Global Data Set on Education Quality

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This paper presents the largest globally comparable panel database of education quality. The database includes 163 countries and regions over 1965-2015. The globally comparable achievement outcomes were constructed by linking standardized, psychometrically-robust international and regional achievement tests. The paper contributes to the literature in the following ways: (1) it is the largest and most current globally comparable data set, covering more than 90 percent of the global population; (2) the data set includes 100 developing areas and the most developing countries included in such a data set to date -- the countries that have the most to gain from the potential benefits of a high-quality education; (3) the data set contains credible measures of globally comparable achievement distributions as well as mean scores; (4) the data set uses multiple methods to link assessments, including mean and percentile linking methods, thus enhancing the robustness of the data set; (5) the data set includes the standard errors for the estimates, enabling explicit quantification of the degree of reliability of each estimate; and (6) the data set can be disaggregated across gender, socioeconomic status, rural/urban, language, and immigration status, thus enabling greater precision and equity analysis. A first analysis of the data set reveals a few important trends: learning outcomes in developing countries are often clustered at the bottom of the global scale; although variation in performance is high in developing countries, the top performers still often perform worse than the bottom performers in developed countries; gender gaps are relatively small, with high variation in the direction of the gap; and distributions reveal meaningfully different trends than mean scores, with less than 50 percent of students reaching the global minimum threshold of proficiency in developing countries relative to 86 percent in developed countries. The paper also finds a positive and significant association between educational achievement and economic growth. The data set can be used to benchmark global progress on education quality, as well as to uncover potential drivers of education quality, growth, and development.

Type: 
Time Series
Languages Supported: 
English
External Contact Email: 
Topics: 
Economic Growth
Education
Gender
Granularity: 
Geographical Coverage: 
World
East Asia & Pacific
American Samoa
Australia
Brunei Darussalam
Cambodia
China
Cook Islands
Fiji
French Polynesia
Guam
Hong Kong SAR, China
Indonesia
Japan
Kiribati
Korea, Dem. People's Rep.
Korea, Rep.
Lao PDR
Macao SAR, China
Malaysia
Marshall Islands
Micronesia, Fed. Sts.
Mongolia
Myanmar
Nauru
New Caledonia
New Zealand
Niue
Northern Mariana Islands
Palau
Papua New Guinea
Philippines
Samoa
Singapore
Solomon Islands
Taiwan, China
Thailand
Timor-Leste
Tonga
Tuvalu
Vanuatu
Vietnam
Europe & Central Asia
Albania
Andorra
Armenia
Austria
Azerbaijan
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Channel Islands
Croatia
Cyprus
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Georgia
Germany
Gibraltar
Greece
Greenland
Hungary
Iceland
Ireland
Isle of Man
Italy
Kazakhstan
Kosovo
Kyrgyz Republic
Latvia
Liechtenstein
Lithuania
Luxembourg
North Macedonia
Moldova
Monaco
Montenegro
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Tajikistan
Turkey
Turkmenistan
Ukraine
United Kingdom
Uzbekistan
Latin America & Caribbean
Anguilla
Antigua and Barbuda
Aruba
Argentina
Bahamas, The
Barbados
Belize
Bolivia
Brazil
British Virgin Islands
Cayman Islands
Chile
Costa Rica
Colombia
Cuba
Curaçao
Dominica
Dominican Republic
Ecuador
El Salvador
Grenada
Guatemala
Guyana
Haiti
Honduras
Jamaica
Martinique
Mexico
Montserrat
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Sint Maarten (Dutch part)
St. Barthélemy
St. Kitts and Nevis
St. Martin (French part)
St. Lucia
St. Vincent and the Grenadines
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela, RB
Virgin Islands (U.S.)
Middle East & North Africa
Algeria
Bahrain
Egypt, Arab Rep.
Djibouti
Iraq
Iran, Islamic Rep.
Israel
Jordan
Kuwait
Lebanon
Libya
Malta
Morocco
Oman
Qatar
Saudi Arabia
Syrian Arab Republic
West Bank and Gaza
United Arab Emirates
Tunisia
Yemen, Rep.
North America
Bermuda
Canada
United States
South Asia
Afghanistan
Bangladesh
Bhutan
India
Pakistan
Nepal
Maldives
Sri Lanka
Sub-Saharan Africa
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d'Ivoire
Ethiopia
Eritrea
Equatorial Guinea
Gabon
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Rwanda
São Tomé and Principe
Seychelles
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Eswatini
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Economy Coverage: 
Blend
High Income
IBRD
IDA
Low Income
Lower Middle Income
Upper Middle Income
Number of Economies: 
163
Periodicity: 
Periodicity not specified
Temporal Coverage: 
1965 - 2015
Release Date: 
January 23, 2018

Last Updated

Last Updated: 
February 21, 2018

Harvest System ID

Harvest System ID: 
Research papers

Harvest Source ID

Harvest Source ID: 
WPS8314
Time Periods: 
February, 2018

No Visualizations Available.

This paper presents the largest globally comparable panel database of education quality. The database includes 163 countries and regions over 1965-2015. The globally comparable achievement outcomes were constructed by linking standardized, psychometrically-robust international and regional achievement tests. The paper contributes to the literature in the following ways: (1) it is the largest and most current globally comparable data set, covering more than 90 percent of the global population; (2) the data set includes 100 developing areas and the most developing countries included in such a data set to date -- the countries that have the most to gain from the potential benefits of a high-quality education; (3) the data set contains credible measures of globally comparable achievement distributions as well as mean scores; (4) the data set uses multiple methods to link assessments, including mean and percentile linking methods, thus enhancing the robustness of the data set; (5) the data set includes the standard errors for the estimates, enabling explicit quantification of the degree of reliability of each estimate; and (6) the data set can be disaggregated across gender, socioeconomic status, rural/urban, language, and immigration status, thus enabling greater precision and equity analysis. A first analysis of the data set reveals a few important trends: learning outcomes in developing countries are often clustered at the bottom of the global scale; although variation in performance is high in developing countries, the top performers still often perform worse than the bottom performers in developed countries; gender gaps are relatively small, with high variation in the direction of the gap; and distributions reveal meaningfully different trends than mean scores, with less than 50 percent of students reaching the global minimum threshold of proficiency in developing countries relative to 86 percent in developed countries. The paper also finds a positive and significant association between educational achievement and economic growth. The data set can be used to benchmark global progress on education quality, as well as to uncover potential drivers of education quality, growth, and development.

Data Resources

FieldValue
Groups audience
Modified Date
2020-02-14
Release Date
Periodicity
Periodicity not specified
Identifier
bd6585cc-9a97-41b5-9d48-d0e522bcac85
Temporal Coverage

1965 - 2015

License
License Not Specified
Contact Email
Rating: 
0
No votes yet
Type: 
Languages Supported: 
Time Periods: 
February, 2018
Number of Economies: 
163
Geographical Coverage: 
Data Classification of a Dataset: 
Start Date: 
Friday, January 1, 1965
End Date: 
Thursday, December 31, 2015
HEC
Programatic Region: 
Release Date: 
Tuesday, January 23, 2018
Last Updated Date: 
Wednesday, February 21, 2018
External Contact Email: 
Granularity: 
Harvest Source: 
Harvest System ID: 
WPS8314
Modified date: 
17583
Primary Dataset: 
Yes

Data Access and Licensing

This dataset is classified as Public under the Access to Information Classification Policy. Users inside and outside the Bank can access this dataset.

This dataset is licensed under CC-BY 4.0

CC-BY 4.0

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