• Consumption shares in selected non-essential products - World Bank Global Consumption Database

  • Entity Year Share of alcohol in total household consumption (World Bank Global Consumption Database) Share of games of chance in total household consumption (World Bank Global Consumption Database) Share of tobacco in total household consumption (World Bank Global Consumption Database) Share of non-essential products in total household (World Bank Global Consumption Database)
    Liberia 2010 1.27 0.0 0.19 1.46
    Montenegro 2010 1.1 0.24 2.68 3.02
    Morocco 2010 0.02 0.02 2.21 2.25
    Mozambique 2010 0.49 0.01 0.13 1.62
    Namibia 2010 1.89 0 0.2 1.08
    Nepal 2010 2.75 0 1.94 3.69
    Nicaragua 2010 0.42 0.08 0.46 1.96
    Niger 2010 0.02 0 1.9 1.92
    Nigeria 2010 0.45 0.02 0.02 0.48
    Pakistan 2010 0 0 1.1 1.1
    Mongolia 2010 1.96 0.0 1.86 2.82
    Moldova 2010 1.64 0.2 1.58 1.42
    Lithuania 2010 3.63 0.49 1.3 4.41
    Macedonia 2010 2.98 0.18 3.21 5.36
    Madagascar 2010 1.54 0.03 2.31 3.88
    Malawi 2010 1.01 0 0.14 1.15
    Maldives 2010 0 0 1.17 1.17
    Mali 2010 0.07 0.02 1.01 1.1
    Mauritania 2010 0 0 0.47 0.47
    Mauritius 2010 2.07 1.85 3.63 6.55
    Mexico 2010 0.2 0.05 0.1 0.35
    Papua New Guinea 2010 0.38 0.17 3.1 4.66
    Peru 2010 0.21 0 0.06 0.27
    Philippines 2010 1.68 0 1.01 2.69
    Tanzania 2010 2.33 0.0 1.59 3.93
    Thailand 2010 1.93 0.08 1.72 2.72
    Timor 2010 1.03 0.0 3.19 4.22
    Togo 2010 2.93 0.08 0.15 2.16
    Turkey 2010 0.28 0.09 5.69 5.06
    Uganda 2010 1.07 0.01 0.21 1.29
    Ukraine 2010 2.7 0.0 2.25 4.95
    Vietnam 2010 1.09 0.31 1.13 3.53
    Yemen 2010 0 0 1.43 1.43
    Tajikistan 2010 0.09 0.02 0.19 0.3
    Swaziland 2010 0.33 0.02 0.13 0.49
    Romania 2010 3.54 0.04 5.76 7.33
    Russia 2010 2.54 1.2 1.62 3.36
    Rwanda 2010 2.97 0 0.29 2.26
    Sao Tome and Principe 2010 3.4 1.91 0 4.31
    Senegal 2010 1.52 0.0 0.37 1.89
    Serbia 2010 1.48 0.15 4.52 5.15
    Sierra Leone 2010 1.22 0 2.78 3.01
    South Africa 2010 1.58 0.07 1.5 1.15
    Sri Lanka 2010 1.99 0.13 1.64 2.76
    Zambia 2010 1.3 0 0.12 1.43
    Afghanistan 2010 0 0 0.43 0.43
    Burkina Faso 2010 1.77 0.13 1.05 2.95
    Burundi 2010 4.6 0 0.34 4.94
    Cambodia 2010 1.12 0.08 1.01 2.21
    Cameroon 2010 3.99 0.06 0.23 3.29
    Cape Verde 2010 1.85 0.29 0.41 2.55
    Chad 2010 2.08 0.07 1.03 3.19
    China 2010 1.84 0.04 2.85 3.73
    Colombia 2010 1.78 0.28 0.2 1.26
    Congo 2010 1.07 0.17 0.19 1.44
    Bulgaria 2010 2.97 0.14 7.53 9.64
    Brazil 2010 0.4 0.28 1.68 1.36
    Albania 2010 1.06 0.01 2.01 3.07
    Armenia 2010 1.83 0.0 4.77 5.6
    Azerbaijan 2010 0.23 0.33 5.89 5.45
    Bangladesh 2010 0 0 1.26 1.26
    Belarus 2010 2.16 0.02 1.22 3.4
    Benin 2010 2.98 0.1 0 2.09
    Bhutan 2010 2.64 0 0.29 2.93
    Bolivia 2010 0.3 0.01 0.1 0.41
    Bosnia and Herzegovina 2010 1.1 0.29 2.12 4.51
    Cote d'Ivoire 2010 0.47 0.23 1.62 1.32
    Democratic Republic of Congo 2010 1.42 0.0 1.53 2.96
    Djibouti 2010 0 0 1.39 1.39
    Indonesia 2010 0.05 0.0 6.54 6.59
    Iraq 2010 0.03 0 1.75 1.77
    Jamaica 2010 1.59 0.3 0 1.88
    Jordan 2010 0.02 0 4.72 4.75
    Kazakhstan 2010 2.62 0 2.88 3.49
    Kenya 2010 1.35 0.0 1.5 2.85
    Kyrgyzstan 2010 1.58 0 1.66 1.24
    Laos 2010 1.32 0.2 1.69 2.21
    Latvia 2010 2.77 0.01 2.01 4.79
    India 2010 1.51 0 1.83 1.34
    Honduras 2010 0.37 0.15 0.47 1.0
    Egypt 2010 0.0 0 2.42 2.42
    El Salvador 2010 0 0.01 0 0.01
    Ethiopia 2010 1.81 0.01 0.18 1.0
    Fiji 2010 1.79 0.01 1.93 2.73
    Gabon 2010 1.37 0.14 0.36 2.87
    Gambia 2010 0.07 0 0.49 1.57
    Ghana 2010 2.55 0.22 0.13 2.9
    Guatemala 2010 0.41 2.18 0.19 3.78
    Guinea 2010 0.49 0.0 0.42 1.92
    Lesotho 2010 1.64 0.05 1.54 1.23
  • The Global Consumption Database is composed of individual country surveys to form a database on household consumption patterns in developing countries. The data has been standardized following a six-step process:

    Step 1: Annualizing consumption or expenditure data:

    In simple cases, this amounts to using a multiplying factor determined by the recall period (the period in which households are asked to recall their expenditure during that period). For example, food data collected for the last 7 days would be divided by 7, then multiplied by 365; monthly values by 12 etc.

    Step 2: Detecting and fixing outliers:

    Expenditure values were flagged to be outliers if they exceeded the average amount consumed in the third quartile plus 5 times the interquartile range (the difference between the first and third quartiles of the data).

    Any flagged values need to be confirmed before imputations are made. If three or more non-food values are flagged as outliers for a household, it was assumed this indicates a rich household; hence the flags were removed. Households in the top two consumption quintiles were also assumed to spend unusually large shares of their income on education and jewellery. Outlier values that did not fit either of these criteria were replaced with the weighted mean of the non-extreme values for the consumption variable in question.

    Step 3: Mapping commodities to the ICP/COICOP classification:

    Commodities found in each survey dataset were mapped to a standard classification of products and services, and then aggregate standard products and services into sectors and categories. This used the International Comparison Program (ICP) classification which is equivalent to the International Classification of Individual Consumption According to Purpose (COICOP).

    Step 4: Extrapolation to 2010:

    Extrapolations were undertaken to convert all consumption and population data to a common reference year, 2010. For example, for the 2007 survey conducted in Guinea: final consumption expenditure per capita in LCU was 3,177,774 in 2010 and 1,547,012 in 2007 (the survey year). All survey values were therefore multiplied by 3,177,774/1,547,012=2.054137.

    Consumption data were converted from local currencies to international dollars adjusted for purchasing power parity (PPP$).

    Step 5: Review and validation:

    Data was compared with other sources, notably the respective survey reports, and the World Bank’s poverty dataset, Povcalnet.

    Step 6: Production of summary tables and metadata:

    The World Bank generated of a standard set of tables for each country showing consumption and demographic patterns across consumption segments.

    For more information on the Global Consumption Database methodology see: http://datatopics.worldbank.org/consumption/detail under the ‘Standardization of Data’ tab.

    As the World Bank’s Global Consumption Database draws on a variety of country surveys which differ in design, methodology, and timing, there are limits to the extent to which surveys can be standardized. Therefore, cross-country comparisons should be made with caution. For more information see http://datatopics.worldbank.org/consumption/detail under the ‘Note on comparability’ tab.

    All figures reported are based on national totals. The World Bank notes “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.”

    The surveys used in the database were conducted between 2000 and 2010. For more information see http://datatopics.worldbank.org/consumption/detail under the ‘Sources of Data’ tab.

  • Sources

    Data Published By: World Bank Global Consumption Database

    Data publisher source: National household consumption or expenditure survey datasets. For a comprehensive list see: http://datatopics.worldbank.org/consumption/detail under 'Sources of Data' tab.

    Link: http://datatopics.worldbank.org/consumption/

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