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What Can We Know about the World’s Future?: Long-term Assessment of SocioEconomic Development Mikhail Dmitriev Center for Strategic Research Moscow, 13 October 2006 ABOUT THE PROJECT These are the very preliminary findings of the Center for Strategic Research on global long-term development trends This project is designed as a policy oriented empirical research, rather than a theoretical study 2 Bird’s Eye View on Economic Growth -10,000 -5,000 Source: Charles Jones 0 2,000 5,000 3 Economic Growth Before the Industrial Revolution • Wages in Athens in 328 B.C. were roughly the same as in Britain in 15th century • Wages in Ancient Rome of Diocletian in the year 302 A.D. were at least as high as in France at the eve of the French Revolution in 1790 • Real wage in England was nearly unchanged from its level in 1300 4 Economic Growth Before the Industrial Revolution Per Capita Consumption 0 0 0 -1 19 00 17 00 15 00 13 00 11 00 85 0 20 0 -2 50 600 550 500 450 400 350 300 250 200 -1 00 0 600 550 500 450 400 350 300 250 200 1990 US Dollars 1990 US Dollars Per Capita Consumption Year 0 5 -2 0 0 2 0 5 8 0 0 11 0 0 13 0 0 15 0 0 17 0 0 19 Year Source: Charles Jones 5 Economic Growth Over the Very Long Run • Endogenous growth theoretical framework implies that modern economic growth may be a temporary deviation from the static growth pattern • Some of the models suggest that fast economic growth may come to a halt by the beginning of the next century 6 Economic Growth in the 20th Century and Beyond Source: Charles Jones 7 Economic Growth During Industrial Revolution • Industrial revolution caused economic divergence of the world • Repercussions of such divergence could still have been observed in the second half of the 20th century 8 World Income Distribution Source: Charles Jones 9 Divergence and Predictability • Divergence makes long-term global development less predictable • In divergence phase the outcome of global development is decided mainly by the fast growing frontier economies • Anything beyond the productivity frontier is difficult to predict from the evidence of the past 10 Convergence and Modern Growth • Initial economic divergence during Industrial Revolution created vast convergence opportunities • These opportunities now come into being at a global scale 11 Global Income Distribution since 1960 0.7 0.6 0.5 1960 1970 1980 1990 2000 0.4 0.3 0.2 0.1 0 100 1000 10000 Source: Center for Strategic Research 100000 12 Convergence and Modern Growth • Convergence makes long-term global development more predictable • During convergence the outcome of global development is determined to much extend by economies which are catching up • In the modern world over two thirds of incremental value added is created deep inside the productivity frontier (China alone is creating twice as much 13 incremental value added as the US) Convergence and Predictability • Socio-economic development inside the frontier is easier to predict from the past experience • The long-term progress of frontier economies is still difficult to predict but they are mature and less dynamic than in the past • In the next two decades many of them may not necessarily go too far beyond the modern frontier 14 Convergence and Predictability Luxemburg Russia I GDPppp USA, Norway Russia II Russia II Portugal Mexico Source: Vladimir Mau 15 Convergence and Predictability For the time being, world may become a more predictable place 16 Socio-Economic indicators Indicators 1 Political rights 2 Civil liberties 3 Voice and accountability 4 Political instability and violence 5 Government effectiveness 6 Regulatory burden 7 Rule of law 8 Graft 9 Property rights index 10 Business regulation index 11 Corruption 12 Bureaucratic delays 13 Tax compliance 14 Log of infant mortality 15 Log of school attainment 16 Infrastructure quality 17 Transfers and subsidies/GDP 18 Government consumption/GDP 19 SOE index Form of realtionship to GDP Regression with time effects Linear regression Linear regression Source Barro “Determinants of democracy” Roumeen Islam and Montenegro “What determines the quality of institutions” La Porta “Quality of governance” 17 Socio-Economic indicators Indicators 20 21 Government enterprises and investment as a percentage of total investment 23 Top marginal tax rate 24 Size of Government 25 Legal Structure and Security of Property Rights 26 Average annual growth of the money supply in the last five years minus average annual growth of real GDP in the last ten years Standard inflation variability in the last five years 28 Standard inflation variability in the last five years 29 Recent inflation rate, Freedom to own foreign currency bank accounts domestically and abroad Access to Sound Money 30 Source General government consumption spending as a percentage of total consumption Transfers and subsidies as a percentage of GDP 22 27 Form realtionship to GDP Регрессия с распределенными лагами, наши расчеты База данных с сайта Economic Freedom of the World 18 Socio-Economic indicators Indicators 20 23 General government consumption spending as a percentage of total Transfers and subsidies as a percentage consumption of GDP Government enterprises and investment as a percentage of total investment Top marginal tax rate 24 Size of Government 25 Legal Structure and Security of Property Rights Average annual growth of the money 21 22 26 27 28 29 30 Form realtionship to GDP Regression with time effects Source Economic Freedom of the World supply in the last five years minus average Standard inflation variability thelast lastten five annual growth of real GDP ininthe years Standard inflation variability in the last five years Recent inflation rate, Freedom to own foreign currency bank accounts Access to Sound Money domestically and abroad Indicators 31 Taxes on international trade 32 Regulatory trade barriers 33 34 Actual size of trade sector compared to expected Differencesize between official exchange rate 35 and black market rate International capital market controls 36 Freedom to Trade Internationally 37 Credit Market Regulations 38 Labor Market Regulations 39 Business Regulations 40 Regulation of Credit, Labor, and Business Form of realtionship to GDP Source 19 Socio-Economic indicators Indicators 41 Average years of primary schooling 42 Average years of total schooling 43 Index Gini 44 Fractionalization of GDP 45 Corruption 46 47 Share of slum dwellers in urban population CO2emission, 48 Waterpollution 49 HIV 50 Malaria 51 Tuberculosis 52 Global Insight risk ratings 53 Poverty headcount 54 Poverty headcount in percent of total population Number of terrorist attacks 55 56 Genocide and other indicatiors of political violence Form of realtionship to GDP Linear regression Source Barro-Lee CSR Regression with thresholds Nonlinear regression Regression with thresholds Regression with thresholds Regression with nonlinear effects Regression with thresholds Transparency International, CSR UN-Habitat World Development Indicators, CSR Global Insight, CSR Abadie “Poverty, Political Freedom and the Roots of Terrorism” Peace and Conflict biannual Reports, 20 Socio-Economic indicators • All in all, we considered about 100 different economic, social, and political indicators • They cover a broad array of issues, including: • • • • • • • The state of public and private institutions Public finance Business and financial risks Trade openness Political system and political stability Health, education, and environment Poverty, and social exclusion 21 Socio-Economic indicators • Almost all indicators from our sample have a strong statistical relationship to GDP per capita • Some of these indicators have a high probability to stay within certain value range below (above) certain GDP thresholds 22 Socio-Economic indicators Political Rights 8 7 6 5 4 3 2 1 0 0 5000 10000 15000 Political rights 20000 25000 Полиномиальный (Political rights) 30000 35000 40000 23 Socio-Economic indicators Government Effectiveness 3.00 2.00 1.00 0.00 0 5000 10000 15000 20000 25000 30000 35000 40000 -1.00 -2.00 -3.00 Government Effectiveness Полиномиальный (Government Effectiveness) 24 Socio-Economic indicators Corruption 3.00 2.50 2.00 1.50 1.00 0.50 0.00 0 5000 10000 15000 20000 25000 30000 35000 40000 -0.50 -1.00 -1.50 -2.00 Control of Corruption Полиномиальный (Control of Corruption) 25 Socio-Economic indicators Freedom to Trade Internationally 12.0 10.0 8.0 6.0 4.0 2.0 0.0 0 5000 10000 15000 Freedom to Trade Internationally 20000 25000 30000 35000 40000 Полиномиальный (Freedom to Trade Internationally) 26 Socio-Economic indicators Global Insight Overall Country Risk 6 5 4 3 OVERRISK OVERRISKF 2 1 0 0 10000 20000 30000 40000 50000 GDPPC 27 Socio-Economic indicators Deaths in Military Conflicts 7 6 5 4 3 2 1 0 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 Lg(number of victims) 28 Socio-Economic indicators Water Pollution .024 WATERPOLLUTIONPC .020 .016 .012 .008 .004 .000 0 20000 40000 60000 GDPPC 29 Socio-Economic indicators Cases of Tuberculosis 1000 TUBERCULOSIS 800 600 400 200 0 0 20000 40000 60000 80000 GDPPC 30 Global GDP Growth Scenario Density, Per Capita GDP on PPP 0.7 0.6 0.5 2000 2010 2020 2030 0.4 0.3 0.2 0.1 0 100 1000 10000 100000 31 Global GDP Growth Scenario • Our scenario of global economic growth, as well as other available scenarios (Goldman Sachs, BP, Global Insight), demonstrate rapid conditional convergence • Hence, when we project the indicators from our sample, they tend to converge over time towards developed societies, notwithstanding of growth scenario we use 32 Socio-Economic Projections Political Rights 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 33 Socio-Economic Projections Civil Liberties 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 34 Socio-Economic Projections Political Instability 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 35 Socio-Economic Projections Government Effectiveness 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 36 Socio-Economic Projections Regulatory Burden 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 37 Socio-Economic Projections Rule of Law 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.8-1.0 0.6-0.8 2020 2030 38 Socio-Economic Projections Graft (Corruption) 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 39 Socio-Economic Projections Global Insight Overall Country Risk 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 40 Socio-Economic Projections Global Insight Economic Risk 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 41 Socio-Economic Projections Global Insight Political Risk 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 42 Projections for Africa Political Rights 0.6 0.5 0.4 0.3 0.2 0.1 0 0-0.2 0.2-0.4 2000 0.4-0.6 2010 0.6-0.8 2020 0.8-1.0 2030 43 Endogenuity Problem i • Strong endogenous effects mean that the direction of causal relationship between our indicators and economic growth remain unclear • Only few successful causality tests are available from economic literature • Whether institutions determine growth, or vice versa, remains unclear • We are not prepared to attack this fundamental problem in our study 44 Endogenuity Problem i • We are trying to avoid this problem by containing our objectives • By convention, we do not intend to predict long-term economic growth • We are only trying to assess, how much economic, social and political transformation could be realistically expected for any given growth scenario 45 Frontier Societies i • The scale of almost all available institutional indicators is normalized to frontier societies • It is meaningless to use these indicators beyond the existing productivity frontier • Over the long run, we can tell little or nothing on what may happen to developed world 46 Major conclusions • Fast economic convergence makes global socio-economic development more predictable over the long run • Our approach allows to reasonably predict socio-economic patterns only deep inside the productivity frontier • Our research framework does not allow to assess: • Long-term economic growth rates even inside the productivity frontier • Long-term socio-economic progress of 47 developed economies Major conclusions • In almost all feasible economic growth scenarios world in 2030 is likely to become much safer, healthier, and even happier place to live in • The world may become much less corrupt, much less violent, and much more democratic, but not necessarily much more environmentally friendly • Business risks worldwide may sharply decline, economies may become more opened and global capital market – much more efficient and penetrating 48 The Next Steps • These are very preliminary findings • Our next steps on technical issues may include: • Extending the pool of socioeconomic indicators • More panel data and tests on timeeffects • Integration of generational value transfers to our research framework 49 The Next Steps • Non-technical steps: •Mapping economic, social, political, and security environment for the regions of the world •Assessment of implications for international trade, capital, and labor markets, global financial and political architecture •Review of implications for Russia 50