Exchange Rate Volatility

Chapter 1: Introduction

The relationship between exchange rate volatility and trade flows has been extensively reviewed in literature. Exchange rate volatility refers to the extent to which prices of currencies tend to fluctuate over time. Theoretical literature has provided diverging views on the effect on exchange rate volatility on trade flows. Some authors argue that an increase in exchange rate volatility implies that risk averse firms are faced with uncertainty with respect to their earnings and hence would generally respond by redirecting their activity to local markets. On the other hand, other researchers pointed out that when the assumption of risk aversion is lifted, it can be argued that market participants are more likely to take advantage of the fluctuations in the exchange rate so as to increase their profits which will cause an increase in international trade. The various empirical studies carried out on this topic have not been able to establish a clear link between exchange rate volatility and trade. Therefore from both theoretical and empirical point of view, the relationship between exchange rate and volatility is ambiguous. Mauritius is often cited as an example of a country which has undergone successful trade liberalization and export-led growth. It is also said that trade policies has shaped the country’s path of industrial development, contributing to over two decades of steady growth and propelling the country in the ranks of the “newly industrialized economies”. However since the 1960s, the Mauritius has experienced much changes and reforms in its trade policy. Early trade policies adopted by Mauritius involved an import substitution strategy while at the same time providing incentives for export promotion. However as from the 1980s, Mauritius moved towards a more outward-oriented strategy and embarked on trade liberalisation. Imports restrictions and tariffs were reduced while economic stability was maintained. By the mid-1990s, Mauritius had one of the most liberal economic regimes in Africa. Incentives for export promotion like tax incentives, preferential rates of borrowing and so on were maintained. One of the key factors of exports competitiveness is the level of exchange rate in Mauritius which had to be kept low. In addition the exchange rate regime itself in Mauritius has been deregulated over the years in a set of financial liberalisation measures. The exchange rate regime in Mauritius has also evolved from a fixed exchange rate system to a manage float one. In the 1970s, Mauritius adopted a pegged exchange rate system where the rupee was first pegged to the sterling. The rupee started floating vis-à-vis other foreign currencies in June 1972 while still being pegged to the sterling. However as from 1976, the Mauritian rupee was delinked from the sterling and was pegged to the SDR. The rupee-SDR peg lasted for seven years and as from 1983 Mauritius pegged its currency to a trade-weighted basket of currencies. This is because the appreciation of the dollar US which had the highest weight in the SDR basket caused the rupee to appreciate considerably and hence causing inflation. Hence the Mauritian rupee had to be delinked to the SDR. In the 1990s, Mauritius embarked on a set of financial liberalisation reforms and in 1994 exchange rate controls were removed and Mauritius adopted a manage float exchange rate regime. The evolution of the exchange rate system from a fixed to a manage float one implies that the exchange rate in Mauritius is subject to wider fluctuations. This begs the question whether the fluctuations in the rupee has any significant impact on the volume of trade in Mauritius and which of the theories advanced by researchers is applicable for Mauritius. Bilateral trade between Mauritius and USA is considered to assess this question. The rest of the paper is organised as follows: Chapter 2 presents a broad survey of the literature concerning the relationship between trade and exchange rate volatility. Chapter 3 describes the model that will be used and presents the methodology that will be applied. Chapter 4 presents the empirical findings of our study and the interpretation of our results. Finally chapter 5 presents the summary and conclusion of our study and also provides some policy implications and implications.

2.1 Introduction

The 1970s saw the demise of the Bretton Woods system since a fixed exchange rate system no longer appeared feasible given the speculative flows of the currencies. This led to the adoption of a freely-floating exchange rate regime by many countries. Since March 1973, exchange rates have become more volatile and less predictable than they were during the fixed exchange rate period when changes occurred infrequently. There have been considerable investigations on the effect of Exchange rate volatility on the volume of trade. The increase in the risk of international transactions led researchers to investigate the exchange rate volatility-trade flows connection. Investigators argue that variability increases uncertainty and risk which causes firms to produce less than they would produce under certainty. This view was supported by Baron(1970), Clark(1973) and Ethier(1973). Empirical studies which yielded a negative relationship between exchange rate volatility and trade include Akhtar and Hilton(1984), Fountas and Aristotelous(1999), Arize(1997, 1998a and 1998b) and Rose(2000). However other authors have rejected this view, arguing that the exchange rate volatility have very little or at times even positive impact on trade volume. Researchers like Hooper and Kohlhagen (1978), Bahmani et Tavlas(1988), Bahmani et al.(1993), Bailey, Tavlas and Ulan(1987), found evidence of a negative effect of exchange rate uncertainty on trade volume, the effect was insignificant. Klassen(2004) also found no significant relationship between Exchange rate volatility and international trade. Research conducted by McKenzie and Brooks(1997), Franke(1991), Neumann(1995), Viaena and Vries(1992) and Baum et al(2004) on the other hand found a positive relationship between exchange rate volatility and trade. Other researchers like Cushman(1983) on the other hand obtained mixed results. This chapter provides an overview of the vast literature that covers this particular issue of exchange rate volatility and trade. Section 2.2.1 provides an overview traditional exports and imports functions used in most studies and their findings. Section 2.2.2 elaborates on additional factors which have been used in empirical studies. Finally section outlines the research carried out to determine the relationship between exchange rate volatility and trade. Literature defines volatility as the tendency of prices to fluctuate either up or down. Exchange rate volatility is in fact a measure of how exchange rate changes over time. It has been argued that exchange rate volatility has a significant impact of the level of trade. First we will discuss the various factors that have an impact of trade in an economy.

2.2 Determinants of Bilateral Trade Flows

Most of the empirical works used the traditional export and import demand models. While the traditional models were deemed to be significant in explaining trade, these works were often deemed to be unsatisfactory since several key determinants of trade were omitted which led to unreliable results and conclusions. Therefore, the traditional trade function was used in addition to other explanatory variables. Nevertheless, the major contribution of the traditional trade model in explaining exports and imports cannot be ignored.

2.2.1 Traditional Export Demand Function

The traditional export demand function commonly used by many studies was expressed as a function of real income, relative prices and/or exchange rate. This was termed by Goldstein and Khan (1985) as the imperfect substitute model. An aggregate export demand linking real exports with a measure of foreign real income and relative prices is an important element in most conventional trade models. In theory, the higher the foreign income, the higher the demand for export. This is because an increase in foreign income is relative to an increase in the purchasing power of the foreign economy. Likewise an increase in domestic income will increase the demand for imports. Real foreign income were normally proxied using real GDP or real GNP or index of industrial production of the foreign economy. Relative prices were also included in the model. Relative prices are an indicator of a countries competitiveness and are normally proxied by the ratio of foreign prices to domestic prices or the ratio of import prices to import prices. Exports and relative prices is expected to have a positive relationship since an increase in relative prices implies that foreign prices are increasing which means that the competitiveness of exports is increasing. One of the most influential empirical work on export demand was that of Senhadji and Montenegro(1999) who estimated demand elasticities for a large number of developing and industrial countries using OLS and Phillip Hansens’s fully modified ordinary least square techniques. They found that exports react to both the trade partner’s income and to relative prices in a large sample of both developing and industrial countries. Marquez and McNeilly(1988) examined income and price elasticities for exports of non-OPEC developing countries using quarterly data for 1973-84. This study was based on the two-stage square estimation technique. Import prices, real income and lagged endogenous variables were the main explanatory variables. They found a positive and significant income elasticities for exports and a significant relationship between prices and exports. Among other prominent empirical works which find a positive and significant relationship between trade and income are Sachs and Warner(1995), Frankel and Romer(1999) and Edwards(1998). Wu(2004)constructed a foreign trade model for China using error correction model. They found a significant and inelastic relationship between relative price and export demand. Other empirical works included exchange rate as a determinant of export in their model. It is widely known in the international trade literature that a change in real exchange rates will affect trade flows directly with all other things being equal. A change in the real exchange rate rather than a change in the nominal exchange rate will affect exports and imports under the Generalized Marshall-Lerner condition. Also real exchange rate is another important measure of a country’s competitiveness. Real exchange rate is the nominal exchange rate that has been adjusted for inflation differentials. A real depreciation or devaluation of domestic currency will lead to an improvement in trade flows of a country and vice versa. This is because if the price of the currency of a country is low, its exports will be cheaper hence demand for its exports will increase. Imports also will be affected since imports will appear more expensive to local residents. However empirical works have found diverging results when assessing whether exchange rate have any effects on trade. Miles (1979) tested the effects of devaluation by entering the exchange rate directly into the trade flows. The results obtained were not conclusive since the exchange rate coefficient with respect to trade flows was significant in only three out of 14 cases examined. Warner and Kreinin(1983) specified the determinants of trade flows of 19 developing countries using conventional models. They found that the effect of real exchange rate changes on the volume of exports are significant as predicted by the theory. Similarly Himarios(1989) reassessed the impact of devaluation on real magnitude of trade flows and found that real exchange rates had a significant effect on trade flows. Rose (1991) analysed the relationship between the effective real exchange rate and the real trade flows for five major Organization for Economic Cooperation and Development (OECD) countries: the United Kingdom, Canada, Germany, Japan, and the United States. He found no relationship between these two variables, and thus the generalized Marshall-Lerner condition did not hold. Bahmani-Oskooee and Malixi (1992) based their work on Almon lag structure on real exchange rate but found no support for a relationship between trade and real exchange rate. However on employing the Engle-Granger cointegration approach, Bahmani-Oskooee and Alse (1994) assert that the long-run impact of devaluation on the trade balance model is positive. Bahmani-Oskooee concluded that trade flows are more responsive to changes in relative prices and to changes in the exchange rates in the long run than in the short run. Brada et al. (1997), who divided the data set into two sub-samples, reports no long-run relationship between the variables of the trade balance function in the 1970s but they have revealed reverse results for the 1980s Kale (2001) points out that a real depreciation of the domestic currency helps to improve the trade balance with a lag of about one-year and the impacts of devaluations on the trade balance are positive in the long-run. Haque et al.(1990) used a generalised non-linear 3-staged least square estimation for the period 1963-87. They used a conventional model where real imports is expressed as a function of real domestic output, real exchange rate and a lagged import term. All signs were significant. Real imports were found to be real exchange and income inelastic. While the above factors were used as the main determinants of exports, there are also other also factors which are important determinants of trade.

2.2.2 Other factors affecting bilateral trade Inflation rate and trade

Inflation is defined as a rise in the general level of prices of goods and services in an economy over a period of time. High inflation is like to have a negative effect on trade flows because it reduces exports competitiveness and makes imports cheaper. When domestic price rises, foreign goods are relatively cheaper (ceteris paribus) and demand for imports should increase, Inflation adversely affects some sections of the population, distorts relative prices, erodes value of financial assets and creates uncertainty and instability in the economy. This may lead to an overall decrease in output in the economy since investors and producers is faced with uncertainty about future prices and economic outcome. Gylfason(1998) used cross-sectional data covering 160 countries for the period 1985-1994 and found that high inflation tended to be associated with low exports in proportion to GDP. Kotan and Saygili(1999) found that inflation rate significantly and positively affect non-oil exportation in the long-run while in short run inflation did not have any significant impact of non-oil production. Investment and Trade

There are valid theoretical reasons why a high investment ratio should give rise to a strong export growth performance. One theoretical background is provided by Ghosh and Chandrasekhar(2001). They stated that the rate at which international trade grows varies over any period. Also a country’s ability to increase its exports would depend on its production structure and the rate at which this structure is changing. Furthermore, countries normally engage in international trade by XXXodernizesXXXg in the production of certain commodities only. Therefore a country’s ability to increase its exports will therefore depend on its capacity to rapidly transform its production structure in the direction of commodities where world trade would grow faster. The rapidity of this transformation is linked to the investment ratio(ratio of investment to GDP), that is the higher the investment ratio, the higher the rate of transformation of the production-structure and hence the greater the ability of the country to participate in world trade, that is the greater the rate of export growth. Also production capacity, potential productivity, cost effectivesness, production process will all be increased by properly-oriented investment and hence export competitiveness should also increase. Investment is said to enlarge the production base and thus increasing production capacity. It XXXodernizes production processes and thus improving cost effectiveness. It also allows for the production of new and improved products, increasing value added in production. In addition it incorporates international world-class innovations and quality standards. All this leads to an active participation in international trade and favourably affects exports. Patnaik and Chandrasekhar(1996) in their research analysed cross sectional data for 25 developing countries for 20 years and found a positive relationship between investment-ratio and export growth. FDI is said to foster innovation and competitiveness in the local industry. Moreover it contributes to technological innovation and increased production capacity in the domestic economy. Another import element of investment is foreign direct investment(FDI) which has been argued to be a prominent factor in promoting exports. Horst(1972), Lipsey and Weiss(1984), Head and Ries(2001) and Camarero and Tamarit(2004) are among the authors that find a positive relationship between FDI and trade. Capacity Utilisation and Trade

Capacity utilization refers to the extent to which an enterprise or a nation actually uses its installed productive capacity. Thus, it refers to the relationship between actual output that is produced with the installed equipment and the potential output which could be produced if capacity was fully used. From theoretical and empirical point of view, the relationship between capacity utilisation and exports is ambiguous. On one hand, researchers argue that when firms uses excess capacity, this will increase to a general increase in capacity utilisation and will lead to an increase in output. It will be possible for firms to export more. Productivity also may increase since firms are employing more of their excess capacity. Likewise an increase in foreign capacity utilisation is likely to have a negative impact on domestic exports. This is because an increase in foreign capacity utilisation means firms are able to increase their productivity and output. Also Hooper and Kohlagen(1978) who were the first to introduce capacity utilisation in their model to determine the relationship between exchange rate volatility and exports, argued that as domestic capacity utilisation increases, domestically produced goods are delivered with longer lags and hence decreasing quantity demanded of imports. Likewise an increase in foreign capacity should decrease the demand of exports. Correa, Dayoub and Francisco(2007) in their study found that domestic capacity utilisation positively affect export intensity of Ecuador. On the other hand other authors argue that exports growth is possible mainly in the presence of large unemployment of domestic resources. Dunlevy(1979) and Artus(1977) argued that in the long run an increase in capacity utilisation will reduce the quantity of exports and increase the export prices. However Medhora(1990) found that both domestic and foreign capacity utilisation was insignificant in explaining West African imports. Exchange Rate Volatility and trade

Basic uncertainty trade models

The traditional models examine the behaviour of undiversified firms and are based on the assumption that the firm’s profitability is linked directly and unambiguously to the movement in one bilateral exchange rate. The variability of that exchange rate is assumed to measure the risk to the firm in conducting trade. Therefore in the simplest model, higher exchange rate risk is assumed to have a negative impact on trade, since it creates uncertainty with respect to profits of firms’ exports and, hence, lead risk-averse exporters to reduce their supply of exports, an effect that increases with the degree of risk aversion. An example provided by Clark(1973) can be used to illustrate the concept of how exchange rate volatility can affect the level of a firm’s exports. Clark develops a model of a firm operating under competitive conditions. In the simplest version described, it is assumed that the firm produces a homogeneous commodity which is sold entirely in a foreign market. The firm has no market power and its does not import any inputs and the production decision is taken before observing exchange rate volatility, therefore output is constant over the planning horizon. Also the price of the exported good in foreign currency is an exogenous variable. The firm in paid in foreign currency and hedging possibilities such as forwards or futures market is very limited. The firm converts its proceeds from exports at the current exchange rates. Given the above assumptions, variability in the exchange rate will affect the firm’s level of profits since output cannot be altered in response to a favourable or unfavourable move in the profitability of exports due to exchange rate movements and there are also limited hedging techniques. Therefore uncertainty about future exchange rates translates into uncertainty on future export receipts in domestic currency. This uncertainty will be considered by the firm when deciding on the level of exports. The firm maximises the expected value of utility which is assumed to take the following quadratic form: U(p)= a p +b p2 Under conditions of risk aversion (b < 0), the first-order condition requires that marginal revenue exceed marginal cost. The firm must be compensated for the exchange risk it bears and thus the supple curve shifts towards the left and the volume of production and trade is reduced. A risk-averse firm tries to reduce its exposure to risk by reducing sales, hence both expected profits and the variance of profits decline, but expected utility increases. If inputs were imported, the contraction in the supply of exports would be smaller. The variance in profits would not rise in proportion to the increase in the variance of the exchange rate. Only in the extreme case of perfect correlation between revenues and costs in domestic currency terms would greater variability have no effect on the variance of profits. Ethier (1973) also supported this view and shows that, if traders were uncertain as to how the exchange rate affects their firms’ revenue, the volume of trade will be reduced. However the above analysis is based on a number of restrictive assumptions. Other researchers attempted to examine the relationship between exchange rate variability and trade flows by relaxing some of the assumptions like no hedging possibilities while still maintaining the risk aversion theory. Clark (1973) notes that while risk-aversion among traders might depress the volume of a country’s exports, perfect forward markets might reduce this effect. Advanced economies have well developed forward markets where specific transactions can be easily hedged, thus reducing exposure to unforeseen movements in exchange rates. However most developing countries do not have access to such markets for currencies. Baron (1976) finds that forward markets may not be sufficiently developed, and traders may still be unsure of how much foreign exchange they want to cover. In addition, Baron provides another approach to the model developed by Clark by relaxing the assumptions of perfect competition and by emphasising on the role of the currency in which the products are invoiced. He argues that invoicing in a foreign currency will result in a price risk. When an exporting firm invoices its commodity in foreign currency, it is faced with the risk of variations in the foreign exchange which will affect revenue. The quantity demanded will however remain the same since the price will not change over the contract period and hence the firm cannot benefit from fluctuations in the foreign exchange rate. When invoicing in home currency, the exporter will face a quantity risk. This is because the quantity demanded will be uncertain since the price of the commodity to the buyer will be uncertain. The firm will also face uncertainties regarding its cost of production since the assumption that the firm will not import factor inputs is relaxed. In both cases the risk averse firm will try to minimise its risk exposure either by expanding or contracting supply. Baron shows that an increase in risk will cause prices to rise which will result in an increase in supply. The higher price reduces expected profits since demand is elastic at optimal prices, but it increases expected utility. On the other hand, if the firm invoices in domestic currency, its response will depend on the properties of the demand function in the destination market. Baron shows that if the function is linear, prices will decrease resulting in an increased demand. However the price-cost margin decreases which reduces the expectation and variance of profits. Also, under the basic model, changes in exchange rate does not have any effect on real opportunities available to the firm. Firms are held to be risk averse and factor inputs are assumed to be fixed. They are also assumed to make production and export decisions before the exchange rate is known and inventories are ignored. When the assumption of risk aversion is lifted, the negative relationship between exports and exchange rate volatility can even be reversed. De Grauwe(1988) developed a model that shows that the effect of volatility on trade will depend on the degree of risk aversion. He argued that firms with a slight degree of risk aversion will decrease their exports whereas very risk averse firms will increase exports so as to avoid a drastic decrease in their export revenues caused by higher exchange rate volatility. Franke(1991) showed in given a monopolistic setting, risk neutral firms may increase exports if exchange rate volatility increases. The theory that trade may be affected by exchange rate volatility is also based on the assumption that factor inputs cannot be altered so as to adjust optimally to a change in exchange rates. If firms are able to adjust one or more factors of production with respect to a change in exchange rates, variations in exchange rate may provide firm with the possibility of making a profit. This view was analysed by Canzoneri et al.(2004), De Grauwe(1992) and Gros(1987). In addition, Clark et al.(2004) affirm that there are several other factors which can reduce the negative effects of exchange rate volatility and trade. They argued that a multinational firm which engages in a diversity of trade and financial transactions across several countries can benefit from various opportunities to exploit offsetting movements in currencies and other variables. For example if an exporting firm is importing intermediate inputs from a country whose currency is depreciating, this can offset a decrease in export revenues through a decrease in cost of production. Also recent studies has shown that the tendency for exchange rates to adjust to differences in inflation rates and hence if exports are priced in a foreign currency that is depreciating, the loss to the exporter from the declining exchange rate is at least partly offset by higher foreign currency export price(Cushman 1083 and 1986) Finally as put forward by Makin(1978), multinationals have many possibilities of internally managing their exposure to foreign exchange risk, for example by holding a portfolio of assets and liabilities in different currencies. In his analysis of exchange rate volatility, Gros(1987) takes into account adjustment costs. His model consist of a risk neutral and competitive firm which exports its entire output. It is shown that if some factor can be adjusted instantaneously, an increase in exchange rate volatility increases a firm’s investment. The rationale behind this is that if exchange rate for the exporting firm is high, this means output price will be high and thus the firm can increase production by utilising more of the flexible factor so as to obtain a more than proportionate increase in profits. On the contrary if prices are low, production can be reduced to limit losses. An increases in the volatility of prices means that there is the possibility for excessive prices increases. Therefore it is more desirable for firms to have high capital stock and over time the export supple function shifts upwards. In this study, exchange rate variability affects exports through its effect on investment. Another aspect of the relationship between exchange rate variability and trade is the presence of sunk cost. Sunk market-entry costs are faced by risk neutral firms when they enter the market for exports. This would arise particularly where the firm is exporting differentiated goods and require substantial investment by the firm for example to adapt their product to foreign market and to create a marketing and distribution network. Sunk cost tend to make firms less responsive to short run fluctuations in the foreign exchange rate as they would have the tend to continue to operate in the market as long as they can recover their variable costs and to wait for a change in the exchange rate which will allow them to recoup their sunk costs((Baldwin,1988; Krugman, 1989) Finally, other researches like Bacchetta and Van Wincoop (2000) conduct their study within a general equilibrium framework. They use a simple general equilibrium model for two countries where the source of uncertainty are monetary, fiscal, and technology shocks, and they compare the level of trade and welfare for fixed and floating exchange rate arrangements. They reach two main conclusions. First, there is no clear relationship between the level of trade and the type of exchange rate arrangement. Second, the level of trade does not provide a good index of the level of welfare in a country, and hence there is no one-to-one relationship between levels of trade and welfare in comparing exchange rate systems. Theoretical analysis of the relationship between exchange rate volatility and trade flows has yielded indeterminate results and hence this issue has attracted a large number of empirical researches. One of the earliest analysis was carried out by Hooper and Kohlhagen(1978) who assessed the effect of exchange rate volatility on the volume of aggregate and bilateral trade flow for all G7 countries except for Italy using time series data for the period 1965-1975. They utilised the model by Ethier(1973) for traded goods and derived equations expressing export prices and quantities in terms of cost of production reflection both domestic and imported inputs, other domestic prices, domestic income and capacity utilisation. Exchange rate risk was measured using the average absolute difference between the current period spot exchange rate and the forward rate last period, as well as the variance of the nominal spot rate and the current forward rate. Their conclusion was that they found no significant effect of exchange rate risk on the volume of trade. Cushman(1983) uses a model similar to Hooper and Kohlhagen to investigate the effect of exchange rate uncertainty on trade flows among industrialised countries. However he enhances the model by extending the sample size to include more recent data and by using real rather than nominal exchange rate. Of the 14 sets of bilateral trade flows, Cushman found a significant negative effect of real exchange rate on trade flows in 6 cases against only 2 cases where the association is statistically significant and positive. Along the same line Bailey and Tavlas(1988) did not find any significant evidence of a negative effect of exchange rate variability on trade. The work of Akhtar and Hilton(1984) were among the few early papers which generated fairly consistent results. They derived volume and price equations for Germany and United States multilateral trade for the period pertaining to a floating exchange rate. Exchange rate volatility was measured in terms of the standard deviation of daily effective exchange rate within each quarter. The results suggested that nominal exchange rate volatility has a significant negative impact on the exports and imports of two countries. However Gotur(1985) points out the flaws in the methodology provided by Akhtar and Hilton by arguing that with small changes, their model generates only one negative significant effect and many positive effect. Gotur(1985) entended their work by increasing the number of countries to include France, United Kingdom and Japan and modifying the measures of exchange rate volatility but found a significant negative effect for German imports only and significant positive effects on multilateral US exports and Japanese imports. Also Kenen and Rodrigues(1986) studied the effects on exchange rate uncertainty with respect to multilateral manufacturing imports for eleven industrialised countries and found a significantly negative effect in only four of them. On the other hand Bailey, Tavlas and Ulan(1987) found no significant effect of exchange rate uncertainty on multilateral exports of industrialised countries. However most of the early works were inclusive about the relationship between exchange rate risk and trade and this could be attributed to a number of factors. First, the sample data used covered only a short period of exchange rate variability. Second, the equations used were rather basic and consisted only a few macro economic variables. According to the analysis of Mckenzie(1999) recent empirical studies have been more successful at generating statistically significant relationship between volatility and trade. This was due mainly to the emergence of more precise techniques of estimation and measurement of volatility and the use of more appropriate models. Kroner and Lastrapes (1993) and Arrize(1997a) argued that the mixed results obtained from early studies could be attributed to the use of inadequate measures of exchange rate risk. Unconditional measures of exchange rate volatility were mostly used, usually a moving standard deviation of levels or changes in past exchange rate. Recent studies use autoregressive conditional heteroskedasticity (ARCH) or generalised autoregressive conditional heteroskedasticity (GARCH) models instead. Other investigators like Caporale and Doroodian (1994) used a generalized autoregressive conditional heteroskedasticity (GARCH) technique to measure the volatility of exchange rate. They used monthly data for the period of 1974 -92 and found a significant negative effect of volatility on US imports from China. McKenzie and Brooks (1997) and McKenzie (1999) adopted ARCH modeling for measuring exchange rate volatility in their model for export trade for both German-US and Australian trade flows respectively. Even if their results were statistically significant they showed positive impact of volatility on trade, while for McKenzie (1999), the results were mixed. Some recent studies adopted the co-integration analysis which takes into account trend characteristics of the time-series data. It was found that such studies tend to be more clear-cut and most of them yield a significant negative impact of exchange rate volatility on the trade variables. Examples of such studies include Koray and Lastrapes (1989), Arize (1997, 1998a and b), Fountas and Aristotelous (1999) and Flam and Jansson (2000). Fountas and Aristotelous (1999) used cointegration technique to assess the effect or exchange rate variability on exports among European Union countries and found a significant negative long run effect. Similarly, in a series of studies, Arize(1997, 1998a and 1998b) found a significant negative long run and short run effect. Koray and Lastrapes (1989) arrived at a significant negative relationship between exchange rate uncertainty and bilateral imports for five industrialised countries and a smaller and weaker negative short run relationship. Finally, another set of empirical research employed the gravity model and has suggested significant evidence of a negative impact of exchange rate volatility on international trade. Basically, the gravity model express bilateral trade flows as depending positively on the size of the economy which is most often represented by GDP and negatively on their geographical distance from each other. Other variables such as population sizes are often included and the use of dummy variables to account for common characteristics which has the possibility of increasing trade between the two countries for example common language or common border. Pugh and al.(1999) use gravity model and panel data for 16 OECD countries within the period 1980-1992 and found that exchange rate volatility leads to a decrease in the level of trade by 8 percent points. Along the same line, the work of Dell’Ariccia(1999) suggest a significant and substantially negative impact of exchange rate volatility on bilateral trade flows of the 15 EU members and Switzerland for the period 1975-94. He also found that the elimination of the exchange rate volatility would lead to an increase of 10 percent in trade. Rose(2000) also bases his analysis on a gravity model of bilateral trade for 186 countries for the five years 1970, 1975, 1980, 1985, and 1990. His primary measure of volatility is the standard deviation of the first difference of the monthly logarithm of the bilateral nominal exchange rate, which is computed over the five years preceding the year of estimation. His finding is that exchange rate volatility has a significant negative effect on trade. Rose in another research paper provides empirical evidence that the adoption of a common currency has a substantial impact on trade flows. He finds that countries sharing a common currency, trade around three times more than countries outside a monetary union and this discovery was entitled the rose effect. Rose and Engel (2002) and Glick and Rose (2002) also found empirical evidence in support of rose previous findings. The above discussion shows that the effect of exchange rate volatility on trade volume is a priori ambiguous from theoretical and empirical perspective. Hence we will carry out an empirical investigation on this issue for bilateral trade between Mauritius and the United States.

Chapter 3: Research Methodology

3.1 Introduction

It can be concluded from the literature review that there have been mixed results from investigations carried out by investigators. The results varied from country to country and with the methodology used. The aim of this chapter is to specify and explain the model used to test the effect on exchange rate in volatility on the volume of trade in Mauritius. That is we will assess whether exchange rate volatility has a significant impact on the volume of trade and whether it is a positive or negative effect.

3.2 Population studied and data source

For the analysis, time series data will be used and will consist of annual data for the period 1978-2008. Also bilateral trade between the USA and Mauritius will be considered. The United States is among the top trading partners of Mauritius. Also exchange rates the rupees and the dollar is avai

3.3 Model specification

To test the effect of exchange rate volatility a theoretical model is developed to capture the impact of variability in exchange rate on exports and imports. Hence for our analysis two functions are specified: the export function and the import function. Each of these linear regressions models will be regressed and individual tests will be carried out on each of them.

3.3.1 The export function

In the analysis, we will use a traditional export demand which was used by Asseery and Peel (1991), Chowdhury (1993), Arize (1995) and Aristotelous(2002). However, this model is augmented by three additional variables: investment, inflation and capacity utilisation. Hence the the long-run equilibrium export demand can be written as: Xt = {Vt, RYt, RERt,, INVGt, INFt, CUt } REXP= ß0 + ß1Vt + ß2RYt + ß3RERt + ß4INVGt+ ß5INFt + ß6CUt + ut Where REXPt = Real Exports of Mauritius Vt = Exchange Rate volatility RYt = Real Foreign Income RERt = Real Exchange Rate INVGt= Investment as a percentage of GDP INFt=Domestic inflation rate CUt=Capacity utilisation of USA Ut = the error term Gotur (1985) illustrated that Equation 1 is a long-run reduced solution to a system of behavioural demand and supply functions for exports. Also the above variables will be in logs such that the equation can be written as follows: LREXP= ß0 + ß1LVt + ß2LRYt + ß3LRERt + ß4LINVGt+ ß4LINFt + ß4LCUt + ut

Definition of variables

Real Exports

The dependent variable in the equation is real exports. It represents the inflation-adjusted measure that reflects the total exports to the USA from Mauritius in a givenquarter, expressed in base-year prices. Real exports is obtained by dividing the nominal exports figures by export prices of Mauritius. Data will be obtained from the CSO and from the IMF statistical database.

National Income

The real foreign income of an economy is proxied by the real GDP of the importing country that is USA. It is measured in the importing country’s currency. Theory, supported by empirical evidence, suggests that the impact of real foreign income on exports should be positive. An increase in real GDP implies that the overall purchasing power of the country has increased and thus demand for Mauritian exports should increase and vice versa. Hence a positive coefficient is expected.

Bilateral Real Exchange Rate

This is the real spot exchange rate between Mauritius and the US. The real exchange rate must be define in such a way that an increase in ER reflects a depreciation of the Mauritian Rupees and if this depreciation should cause demand for Mauritian exports to increase, then the estimation of ß4 should be positive. Data about the exchange rate will be obtained from the IMF statistics. The real exchange rate will be obtained by dividing the nominal exchange rate with domestic prices and multiplying it by foreign prices. LRER= (ERxPf)/P* Where ER is the nominal exchange rate. Pf is the foreign prices that is the CPI of USA and P* is the domestic price that is the CPI of Mauritius.

Exchange Rate Volatility

There are a number of ways of measuring exchange rate volatility. One of the methods used by many researches is the standard deviation. The exchange rate volatility will be calculated by the standard deviation of the monthly percentage changes in the exchange rate a year. The effect of exchange rate volatility on exports is, from the theoretical viewpoint, ambiguous and may have a positive or negative impact on export flows.


Investment will be measured as a percentage of GDP. A positive sign is expected as an increase in investment will normally lead to an increase in exports. Data will be obtained from the CSO.


A negative coefficient for inflation is expected as an increase in inflation will make exports prices less competitive in international market. Data will be obtained from the CSO.

Foreign Capacity Utilisation

A negative sign is expected between foreign capacity utilisation and exports, This is because an increase in foreign capacity utilisation will lead to a decrease in exports. Data will be obtained from the federal reserve statistics release website.

3.3.2 The import function

The long run demand function is specified as follows: Mt = { Vt, RGDPt, RERt, INFt } RIMPt = ?0 + ? 1Vt + ?2RGDPt + ?3RERt + ?4INFt+ut The above equation will be expressed in its logarithmic form which gives: LRIMPt = ?0 + ? 1LVt + ?2LRGDPt + ?3LRERt + ?4LINFt + ut Where Vt=Exchange rate volatility LRIMPt =Real Imports LRGDPt =Real Domestic Income LRERt =Bilateral exchange rate LINFt= The domestic inflation rate ut =The error term

4.1.1 Definition of variables

Real Import

Real import is the dependent variable in the above equation. It reflects the inflation adjusted imports from the USA. Real Imports is obtained by dividing the nominal imports by impor pirces. The data for imports will be obtained from the CSO

Real Domestic Income

Real domestic income will be measured by the real GDP of Mauritius. The coefficient is expected to be positive since an increase in the real GDP of Mauritius is expected to increase the demand for foreign goods, i.e for US imports. Data about GDP will be obtained from the CSO.

Bilateral exchange rate

It is the real bilateral exchange rate between US dollars and Mauritian rupees. In this case also the real exchange rate must be defined in a manner that an increase in LRER reflects an appreciation of the Mauritian Rupee, which means the US dollar is depreciating against the rupee an hence imports are cheaper. This will positively effect imports from the US. Hence a negative coefficient is expected.

Exchange rate volatility

Exchange rate volatility will be the same as measured for the export function. The relationship of exchange rate volatility and real imports is ambiguous.

3.4 Econometric methodology

A multiple linear regression analysis will be used to assess the above relationship. Regression analysis is basically concerned with the study of the dependence of one variable(dependent variable) on one or more other variables(explanatory) in view of determining a relationship between the variables. Also stationary test will be performed on the data due to problems associated with non-stationary time series data. An error correction model will be used to specify the short run equation while cointegration will be used to obtain the long run equation.

Chapter 4: Estimation Procedure and Empirical Results

4.1 Introduction

This section reports the estimates for the long-run and short-run Mauritius import and export functions to the US and provides evidence of the impact of exchange rate volatility on the exports of Mauritius in the context of an error-correction model. The study will be based on time series analysis of the variables and hence prior to estimating the functions, the individual time-series properties of series must be tested.

4.2 Test for unit root

One major assumption of time series analysis is that the underlying time series is stationary. However researchers have found that the use of non-stationary time series or random walk series can lead to intriguing results, that is they tend to find evidence of a relationship when none in fact exist. This concept is termed as spurious regression and was first introduced by Newbold and Granger(1974). Hence it is important to test for stationarity when dealing with time series data. The ADF test will be used to test whether the underlying time series is stationary and to determine the order of integration.

4.3 Test for Cointegration

Even if all the variables are integrated order 1, it does not mean that they are cointegrated. If a series of variables are themselves non-stationary, but a linear combination of them yield a stationary process, then the series are said to be cointegrated. Therefore two or more variables are said to be cointegrated if they have a long term relationship between them. The two tests that will be carried out to test for cointegration are the Engle-Granger two step approach and the Johansen test for cointegration.

4.3.1 Johansen Test for cointegration

The Johansen test consist of comparing the trace statistics with the critical values in order to obtain the cointegrating rank. The hypotheses for the test are as follows: Trace Statistics: H0 : rank(?) = r0 H1: r0 < rank(?) = k

4.3.2 The Engle-Granger two step approach

The Engle-Granger test is used to confirm if any cointegrating relationship exits between the dependent and the independent variables. The first step of the test consists of evaluating whether the residuals from the regression are stationary. If significant ADF test is obtained from the test, then we can conclude that the variables are cointegrated.

ADF Test for stationarity of residuals

In absolute terms, the t-statistic is greater than the critical value in both equations. Therefore the variables cointegrate despite the fact that they are individually non-stationary. Hence it can be concluded that there is a long run relationship between exports and its explanatory variables and between imports and its explanatory variables. Consequently we can proceed to estimate the long run equation.

4.4 Test for Multicollinearity

Multicollinearity exist when there is a near perfect linear relationship among the predictors in a model. As the degree of multicollinearity increases, the regression model estimates of the coefficients become unstable and the standard errors for the coefficients can get wildly inflated. The variance inflation factor(VIF) can be used to detect presence of multicollinearity. As a rule of thumb, a variable whose VIF values are greater than 10 imply that the variable could be considered as a linear combination of other independent variables.

4.5 Model Specification Test

A model specification error can occur when one or more relevant variables are omitted from the model or one or more irrelevant variables are included in the model. The linktest can be used to detect specification errors. The linktest creates 2 new variables, hat which is the variable of prediction and hatsq, the variables of squared prediction. The model is then refit using these two variables as predictors. While the hat is expected to be statistically significant, hatsq is expected to be insignificant since if our model is specified correctly, the squared predictions should not have much explanatory power. The linktest shows that test statistics of hatsq is not significant. Therefore the linktest has failed to reject the assumption that the model is specified correctly.

4.6 Estimation result of Export Function

4.6.1 The Long run equation

Table 5 depicts the results for the short run equation. The results indicate that except for LCU and LV, all the variables are statistically significant. Therefore volatility is not statistically significant in explaining export volume, that is, it does not have any effect on the volume of exports to the USA in the long run. The result support the results obtained by Hooper and Kohlhagen (1978), Bahmani et Tavlas.(1988), Bailey et al.(1986), Cushman(1983) and recently Klassen(2004) who found no evidence of a significant relationship between volatility and international trade in their studies. This can be explained by the fact that in Mauritius operates under a managed float exchange rate regime and hence volatility is quite small compared to other countries which operate a freely floating exchange rate system. The coefficient of LCU also is insignificant and hence capital utilisation does not have any effect on volume exported to the USA. This is in line with the results obtained by Medhora(1990) The coefficient of LRY is significant at 1% and is positive. It is of the expected sign since an increase in the GDP of USA imply that the income of USA is increasing and hence demand for Mauritian exports should increase. A 1% increase in real GDP of USA lead to a 0.895% increase in export volume of Mauritius or differently stated, a 10% increase in the real GDP of US leads to 8.95% increase in volume of exports. Therefore it is one of the important determinants of the volume of exports to the USA. The same result was obtained by and Senhadi and Montenegro(1999), Marquez and McNeilly(1988), Sachs and Warner(1995), Frankel and Romer(1999) and Edwards(1998) in their work. LRER is another major determinant of export volume. positive and significant at 1%. It has a coefficient of 2.75 which implies that a 1% increase in the real exchange rate leads to a 2.75% increase in exports. This is because the exchange rate is expressed in terms of Rupees per US dollar. An increase in the LRER is indicative of a depreciation of the Mauritian Rupee vis-à-vis the US dollar, since $1 can buy more Mauritian Rupees. Therefore an increase in LRER means that the Rupees is cheaper vis-à-vis the US dollar and thus Mauritian exports will be cheaper for US which will cause an increase in its demand. This result support the results obtained by Himarios(1985) and Warner and Kreinin(1983) The coefficient of LINVG is positive and significant at 1%. This means that a 1% increase in investment as a percentage of GDP leads to a 1.54% in volume of exports to the USA. It is another major determinant of export volume. This is because in the long run, an increase in investment is likely to increase productivity and output. Patnaik and Chandrasekhar(1996) obtained the same results. The variable LINF has a negative coefficient and is significant at 2%. The results indicate that a 1% increase in inflation rate will bring about a 0.226% decrease in volume of exports. The results obtained are in line with those obtained by Kotan and Saygili(1999) and Gylfason(1998). Finally the R2 is 0.8785 which implies that the explanatory variables jointly explain 87.8% of the variations in the dependent variable. The Durbin-Watson statistic of 1.3, which is close to 2, indicates that there is no autocorrelation and since it is higher than the R2, means that there is no evidence of spurious regression.

4.6.2 The Short run equation

According to the Representation Theorem developed in Engle and Granger(1987), if the variables are cointegrated, it can be shown that the ECM will be of the following form: ?LREXPt= ß0 + ß1?LREXPt-2 + ß2?LVt-2 + ß3?LRYt-2 + ß4?LRERt-2 + ß5?LINVGt-2 + ß6?LINFt-2 + ß7?LCUt-2+ ß8 Rt-1 + ut Where Rt-1 is the lagged error correction term and is the residual from the cointegrating equation. If the variables in equation 1 have a cointegrating vector, then Rt is I(0) and represent the deviation from the equilibrium in period t. Hence the coefficient of Rt, ß7 indicates the adjustment towards equilibrium that takes place in a given period. It was shown in the Engle-Granger test for cointegration that the residuald from estimating equation 1 was I(0). The ECM which give information on the short-run export functions are presented in the table below. The ECM was estimated using a VECM. The VECM captures both the long run equilibrium and the short run dynamics of the model. The results report that exchange rate volatility is insignificant in the short run also. The coefficient of LRY is positive and significant at 1%. The impact of a change in real GDP is even more significant in the short run than in the long run, since a 1% increase in change in real GDP leads to a 11.5% increase in growth of volume of exports. This is because an increase in real GDP tends to have a higher immediate effect than in the long run as in the long run, the economy will tend to adjust itself to reach its initial equilibrium. That is in the long run the foreign economy will be able to increase its domestic output to meet any excess demand caused by an increase in income. ?LCUt is significant at 10% with a negative coefficient. This is because an increase in capacity utilisation will have a supply side effect on the country’s level of output. That is if a country is increasing its capacity utilisation, it will be able to increase domestic output. Hence there might be a temporary shift from consumption of foreign products to locally produced goods. However LCU does not have any effect on volume of exports from Mauritius in the long run. As regards the coefficient of ?LRERt, it is positive and significant. A 1% increase in growth of exchange rate leads to a 1.97% increase in growth of volume of exports. The effect of exchange rate is greater in the long run which supports the view put forward by Bahmani-Oskooee(1986) who concluded that trade flows are more responsive to changes in exchange rates in the long run. The coefficient of ?LINVGt is insignificant. This is because in the short run an increase in investment may not have any significant effect on the level of exports since it is only in the long run that productivity and output will increase as a results of an increase in investment. Also ?LINFt does not have any immediate effect on volume of export as in the short run since there’s always the expectation that inflation will decrease. Also there’s less scope to switch consumption to other products in the short run than in the long run where the importing country, i.e USA, can look for cheaper products from other countries. The coefficient of the error correction term Rt-1 is significant and negative which confirm the existence of a long run relationship between exports and the explanatory variables. It’s coefficient is 0.014 which is quite low which suggest a low speed of adjustment from the short run deviation to the long run equilibrium in LREXP. It indicates that only 1.4% of the deviation is corrected every year.

4.7 Estimation result of Export Function

4.7.1 The long run equation

Our Long-run equation can be formulated as follows: The results indicate that all the variables are significant except for volatility. Therefore volatility does not have any effect on volume of imports also. Gotur(1985), Cushman(1986) obtained similar results in their studies. LRGDP is again the major determinant of volume of imports from USA with a coffecient of 1.39. This means that a 1% increase in real GDP of Mauritius increases volume of imports from US by 1.38%. It is also significant at 1% level of significance. This result is in line with that obtained by Haque et al. The real exchange rate also is significant at 10% and is of the expected negative sign. A 1% increase in the real exchange rate of the Rupees against the dollar leads to a 0.78% decrease in imports. This is because an increase in LRER means that the Rupee is depreciating vis-à-vis the US dollar which makes the foreign price of imported goods denominated in the local currency higher. That is local consumers will have to pay more for the same goods. Hence demand for imported goods will decrease. The coefficient of LINF is negative and significant at 5%. However the effect of inflation on imports is quite small since a 1% increase in the rate of inflation brings about only a 0.12% increase in volume of imports. This may be because inflation rate in Mauritius is quite low and stable. Finally the R2 is 0.8815 which means that the independent variables explain 88.15% of the changes in the dependent variable. The Durbin Watson is 0.12 which is close to 2, indicating that there is no autocorrelation.

4.7.2 The Short run equation

The short run equation for volume of imports can be formulated as follows: ?LIMPt= ?0 + ? 1?LRIMPt-2 + ? 2?LVt-2 + ? 3?LRYt-2 + ? 4?LRERt-2 + ? 5 ?LINFt-2 + ?8 Rt-2 + ut-1 The results indicate that apart from ?LRERt-2, and Rt-1, all the variables are insignificant in the short run. Hence ?LRIMP, ?LVt, ?LRYt and ?LINFt has no immediate effect on the volume of exports. This may be because imports from US represent only a small share of total imports from US for Mauritius and hence changes in real GDP, volatility and inflation rate does not have any major effect on volume of imports in the short run. However ?LRERt is significant and negative. Hence a 1% increase in the exchange rate causes level of imports to increase by 0.96%. Finally the error correction term, Rt-1 is statistically significant and negative which confirm the existence of a long run relationship. The coefficient of the error correction term is 0.31 and suggests a fairly high speed of adjustment from the short run deviation to the long run equilibrium in RIMP. It indicates that 31% of the deviation is corrected every year

Chapter 5: Conclusion

5.1 Summary and Conclusion

This study examined the impact of exchange rate volatility of exchange rate volatility on bilateral trade flows between Mauritius and USA. Cointegration was used to estimate the long run equation and an error correction model was used to specify the short run equation. The empirical showed that exchange rate volatility has a negative but insignificant impact on bilateral exports and imports. Therefore it can be concluded that exchange rate volatility does not have any effect on bilateral trade between Mauritius and USA. Also, the results showed that other economic variables were significant at explaining volume of trade. In the long run, real exchange rate, foreign income and private investment had the greatest impact on the volume of exports and had the expected positive sign. Inflation was shown to have a negative effect on volume of trade but the effect was less important. Foreign capacity utilisation was found to be insignificant in the long run. In the short run private investment and inflation lost their significance while foreign capacity utilisation was found to have a negative and significant effect on exports volume. As for imports, real domestic income and real exchange rate were the variables that had the largest effect on volume of imports. Foreign income had a positive sign and while real exchange rate had the negative sign which are in line with most theoretical and empirical literature. Inflation rate had a positive effect on imports. In the short run however only real exchange rate was significant.

5.2 Policy implications and recommendations

The main finding of this paper is that exchange rate volatility does not have any significant impact on trade flows. These results are in line to those obtained by Akhtar and Hilton, Hooper and Kohlhagen(1978), Bahmani et al.(1993), Bailey et al.(1986) who dounf evidence of a negative but insignificant relationship between exchange rate volatility and trade. The insigficance of this relationship may be due to the fact that Mauritius has a manage float exchange rate regime which prevents wide fluctuations in the exchange rates. Hence the level of exchange rate volatility may be quite low in Mauritius and hence may not be a major concern for firms engaging in international trade. However government should still adopt and implement policies for stabilisation of the exchange rate market. This is because in this era of globalisation, countries are moving towards liberalisation of trade. Mauritius is member of the World Trade Organisation whose main aims is the elimination of trade barriers. Mauritius may eventually remove exchange rate controls by government and adopt a system of freely floating exchange rate. If sound macroeconomic policies are not adopted, this may lead to wide fluctuations in the exchange rate markets which would constitute a high level of foreign exchange risks to firms. In addition, firms must have the opportunity to hedge against foreign exchange risks. Ethier and Baron(1973a) concluded that with perfect forward markets and no other sources of uncertainty but the exchange rate, the volume of trade is unaffected by exchange rate volatility. Foreign exchange rate risk exposure is common to virtually all who conduct international business and/or trading. Buying and/or selling of goods or services denominated in foreign currencies can immediately expose you to foreign exchange rate risk. While firms may adopt internal risk management techniques to protect themselves again such risks, there are also external risk management techniques. There has been much advancement in the financial sector with regards to management of risk with regards the development of new financial instrument which involves the use of derivatives. Financial derivatives are financial instruments whose values are determined by an underlying financial instrument or indicator or commodity. The three major classes of derivatives include forwards or futures contract, options and swaps. Futures contract are contracts to buy or sell a specified asset, at a specified price, before or on a specified date. Forward/futures contracts are the oldest form of derivatives and are the most common form of hedging technique. Options are contract that give the owner the right but not the risk to buy or sell an asset. Swaps are the latest addition to the class of financial derivatives. Swaps are contracts to exchange cash flows or other rights or a stream of future payments based on the underlying value of currencies/exchange rate, bonds/interest rates, commodities, stocks or other assets. In Mauritius the derivatives market is still at its initial development stage. Hedging against foreign exchange risk through financial instruments is possible only for big companies since it is very costly. Government must implement the adequate policies and provide the initiatives for the development of the derivatives market in Mauritius. The latest development in the derivatives sector is the implementation of a new derivatives(commodity and currency futures) exchange in Mauritius. This exchange will be Africa’s 1st international multi-asset derivatives. The Commodity Exchange should allow different and categories of participants from within Mauritius and abroad to trade through an electronic platform linking geographically dispersed buyers and sellers in real time. The promoters of GBOT expect that the Commodity Exchange based in Mauritius will help accelerate the integration of the African sub-continent with the world economy by leveraging the strategic location of Mauritius between the time zones of New York, London, and Tokyo and will boost the image of Mauritius as a globally-integrated, leading financial centre in the region. The Exchange will facilitate links between commodity markets in Africa and global trading hubs, in accordance with principles of price transparency, trade efficiency, risk hedging and structured finance to the interiors of the region. Hooper and Kohlhagen(1978) concluded that the effect of exchange rate volatility on trade is ambiguous and depending on the relative degree of risk aversion of exporters and importers and their degree of risk exposure, which in turn depends on the invoicing currency and the extent of forward cover. Hence if firms in Mauritis are risk neutral, volatility of exchange rate will not impact on their decisions to import and exports. Moreover firms have the possibility to pass on increases in exchange rate in their prices. If demand for exports or imports is inelastic, then increases in prices of exports and imports should not have any effect on their quantity demanded. However passing on any unfavourable change in exchange rate in the prices charged might not be the appropriate solution since when competing in international market, remaining competitive in terms of prices is essential as otherwise firms may be driven out of competition. In addition, while our empirical study showed that exchange rate volatility does not significantly affect the volume of trade, the results confirmed that an appreciation or depreciation of the real exchange rate contribute to the improvement or deterioration of trade both in the long run and in the short run. In other words, real depreciations were found to have a positive impact on volume of exports and a negative impact on volume of imports. These results are consistent to the findings of authors like Warner and Kreinin(1983), Himarios(1989) and Kale(2001). Hence firms dealing through the foreign exchange are exposed to transaction risks. Transaction risks occurs due to the time differential between the date the contract is entered into and the settlement date when dealing through the foreign exchange. This is because firms are faced with uncertainty with respects to proceeds to be received or payments to be made if exchange rate fluctuate during the time interval. These arguments therefore reinforce the need for a derivatives market in Mauritius to manage risk. Apart from risk management facilities, Mauritius must adopt trade policies which will promote export growth and which will improve the trade of Mauritius. Trade regime in Mauritius previously emphasized on both imports substitution and incentives for exports. Early strategies included trade diversification, providing tax incentives, credit facilities and protective import duties and quotas. However import substitution turned out to be unfavourable. The trade regime in Mauritius now is more liberal. Mauritius must implement measures which will allow it in remain competitive in international market and to increase its international market share. Real exchange rate was shown to be a major determinant of volume of trade. Policies that will keep the exchange rate stable and depreciating can be adopted to promote export. Furthermore Mauritius has the option to devalue its currency to improve its trade deficit. However these types of measures are only short term. Mauritius needs to lay emphasis on trade promotion and export-driven policies which will guarantee long term competiveness of Mauritian exports. Mauritian products have to be made more competitive so as to retain and enhance the competitive advantage of Mauritius in the international market. One way to achieve this objective is by promoting private investment. Government must provide the adequate economic environment and incentives to encourage investment. Literature has provided much support towards investment as a tool for export growth. One such theory has been provided by Ghosh and Chandrsekhar(2001). Overall, Mauritius has provided a number of incentives in order to encourage investment local investors and to attract foreign investors from all over the world, with Hong Kong accounting for about two thirds of investment in the mid-1980s, followed by France, with 10 percent. Fiscal and financial incentives include income tax relief and exemptions from customs duties on EPZ-related imports and exports. Profits and dividends may be freely repatriated, capital brought into Mauritius (excluding capital appreciation, which is subject to exchange control and the regular rate of stamp duty) may be freely taken out, and preferential financing schemes are available. Sound monetary and fiscal policies must be maintained to attract and promote investment. The regulatory framework must the enhanced in Mauritius to protect the interest of investors, to promote fair competition and to eliminate anti-competitive behaviour. It must promote the free entry of exporting firms. Competition in an industry has a positive impact on productivity for example the quality of products are enhanced and prices are maintained at a competitive level. The regulatory framework should also aim at protecting Mauritius from external shocks. Government must also encourage investment in the technological innovation which helps the productive capacity and productivity of exporting firms. Another factor that affects the volume of trade is the rate of inflation. Policies to achieve a stable and low level of inflation should be adopted. A low rate of inflation imply that exports are more competitive. A low and stable rate of inflation is normally achieved through sound fiscal and monetary policies and also by maintaining a stable level of exchange rate. Since the abolition of trade preferences for both textiles and sugar, two pillars of the economy and the emergence of China as a major trading nation has had serious implications on trade and economic growth of Mauritius. Hence government needs to find new development strategies to ensure that Mauritius retain its place in the global market.  

Did you like this example?

This paper was written and submitted by a fellow student

Our verified experts write
your 100% original paper on any topic

Check Prices

Having doubts about how to write your paper correctly?

Our editors will help you fix any mistakes and get an A+!

Get started
Leave your email and we will send a sample to you.
Thank you!

We will send an essay sample to you in 2 Hours. If you need help faster you can always use our custom writing service.

Get help with my paper
Sorry, but copying text is forbidden on this website. You can leave an email and we will send it to you.