Social Costs of the Asian Economic Crisis Yinglan Tan — Department of Economics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 Faculty Advisor:

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Presentation transcript:

Social Costs of the Asian Economic Crisis Yinglan Tan — Department of Economics, Carnegie Mellon University, Pittsburgh, Pennsylvania Faculty Advisor: Dr Daniele Coen-Pirani (Graduate School of Industrial Administration) Research Question and Significance Few people in the “Crisis Five”, namely Indonesia, Korea, Thailand, Malaysia and Philippines have been untouched by the Asian Economic Crisis which occurred in What is unclear is which groups of people were hit the hardest. It is increasingly important to focus on the distributional impact of crises for policy-makers to cater to the needs of those most adversely affected. Objectives Objectives Results Conclusion Conclusion Income Inequality did not change much Discussion 1.Increases in inequality were generally smaller than anticipated (Reason: High labor mobility, devaluation and composition of job losses.) 2.Gini coefficient remained almost constant except Indonesia and Thailand which dropped significantly (Reason in Indonesia Thailand: higher rural wage workers had higher wage declines, percentage of rural population.) 3.Deterioration of Jobs – vicious cycle of displaced college graduates taking up jobs of high school graduates. 4.Social Income Poverty- reduces social income from the state via public works and income transfers. 5.The tenor of empirical evidence indicates that the emphasis of government policies in time of crisis should be on specific categories of people. Eg. Cash Transfers, Workfare Programs, Unemployment Assistance, Active Labor Market Policies. Acknowledgements: Undergraduate Research Initiative, for funding this study and Dr Daniele Coen-Pirani for insightful advice and his kind guidance. Fig. 1. Aggregate Statistics of the Asian Economic Crisis Quantitatively analyze social costs of the Asian Economic Crisis on different social-economic groups. Analyze the time-series trends of the determinants of poverty. (Employment, Real Wage, Income Distribution, Working hours, Poverty Index) Methodology Methodology Constructed time-series tables and charts, restricting statistical analysis to the “Crisis Five”, Indonesia, Thailand, Korea, Malaysia and Philippines. The datasets were collected mostly from the International Labor Organization and spanned 1990 to Fig. 2. Gini Coefficient, G, measures income inequality in the country and (Most Equal) 0  G  1 (Most Unequal). But Poverty and, Fig. 3. shows that poverty increased in most countries. The rural indicator showed a greater increase than urban generally. Unemployment for the less educated, the middle-aged and certain sectors. Unemployment rate of Korea (by Sector from 1992 to 1999) D1992D1993D1994D1995D1996D1997D1998D1999 Unemployment rate(in %) Services Manufacturing/Construction Primary Industries Fig. 4(a-c) Groups of people most affected are the less educated (a), workers aged 25 to 44 yrs, recent school dropouts, first-time job seekers (b), and workers in the manufacturing construction and service sector. (c) (a) (c) (b) Average wages of Korea (by sector) D1993D1994 D1995 D1996 D1997D1998 D1999 Average monthly wage (in $) Primary Sector Manufacturing /Construction Services Fig. 5 Employment has become less formal in Indonesia Fig. 7 Real Wages were computed using the Consumer Price Index (CPI) Wages in manufacturing and construction showed the most obvious dip. Fig. 6 Hours of work generally dropped from the period of 1997 to Services sector worked less. Fig. 8 Faces of Poverty in Chiangmai, Thailand. We observe an influx of young children into the informal sector. Analyzing the distributional impacts of economic crises is an important and pressing need. Policymakers need to identify those who have been most harmed and the magnitude of that harm. Although there were not large distributional effects (in the sense of changes in the Gini coefficient), but since many people fell below the poverty line the crisis caused pain anyway to many individuals. Future work would entail analyzing household data which could paint a more accurate picture of the facade of poverty. Average Real Wages Working Hours Informality