SEWING SUCCESS: EMPLOYMENT AND WAGES OF THE END OF THE MULTI- FIBRE ARRANGEMENT

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Transcription:

1 SEWING SUCCESS: EMPLOYMENT AND WAGES OF THE END OF THE MULTI- FIBRE ARRANGEMENT

Motivation Apparel and Poverty 70% of world apparel exports came from low income countries in 2008 Apparel provides entry to formal employment for the unskilled, the poor and women The Multi-fibre Arrangement (MFA) was a Global System of Quotas Controlled apparel and textile trade Phased out with final end in December 2004 Implications of the MFA end Reallocation of production across countries Increase in exports Decrease in apparel prices

Characteristics of the Apparel Industry (T&G) In nearly all countries, most workers in apparel sector are women Vertically Integrated (Value Chains) Buyer Driven Good Jobs Higher wages than alternative (agriculture) Better working conditions than alternatives Gateway for women into manufacturing Very Wage Sensitive

60% 50% The T&C sector employs a large share of unskilled workers and Share of unskilled production workers T&C women 40% 30% 20% 10% 0% Turkey Bangladesh Morocco Pakistan Egypt 70% 60% 50% Female intensity is larger for firms in the textile and clothing sectors compare to the overall average. Source: Enterprise Surveys 40% 30% 20% 10% 0% Bangladesh Pakistan Morocco Tukey Mexico Egypt Source: Enterprise Surveys.

Azerbaij Mauritiu M ongolia Kazakhst Bulgaria Bot swana M ac e do n i Uk r aine Albania J ord a n Per u Ecuador Lat via Bolivia L ith ua ni Par aguay Czech Re G uyana Tr inidad Chile Saint Vi Ar gent in E sto nia Bra zil IMalaysia r an, I s Cr o atia Panam a South Af Swazilan S lo v en ia M alta Andor r a Cyprus Isr a el Austr ali Ireland B elarus Swed en J ap an Luxem bou Switzerl I celand Nor way The sector is very wage sensitive, but wages explain only 30 percent of export variation Fitted values Log Change in Total Apparel Exp 1.5 1 China Cambodia Spain.5 India France Turkey Austria Belgium Netherla Denmark Indonesi Poland United K Pakistan Sri Lank Romania 0 Philippi Thailand Portugal Singapor Greece Mexico Hungary -.5 Korea, R Macau, C Hong Kon Taiwan, Canada United S -1-1.5-2 0 2 4 Log Wage MFA

Our Approach Analyze global change in apparel production Identify key countries Use available data to examine employment and wages following the end of the MFA Identify policy implications

Country Selection Nine Countries: South Asia: Bangladesh, India, Sri Lanka, and Pakistan; East Asia and Pacific: Cambodia and Vietnam; Latin America and the Caribbean: Honduras and Mexico; North Africa: Morocco. Criteria for selection: Significance of apparel in overall economy Regional coverage Position in global value chain Data availability China is not included

Methodology and Data Trade data: changes in exports and unit prices Household and Labor Force Surveys Wage premia in apparel Male-female wage differentials Working conditions Firm-level and Industry-level data Expansion/contraction of industry (employment) Evidence of change in industry structure Vertical Integration Shifts between textile and apparel Change in female intensity (demand for women)

Across Countries Changes Increased total exports: from US$41.4 billion in 2004 to US$58.7 billion in 2008 in 9 country studies Significant increase in Bangladesh, Cambodia, India, Vietnam; moderate in Honduras, Morocco, Pakistan and Sri Lanka; decline in Mexico Reallocation of production: increase in market share - Bangladesh, Cambodia, India and Vietnam; decline- Mexico, Honduras and Morocco Decline in apparel prices due to increased global supply; highly cost-competitive exports from China

Within Country Changes Employment changes over 2004-2008 : Increased: Bangladesh - 40%, Cambodia - 20%, India - 48%, Pakistan 8%, Vietnam 50% Declined: Honduras - 3%, Mexico - 35%, Morocco 8%, Sri Lanka - 12% Wage premia changes, in general, coincided with employment changes : Increased in Bangladesh, India, Pakistan, Vietnam Declined in Honduras, Mexico, Morocco, Sri Lanka Only in Cambodia wage premium declined while employment went up Change in value chain position : Upgrading or moved up: Bangladesh, India, Morocco, Pakistan, Sri Lanka, Vietnam No change: Cambodia, Honduras, Mexico

Closing of Female-Male Wage Gap Decrease in wage gap in Bangladesh, Cambodia, India, Pakistan and Sri Lanka (countries that gained after 2004) Increase in wage gap in Honduras and in Vietnam Impact of Female dummy on log wages 2004 2005 2006 2007 2008 2009 Bangladesh -0.373*** 0.158 Cambodia -0.120*** -0.128*** -0.133 *** -0.115** Honduras -0.307*** -0.324** India -0.489** -0.400*** -0.403*** Pakistan -0.721*** -0.473*** -0.630*** Sri Lanka -0.553*** -0.443*** Vietnam -0.138*** -0.135*** -0.215*** Several rounds of household surveys. Preliminary numbers.

increase Employment decline Changes within industry are important for employment limited Sub-Saharan Africa Caribbean/Hondura s Mexico* Romania* Cambodia Indonesia/Pakistan* ** Upgrading substantial * No upgrading within apparel and textile sectors but upgrading to other sectors. ** Upgrading not as substantial as in other cases. *** Upgrading more substantial than in other case. Hong Kong, Korea, Taiwan Malaysia, Singapore Thailand Turkey Sri Lanka Mauritius Tunisia/Morocco** China India Bangladesh Vietnam

Conclusions Export and employment patterns did not necessarily match the predictions Only 30% in export variation explained by wages Upgrading, ownership, domestic policies were important in explaining changes in exports Changes in exports are usually, but not always, good indicators of changes in wages and employment. Wage premia rise in countries that were proactive in adapting to the MFA phase-out (increased their market share), and fall in countries that failed to respond timely to the changing environment. Promoting upgrading seems to be necessary for sustainable competitiveness in the apparel sector but does not necessarily help the poor.

THANK YOU!

Framework: across countries changes Changes in Total Exports Changes in Countries Market Shares Changes in Global Apparel Prices

Framework: within country changes Income can be defined as the product of employment (l), hours (h), and wages (w): income=y=lhw The change in income can therefore be decomposed into changes in each component: % y= % l+ % h+ % w % l capture changes between apparel and other sectors % h represent changes within sector that reflect the evolution of the apparel sector itself % w represent changes in wage levels that can be attributed to different characteristics

Change in Apparel Wage Premia 2004 2005 2006 2007 2008 2009 Bangladesh 0.343*** 1.545*** Cambodia 0.287*** 0.354*** 0.374*** 0.13** Honduras 0.275*** 0.14** India -0.046** -0.124*** 0.084*** Pakistan 0.076*** -0.085*** 0.019 Sri Lanka 0.05*** 0.082** Vietnam -0.340*** -0.092-0.076*** Several rounds of household surveys. Preliminary numbers.

The Apparel Sector and Value Chain

Countries Have Different Positions in the Value Chain Functional Categories Capabilities Country Examples CMT (Assembly) Marginal supplier; low-cost volume production Cambodia, Vietnam, Sub-Saharan Africa, Caribbean, Honduras FOB (OEM) Full Package Provider ODM: Full Package with Design Global Lead Firm Full Package Service Provider Preferred supplier; scale economies in volume production Niche supplier; specialize in specific product areas Strategic supplier; export: high-value, complex products or volume. Brand development (OBM) for domestic market Global brand owners; marketing and retailing Coordinate supply chain and OEM or ODM activities; contract out manufacturing or invest in production in foreign countries Bangladesh, Pakistan, Morocco, Indonesia Sri Lanka, Mexico India, China, Turkey EU-15, USA Hong Kong, Korea, Taiwan (1980); Malaysia, Singapore (1995); Thailand (2010)

Future Work Impact of post MFA changes in the apparel labor and product markets on employment and wage opportunities in other sectors and the overall structure and welfare of the economy Impact of China safeguard removal in 2008 and world financial crisis on wages and employment in global apparel sector How changes in domestic policies affected workers and which policies were the most efficient in improving workers welfare in short