Simulating Poverty in Europe : The Potential Contributions of Employment and Education to Reducing Poverty and Social Exclusion by 2020
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World Bank, Washington, DC
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This paper sheds light on the impact of
improving employment and education conditions on poverty and
social exclusion indicators. More specifically, it answers
the following question: Will achieving the Europe 2020
national targets on employment and education lead countries
to achieve the Europe 2020 poverty and social exclusion
target with no other policy interventions? The paper
presents a simple partial equilibrium model that is flexible
enough to be implemented in a number of different settings
and uses widely available household survey data. The
simulation model analyzes poverty and social exclusion
outcomes in response to changes in education completion
rates and employment rates. The model is applied to ten of
the European Union's new Member States -- Bulgaria, the
Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland,
Romania, Slovakia, and Slovenia -- and the model's
performance is evaluated through a validation exercise. The
Europe 2020 national employment targets are ambitious in
many of the new Member States, given historical employment
patterns in the countries. Especially in light of the slow
and uncertain recovery, labor markets remain weak and
employment rates in 2020 could fall short of rates targeted
by national policy makers. In this eventuality, the poverty
and social exclusion goals may not be reached in many of the
new Member States without additional policy measures.
Palabras clave
ABSOLUTE POVERTY, BENEFICIARIES, CAPITAL INVESTMENTS, CHRONIC ILLNESS, CITIES, COUNTRY LEVEL, DEPENDENT VARIABLE, DEVELOPMENT POLICY, DEVELOPMENT STRATEGY, DISABLED PEOPLE, DISADVANTAGED GROUPS, ECONOMIC GROWTH, EDUCATION LEVEL, EDUCATIONAL ATTAINMENT, EMPLOYMENT GROWTH, EMPLOYMENT PATTERNS, EMPLOYMENT STATUS, EQUILIBRIUM, ESTIMATED COEFFICIENTS, EXPLAINING CHANGES, EXPLANATORY VARIABLES, FAMILY LABOR, FINANCIAL CRISIS, FORECASTS, GROWTH RATE, GROWTH RATES, HIGH EMPLOYMENT, HIGH GROWTH, HOSPITALS, HOUSEHOLD BUDGET, HOUSEHOLD INCOME, HOUSEHOLD SIZE, HOUSEHOLD SURVEY, HUMAN DEVELOPMENT, IMMIGRANTS, IMPACT ON POVERTY, INCOME, INCOME DATA, INCOME DISTRIBUTION, INCOME DISTRIBUTIONS, INCOME INEQUALITY, INCOME POVERTY, INCOME TRANSFERS, INDEPENDENT VARIABLES, INDEXES, INDICATORS OF POVERTY, INEQUALITY, INNOVATION, INSURANCE, LABOR FORCE, LABOR MARKET, LABOR MARKET INDICATORS, LABOR MARKETS, OLD AGE, OLDER WORKERS, OUTCOME INDICATORS, PER CAPITA GROWTH, PERSISTENT POVERTY, POLICY CHANGE, POLICY INTERVENTIONS, POLICY MAKERS, POLICY MEASURES, POLICY REFORMS, POLICY RESEARCH, POOR, POOR PEOPLE, POVERTY IMPACTS, POVERTY INCIDENCE, POVERTY INDICATORS, POVERTY LEVELS, POVERTY LINE, POVERTY POVERTY, POVERTY RATE, POVERTY RATES, POVERTY REDUCTION, POVERTY THRESHOLD, PRIVATE TRANSFERS, PROBABILITY, REDUCING POVERTY, REFORM PROGRAMS, RELATIVE POVERTY LINE, RETIREMENT, RURAL, RURAL AREAS, SECOND ROUND EFFECTS, SELECTION BIAS, SHARP REDUCTION, SIGNIFICANT IMPACT, SOCIAL ASSISTANCE, SOCIAL BENEFITS, SOCIAL INCLUSION, SOCIAL PROGRAMS, SOCIAL PROTECTION, TARGETING, UNEMPLOYED, UNEMPLOYMENT, UNEMPLOYMENT BENEFITS, WAGES