In 2023, pasta consumption per capita varied significantly across countries. Italy topped the list, with its citizens consuming an average of **** kilograms of pasta annually. Tunisia ranked second with a per capita consumption of ** kilograms. Germany, on the other hand, had a much lower per capita consumption of *** kilograms, which was nearly three times less than Italy's figure. Pasta in Italy According to a survey, ** percent of Italian respondents said they eat pasta six to seven times a week. Another ** percent of respondents stated they have pasta four to five times a week. By contrast, for ***** percent of respondents eating pasta was a weekly occurrence. Most popular pasta Barilla was the most widespread pasta brand in Italy, found in approximately ** percent of supermarkets. Private label pasta is very popular as well, followed by the brand De Cecco. Classic, or durum wheat, pasta was the preferred pasta type, with more than ************* of Italians choosing it. This was followed by whole-wheat chosen by ** percent of the survey respondents.

Qatar has the highest per capita energy consumption worldwide. In 2024, residents in Qatar used an average of *** megawatt-hours worth of energy - all of which was derived from fossil fuels. Sources of primary energy In 2024, oil and coal were the main fuels used for primary energy worldwide. Except for the Nordic countries and Canada, all other countries listed among the leading 10 consumers sourced energy almost exclusively from fossil fuels. Many of them are also responsible for large oil production shares or the refining thereof. Differences in energy consumption There is a notable disparity between the highest and lowest energy users. Resource-rich countries outside the temperate climate zone tend to use more energy to heat or cool homes and are also more likely to use greater amounts of energy as costs are much lower. For example, electricity prices in oil and gas-producing countries such as Qatar and Saudi Arabia are only a fraction of those of resource-poor countries in Europe. Furthermore, energy consumption disparity is a strong indicator of the different income levels around the world and largely tied to economic prosperity.

The rating reflects how many liters of pure ethyl alcohol are drunk by residents of a particular country per year. Ethyl alcohol is accepted as the unit of assessment, but this is done for ease of comparison: in fact, any alcohol is taken into account in the rating, including beer, wine and others.

The Global Consumption Database (GCD) contains information on consumption patterns at the national level, by urban/rural area, and by income level (4 categories: lowest, low, middle, higher with thresholds based on a global income distribution), for 92 low and middle-income countries, as of 2010. The data were extracted from national household surveys. The consumption is presented by category of products and services of the International Comparison Program (ICP) 2005, which mostly corresponds to COICOP. For three countries, sub-national data are also available (Brazil, India, and South Africa). Data on population estimates are also included. The data file can be used for the production of the following tables (by urban/rural and income class/consumption segment): - Sample Size by Country, Area and Consumption Segment (Number of Households) - Population 2010 by Country, Area and Consumption Segment - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population - Population 2010 by Country, Age Group, Sex and Consumption Segment - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million) - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million) - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million) - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency (Million) - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP (Million) - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ (Million) - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in Local Currency (Million) - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in $PPP (Million) - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in US$ (Million) - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$ - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP - Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent) - Consumption Shares 2010 by Country, Category of Products/Services, Area and Consumption Segment (Percent) - Consumption Shares 2010 by Country, Product/Service, Area and Consumption Segment (Percent) - Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)

Water withdrawals per capita in Montenegro amount to 3590.74 cubic meters per inhabitant, according to the latest available data from 2022. This is a far higher volume than in many other countries, such as India, where per capita water withdrawals were 533.88 cubic meters as of 2022. Global water withdrawals Countries around the world withdraw huge volumes of water each year from sources such as rivers, lakes, reservoirs, and groundwater. China has some of the largest annual total water withdrawals across the globe, at 568.48 billion cubic meters in 2022. In comparison, Mexico withdrew almost 90 billion cubic meters of water that same year. Water scarcity Although roughly 70 percent of Earth's surface is covered with water, less than one percent of the planet's total water resources can be classified as accessible freshwater resources. Growing populations, increased demand, and climate change are increasingly putting pressure on these precious resources. This is expected to lead to global water shortages around the world. In the United States, the megadrought in the west has seen water levels of major reservoirs that provide water to millions of people plummet to record lows. To prevent severe droughts in water-stressed areas today and in the future, a more efficient use of water is essential.

The average for 2024 based on 177 countries was 27291 U.S. dollars. The highest value was in Singapore: 132570 U.S. dollars and the lowest value was in Burundi: 836 U.S. dollars. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

Abstract

The Global Consumption Database (GCD) contains information on consumption patterns at the national level, by urban/rural area, and by income level (4 categories: lowest, low, middle, higher with thresholds based on a global income distribution), for 92 low and middle-income countries, as of 2010. The data were extracted from national household surveys. The consumption is presented by category of products and services of the International Comparison Program (ICP) 2005, which mostly corresponds to COICOP. For three countries, sub-national data are also available (Brazil, India, and South Africa). Data on population estimates are also included.

       The data file can be used for the production of the following tables (by urban/rural and income class/consumption segment):
       - Sample Size by Country, Area and Consumption Segment (Number of Households)
       - Population 2010 by Country, Area and Consumption Segment
       - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population
       - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population
       - Population 2010 by Country, Age Group, Sex and Consumption Segment
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in US$ (Million)
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP
       - Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent)
       - Consumption Shares 2010 by Country, Category of Products/Services, Area and Consumption Segment (Percent)
       - Consumption Shares 2010 by Country, Product/Service, Area and Consumption Segment (Percent)
       - Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)

Geographic coverage notes

For all countries, estimates are provided at the national level and at the urban/rural levels. For Brazil, India, and South Africa, data are also provided at the sub-national level (admin 1): - Brazil: ACR, Alagoas, Amapa, Amazonas, Bahia, Ceara, Distrito Federal, Espirito Santo, Goias, Maranhao, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Para, Paraiba, Parana, Pernambuco, Piaji, Rio de Janeiro, Rio Grande do Norte, Rio Grande do Sul, Rondonia, Roraima, Santa Catarina, Sao Paolo, Sergipe, Tocatins - India: Andaman and Nicobar Islands, Andhra Pradesh, Arinachal Pradesh, Assam, Bihar, Chandigarh, Chattisgarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Lakshadweep, Madya Pradesh, Maharastra, Manipur, Meghalaya, Mizoram, Nagaland, Orissa, Pondicherry, Punjab, Rajasthan, Sikkim, Tamil Nadu, Tripura, Uttar Pradesh, Uttaranchal, West Bengal - South Africa: Eastern Cape, Free State, Gauteng, Kwazulu Natal, Limpopo, Mpulamanga, Northern Cape, North West, Western Cape

Kind of data

Data derived from survey microdata

There are large inequalities in energy consumption between countries. The average US citizen still consumes more than ten times the energy of the average Indian, 4-5 times that of a Brazilian, and three times more than China. The gulf between these and very low-income nations is even greater- a number of low-income nations consume less than 100 kilowatt-hour equivalents per person.

Secondly, global average per capita energy consumption has been consistently increasing; between 1970 and 2014, average consumption increased by approximately 45%.

This growth in per capita energy consumption does, however, vary significantly between countries and regions. Most of the growth in per capita energy consumption over the last few decades has been driven by increased consumption in transitioning middle-income (and to a lesser extent, low income countries). In the chart we see a significant increase in consumption in transitioning BRICS economies (China, India and Brazil in particular); China’s per capita use has grown by nearly 250 percent since 2000; India by more than 50 percent; and Brazil by 38 percent.

Whilst global energy growth is growing from developing economies, the trend for many high-income nations is a notable decline. As we see in exemplar trends from the UK and US, the growth we are currently seeing in transitioning economies ended for many high-income nations by over the 1970s and 80s. Both the US and UK peaked in terms of per capita energy consumption in the 1970s, plateauing for several decades until the early 2000s. Since then, we see a reduction in consumption; since 2000, UK usage has decreased by 20 to 25%.

Source

Hannah Ritchie (2019) - "Access to Energy". Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/energy-access'

The alcohol consumption per capita ranking is led by Romania with ***** liters, while Georgia is following with ***** liters. In contrast, Bangladesh is at the bottom of the ranking with **** liters, showing a difference of ***** liters to Romania. Depicted is the estimated alcohol consumption in the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Goal 3Ensure healthy lives and promote well-being for all at all agesTarget 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live birthsIndicator 3.1.1: Maternal mortality ratioSH_STA_MORT: Maternal mortality ratioIndicator 3.1.2: Proportion of births attended by skilled health personnelSH_STA_BRTC: Proportion of births attended by skilled health personnel (%)Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsIndicator 3.2.1: Under-5 mortality rateSH_DYN_IMRTN: Infant deaths (number)SH_DYN_MORT: Under-five mortality rate, by sex (deaths per 1,000 live births)SH_DYN_IMRT: Infant mortality rate (deaths per 1,000 live births)SH_DYN_MORTN: Under-five deaths (number)Indicator 3.2.2: Neonatal mortality rateSH_DYN_NMRTN: Neonatal deaths (number)SH_DYN_NMRT: Neonatal mortality rate (deaths per 1,000 live births)Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesIndicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsSH_HIV_INCD: Number of new HIV infections per 1,000 uninfected population, by sex and age (per 1,000 uninfected population)Indicator 3.3.2: Tuberculosis incidence per 100,000 populationSH_TBS_INCD: Tuberculosis incidence (per 100,000 population)Indicator 3.3.3: Malaria incidence per 1,000 populationSH_STA_MALR: Malaria incidence per 1,000 population at risk (per 1,000 population)Indicator 3.3.4: Hepatitis B incidence per 100,000 populationSH_HAP_HBSAG: Prevalence of hepatitis B surface antigen (HBsAg) (%)Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseasesSH_TRP_INTVN: Number of people requiring interventions against neglected tropical diseases (number)Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-beingIndicator 3.4.1: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory diseaseSH_DTH_NCOM: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability)SH_DTH_NCD: Number of deaths attributed to non-communicable diseases, by type of disease and sex (number)Indicator 3.4.2: Suicide mortality rateSH_STA_SCIDE: Suicide mortality rate, by sex (deaths per 100,000 population)SH_STA_SCIDEN: Number of deaths attributed to suicide, by sex (number)Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcoholIndicator 3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disordersSH_SUD_ALCOL: Alcohol use disorders, 12-month prevalence (%)SH_SUD_TREAT: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders (%)Indicator 3.5.2: Alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcoholSH_ALC_CONSPT: Alcohol consumption per capita (aged 15 years and older) within a calendar year (litres of pure alcohol)Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidentsIndicator 3.6.1: Death rate due to road traffic injuriesSH_STA_TRAF: Death rate due to road traffic injuries, by sex (per 100,000 population)Target 3.7: By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programmesIndicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methodsSH_FPL_MTMM: Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods (% of women aged 15-49 years)Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000 women in that age groupSP_DYN_ADKL: Adolescent birth rate (per 1,000 women aged 15-19 years)Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allIndicator 3.8.1: Coverage of essential health servicesSH_ACS_UNHC: Universal health coverage (UHC) service coverage indexIndicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeSH_XPD_EARN25: Proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income (%)SH_XPD_EARN10: Proportion of population with large household expenditures on health (greater than 10%) as a share of total household expenditure or income (%)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationIndicator 3.9.1: Mortality rate attributed to household and ambient air pollutionSH_HAP_ASMORT: Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)SH_STA_AIRP: Crude death rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_STA_ASAIRP: Age-standardized mortality rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_AAP_MORT: Crude death rate attributed to ambient air pollution (deaths per 100,000 population)SH_AAP_ASMORT: Age-standardized mortality rate attributed to ambient air pollution (deaths per 100,000 population)SH_HAP_MORT: Crude death rate attributed to household air pollution (deaths per 100,000 population)Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)SH_STA_WASH: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (deaths per 100,000 population)Indicator 3.9.3: Mortality rate attributed to unintentional poisoningSH_STA_POISN: Mortality rate attributed to unintentional poisonings, by sex (deaths per 100,000 population)Target 3.a: Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriateIndicator 3.a.1: Age-standardized prevalence of current tobacco use among persons aged 15 years and olderSH_PRV_SMOK: Age-standardized prevalence of current tobacco use among persons aged 15 years and older, by sex (%)Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allIndicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeSH_ACS_DTP3: Proportion of the target population with access to 3 doses of diphtheria-tetanus-pertussis (DTP3) (%)SH_ACS_MCV2: Proportion of the target population with access to measles-containing-vaccine second-dose (MCV2) (%)SH_ACS_PCV3: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (%)SH_ACS_HPV: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis, human papillomavirus (HPV) (%)Indicator 3.b.2: Total net official development assistance to medical research and basic health sectorsDC_TOF_HLTHNT: Total official development assistance to medical research and basic heath sectors, net disbursement, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_HLTHL: Total official development assistance to medical research and basic heath sectors, gross disbursement, by recipient countries (millions of constant 2018 United States dollars)Indicator 3.b.3: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basisSH_HLF_EMED: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis (%)Target 3.c: Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing StatesIndicator 3.c.1: Health worker density and distributionSH_MED_DEN: Health worker density, by type of occupation (per 10,000 population)SH_MED_HWRKDIS: Health worker distribution, by sex and type of occupation (%)Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risksIndicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparednessSH_IHR_CAPS: International Health Regulations (IHR) capacity, by type of IHR capacity (%)Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organismsiSH_BLD_MRSA: Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) among patients seeking care and whose

Iceland is by far the largest per capita consumer of electricity worldwide, averaging 51.9 megawatt-hours per person in 2024. This results from a combination of factors, such as low-cost electricity production, increased heating demand, and the presence of energy-intensive industries in the country. Norway, Qatar, and Canada were also some of the world's largest electricity consumers per capita that year. China is the leading overall power consumer Power-intensive industries, the purchasing power of the average citizen, household size, and general power efficiency standards all contribute to the amount of electricity that is consumed per person every year. However, in terms of total electricity consumption, a country's size and population can also play an important role. In 2024, the three most populous countries in the world, namely China, the United States, and India, were also the three largest electricity consumers. Global electricity consumption on the rise In 2023, net electricity consumption worldwide amounted to over 27,000 terawatt-hours, an increase of 30 percent in comparison to a decade earlier. When compared to 1980, global electricity consumption more than tripled. On the generation side, the world is still strongly dependent on fossil fuels. Despite the world's renewable energy capacity quintupling in the last decade, coal and gas combined still accounted for almost 60 percent of global electricity generation in 2023.

Energy Consumption and Mix Dataset by Our World in Data

Dataset Description

This dataset is a comprehensive collection of key metrics related to energy consumption and energy mix, maintained by Our World in Data. It includes global, regional, and country-level data on primary energy consumption, energy mix, electricity mix, fossil fuel production, and related energy metrics.

Key Metrics

The dataset contains several important metrics related to global energy:

• Energy Consumption (primary energy, per capita consumption, growth rates)
• Energy Mix (share of renewables, fossil fuels, etc.)
• Electricity Mix (sources of electricity generation such as coal, hydro, wind, solar)
• Fossil Fuel Production
• Primary Energy Consumption
• Per Capita and Per GDP Energy Indicators
• Yearly data by country and global aggregates

Possible Analyses

The "Energy Consumption and Mix" dataset offers a wide range of opportunities for analysis. Here are some examples of what can be done with this dataset:

1. Global Energy Consumption Trends

• Objective: Examine how global primary energy consumption has evolved over time.
• Approach:
  • Plot global energy consumption year by year, broken down by energy source (e.g., coal, oil, natural gas, renewables).
  • Analyze growth rates in total energy consumption.
  • Investigate how the share of renewables has changed in the global energy mix.
• Potential Insights: This analysis can provide insight into which energy sources are becoming more dominant globally and how the energy landscape has shifted.

2. Energy Mix by Country

• Objective: Compare the energy mix of different countries.
• Approach:
  • For each country, visualize the breakdown of energy sources (e.g., renewables, fossil fuels) over time.
  • Analyze which countries have transitioned towards cleaner energy sources.
  • Compare the energy mix of developed vs. developing countries.
• Potential Insights: This could show which countries are leading in the transition to renewable energy and which are still reliant on fossil fuels.

3. Electricity Generation Sources by Region

• Objective: Explore regional differences in electricity generation.
• Approach:
  • Compare regions based on the percentage of electricity generated from different sources (e.g., coal, hydro, wind, solar).
  • Analyze trends in renewable electricity generation by region.
• Potential Insights: This analysis can identify regions that have made the most progress in transitioning to cleaner electricity sources.

4. Energy Consumption Per Capita

• Objective: Investigate energy consumption on a per capita basis.
• Approach:
  • Calculate the per capita energy consumption for different countries and regions.
  • Compare energy consumption per capita over time.
  • Identify which countries have the highest and lowest per capita energy consumption.
• Potential Insights: This can help uncover disparities in energy access and usage between different countries or regions.

5. Energy Consumption and Economic Growth

• Objective: Analyze the relationship between energy consumption and GDP.
• Approach:
  • Plot energy consumption per capita vs. GDP per capita for different countries and regions.
  • Look for correlations between energy consumption growth and economic growth.
  • Explore how energy consumption patterns differ between high-income and low-income countries.
• Potential Insights: This analysis can highlight the role of energy in driving economic development and the efficiency of energy usage across income levels.

6. Carbon Emissions from Energy Sources

• Objective: Assess the impact of different energy sources on carbon emissions.
• Approach:
  • Calculate emissions based on the share of fossil fuels in the energy mix.
  • Analyze trends in carbon emissions as countries transition to cleaner energy sources.
  • Compare countries or regions with high fossil fuel dependency to those with higher renewable energy shares.
• Potential Insights: This analysis could highlight the environmental impact of different energy sources and track progress towards emissions reductions.

Citation

Hannah Ritchie, Pablo Rosado and Max Roser (2023) - “Energy” Published online at OurWorldinData.org. Retrieved from: https://ourworldindata.org/energy [Online Resource]

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

If this was helpful, a vote is appreciated ❤️ Thank you 🙂

Introduction

Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. It is a key metric for assessing population health.

Life expectancy has burgeoned since the advent of industrialization in the early 1900s and the world average has now more than doubled to 70 years. Yet, we still see inequality in life expectancy across and within countries. The study by Acemoglu and Johnson demonstrated the relationship between increased life expectancy and improvement in economic growth (GDP per capita), controlling for country-fixed effects [3]. In the table below, we have shown how life expectancy varies between high-income and low-income countries. However, further analysis is necessary to determine how the allocation of a country’s wealth through certain investments in healthcare, education, environmental management, and some socioeconomic factors have an overall effect in determining average life expectancy.

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The Sub-Saharan African region experiences the lowest life expectancy at birth compared to other regions over the past 3 decades. SSA countries have consistently ranked as the lowest-earning countries in terms of GDP per capita. Therefore, there is a huge scope for improvement in life expectancy in SSA countries and hence our research focuses on the 40 Sub-Saharan African (SSA) countries with the lowest GDP per capita

Research Questions

After reviewing the rich existing literature on Life Expectancy, we realized the lack of concrete research on understanding the impact of all-encompassing determinants that cover socio-economic and environmental factors for SSA countries using Panel Data techniques. Hence, we tried to address this inadequacy through our research. In this paper, we aim to have a better understanding of factors affecting life expectancy in the SSA region for an efficient policy-making process and better allocation of funds and resources in addressing the prevalence of low life expectancy in Sub-Saharan Africa. To achieve that we attempt to answer the following questions in this research:

1. What’s the Impact of Expenditure on Health and Education (% of GDP) on Life Expectancy?
2. How does the prevalence of undernourishment and communicable disease Affect Life Expectancy?
3. Do factors like corruption and unemployment rate impact life expectancy? If yes, quantify
4. Increase in CO2 emissions decrease life expectancy? Is it significant?

Data

Main sources of data - World Bank Open Data & Our World in Data

1. Country - 174 countries - list

2. Country Code - 3-letter code

3. Region - region of the world country is located in

4. IncomeGroup - country's income class

5. Year - 2000-2019 (both included)

6. Life expectancy - data

7. Prevalence of Undernourishment (% of the population) - Prevalence of undernourishment is the percentage of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normally active and healthy life

8. Carbon dioxide emissions (kiloton) - Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during the consumption of solid, liquid, and gas fuels and gas flaring

9. Health Expenditure (% of GDP) - Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT, and stocks of vaccines for emergencies or outbreaks

10. Education Expenditure (% of GDP) - General government expenditure on education (current, capital, and transfers) is expressed as a percentage of GDP. It includes expenditures funded by transfers from international sources to the government. General government usually refers to local, regional, and central governments.

11. Unemployment (% total labor force) - Unemployment refers to the % share of the labor force that is without work but available for and seeking employment

12. Corruption (CPIA rating) - Transparency, accountability, and corruption in the public sector assets the extent to which the executive can be held accountable for its use of funds and for the results of its actions by the electorate and by the legislature and judiciary, and the extent to which public employees within the executive are required to...

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

Gross domestic product (GDP) is a measure for the economic activity. It refers to the value of the total output of goods and services produced by an economy, less intermediate consumption, plus net taxes on products and imports. GDP per capita is calculated as the ratio of GDP to the average population in a specific year. Basic figures are expressed in purchasing power standards (PPS), which represents a common currency that eliminates the differences in price levels between countries to allow meaningful volume comparisons of GDP. The values are also offered as an index calculated in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Please note that this index is intended for cross-country comparisons rather than for temporal comparisons. Finally, the disparities indicator offered for EU aggregates is calculated as the coefficient of variation of the national figures. This time series offers a measure of the convergence of economic activity between the EU Member States.

About this Dataset

This dataset contains 25 columns which are: 1. Country: Corresponding country. 2. Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population): Poverty in country. 3. Life expectancy at birth, total (years): Expected life from birth. 4. Population, total: Population of Country. 5. Population growth (annual %): Population growth each year. 6. Net migration: is the difference between the number of immigrants and the number of emigrants divided by the population. 7. Human Capital Index (HCI) (scale 0-1): is an annual measurement prepared by the World Bank. HCI measures which countries are best in mobilizing their human capital, the economic and professional potential of their citizens. The index measures how much capital each country loses through lack of education and health. 8. GDP (current US$)current US$constant US$current LCUconstant LCU: Gross domestic product is a monetary measure of the market value of all the final goods and services produced in a specific time period by a country or countries. 9. GDP per capita (current US$)current US$constant US$current LCUconstant LCU: the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output, divided by mid-year population. 10. GDP growth (annual %): The annual average rate of change of the gross domestic product (GDP) at market prices based on constant local currency, for a given national economy, during a specified period of time. 11. Unemployment, total (% of total labor force) (modeled ILO estimate) 12. Inflation, consumer prices (annual %) 13. Personal remittances, received (% of GDP) 14. CO2 emissions (metric tons per capita) 15. Forest area (% of land area) 16. Access to electricity (% of population) 17. Annual freshwater withdrawals, total (% of internal resources) 18. Electricity production from renewable sources, excluding hydroelectric (% of total) 19. People using safely managed sanitation services (% of population) 20. Intentional homicides (per 100,000 people) 21. Central government debt, total (% of GDP) 22. Statistical performance indicators (SPI): Overall score (scale 0-100) 23. Individuals using the Internet (% of population) 24. Proportion of seats held by women in national parliaments (%) 25. Foreign direct investment, net inflows (% of GDP): is when an investor becomes a significant or lasting investor in a business or corporation in a foreign country, which can be a boost to the global economy.

Category

Economic

Keywords

Row Count

217

Price

$5.50

** Content**

% of population living in households with an income or consumption per person below $10 a day.

The data is measured in international-$ at 2021 prices – this adjusts for inflation and for differences in living costs between countries.

Depending on the country and year, the data relates to income (measured after taxes and benefits) or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).

Non-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.

Regional and global estimates are extrapolated up until the year of the data release using GDP growth estimates and forecasts

For most countries in the PIP dataset, estimates relate to either disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making.

Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013, amended by Council Regulation (EU) 2023/734 of 15 March 2023.

Gross domestic product (GDP) is one of the key aggregates in the European system of accounts (ESA). GDP is a measure of the total economic activity taking place on an economic territory which leads to output meeting the final demands of the economy.

There are three ways of measuring GDP at market prices:

1. the production approach, as the sum of the values added by all activities which produce goods and services, plus taxes less subsidies on products;
2. the expenditure approach, as the total of all final expenditures made in either consuming the final output of the economy, or in adding to wealth, plus exports less imports of goods and services;
3. the income approach, as the total of all incomes earned in the process of producing goods and services plus taxes on production and imports less subsidies.

Data published in the following tables reflect these 3 approaches.

Breakdowns provided are based on the ESA Transmission Programme, which list all tables requested from the countries.

The annual tables under this collection are the following:

• nama_10_gdp GDP and main components (output, expenditure and income)
• nama_10_pc Main GDP aggregates per capita
• nama_10_a10 Gross value added and income components by A*10 industry
• nama_10_a64 Gross value added and income components by A*64 industry

Geographical entities covered are the European Union, the euro area, EU Member States, EFTA countries and Candidate Countries. Data from other countries (e.g. US, Japan and other countries) are received via the OECD and IMF and published in Eurobase in the naid_10 collection.

Data sources: National Statistical Institutes, Eurostat (for European aggregates).

Time series data for the data Real Gross Domestic Product - Components - Current Local Curreny Unit (CLU) for the country Czechia. Indicator Definition:Real Private Sector Final Consumption Expenditure, Unadjusted, Domestic CurrencyThe indicator "Real Private Sector Final Consumption Expenditure, Unadjusted, Domestic Currency" stands at 2.41 Trillion as of 3/31/2025, the highest value since 12/31/2022. Regarding the One-Year-Change of the series, the current value constitutes an increase of 2.51 percent compared to the value the year prior.The 1 year change in percent is 2.51.The 3 year change in percent is -0.9201.The 5 year change in percent is -1.31.The 10 year change in percent is 16.84.The Serie's long term average value is 1.94 Trillion. It's latest available value, on 3/31/2025, is 24.02 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 3/31/1996, to it's latest available value, on 3/31/2025, is +80.86%.The Serie's change in percent from it's maximum value, on 12/31/2019, to it's latest available value, on 3/31/2025, is -1.63%.Indicator Definition:Real General Government Final Consumption Expenditure, Unadjusted, Domestic CurrencyThe indicator "Real General Government Final Consumption Expenditure, Unadjusted, Domestic Currency" stands at 1.03 Trillion as of 3/31/2025, the highest value at least since 6/30/1996, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 3.11 percent compared to the value the year prior.The 1 year change in percent is 3.11.The 3 year change in percent is 6.90.The 5 year change in percent is 12.26.The 10 year change in percent is 27.49.The Serie's long term average value is 0.807 Trillion. It's latest available value, on 3/31/2025, is 27.94 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 3/31/1996, to it's latest available value, on 3/31/2025, is +60.94%.The Serie's change in percent from it's maximum value, on 3/31/2025, to it's latest available value, on 3/31/2025, is 0.0%.Indicator Definition:Real Gross Fixed Capital Formation, Unadjusted, Domestic CurrencyThe indicator "Real Gross Fixed Capital Formation, Unadjusted, Domestic Currency" stands at 1.47 Trillion as of 3/31/2025, the lowest value since 6/30/2023. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -2.52 percent compared to the value the year prior.The 1 year change in percent is -2.52.The 3 year change in percent is 5.22.The 5 year change in percent is 9.30.The 10 year change in percent is 38.70.The Serie's long term average value is 1.07 Trillion. It's latest available value, on 3/31/2025, is 37.66 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 9/30/1999, to it's latest available value, on 3/31/2025, is +95.67%.The Serie's change in percent from it's maximum value, on 12/31/2023, to it's latest available value, on 3/31/2025, is -3.06%.Indicator Definition:Real Changes in Inventories, Unadjusted, Domestic CurrencyThe indicator "Real Changes in Inventories, Unadjusted, Domestic Currency" stands at -0.0063 Trillion as of 3/31/2025, the highest value since 3/31/2024. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.0231 Trillion compared to the value the year prior.The Serie's long term average value is 0.0315 Trillion. It's latest available value, on 3/31/2025, is -0.0378 Trillion lower, compared to it's long term average value.The Serie's change from it's minimum value, on 9/30/2024, to it's latest available value, on 3/31/2025, is +0.0473 Trillion.The Serie's change from it's maximum value, on 12/31/2022, to it's latest available value, on 3/31/2025, is -0.1684 Trillion.Indicator Definition:Net Trade is defined as exports minus imports (measured in local currency units (LCU)).The indicator "Net Trade (Current LCU)" stands at 0.2637 Trillion as of 3/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.0153 Trillion compared to the value the year prior.The Serie's long term average value is 0.12 Trillion. It's latest available value, on 3/31/2025, is 0.144 Trillion higher, compared to it's long term average value.The Serie's change from it's minimum value, on 12/31/2003, to it's latest available value, on 3/31/2025, is +0.3468 Trillion.The Serie's change from it's maximum value, on 12/31/2017, to it's latest available value, on 3/31/2025, is -0.0859 Trillion.