Eastern Cape Automotive Sector Analysis: An Economic Model For Policy .

Important lessons and definitions from table 1 are summarised below: Employment output ratio is a measure of labour productivity in the economy. Employment output ratio (EOR) is equal to the output produced by the workers (Q) divided by the number of workers (N): EOR Q / N. Between 1995 and 2010, labour productivity in the Eastern Cape automotive sector improved significantly. In 2010, each worker in the automotive sector generated production output worth R1.45 million compared to R0.67 million generated in 1995. Increase in labour productivity in the sector could partly be attributed to the increase in highly skilled employees in the sector. Remuneration value added ratio is a measure of the cost of labour relative to the value added by the labour expressed as a percentage. Remuneration value added ratio is equal to the total remuneration received by the employees (C) divided by the value added to the products or services by the employees (VA) times one hundred: remuneration value added ratio (C / VA)*100. Table 1 shows that in 2010, the labour remuneration in the Eastern Cape automotive sector accounted for 47% of the automotive sector’s gross value added, compared to 64% experienced in 1995 and 2000. Income distribution ratio is a measure that compares the amount of money that employees receive in the form of compensation of employee (wages and salaries) with the amount of money that shareholders receive (in the form dividends). Income distribution ratio compensation of employee divided by gross operating surplus. The income ratio shows that for every R1 that shareholders received, employees received R1.7 in 1995 down to R1.20 in 2005 and to R0.87 in 2010. As more income is generated in the sector, the distribution is skewed towards shareholders. Unit labour cost measures the average cost of producing one unit of output. Unit labour cost is equal to wage rate or earnings per worker (w) times the number of workers (N) divided by the output produced by the workers (Q): Unit labour cost (w*N) / Q. Where w*N is a measure of the cost of labour. It is

evident from table 1 that between 1995 and 2010 the unit labour cost in the Eastern Cape automotive sector has declined by half. The unit labour cost represented 14% of output in 1995, down to 7% of output in 2010. Overall productivity is a ratio of what is produced to what is required to produce it. Usually this ratio is in the form of an average, expressing the total output divided by the total input (P O/I). Productivity is a measure of output from a production process, per unit of input. The analysis shows that between 1995 and 2010, the cost of production grew much faster (input growth rate 128%) than that of output production (output growth rate 111%). As a result, the overall productivity ratio in the automotive sector fell to 1.18 in 2010 from 1.27 in 1995. The difference between output and input is the gross value added. Table 1 shows that in 1995, every R1.00 input generated R1.27 output (making R0.27 for GVA). In 2010, this GVA declined to R0.18 signalling a drop in the sector’s contribution to the provincial economy, and a decline in the overall productivity in the automotive sector. Fixed capital productivity is a measure of output per unit of fixed capital input. Fixed capital productivity is equal to total output (Q) divided by the fixed capital input (C), i.e. the capital stock. The analysis contrasts two ratios namely capital (output divided by capital stock) and labour (output divided by compensation of employees) to determine which factor of production (capital or labour) yields greater production output. The result shows that every R1 fixed capital stock corresponds to R4.9 output in 1995 and R7.2 output in 2010. Similarly, every R1 wages and salary corresponds to R7.1 output in 1995 and R13.4 output in 2010. It can be concluded that capital stock yields more output than labour. The import-domestic demand ratio or (import penetration) is equal to total imports (Z) divided by total domestic demand (DD) times one hundred: Import-domestic demand ratio (Z / DD)*100. Domestic demand is equal to total output plus imports minus exports. The import-domestic demand ratio is an indication of how much of the domestic

demand is satisfied by imports. The result shows that between 1995 and 2010, imports penetration almost doubled. In 1995, a quarter (25%) of domestic demand in the automotive sector was imported compared to almost half (46%) of domestic demand imported in 2010. Import leakage is a measure of how much is imported to satisfy local demand. Import leakage is equal to total imports (Z) divided by total imports added total output (Q) times one hundred. Import leakage [Z / (Z Q)]*100. The import leakage ratio has improved significantly over the period under review. The export-output ratio is a measure of how much of a country’s output they export. The export-output ratio is equal to total exports (X) divided by total output (Q) of an economy times one hundred. Export-output ratio (X / Q)*100. The analysis shows that between 1995 and 2010, the export-output ratio grew over ten-fold. In 2010, nearly half (43%) of output produced in the Eastern Cape automotive sector was exported. The value of exports increased from R0.6 million in 1995 to R14 million in 2010. The export destinations fall outside the scope of this report. Gross operating surplus is the surplus generated by operating activities after the labour factor input has been recompensed. It can be calculated from the value added at factor cost less the personnel costs. It is the balance available to the unit which allows it to recompense the providers of own funds and debt, to pay taxes and eventually to finance all or a part of its investment 2.3 How significant is the size of the Eastern Cape automotive sector? Table 2 shows the 2010 Eastern Cape automotive sector’s contribution to the Eastern Cape manufacturing sector, total provincial (EC) economy, total South Africa’s automotive sector, and total economy of South Africa. Important lessons derived from the Table 2 are summarised below.

Province-wide, the Eastern Cape automotive sector’s exports and imports contributed a lion share to the regional trade accounts. In 2010, the sector accounted for more than half (58%) of total imports in the province; slightly less than half (49%) of total exports in the Eastern Cape. Imports and exports in the Eastern Cape automotive represented 2.9% of total imports and 2.8% of total exports of the country as a whole. This means that the sector has a significant impact on the country’s balance of payment. There are risks and benefits associated with having half of your demand-side and the supply-side dependent on foreign trade. This means that any significant shock or structural change that occurs in the foreign importing country’s economy (recession, inflation/deflation, appreciation/depreciation of foreign currencies etc.) will also affect the automotive sector in the Eastern Cape. The automotive sector is not entirely dependent on the local economic conditions. The trade risk is split between domestic and foreign countries. Table 2: Eastern Cape automotive sector’s contribution (%) to the economy, 2010 Total EC manufactur ing sector Gross value added at basic prices 22.5 Compensation of employees - Total 21.5 Compensation of employees - Highly skilled 26.1 Compensation of employees - Skilled 28.6 Compensation of employees - Semi & unskilled 14.1 Gross operating surplus 23.9 Tax on production 26.4 Subsidies on production 39.9 Intermediate consumption 36.1 Output at basic prices 33.1 Gross domestic fixed investment: Rm constant 2005 prices 23.9 Fixed capital stock: Rm constant 2005 prices 16.9 Imports 57.3 Exports 53.2 Number of people employed (formal & Informal) 17.7 RSA EC total automotiv economy e sector 4.0 22.6 3.6 22.6 3.5 22.9 4.2 22.7 4.1 21.9 4.6 21.8 3.9 22.6 24.7 22.6 15.6 22.6 10.9 21.9 4.0 23.0 2.0 23.0 58.0 20.0 49.0 31.0 2.0 24.0 RSA total economy 0.3 0.3 0.3 0.4 0.3 0.3 0.3 2.0 1.3 0.9 0.3 0.1 2.9 2.8 0.2 Source: Author’s calculation derived from Statistics South Africa In terms of the labour market, table 2 shows that in 2010 the Eastern Cape (EC) automotive sector employed 18% of total employment in the EC manufacturing sector; 2% of total employment in the province; 24% of total employment in RSA automotive sector; and 0.2% of all total employment in RSA.

A quarter of subsidies on product in the Eastern Cape accrue to the automotive sector. Looking at total production output, the EC automotive sector’s output accounts for a third (33%) of total output in the EC manufacturing sector; more than a tenth (11%) of total output in the EC economy; almost a quarter (23%) of total output in the RSA automotive sector; and 1% of the country’s total output. More than a third (36%) of total input cost in the EC manufacturing sector is allocated to the automotive sector. This input cost is by large affected by the imports as shown in the table above. 2.4 Breakdown of demand in the automotive sector Who are the clients in the automotive sector? Asked differently, who are the consumers of the final products? Is the province producing for local (domestic) or for foreign market? Graph 1 presents the EC automotive products’ final demand. It shows that more than half of final demand is from foreign markets. A fifth of the demand for the automotive products is from households. Figure 1: Final demand in the EC automotive sector is driven by exports Source: Author’s calculation derived from Statistics South Africa

2.5. Performance, development and trends of the Eastern Cape automotive sector for selected indicators (1995 – 2010) Table 3 compares the average annual performance of the Eastern Cape’s automotive sector with that of the country as a whole. Clear evidence from table 3 reveals that, for almost all the indicators analysed, the Eastern Cape automotive sector performed below the average automotive sector for the country as a whole. Other important lessons from the table are summarised below: Employment in the automotive sector was very negligible during the period under review. Between 1995 and 2010, job creation grew at an annual average rate of 0.05% in the Eastern Cape while that of the country as a whole declined at an annual average rate of 0.6%. However, with the decline in employment, total production output in the automotive sector did not suffer. It increased at an average annual rate of 5.8% in the Eastern Cape and 6.7% in South Africa. Between 1995 and 2010, the input cost outgrew the production output, eroding the value added in the automotive sector. Persistent increase in input cost could in the long run make the sector less competitive and unsustainable. It is also noted that on average between 1995 and 2010, subsidies on production grew faster than taxes on production. A very interesting fact is the ten-fold annual increase in the gross operating surplus compared to the compensation of employees. In other words, on average between 1995 and 2010, on an annual basis, the workers’ income in the automotive sector grew ten times less than that of the shareholders. Export growth in the automotive sector performed above that of all other indicators. For the period under review, export grew on average three times faster than that of imports.

Table 3: Automotive sector’s average annual growth rate (1995 – 2010) for selected indicators in the Eastern Cape and South Africa Eastern Cape Gross value added at basic prices, Rm Compensation of employees - Total, Rm Compensation of employees - Highly skilled, Rm Compensation of employees - Skilled, Rm Compensation of employees - Semi & unskilled, Rm Gross operating surplus, Rm Tax on production, Rm Subsidies on production, (-) Rm Intermediate consumption, (-) Rm Output at basic prices, Rm Gross domestic fixed investment: Rm constant 2005 prices Fixed capital stock: Rm constant 2005 prices Imports value, Rm Exports value in current Rands Number of people employed (formal & Informal) Value (2010) 5 120 2 414 720 1 192 502 2 768 95 -157 29 145 34 264 897 4 779 16 771 14 686 23 700 Average annual growth rate (%) (1995-2010) 2.9 0.7 1.6 0.9 -0.6 7.2 7.2 9.2 6.5 5.8 4.7 2.8 10.3 34.1 0.1 South Africa Value (2010) 22 655 10 681 3 144 5 249 2 288 12 247 421 -695 128 962 151 617 3 940 21 147 85 458 47 418 96 794 Average annual growth rate (%) (1995-2010) 3.9 1.7 2.6 1.9 0.4 8.1 8.2 10.6 7.4 6.7 5.5 3.7 14.8 23.3 -0.6 Source: Author’s calculation derived from Statistics South Africa The next section provides a brief methodology in constructing the SUTs and SAMbased models. It explains the type of impacts analysing that can be derived from the supply and use tables (SUTs) and the social account matrix (SAM). It also shows how these models are used to analyse the impact of a particular sector of the economy.

3. Methodology and type of impact analysis The economic model used in this study is based on the Eastern Cape supply and use tables (SUTs) and the social account matrix (SAM). The model is being used to simulate major investment projects and their impact on the province’s economy. The SUTs and the SAM are based on the newly released 2008 system of national accounts developed by the United Nations. This section presents very briefly the methodology used to derive the regional multipliers. It provides definitions of a range of multipliers. The central focus in this section is the explanation of the type of impacts analyses that are derived from the economic model. The section prepares the reader to have a better understanding of the results that are presented in section 4. The section starts by defining the concept of the SUTs and the SAM. According to the United Nations’ 2008 system of national accounts (2008 SNA), a SAM is defined as the presentation of SNA accounts in a matrix which elaborates the linkages between the supply and use tables and institutional sector accounts. In many instances, SAM’s have been applied to an analysis of interrelationships between structural features of an economy and the distribution of income and expenditure among household groups (Kavese, 2007). The 2008 SNA also provides the definition of the supply and use table. The supply table shows the origin of the resources of goods and services. The use table shows the uses of goods and services and the cost structure of the various industries. The supply and use tables have both statistical and analytical functions. As a statistical tool SUTs provide a coordinating framework for checking the consistency of economic statistics on flows of goods and services obtained from the different kinds of statistical sources. As an analytical tool, the SUTs are conveniently integrated into macroeconomic models in order to analyse the link and interaction between final demand and industrial output levels (Kavese 2007a, 2007).

3.1 Type of impact analysis The SUTs and the SAM are valuable tools in estimating the effects of a major investment project, changes in government spending, or changes in income giving rise to changes in household spending. In principle, an increase in the demand for a product is not an once‐off event: it triggers secondary effects along the way. However, it takes time for a particular increase in final demand to work through all the sectors in the economy (Jeffery Round, 2005 and Round, (2003). The type of impact analysis used in the SUTs and the SAM are shown diagrammatically in figure 2. Figure 2: Effects caused by a change in final demand Initial impact: refers to the factors of production (capital, labour) that are initially brought into the project. First round impact (also referred to as first order effects): includes the impact of sectors required to produce more to meet the demand from the project. For example: the construction of a building plant will need brick, mortar, steel,

machinery, etc., so the other sectors in the economy need to supply these materials. First order effects are the changes in business activity and production occurring as a direct consequence of a project. Direct impact: The direct impact is the sum of the initial and first round impacts. Indirect impact: Indirect effects result from changes in sales by suppliers to the directly‐affected businesses, including trade and services at the retail, wholesale, and producer levels. The businesses needing to supply the project will also need to expand, which will affect other businesses/sectors (theoretically an infinite number of times, until the change becomes too small to measure). Direct and indirect impact: This is the sum of the direct and indirect impacts. Induced impact: Induced effects are further shifts in spending on food, clothing, shelter, and other consumer goods and services caused by a change in personal income of workers employed by the directly and indirectly affected businesses. Economy‐wide impact: This is the sum of the direct, indirect, and induced effects. Type I multipliers measure the direct and indirect effects, while Type II multipliers measure the induced effect. In analysing the multipliers, it is important to specify which one to use. Depending on the problem at hand, one can use the type I and type II demand-side multipliers or type I and type II supply-side multipliers. This study uses type I and type II demandside multipliers because it assumes R1 million increases in final demand in the automotive sector (Defourney and Thorbecke (1984): 111-136; Wassily Leontief (1905).

3.2 Methodology and structure of the two‐region inter-regional economic model 3.2.1. Basic structure of the two‐region inter-regional economic model5 Given region R (Eastern Cape) and N (the rest of South Africa excluding the Eastern Cape), the two region tables represent the complete intra-regional (ZRR and ZNN) and inter-regional (ZNR and ZRN) intermediate data flows. The inter‐industry transactions table can be represented as shown in equation 1. Z (1) Where ZRR and ZNN represent intra-regional trade and ZRN represents inter-regional trade (exports) of region R to region N and ZNR of region N to region R. The intra-regional input coefficients for regions R and N will be: and (2) The inter-regional input coefficients for regions NR and RN will be: and (3) Equations 2 and 3 can be compactly rewritten as two equations: (I – ARR)XR – ARNXN YR 5 (4) Refer to the work done by Defourney, j., and E. Tho

productivity ratio in the automotive sector declined from 1.27 in 1995 to 1.18 in 2010. In 2010, employment in the Eastern Cape automotive sector accounted for 0.2% of the total employment in South Africa, 24.0% of the RSA automotive sector's employment, 2.0% of the total employment in the Eastern Cape, and 17.7% of the