Assessing the Impact of Exchange Rate Volatility on the Competitiveness of South Africa’s Agricultural Exports
Bibliographic record
Abstract
The fluctuations of the exchange rate of the domestic currency have been a major concern. Since the 1970’s there has been a debate on the relationship between exchange rate volatility and export flows. In the wake of the recent global financial crisis and rising food prices, this debate has become even more strident and the concerns even more palpable. South Africa has not escaped the debate. The exchange rate of the South African Rand has been undergoing a series of devaluations for several decades. In such a situation, exporters must contend with some exchange rate volatility which might have implications for export flows. However, in the absence of systematic study, neither the magnitude of the fluctuations nor their impacts is known with certainty and this presents immense policy difficulties. This paper seeks to provide answers to the most commonly asked question as to the magnitude and extent of such fluctuations and their precise impacts on export levels and the market shares of South African citrus exports in the destination markets around the world. The principal objective it to estimate the impact of exchange rate volatility on the competitiveness of South Africa’s agricultural exports. The paper reviews the theoretical literature in respect to foreign exchange market, Balance of Payments, exchange rate models and the evidence from monetarists and the Purchasing Power Parity. Laspeyres-indexed export prices, exchange rates and export volumes for maize, oranges, sugar, apples, grapes, pears, avocados, pineapples, apricots and peaches for the period 1980-2008 and exports to the European Union are modeled by means of ARIMA (AR) and Autoregressive Conditional Heteroscedasticity (ARCH) and export demand equation estimated. The Constant Market Share (CMS) model was applied to assess the extent to which the SA citrus industry has maintained its competitive advantage in several markets. The overall results obtained strongly confirm that exchange rate volatility have a positive impact on the competitiveness of South Africa’s agricultural exports and that, despite the on-going financial crisis that has engulfed the world, South Africa’s citrus exports have maintained a healthy market share. This result is surprising but understandable in the light of the special arrangements put in place by South Africa’s monetary authorities to protect the Rand from over-exposure to global financial developments over the period under review. The important practical implications of these findings for the success of the agricultural restructuring programmes going on in South Africa are evaluated and discussed against the backdrop of the fresh debates on national economic policy management in the wake of financial meltdown that has once again threatened the financial stability of virtually every region in the world in recent years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".