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BANCA D’ITALIA E U R O S I S T E M A Trade and Wage Inequality, Mirage or Reality? Gian Maria Tomat New Directions in Welfare 2011 6-8 July 2011, OECD,

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Presentation on theme: "BANCA D’ITALIA E U R O S I S T E M A Trade and Wage Inequality, Mirage or Reality? Gian Maria Tomat New Directions in Welfare 2011 6-8 July 2011, OECD,"— Presentation transcript:

1 BANCA D’ITALIA E U R O S I S T E M A Trade and Wage Inequality, Mirage or Reality? Gian Maria Tomat New Directions in Welfare 2011 6-8 July 2011, OECD, Paris

2 Description of movements of wage inequality during 1980-2000 period in EU15 area. Main data source is the Luxembourg Income Study (LIS). Evidence reviewed in terms of international trade theory. Contents

3 Framework Main framework is the Heckscher-Ohlin (HO) model, with two factors of production: skilled labor and unskilled labor (Bhagwati and Kosters, 1994). In 2x2x2 HO model there exists one to one relation between relative good prices and relative factor prices (Stolper-Samuelson): trade increases wage inequality in skilled labor abundant country. The Stolper-Samuelson theorem can be reversed in the “augmented” HO model, as a consequence of economies of scale in differentiated product industries (Helpman and Krugman, 1985).

4 EU15 Trade/GDP ratio increases from 53.2 to 70.7 per cent in 1980-2000 period. Intra EU15 merchandise trade is about 60 per cent throughout 1990-2000 period. Share of commodity imports increases from 10.9 to 13.8 per cent for Asia and from 9.7 to 11.5 per cent for Europe extra EU15. Share of commodity exports increases from 7 to 7.5 per cent for Asia and from 10.7 to 11.9 per cent for Europe extra EU15. Trade Facts

5 Share of Commodity Imports by World Area

6 Share of Commodity Exports by World Area

7 The Data LIS, Income survey data for EU15 countries in waves I-V, years 1980-2000. OECD, National accounts statistics for EU15 countries, years 1980-2000. Eurostat, Purchasing power parities (PPPs) for EU15 countries, EKS PPPs for year 2000. Eurostat, Demographic statistics, years 1980-2000.

8 LIS unit of analysis is the individual, income variable is gross wage (excluding employer’s social security contributions and taxes and including employee’s social security contributions and taxes). Nominal values converted in constant 2000 prices, using OECD household final consumption deflators, for each EU15 country in sample in LIS waves I-V. Constant 2000 values in units of national currencies converted in 2000 EKS EU15 prices, with Eurostat EU15 EKS PPPs for year 2000. Definition of Income Measure

9 Conversion of sampling weights of each country survey to EU15 population weights in each LIS wave I-V, with Eurostat demographic statistics. Sample restricted to male population in 25-54 age range and not self employed, in order to obtain comparable full-year, full-time equivalent observations. Type I Winsorization, with bottom and top thresholds equal to 1 per cent in the EU15 gross wage distribution of each LIS wave I-V. Construction of EU15 Gross Wage Distribution

10 LIS Sample Population Shares

11 EU15 Average Gross Wages

12

13 Wage Inequality in Europe Wage inequality in year 2000 is greater than in year 1980 in the EU15 distribution: the 90/10 ratio increases from 2.9 to 3.7. Inequality changes are determined by movements in the EU15 distribution around the median: the 90/50 ratio increases from 1.7 to 1.9, the 50/10 ratio increases from 1.7 to 2. Movements at the top of the EU15 distribution are also important: the 95/50 ratio increases from 2 to 2.3, the 99/50 ratio increases from 2.9 to 3.7.

14 Inequality Indexes

15 Gini Coefficient

16 Inequality Decompositions by Country Index decompositions by country show that between component is lower than 20 per cent and within component greater than 80 per cent in 1980-2000 period. According to Variance of Logarithm index the between component declines from 17 per cent in 1980 to 8 per cent in 2000, the within component increases from 83 to 92 per cent. For the Gini index the residual component increases from 36.1 per cent in 1980 to 54.9 per cent in 2000.

17 Human Capital and Wage Inequality Skill level of a person defined along two dimensions: education and experience. Education level defined according to ISCED-97 classification: (i) low – from pre-primary to lower secondary, (ii) medium – from upper secondary to post-secondary and (iii) high – university. Experience level defined according to age: (i) low – 25-34 years, (ii) medium – 35-44 years and (iii) high – 45-54 years.

18 Education and Experience Wage Premiums

19 Inequality Decompositions by Skill Level Index decompositions by education level show that between component is lower than 30 per cent and within component greater than 70 per cent in 1980- 2000 period. According to Variance of Logarithm index the between component declines from 22.3 per cent in 1980 to 14.9 per cent in 2000, the within component increases from 77.7 to 85.1 per cent. For the Gini index the residual component increases from 18.2 per cent in 1980 to 23.8 per cent in 2000.

20 Wage Regressions

21 Conclusions Increase in inequality in 1980-2000 period provides motivation for further research, longer time span and broader income concept are two important extensions (Atkinson, Piketty and Saez, 2011). Interpretation of changes in wage and income inequality over time requires also greater integration between economic growth, trade and labor market theories (OECD, 2011).

22 BANCA D’ITALIA E U R O S I S T E M A


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