 D(LM2) -21.76062 20.13089 -1.080957 0.2881 D(LRES) 16.10466 8.746443 1.841281 0.0752 D(LAGEXR) 0.506728 0.179592 2.821555 0.0083* ECM(-1) -0.246387 0.106765 -2.307746 0.0279* * indicates significance at 5% level Source: Computed by the Author For the exchange rate and currency intervention model, only one period lag of exchange (LAGEXR) rate is significant in explaining changes in the exchange rate (EXR) in the short run. This is because a 1 percent change in the previous year�s exchange rate will result in 50% change in exchange rate in the current period. The result also revealed that net foreign assets (LNFA), money supply (LM2) and foreign reserves (LRES) do not have significant impact on exchange rate (EXR) in the short run. Thus, currency intervention policy in Nigeria does not have significant impact on exchange rate of the naira in the short run. This in line with the findings of Miyajima and Montoro (2012), Chipili (2014) and Akinkunmi (2017. The error correction term showed a very weak speed of adjustment as only 24.6% of the total short-run disequilibrium is corrected in the long run. Table 7: ECM: Money Supply and Currency Intervention Model Variables Coefficients Standard Error T-value Prob. Value C 0.190505 0.020164 9.447581 0.0000* D(LNFA) 0.040424 0.035607 1.135269 0.2644 D(LR) 0.005489 0.006401 0.857567 0.3973 D(LDCP) 0.338765 0.085527 3.960927 0.0004* ECM2(-1) -0.089590 0.034860 -2.569980 0.0149* * indicates significance at 5% level Source: Computed by the Author For the money supply and currency intervention model, only domestic credit to the private sector (LDCP) is significant in influencing the money supply in Nigeria in the short run. This is because 1% change in domestic credit to the private sector will result in 33.9% changes in money supply at 5% level of significance. The result also revealed that net foreign assets (LNFA) and lending interest rate (LR) are not significant in influencing money supply in Nigeria in the short run. Thus, currency intervention in Nigeria is non-sterilized because net foreign assets which is a proxy for currency intervention is not statistically significant. This result is in conformity with the study of Omojolaibi and Gbadebo (2014) and Dayyabu et al. (2016) but defer from the result obtained in the study of Adebiyi (2007). 6. CONCLUSION AND RECOMMENDATION The two models estimated showed that currency intervention does not have significant impact on the exchange rate of the naira and it is non-sterilized in the context of Nigeria. This can be traceable to the corruption inherent in the Nigerian Foreign Exchange Market. Most times, the CBN releases certain amount of money as intervention in most cases to importers of raw materials, machinery among others; however, the businessmen will rather prefer to sell these currencies at the black market where they can make a lot of profit without doing anything. These persons sometimes hold the money for speculative reasons so as to take advantage of increased prices in other markets and also make more money. Thus, this study recommended that the Central Bank of Nigeria (CBN) should establish a monitoring unit that will be saddle with the responsibility of seeing that the money released as an intervention is used for the purpose it is meant for so as to avoid speculative tendencies of businessmen involve in international trade. References Adebiyi, M. A. (2007). An Evaluation of Foreign Exchange Intervention and Monetary Aggregates in Nigeria (1986-2003). Munich Personal RePEc Archive (MPRA), No. 3817, 1-20. Retrieved from http://mpra.ub.uni-muenchen.de/3817/ Adler, G., & Tovar, C. E. (2014). Foreign Exchange Interventions and their Impact on Exchange Rate Levels. Centro de Estudios Monetarios Latinoamericanos (CEMLA), 0(1), 1-48. Akinkunmi, M. A. (2017). Rebound Effects of Exchange Rate and Central Bank Interventions in Selected ECOWAS Countries. International Journal of Economics and Financial Issues, 7(3), 489-500. Bakare, A. S. (2011). An Empirical Study of the Determinants of Money Supply Growth and Its Effects on Inflation in Nigeria. Journal of Research in International Business and Management, 1(5), 124-129. Retrieved from http://www.interesjournals.org/JRIBM Central Bank of Nigeria (2016). Foreign Exchange Rate. Education in Economic Series, no. 4. 1-43. Chipili, M. J. (2014). Central Bank Intervention and Exchange Rate Volatility in Zambia. African Economic Research Consortium (AERC) Research Paper 268, 1-25. Chutasripanich, N., & Yetman, J. (2015). Foreign exchange intervention: strategies and effectiveness. Bank for International Settlements (BIS) Working Paper, no. 499, 1-36. Dayyabu, S., Adnan, A. A. & Sulong, Z. (2016). Effectiveness of Foreign Exchange Market Intervention in Nigeria (1970-2013). International Journal of Economics and Financial Issues, 6(1), 279-287. Retrieved from https://pdfs.semanticscholar.org/db0f/7a1b4a4de271631713784b98120e6e2abc3c.pdf Disyatat, P., & Galati, G. (2005). The Effectiveness of Foreign Exchange Intervention in Emerging Market Countries: Evidence from the Czech koruna. BIS Working Papers, no. 172. Essien, S. N., Stephen, O. U., & Omotosho, B. S. (2017). Exchange Rate Misalignment Under Different Exchange Rate Regimes in Nigeria. CBN Journal of Applied Statistics, 8(1), 1-21. Fatum, R., & Hutchison, M. (2003). Effectiveness of Official Daily Foreign Exchange Market Intervention Operations in Japan. National Bureau of Economic Research (NBER) Working Paper, 9648. Retrieved from Doi:103386/w9648 International Monetary Fund (1998). Nigeria: Selected Issues and Statistical Appendix, IMF Staff Country Report, 98(78). Retrieved from http://www.books.google.com.ng/books?id=KOceohbjEVgC&pg International Monetary Fund (IMF) factsheet (2017). Monetary policy and central banking. Retrieved from http://www.imf.org/external/np/exr/facts/mtransp.htm Maurice, O. (1996). Foundations of International Finance. Boston: Massachusetts Institute of Technology, 597�599. Miyajima, K., & Montoro, C. (2012). Impact of Foreign Exchange Interventions on Exchange Rate Expectations. BIS Working Papers, no. 73. Retrieved from https://www.bis.org/publ/bppdf/bispap73d_rh.pdf Moreno, R. (2005). Foreign Exchange Market Intervention in Emerging Markets: Motives, Techniques, and Implications. Bank for International Settlements (BIS) Paper, No. 4. 1-304. Retrieved from Omojolaibi, J. A., & Gbadebo, A. D. (2014). Foreign Exchange Intervention and Monetary Aggregates: Nigerian Evidence. International Journal of Economics, Commerce and Management, 2(10), 1-21. Omoke, P. C. (2010). Error Correction, Co-integration and Import Demand Function for Nigeria. International Journal of Development and Management Review, 5(1), 20-31. Oyinlola, M. A. (2018). Modeling Volatility Persistence and Asymmetry of Naira-Dollar Exchange Rate. CBN Journal of Applied Statistics, 9(1), 141-165. Pontines, V. (2018). Self-selection and treatment effects: Revisiting the effectiveness of foreign exchange intervention. Journal of Macroeconomics, 57, 299-316. Retrieved from doi:10.1016/j.jmacro.2018.06.007 Ryan, P. (2017). Backing Scotland�s Currency-Foreign Exchange Reserves for an Independent Scotland. The White Paper Project, 1-17. Retrieved from https//commonweal.scot>filesPDF 48282