ANALYSIS OF THE EFFECT OF EXCHANGE RATE FLUCTUATIONS ON COFFEE EXPORTS IN UGANDA. CASE STUDY 1991-2015
CHAPTER ONE
1.0 Introduction
This chapter presents the background of the study, the problem statement, and objectives of the study, research questions, scope of the study, and significance of the study and final definition of key terms.
Exporting is one of the most important channels through which developing countries can link with the world economy (World Bank, 2001). Exporting allows firms in developing countries to enlarge their markets and benefit from economies of scale. Additionally, several scholars have pointed out the importance of exporting as a channel of technology transfer (Pack, 1993).Thus, for better performance of developing country, it is vital to identify the major determinants of its export supply. In order to formulate trade and industrial policies aimed at stimulating exports, it is important to understand which factors stimulate ordeter firms from entering foreign markets.
Redding and Venable (2004), investigate the relative contribution towards export performance. They find that internal components related to supply capacity such as internal geography and institutional quality played a significant role in explaining the observed differential inexport performance. According to Redding and Venables (2004), the relative export performance of the African and Middle Eastern countries tended to deteriorate over 1980s and 1990s. This was driven by relatively poor performance in supply capacity. However, since the late 90s, East Asian and Pacific countries in particular have been among the main beneficiaries of foreign market access which coincides with their successful diversification efforts. Exchange rate which reflects the underlyingrelative movement of prices at home and abroad is proved to have a significant effect on the export performance ofthe lowest performers.
One of the world’s most widely traded commodities is coffee. Coffee beans when roasted produce a flavorful, aromatic and caffeine filled drink that is popular all over the world, with over 600 billion cups sold each year (ICO, 2014). Two botanically different trees can produce coffee. Arabica coffee trees produce coffee beans that are more labor intensive in its cultivation and are grown at higher altitudes. This coffee is milder, more aromatic and more complex than its Robusta counterpart (ICE, 2014). For many countries, over 50% of their total export earnings can be accounted for by coffee exports. In fact, the top 10 Arabica coffee exporting countries in the world are considered developing. The UCDA estimates that approximately 77 million 60 Kilogram bags were exported from the top 10 coffee exporting countries in 2011-2012.
Coffee is one of the most significant exported commodities by Brazil Colombia, Guatemala and Honduras, and as previously noted, these are among the top exporting countries of Arabica coffee. Naturally, coffee plays a significant role in the composition of the Gross Domestic Product and Agricultural Gross Domestic Product of these countries, Coffee makes up the highest percentage of both GDP and AGDP for Honduras with 7.37% and 48.17 %, respectively. Honduras is similarly followed by Guatemala with 2.49% and 21.08%; Colombia with 0.86% and 12.53%; and finally Brazil with 0.35% and 6.41%, (ICE, 2014).
For most low developed economies in Sub-Sahara Africa (SSA), agriculture has been the main source of livelihood both in terms contributing 34% to Gross Domestic Product (GDP) and 64% to employment, either directly or indirectly, Dependence on agricultural commodities like coffee for exports has been accompanied by a high degree of price risk in terms of both volatile and declining prices, a phenomenon which has not only affected the way households allocate their resources but also affected their welfare in terms of consumption and export volume to the world market.
Uganda’s export sector is dominated by primary products (about 74.1 %), (Roberta, 2004). These include agricultural products; mainly coffee, cotton, flowers, simsim, fish; unprocessed minerals such as gold; live animals, hides and skins among others. At independence time (1962), Uganda’s traditional exports constituted agricultural commodities and unprocessed minerals. By the end of the 1970s, coffee was the largest foreign exchange earner accounting for about 51 percent leaving cotton, copper, tea and tobacco sharing the other portion of the earnings (Musinguzi, 2002).
Coffee continues to play a leading role in the economy of Uganda, contributing 18% of the export earnings between 2000 and 2010, despite the vigorous efforts by Government to diversify the economy. Though large scale coffee producers are gradually emerging, the coffee sub-sector is almost entirely dependent on about 500 000 smallholder farmers, 90 percent of whose average farm size ranges from less than 0.5 to 2.5 hectares (UCDA, 2012). The coffee industry employs over 3.5 million families through coffee related activities.Though large scale coffee producers are gradually emerging, the coffee sub-sector is almost entirely dependent on about 500000 smallholder farmers, Domestic consumption of the commodity in Uganda is relatively small ranging from 4-10% of production. As such, coffee is primarily an export crop, between 2005 and 2010, (Sayer, 2002).
Coffee has continued to play a leading role in the economy of Uganda (UBOS 2011). It contributes between 20-30 percent of the foreign exchange earnings (Uganda Coffee Development Authority, 2009). In 1995, the National Union of Coffee Agribusinesses and Farm Enterprises (NUCAFE), this has led to the coming up of some large scale coffee farmers. Though large scale coffee producers are gradually emerging, the coffee sub-sector is almost entirely dependent on about 500,000 smallholder farmers, 90 percent of whose average farm size ranges from 0.5 to 2.5 hectares. The coffee industry employs over 3.5 million family members through coffee related activities. From the 1920s, coffee was grown for export and in the 1950s an extensive coffee production programme was launched. In 1972, coffee production reached 4.2 million bags of 60Kgs each. Thereafter, coffee production declined tremendously because of civil strife, poor marketing systems, and low producer prices arising from government monopoly and controls (Rudaherenwa, et al 2003).
Uganda ranks fourth after Burundi, Ethiopia and Honduras in terms of contribution of coffee exports in total export earnings in the period 2000-2010 with an average share of 18% during this period (ICO, 2012). The post-1997 coffee price decline has had a negative effect on production and exports(Baffes, 2006). However, production kept declining even when prices recovered until 2006 and has recently been declining.
Although coffee contributed as much as $400 million annually to total merchandise exports during the mid-1990s, it currently (2010) contributes about $280 million (MAAIF, 2011). Understandably, the sector’s poor performance raised concerns among policy makers. However, despite the declining foreign earnings compared to the mid-1990s, coffee remained the main foreign exchange earner for the country. Its share in total export earnings declined marginally from 17.9 percent in 2009 to 17.5 percent in 2010.
Despite a significant decline in quantity exported coffee export earnings in 2010 increased by 13.1 percent as a result of higher global prices although there was an overall 14.3 percent decline in the quantity of coffee produced in 2010. Coffee exports in 2010/11 were 156,000 MT valued at US$ 338 million. European Union is the main market for Uganda coffee export accounting for over 70% of total exports followed by Sudan importing over 10% of Ugandan coffee and USA with 3% of coffee exports of Uganda (Figure 3) (UCDA, 2011). However, the export market of Uganda is quite diverse with a total of 16 importing countries. The export market is controlled by 29 national and multi-national companies with ten companies controlling about 85% of the export market. The leading company Ugacof (U), Ltd) controlled 15% of the coffee export in 2011 (UCDA, 2011). The top ten importing companies held a market share of 73.4% in 2011.
Uganda’s export sector is dominated by primary products (about 74.1 %), (Roberta, 2004). These include agricultural products; mainly coffee, cotton, flowers, simsim, fish; unprocessed minerals such as gold; live animals, hides and skins among others. At independence time (1962), Uganda’s traditional exports constituted agricultural commodities and unprocessed minerals. By the end of the 1970s, coffee was the largest foreign exchange earner accounting for about 51 percent leaving cotton, copper, tea and tobacco sharing the other portion of the earnings (Musinguzi, 2002).
In Uganda, Robusta Coffee is mainly grown in the low altitude areas of Central, Eastern, Western and South Eastern Uganda up to 1,200 meters above sea level. Arabica coffee requires cool, moist and higher altitude. It is mainly grown on Uganda’s mountain fringes, on Mount Elgon in the east (notably in Bugisu, on the western slopes of Mount Elgon in Mbale district) and on the Ruwenzori’s and West Nile (Nebbi and Okoro districts) on the border with Congo. Some Arabica is also grown in Mbarara district in Western Uganda (Sayer, 2002).
Figure 1: Graph showing the changes in the quantity of coffee exported by Uganda since 1991-2010
The figure 1 above shows that Uganda’s exports of coffee in 1994 increased 1000,000 Kgs and Uganda exported the largest amount of coffee in 1996 which was above 4,000,000 Kgs , this figure also indicates that the export of Uganda coffee has been fluctuating over the years and by 2010 there was a great general decline of the coffee exports as compared to other years like 1996, 1998, 2000, 2002 this volatility in exports therefore indicates that Uganda’s coffee faces various challenges in its export of coffee to the world markets. From 1991 to 1998, coffee exports increased mainly due to fair prices on the international market. Thereafter, coffee exports declinedalmost every subsequent year. This is mainly due to adverse prices on the international market, and there exists a huge value gap between the global revenues generated from coffee and what producing countries earn, due to a long supply chain with very many participants. For instance, in the year 2006/2007, the global coffee revenues were US$90 billion but farmers in producing countries all combined including Brazil earned only US$9 billion which is 10 percent of the global value share (UCDA, 2009). Basing on this background, this study therefore intends to analyze the effect of exchange rate fluctuations on coffee exports in Uganda.
1.2 Problem statement
Uganda ranks fourth after Burundi, Ethiopia and Honduras in terms of contribution of coffee exports in total export earnings in the period 2000-2010 with an average share of 18% during this period (ICO, 2012).According to figure 1 above there has been unstable export volume of coffee in Uganda from 1991 up to 2010, this is also shown by the fact that there was a rise in coffee export to the world market from 159,983 tons in 2004 up to 200,640 tons in 2008 however the coffee exports generally declined from 200,640 tons in 2008 to 159, 433 tons in 2010.Coffee exports have been declining since 1998 (refer to fig 1) despite the measures undertaken by the government to boost the sector.
Although coffee contributed as much as $400 million annually to total merchandise exports during the mid-1990s, it currently (2010) contributes about $280 million (MAAIF, 2011). Understandably, the sector’s poor performance raised concerns among policy makers.However, despite the fluctuations in coffee forex earnings compared to the mid-1990s, coffee remains the main foreign exchange earner for the country. Its share in total foreign exchange earnings is not stable. According to the international coffee organization (2015) the downward trend in the coffee market continued by December2015, although the rate of decline slowed. The monthly average of the ICO composite settled on 114.63 US cents/lb, down by 0.3% compared to November. This is nearly 24% lower than its level in December 2014, albeit 7.6% higher than December 2013. Over 2015, coffee prices have remained in a relatively narrow range between 110 and 130 cents, whereas the first six months of 2015 saw a much greater range of 115 to 155 cents (ICO 2015). Therefore this study intends to analyze of the effect of exchange rate fluctuations on coffee exports in Uganda.
The general objective of the study is to analyze of the effect of exchange rate fluctuations on coffee exports in Uganda.
1.3.2 Specific objectives
- To determine the causes of exchange rate fluctuations on coffee exports in Uganda.
- To examine the impact of coffee prices on coffee exports in Uganda.
- What are the causes of exchange rate fluctuations on coffee exports in Uganda?
- What are the impacts of Coffee prices on coffee exports in Uganda?
1.5 Scope of the study
1.5.1 Content scope.
The study will specifically provide in-depth examination on the effects of exchange rate fluctuations on coffee exports in Uganda, the effects of coffee prices on coffee exports in Uganda and the effects of coffee quality on its exports in Uganda.
The study will focus on the determinants of export volumes of Uganda’s coffee covering the period 1991-2015. The period was chosen because reforms in the coffee export sub-sector were introduced in 1991. These were expected to have contributed to a sustained increase in coffee exports by 2015.
1.6 Significance of the study
The findings of the study will be beneficial in the following ways;
- The study provides academicians with analysis of the effect of exchange rate fluctuations on coffee exports in Uganda.
- The study helps researchers have information regarding the effects of coffee prices on coffee exports.
- The study adds on existing literature regarding the effects of coffee quality on its exports.
LITERATURE REVIEW
2.1 Determinants of coffee exports
These will include Exchange Rate Fluctuation, coffee prices and coffee quality
2.1.1 Exchange Rate Fluctuation and coffee export performance
For a study of the Fridman (1953) proposition that floating exchange rate regimes allow the nominal exchange rate to act as a shock absorber in small, open economies and thus help insulate them against real external shocks, see among others Broda (2004), who found that the short-run real GDP impact of negative terms of trade shocks was smaller in floats than in pegs, and Hoffman (2007), who also found that external shocks were less contractionary under floating than under pegged exchange rates.
Gonenc and Yilmaz (2008) point out the high effect of exchange rate on the competitiveness. They did find out that imported input costs act as a natural hedge against exchange rate movements and have a substantial effect on competitiveness. Aysan and Hachasanoglu (2007), on the other hand, found that real exchange depreciation does not induce a huge increase in exports.
Exchange rate volatility is defined as the risk associated with unexpected movements in the exchange rate. Economic fundamentals such as the inflation rate, interest rate and the balance of payments, which have been more volatile in the 1980s and early 1990s, by themselves, are sources of exchange rate volatility (Ozturk, 2006). The NEWS impacts suggested by Tibesigwa and Kaberuka (2014) could also be added onto the list of the factors that bring about volatilities or abrupt shifts in the exchange rates of any economy.
The last decades have brought on board various models, modelling techniques and modelling software in modelling exchange rate volatility, since the early 1980s to date researchers like Engle (1982), Bollerslev (1986) have advanced various time series models and edited the ARCH model to come up with a more generalized ARCH model, Tibesigwa and Kaberuka (2014) however, state that though these models have been used in developed countries, their applicability is still minimal in the analysis of developing countries like Uganda.
The period of late 90’s, Uganda was characterized by general high prices of conventional traditional exports and market determined exchange rate as a result of abolition of the auction in 1993, which in turn led to inflows of foreign currency and appreciation of a shilling thus negatively impacting on coffee exports (Bigstern and Kayizzi 1999).
Studies by Friedman (1953) and Johnson (1969) indicate that exchange rate has an effect on volume of trade and that flexible exchange rates promote trade and macroeconomic stability, however, in the short run fluctuations in rates do not affect volume of trade. While findings by Sangita (2000) indicated that exchange rate depreciation promotes increased export volumes. Additionally, an increase in RER means a real appreciation of the domestic currency, which makes exportable items more costly. If the RER appreciates, the demand for exports is likely to fall, and the reverse is likely to occur if the RER depreciates. On the other hand, the study by Ajab(1996) indicated that favourable exchange rates for the export sub sector made imports more expensive thus encouraging the production of import-substitutes and services in Uganda. He adds that overvaluation of exchange rate discourages domestic production of exports making imports cheap and exports non-competitive. But despite the importance of an appropriated Exchange Rate Fluctuation, it is easy to maintain a favourableExchange Rate Fluctuation as it involves also the macro-level management of the economy (Ajab, 1996).
Studies by Ayudin.et al., (2004) also indicate that Exchange Rate Fluctuation is a significant determinant of imports and the trade deficit, but not of exports and that it exhibits a negative relationship. However, Rodrick (1998) in his study on Trade Policy and Economic Performance in Sub- Saharan Africa pointed out that overvalued currencies were due to inward oriented policies, which reduced openness.
2.1.2 Coffee prices and coffee exports
From 1991 to 1998, coffee exports increased mainly due to fair prices on the international market. Thereafter, coffee exports declined almost every subsequent year. This is mainly due to adverse prices on the international market, and there exists a huge value gap between the global revenues generated from coffee and what producing countries earn, due to a long supply chain with very many participants. For instance, in the year 2006/2007, the global coffee revenues were US$90 billion but farmers in producing countries all combined including Brazil earned only US$9 billion which is 10 percent of the global value share (UCDA, 2009).
Coffee farmers in African producing countries all combined earned less than US$2 billion, which is about 22 percent of the total value share that producing countries earned when all combined. Africa’s total value share to global value was only about two percent. Uganda earned about US$170 million and the coffee farmers altogether earned less than US$90 million which is about 53 percent value share, while middlemen (occasional traders) and exporters earned 38 percent and nine percent respectively. This clearly shows that coffee farmers have to upgrade and increase their value share (UCDA, 2009).
Old and Prizzon (2010) showthat the performance of Exportvolumeishighlyambiguous with respect to price: positive, but not significant.Thiswas based on theprice elasticity of0.09which was insignificant.This means that a one percent increase in the international price marginally increases exports by about 0.1 percent.
Jaeger (1992) carried out an ambitious econometric study on 21 SSA countries in order to estimate the price responsiveness of total agricultural supply and of a few key crops taken individually. In the case of coffee, he found a positive short-run elasticity of 0.237 for SSA producers as a whole, but almost no significant results when examining each country separately.This implies that a one percentage increasein price leads to 0.2 percent increasein the supply of Sub-Saharanagricultural exports.
In another study (Gabriele, 1994) tried to estimate the price elasticity of traditional primary Exportsin four Central American countries over the 1960-1990 periods. Short-term price elasticity variedbetween 0.08 and 0.19. This implies that traditional primaryexports of Central American countries do not respond highly to changes in price.
According to Ackah and Morrissey (2005),factors external to an individual country, such as world pricesare typically more important determinantsof the volume and value of exports than a country’s own trade policies.This is because small country producers have no capacity to determine these prices on their own.
A set of theoretical models by Dixit (1989), Krugman (1989) and others suggest that hysteresis in exports may be due to the sunk costs in entering the export market at firm level. The underlying theory is that there are fixed costs of exporting that deter those firms operating below a threshold level of efficiency because their prospective profits from exporting do not compensate for additional costs (Roberts and Tybout, 1997). Sunk costs may include expenses related to establishing a distribution channel and modification of commodities to foreign tastes. These costs may vary with the skill of staff, firm age, firm size and ownership structure of the firm (Graner and Isaksson, 2002)
Mbowa (1992) noted that cotton, coffee and tea exports increased with depreciation in the Ugandan shilling. This implied that improving price incentives through exchange rate adjustment was effective in boosting traditional export growth. While Orcutt (1950) indicated that trade flows respond positively or negative to small and temporary changes in prices on the international market. According to Morrissey et al., (2003), export revenues are largely determined by world prices and the prices play an important role in the determination of imports and exports in developing countries.
Oskooee (1986) argued that trade flows are more responsive to changes in the relative prices than to changes in the exchange rates in the long-run. In addition Goldstein and Khan (1985) reported that for perfect substitutes, price respond negatively and so export volumes shrink as relative export price increases and expand as relative prices of substitutes decrease, which is an important assumption in the perfect elasticities of export supplies. However, all the above studies were assessing the impact of export prices of a country’s general trade volumes not isolating the fast growing export commodities like the organics.
On the other hand, Vijaya (2007) argued that the drivers of price volatility for cotton and other agricultural exports are at the production, processing, exporter and macro levels summarized in Table 3.1. Although this may also be true to the Ugandan context, other factors like high certification costs, quality inconsistencies, absence or limited support policies are likely to affect the entire organic sub-sector in Uganda.
2.1.3Coffee quality and coffee exports
(Adams, F.G. and J.R. Behrman 1982, p. 3) Clearly, the role of primary commodity exports as the main source of foreign exchange for LOCs is of vital importance. For Ethiopia, about 90 percent of its exports are agricultural primary products, and as has been discussed in the preceding chapter, coffee is the single most important crop contributing 60-65 percent, on average, of the total foreign exchange earnings of the country.
Quality is a key factor for Uganda’s access to the world coffee market and for the price obtained for its coffee. The price paid for different coffee qualities depends on the type of coffee (Arabica/Robusta), bean size (screen), processing (dry/wet), color, taste (cup), and the reputation of the country of origin(Belling, 2002). In addition, western consumers are increasingly willing to pay a higher price for coffee produced in socially and environmentally responsible ways, and in reputable localities or appellations. Obtaining a price premium thus depends as much on the ability to sell a story as on the intrinsic qualities of the coffee (Ponte, 2001).
A spectacular growth in the specialty coffee niche markets in North America and Western Europe in the 1990s (Ponte 2002b) provides the Ugandan coffee industry with an opportunity to increase its revenues from this market segment and so partly compensate for revenue losses in the industrial blends markets. Specialty coffee here includes all coffees that are not traditional industrial blends, notably single-origin and high-grade Arabica coffee grown in certified, environmentally friendly ways (organic, shade-grown, bird-friendly), and coffee sold through Fair Trade organizations, which guarantee a higher compensation to producers and workers (Ibid).
Climatic change is expected to result in a change of forest type and species (Bezabih et al, 2010). Depending upon the resilience of the forest trees to climatic change, the impact on Arabica coffee may be less than expected, or more if the forest stand is expected change significantly, as climate changes. Forests can provide a more sheltered environment and more protective atmosphere than field grown crops , and forests may provide a greater resilience to climatic change through changed water holding dynamics, interception of heavy rainfall , and shaded environments (Senbeta et al ., 2007).
Using mean annual temperatures and total annual precipitation as predictors of climatic suitability has limitations. Crops do not respond directly to the amount of precipitation but, instead, to water availability. Evapotranspiration, soil water capacity and management systems affect water availability, along with other factors that are not modeled or accounted for in this study, while precipitation may act as a good proxy for water availability, especially in large parts of East Africa where Arabica coffee is most often farmed as a rain-fed crop, (Willson, 1985).
Mean annual temperature and precipitation are not the only variables that will affect the distribution and success of Arabica coffee. Atmospheric composition affects yields and plant health and some studies suggest that yields of C plants such as rice, wheat and soybean could rise by 10% -20% under increased CO concentrations (Tubiello, 2007). Arabica coffee is a C plant and should benefit from yield increases through increased CO2 atmospheric concentrations.
Arabica coffee requires slightly acidic soils and a good supply of nutrients, especially potassium (Willson, 1985). Nutrient availability may be affected by future climatic change, through changing interactions between minerals, water supply and above ground versus below ground processes (Montoya and Raffaelli, 2010).
Gregory et al.(2009), concluded that the number of soil dwelling weevil larvae Sitoniaspp, which attacks legume root nodules, will increase under higher CO2 concentrations, reducing the rate of nitrogen fixation (Gregory et al., 2009).
Arabica coffee is susceptible to a number of pests and diseases. The coffee berry borer, Hypothenemushampei, is the most devastating pest of coffee in the world, and as mean annual temperatures increase across East Africa the incidence of H. hampei will increase , as the insect develops fastest at temperatures between 27°C -30°C (Jaramillo et al., 2009).
Currently, mean temperatures across East Africa are around 22°C but this will increase to 26C by 2080. Before 1984, the region of Jimma, Southwest Ethiopia was too cold for H. hampei to develop; today there are at least one -two cycles of generation each year (Jaramillo et al .2009). Coffee Berry Disease, Cooletotrichumcoffeanum, attacks young coffee berries and thrives in wet conditions as rainfall is required for spore production and dispersal (Waller, 1985). The future climate in East Africa may become more favourable for a variety of pests and diseases, decreasing the productivity of Arabica coffee.
Disease may burden the local population, as malaria is predicted to expand into new areas within East Africa and water -borne sanitation diseases such as cholera thrive in warm water environments (Hay et al., 2002;Lippet al., 2002).
As East Africa becomes warmer and wetter, new environmental conditions may favour the development of human diseases. Increasing illness and mortality amongst the populations of East Africa limits the workforce available to manage farmland.
Coffee is a labour intensive crop, requiring pruning on a regular basis to maintain the highest quality and quantity yields (Gay et al., 2006). Malnutrition and hunger is expected to remain high in large parts of East Africa, and some regions are expected to endure higher rates of malnutrition than the present day (Liuetal., 2008).
METHODOLOGY
3.1 Research design
This study will adopt a cross sectional survey design. This design will be preferred because it enables collecting data in a short time (Creswell 2003 and Koul 2005).Quantitative approach will be used because of its flexibility to form multiple scale and indices focused on the same construct (Ahunja 2005).
3.2 Study population
The researcher will use secondary data obtained from the national income accounts of Uganda as prepared and compiled by the Ministry of Finance and Economic Development (MOFED), Department of National Accounts, UBOS, UCDA and World Bank Africa database for the period between 1991 and 2015.
3.3 Sample size and selection technique
The study will focus on determinants of export volumes of Uganda’s coffee covering 20 years that was from 1991 to 2015. The period will be chosen because reforms in the coffee export sub-sector were introduced in 1991. These will be expected to have contributed to a sustained increase in coffee exports.
3.4 Data type and sources
Source of data will be from secondary sources. The main source of data for this study will be the national income accounts of Uganda as prepared and compiled by the Ministry of Finance and Economic Development (MOFED), Department of National Accounts, UBOS, UCDA. In addition World Bank Africa database will be used. The data was for the period 1991-2015.
Data on quantity of coffee exports and coffee prices will be got from the Uganda coffee development authority (UCDA), Uganda Bureau of statistics, journals, newspapers, text books and while data on interest rates will be got from Bank of Uganda and UBOS. Secondary data will be sourced because it yields more accurate information than obtained through primary data, and it was also cheaper.
3.5 Tools of data collection
The data will be got by presenting an introduction letter given to me by the head of department. This will clearly present my purpose to the different organizations where I am egible to collect the necessary data for my analysis.
3.6 Data Analysis
The time series data will be analyzed using Ordinary Least Squares. Unit root tests will be conducted using ADF to find out the existence of unit root. The variables will be tested to determine the presence or absence of integration. Error Correction Model will be used to capture the short run effects. There after a short-run parsimonious model will be estimated after isolating the statistically insignificant variables from the error correction model. This will be followed by performing diagnostic tests of serial correlation, stability and heteroskedasticity.The instruments of data analysis will be SPSS, EVIEWS.
Analytical Procedure
This study will use annual data to examine the determi nants of coffee export in Uganda. The co-integration procedure requires time series in the system to be non-stationary in their levels. Moreover, it is imperative that all time series in the co-integrating equation have the same order of integration. Thus, the study will first ascertains the time series properties of coffee export and other explanatory variables by using the augmented Dickey-Fuller (ADF) and Philips-Perron test for stationarity (Dickey and Fuller, 1979 and 1981). The equation will estimate for the ADF test as follows:
Where, for example Xt=LCX is the coffee export supply in natural logarithmic, D is the first difference operator, t is the time trend, β, δ and θ are parameters, Ɛ is the stationary random error and n is the maximum lag length. The null hypothesis is that the series contains a unit root which implies that β1=0 the null hypothesis is rejected if β1 is negative and statistically significant. To determine the long run relationship between coffee export supply and explanatory variables, the Johansen co-integration procedure is used (Johansen and Juselius, 1990 and Johansen, 1991). The procedure involves the estimation of a VECM. The VECM used in the study is as follows:
Where, Yt is the dependent variable, Zt is the explanatory variables, Xt is exogenous variable, Yt-1 –θZt-1 is the error correction and D is represents the difference operator. Furthermore, ε represents the vector of white noise process. The VECM allows causality to emerge even if the coefficients of the lagged differences of the explanatory variable are not jointly significant.
(Granger, 1983; Engle and Granger, 1987; Miller and Russek, 1990; Miller, 1991; Dawit, 2003). In this study, an attempt is made to specify the coffee export supply function of Ethiopia following Alemayehu (2002) and UNCTAD (2005). The hypothesized variables in this study will be rainfall, relative domestic price, labour employed in agriculture, Exchange Rate Fluctuation, domestic interest rate, foreign capital inflow, capacity utilization rate, real income, and term of trade. All variables are in natural logarithmic forms and β’s are parameters to be estimated which are elasticities.
3.7 Limitations of the study
- The researcher may face financial constraint in terms of transport, stationery, research assistants, printing and binding services during the research process.
- The time available for the research will be limited however the researcher will balance time between research and other responsibilities to enable the success of research.
