The average for 2023 based on 184 countries was 0.744 points. The highest value was in Iceland: 0.972 points and the lowest value was in South Africa: 0.388 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

Nigeria obtained 0.88 points in the Gender Development Index (GDI) in 2019. The index score in the country increased in 2019, indicating a worsening gender inequality situation in the fields of education, health, and wealth. The GDI measures the levels of gender parity within societies. It ranges from zero (perfect gender equality) to around one (no gender parity).

0,54 (puntaje, el más alto=el mejor) in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

In sub-Saharan Africa, a score of 0.55 was achieved on the Human Development Index (HDI) in 2021. This represented a low level of human development. Throughout the periods under study, the sub-region remained within the index scores of 0.42 and 0.56, an indication of low human development.

Graph and download economic data for Index of Human Capital per Person for Nigeria (HCIYISNGA066NRUG) from 1960 to 2019 about Nigeria, capital, and indexes.

0,54 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. Ein zusammengesetzter Index, der den durchschnittliche Fortschritt dreier grundlegender Dimensionen der menschlichen Entwicklung misst - ein langes und gesundes Leben, Wissen und einen annehmbaren Lebensstandard

Explore The Human Capital Report dataset for insights into Human Capital Index, Development, and World Rankings. Find data on Probability of Survival to Age 5, Expected Years of School, Harmonized Test Scores, and more.

Low income, Upper middle income, Lower middle income, High income, Human Capital Index (Lower Bound), Human Capital Index, Human Capital Index (Upper Bound), Probability of Survival to Age 5, Expected Years of School, Harmonized Test Scores, Learning-Adjusted Years of School, Fraction of Children Under 5 Not Stunted, Adult Survival Rate, Development, Human Capital, World Rankings

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahrain, Bangladesh, Belarus, Belgium, Benin, Bhutan, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cyprus, Denmark, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kuwait, Latvia, Lebanon, Lesotho, Liberia, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovenia, Solomon Islands, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Sweden, Switzerland, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Vietnam, Yemen, Zambia, Zimbabwe, WORLD

Follow data.kapsarc.org for timely data to advance energy economics research.

Last year edition of the World Economic Forum Human Capital Report explored the factors contributing to the development of an educated, productive and healthy workforce. This year edition deepens the analysis by focusing on a number of key issues that can support better design of education policy and future workforce planning.

The Multiple Indicator Cluster Survey (MICS) is a primary source of information on women and children as it provides statistical indicators that are critical for the measurement of human development. It is an international household survey programme developed by United Nations Children’s Fund (UNICEF). The MICS is designed to collect statistically sound and internationally comparable estimates of key indicators that are used to assess the situation of children and women in the areas of health, education, child protection and HIV/AIDS. It can also be used as a data collection tool to generate data for monitoring the progress towards national goals and global commitments which aimed at promoting the welfare of children and women such as MDGs and SDGs. OBJECTIVES The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are: To provide up-to-date information for assessing the situation of children and women in Nigeria; To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention; To contribute to the generation of baseline data for the SDG; To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action; To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.

Nigéria: Human Development Index (0 - 1): Pour cet indicateur, The United Nations fournit des données pour la Nigéria de 2003 à 2023. La valeur moyenne pour Nigéria pendant cette période était de 0.508 points avec un minimum de 0.452 points en 2003 et un maximum de 0.56 points en 2023.

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

Somalia ist nicht nur in Afrika, sondern auch weltweit das Land mit dem geringsten Entwicklungsstand nach dem Human-Development-Index (HDI) im Jahr 2022 mit einem Indexwert von 0,380. Es folgt der Südsudan mit einem Indexwert von 0,381. Auf Rang drei liegt die Zentralafrikanische Republik mit einem HDI von 0,387. Insgesamt werden alle 20 Staaten der Klasse des "low human development" zugeordnet. Der Weltdurchschnitt des HDI liegt bei 0,739 Punkten. Was ist der Human Development Index (HDI)? Der HDI ist ein Wohlstandsindikator, der neben dem Bruttonationaleinkommen pro Kopf auch Lebenserwartung und Bildung berücksichtigt. Der Indikator kann einen Wert zwischen 0 und 1 annehmen (zur besseren Darstellung wurden die ursprünglichen Werte in dieser Statistik mit 1.000 multipliziert). Je höher der Wert, desto weiter ist die Entwicklung in den jeweiligen Ländern vorangeschritten.

Abstract

The Multiple Indicator Cluster Survey (MICS) is a primary source of information on women and children as it provides statistical indicators that are critical for the measurement of human development. It is an international household survey programme developed by United Nations Children’s Fund (UNICEF). The MICS is designed to collect statistically sound and internationally comparable estimates of key indicators that are used to assess the situation of children and women in the areas of health, education, child protection and HIV/AIDS. It can also be used as a data collection tool to generate data for monitoring the progress towards national goals and global commitments which aimed at promoting the welfare of children and women such as MDGs and SDGs.

OBJECTIVES

The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are:

• To provide up-to-date information for assessing the situation of children and women in Nigeria;

• To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention;

• To contribute to the generation of baseline data for the SDG;

• To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action;

• To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.

Geographic coverage

National, rural/urban, states as well as the 6 geo-political zones of Nigeria.

Analysis unit

• Individuals

• Households

Universe

All household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 years of age.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size for the Nigeria MICS5 was calculated as 37,440 households.

The principal domain of reporting to which the sample size n refers in this calculation is the state. For this sample design, determination of the sample size is based on the indicator stunting prevalence in under-5 children as the design variable. The results from the MICS4 of 2011 reported stunting prevalence at 35.8 percent at the national level. This estimate had a relatively high design effect (deff) of 4.85, indicating a large clustering effect for this characteristic. However, with the more efficient sample design for the MICS 2016-17 it was expected that the deff will be lower, so a value of 3.5 was assumed for the deff in calculating the sample size. The value for pb (percentage of children aged 0-4 years in the total population) based on the results of the MICS4 2011 and NDHS 2013 is 17.1; and Average Size (average household size) is 5.0. For state-level results, it is reasonable to use a relative margin of error (RME) of 18%. Based on previous survey results, the household response rate is assumed to be 95%.

For 34 states and the FCT Abuja a sample of 60 EAs was selected per state and 16 households per EA, which gives a sample size of 960 households in each of these states. Six (6) replicates containing ten (10) EAs/clusters each was selected from the NISH2 master sample for each of these states. In the case of Kano and Lagos States, additional results were needed at the level of the three senatorial districts in each state. Therefore, a sample of 40 EAs per senatorial district was selected in these two states from the NISH2 master sample, for a total of 120 sample EAs and 1,920 sample households in each state. The total sample size for Nigeria was 37,440 households. And the selection of 16 households per EA slightly reduces the design effects compared to the MICS 2011, in which 20 households were selected per EA

SAMPLING FRAME AND SELECTION OF CLUSTERS

The MICS sample clusters were selected from the NISH2 master sample, based on the 2006 census frame. For the NISH2 master sample the census enumeration areas were defined as primary sampling units (PSUs), stratified by state. The first stage of sampling for MICS was completed by selecting the required number of enumeration areas from the NISH2 master sample for each of the 36 states of the federation and FCT Abuja which cut across urban and rural areas.

LISTING ACTIVITIES

Since the sampling frame (the 2006 Census) was not up-to-date, a new listing of households was conducted in November 2015 for all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in each enumeration area. Selected staff of the National Bureau of Statistics (NBS) in all the states carried out the listing exercise. Six (6) teams were constituted that carried out the listing exercise in each state except Lagos and Kano where twelve teams were constituted respectively. Each team comprises of 2 enumerators and one (1) supervisor who supervised two (2) teams. There were three (3) supervisors in each of the 35 states, and six (6) supervisors for Lagos and Kano states respectively. The listing exercise lasted for twelve (12) days. Out of the 2,340 enumeration areas selected for the household listing, one hundred and one (101) of them were not visited because they were inaccessible due to insecurity during the listing exercise.

SELECTION OF HOUSEHOLDS

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to N (the total number of households in each enumeration area) at the National Bureau of Statistics (Field Services and Methodology Department), where the selection of 16 households in each enumeration area was carried out using random systematic selection procedures.

The survey also included a questionnaire for individual men aged 15 to 49 years. It was administered in eight out of sixteen sampled households. Households with even number in each sample cluster were selected and all eligible men were interviewed.

Within each state, a sub-sample of 30 enumeration areas was systematically selected for the water quality test. In each of these sampled EAs, a systematic sub sample of three households out of sixteen (16) MICS sample households was selected for the water quality tests.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires are based on the MICS5 questionnaire3 model (English version), customized and pre-tested in Cross River, Enugu, Gombe, Lagos, Kaduna, Kano, Nasarawa and Oyo states in April 2016. Based on the results of the pre-test, modifications were made to the wording of the questionnaires. A copy of the Nigeria MICS questionnaires is provided as Related Material.

In addition to the administration of questionnaires, salt iodization and water quality tests were conducted. Weight and height of children age under 5 years were also measured.

Cleaning operations

Data were analyzed using the Statistical Package for Social Scientists (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF MICS team were customized and used for this purpose.

Response rate

Out of 37,440 households sampled, 35,747 households were visited, 34,289 were found to be occupied and 33,901 were successfully interviewed, representing a household response rate of 98.9 percent.

In the interviewed households, 36,176 women (age 15-49 years) were identified. Of these, 34,376 were successfully interviewed, yielding a response rate of 95.0 percent within the interviewed households.

The survey also sampled men (age 15-49), but required only a subsample. All men (age 15-49) were identified in 17,868 households selected for the men questionnaire; 16,514 men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 15,183 eligible men, which corresponds to a response rate of 91.9 percent within eligible interviewed households.

There were 28,578 children under age five listed in the household questionnaires. Questionnaires were completed for 28,085 of these children, which corresponds to a response rate of 98.3 percent within interviewed households.

Overall response rates of 93.9, 90.9 and 97.2 are calculated for the individual interviews of women, men, and under-5s, respectively.

Sampling error estimates

The sample of respondents selected in the Multiple Indicator Cluster Survey (MICS) 2016 is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.

The following sampling error measures are presented in this appendix for each of the selected indicators:

• Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation.

• Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error.

• Design

As of 2020, Mauritius was ranked highest among African countries based on E-Government Development Index (EGDI), with a rating of 0.72. The EGDI assesses e-government development at a national level and is based on three components: online service index, telecommunication infrastructure index, and the human capital index. At 0.39, the regional average EDGI for the African continent is almost a third lower than the world average of 0.60.

The study examined the relationship between environmental accounting and sustainability development in Nigeria from 2007 - 2016. Oil spillage cost, oil drilling waste disposal cost and degradation cost were the proxies of environmental accounting while human development index and human poverty index were sustainability development proxies. The researchers adopted correlational research design for the study. The study used secondary data obtained from Nigeria National Petroleum Corporation annual reports, CBN Statistical Bulletin, National Bureau of Statistic Bulletin and United Nation Development Programs (UNDP) Report 2016. The research Hypotheses test and other data were analyzed by Pearson Product Moment Correlation and simple linear regression tools with the aid of SPSS version 22. The outcomes of this study depicted that environmental accounting variables (OSC and ODWDC) has no significant relationship with sustainability development in Nigeria in the period of this study. However, Degradation cost revealed significant relationship with both human development index and human poverty index. Thus, the study concluded that environmental accounting has not fully influenced sustainability development in Nigeria in the period of this study. It is recommended that the National Assembly should immediately pass a Degradation Protection Law mandating all Oil multinational companies operating in the Niger-Delta region to observe and comply strictly with the highest environmental protection standards in line with global best practice to prevent degradation. We equally endorsed that Nigerian government should initiate degradation oriented policies in governance to ensure adequate human capital development of the people of the oil producing states in particular and the entire country aimed at reducing the rate of poverty, unemployment, and improve decent standard of living.

Nigeria registered the highest gender inequality score in Africa. As of 2021 the country received a score of around 0.68. The Central African Republic, Liberia, and Chad followed, with 0.67, 0.65, 0.65, respectively. On the other hand, Cabo Verde, Tunisia, and Libya achieved the lowest scores on the African continent.

The indicator measures the potential of human development loss resulting from gender achievement disparities based on reproductive health, empowerment, and the labor market. Higher values on a scale from zero to one indicate higher inequalities between women and men.

Nigeria hat im FSI 2024 einen Indexwert von 96,6 Punkten erreicht und belegt damit Platz 15 von 179 untersuchten Staaten weltweit. Diese Statistik zeigt die Bewertung Nigerias nach dem Fragile States Index (FSI) von 2014 bis 2024. Der Fragile States Index (ehemals: Failed States Index) ist eine von der Organisation Fund for Peace etablierte Kennzahl, die zur Beurteilung der Stabilität eines Staates dient. Der FSI bewertet auf einer Skala von 0 (= stabiler Staat) bis 120 (= instabiler Staat) jährlich weltweit 179 Staaten. Eine ähnliche Maßzahl ist der Bertelsmann Transformationsindex (BTI), der alle zwei Jahre für die Messung von Demokratie, Marktwirtschaft und politischem Management herangezogen wird. Die Methodik des Fragile States Index basiert auf Triangulation von drei Primärquellen und der jährlichen Analyse von über einer Million relevanter Dokumente. Die Analyse und Indexierung gliedert sich in 12 politisch-militärische, ökonomische und soziale Primärindikatoren und über 100 Teilindikatoren. Der Gesamtindexwert für jedes Land ergibt sich aus der Summe der folgenden 12 Primärindikatoren, für die jeweils ein Indexwert von 0 bis 10 errechnet wird:Politische und Militärische Indikatoren:-ST: State Legitimacy (Staatliche Legitimität)-PS: Public Services (Öffentlicher Dienst)-HR: Human Rights & Rule of Law (Menschenrechte & Rechtsstaatlichkeit)-SEC: Security Apparatus (Sicherheitsapparat)-FE: Factionalized Elites (Nichtstaatliche Eliten - Staat im Staat) -EXT: External Intervention (Interventionen von Außen)Ökonomische Indikatoren:-UED: Uneven Economic Development (Ungleiche wirtschaftliche Entwicklung)-ECO: Poverty & Economic Decline (Armut und wirtschaftlicher Abstieg)Soziale Indikatoren:-DP: Demographic Pressures (Demographischer Druck)-REF: Refugees and IDPs (Flüchtlinge und Vertriebene)-GG: Group Grievance (Spannungen zwischen Gruppen - z.B. ethnisch oder religiös)-HF: Human Flight & Brain Drain (Migration und "brain drain")