OECD s Work on South Africa s Trade

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Transcription:

OECD s Work on South Africa s Trade By Przemyslaw Kowalski, Development Division, Trade and Agriculture Directorate National Agricultural Marketing Council, Pretoria, 24 November 2009

Presentation Outline Part I: Overview of completed work: South Africa chapter in the Globalisation and Emerging Economies (South Africa s Trade and Growth, OECD Trade Policy Working Paper No. 87) Part II: OECD s current work on Globalisation and Comparative Advantage in OECD and emerging market economies Discussion of past, current and future work, possible future co-operation

South Africa s Trade and Growth Working Paper Contents Economic growth and general trade performance Positioning in the world trade network Composition and performance of SA s exports at a product and sector level Econometric assessment of comparative trade performance Main historical and trade policy developments Econometric assessment of impact of trade liberalisation on total factor productivity

Changing architecture of world trade network Stable core with new and well established member: China Many countries became middle powers by increasing bilateral relationships Globalisation has not led to marginalisation of less well connected in fact the trade network has become more multilateral

SA: striding towards the core of 100 C 95 IP United States Soviet Union/Russia the trade network India China 90 Brazil P 85 80 Indonesia O75 70 65 South Af rica 1980 1985 1990 1995 2000 2004 2005

Major South African Export Sectors Chapter Structural Performance Export Share % Trade Ratio Sector HS 2003 2006 2003 2006 M/X 2006 71 Pearls, precious stones and metals etc star star 17.0 21.0 0.1 72 Iron and steel star traditional 12.0 11.0 0.2 27 Mineral fuels traditional traditional 10.0 10.0 2.5 84 Boilers, machinery emerging emerging 8.0 9.0 2.4 87 Vehicles other than railway emerging emerging 10.0 9.0 1.5 26 Ores etc snail traditional 4.0 6.0 0.1 76 Aluminium snail star 3.0 4.0 0.1 85 Electrical, electronic equipment emerging emerging 2.4 2.3 6.5 8 Edible nuts, fruit star emerging 2.8 2.2 0.1 28 Inorganic chemicals snail traditional 1.8 2.0 0.9 29 Organic chemicals star emerging 1.6 1.8 1.2 73 Iron and steel emerging star 1.4 1.6 1.0 22 Beverages and spirits star snail 2.0 1.4 0.4 74 Copper, articles of snail star 0.5 1.2 0.4 88 Aircraft emerging emerging 0.3 1.1 1.4 39 Plastics star traditional 1.3 1.1 2.7 38 Misc. chemical products traditional emerging 1.0 1.1 1.4 48 Paper, paperboard emerging snail 1.5 1.0 1.4 94 Furniture, lighting, prefab buildings emerging snail 1.8 1.0 1.0 44 Wood, articles emerging snail 1.4 0.8 0.8

Sectors with Highest Comparative Advantage HS chapter 1996 2006 Annual average growth rate 71 Natural/cultured pearls, prec stone 7.427 10.464 3.5 26 Ores, slag and ash. 8.516 7.846-0.8 08 Edible fruit and nuts; peel of citr 3.695 5.016 3.1 36 Explosives; pyrotechnic prod; match 3.671 4.779 2.7 72 Iron and steel. 4.272 3.717-1.4 76 Aluminium and articles thereof. 3.004 3.570 1.7 51 Wool, fine/coarse animal hair, hors 3.359 3.487 0.4 47 Pulp of wood/of other fibrous cellu 4.118 3.115-2.8 17 Sugars and sugar confectionery. 4.092 3.068-2.8 28 Inorgn chem; compds of prec mtl, r 4.841 2.884-5.0 22 Beverages, spirits and vinegar. 2.467 2.375-0.4 75 Nickel and articles thereof. 8.283 2.369-11.8 81 Other base metals; cermets; article 3.349 2.249-3.9 20 Prep of vegetable, fruit, nuts or o 2.759 2.041-3.0 24 Tobacco and manufactured tobacco su 0.492 1.649 12.9 86 Railw/tramw locom, rolling-stock & 5.240 1.613-11.1 41 Raw hides and skins (other than fu 2.617 1.431-5.9 25 Salt; sulphur; earth & ston; plaste 2.183 1.428-4.2 03 Fish & crustacean, mollusc & other 1.090 1.378 2.4 68 Art of stone, plaster, cement, asbe 1.191 1.350 1.3

Intensely exported manufactures HS chapter 1996 2006 Annual average growth rate 84 Nuclear reactors, boilers, mchy & m 0.345 0.644 6.4 85 Electrical mchy equip parts thereof 0.138 0.162 1.6 87 Vehicles o/t railw/tramw roll-stock 0.303 1.014 12.8 88 Aircraft, spacecraft, and parts the 0.209 0.740 13.5

Top 25 Export Growth Products Rank Product Product_Name Value Growth % 1 711019 Platinum in other semi-manufactured 670,107,487 2 711011 Platinum unwrought or in powder form 580,953,720 3 711031 Rhodium unwrought or in powder form 246,679,447 4 711021 Palladium unwrought or in powder form 104,677,185 5 711039 Rhodium in other semi-manufactured 91,089,273 6 711029 Palladium in other semi-manufacture 71,251,081 7 711041 Iridium, osmium and ruthenium unwrought 38,277,940 8 720292 Ferro-vanadium 7,648,933 9 261590 Niobium, tantalum and vanadium ores 1,615,154 10 750610 Plates, sheet, strip and foil, nickel 550,157 11 260400 Nickel ores and concentrates 493,496 12 291612 Esters of acrylic acid 260,965 13 271000 Petroleum oils, etc, (excl. crude) 229,532 14 290513 Butan-1-ol (n-butyl alcohol) 184,971 15 240310 Smoking tobacco 112,506 16 480419 Kraftliner, uncoated 32,822 17 740811 Wire of refined copper 25,148 18 854140 Photosensitive semiconductor device 22,911 19 852721 Radio receivers 16,076 20 840820 Engines, diesel 14,555

Export mix according to skill 100% intensity Primary Low-skill manufacture High-skill manufacture 90% 80% 70% 60% 50% 40% 30% 17 41 26 31 20% 42 43 10% 0% 1996 2006

Taxes on international trade and 12 transactions % of revenue % of GDP % of merchandise imports 10 8 6 4 2 0

Simple average tariff by production stage Capital goods Consumer goods Intermediate goods Raw materials 1988 5.85 18.11 10.74 3.80 1990 5.83 16.22 9.92 3.69 1991 6.02 15.85 9.59 4.34 1993 6.19 27.89 14.55 5.61 1996 2.83 27.15 11.80 6.28 1997 4.27 12.93 5.21 5.65 1999 2.35 11.34 4.49 4.47 2001 2.17 15.24 6.10 5.22 2004 2.05 15.18 6.18 4.09 2005 2.03 14.95 6.11 2.86 2006 2.01 14.93 6.08 2.86 2007 2.06 15.28 5.64 4.19

Effective rates of protection Effective Rate of Protection 1988 1994 2003 Tobacco 410.9 340.5 315.4 Wearing apparel 101.9 218.4 96.7 Textiles 95.3 149.7 85.3 Footwear 77.3 106.0 50.7 Furniture 83.8 82.6 46.3 Food 51.4 55.3 36.4 Rubber products 68.0 46.6 33.3 Motor vehicles, parts and accessories 58.1 45.1 32.7 Average across sectors 58.1 59.8 32.4 Beverages 43.1 52.0 25.3 Plastic products 51.0 36.2 20.2 Leather and leather products 52.4 59.7 19.2 Other manufacturing 95.8 96.5 17.3 Metal products excluding machinery 46.4 36.7 16.6 Wood and wood products 25.9 21.7 14.8 Glass and glass products 40.7 32.1 14.3 Basic iron and steel 24.6 20.1 11.1 Non-metallic minerals 34.6 29.9 10.8 Paper and paper products 12.4 15.8 10.1

Outstanding issues How does further liberalisation fit with economic policy objectives? Employment Dependency on natural resources Relation of trade and labour market policies Relation of trade and industrial policies How to avoid negative consequences of industrial policy? Future of SA agriculture? Importance of services in South Africa s trade and growth

Special focus: How to assess country s relative trade global trends performance? permanent exporting country factors permanent partner country factors permanent bilateral factors role of own competitiveness and policy developments

From gravity to fixed effects ij ij i j M m m ij m ji ij j i ij P z b d Y Y Y X log 1 log 1...... log ) log( log 1 log log 1 ijt N N j jt N i it N N j N N p ij j N i i T t t jt it ijt Y Y X 2 1 1 2 1 2 / ) ( 1 1 1 2 log

Interpretation of fixed N i1 T t1 i t 2 N jn 1 j effects terms isolate the time effects that are common to all trading country pairs time-invariant fixed effects for exporting and importing countries, respectively 2 ( N N ) ij p1 are country pair-specific time-invariant fixed effects that account for factors such as the time-invariant bilateral trading costs N i1 it 2N jn 1 jt time-variant importer and exporter-specific fixed effects (price effects along with time-varying factors specific to an exporting or importing country e.g. opening up to trade on an MFN basis or country-specific reforms and policies)

Data Trade bilateral exports from Comtrade, 1985-2005 46 countries: OECD countries plus Brazil, India, Indonesia, China, Russian Federation and South Africa (BRIICS) and Chile; Hong Kong, China; Singapore; Thailand; China Taipei; Malaysia; Philippines; Venezuela; Israel; Colombia and Argentina raw materials, intermediate goods, consumption goods, capital goods

Source: ComTrade data, authors calculations Average annual percentage change in relative export indicator (1988-2005) South Africa s comparative trade performance 12 10 8 6 4 2 0 China Brazil India Indonesia Russia South Africa

Summary of average annual change in exporter and importer fixed effects China Brazil India Indonesia Russia South Africa Exporter Total trade 8 3 7 7 11 6 Consumption goods 6 2 9 6 11 12 Raw materials 0 8 7 7 9 8 Capital goods 22 7 13 28 3 11 Intermediate goods 5 1 6 7 12 9 Importer Total trade 1 6 3-7 1 4 Consumption goods 3 12 4-2 -2 4 Raw materials 6 2 5 0-4 1 Capital goods 9 9 7-9 2 5 Intermediate goods -1 6 5-6 8 0

Current OECD work on trade and specialisation dynamics scope of research

Current OECD work on trade and specialisation dynamics analysis of production, trade and comparative advantage developments in OECD and major emerging market (EM) economies determining the impact on trade competitiveness of various underlying economic and policy factors

Four reports + case studies Production, Consumption and Trade Developments Comparative Advantage Developments Factor Content of Trade and Labour Market Implications of Globalisation Changing Patterns of Comparative Advantage: Policy Implications Case studies: construction services in India and China, agriculture in Brazil and South Africa, textiles worldwide, others?

Assessment of Policy Implications Comparative empirical assessment of effectiveness of a range of trade and domestic (but trade-related) policies in improving trade performance Export performance at sector level determined by: industry measures of dependence on various policies economy wide policies Result: establishing the relative importance of various policies for export performance across the OECD membership and EM economies

Assessment of Policy Implications (2) database of policy indicators and econometric assessment of the actual export performance at the sector level decomposition of determinants of trade flows that allows to capture how well conditions in country i provide for the production needs of industry k (Chor, 2008):

Comparative Advantage Dynamics Selected Preliminary Results with Special Focus on South Africa

Comparative Advantage Developments Concept and policy implications of revealed comparative advantage (RCA) analysis Patterns and trends in RCA using various indices; similarities and disparities across the OECD membership and EM economies Dynamic analysis of RCA; mobility in the middle-scale and upper and lower ranges of RCA Identification of potential case studies

RCA indices by broad sector 13 12 11 10 9 8 7 6 5 4 3 1992 2000 2008 2 1 0

Incidence of RCA by sector 70 % of products with RCA>1 60 50 40 30 20 2 digit 4 digit 6 digit 10 0

Changes in RCA wrt 1992 1992 0 2 4 6 8 10 12 14 2000 0 2 4 6 8 10 12 14 2008 0 2 4 6 8 10 12 14

Changes in RCA wrt 1992 movements at the top and bottom of distribution

Rank correlation coefficient of RCA indices

0.2.4.6.8 1 Cumulative RCA distribution-sa -1 -.5 0.5 1 bilxrca cumul_bilxrca_90 cumul_bilxrca_07 cumul_bilxrca_97

0.2.4.6.8 1 Cumulative RCA distribution- USA -1 -.5 0.5 1 bilxrca cumul_bilxrca_90 cumul_bilxrca_07 cumul_bilxrca_97

0.2.4.6.8 1 Cumulative RCA distribution- Germany -1 -.5 0.5 1 bilxrca cumul_bilxrca_90 cumul_bilxrca_07 cumul_bilxrca_97

0.2.4.6.8 1 Cumulative RCA distribution- China -1 -.5 0.5 1 bilxrca cumul_bilxrca_90 cumul_bilxrca_07 cumul_bilxrca_97

0.2.4.6.8 1 Cumulative RCA distribution- Brazil -1 -.5 0.5 1 bilxrca cumul_bilxrca_90 cumul_bilxrca_07 cumul_bilxrca_97

0.5 1 1.5 Kernel density estimate--sa Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =. 1990 1997 2007

0.2.4.6.8 1 Kernel density estimate--us Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =.09 1990 1997 2007

0.2.4.6.8 1 Kernel density estimate-- Germany Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =.09 1990 1997 2007

0.2.4.6.8 Kernel density estimate-- China Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =.13 1990 1997 2007

0.5 1 1.5 Kernel density estimate-india Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =.13 1990 1997 2007

0.5 1 1.5 Kernel density estimate-- Brazil Kernel density estimate -1 -.5 0.5 1 bilxrca kernel = epanechnikov, bandwidth =.12 1990 1997 2007

change in coeff of variation Dispersion of RCA indices falls in the OECD 0.6 0.4 0.2 0 0 2 4 6 8 10 12-0.2-0.4 y = -0.0357x + 0.0879 R² = 0.1487-0.6-0.8 Initial coefficient of variation

change in coeff of variation No clear tendency in the EM economies 0.6 0.4 0.2 0 0 2 4 6 8 10 12-0.2 y = 0.0148x - 0.1162 R² = 0.0224-0.4-0.6-0.8 Inittial coeff of variation

RCA transition matrix South Africa 1992-2008 deciles 1 2 3 4 5 6 7 8 9 10 1 0.41 0.22 0.16 0.06 0.05 0.02 0.03 0.02 0.01 0.03 2 0.17 0.17 0.23 0.10 0.08 0.04 0.06 0.03 0.06 0.04 3 0.10 0.19 0.14 0.14 0.12 0.07 0.08 0.05 0.06 0.04 4 0.05 0.05 0.19 0.18 0.16 0.14 0.12 0.05 0.04 0.02 5 0.03 0.10 0.14 0.12 0.15 0.17 0.16 0.10 0.03 0.00 6 0.03 0.10 0.03 0.11 0.19 0.15 0.09 0.15 0.09 0.04 7 0.04 0.08 0.10 0.13 0.06 0.15 0.18 0.14 0.08 0.04 8 0.03 0.05 0.03 0.08 0.08 0.13 0.14 0.24 0.12 0.09 9 0.02 0.03 0.01 0.08 0.09 0.08 0.09 0.18 0.26 0.15 10 0.02 0.02 0.01 0.01 0.03 0.04 0.05 0.05 0.26 0.50

RCA mobility index 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60

Measuring dynamics, ergodic distribution South Africa Brazil 0.2 0.2 0.175 0.175 0.15 0.15 0.125 0.125 0.1 0.1 0.075 0.075 0.05 1 2 3 4 5 6 7 8 9 10 0.05 1 2 3 4 5 6 7 8 9 10

Measuring dynamics, ergodic distribution (2) China India 0.2 0.2 0.175 0.175 0.15 0.15 0.125 0.125 0.1 0.1 0.075 0.075 0.05 1 2 3 4 5 6 7 8 9 10 0.05 1 2 3 4 5 6 7 8 9 10

Measuring dynamics, ergodic distribution (3) United States Germany 0.2 0.2 0.175 0.175 0.15 0.15 0.125 0.125 0.1 0.1 0.075 0.075 0.05 1 2 3 4 5 6 7 8 9 10 0.05 1 2 3 4 5 6 7 8 9 10

Measuring dynamics, ergodic distribution (4) Chile Russia 0.2 0.2 0.175 0.175 0.15 0.15 0.125 0.125 0.1 0.1 0.075 0.075 0.05 1 2 3 4 5 6 7 8 9 10 0.05 1 2 3 4 5 6 7 8 9 10

Some further steps? Assessment of RCA mobility by product group (factor intensity, technology or natural resource content) Bringing out the concept of competitiveness and establishing relation to comparative advantage developments Correlation analysis of dynamics indicators and economic development indicators Impact of policies

Thank you!