Inclusive growth in Russia: Achievements and Challenges
Ana Revenga
Senior Director Poverty and Equity Global Practice, The World Bank
Moscow, 7 April 2015
Achievements and Challenges Ana Revenga Senior Director Poverty - - PowerPoint PPT Presentation
Inclusive growth in Russia: Achievements and Challenges Ana Revenga Senior Director Poverty and Equity Global Practice, The World Bank Moscow, 7 April 2015 Growth is the main driver of improved economic welfare globally, but the inclusiveness
Moscow, 7 April 2015
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The World Bank uses the Shared Prosperity indicator to monitor both average growth and growth of the lower quintiles of the population in every country Shared Prosperity
globally, with the bottom 40 growing faster than the average in more than 70% of countries for which data is available.
growth rates are very low (under 2%) limiting progress on this goal.
countries, including in Europe and Central Asia, shared prosperity has been spurred by social transfers which may not be sustainable.
Source: World Bank, Global Database for Shared Prosperity
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Shared Prosperity in the Eastern Europe and Central Asia region, circa 2006-2011
Annualized growth in income/consumption, %
Source: World Bank, Global Database for Shared Prosperity
10 20 30 40 50 60 70 80 90 100
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: World Bank staff calculations using data from the RLSM-HSE, 2001-2010
Share of the population whose per capita consumption is equal or higher than US$10/day (2005 PPP)
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Middle-class growth in the BRICs, circa 1980–2010
Source: World Bank, Economic Mobility and the Rise of the Latin American Middle Class, 2013
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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% extreme poor poor vulnerable middle class
Source: World Bank staff calculations using the ECAPOV database. Note: Numbers for Russia based on 2008 Household Budget Survey.
Percentage of population in each economic group by country, circa 2010
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Heterogeneity x
Source: Rosstat and World Bank staff calculations.
Poverty rates by Region in 2013, percent
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Income distribution (share of population with per capita income in US$ PPP per day, percent)
Source: World Bank staff calculations based on RLMS data.
10 20 30 40 50 60 70 80 90 100
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
>50 25-50 10-25 5-10 <5 total 10+
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Contribution to observed inflow into middle class (in percentage)
Source: World Bank staff calculations using data from the RLSM-HSE, 2001-2010
0% 20% 40% 60% 80% 100%
2001-2010 2001-2005 2006-2010
Other income Private transfers Other public transfers Pensions Capital Wage (public) Wage (private) Employment rate Dependency (Old) Dependency (Young)
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60 80 100 120 140 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Year Russia Brazil China India
Source: UN World Population Prospects: The 2012 Revision. Projections after 2010, median variant.
Working age population, BRIC countries
Source: UN World Population
5 10 15 2007 2008 2009 2010 2011 2012 2013 2014 Consumption Gross Fixed Capital Formation Change in inventories Export Import Stat error GDP growth
GDP growth in Russia, contributions, 2007-2014
Source: Russian Statistical Authorities
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Russia Rest of ECA
.05 .1 .15 .2 5 10 15 20 25 30 Distribution of observations Russia Rest of ECA
Source: Enterprise Surveys comprehensive dataset (May 2012)
Russia vs. Rest of ECA
Size distribution of firms based on sales revenue (log)
Russia Rest of ECA
10 15 20 25 10 15 20 25 Linear prediction 95% CI Russia Rest of ECA
Source: Authors' calculations based on Enterprise Surveys comprehensive dataset (May 2012)
Russia vs. Rest of ECA
Age predicts sales revenue (log)
Source: World Bank, Russia Economic report, Sep 2013, based on data from United Nations, Comtrade, retrieved June 12, 2012.
bigger in size and less profitable than relevant comparators in other countries
account for a large fraction of fast growing, innovative firms, have a low probability
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A small number of young private firms (“Gazelles”) have been responsible for most of the job creation in Eastern Europe during 2004-08
Notes: The number above each country represents the average growth rate of employment per year; country groupings refer to advanced, intermediate and late reformers (definition by World Bank, in Back to Work). Source: Back To Work: Growing with Jobs in Europe and Central Asia (2013).
% of all firms and all jobs created
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0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0
Annual employment growth in 2012, %
Annual employment growth in 2012, by region
Source: World Bank, Business Enterprise Survey (BEEPS), 2012
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Source: World Bank, Business Enterprise Survey (BEEPS), 2012
0.0 5.0 10.0 15.0 20.0
0.0 5.0 10.0 15.0 20.0
Annual productivity growth, % Annual employment growth, %
Correlation between productivity growth and employment creation in (selected) Russian regions
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Source: World Bank, Business Enterprise Survey (BEEPS), 2012
Days need to obtain an operating license, by region (2012)
can take between 22 and 82 days, depending on the region.
connection can take between 8 and 227 days depending on the region, compared to 31 days in high income non-OECD countries.
about twice as high in Russian as on average in high income non-OECD countries.
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Source: OECD, Health at a Glance, 2014.
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Sources: OECD, Education at a Glance, 2014; and OECD, Boosting Productivity in Russia Skills, Education and Innovation, 2015.
High level of education… …but of low quality
Educational attainment of 25-64 year-olds, 2011 Share of younger and older adults scoring at literacy proficiency level 4/5 (highest levels on the scale), 2012
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Share of SMEs that have admitted to facing difficulties or barriers in finding skilled personnel in the last two years
Source: Demmou, L. and A. Wörgötter (2015), “Boosting Productivity in Russia: Skills, Education and Innovation”, OECD Economics Department Working Papers, No. 1189, OECD Publishing.
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Source: World Bank, Developing Skills for Innovative Growth in the Russian Federation, 2013. Calculations based on PISA scores 2009 (OECD). Note: Regional averages are directly computed from the sample in 44 out of 83 federal subjects. Values in the remaining regions have been estimated using a linear model based on level of education of parents, employment status, occupation and fixed effects at the level of federal districts.
Distribution of PISA reading score (2009), by federal districts
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Sources: Staff calculations based on Rosstat data.
Richer regions tend to allocate more to public health services… … but health outcomes do not seem to improve with higher allocations Need for greater accountability and more efficient use of resources in public service delivery across regions
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