Impact Assessment of the Cocoa Rehabilitation Project on Cocoa Exports in Ghana

Cocoa export is the biggest source of Ghana’s core revenue from agriculture. This study employs the cointegration approach to measure the impact of the factors that influenced cocoa export performance in Ghana after the cocoa rehabilitation project was introduced into the cocoa sector from 1988 to 1993 by analyzing relevant time series data from 1988 to 2018. The results of the analyses show that all the variables used in the study do not substantially in-fluence cocoa exports in the long run. The study concludes that even though the cocoa rehabilitation project may have had a lasting impact on the performance of the cocoa sector in recent years; resulting in increments in foreign exchange revenue, production and exports, the project to a larger extent has failed to adequately cater for all of the needs of the most important stake-holder of the cash crop—the farmer. The study recommends that Government should restructure and empower the Ghana Cocoa Board through the Ministry of Food and Agriculture to ensure proper supervision and accoun-tability in the management of cocoa sector reforms.


Introduction
The

Literature Review
A good number of cocoa sector reforms have led to a more liberal cocoa sector [2] [3] [4] which has impacted positively on production and export performance in Ghana [5] [6] [7] [8], Nigeria [9] [10] [11] and Cote d'Ivoire [12] leading to an increase in exports and thus impacting GDP and GDP growth rate positively [13] [14] [15]. Others such as [16] by applying the comparative cost theory by [17] concluded that a positive relationship between production and exports led to fewer taxes on producers and reduction in costs. References [18] [19] [20] identified real exchange rate as an important driver of cocoa exports in Nigeria during the period of the structural adjustment programs (SAPs) in the 1980s through to the early 2000s. Reference [19] also found a positive relationship between cocoa export and world cocoa prices in Nigeria. However, high trade deficits and international debts as a result of the performance of the Cedi against major trade partners result in a fall in cocoa production and exports.
The share of producer prices comparative to world cocoa prices in the 2000s varied from one country to another [21] where higher producer prices were paid to farmers in Ecuador, as a result of an efficient marketing regime [22] in Cameroun as a result of reduced taxes on cocoa [23] and in Indonesia as a result of limited but supportive government policy reforms [24]. Meanwhile, Ghanaian farmers faced lower producer prices [25] as a result of high inflation levels and exchange rate distortions whiles farmers in Cote d'Ivoire were paid much lower producer prices because of high taxation, estimated between 25% and 30% from 2002-2009 [26]. Moreover, the effect of the world cocoa prices on farmers' investment decisions is quite significant [27] [41]. The Ghana Cocoa Board (COCOBOD), through the Cocoa Research Institute of Ghana (CRIG) has over the years improved on technology in production, leading to quality hybrid cocoa varieties and improved cocoa flavor quality. The significance of this study is to generally assess the feasibility, sustainability and profitability of the CRP as well open up the possibility of conducting studies on other policy reforms introduced into the cocoa sector.

Methodology and Materials Data Sources and Model Specification
Annual time series data from 1988 to 2018 obtained from Ghana Chamber of Mines and the Minerals Commission of Ghana were used for the analyses in this study. Also, the official CRP document and other relevant journals were sourced for secondary information.
The Cointegration Approach was chosen for the modelling and analysis in this study because of its relevance, practicality and usefulness in policy analysis. The cointegration approach also helps to define the relationship between the variables expressed in the models. The multiple regression model used identifies Ghana cocoa exports as the response variable whereas Ghana cocoa production, world cocoa exports, world cocoa production, world cocoa prices (US$/t), gross domestic product growth rate and real exchange rate are the explanatory variables. The model is given as: The general form of the model estimated in this study is expressed in the following form: GCEx is Ghana cocoa exports, whiles GCP is Ghana cocoa production, WCEx (World cocoa exports), WCP (World cocoa production), WCPx (World cocoa prices), GDPgr (gross domestic product growth rate of the Ghanaian economy), and RER (annual average real exchange rate; Ghanaian Cedi relative to the US Dollar).
To reduce the inconsistency in the variables, a natural log was employed into the model. To determine the relationship between the response and explanatory variables, we regressed the following equation. The primary objective here is to establish whether the explanatory variables have any impact on the response variable. β β β β β β β are coefficients of the explanatory variables and ε is the error term.
According to [42], the non-stationarity condition of time series data analysis is often likely to result in misleading results as well as drawing spurious conclusions. So to avoid this, we employed the Augmented Dickey-Fuller (ADF) unit root tests [43] to examine the time series properties of each variable by testing for their stationarity at both levels and first difference. By employing Engel and Granger's two-step methodology, we investigated the short-run equilibrium relationship between the variables by using the error correction model (ECM).
First, we established a long-run model after a cointegration relationship between the variables had been established; after which we used the information on the error term in the long-run model as an added variable in the short-run model.

Results of Analysis of the Time-Series Properties of the Variables
Having employed the ADF unit root tests, we measured the univariate time series properties of the variables to define the characteristics of the roots of the variables in the data. The critical values were tested at 1%, 5%, and 10% significance levels. The ADF tests results show Ghana cocoa exports, world cocoa exports and production to be significant at all levels. However, Ghana cocoa production, world prices, GDP growth rate as well as real exchange rate were found to be insignificant at all levels.
Having confirmed that some of the variables are not stationary at levels, we went ahead to conduct a unit root test for the first difference of the data. All the variables were significant at first difference.

Results on Cointegration Analysis
Johansen Cointegration test was performed to examinewhether there exist a long run relationship among the variables and also to determine the cointegrating rank of the model and the number of common stochastic trends that exist among the variables. The results of the Johansen Cointegration test are presented in Table 4.

Results of the Vector Error Correction Model (VECM) Analysis
Having established the existence of a cointegration relationship among the variables, we proceed to estimate the short-run error correction model to assess equilibrium adjustments by using the disequilibrium estimates from the long-run model. The error correction term (ECT) is given as: [ ] where the response variable is β is constant and Having specified the ECT, we estimated the short-run VECM equation as follows: The results of the VECM are stated in Equation (8) Table 6 presents the results of the error correction model. The first differences and the error term from the model based on the variables as shown in the table above are represented by D and To interpret the results of the adjustment coefficients in Equation (8), it can be seen that the deviation of previous years from long-run equilibrium is corrected in the short-run at an adjustment speed of 32.6%. The result of the short-run estimate is consistent with [44] and [45] which concluded that the level and performance of the real exchange rate significantly affect a country's export volumes and value when they assessed the impact of real exchange rate on export performance in Tanzania and Ethiopia and Bangladesh respectively.
More so, all the explanatory variables used in the study do not significantly influence cocoa exports from Ghana in the short run. Table 7

Conclusion
The results of the analysis show that over the study period, Ghana cocoa production and exports accounted for 14.99% and 16.17% of all world production  [12] [46] and other related research such as [47] which found cocoa production to have a positive impact on exports in the short run in Nigeria and Cote d'Ivoire respectively; even though we report the impact in Ghana to be insignificant. The study also agrees with [48] to report a negative relationship between world cocoa prices and export performance in Ghana. References [19] and [49] however report a positive relationship between world prices and cocoa exports in Nigeria and Cote d'Ivoire respectively. This study also disagrees with findings by [50] and [51] which reported a linkage between cocoa export performance and GDP growth rate as a measure of improved standard of living and poverty

Recommendations
The study recommends that COCOBOD schemes and programs that seek to train farmers to produce cocoa that conform to global demands and standards, to increase production and income must be strictly enforced as well as broadened to cater for practical field or on-site training and periodic supervision to help farmers gain the requisite knowledge and experience in proper farm management in accordance with the provisions made for by the CRP policy document. Secondly, the study recommends that Government should take a second look at Ghana's inputs supply structure and restructure it to meet the pressing demands and needs of the farmers. For instance, the fact that inputs are not readily available in local stores, even when the farmers can afford them typifies a failure of the inputs supply structure.
Lastly, it is recommended that Government recognizes the significant role women play in the various stages of cocoa production and introduces such policies that will attract more women into the sector and also provide financial assistance to make cocoa farming attractive to the youth as a measure to tackle high rural unemployment, increase annual yields and foreign exchange revenues, reduce rural-urban migration as well as help alleviate rural poverty.