Access the full text.
Sign up today, get DeepDyve free for 14 days.
The purpose of this research is to investigate the effect of macroeconomic factors on the volatility of Somalia’s unregulated exchange rates. While utilizing the EGARCH (exponential generalized autoregressive conditional heteroskedastic) model, this study found that the unregulated exchange rate volatility of Somalia is influenced by its own shocks and the macroeconomic factors. This study implies that although Somali shilling circulated without regulatory authority for the period of the statelessness, this circulation has been accompanied by volatile exchange rates. This phenomenon makes this study an appealing work that should be pursued further. Hence, this study contributes notably to the process of reforming the exchange rate system and the monetary policy of the post-conflict economy of Somalia. In addition, the results of this study imply that even in times of war and lawlessness the laws of economics do not change completely. Keywords unregulated exchange rates, exchange rate volatility, macroeconomic factors, Somali shilling creates dislocation during the bust and puts upward pressures Introduction on currencies during the boom (Ostry, 2016). The emerging Exchange rate behavior is important for the people of each economies’ exchange rates have been examined completely country as the exchange rate volatility has a direct effect on due to the numerous and frequent currency crises that the prices of basic commodities (Nor, 2015). The fall down occurred in the previous two decades (Nor, 2015). To iden- of the Bretton Woods fixed exchange rate system pushed tify a common policy direction for such disastrous events, bilateral exchange rates to considerably fluctuate over time numerous studies have analyzed exchange rate volatility of (Chit et al., 2010; Flood & Rose, 1999; Frömmel & Menkhoff, the developing countries (Chit et al., 2010; De Gregorio 2003; Nor, 2015). et al., 2000; Devereux & Lane, 2003; Edison & Reinhart, Exchange rate volatility has been increasing due to major 2001; Glick & Hutchison, 2005). Notwithstanding the enor- changes happening within the global economy (Nor, 2015). mous attempts put in examining the volatility of exchange Although the reasons behind the volatility of exchange rates rates, the findings of Meese and Rogoff (1983) are still inte- differ between developed and developing economies, these gral, which suggest that movements in exchange rates are changes are taking place due to the fiscal and monetary poli- primarily unpredictable (Devereux & Lane, 2003). cies assumed by the governments of every country (Devereux In the context of Somalia, the Somali shilling (SOS; the & Lane, 2003; Nor, 2015). national currency) is used as a medium of exchange and unit Despite the fact that the issue of exchange rate is given exceptional consideration worldwide owing to its negative SIMAD University, Mogadishu, Somalia consequences on the economy, it also continues to be a hot Universiti Sains Malaysia, Malaysia matter in the emerging economies (Chit et al., 2010; Nor, University of Basrah, Basrah, Iraq 2015; Prasad et al., 2003). In the context of emerging market Corresponding Author: economies, countries are facing continuing challenges in Mohamed Ibrahim Nor, Faculty of Management Sciences, SIMAD handling boom–bust capital flow cycles as these capital University, Waddada Warshadaha, Mogadishu, Benadir, Somalia. flows have increasingly become volatile. Such situation Emails: email@example.com Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open of account in small transactions and mainly used by small- analysis made by Luther and his coauthor was based on the scale traders and rural population. It is notable that SOS circulation of Somalia’s unbacked fiat money and how it is in remains the only medium of exchange and unit of account line with the well-known theoretical models of money such for the entire livestock and agriculture markets and this is as the random matching models of Kiyotaki and Wright one of the factors behind the resilience of SOS even after the (1989, 1991, 1993). Therefore, their study contributes very collapse of the central government. On the other side, the little towards understanding the volatility of Somalia’s divisibility problem of USD was also another factor that unregulated exchange rates. encouraged the shilling to remain in the economy because As the monetary authority of Somalia is yet to completely the dollar cannot be used for small transactions (Abdurahman, supervise the exchange rate of SOS, researchers have brought 2005). Whatever reason and by any means, the SOS did not a number of relevant questions. These questions include the disappear due to the lack of sovereign support and it contin- following: (a) Is the unregulated exchange rate volatile? (b) ued circulating in Somali markets following the collapse of What are the macroeconomic factors affecting Somali the government. Although Luther and White (2011b) argue exchange rate volatility? Finding a satisfying response for that SOS circulated at a positive value for the past 20 years, these and other related questions provides imperative infer- there are very limited studies that empirically examine the ence to policymakers and practitioners alike. volatility of the Somali exchange rates. From the available publications, little systematic work In 1980s, the formal financial system of the country failed has been undertaken to examine Somali unregulated to provide adequate financial services to the people, so exchange rate volatility. The purpose of this study is twofold. underground financial services started, which pushed the First, it investigates Somalia’s unregulated exchange rate whole economy into some form of informal system (Nor, volatility. Second, this study examines the effect of macro- 2012; Nor & Masron, 2017; Nurhussein, 2008). Due to the economic factors on the volatility of Somalia’s unregulated collapse of the military regime in 1991 and the breakdown of exchange rates. The remainder of this article is structured as the formal financial system of the country, Somali economy follows. In Section “Literature Review,” the literature review shifted to a complete reliance on informal financial system is provided. In Section “Data and Methodology,” data and operating under informal economic activities (Nor, 2012; the empirical methodology of the study are presented. Nor & Masron, 2017). In terms of monetary system, this Section “Results” provides empirical results of the study. period had suffered from lack of monetary authority because Section “Discussion and Implications” presents the discus- the country’s monetary policy was totally collapsed except sion and policy implications of the study. the reissuance of the 1,000 denominated notes. Somalia’s conventional banknotes continued to circulate in the absence Literature Review of sovereign support and the public receivability of the notes as a legal tender has not been challenged for a long period Volatility of exchange rates have been thoroughly studied (Luther, 2012; Nor & Masron, 2014). using different methodologies. Since the seminal work of In his study about Somalia’s monetary policy and exchange Mussa (1986), traditional wisdom suggests that volatility of rates, Abdurahman (2005) concluded that the exchange rate exchange rates is greater in a flexible exchange rate regime of SOS is affected by a few key items including money sup- than a fixed one (Kocenda & Valachy, 2006). As it is not ply, livestock trade, remittance, and Khat. Nevertheless, directly observable, exchange rate volatility can be identified Abdurahman (2005) did not examine these determinants sys- by employing certain tools and methods (Cheonga et al., tematically and his study relied on descriptive analysis solely. 2005). According to Chit et al. (2010), there is no universal Similarly, Shortland (2011) found that camel exports, price of consensus on the best proxy to represent volatility as differ- rice, and random piracy payments are some of the determi- ent authors prefer different proxies. Some researchers use nants of Somalia’s bilateral exchange rates (SOS/USD). As only a single proxy, whereas others use multiple proxies her focus was on piracy, the study of Shortland is suffering (Aftab et al., 2017; Clark et al., 2004; Dell’Ariccia, 1998; from several limitations. First, she did not examine factors Kumar & Dhawan, 1991). explaining the volatility systematically; thus, her study did As the volatility in exchange rates is characterized as the not provide information about the factors contributing to the clustering of large shocks’ conditional variance, researchers volatility of exchange rates. Second, due to a sample size mainly utilize ARCH (autoregressive conditional heteroske- problem, her study can contribute little towards understand- dastic) and GARCH (generalized autoregressive conditional ing of Somali exchange rates. Although there are a number of heteroskedastic) models to measure the volatility of the goods traded (imported or exported), she only used camel exchange rates (Avdis & Wachter, 2017; Bollerslev, 1990; (proxy of exports) and rice (proxy of imports). Third, the Cheonga et al., 2005; Diebold & Nerlove, 1989). Similarly, focus of her study is after 2000, but this period may not show there are enormous studies on the possibility of forecasting the real picture of the unregulated period. volatility of exchange rates. The ability of forecasting Elsewhere, Luther and White (2011a) argued that SOS is exchange rate movements is counted as a golden opportunity positively valued after the state collapse. However, the for large multinational firms that conduct considerable Nor et al. 3 currency transfers. According to Huang et al. (2004), having quickly to anywhere high profit is available. As the trading the ability to know the future exchange rate movement can activities of foreign currency exchange markets are based on produce a substantial improvement in the firms’ overall currencies, which are very liquid, currency prices are profitability. expected to move quickly in response to surprises (Sensoy, In the literature, researchers found several fundamental 2015; Wei et al., 2018; Yang & Hamori, 2016; Yen-Hsien and technical factors causing exchange rate volatility. et al., 2017). Exchange rates are affected by many economic, political, While examining bilateral trade between the U.S. and and psychological factors that are highly correlated and other G7 economies, Shirvani and Wilbratte (1997) found interactive in a very complex way (Alagidede & Ibrahim, that trade balance significantly responds to exchange rates in 2017; Huang et al., 2004; Yu et al., 2010). Likewise, it has the long run but not in the short run. While using the bounds been observed that exchange rate volatility is generally testing approach, Narayan (2006) found that China’s trade caused by governments’ fiscal and monetary intervention, balance and its real exchange rate are cointegrated. In their fundamental factors of the economy, financial markets, and empirical examination of relationship between export and financial development (Giannellis & Papadopoulos, 2011; exchange rate, Zameer and Siddiqi (2010) concluded that a Grossmann et al., 2014; Li et al., 2016; Simpson & Grossmann, 1% change in exports will lead to a 2.0043% change in 2014). While examining the exchange rate volatility of exchange rate volatility. In their paper, Byrne et al. (2008) European Union countries, Giannellis and Papadopoulos investigated the impact of exchange rate volatility on the vol- (2011) found that monetary side represented by interest ume of bilateral U.S. trade sectoral data and found that rates, domestic stock markets, and industrial production are exchange rate volatility has a robust and significant negative some of the determinants of the volatility of exchange rate effect across sectors. in these countries. While examining the link between mac- roeconomic factors and exchange rate volatility of ASEAN Data and Methodology (Association of Southeast Asian Nations) economies, Chong and Tan (2007) found that macroeconomic factors Data are the forces behind exchange rate volatility via the prob- This study investigates the volatility of Somalia’s unregu- able rigidities of the exchange rates of these countries, lated exchange rates using a monthly exchange rate of SOS coming from the managed float exchange system adopted against USD. Furthermore, the study examines whether mac- by these countries. roeconomic factors have a significant effect on the unregu- Exchange rate is considerably affected by speculation and lated exchange rate volatility of Somalia. Domestic Price these will in turn influence all markets that are dependent on (DP), Imports (M), Money Supply (MS), and Hot Money the exchange rate market. Seasonal movements, capital (HM) are used as explanatory variables in this study. For flight, and political uncertainty are reported to be anticipated each of the macroeconomic factors, monthly data were shocks that affect exchange rates. However, there is heavy obtained for a period of 216 months from January 1995 to speculation in FX (foreign exchange) markets by quickly December 2012. Various sources of data were used for col- purchasing or selling a huge amount of certain currencies, lecting data including International Monetary Fund (IMF) which bring about wide fluctuations in exchange rates. Direction of Trade Statistics, Food Security and Nutrition Speculation is one of the various factors that affect vola- Analysis Unit—Somalia (FSNAU), Food and Agriculture tility of asset prices generally. Some observers argue that a Organization (FAO), and DataStream as reported in Table 1. high trading volume reflects high speculative activities and this induces the high price volatility. It has been observed that more than 90% of FX market participants in Singapore, Model Specification Japan, and Hong Kong agree that speculation increases vola- The focus of this study is to examine the effect of the macro- tility (Carlson & Osler, 2000; Yang & Hamori, 2016). economic factors on Somali unregulated exchange rate vola- Nevertheless, there are some researchers who claim that tility. There are no exogenous variables in the mean equation rational speculation must reduce exchange rate volatility and as presented below as the focus of this study is to examine the this idea stems from the arguments of Freidman (1953), variance equation (volatility). Furthermore, specifications of whose position was that only rational speculators will sur- the GARCH model only are presented in the modeling. vive in the market (Carlson & Osler, 2000). The findings of Carlson and Osler (2000) illustrate that microstructural fac- Mean equation. tors including the degree of speculative activity are part of the fundamental indicators of exchange rate dynamics. SOSS =+ αβ OS + ε , (1) tt tt−1 t According to Dědek and Gregor (1994), the volume of trade in foreign currencies is very huge and a substantial part of it where SOS is the exchange rate of SOS to USD and α , β , is in the form of so-called hot money as these funds do not t t t and ε are the parameters of the model. stay in the same place for a long period and the flow very t 4 SAGE Open Table 1. Source of Data. No. Variable Variable code Source 1 Exchange Rate SOS FSNAU, FAO 2 Imports M IMF Direction of Trade Statistics 3 Money Supply MS DataStream 4 Domestic Price DP FSNAU, FAO 5 Hot Money HM DataStream Note. FSNAU = Food Security and Nutrition Analysis Unit—Somalia; FAO = Food and Agriculture Organization; IMF = International Monetary Fund. Table 2. Stationary Tests. Variables in level Data in the level Data @ first difference ADF PP ADF PP Exchange Rate −1.92 −1.54 −11.15* −11.05* Imports −3.92 −6.25 −23.83* −55.99* Money Supply −0.69 −0.67 −15.01* −15.00* Domestic Price −3.69* −3.55* −17.17* −17.19* Hot Money −0.20 −13.23 −20.41* −106.34* Note. ADF = augmented Dickey–Fuller; PP = Phillips–Perron. *The null hypothesis can be rejected at 5%. supply, HM is the value of hot money, CP is the value of consumer prices, and ε is the error term. Results Unit Root Tests Two common unit root tests, namely, augmented Dickey– Fuller (ADF) and Phillips–Perron (PP), were employed to check the stationarity of the data. All variables, as reported in Table 2, are not stationary at level but are stationary when they differenced once and thus follow unit root process. Test of Structural Break Figure 1. GARCH graph. While examining possible structural break, this study uti- Note. GARCH = generalized autoregressive conditional heteroskedastic. lized the conditional variance produced by the GARCH model. The GARCH graph, as shown in Figure 1, points out the existence of a potential structural break in 2001; how- Variance equation. ever, the Chow test shows the absence of structural break in 2 2 2 2001 as shown in Table 3. To further analyze the existence of σβ =+ ββ σ ++ e β DP tt 01 −− 1 21 t 3 (2) a structural break in the data, a Structural Break (SB) vari- ++ ββ MS M ++ βε HM . 45 6 t able is included in the model as a dummy variable. This is the variance equation of a GARCH model where 2 Results of Heteroskedasticity Test is the variance of the residual derived from the mean β β β equation, β is the constant, , , . . ., are the coeffi- To model the volatility of Somalia’s unregulated exchange 1 2 7 cients of the ARCH and GARCH terms and macroeconomic rates and examine whether macroeconomic factors affect 2 2 factors, σ is the prior period’s residual variance, e is unregulated exchange rate volatility of Somalia, this study t−1 t−1 the previous month’s squared residual derived from the mean utilizes various models of the GARCH family. Before mod- equation, M is the value of imports, MS is the value of money eling the volatility while using GARCH models, the study Nor et al. 5 Table 3. Chow Tests. Somali unregulated exchange rate, several GARCH models were tested. This step contributes to the process of identify- Chow breakpoint test: 2001M04 ing a model that is best fitted to the data. Akaike information F statistic 1.518110 Prob. F(1, 213) .2193 criterion (AIC) is used to select the fittest model to the data. After testing all models, the results show that the GARCH(1, Log likelihood ratio 1.526930 Prob. Chi square(1) .2166 1) model fits the data well and provides better statistical Wald Statistic 1.518110 Prob. Chi square(1) .2179 results when macroeconomic factors are considered. The fit- ness of the model has been assured after checking all neces- sary diagnostic tests. examines the existence of the ARCH effect in the data. In As reported in Table 5, the coefficients of the ARCH and statistics, a collection of random variables is heteroskedastic GARCH terms are significant at 1%. Under normal Gaussian if there are subpopulations that have different variability distribution, the model shows that both previous news and from others. In essence, heteroskedasticity is the absence of previous volatility can influence current volatility. This indi- homoskedasticity. The presence of heteroskedasticity is a cates that the volatility of Somali unregulated exchange rates key concern in the regression analysis as the existence of het- is affected by its own shocks (ARCH and GARCH factors). eroskedasticity can invalidate statistical tests of significance Likewise, the study examined whether macroeconomic fac- (Gujarati & Sangeetha, 2007; Wooldridge, 2013). To check tors have an influence on the volatility of Somalia’s unregu- the presence of heteroskedasticity, the ARCH test was lated exchange rates. As shown in Table 5, except for the employed. As reported in Table 4, the results give strong sup- dummy variable (Structural Break), all other variables such port for rejecting the null hypothesis of the series and indi- as money supply (monetary intervention), imports (trade), cate the presence of ARCH effects in the ordinary least hot money (speculation), and domestic prices have an influ- squares (OLS) models. ence on the volatility of Somalia’s unregulated exchange rates. Results of GARCH, EGARCH, and TARCH EGARCH and macroeconomic factors. While using EGARCH, After having carried out the heteroskedasticity test and the study carried out various EGARCH models. As shown in found the existence of ARCH effects, the next task was to Table 5, the study found that EGARCH(1,1) is the optimal model the unregulated exchange rate volatility of Somalia model for the data when macroeconomic factors are taken by utilizing a GARCH model. Methodologically, GARCH into consideration. The results of the variance equation show models estimate the volatility using conditional variance that the GARCH and asymmetric terms are statistically sig- based on previous period’s volatility and previous period’s nificant. This reveals that past information of the exchange information about exchange rates. To improve the perfor- rates can influence current volatility and past volatility can mance of the GARCH model and overcome its limitations, influence current volatility. In addition, the asymmetric term this study employs EGARCH (exponential generalized is negative and significant, which confirms the existence of autoregressive conditional heteroskedastic) and TARCH asymmetric response. This asymmetric response points out (threshold autoregressive conditional heteroskedastic) mod- that volatility seems to rise in response to positive spikes and els. Such combinations are expected to produce accurate fall in response to negative spikes. The study found that and reliable results and enrich the process of finding effec- Somali unregulated exchange rate volatility seems to have an tive policy formulations. asymmetric characteristic that reveals a negative shock in the Residuals of unregulated exchange rates of Somalia are market is likely to cause more volatility than a positive shock illustrated in Figure 2 before reporting the results of the of the same magnitude. GARCH. As can be observed from the figure, there is an extended period of low volatility from January 1995 to 1999. TARCH and macroeconomic factors. After specifying the Moreover, there is a stretched episode of high volatility from EGARCH model with explanatory variables, the next task is 2000 to 2002. Hence, this enlightens that episodes of high to estimate a TARCH model with macroeconomic factors. volatility are followed by episodes of high volatility and epi- As shown in Table 5, coefficients of the variance equation sodes of low volatility are likely to be followed by episodes show that ARCH and GARCH are not significant at 5%. of low volatility. As a result, the trend of the data apparently Moreover, the asymmetric term is negative and insignificant. suggests that the residual is conditionally heteroskedastic Except for the dummy variable, the other coefficients of the and thus should be represented by ARCH and GARCH explanatory variables (Domestic Price, Money Supply, models. Import, and Hot Money) are significant. This illustrates that the TARCH model is not the best fit for Somali unregulated GARCH and macroeconomic factors. To examine whether exchange rate volatility when macroeconomic factors are macroeconomic factors (domestic prices, money supply, incorporated. imports, and hot money) have an effect on the volatility of 6 SAGE Open Table 4. Results of ARCH Test. Statistics Data in the level I(0) Data in the first difference I(1) 2 2 Obs. R * Prob. Chi square(2) Obs. R * Prob. Chi square(2) ARCH test statistics 202.0607*** .0000 4.784882 .0914 Note. ARCH = autoregressive conditional heteroskedastic. ***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level. Figure 2. Residuals of Somalia’s unregulated exchange rates. Note. SOS = Somali shilling. significant influence on Somali unregulated exchange rate Model Selection volatility. This study employs AIC to select the fittest model. To further This study is in line with previous studies as the same ensure that the preferred model is optimal, serial correlation, results have been found by Abdalla (2012) in the context of normal distribution, and ARCH effect tests were conducted. Arab states. Likewise, this study is aligned with the results As reported in Table 6, the EGARCH model outperforms all of Zahangir Alam and Rahman (2012), who discovered that other models. past exchange rate volatility affects current volatility sig- nificantly. While examining the influence of domestic Discussion and Implications price, money supply, imports, and hot money, the study found that unregulated exchange rate volatility of Somalia Discussion is significantly affected by these macroeconomic factors. To examine the unregulated exchange rate volatility of This gives an added value to this study as it remains one of Somalia and investigate whether macroeconomic factors the limited studies conducted systematically in the context have a significant influence on the volatility, this study uti- of Somalia at this point of time. Somalia is getting out of lizes a conditional heteroskedastic model, namely, EGARCH. decades-old instability and chaos and this makes the coun- The study established that the volatility of Somalia’s unregu- try very attractive to different investors locally and interna- lated exchange rates has significantly been influenced by its tionally. Hence, providing such study does not only help own shocks as well as macroeconomic factors. The EGARCH those investors but also give significant policy recommen- model shows that past information, as well as past volatility, dations to policymakers. has a significant influence on Somali unregulated exchange First, this study ascertained that Somali unregulated rate volatility. In addition, the asymmetric term is negative exchange rate volatility is significantly influenced by money and significant indicating the presence of asymmetric supply. The results of this study are supported by the findings response. The results of the model also point out that domes- of Abdurahman (2005), who found that money supply has a tic price, money supply, imports, and hot money have a significant influence on the exchange rate of Somalia in the Nor et al. 7 Table 5. Results of GARCH, EGARCH, and TARCH Models. Model GARCH(1,1) EGARCH(1,1) TARCH(1,1) Variable Coefficient Prob. Coefficient Prob. Coefficient Prob. C 0.000003 .3661 −12.949 .000 0.000003 .337 ARCH(−1) −0.0533 .000 0.0878 .436 −0.0243 .149 Asymmetry(GAMA) — — −0.1384 .035 — — Leverage effect(Threshold) — — — — −0.0171 .368 GARCH(−1) 1.014 .000 −0.646 .000 1.0071 .000 D(LDP) 0.0013 .000 −3.852 .002 0.0009 .025 D(LMS) 0.0045 .000 20.196 .001 0.0029 .063 D(LM) −0.0005 .005 −2.47 .002 −0.0004 .028 D(LHM) 0.0002 .000 0.546 .036 0.0002 .000 Structural Break (SB) 0.000006 .152 0.305 .401 0.000002 .669 Diagnostics ARCH LM test 11.177 (0.514) 9.396 (0.669) 11.936 (0.450) Serial correlation test Q stat (lag 12) = 0.576 Q stat (lag 12) = 0.635 Q stat (lag 12) = 0.659 Normality test 18.951 (0.000) 16.283 (0.000) 20.823 (0.000) Note. GARCH = generalized autoregressive conditional heteroskedastic; EGARCH = exponential generalized autoregressive conditional heteroskedastic; TARCH = threshold autoregressive conditional heteroskedastic; LM = Lagrange multiplier. Table 6. Model Comparison. exchange rate depreciates in the local currency market. This is exactly what has happened in Somalia in the late 1990s Estimations with explanatory and in the beginning of the 21st century when a huge amount Model variables of paper money is created by warlords and money-lords AIC (greedy businessmen). The effect of that financial catastro- phe is well echoed by every single person, who was present GARCH −4.66 in Somalia during that period. The owners of the businesses EGARCH −4.85 refused to accept SOS as it was depreciating at an alarming TARCH −4.66 scale. This created havoc among consumers, in particular, AIC = Akaike information criterion; GARCH = generalized the poor and low-income households, as they become unable autoregressive conditional heteroskedastic; EGARCH = to purchase basic necessities for the survival of themselves exponential generalized autoregressive conditional heteroskedastic; and their loved ones. TARCH = threshold autoregressive conditional heteroskedastic. Second, the study found that imports can significantly influence the unregulated exchange rates of Somalia. last years of military regime and during the statelessness in Although Somali exports increased drastically since 1970s Somalia. The influence of money supply on exchange rates following the oil boom in Gulf countries, Somali is still has been phenomenon in Somalia since 1996 where General dependent on imports for necessities such as rice, sugar, Mohamed Farah Aidid issued the first Somali banknotes wheat flour, and oil. Somali exports to Gulf States are sea- since the fall down of the military government in 1991. The sonal and very marginal compared with its imports. Thus, issue of printing Somali banknotes has reached its peak in imports play a crucial role in Somalia’s unregulated FX mar- 2001 and 2002 in which SOS lost its value against USD. The ket because traders either send or ship money abroad in the supply of money by the state and federal governments con- form of USD to purchase foreign goods. This is very true in tinued until the value of the money become similar to its cost some sectors of Somali economy such as livestock and agri- (no seigniorage of money). Prior to General Aidid, President cultural markets as the basic medium of exchange in these Ali Mahdi imported new Somali notes. At that point, there markets still remains SOS. For instance, cattle traders use was no interest to print more money as it was not profitable, SOS to buy cattle from the local market, but when they sell and thus the supply of Somali banknotes to the FX market their cattle to the Saudi Arabia market, they use USD as a stopped and the FX market felt some sense of relief. Likewise, medium of exchange. Hence, they should convert their USD it has been learned from the experience of SOS in 1990s that into SOS to buy cattle again from the local market. And that cash injections in the form of forged SOS have an immediate circle continues to repeat. As imports are more than exports, effect on the exchange rates (Abdirahman, 2007). Zhang demand for foreign currency remains more than the supply et al. (2016) argue that when excess money is created, local of foreign currency as long as the country is in a trade deficit. currencies are converted into dollars; consequently, the Somali trade statistics show that Somalia has been in a trade 8 SAGE Open deficit since the state collapse, and thus supply of USD is detected or a sudden capital outflow is discovered. Hence, it is always under its demand assuming that trade is the only clear from the results that speculation is a key variable that channel for the supply and demand of foreign currency. As affects the volatility of Somali unregulated exchange rates and the empirical results confirm, imports can significantly influ- this necessitates the importance of creating an effective mech- ence the volatility of the exchange rates of Somalia. This anism that controls excessive speculation. study is in line with the findings of previous studies such as Abdurahman (2005) and Shortland (2012), which argue that Implications Somali exchange rate is influenced by imports such as rice and Qat. To reduce the impact of imports on the volatility of This study found that Somali informal exchange rate vola- Somali unregulated exchange rates, there should be a solid tility is significantly affected by some macroeconomic fun- policy that resolves this issue. damentals. The results of this study suggest the need for Third, this study found that speculation (as measured by reforming the exchange rate and monetary policies of the hot money) can significantly influence the volatility of unreg- country and the immediate need for creating a national cur- ulated exchange rates in Somalia. To capture the speculative rency that can support Somali postwar economic recovery. trading, hot money is used, which considers short-term capital This study provides some noble contributions to the pro- flow. In the context of Somalia, the speculative trading could cess of understanding the volatility of Somali informal be huge theoretically because of ineffective regulations. In exchange rates. Money supply, imports, and speculation are Somalia, the FX market operates without proper regulation, found to be three important macroeconomic fundamentals supervision, and protection; thus, currency traders can manip- that significantly influence the volatility of Somali infor- ulate the currency prices by either undervaluing or overvalu- mal exchange rates. ing. This may create a huge financial crisis in the country as it It is evident, from these findings, that money supply is a pushes unpredictable price hikes. These price hikes will not key factor to the volatility of Somali informal exchange only create price instability in the country but also affect the rates, and thus Somali policymakers should stress on produc- poor and low-income households in a negative manner. As ing effective regulatory on its monetary issues. One step of Somalia was in chaos and civil war, there were various interest starting is to introduce new currency. Technically, the central groups (both national and international), who used to make bank should establish regional offices in each of the coun- news regarding the stability of the country, for example, the try’s main regions and through these offices; the new cur- news of holding a reconciliation conference and the decision rency can be put into operation. The country is changing and of United Nations to send peacekeeping troops, among others. the capacity of the government is also improving; therefore, With the help of this unpredictable news, Somali currency the old currency can be replaced with the help of communi- speculators sometimes excessively speculate the exchange ties and the private sector. Similarly, the private sector should rate between SOS and foreign currencies such as USD. support the government’s effort toward regulating the private Another important point to be mentioned here is that few indi- sector because a poor monetary policy leads to volatile FX viduals control the Somali FX market because they have been market. We strongly argue that a new currency can be intro- in the market for more than two decades and have sufficient duced by the new government and such decision is feasible if capital to control the market. Due to their experience and dom- a proper monetary mechanism is put forward. inance, these individuals are respected by all other currency Apart from the money supply, import is another macro- traders. As Somali currency traders have not been under the economic factor that significantly influences Somalia infor- surveillance of Somali central bank, they could involve huge mal exchange rate volatility. There are several issues that speculation transactions without any trouble. need to be addressed because imports are associated with Speculation is sometimes associated with currency crisis capital outflow, which is in the form of foreign currency. In and it can lead to a currency collapse. A currency collapse is a the context of Somali, most of the necessities are imported situation wherein the value of a national currency falls com- and the country is spending a huge amount of money on pletely in a very short period of time. Currency collapse can these imports. The current total dependence on imports contribute a wider economic crisis with long-term conse- should be reduced. quences. The South East Asian Financial Crisis in the 1990s is As Somali local currency is not accepted in the exporting a good example. Although there might be a wide variety of country, Somali traders must either send the money via things that can bring about a currency collapse, speculative financial institutions or export it physically. But, in either attack is considered one of the key causes. When a speculative way, the money should be in the form of USD. This implies attack takes place, people perceive that the value of the cur- that imports can contribute drastically to the fluctuation of rency goes down, so they choose to sell their currency to avoid the local currency because traders must convert their funds any potential loss. As the people start selling the currency, the into USD before they send or export it physically. The empir- value begins to decline and this creates more panic among the ical evidence of the study also reveals that imports play an people causing the value of the currency to drop further and important role in Somali informal exchange rate volatility. further. A national currency is regulated in order for the local To lessen the effect of imports on the exchange rate market, currency to be protected in case excessive speculative attack is the government with the help of the private sector should Nor et al. 9 come up with a strategy that reduces the effect of imports on 4. The central bank should facilitate the supply and the informal exchange rate volatility. There are several pol- demand for foreign currency. icy suggestions that can be used by the government with the 5. Remittance companies should use local currency to help of the private sector. transfer remittances. For example, if US$100 is sent The first policy is to reform the economy of the country to Mr. Ali in Mogadishu and the spot exchange rate is wherein a strategic road map is established and domestic 10,000 per dollar; he will be given 1,000,000 SOS. businesses are supported by providing a conducive business 6. All commercial banks should use local currency in environment. To properly implement this strategy, the gov- their finances. ernment should develop a periodical National Economic 7. Opening a foreign currency account should be Development Plan (NEDP) that ensures economic strategies limited. are implemented and an appropriate business environment is 8. All salaries and wages should be quoted and paid in established. the form of local currency. The second one is to look for a trading partner whose cur- 9. Government services should be priced in local rency is relatively stable compared with USD. Then, a suffi- currency. cient amount of that currency has to be put into the market 10. Electronic money (such as EVC-plus and E-MAAL) under the surveillance of the central bank. This can reduce the in the form of foreign currency should be limited. effect of imports on Somali informal exchange rate volatility. 11. Electronic money (such as EVC-plus and E-MAAL) The third policy is to discourage imports via two meth- should be in the form of local currency (SOS). ods: One method is to encourage local businesses to produce 12. Electronic money should be soundly regulated. the necessities locally and the other method is to ask foreign partners to come to the country and produce necessities Furthermore, the results of this study imply that, even in locally. Any of these policy suggestions can help Somalia times of war and lawlessness, the laws of economics remain reduce the effect of the imports on the volatility of the infor- the same and as such nobody can escape these indispensable mal exchange rates. laws in all circumstances. This is another appealing contribu- The forth policy that could help reduce the dependence on tion of this study, which would be worth considering in the the imports is to introduce social reform policies that can economic literature. raise the awareness of domestic consumers to change the mind-set of import dependence. Somali media should be Conclusion engaged in the awareness-raising campaign. Overall, the current total dependence on imports should The aim of this study is to examine the volatility of Somali be reduced. Consequently, the government should adapt informal exchange rates systematically. Furthermore, the inward-oriented policies that support import reduction and study investigates whether macroeconomic fundamentals discourage dependence on foreign goods. have a significant effect on the volatility of the informal The study found that Somali informal exchange rate vola- exchange rates in Somalia. After the analysis, the study tility has been affected by hot money. Foreign capital enter- found several important findings. First, this study found that ing the country supposedly seeking short-term profits is Somali exchange rate volatility is significantly affected by its referred to as hot money. Hot money can be a disastrous tool own shocks (previous information on exchange rates as well for speculators to attach the domestic currency, and thus as past volatility). Second, one of the key findings of this Somali federal government should properly regulate the for- study is that macroeconomic fundamentals have a significant eign capital entering the country. Such speculative capital influence on Somali informal exchange rate volatility. inflow affects not only Somali informal FX market but also Macroeconomic fundamentals like money supply, imports, other financial markets. As Somalia is a small and open and short-term capital flows (known as hot money) have a economy in a post-conflict period, it should control its capi- significant influence on the volatility of Somali informal tal inflows to avoid the consequences of speculative capital exchange rates. Third, Somali informal exchange rate vola- inflows observed in other emerging economies. tility can be adequately modeled using the EGARCH model. The following new polices should be formulated to reduce One of the key recommendations of this study is to replace the effect of macroeconomic fundamentals on Somali infor- the current SOS to a new currency with strong security fea- mal exchange rate volatility: tures to get rid of the huge counterfeit notes circulating into economy. In addition, this study recommends inward-look- 1. Introduce new currency with robust security features. ing trade policies to ultimately become inward-oriented 2. The use of foreign currency as a medium of exchange economy, which eventually reduces the effect of the imports should be made illegal and punishable in front of the on the informal exchange rate volatility. Finally, there should law. be a robust capital control policy that can reduce the effect of 3. Exportation or importation of foreign currencies hot money on the FX market in particular and the economy should be limited. in general. 10 SAGE Open Acknowledgments Chit, M. M., Rizov, M., & Willenbockel, D. (2010). Exchange rate volatility and exports: New empirical evidence from the The authors wish to thank the Center for Research and Development emerging East Asian economies. The World Economy, 33(2), of SIMAD University for funding this research project. 239–263. Chong, L. L., & Tan, H. B. (2007). Macroeconomic factors of exchange Declaration of Conflicting Interests rate volatility: Evidence from four neighbouring ASEAN econ- The author(s) declared no potential conflicts of interest with respect omies. Studies in Economics and Finance, 24(4), 266–285. to the research, authorship, and/or publication of this article. https://doi.org/https://doi.org/10.1108/10867370710831828 Clark, P. B., Tamirisa, N., Wei, S.-J., Sadikov, A., & Zeng, L. (2004). A new look at exchange rate volatility and trade flows Funding (Vol. 235). International Monetary Fund. The author(s) received no financial support for the research, author- Dědek, O., & Gregor, M. (1994). Hot money, speculation, and ship, and/or publication of this article. exchange-rate policy. Russian and East European Finance and Trade, 30(6), 50–70. De Gregorio, J., Edwards, S., & Valdes, R. O. (2000). Controls ORCID iD on capital inflows: Do they work? Journal of Development Mohamed Ibrahim Nor https://orcid.org/0000-0002-3695-9657 Economics, 63(1), 59–83. Dell’Ariccia, G. (1998). Exchange rate fluctuations and trade Notes flows—Evidence from the European Union. International Monetary Fund. 1. A flowering plant found in East Africa and Arabian Peninsula Devereux, M. B., & Lane, P. R. (2003). Understanding bilateral and used as a stimulant. exchange rate volatility. Journal of International Economics, 2. Somali military leader often described as warlord. General 60(1), 109–132. Aidid afterward affirmed himself president of Somalia in June Diebold, F. X., & Nerlove, M. (1989). The dynamics of exchange 1995. Although his announcement received no acknowledg- rate volatility: A multivariate latent factor ARCH model. ment, he was acting as the state president and started doing Journal of Applied Econometrics, 4(1), 1–21. government responsibilities such as issuing Somali banknotes. Edison, H., & Reinhart, C. M. (2001). Stopping hot money. Journal of Development Economics, 66(2), 533–553. References Flood, R. P., & Rose, A. K. (1999). Understanding exchange rate Abdalla, S. Z. S. (2012). Modelling exchange rate volatility volatility without the contrivance of macroeconomics. The using GARCH models: Empirical evidence from Arab coun- Economic Journal, 109(459), 660–672. tries. International Journal of Economics and Finance, 4(3), Friedman, M. (1953). The case for flexible exchange rates. Essays 216–229. in Positive Economics, 157, 203. Abdirahman, M. D. (2007). Exchange rate policy: The Somalia expe- Frömmel, M., & Menkhoff, L. (2003). Increasing exchange rate rience(1960-91). Somalia Watch. http://www.somaliawatch.org/ volatility during the recent float. Applied Financial Economics, archivejuly/000812602.htm 13(12), 877–883. Abdurahman, M. D. (2005). Monetary and exchange rate policies Giannellis, N., & Papadopoulos, A. P. (2011). What causes 1960-2001: The experience of Somalia. AuthorHouse. exchange rate volatility? Evidence from selected EMU mem- Aftab, M., Syed, K. B. S., & Katper, N. A. (2017). Exchange-rate bers and candidates for EMU membership countries. Journal volatility and Malaysian-Thai bilateral industry trade flows. of International Money and Finance, 30, 39–61. Journal of Economic Studies, 44(1), 99–114. Glick, R., & Hutchison, M. (2005). Capital controls and exchange rate Alagidede, P., & Ibrahim, M. (2017). On the causes and effects of instability in developing economies. Journal of International exchange rate volatility on economic growth: Evidence from Money and Finance, 24(3), 387–412. Ghana. Journal of African Business, 18(2), 169–193. Grossmann, A., Love, I., & Orlov, A. G. (2014). The dynamics of Avdis, E., & Wachter, J. A. (2017). Maximum likelihood estima- exchange rate volatility: A panel VAR approach. Journal of tion of the equity premium. Journal of Financial Economics, International Financial Markets, Institutions & Money, 33, 125(3), 589–609. 1–27. Bollerslev, T. (1990). Modelling the coherence in short-run nomi- Gujarati, D. N., & Sangeetha, N. (2007). Basic econometrics. Tata nal exchange rates: A multivariate generalized ARCH model. McGraw-Hill. The Review of Economics and Statistics, 72, 498–505. Huang, W., Lai, K. K., Nakamori, Y., & Wandg, S. (2004). Byrne, J. P., Darby, J., & MacDonald, R. (2008). US trade and Forecasting foreign exchange rates with artificial neural exchange rate volatility: A real sectoral bilateral analysis. networks: A review. International Journal of Information Journal of Macroeconomics, 30(1), 238–259. https://doi Technology & Decision Making, 3(1), 145–165. .org/10.1016/j.jmacro.2006.08.002 Kiyotaki, N., & Wright, R. (1989). On money as a medium of Carlson, J. A., & Osler, C. L. (2000). Rational speculators and exchange exchange. Journal of Political Economy, 97(4), 927–954. rate volatility. European Economic Review, 44, 231–253. Kiyotaki, N., & Wright, R. (1991). A contribution to the pure theory Cheonga, C., Mehari, T., & Williams, L. V. (2005). The effects of money. Journal of Economic Theory, 53(2), 215–235. of exchange rate volatility on price competitiveness and trade Kiyotaki, N., & Wright, R. (1993). A search-theoretic approach volumes in the UK: A disaggregated approach. Journal of to monetary economics. The American Economic Review, Policy Modeling, 27, 961–970. 63–77. Nor et al. 11 Kocenda, E., & Valachy, J. (2006). Exchange rate volatil- Shortland, A. (2011). “Robin Hook”: The developmental effects of ity and regime change: A Visegrad comparison. Journal of Somali piracy. https://ideas.repec.org/p/diw/diweos/diweos54 Comparative Economics, 34, 727–753. .html Kumar, R., & Dhawan, R. (1991). Exchange rate volatility and Shortland, A. (2012). Treasure mapped: Using satellite imagery Pakistan’s exports to the developed world, 1974–85. World to track the developmental effects of Somali piracy. Chatham Development, 19(9), 1225–1240. http://dx.doi.org/10.1016/0305- House. 750X(91)90069-T Simpson, M. W., & Grossmann, A. (2014). An examination of the Li, G., Zhu, J., & Li, J. (2016). Understanding bilateral exchange forward prediction error of US dollar exchange rates and how rate risks. Journal of International Money and Finance, 68, they are related to bid-ask spreads, purchasing power parity 103–129. disequilibria, and forward premium asymmetry. The North Luther, W. J. (2012). Money without a state [Doctor of philosophy American Journal of Economics and Finance, 28, 221–238. economics]. George Mason University. Wei, Y., Yu, Q., Liu, J., & Cao, Y. (2018). Hot money and China’s Luther, W. J., & White, L. H. (2011a). Positively valued fiat stock market volatility: Further evidence using the GARCH– money after the sovereign disappears: The case of Somalia. MIDAS model. Physica A: Statistical Mechanics and Its Department of Economics Paper, George Mason University. Applications, 492, 923–930. Luther, W. J., & White, L. H. (2011b). Positively valued fiat money Wooldridge, J. M. (2013). Introductory econometrics: A modern after the sovereign disappears: The case of Somalia. Social approach. CENAGE Learning. Science Research Network. http://papers.ssrn.com/sol3/papers Yang, L., & Hamori, S. (2016). Hot money and business cycle vol- .cfm?abstract_id=1801563 atility: Evidence from selected ASEAN countries. Emerging Meese, R. A., & Rogoff, K. (1983). Empirical exchange rate mod- Markets Finance & Trade, 52(2), 351–363. els of the seventies: Do they fit out of sample? Journal of Yen-Hsien, L., Ya-Ling, H., & Tsu-Hui, C. (2017). Does hot money International Economics, 14(1–2), 3–24. impact stock and exchange rate markets on china? Asian Mussa, M. (1986, September). Nominal exchange rate regimes Academy of Management Journal of Accounting & Finance, and the behavior of real exchange rates: Evidence and impli- 13(2), 95–108. cations. In Carnegie-Rochester Conference series on public Yu, L., Wang, S., & Lai, K. K. (2010). Foreign-exchange-rate policy (Vol. 25, pp. 117–214). North-Holland. forecasting with artificial neural networks (Vol. 107). Springer Narayan, P. K. (2006). Examining the relationship between trade Science & Business Media. balance and exchange rate: The case of China’s trade with the Zahangir Alam, M., & Rahman, A. (2012). Modelling volatility of USA. Applied Economics Letters, 13(8), 507–510. the BDT/USD exchange rate with GARCH model. International Nor, M. I. (2012). The nature and operations of the informal finan- Journal of Economics & Finance, 4(11), 193–204. cial institutions in Somalia: An empirical survey. Academic Zameer, S., & Siddiqi, M. W. (2010). The impact of exports, FDI Research International, 2(2), 661–674. and external debt on exchange rate volatility in Pakistan. Nor, M. I. (2015). The volatility of Somalia’s unregulated exchange International Journal of Contemporary Research in Business, rates. Universiti Sains Malaysia. 2(7), 337–354. Nor, M. I., & Masron, T. A. (2014). Modeling exchange rate vola- Zhang, G., Marsh, I., & MacDonald, R. (2016). A hybrid approach tility of post-conflict economies: The role of regulation [Paper to exchange rates: How do macro news and order flow affect presentation]. The Proceeding—Kuala Lumpur International exchange rate volatility? Studies in Economics and Finance, Business, Economics and Law Conference, Kuala Lumpur, 33(1), 50–68. Malaysia. Nor, M. I., & Masron, T. A. (2017). Does the observed value of Author Biographies Somali shilling deviate from its predicted value? Journal of Mohamed Ibrahim Nor is currently working at SIMAD University Policy Modeling, 39(3), 532–546. https://doi.org/10.1016/j as the deputy rector for academics. Mohamed received his PhD .jpolmod.2017.03.007 from Universiti Sains Malaysia in Malaysia. He is a lecturer at the Nurhussein, S. (2008). Global networks, fragmentation, and the faculty of management sciences and faculty of economics, SIMAD rise of telecommunications in stateless Somalia [Master of UNIVERSITY. His area of research interests includes monetary arts]. University of Oregon. economics, international finance, financial economics, and housing Ostry, J. D. (2016). Managing the exchange rate in the face of economics. He has published his works in several outlets including volatile capital flows. In J. E. Stiglitz & M. Guzman (Eds.), Journal of Policy Modeling, International Journal of Social Contemporary issues in macroeconomics. International Economics and International Journal of Energy Economics and Economic Association Series (pp. 129–147). Springer. Policy. Prasad, E., Rogoff, K., Wei, S.-J., & Kose, M. A. (2003). Effects of financial globalization on developing countries: Some empiri- Tajul Ariffin Masron, PhD is an associate professor at the School cal evidence (Vol. 17). International Monetary Fund. of Management, Universiti Sains Malaysia (USM). He has been Sensoy, A. (2015). An alternative way to track the hot money in with USM since March 2007. He has taught courses at the under- turbulent times. Physica A: Statistical Mechanics and Its graduate and post graduate level. Amongst courses he has taught Applications, 419, 215–220. are: Mathematic for Business, Macroeconomics, Microeconomics, Shirvani, H., & Wilbratte, B. (1997). The relationship between the Managerial Economics and International Trade. He supervises a real exchange rate and the trade balance: An empirical reas- number of MBA and PhD students in the field of International sessment. International Economic Journal, 11(1), 39–50. Trade and Finance. He has published research articles in both local 12 SAGE Open and international refereed journals. His Area of research specializa- He has published several papers (Scopus and ISI) in international tion is in International Economics. journals and proceedings (27 papers), and also has participated and presented 26 papers in various international conferences in Tariq Tawfeeq Yousif Alabdullah holds a PhD in accounting in USA, UK, Turkey, Germany, France, Spain, Italy, Austria, Corporate Governance in 2015 from Universiti Sains Malaysia Malaysia, and Jordan. He is an editorial board member and regu- (USM). He is currently a lecturer in accounting in the Accounting lar reviewer in the editorial board for 56 International conferences Department in the College of Administration and Economics at and international Journals. He is also a corporate governance the University of Basrah, Iraq. His research interests are mainly in expert for Virtus InterPress and Virtus Global Center of Corporate the areas of Accounting, Management, and corporate governance. Governance.
SAGE Open – SAGE
Published: Jan 12, 2020
Keywords: unregulated exchange rates; exchange rate volatility; macroeconomic factors; Somali shilling
Access the full text.
Sign up today, get DeepDyve free for 14 days.