{"doc_desc":{"title":"WLD_2010_GCD_v01_M_v01_A_ESS","idno":"DDI_WLD_2010_GCD_v01_M_v01_A_ESS_FAO","producers":[{"name":"Development Data Group","abbr":"DECDG","affiliation":"World Bank","role":"Metadata producer"},{"name":"Statistics Division","abbr":"ESS","affiliation":"Food and Agriculture Organization of the United Nations","role":"Metadata adapted for FAM"}]},"study_desc":{"title_statement":{"idno":"WLD_2010_GCD_v01_M_v01_A_ESS","title":"Global Consumption Database 2010 (version 2014-03)"},"authoring_entity":[{"name":"World Bank, Development Data Group (DECDG)","affiliation":""}],"distribution_statement":{"contact":[{"name":"Data helpdesk","affiliation":"World Bank","email":"data@worldbank.org","uri":"https:\/\/data.worldbank.org\/about\/contact"}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]"},"study_info":{"keywords":[{"keyword":"Consumption","vocab":"","uri":""},{"keyword":"Expenditure","vocab":"","uri":""},{"keyword":"Consumption pattern","vocab":"","uri":""},{"keyword":"Consumption profile","vocab":"","uri":""},{"keyword":"Consumption share","vocab":"","uri":""},{"keyword":"Icp basic heading","vocab":"","uri":""}],"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.\n\nThe data file can be used for the production of the following tables (by urban\/rural and income class\/consumption segment):\n- Sample Size by Country, Area and Consumption Segment (Number of Households)\n- Population 2010 by Country, Area and Consumption Segment\n- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population\n- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population\n- Population 2010 by Country, Age Group, Sex and Consumption Segment\n- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million)\n- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million)\n- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million)\n- Household Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in Local Currency (Million)\n- Household Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in $PPP (Million)\n- Household Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in US$ (Million)\n- Household Consumption 2010 by Country, Product\/Service, Area and Consumption Segment in Local Currency (Million)\n- Household Consumption 2010 by Country, Product\/Service, Area and Consumption Segment in $PPP (Million)\n- Household Consumption 2010 by Country, Product\/Service, Area and Consumption Segment in US$ (Million)\n- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency\n- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$\n- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP\n- Per Capita Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in Local Currency\n- Per Capita Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in US$\n- Per Capita Consumption 2010 by Country, Category of Product\/Service, Area and Consumption Segment in $PPP\n- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency\n- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$\n- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP\n- Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent)\n- Consumption Shares 2010 by Country, Category of Products\/Services, Area and Consumption Segment (Percent)\n- Consumption Shares 2010 by Country, Product\/Service, Area and Consumption Segment (Percent)\n- Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)","coll_dates":[{"start":"2010","end":"2010","cycle":""}],"nation":[{"name":"Afghanistan","abbreviation":"AFG"},{"name":"Albania","abbreviation":"ALB"},{"name":"Armenia","abbreviation":"ARM"},{"name":"Azerbaijan","abbreviation":"AZE"},{"name":"Bangladesh","abbreviation":"BGD"},{"name":"Belarus","abbreviation":"BLR"},{"name":"Benin","abbreviation":"BEN"},{"name":"Bhutan","abbreviation":"BTN"},{"name":"Bolivia (Plurinational State of)","abbreviation":"BOL"},{"name":"Bosnia and Herzegovina","abbreviation":"BIH"},{"name":"Brazil","abbreviation":"BRA"},{"name":"Bulgaria","abbreviation":"BGR"},{"name":"Burkina Faso","abbreviation":"BFA"},{"name":"Burundi","abbreviation":"BDI"},{"name":"Cambodia","abbreviation":"KHM"},{"name":"Cameroon","abbreviation":"CMR"},{"name":"Cabo Verde","abbreviation":"CPV"},{"name":"Chad","abbreviation":"TCD"},{"name":"China","abbreviation":"CHN"},{"name":"Colombia","abbreviation":"COL"},{"name":"Congo","abbreviation":"COG"},{"name":"C\u00f4te d'Ivoire","abbreviation":"CIV"},{"name":"Democratic Republic of the Congo","abbreviation":"COD"},{"name":"Djibouti","abbreviation":"DJI"},{"name":"Egypt","abbreviation":"EGY"},{"name":"El Salvador","abbreviation":"SLV"},{"name":"Eswatini","abbreviation":"SWZ"},{"name":"Ethiopia","abbreviation":"ETH"},{"name":"Fiji","abbreviation":"FJI"},{"name":"Gabon","abbreviation":"GAB"},{"name":"Gambia","abbreviation":"GMB"},{"name":"Ghana","abbreviation":"GHA"},{"name":"Guatemala","abbreviation":"GTM"},{"name":"Guinea","abbreviation":"GIN"},{"name":"Honduras","abbreviation":"HND"},{"name":"India","abbreviation":"IND"},{"name":"Indonesia","abbreviation":"IDN"},{"name":"Iraq","abbreviation":"IRQ"},{"name":"Jamaica","abbreviation":"JAM"},{"name":"Jordan","abbreviation":"JOR"},{"name":"Kazakhstan","abbreviation":"KAZ"},{"name":"Kenya","abbreviation":"KEN"},{"name":"Kyrgyzstan","abbreviation":"KGZ"},{"name":"Lao People's Democratic Republic","abbreviation":"LAO"},{"name":"Latvia","abbreviation":"LVA"},{"name":"Lesotho","abbreviation":"LSO"},{"name":"Liberia","abbreviation":"LBR"},{"name":"Lithuania","abbreviation":"LTU"},{"name":"North Macedonia","abbreviation":"MKD"},{"name":"Madagascar","abbreviation":"MDG"},{"name":"Malawi","abbreviation":"MWI"},{"name":"Malaysia","abbreviation":"MYS"},{"name":"Maldives","abbreviation":"MDV"},{"name":"Mali","abbreviation":"MLI"},{"name":"Mauritania","abbreviation":"MRT"},{"name":"Mauritius","abbreviation":"MUS"},{"name":"Mexico","abbreviation":"MEX"},{"name":"Mongolia","abbreviation":"MNG"},{"name":"Montenegro","abbreviation":"MNE"},{"name":"Morocco","abbreviation":"MAR"},{"name":"Mozambique","abbreviation":"MOZ"},{"name":"Namibia","abbreviation":"NAM"},{"name":"Nepal","abbreviation":"NPL"},{"name":"Niger","abbreviation":"NER"},{"name":"Nigeria","abbreviation":"NGA"},{"name":"Pakistan","abbreviation":"PAK"},{"name":"Papua New Guinea","abbreviation":"PNG"},{"name":"Paraguay","abbreviation":"PRY"},{"name":"Peru","abbreviation":"PER"},{"name":"Philippines","abbreviation":"PHL"},{"name":"Republic of Moldova","abbreviation":"MDA"},{"name":"Romania","abbreviation":"ROU"},{"name":"Russian Federation","abbreviation":"RUS"},{"name":"Rwanda","abbreviation":"RWA"},{"name":"Sao Tome and Principe","abbreviation":"STP"},{"name":"Senegal","abbreviation":"SEN"},{"name":"Serbia","abbreviation":"SRB"},{"name":"Sierra Leone","abbreviation":"SLE"},{"name":"South Africa","abbreviation":"ZAF"},{"name":"Sri Lanka","abbreviation":"LKA"},{"name":"Tajikistan","abbreviation":"TJK"},{"name":"Tanzania","abbreviation":"TZA"},{"name":"Thailand","abbreviation":"THA"},{"name":"Timor-Leste","abbreviation":"TLS"},{"name":"Togo","abbreviation":"TGO"},{"name":"T\u00fcrkiye","abbreviation":"TUR"},{"name":"Uganda","abbreviation":"UGA"},{"name":"Ukraine","abbreviation":"UKR"},{"name":"Viet Nam","abbreviation":"VNM"},{"name":"Yemen","abbreviation":"YEM"},{"name":"Zambia","abbreviation":"ZMB"}],"geog_coverage":"All surveys used have a nationwide coverage.\n\t\t  \nFor all countries, estimates are provided at the national level and at the urban\/rural levels.\n\t\t  \nFor Brazil, India, and South Africa, data are also provided at the sub-national level (admin 1):\n- 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\n- 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\n- South Africa: Eastern Cape, Free State, Gauteng, Kwazulu Natal, Limpopo, Mpulamanga, Northern Cape, North West, Western Cape","analysis_unit":"Households","universe":"The universe of each survey is composed of ordinary households only. Institutional households (prisons, military barracks, hospitals, convents, and others) are not covered by household surveys. Homeless and nomadic populations and visitors present in a country during a survey are also excluded from the sample.","data_kind":"Data derived from survey microdata","notes":"The questionnaires collected information on the consumption patterns of products and services such as:\n- Bread and cereals\n- Meat\n- Fish and seafood\n- Milk, cheese, and eggs\n- Vegetables\n- Clothing\n- Water supply and miscellaneous services relating to the dwelling\n\nFor more information on the questionnaire coverage by country and category see the summary of survey questionnaire coverage of ICP\/COICOP categories document in the downloads section."},"method":{"data_collection":{"sampling_procedure":"The sample size for individual surveys ranges from less than 2000 households to more than 100 000.","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"Few developing countries conduct household consumption or expenditure surveys on an annual basis. International organizations recommend conducting such surveys every three or four years. The surveys used in the database were conducted between 2000 and 2010 (except the one for Djibouti, which was conducted in 1996); most were conducted during the period 2007-10. All data presented in the Global Consumption Database are as of 2010. When based on a survey conducted before 2010, the estimates were obtained by extrapolation, as described in the notes on the standardization of data (see Step 4).\n\nHousehold survey datasets are complemented by data on population, purchasing power parity (PPP) conversion factors, and average exchange rates obtained from the World Bank's World Development Indicators database.\n\nSince of the diversity of methods and instruments used by the surveys, comparability across countries is limited. Survey questionnaires are provided below as an important metadata component. Links are also provided to the microdata when available.\n\nFurthermore, since household surveys differ across countries in design, methodology, and timing, there are limits to the extent to which household data can be standardized after they have been collected. Comparisons of household data across countries and over time must therefore be done with caution.\n\nThe Global Consumption Database uses multiple types of surveys, depending on data availability-including household budget surveys, living standards measurement surveys, and various kinds of country-specific socioeconomic surveys. All these surveys measure consumption or expenditure at the household (not individual) level. But because the surveys are designed for different purposes (such as to measure poverty or to update the consumption basket used to compile consumption price indices), they may differ substantially in design and methodology.\n\nKey differences between surveys include these:\n- Duration of data collection. Some surveys collect data over a period of 12 months to account for seasonality and some over a shorter period (a few weeks or a few months).\n- Method for household reporting on consumption. Some surveys collect data on food and some non-food consumption using diaries in which households or individuals report daily on what they spend. However, most studies rely on the recall method, asking households to report what they recall spending over a certain period. The recall period varies across surveys and categories. For example, data might be collected on: spending on food for the past 7 days, the past 2 weeks, or a typical month; on education for the past 12 months or the last academic year; on rent, outpatient health services, clothing, and footwear for the past month or the past 4 weeks; on durable goods and hospitalization for the past 6 or 12 months. The choice of recall period may have a substantial effect on the levels of consumption reported. Longer recall periods for frequently purchased items typically produce lower levels of reported spending than shorter recall periods do.\n- Level of detail. Some survey questionnaires include a long, detailed list of goods and services while others provide a shorter, more aggregate list. Longer lists with a finer breakdown of categories typically generate higher estimates of consumption.\n- Method for estimating rental value of dwellings. In some countries, surveys ask households that own their home or occupy it for free to provide an estimate of the rental value of the dwelling. In others, surveys collect data on the characteristics of dwellings that can be used to impute the rental value of owner-occupied dwellings through hedonic regressions. And for still other countries it is not possible to measure the rental value of owner-occupied dwellings because the rental market is too limited. Because this rental value represents a substantial share of household expenditure, these differences have major implications for the calculation of household consumption aggregates and for the comparability of data across countries.\n- Method for estimating value of durable goods. Some surveys collect data on household expenditures on durable goods such as musical instruments. Others attempt to estimate the annual use value of these goods. Estimating the use value of a good requires data on its price and date of purchase or on its resale value, data that is not available in all surveys. This too affects the calculation of household consumption aggregates and the cross-country comparability of data.","cleaning_operations":"See the technical note on the standardization of survey data files for information on the standardization process employed to produce internationally comparable price levels, expenditure values, and Purchasing Power Parity (PPP) estimates."}},"data_access":{"dataset_availability":{"access_place":"","access_place_url":""}}},"schematype":"survey"}