Instability is one of the most important decision parameters in development dynamics and in the context of export values. There are various ways of calculating export instability indices (as discussed in Chapter Four) which range from the one which is based on the deviations between observed and estimated values obtained by fitting the linear, exponential trend lines or logarithmic parabola function and the measure based on moving log averages. As indicated before, since there is no unique way of defining and measuring instability, three methods of calculating export instability index are employed and results based on the same measure are presented in Table 5.3.
Table 5.3: Instability Indices for Selected export commodities in South Africa Method Primary Commodities I1 I2 I3 Agriculture 35.4 62.3 18.0 Coal 13.2 17.8 12.4 Gold 14.3 17.7 16.7 Semi-Manufactured Commodities Tobacco 72.1 9.3 21.6 Textiles 18.0 20.9 7.4 Footwear 42.5 55 15.4 Beverages 44.8 55.1 8.6 Petroleum 23.5 29.4 10.5 Coke 61.0 82.6 21.2 Rubber 38.5 45.7 10.2 Plastic 30.6 38.1 10.5
Iron & Steel 14.0 16.5 7.6
Food 10.8 13.6 6.5 Manufactured commodities Chemicals 14.8 18.3 9.1 Machinery 23.9 30.2 14.7 Electronics 26.4 31.5 11.9 TV & Radio 32.6 41.2 17.3 Scientific Equipment 27.8 36 13.5 Transport Equipment 26.5 32.5 12.6 Motor Vehicles 30.6 37.2 12.1 Other Manufactures 14.7 18.9 9.3
Source: Own table made from figures obtained from Quantec, 2013 website. Computed based on the instability formulas given in Chapter 4.
As shown by Table 5.3, results from the deviations between the observed and estimated values obtained by an exponential trend lines exhibit the same trend. Results obtained from
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the five year moving average method and the coefficient are totally different from those obtained based on the deviations observed and estimated values obtained by fitting an exponential trend lines.
The interpretation of results in this section is linked to the conclusion made on the extent and nature of export diversification in South Africa. It is important that we group our commodities in terms of primary, semi manufactured and manufactured depending on the export diversification measures discussed in section 5.3. On comparison of the instability indices of primary commodities and semi manufactured goods with manufactured goods based on the linear and exponential measures, it is clear that the export instability index is higher for semi-manufactured and primary commodities in the period 1980 to 2012. Commodities that fall in the category of primary and semi manufactures are among others: agricultural products, coal, gold, iron and steel, textiles, footwear, beverages, petroleum, coke plastic, iron and steel and rubber products. The instability index for agricultural products is (62.3), coke (82.0), rubber (45) footwear (55), beverages (55.1). Based on these results we may be tempted to conclude that less diversified or primary commodities are associated with high instability indices. However, there are exceptional cases for TV and radio (41.2) and motor vehicles (37.2) which have high instability indices. Therefore, based on the results obtained on the deviations observed and estimated values obtained by fitting an exponential trend line, one cannot safely conclude that export diversification is directly linked to export stability. Results obtained from the two measures are to a larger extent against the findings from other researchers such as Wasim (2003) who found a direct link between export diversification and export instability.
Results produced by the moving log average method do not also give a clear picture as to whether manufactured or diversified export commodities are stable or unstable or it does not tell whether export diversification is directly linked to export stability. In other words, each index is based on a specific commodity be, it primary or secondary. If the commodities are in terms of the instability index, Tobacco has the highest of (21.6) followed by coke (21.2), agricultural products (18.0), television and radio (17.3), footwear (15.4), machinery (14.7), scientific equipment (15.5), transport equipment (12.6), coal (12.4), motor vehicle (12.1), electronics (11.9), plastics (10.5) petroleum (10.5), rubber (10.2), other manufactures (9.3) chemicals (9.1,) beverages (8.6), iron and steel (7.6), textiles (7.4) food stuffs (6.5) and gold
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5.8. The general conclusion would be that the majority of primary commodities are unstable as compared to manufactured commodities. Another notable feature is that all sections of exports relating to primary commodities and manufactured goods have shown a mixed trend in their instability indices. The reasons for the instability are associated with fluctuations in export value, volatile world prices and policy changes which have induced a very high degree of instability in some exports. The next section discusses export diversification and export growth in South Africa.
5.3 Export Diversification and export Growth in South Africa
The impact of export diversification on export growth is obtained when the growth rate of total exports is regressed against the growth rate of aggregate non-traditional commodities (vertical diversification) and the growth rate of aggregate traditional commodities (horizontal diversification). The regression results of the impact of export diversification on export growth are presented in Table 5.4.
Table 5.4: Results on the impact of export diversification on export growth
Constant GRNTC GRTC R2 DW 0.2487 0.1162 (1.92)* 0.3840 (2.48)** 0.62 1.5
Note: ** denotes significance at 5% level, * denotes significance at 1%, DW represents the Durbin-Watson statistics and R2 represent the power of the regression equation
The results in Table 5.4 indicate that the impetus for export growth in South Africa stems from both non-traditional vertical diversification and traditional (horizontal diversification). This is evidenced by the export commodity variables which are statistically significant. This implies that in order to augment total export growth, South Africa relies on more traditional commodities such as gold platinum and agricultural products and relies less on valued added non- traditional commodities such as electronic equipment and manufactured goods. The results are similar to Hasan and Toda (2004). Out of the four countries Malaysia, was the only country that had results similar to South Africa. Having established the relationship between export diversification and export growth, the next section is devoted to finding the association between export growth and export stability.
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