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Dmitry Volchenkov : Work Package 7 “Analysis and Validation of Data from Multi-Level Anticipatory Complex Systems”(UNIBI - Bielefeld University) Workshop "Analytical approaches to financial and economic problems“, Università Politecnica delle Marche in Ancona on September 9-10 2014. How can we save Europe? Integration of databases for forecasting future trends: Maddison historical GDP +Polity IV (Political Regimes) + The World Top income database Forecasting future trends Present Database ? time Forecasting future trends Kalman filter Hypothesis (fitting parameters) Present Forecasting ? Database Training sequence time Real-world databases Many real-world databases are inhomogeneous & incomplete: Real-world databases Many real-world databases are inhomogeneous & incomplete: • The major statistics come after WWII; • The number of states is ever growing; Real-world databases We have to forecast the future development Varying composition Database A Many gaps/ questionable data time Relevant databases Real-world databases Database C Database A Database B time Relevant databases Markov chain model for real-world databases Transitions between states Database C Database A Database B A graph of states time Crisis for Europe as trust hits record low: Is there a common trend for European countries? No common trends for EU if we replay the recent history ▪ Maddison historical GDP data Kalman filter Model equation The Kalman filter (the linear estimation algorithm) operates recursively on streams of noisy input data to produce a statistically optimal estimate of the underlying system state. Stochastic version of Kalman’s filter Annual GDP changes in all countries Markov chain predictions based on the previous history PDF generated over the preliminary forecasts Predicted values are generated w.r.t. PDFs Different “future scenarios” via PDFs: • bandwidths; • left/right bounds; Average over ALL derived scenarios Different scenarios via the PDFs: Smallest bandwidth Play mostly the previous history Larger bandwidth A greater variety of scenarios Bounds on PDFs yes/no for big shocks (wars) - $500/year + $500/year Under the different polices on PDFs, different “historical scenarios” could be modelled. No common trends for EU if we play the previous history SCENARIO #1 SCENARIO #2 High trend High trend Low trend Low trend Economic recovery after the WWII came at different rates in different parts of Europe. Maddison’s database tediously retells us the story about the recovering after the WWII Industrial countries have an edge on competitors if there is no war (GDP variations are limited to ± $500/year) Traditional capital shelters thrive for larger variations Maddison’s database predicts bankruptcy to the countries that remained uninvolved in the global recovery process. To catch up with new tendencies, we have to add more databases Evolution of political Regimes Democracy/Autocracy indices Inequality Top income shares; the largest historical database available concerning the evolution of income inequality Polity IV tells us that • Six criteria are enough to fully describe a governing regime; • These criteria describe a political state- no matter whether this state is presently occupied, or not; • The historical data on governing polices are well documented (no interruptions/almost no “noise”); • It is possible to quantify the difference between political regimes Regulation of chief executive recruitment Unregulated Openness of Executive Recruitment Closed Competitiven ess of Executive Recruitment Unregulated Dual executive designation Transitional Selection Dual executive election Regulated Open Executive constrains Regulation of Participatio n Competitiv eness of participatio n Unlimited Authority Unregulated Unregulated Intermediate Multiple identity Repressed Slight to moderate limitations Sectarian Suppressed Intermediate Substantial limitations Dual hereditary/co mpetitive Factional Restricted Transitional Intermediate Executive Parity Regulated Competitive “Political distance” – the minimal number of political changes (reforms) required to convert the political system of one country into that of another Trends in Governance in 1810 Trends in Governance in 2012 Polity IV tells us that • There should be a positive feedback, reinforcing the multiplication of polities; dN N dt • We witness the very beginning of a chain reaction process (of atomization of the polity landscape) The World Top Income database tells us that There are many inequality metrics The Pareto principle: income follows a power law probability distribution. Vilfredo Pareto → number of people → I’ve used the inverse Pareto-Lorenz coefficient (IPLC) → wealth → The World Top Income database tells us that Parabolic fit(!) If the GDP-gain substantially outmatches/ lags below the mean (red line), it apparently comes at the cost of increasing inequality. The World Top Income database tells us that Parabolic fit(!) If the GDP-gain substantially outmatches/ lags below the mean (red line), it apparently comes at the cost of increasing inequality. The high concentration of capital The high concentration of capital Perhaps, it reflects the fact that the global economy depends upon investments: When the rate of return on capital significantly exceeds the growth rate of the economy, then it logically follows that inherited wealth grows faster than output and income, so that inherited wealth will dominate wealth amassed from a lifetime’s labor by a wide margin, and the concentration of capital will attain extremely high levels (Thomas Piketty, Capital in the Twenty-First Century (2014)) The World Top Income database tells us that ▪ Rapidly rising inequality marks wars/conflicts/ instabilities; ▪ Global synchronization of inequality dynamics; The World Top Income database tells us that ▪ Rapidly rising inequality marks wars/conflicts/ instabilities; ▪ Global synchronization of inequality dynamics; South–East Asia ▪ Hypercompetition in elites destabilizes states; ▪ Instabilities multiply polities; Integration of databases for forecasting future trends define transitions between different governing regimes; defines the graph of governing regimes; Polity IV: 7,563 governance configurations Regulation of chief executive recruitment Unregulated Openness of Executive Recruitment Closed Competitiveness of Executive Recruitment Selection Dual executive election Regulated Open Regulation of Participation Competitiveness of participation Unlimited Authority Unregulated Unregulated Intermediate Multiple identity Repressed Slight to moderate limitations Sectarian Suppressed Unregulated Dual executive designation Transitional Executive constrains Intermediate Substantial limitations Dual hereditary/competit ive Factional Restricted Transitional Intermediate Regulated Competitive Executive Parity + Interruption (foreign occupation) + Interregnum (anarchy) + Transitional = 7,566 “states” 232 configurations have been observed since 1800 "Tajikistan", 2013 "Nepal", 1945 "Korea North", 2013 Foreign interruption "Cuba", 2005 "Libya", 2010 "United States", 2013 "Thailand", 2013 "Korea South", 2013 "Czech Republic", 2013 "Estonia", 2013 New configurations arise from time to time … Historical transition probabilities between 232 configurations observed since 1800 • 17,000 transitions Most transitions between different states happen within the groups of authoritarian states/ presidential republics, while liberal democracies and dictatorships are quite “sticky”. Random walks on the graph of political regimes Graph of governance regimes Each political regime has its own dynamics for GDP and IPLC Process starts from the actual data (GDPPC & IPLC) for 2013 + Averaging over all collected histories Random walks on the graph of political regimes • A common state insists on a common economic and political destiny for its citizens. • However, the actual trends of different economic groups might be statistically inconsistent. Polities proliferation score ▪ Greece vs. Russia Possible splitting of a country is visible as the statistically inconsistent trends. Main factors resulting in multiplying scores: 1. Inequality (stretches bandwidth of boxes); 2. Authoritarian regimes are short-lived, quickly transforming to other modes of authoritarianism, provoking instability Polities proliferation score ▪ Expected number of countries There can be a common European trend if… • if the workforce will be able to migrate freely, • and polities will be able to split without wars. Possible splitting of a country is visible as the statistically inconsistent trends. Germany vs. Greece Back to the City-States? Strong inequality worsens perspectives, authoritarian governance worsens perspectives… USA vs. China IPLC ~ O(GDPPC2) “In slowly growing economies, past wealth naturally takes on disproportionate importance, because it takes only a small flow of new savings to increase the stock of wealth steadily and substantially.” (Thomas Piketty, Capital in the Twenty-First Century (2014)) Battle in Asia, concord in Europe China (red) vs. Indonesia (blue) The future is fraught with surprises Battle in Asia, concord in Europe Germany (dark) vs. Austria (light) Conclusions ▪ In purpose of forecasting, it might be useful to integrate data from many relevant databases; ▪ In the proposed integration model, one database should be continuous, well defined (a graph of states); others would define transitions; ▪ Combined analysis of three databases shows interesting features related to inequality a permanent increase of the number of self governing polities, indicate a possibility common development for a union of European states. many growth, of city-