How to Aim High Conclusions for entrepreneurs and policy makers Conclusions for entrepreneurs how to run with the best Conclusions for policy makers how to support high-impact entrepreneurs Methodology Data Tables for Life cycle Phases and Industry Groups 7813 13
In this report, we are able to draw for the first time on a private data set generously provided by the EY Entrepreneur of the Year contest.
adding to an already impressive body in the field by other institutions from a unique data set.
we also had a unique opportunity to analyze for the first time a data set generously made available by our partner EY.
The data analyzed in this report stem from the most recent survey of program participants along both quantitative and qualitative metrics.
but data availability gave no other choice. In order to make this explicit, we chose a human analogy to describe the different life stages,
and Reinvent Adult Fig. 3. 2. Life stage descriptions for Eoy data set Fig. 3. 3 Number of EOY Contest Companies by Sectors
Painting by Numbers Insights from the World Entrepreneur of the Year contestants This chapter will delve into the rich detail of the Eoy data set,
Median Return on Assets data for Entrepreneur Of The Year participant companies Fig. 4. 3. Marginal 2-year job creation rates for Eoy sample and the US economy
While we lack the data for a proper longitudinal study of those firms (or a wider set of companies to corroborate our findings beyond the Eoy universe),
this is clearly an instance where the quantitative data show only part of the story, with a significant missing part in the qualitative factors of business strategy,
With only 5 and 7 companies in the Traditional and Services categories, respectively, it is hard to draw strong conclusions from data that shows a much higher sales effectiveness (sales/assets) for Traditional highimpact enterprises,
For Traditional companies, it seems that the peer group's operational metrics are already par for course and the winners'differentiation lies outside the quantitative data.
it is clear that the differentiation must come from variables outside the quantitative data and operational metrics
Where the Eoy data can add some intriguing insight however, is on the topic of job creation.
Marginal job creation 34 The Bold Ones High-impact Entrepreneurs Who Transform Industries 35 After an extensive analysis of a data set containing some of the most impressive entrepreneurs
the quantitative data are only part of the story every company is different, and often the key for success lies in the qualitative inputs.
and is currently an adjunct professor at Brandeis University's International Business school. 40 The Bold Ones High-impact Entrepreneurs Who Transform Industries 41 This report draws on data from the participants of the EY 2013
We then eliminated incomplete data entries (a total of 22) and age outliers (a total of 44),
Since the data in the survey for this report only cover a two-year period, this report follows the OECD's definition,
Sector breakdown of industry groups High-impact Entrepreneurs Who Transform Industries 43 Data Tables for Lifecycle Phases
Multiple data sources indicate that European conditions are far from ideal for entrepreneurs and fast-growing companies
In addition to extensive inputs from the Forum's Members, Global Shapers, Young Global Leaders, Network of Global Agenda Councils and leading policy-makers across Europe, the findings in the report have benefitted from data gathered from over 60 structured interviews
the Forum partnered with Research+Data Insights, Junior Achievement-Young Enterprise (JAYE) Europe, and the European Confederation of Young Entrepreneurs (YES) to survey a broad range of Europeans with experience
while data is hard to come by, in recent years the European venture capital segment has seen a number of notable successes such as Supercell and Spotify.
Many European venture capital experts say the sector is stronger than the long-term data indicate. Today
Young Global Leader Building a database and evaluating data with a clearly defined process Google Ventures uses algorithms with data from academic literature or from due diligences.
One important aspect of such a network would be a layer of data, not only on the initiatives themselves,
The best way of doing this is to align on a standard format to systematically publish search fields online to boost the development of platforms that can draw on the data.
Efforts to share governmentowned data intelligently can also help in this respect: the strategy initiated in countries like the United kingdom around datagov (in
which central and local governments offer access to their data on traffic, criminality or available services, for example) and opengov (in
and feedback on policies) have played a positive role in allowing ordinary citizens to regain ownership of their data,
Fostering Innovation-driven Entrepreneurship in Europe 55 Conclusion Over the course of 2013 and 2014, the Forum's Fostering Innovation-driven Entrepreneurship in Europe project has drawn on survey data, structured interviews,
Central and Eastern europe (no EVCA data available on Turkey: Bulgaria, Croatia, Czech republic, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Poland, Romania, Slovakia, Slovenia;
-YE Europe Alumni Research+Data Insights, a Hill+Knowlton Strategies company David Iannelli, President Amber Ott, Senior Account Supervisor YES Dimitris Tsigos, President
the city is pursuing an open-data strategy that uses insights gathered through data analysis and visualization (big data) to provide real-time information,
which real-time data and results are not yet available. 3. Hard connectivity and infrastructure International trade gateway:
Data on food quality was made available via the media. Such a crackdown had an immediate impact on the quality of food,
Looking at publicly available data, Surat recorded 11.5%growth in GDP between 2001 and 2008,
Many city competitiveness metrics include hard-connectivity data on transport, communications and energy. This helps to understand how hard connectivity leads to productivity and to a city's insertion into global value chains.
and allowing for streams of data that simply disappear into daily life. This computing power will digitize nearly everything in society,
and will derive insights from all of the data being generated by interactions among people, and between people and machines.
They need to strike the right balance between using data to create intelligent personal experiences
For example, today an assistant application on a smartphone merges data from highway sensors and a personal calendar to remind users to leave work
Klaus Schwab World Economic Forum Editor Professor Xavier Sala-i-Martín Columbia University Chief Advisor of The Global Competitiveness and Benchmarking Network Full Data Edition
Full Data Edition is published by the World Economic Forum within the framework of The Global Competitiveness
which statistical data are maintained on a separate and independent basis. World Economic Forum Geneva Copyright 2014 by the World Economic Forum All rights reserved.
The Report and an interactive data platform are available at www. weforum. org/gcr. 2014 World Economic Forum The Global Competitiveness Report 2014 2015 iii Partner
Data Presentation 97 2. 1 Country/Economy Profiles 99 How to Read the Country/Economy Profiles...
104 2. 2 Data Tables 393 How to Read the Data Tables...395 Index of Data Tables...
397 Data Tables...399 Technical Notes and Sources 537 About the Authors 547 Contents 2014 World Economic Forum 2014 World Economic Forum The Global Competitiveness Report 2014
2015 v The World Economic Forum's Global Competitiveness and Benchmarking Network is pleased to acknowledge
as well as an extensive section of data tables with global rankings covering over 100 indicators. This Report is one of the flagship publications within the Forum's Global Competitiveness
which provides the foundation data of this Report as well as imparting the results of the Report at the national level.
because internationally comparable data on wages are not available for all countries covered. The thresholds used are shown also in Table1.
DATA SOURCES To measure these concepts, the GCI uses statistical data such as enrollment rates, government debt, budget deficit
These data are obtained from internationally recognized agencies, notably the United nations educational scientific and cultural organization (UNESCO), the International monetary fund (IMF), and the World health organization (WHO).
The descriptions and data sources of all these statistical variables are summarized in the Technical Notes and Sources at the end of this Report.
Furthermore, the GCI uses data from the World Economic Forum's annual Executive Opinion Survey (the Survey) to capture concepts that require a more qualitative assessment or for
which internationally comparable statistical data are not available for the entire set of economies. The Survey process and the statistical treatment of data are described in detail in Chapter 1. 3 of this Report.
COUNTRY COVERAGE This year the Report covers 144 economies. In this edition because of data availability issues, we could not include Benin, Bosnia and herzegovina, Brunei Darussalam, Ecuador, or Liberia.
On the other hand, Tajikistan, which could not be included in the last edition, is reinstated this year. Table 2:
Our data also point to improvements in health and primary education, thanks to a higher primary enrollment rate,
It must be noted that all the data used in our assessment were collected before the most recent developments including the military coup of May 2014 took place.
To some extent this overall ranking improvement is technical and due to the fact that data on tertiary enrollment are no longer available.
our data suggest a steady improvement across a range of indicators, albeit from low levels.
The data used cover the years 2009 through 2013. Further information on these data can be found at http://legacy. intracen. org/appli1/Tradecom/Documents/Tradecompmap-Trade%20performance%20index-Technical%20 Notes-EN. pdf. All
countries that with more than 70 percent of their exports made up of mineral products are considered to be to some extent factor driven.
Countries at the technology frontier are the 10 countries with the highest per capita patenting activity according to Patent Cooperation Treaty data. 23 We have retained the geographical classifications used in past editions of the Report
The groupings in the profiles are based on IMF data, and use the IMF classifications. 24 IMF 2014a.25 World bank 2014.26 Overall,
OECD, and UNDP 2014.27 IMF 2014b.28 The Central bank's bailout of African Bank Investments on August 11, 2014, is reflected not in the EOS data this year,
Available at http://data. worldbank. org/products/wdi. World Economic Forum. 2009. The India Competitiveness Review 2009.
yi 0 1 ln (GCII) ln (yit) i (1) Using World bank GDP purchasing power parity-adjusted data,
Available at http://data. worldbank. org/products/wdi. 2014 World Economic Forum The Global Competitiveness Report 2014 2015 49 1. 1:
The numbering of the indicator matches the numbering of the data tables. The number preceding the period indicates to
To combine these data we first take the ratio of each country's disease incidence rate relative to the highest incidence rate in the whole sample.
Data are normalized then on a 1-to-7 scale. PPP estimates of imports and exports are obtained by taking the product of exports as a percentage of GDP and GDP valued at PPP.
The underlying data are reported in the data tables section (see Tables 10.03,6. 14, and 10.04.
The underlying data are reported in the data tables. 2014 World Economic Forum 2014 World Economic Forum The Global Competitiveness Report 2014 2015 53 CHAPTER 1
Despite this progress, a generalized lack of high-quality, internationally comparable data that would allow countries to fully understand how they fare in these critical areas
Without an improvement in the quality and availability of key data on social and environmental sustainability, countries will continue to face challenges
The lack of data also renders far-reaching quantitative analysis of the topic impossible and makes it difficult to identify channels of influence
Better data would enable countries to make better decisions in their attempt to identify and implement appropriate policies
The lack of data is a challenge that is shared by all the frameworks described above as well as by our sustainable competitiveness assessment
but could not because of the lack of data include access to decent housing and food security.
and to understand the strengths and limitations of these data. More generally, the measures captured here
Although the data in this area are among the most difficult to collect and interpret, it is crucial for a country to manage these resources
because data became available or because improved measurement methodologies were provided. The indicator Baseline water stress replaces Agricultural water intensity.
In the Sustainable Competitiveness exercise, country coverage is driven again by data availability: we are able to cover 113 economies this year,
The country does not report data related to youth unemployment or vulnerable employment; these indicators cannot therefore be assessed.
Given the complexity of the issue at hand and important gaps in data, it must be remembered that this is a work in progress
based on 2012 Households Budget Survey data. In 2012 the relative poverty incidence was equal to 12.7 percent,
What Can the Data say? Journal of Economic growth 8 (2003): 267 99. Barbier, E. 1997.
A New Data Set Measuring Income Inequality. World bank Economic Review 10 (3): 565 91. The Economist. 2014.
2 june 3. Available at http://www. euro. who. int/data/assets/pdf file/0014/251213/Floods-in-the-Balkans,-Situation-Report-no-2-Eng. pdf. World bank. 2012.
and using the actual sample maximum and minimum are corroborated by the statistical distribution of the data,
so as to ensure that the final data are skewed not. In the absence of empirical evidence, the selection of the impact limits (0. 8 1. 2) relies on the best judgment of the authors
Assessing Progress toward Sustainable Competitiveness 80 The Global Competitiveness Report 2014 2015 The data in this Report represent the best available estimates from various national authorities, international agencies,
It is possible that some data will have been revised or updated by the sources after publication.
or that the available data are outdated unreasonably or do not come from a reliable source.
in the case of Executive Opinion Survey data, the full question and associated answers. If necessary, additional information is provided underneath.
World health organization, World Health Statistics 2014 available at http://apps. who. int/gho/data/node. main. 606?
World health organization, World Health Statistics 2014, available at http://apps. who. int/gho/data/node. main. 606?
or most recent This indicator is calculated by CIESIN (Columbia University's Center for International Earth science Information Network) by overlaying the protected area mask on terrestrial biome data from Olson et al.
World Resources Institute, Aqueduct Country and River basin Rankings, December 2013 edition, available at http://www. wri. org/resources/data-sets/aqueduct-country
1) country-level statistical data and reports;(2) values derived from the Organisation of Economic Co-operation
A logarithm transformation is applied to the ratio of these statistics in order to spread the data distribution.
World bank, World Development Indicators database, http://data. worldbank. org (retrieved June 20, 2014) S17 Fish stocks overexploited Fraction of the country's exclusive economic zone with overexploited and collapsed stocks 2011 or most recent The Sea Around Us (SAU) project‘s Stock
A logarithm transformation is applied to these statistics in order to spread the data distribution. Source: Yale Center for Environmental law & Policy (YCELP) and the Center for International Earth science Information Network (CIESIN) at Columbia University, Environmental Performance Index 2014, available at http://epi
This indicator is based on a model that was parameterized by data on aerosol optical depth (AOD) from NASA's MODIS
Population-weighted average exposure values were calculated using population data from the Global Rural Urban Mapping Project (2011) database.
which data sources are scarce or, frequently, nonexistent on a global scale. It helps to capture aspects of a particular domain such as the extent of the skills gap, the level of corruption,
or the intensity of market competition that are more qualitative than hard data can provide.
Thus it is an indispensable complement to the sources of data made available by international organizations and national statistical offices.
A truly unique source of data, the Survey has also long been used by a number of international and nongovernmental organizations, think tanks,
For example, Transparency International has been using the Survey data for the elaboration of their Corruption Perceptions Index and the Bribe Payers Index.
and the International monetary fund (IMF) also refer to the Forum's Survey data in their publications,
or refer to the Survey data. THE SURVEY IN NUMBERS The 2014 edition of the Survey captured the opinions of over 14,000 business leaders in 148 economies between February and June 2014;
because of data issues, out of the 148 economies surveyed, 144 are included in the GCI this year (please see the data treatment section below for further details).
Figure1 presents some key descriptive statistics. The Survey is available in 42 languages, of which 20 are available online (see Table1).
*Following data treatment. See text for details. Based on purchasing power parity estimates. 2014 World Economic Forum The Global Competitiveness Report 2014 2015 87 1. 3:
Furthermore, Bosnia and herzegovina and Ecuador are included not in this edition of the Report because of data quality concerns (see Trend analysis and exceptions below for more detail.
All statistics were computed following the edition of the data. See text for details. Survey edition (s) used for the computation of economy scores:
In parallel, Forum researchers visited statistical offices and ministries in order to gather relevant quantitative data. The report was finalized in November 1979.
therefore been including a mix of proprietary survey data and statistics from international organizations since its very inception.
the Forum decided not to re-weight the data using vignettes because of the limited effectiveness of such a procedure
and to prevent introducing additional noise into the data that occurs with such an approach.
the Global Competitiveness and Benchmarking Network team continues to improve processes to achieve greater data accuracy
DATA TREATMENT AND SCORE COMPUTATION This section details the process whereby individual responses are edited and aggregated in order to produce the scores of each economy on each individual question of the Survey.
and other research projects. 4 Data editing Prior to aggregation, the respondent-level data are subjected to a thorough editing process.
A first series of tests is run to identify and exclude those surveys whose patterns of answers demonstrate a lack of sufficient focus on the part of the respondents.
a multivariate test is applied to the data using the Mahalanobis distance method. This test estimates the probability that an individual survey in a specific country belongs to the sample of that country by comparing the pattern of answers of that survey against the average pattern of answers in the country sample.
This improves the comparability of data across years. 0 20406080100 Sub-saharan africa Middle east, North africa, and Pakistan Latin america and the Caribbean Emerging and Developing Europe Emerging and Developing Asia Commonwealth of independent states Advanced economies0 20406080100 Sub-saharan africa Middle east, North africa,
the average of the responses in the first quarter of 2013 and first quarter of 2014 better aligns the Survey data with many of the data indicators from sources other than the Survey,
which are often year-average data. To calculate the moving average, we use a weighting scheme composed of two overlapping elements.
We therefore carry out an analysis to assess the reliability and consistency of the Survey data over 2014 World Economic Forum 1. 3:
Based on these quantitative and qualitative analyses, the 2014 Survey data collected in Bosnia and herzegovina, Ecuador, and Rwanda deviate significantly from the historical trends,
In the case of Rwanda, we use only the 2013 Survey data in the computation of the Survey scores (see the Exceptions section in Box4.
The Executive Opinion Survey measure, we will continue to investigate the situation over the coming months in an effort to improve the reliability of the Survey data in this country.
Last year, the same analysis resulted in the Survey data of four countries Bosnia and herzegovina, Jordan, Oman,
as an intermediate step toward the re-establishment of the standard computation method, we used a weighted average of the Survey data of 2012 and 2014 for these countries,
We will work closely with the respective Partner Institutes to improve the administration process and the reliability of the data,
CONCLUSION Since 1979, the World Economic Forum has been conducting a survey to gather perception data for its research on competitiveness.
which data sources are scarce or nonexistent. For this reason, and for the integrity of our publication and related research, sampling thoroughness
no past data exist, the weight applied to the 2013 score is wc2013=0 and the weight applied to the 2014 score is wc2013=1. Equation (1) simply is qi, c2013 14=qi, c2014.
which the 2013 data were discarded, we use the Survey data from 2012 instead, and combine them with those of 2014 to compute the scores.
Equation (1) then becomes qi, c2012 2014=wc2012 qi, c2012 wc2014 qi, c2014. Example of score computation For this example
and to one decimal place in the data tables, exact figures are used in all calculations.
and data gathered through the administration of the Survey in past years. 3 In order to reach the required number of surveys in each country (80 for most economies and 300 for the BRICS countries and the United states),
all data in the Key indicators'section are sourced from the April 2014 edition of the International monetary fund (IMF)' s World Economic Outlook (WEO) Database:
Data for Puerto rico are sourced from Puerto rico's national statistics. The chart on the upper right-hand side displays the evolution of GDP per capita at purchasing power parity (PPP) from 1990 through 2013 (or the period for which data are available) for the economy under review (blue line.
The gray line plots the GDP-weighted average of GDP per capita of the group of economies to which the economy under review belongs.
For more information regarding the classification and the data, visit www. imf. org/weo. Data for Puerto rico are not available.
Percent of responses GDP (PPP) per capita (int'l $), 1990 2013 Rank Score out of 144)( 1 7) Note:
For further analysis, the data tables in the following section of the Report provide ranks, values,
ONLINE DATA PORTAL In addition to the analysis presented in this Report, an interactive data platform can be accessed via www. weforum. org/gcr.
The platform offers a number of analytical and visualization tools including sortable rankings, scatter plots, bar charts,
as well as the option of downloading portions of the GCI data set. NOTE 1 The IMF refers to this region as Middle east, North africa, Afghanistan, and Pakistan.
Data Tables The Global Competitiveness Report 2014 2015 395 EXECUTIVE OPINION SURVEY INDICATORS In the tables, indicators derived from the World Economic Forum's Executive Opinion Survey
refer to Chapter 1. 3. How to Read the Data Tables The following pages provide detailed data for all 144 economies included in The Global Competitiveness Report 2014 2015.
The data tables are organized into 13 sections: Key indicators Pillar 1: Institutions Pillar 2: Infrastructure Pillar 3:
Data Tables 406 The Global Competitiveness Report 2014 2015 2014 World Economic Forum 2. 2:
Data Tables 396 The Global Competitiveness Report 2014 2015 OTHER INDICATORS Indicators not derived from the Survey are presented in black bar graphs.
, the period when a majority of the data was collected) follows the description. When the year differs from the base year for a particular economy,
When data are not available or are outdated too, n/a is used in lieu of the rank and the value.
Because of the nature of data, ties between two or more economies are possible. In such cases, shared rankings are indicated accordingly.
ONLINE DATA PORTAL In addition to the analysis presented in this Report, an interactive data platform can be accessed via www. weforum. org/gcr.
The platform offers a number of analytical and visualization tools, including sortable rankings, scatter plots,
as well as the option of downloading portions of the GCI data set. RANK COUNTRY/ECONOMY VALUE 1 United states...
Data Tables 400 The Global Competitiveness Report 2014 2015 2014 World Economic Forum 2. 2:
Data Tables The Global Competitiveness Report 2014 2015 397 Index of Data Tables Key indicators...
Data Tables 398 The Global Competitiveness Report 2014 2015 Pillar 10: Market size...513 10.01 Domestic market size index...
536 2014 World Economic Forum Key indicators Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 United states...
Data Tables 400 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 China...
Data Tables The Global Competitiveness Report 2014 2015 401 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Luxembourg...
Data Tables 402 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 United states...
Data Tables The Global Competitiveness Report 2014 2015 403 2014 World Economic Forum 2014 World Economic Forum Pillar 1 Institutions Data
Data Tables 406 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 407 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 5 7
Data Tables 408 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 1 7
Data Tables The Global Competitiveness Report 2014 2015 409 2014 World Economic Forum 1. 05 Irregular payments and bribes Average score across the five
Data Tables 410 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 9 7
Data Tables The Global Competitiveness Report 2014 2015 411 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 2 7
Data Tables 412 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 2 7
Data Tables The Global Competitiveness Report 2014 2015 413 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 4 7
Data Tables 414 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 415 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 4 7
Data Tables 416 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 417 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 5. 1 7
Data Tables 418 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 4 7
Data Tables The Global Competitiveness Report 2014 2015 419 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 8 7
Data Tables 420 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables The Global Competitiveness Report 2014 2015 421 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables 422 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 6 7
Data Tables The Global Competitiveness Report 2014 2015 423 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 6 7
Data Tables 424 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 1 7
Data Tables The Global Competitiveness Report 2014 2015 425 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 New zealand...
Data Tables 426 The Global Competitiveness Report 2014 2015 2014 World Economic Forum Pillar 2 Infrastructure Data Tables 2014 World Economic
Data Tables 428 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 429 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 3 7
Data Tables 430 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 1 7
Data Tables The Global Competitiveness Report 2014 2015 431 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 4 7
Data Tables 432 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 United states...
Data Tables The Global Competitiveness Report 2014 2015 433 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7
Data Tables 434 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR...
Data Tables The Global Competitiveness Report 2014 2015 435 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Taiwan, China...
Data Tables 436 The Global Competitiveness Report 2014 2015 2014 World Economic Forum Pillar 3 Macroeconomic environment Data Tables 2014 World
Data Tables 438 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Timor-Leste1...
Data Tables The Global Competitiveness Report 2014 2015 439 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Ireland...
Data Tables 440 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Libya...
Data Tables The Global Competitiveness Report 2014 2015 441 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Norway...
Data Tables 442 The Global Competitiveness Report 2014 2015 2014 World Economic Forum Pillar 4 Health and primary education Data Tables 2014 World
Data Tables 444 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 7 7
Data Tables The Global Competitiveness Report 2014 2015 445 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Barbados...
Data Tables 446 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 5. 4 7
Data Tables The Global Competitiveness Report 2014 2015 447 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Albania1...
Data Tables 448 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 5. 3 7
Data Tables The Global Competitiveness Report 2014 2015 449 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR...
Data Tables 450 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR...
Data Tables The Global Competitiveness Report 2014 2015 451 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 9 7
Data Tables 452 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Singapore...
Data Tables The Global Competitiveness Report 2014 2015 453 2014 World Economic Forum 2014 World Economic Forum Pillar 5 Higher education and training
Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Australia...135.5 2 Spain...
Data Tables 456 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Greece11...
Data Tables The Global Competitiveness Report 2014 2015 457 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 7 7
Data Tables 458 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 459 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables 460 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 3 7
Data Tables The Global Competitiveness Report 2014 2015 461 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables 462 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 463 2014 World Economic Forum 2014 World Economic Forum Pillar 6 Goods market
efficiency Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 5. 0 7 1 Japan...
Data Tables 466 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 467 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 1 7
Data Tables 468 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 469 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Macedonia, FYR...
Data Tables 470 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Canada...
Data Tables The Global Competitiveness Report 2014 2015 471 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 New zealand...
Data Tables 472 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 473 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 3 7
Data Tables 474 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR8...
International Trade Centre, Trade Competitiveness Map data 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 7
Data Tables The Global Competitiveness Report 2014 2015 475 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7
Data Tables 476 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 3 7
Data Tables The Global Competitiveness Report 2014 2015 477 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 1 7
Data Tables 478 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR...
Data Tables The Global Competitiveness Report 2014 2015 479 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7
Data Tables 480 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 4 7
Data Tables The Global Competitiveness Report 2014 2015 481 2014 World Economic Forum 2014 World Economic Forum Pillar 7 Labor market efficiency
Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 4 7 1 Switzerland...
Data Tables 484 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 9 7
Data Tables The Global Competitiveness Report 2014 2015 485 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables 486 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Denmark...
Data Tables The Global Competitiveness Report 2014 2015 487 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 7 7
Data Tables 488 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 9 7
Data Tables The Global Competitiveness Report 2014 2015 489 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables 490 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 5 7
Data Tables The Global Competitiveness Report 2014 2015 491 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 5 7
Data Tables 492 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Malawi...
Data Tables The Global Competitiveness Report 2014 2015 493 2014 World Economic Forum 2014 World Economic Forum Pillar 8 Financial market
development Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7 1 Switzerland...
Data Tables 496 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables The Global Competitiveness Report 2014 2015 497 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 4 7
Data Tables 498 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 2. 9 7
Data Tables The Global Competitiveness Report 2014 2015 499 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 2. 8 7
Data Tables 500 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 8 7
Data Tables The Global Competitiveness Report 2014 2015 501 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 1 7
Data Tables 502 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Australia...
Data Tables The Global Competitiveness Report 2014 2015 503 2014 World Economic Forum 2014 World Economic Forum Pillar 9 Technological readiness
Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 8 7 1 Finland...
Data Tables 506 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 7 7
Data Tables The Global Competitiveness Report 2014 2015 507 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7
Data Tables 508 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Iceland...
Data Tables The Global Competitiveness Report 2014 2015 509 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Switzerland...
Data Tables 510 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Luxembourg...
Data Tables The Global Competitiveness Report 2014 2015 511 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Singapore...
Data Tables 512 The Global Competitiveness Report 2014 2015 2014 World Economic Forum Pillar 10 Market size Data Tables 2014 World
Data Tables 514 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 China...
Data Tables The Global Competitiveness Report 2014 2015 515 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 United states...
Data Tables 516 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Hong kong SAR...
Data Tables The Global Competitiveness Report 2014 2015 517 2014 World Economic Forum 2014 World Economic Forum Pillar 11 Business sophistication
Data Tables 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 5 7 1 Japan...
Data Tables 520 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 4 7
Data Tables The Global Competitiveness Report 2014 2015 521 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables 522 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 7 7
Data Tables The Global Competitiveness Report 2014 2015 523 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 9 7
Data Tables 524 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 525 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables 526 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 2 7
Data Tables The Global Competitiveness Report 2014 2015 527 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables 528 The Global Competitiveness Report 2014 2015 2014 World Economic Forum Pillar 12 Innovation Data Tables 2014 World Economic
Data Tables 530 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 8 7
Data Tables The Global Competitiveness Report 2014 2015 531 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 3 7
Data Tables 532 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 7 7
Data Tables The Global Competitiveness Report 2014 2015 533 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 3. 5 7
Data Tables 534 The Global Competitiveness Report 2014 2015 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 MEAN 4. 0 7
Data Tables The Global Competitiveness Report 2014 2015 535 2014 World Economic Forum RANK COUNTRY/ECONOMY VALUE 1 Switzerland...
Data Tables 536 The Global Competitiveness Report 2014 2015 2014 World Economic Forum The Global Competitiveness Report 2014 2015 537 This section complements the Data
It is possible that some data will have been updated or revised after publication. Key indicators 0. 01 Gross domestic product Gross domestic product in billions of current US dollars 2013 Sources:
but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services
private trunked mobile radio, telepoint or radio paging, and telemetry services are excluded also. It includes all mobile cellular subscriptions that offer voice communications.
The weights are the trade patterns of the importing country's reference group (2012 data.
International Trade Centre, Trade Competitiveness Map Data 6. 11 Prevalence of foreign ownership In your country, how prevalent is foreign ownership of companies?
Data are based on surveys generally carried out by national statistical offices or estimated based on the number of Internet subscriptions.
Data are normalized then on a 1 7 scale. PPP estimates of imports and exports are obtained by taking the product of exports as a percentage of GDP and GDP valued at PPP.
In the absence of reliable data on PCT applications for Taiwan (China) and Hong kong SAR, two advanced economies that are not signatories of the Treaty
He works on the development and computation of a range of indexes and on the analysis of data for the elaboration of various reports.
The data used in the Report are obtained from leading international sources as well as from the World Economic Forum's annual Executive Opinion Survey, a unique source that captures the perspectives of more than 14,000 business leaders on topics related to
as well as an extensive section of data tables displaying relative rankings for more than 100 variables. The Report and an interactive data platform are available at www. weforum. org/gcr
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