Bloomberg ranking of Drivers and Disrupters countries

Source

Methodology and Rankings

The Drivers and Disrupters Report evaluates economies on two sets of metrics. One captures the drivers of development, while the other captures exposure to the disruptive forces creating new risks and opportunities in the global economy.

EconomyDrivers
Rank
ScoreDisrupters
Rank
Score
Sweden172.9380.8
Switzerland272.8874.2
Denmark370.0576.6
China469.65059.0
Australia569.4284.5
United Kingdom669.32069.0
Netherlands769.21372.9
Israel869.1675.2
Finland969.0477.5
Ireland1068.84459.9
New Zealand1168.4186.8
Germany1268.31073.2
Norway1367.9974.2
South Korea1467.51572.1
Canada1567.13861.1
Luxembourg1666.81472.7
United States1766.62765.9
Singapore1864.4774.4
France1964.01970.1
Hong Kong2063.73463.8
Austria2163.51871.0
Belgium2263.43064.5
Taiwan2363.11671.8
Japan2462.92168.5
Czech Republic2562.63264.3
Malaysia2662.44360.0
Iceland2762.12267.9
Spain2861.63363.9
Georgia2961.55258.1
Estonia3060.81771.6
Panama3160.57149.2
Bahrain3259.88443.4
Botswana3359.66850.1
Chile3458.24060.7
United Arab Emirates3557.74260.0
Thailand3657.72666.2
Italy3757.43662.1
Indonesia3857.36650.3
South Africa3956.78741.3
Turkey4056.66053.0
Oman4156.56252.7
Portugal4256.42865.4
India4356.28046.4
Poland4455.71173.2
Slovenia4555.62567.0
Tanzania4655.410033.9
Hungary4755.34659.3
Malta4855.2
Peru4955.16451.0
Bulgaria5055.13761.3
Morocco5155.15457.5
Cyprus5254.65855.9
Mexico5354.49437.2
Saudi Arabia5454.07049.4
Nicaragua5553.79040.6
Vietnam5653.57349.1
Philippines5753.35954.0
Slovak Republic5853.24759.3
Colombia5952.75158.9
Mauritius6052.04859.2
Kenya6151.99635.9
Latvia6251.82367.8
Algeria6351.69140.3
Serbia6451.35358.0
Sri Lanka6551.38343.8
Costa Rica6651.25556.6
Kazakhstan6751.21273.2
Romania6851.03563.2
Zambia6950.99934.3
Croatia7050.63164.4
Uzbekistan7150.67747.6
Albania7250.54959.0
Uganda7350.310430.1
Jordan7449.66352.3
Gabon7549.610133.7
Nepal7649.09339.2
Paraguay7748.97648.2
Lithuania7848.63960.9
Cameroon7948.510629.0
Ecuador8048.47847.2
Dominican Republic8148.36950.0
Greece8247.94559.7
Senegal8347.910332.1
Ethiopia8447.811310.2
Uruguay8547.75656.3
Honduras8647.49735.8
Ghana8747.28543.2
Jamaica8847.27249.1
Tunisia8946.87449.0
Kuwait9046.67947.2
Ivory Coast9146.510529.2
Bangladesh9246.010232.7
Cambodia9345.98940.7
Russia9445.32965.4
Guatemala9544.98146.2
Azerbaijan9644.86750.1
El Salvador9744.18642.4
Iran9844.08841.2
Myanmar9943.89239.4
Brazil10043.86152.9
Bosnia and Herzegovina10143.45755.9
Bolivia10242.97548.8
Mali10342.411117.7
Belarus10441.02467.6
Afghanistan10538.810728.9
Argentina10638.66550.9
Pakistan10738.39834.7
Mozambique10837.811027.1
Nigeria10937.310927.6
Ukraine11036.54160.0
Libya11133.69536.5
Egypt11233.58244.8
Angola11331.310827.8
Democratic Republic of the Congo11425.911217.4

Show LessNote: Rankings are based on average score values to the third decimal place. Malta’s disrupter ranking is not displayed due to insufficient data.

Drivers

The drivers consist of a composite gauge of productivity, as well as the projected growth in the labor force, the scale and quality of investment, and a measure of distance from the development frontier.

Weights for these measures in the overall drivers index are set at different levels for high-income and low- and middle-income economies. The weights reflect evidence in the academic literature, as well as empirical analysis by Bloomberg Economics.

The productivity gauge includes six underlying indicators. As with the overall drivers index, weights for these factors reflect separate panel regressions for high-income and low- and middle-income economies.

Productivity

  • EducationU.N. Education Index, years of schooling, five-year averageUNITED NATIONS
  • Macroeconomic StabilityFive-year volatility of headline CPI inflationINTERNATIONAL MONETARY FUND
  • Openness to TradeTrade Logistics Performance Index, 2012-18 AggregateWORLD BANK
  • Financial Markets and InstitutionsFinancial Development Index, five-year averageINTERNATIONAL MONETARY FUND
  • InnovationGlobal Innovation Index, latest innovation output scoreCORNELL INSEAD WIPO
  • Business ClimateWorld Bank’s Ease of doing business indexWORLD BANK
  • GovernanceWorld Governance Indicators Government Effectiveness IndexWORLD BANK

Income Gap

  • Real GDP per capita, percentage of distance from frontierINTERNATIONAL MONETARY FUND

Investment

  • Composite: Gross domestic investment, percentage of GDP, five-year average; Investment Freedom index, latest score; gross government debt, percentage of GDP, five-year averageINTERNATIONAL MONETARY FUND; HERITAGE FOUNDATION

Labor Force Growth

  • Population growth through 2030, men and women age 15-64UNITED NATIONS; BLOOMBERG ECONOMICS INTERPOLATION

Disrupters

Data sources for tracking economies’ exposure to disruptive forces are set out in the table below.

Populism

  • MobilityIntergenerational mobility scoreWORLD BANK
  • InequalityIncome share of the bottom 40%WORLD BANK
  • Economic InsecurityUnemployment rate, change since global financial crisis; labor force participation, latest; projected population change, ages 15-24 in 2015-30WORLD BANK, UNITED NATIONS
  • Trade25-year change in the trade balance as a percentage of GDPWORLD BANK
  • Immigration25-year change in the international migrant share of the populationWORLD BANK
  • Political InsecurityWorld Governance Indicators Political Stability & Absence of Violence scoreWORLD BANK
  • Political RepresentationWorld Governance Indicators Voice and Accountability scoreWORLD BANK

Protectionism

  • Trade OpennessExports and imports as percentage of GDP; Global value chain participation indexWORLD BANK, BLOOMBERG ECONOMICS CALCULATIONS BASED ON THE UNCTAD-EORA GLOBAL VALUE CHAIN DATABASE
  • Trade ComplexityEconomic Complexity IndexSIMOES AND HIDALGO: THE ECONOMIC COMPLEXITY OBSERVATORY
  • Trade War ExposureShare of value added exposed to U.S.-China, the U.K., U.S. auto imports, and U.S.-Mexico trade; trade balance with the U.S.; trade uncertainty indexBLOOMBERG ECONOMICS CALCULATIONS BASED ON THE OECD TIVA DATABASE; UNITED NATIONS; AHIR, BLOOM & FURCERI
  • Existing Tariff BarriersAverage percentage of applied tariff rate, all productsWORLD BANK
  • Existing Non-Tariff BarriersServices Trade Restrictiveness IndexWORLD BANK

Automation

  • Exposure to RoutinizationExposure ScoreINTERNATIONAL MONETARY FUND (DAS AND HILGENSTOCK)
  • Labor Force QualityTotal Workforce Index rankMANPOWERGROUP
  • AgingProjected old-age dependency ratio in 2030UNITED NATIONS
  • InequalityBottom 40% share of incomeWORLD BANK
  • Social ProtectionComposite: total spending on the labor market and training (high-income economies only); total social protection spending percentage of GDP (all economies)OECD, INTERNATIONAL LABOUR ORGANIZATION
  • Higher EducationProjected total tertiary education, percentage of population aged 15-64, in 2030BARRO-LEE EDUCATIONAL ATTAINMENT DATASET

Digitization

  • Internet infrastructureMobile and fixed broadband speeds; percentage of people using the Internet; mobile and fixed broadband subscriptions per capitaSPEEDTEST GLOBAL INDEX (OOKLA), INTERNATIONAL TELECOMMUNICATION UNION
  • Consumer EngagementShare of population older than 15 that used the internet to pay bills or make a purchase in past year; total number of active usersWORLD BANK, UNITED NATIONS, INTERNATIONAL TELECOMMUNICATION UNION
  • Business EngagementICT services as percentage of intermediate manufacturing consumption; Global value chain-participation index; World Bank Digital Adoption Index: BusinessWORLD INPUT OUTPUT DATABASE, UNCTAD-EORA GLOBAL VALUE CHAIN DATABASE, WORLD BANK
  • Government EngagementWorld Bank Digital Adoption Index: GovernmentWORLD BANK

Climate Change Component

  • Climate Change Vulnerability IndexNOTRE DAME GLOBAL ADAPTATION INITIATIVE

Deriving the scores

To build the composite series for both drivers and disrupters, we first score the economies on the underlying indicators, using the min-max approach. This transforms the data for the separate series to a common scale of zero to 100, allowing us to take a weighted average of the components. Winsorization limits distortion of the scores caused by extreme values.

For occasional missing data points, we impute scores, based on alternative sources of data or—where those are unavailable—assume that a economy’s scores are in line with the average for the available indicators.