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structural transformation

China's secret weapon in light manufacturing: Small and Medium Enterprise-oriented "Plug and Play" industrial zones

Vincent Palmade's picture

 

Light manufacturing operations in a Chinese standardized factory building
  Light manufacturing operations in a Chinese standardized factory building
The success of Chinese manufacturing growth in recent decades is indisputable and has irrevocably shifted the global landscape for manufacturing competitiveness. In contrast, manufacturing in Sub -Saharan Africa has failed to deliver broad-based growth and poverty reduction on anything close to the scale as has been observed in East Asia. As countries, such as China and Vietnam, look to upgrade technology and move up the value-chain, there may be an opportunity for Africa to become competitive in the low-technology, labor-intensive light manufacturing sectors and enter the global manufacturing supply chain.

Trade, Employment, and Structural Transformation

Margaret McMillan's picture
  Photo: istockphoto.com

There is a shared sense that globalization has a strong potential to contribute to growth and poverty alleviation.  There are several examples of countries in which integration into the world economy was followed by strong growth and a reduction of poverty, but evidence also indicates that trade opening does not automatically engender growth. The question therefore arises, why the effects of globalization have been so different among countries of the world.

A look at changes in the structure of employment in Latin America and in Asia hints at possible explanations for observed differences in the growth effects of trade.  Since the 1980s, Asia and Latin America have both rapidly integrated into the world economy.  Asia has enjoyed rapid employment and productivity growth, but the consequences for Latin America have been less stellar.

The chart below shows how the pattern of structural change has differed in the two continents. The chart decomposes labor productivity growth in the two regions into three components: (i) a “within” component that is the weighted average of labor productivity growth in each sector of the economy; (ii) a “between” component that captures economy-wide gains (or losses) from the reallocation of labor between sectors with differing levels of labor productivity; and (iii) a “cross” component that measures the gains (or losses) from the reallocation of labor to sectors with above-average (below-average) productivity growth.  The underlying data for the charts come from the Groningen Growth and Development Centre.

Sectoral upgrading a half century later – 2010 is not 1960

Howard Pack's picture

There is an increasing consensus about the need of poorer economies to shift away from low technology, low productivity areas into new product areas, particularly to generate non-commodity exports. The figure below shows the low level of manufactured exports from the poorest region, sub-Saharan Africa (SSF) as well as from Southeast Asia (SAS) compared to other regions. It is this disparity that many have in mind in urging a sectoral transformation. In the 1950s and early ‘60s there was an argument for a “big push” in development premised on export pessimism.

*lcn- Latin America & Caribbean, mea- Middle East & Africa, SAS - Southest Asia, ssf- Sub-Saharan Africa, eap- East Asia & Pacific, and eca- Europe & Central Asia

The emphasis on the big push and balanced growth continued until the 1970s when the success of export oriented countries in Asia such as Korea and Taiwan (China) demonstrated that it was possible to escape  the need to have balanced  internal growth. Annual export growth of 15 percent or more helped to effect a major transformation in many of the newly industrialized Asian nations.  A critical question is whether five decades later this option is still open.

Taking Stock of the Role of Statistics in Economic Development

Vamsee Kanchi's picture

In today’s data-saturated, highly visual and networked world, statistics are used by policymakers, researchers and journalists for just about everything. However, a veritable mix of government officials, economists and statisticians work – often against overwhelming odds - to produce data sets that are, paradoxically, often taken for granted, but also used as gospel in policy discussions.

Earlier this week, the World Bank celebrated the first ‘World Statistics Day,’ where the successes, challenges and future directions for collecting and analyzing economic development-related data were discussed.

The statistics discipline in the economic development field has seen some breakthroughs in the recent past.

Princeton University's Angus Deaton, a panelist at the event, pointed to the 2005 round of the largest international data collection exercise in the world, called the International Comparison Program, which collects internationally comparable price levels. This data set is critical for comparing living standards between countries.

Why ‘Securing Transformation’ matters in development economics

Justin Yifu Lin's picture

In his September 29 speech at Georgetown on ‘Democratizing Development Economics’, World Bank Group President Robert B. Zoellick insisted on the importance of ‘securing transformation’. The new structural economics approach to development, which I have proposed, aims exactly at that objective.

 Photo: © Simone D. McCourtie / World Bank
As I see it, ‘securing transformation’ highlights certain key features in the economic development process: the importance of endowments; different industrial structures atvarious stages of development and various distortions stemming from past, misguided interventions by policymakers whose belief in old structural economics led them to over-estimate governments’ ability to correct market failures.

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