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Strategies for Structural Transformation in Countries in South and South-West Asia Bangkok, 6 September 2012 Clovis Freire Economic Affairs Officer Macroeconomic Policy and Development Division (MPDD) Economic and Social Commission for Asia


  1. Strategies for Structural Transformation in Countries in South and South-West Asia Bangkok, 6 September 2012 Clovis Freire Economic Affairs Officer Macroeconomic Policy and Development Division (MPDD) Economic and Social Commission for Asia and the Pacific (ESCAP) Based on:  MPDD Working Paper WP/12/04: Strategies for Structural Transformation in Countries in South and South-West Asia • ESCAP Expert Group Meeting on Inclusive Development and Regional Cooperation in South and South-West Asia, held in New Delhi, 30-31 July 2012 • SSWA: Afghanistan, Bangladesh, Bhutan, India, Iran (Islamic Republic of), Maldives, Nepal, Pakistan, Sri Lanka, and Turkey • Note: references are listed in the in the paper 1

  2. Content  Introduction – structural transformation in SSWA  Development, diversification and productive capacities  Methodology and data  Opportunities for diversification  The role of the State SSW A - Little progress in structural transform ation in the past 4 0 years Share of South and South-West subregion on global production, trade and technology (percentage) Indicator 1970 1980 1990 2000 2008 2009 2010 Population 21.31 22.41 23.84 25.09 25.80 25.87 25.95 Rural population 26.53 27.85 30.15 32.66 34.62 34.84 35.06 GDP 4.27 3.83 3.10 3.09 4.29 4.59 4.48 Manufacturing, value added 3.68 2.86 2.91 2.78 3.74 4.00 4.49 High-technology exports - - 0.17 0.29 0.56 0.83 0.76 Receipts of royalty and license fees - - 0.01 0.10 0.10 0.11 0.07 Scientific and technical journal articles - - 2.23 2.44 4.44 4.66 - Source: Author based on data from the World Bank. 2

  3. Developm ent is associated w ith diversification ( I mbs and Wacziarg, 2003; Carrere et all, 2007; ESCAP, 2011 ) 100,000 Diversification (number of products exported) 10,000 1,000 y = 15.596x 0.5162 R 2 = 0.8064 100 10 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 GDP (Millions US$) Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE) and from the World Bank’s World Development Indicators. More diversified countries face low er com petition (ESCAP, 2011; Hausmann and Hidalgo , 2010) Source: ESCAP (2011), Economic and Social Survey 2011. 3

  4. Theoretical framework (Hausmann and Hidalgo, 2010)  Products require specific combinations of capabilities to be produced  Countries have some capabilities but not others  Countries will produce goods as long as they have all the required capabilities Source: Hidalgo and Hausmann (2009) Method of reflections Hidalgo and Hausmann (2009). The building blocks of economic complexity . Source: Hidalgo and Hausmann (2009) 4

  5. Product complexity Abdon and others (2010): Major Maldives exporters of more 8 6 complex products 4 are high-income 2 0 countries and major Bangladesh exporters of less 8 Percent 6 complex products 4 are low-income 2 0 countries Japan 8 ESCAP (2012): 6 Rich countries 4 2 export products 0 -4 -2 0 2 with a wide range Product complexity (global average=0, sd=1) of complexity Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Product complexity by industry Food and live animals Beverages and tobacco Crude materials, inedible, except fuels 12 12 12 10 10 10 8 8 8 Percent Percent Percent 6 6 6 4 4 4 2 2 2 0 0 0 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) Mineral fuels, lubricants and related materials Animal and vegetable oils, fats and waxes Chemicals and related products 12 12 12 10 10 10 8 8 8 Percent Percent Percent 6 6 6 4 4 4 2 2 2 0 0 0 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) Manufactured goods classified chiefly by materials Machinery and transport equipment Miscellaneous manufactured articles 12 12 12 10 10 10 8 8 8 Percent Percent Percent 6 6 6 4 4 4 2 2 2 0 0 0 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 -4 -3 -2 -1 0 1 2 3 4 How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) How common is the product-mix (Number of countries that export the product) Source: Freire, 2012. 5

  6. Path dependency  C. A. Hidalgo, B. Klinger,A.-L. Barabási,R. Hausmann (2007). The Product Space Conditions the Development of Nations. Source: Hidalgo, C.A., and others (2007) What a country produces today affects what it will be able to produce tomorrow Source: ESCAP (2011). 6

  7. 1990 Pakistan 2000 2009 Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE).  Lin (2012), with Celestin Monga  Six-step procedure to identify and facilitate growth  Governments in developing countries to “identify the list of tradable goods and services that have been produced for about 20 years in dynamically growing countries with similar endowment structures and a per capita income that is about 100% higher than their own.” 7

  8.  Hausmann (2012) • better method to identify the potential industries for diversification is by using the product space and measures of product complexity.  MPDD WP 12/01 uses similar method to identify potential products for diversification in least developed countries taking into consideration the higher export opportunities. Methodology identify the opportunities for countries in SSW A  Identify the products that are more complex and that are nearby in the product space to the existing product-mix of the countries • Calculate product complexity using Method of reflections • Map the structure of the product space • Analyze price incentives (export, import substitution) 8

  9. Data  Trade data disaggregated at 6-digit level of HS 2002  Products are also differentiated based on their unit value Source: Author based on data from COMTRADE.  43,293 products in 2010 code = 6-digit (HS) + 1digit (quantity unit code) + 1 digit (unit value range) Map of potential new products Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 9

  10. Map of potential new products Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Top five industries w ith higher percentage of potential new products Afghanistan Bangladesh Bhutan India Iran (Islamic Republic of) 18 20 20 22 21 26 25 24 25 24 7 14 10 8 9 23 18 13 16 5 21 8 20 8 23 8 6 25 7 24 Maldives Nepal Pakistan Sri Lanka Turkey 18 19 21 22 23 23 23 23 24 25 8 8 9 8 23 14 9 20 11 24 7 26 8 6 6 7 8 30 26 21 BASE METALS CHEMICALS MACHINERY & ELECTRICAL EQUIP. MISCELLANEOUS MANUFACTURING OPTICAL, PHOTO, WATCHES, MUSICAL INSTR. PLASTIC & RUBBER TEXTILES OTHER Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 10

  11. Dem and Effects Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Dem and Effects Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 11

  12. Dem and Effects Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Dem and Effects Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 12

  13. Dem and Effects Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). The Role of Governm ent 13

  14. Facilitate the creation of new private sector activities that increase the productive capacity of the economy by supporting of both the emulation and innovation strategies. Balance depends on the level of diversification. 2,500 AFG NPL Number of potential new products IRN BGD 2,000 (above 80% probability) LKA MDV PAK 1,500 BTN 1,000 500 IND TUR 0 0 5,000 10,000 15,000 20,000 Number of existing products Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Percentage of new products w ith above country’s average product com plexity 100% Percentage of potential new products with TUR 90% IND above country's average complexity 80% PAK LKA IRN 70% BGD AFG NPL 60% MDV 50% BTN 40% 30% 20% 10% 0% 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 Number of existing products Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 14

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