Income convergence prospects in Europe: Assessing the role of human capital dynamics Jesus Crespo Cuaresma Miroslava Luchava Havettová Martin Lábaj BRATISLAVA ECONOMIC MEETING June 2012

Structure of the presentation Motivation o Income convergence in Europe: The recent experience An income projection model for Europe o The theoretical setting o Estimation results and the projection model Income convergence prospects in Europe o Setting and assumptions Projection results Conclusions

WEST EU-17 2,531,26-0,071,33 CEEC EU-11 3,514,643,433, CEEC/WEST0,350,360,430,49 Average GDP per capita growth in EU-17 and EU-11 in % and the share of an average GDP per capita in CEEC countries on average GDP per capita in EU-17.

1. Correlation between the logarithm of real GDP per capita in 1995 and the average growth of GDP per capita ( ), EU-28.

2. Correlation between the logarithm of real GDP per capita in 1995 and the average growth of GDP per capita ( ), EU-28.

3. Correlation between the logarithm of real GDP per capita in 2000 and the average growth of GDP per capita ( ), EU-28.

4. Correlation between the logarithm of real GDP per capita in 2005 and the average growth of GDP per capita ( ), EU-28.

EU-11EU-17EU-28 log y Observations R2R log y ** *** Observations R2R log y ** Observations R2R log y * *** Observations R2R Beta convergence in Europe

An income projection model for Europe The theoretical setting: Standard aggregate production function with heterogeneous labour input: Rewriting the equation in growth rates implies:

In the spirit of the Nelson-Phelps paradigm (Nelson and Phelps, 1966; Benhabib and Spiegel, 1994; Lutz et al., 2008) we assume that the role of education also plays the role through its effect on innovation and technology adoption Total factor productivity depends on: a) the distance to the technology frontier b) the technology innovation potential of the economy c) the technology adoption potential

Database Panel data for 32 European countries for the period 1970 – 2010, with growth rates defined over 5-year non- overlapping intervals The data on income per capita and total GDP – from the Penn World Table 7.0 Physical capital stocks – estimated using PIM (investment rates from PWT 7.0) with 6 % depreciation rate The data on population by age and educational attainment level – IIASA-VID dataset

IIASA - International Institute for Applied Systems Analysis – World population program Education, Reconstruction and Projections Reconstruction of Populations by Age, Sex and Level of Educational Attainment for 120 Countries for Using Demographic Back-Projection Methods IIASA World Population Program and Vienna Institute of Demography (VID) Anne Goujon Samir K.C. Wolfgang Lutz Warren Sanderson IIASA World Population Program Vienna Institute of Correspondence and requests should be addressed to Anne Goujon or Samir K.C. Anne GoujonSamir K.C.

Structure by age, sex, and level of education for South Africa for the year 2000

Projected structure for South Africa for the year 2050

Panel estimates Estimation results and the projection model

An income projections EU-11 (CEEC)and EU-17 (WEST) regions over the period We design different simple scenarios for each one of the main drivers of economic growth in the model Physical capital accumulation o Medium, Low and High scenario Human capital accumulation o Constant Attainment scenario and Global Education Trend scenario Global shocks in income growth o Constant scenario and Trend scenario Since there are 12 possible scenarios for each region, this results in 144 possible income per capita scenarios for the 28 European countries in our sample

Kernel density of ratio of average income per capita in EM-11 to average income per capita in EU-17 based on projections for all scenarios

Share of simulations where the country attains at least 75% of average income per capita in EU-17, by projection year

Kernel density of ratio of average income per capita in EM-11 to average income per capita in EU-17 in the projection year 2050: Benchmark scenario and scenarios based on human capital advantage/disadvantage for EM-11

Increase in convergence probability from human capital gains versus income per capita in 2010 for EM-11 countries

Concluding remarks We have computed several income convergence scenarios in Europe with a concentration on human capital dynamics Our results indicate that improvements in human capital contribute significantly to the income convergence potential of European emerging economies Convergence over the longer-period, bi-modal structure and still great variation among the EU-11 countries

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