Wages in Tanzania increased to 362400 TZS/Month in 2016 from 353589 TZS/Month in 2015. This dataset provides the latest reported value for - Tanzania Monthly Average Wages in Private Sector - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The national gross income per capita in Tanzania saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 1,220 U.S. dollars. Nevertheless, 2023 still represents a peak in the national gross income in Tanzania with 1,220 U.S. dollars. Gross national income (GNI) per capita is the total amount of money received by a country (regardless of whether it originates in the country or abroad) divided by the midyear population. The World Bank uses a conversion system known as the Atlas method, which uses a price adjusted, three year moving average, which smooths out exchange rate fluctuations.Find more key insights for the national gross income per capita in countries like Kenya and Mozambique.

Minimum Wages in Tanzania remained unchanged at 60000 TZS/Month in 2025 from 60000 TZS/Month in 2024. This dataset includes a chart with historical data for Tanzania Minimum Wages.

Tanzania TZ: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.000 % in 2011. This records a decrease from the previous number of 13.200 % for 2007. Tanzania TZ: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 12.300 % from Dec 1991 (Median) to 2011, with 4 observations. The data reached an all-time high of 13.200 % in 2007 and a record low of 9.000 % in 2011. Tanzania TZ: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Tanzania TZ: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data was reported at 17.770 % in 2017. This records an increase from the previous number of 17.748 % for 2016. Tanzania TZ: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data is updated yearly, averaging 14.312 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 23.127 % in 2013 and a record low of 7.405 % in 1996. Tanzania TZ: Wage And Salary Workers: Modeled ILO Estimate: Male: % of Male Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank: Employment and Unemployment. Wage and salaried workers (employees) are those workers who hold the type of jobs defined as 'paid employment jobs,' where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

Abstract

The EESs are conducted by the National Bureau of Statistics (NBS), as mandated by Statistics Act 2015, which empowers NBS to collect, compile and disseminate official statistics in the country. The summary is presented for the six main topical areas namely:- Employment Profile; Wage Rates Profile; Cash Earnings Profile; Annual Wage Bill Profile; Newly Recruited Workers; and Job Vacancies.

Employment Profile

The findings on employment profile reveal an increase in total employment in the formal sector from 2,334,969 employees in 2015 to 2,599,311 employees in 2016; which is an increase of 308,951 employees. The majority of employees are employed in the private sector (1,748,695 private and 850,616 public). Proportion of regular employment has increased from 88.2 percent in 2015 to 92.9 percent in 2016, while casual employment has decreased from 11.8 percent in 2015 to 7.1 under the same span of time. Education industry had the largest share of total employment with 18.5 percent followed by manufacturing industry (18.1 percent); and public administration and defence, compulsory social security industry with 13.6 percent of total employment. It is also indicated that there are more adult employees under regular employment (63.2 percent) compared to youth employees who accounted for 36.8 percent of the total regular employees. With regard to disability status, the results indicate that, there were 3,935 employees (about 0.2 percent of total employment in the formal sector) with various types of disabilities. The results also show that, Dar es Salaam region had the largest proportion of employment, with 31.2 percent of all employees, followed by Morogoro region (10.9 percent) and Arusha region (6.8 percent).

Wage Rates Profile

Regarding the wage rates of employees in the formal sector, the findings show that, overall in 2016, majority of citizen employees (22.9 percent) earned monthly wages between TZS 500,001 and 900,000. In the private sector however, there were more citizen employees in lower wage rates with 17.8 percent earning monthly wages between TZS 150,001 and 300,000 and 14.6 percent earning between TZS 100,001 and 150,000. For the public sector, about 15.3 percent of citizen employees earned between TZS 500,001 and 900,000 and about 8.1 percent earned monthly wages between TZS 300,001 and TZS 500,000. The findings also reveal that, about 4.5 percent of all citizen employees earned TZS 1,500,000 or above, with a slightly larger proportion in the private sector (2.7 percent) than public sector (1.8 percent). Financial and insurance activities had the highest proportion of employees (33.3 percent) earning wages above TZS 1,500,000 followed by information and communication industry (22.1 percent). Conversely, construction, wholesale and retail trade and repair of motor vehicles and motorcycles activities had larger proportions of their employees in lower wage rates between TZS 150,001 and 300,000.

Cash Earnings Profile

The findings indicate that, overall monthly average cash earnings for employees in the formal sector surged up slightly from TZS 403,729 in 2015 to TZS 448,462 in 2016. Monthly cash earnings in the public sector increased from TZS 1,063,064 in 2015 to TZS 1,243,945 in 2016, whereas in the private sector it increased slightly from TZS 353,589 to 362,400. The results boldly note that, on average, cash earnings for employees in the public sector were three times as much as that of the private sector. In addition, analysis of monthly cash earnings by sector reveals that, parastatal organizations had the highest monthly average cash earnings of TZS 1,452,326, while profit making institutions had the lowest monthly average cash earnings of TZS 339,229. It is also found that in 2016, financial and insurance activities had the highest monthly average cash earnings of TZS 1,388,070 followed by public administration and defense; compulsory social security with TZS 1,292,652.

Annual Wage Bill Profile

Analysis on annual wage bill indicates that, overall, employers in public and private sectors had collective annual wage bill of TZS 23,637 billion in 2016, with employers in private sector having higher annual wage bill than in the public sector. The largest annual wage bills were incurred by employers in private profit- making institutions amounting to TZS 9,536 billion followed by employers in private nonprofit -making institutions with TZS 5,295 billion. Employers in parastatal institutions, including both non - profit and profit - making institutions had relatively smaller annual wage bills of TZS 662 billion and TZS 236 billion respectively. Results on annual wage bill by industry indicates that, the largest proportion of wage bill were in the education industry with 20.4 percent. Public administration and defence; compulsory social security had the second largest annual wage bill of 16.6 percent.

Newly Recruited Workers

The findings on the newly recruited workers reveal that, total number of newly recruited workers in 2016 was 69,639 of which 34,594 employees filled newly created posts and 35,045 employees filled existing vacancies. The findings also indicate that, among the newly recruited employees, there were more females (19,433) than males (15,161). On the other hand, private sector had more new recruits with 51,251 employees compared to public sector with 18,388. It is further indicated that, occupations of service workers and shop sales workers; and technicians and associate professionals had larger number of new recruits with 15,515 employees and 15,346 employees, respectively. With regard to education qualification, the findings indicate that, number of males with tertiary education are more in the new recruits (8,279 employees) equivalent to 23.7 percent compared to female comprised of 4,559 employees (about 13.2 percent). Moreover, it is established that, out of the total number of newly recruited employees, the largest proportion, 66.4 percent (46,262 employees) were employed on permanent basis followed by 25.3 percent (17,615 employees) who were engaged on contractual basis. Job Vacancies Analysis for job openings in the formal sector shows that, the largest proportion of job vacancies in 2015/16 (63.6 percent) were for technicians and associate professionals, followed by professionals (21.6 percent). The remaining occupations each had less than 5 percent of the total job vacancies. The majority of these jobs, (85.3 percent) did not require any working experience. Vacancies that required prior working experiences of 1-2 and 3-4 years constituted about 10.6 percent and 2.8 percent respectively. The findings also reveal that, the largest proportion of the reported vacancies (93.3 percent) did not attach any sex preference for the potential candidates. However, 4.4 percent of vacancies preferred male employees compared to 2.3 percent which preferred female employees.

Geographic coverage

Tanzania Mainland Regions

Analysis unit

Formal Establishment.

Universe

The survey covers formal establishments with employees in both private and public sectors. The establishments are divided into three main categories which are all public -sector establishments, all registered private establishments employing at least 50 persons and a sample of all registered private establishments whose number of employees are from 5 to 49 persons.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Employment and Earnings Survey 2016 is an establishment- based survey covering a total of 9,628 establishments from a frame of 68,119 establishments. This frame consists of all public establishments and formal private establishments employing 5 persons and above.

As in previous surveys, the sampling unit of this survey is an establishment which is defined as a legal economic entity engaging itself in one main kind of economic activity at a fixed location. The EES 2016 covered formal establishments in both private and public sectors in Tanzania Mainland in such a way that they formed a representative sample, reflecting the level and magnitude of the economic activities within their respective industrial groups. The EES sample was based on a sampling frame obtained from the Central Register of Establishments (CRE) developed and maintained by NBS. The existing sampling frame was developed on the basis of International Standard Industrial Classification Revision 4 (ISIC Rev.4).

The survey covered all public -sector establishments and private sector establishments with at least 50 employees. Furthermore, the survey covered a sample of private establishments employing 5 to 49 persons. The sampling for this group involved stratifying establishments into those with 5 to 9 employees and those with 10 to 49 persons. Establishments in these strata were further stratified on the basis of their economic activities and ultimately a single stage sampling technique was used to derive representative establishments from each activity using the probability proportion to size (PPS).

Mode of data collection

Face-to-face [f2f]

Research instrument

The establishment based questionnaires were developed in English, and were translated into Kiswahili Language.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry. c) Structural checking of SPSS data files.

Response rate

90.8

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling

As of 2023, Rwanda had the lowest average monthly salary of employees in the world in terms of purchasing power parities (PPP), which takes the average cost of living in a country into account. Gambia had the second lowest average wages, with Ethiopia in third. Of the 20 countries with the lowest average salaries in the world, 17 were located in Africa. On the other hand, Luxembourg had the highest average monthly salaries of employees.

As of 2022, Seychelles was the African country with the highest estimated minimum gross monthly wage, standing at ****** U.S. dollars. It was followed by Morocco at ****** U.S. dollars and South Africa ****** U.S. dollars. Among the selected nations, only **** countries had a minimum wage above *** U.S. dollars on the continent. Minimum wage adjustments Legislations regarding minimum wages vary significantly across countries. The minimum remuneration of employees is usually proportionate to a specific area's cost of living. Determining a minimum wage aims to increase employees' living conditions while reducing poverty and inequality. Due to rising prices and inflation, governments occasionally adjust the minimum salary. In Africa, Sierra Leone experienced the highest increase in the minimum wage in recent years, with a growth of almost ** percent between 2010 and 2019. However, governments can also lower minimum wages. Liberia and Burundi reduced the lowest possible remuneration by around ** percent and ***** percent, respectively, between 2010 and 2019. Widespread informal employment Despite legislation in force, minimum wages are not always guaranteed. In fact, several forms of employment allow employers to avoid paying minimum wages. In addition, undeclared work remains a common practice in many countries worldwide. The situation is particularly critical in some African countries. According to estimates, over ** percent of the working population in Niger, The Democratic Republic of Congo, Benin, and Madagascar engaged in informal employment between 2019 and 2023. In Egypt and South Africa, the share stood at ** percent and ** percent, respectively. Seychelles had the lowest rate on the continent at around ** percent.

Tanzania: Income from natural resources, percent of GDP: The latest value from 2021 is 6.69 percent, an increase from 3.85 percent in 2020. In comparison, the world average is 6.83 percent, based on data from 186 countries. Historically, the average for Tanzania from 1988 to 2021 is 6.82 percent. The minimum value, 3.53 percent, was reached in 2019 while the maximum of 14.05 percent was recorded in 1995.

Tanzania TZ: Number of People Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure data was reported at 1,218,000.000 Person in 2012. This records an increase from the previous number of 769,000.000 Person for 2010. Tanzania TZ: Number of People Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure data is updated yearly, averaging 885,000.000 Person from Dec 2008 (Median) to 2012, with 3 observations. The data reached an all-time high of 1,218,000.000 Person in 2012 and a record low of 769,000.000 Person in 2010. Tanzania TZ: Number of People Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank: Poverty. Number of people spending more than 25% of household consumption or income on out-of-pocket health care expenditure; ; Wagstaff et al. Progress on catastrophic health spending: results for 133 countries. A retrospective observational study, Lancet Global Health 2017.; Sum;

In 2023, the national gross income per capita in Kenya decreased by 60 U.S. dollars (-2.76 percent) compared to 2022. Nevertheless, the last two years recorded a significantly higher national gross income than the preceding years.Gross national income (GNI) per capita is the total value of money received by a country, from both domestic or foreign sources, divided by the midyear population. The World Bank uses a conversion system known as the Atlas method, which implements a price adjusted, three year moving average, smoothing out fluctuations in exchange rates.Find more key insights for the national gross income per capita in countries like Tanzania and Mozambique.

Abstract

The main objective of the 2013 Employment and Earnings Survey was to obtain comprehensive data on the annual status of employment and earnings as well as data on the socio-economic characteristics of the labour market.

Geographic coverage

Tanzania Mainland Regions

Analysis unit

Establishment

Universe

Formal establishments of both public and private sectors

Kind of data

Sample survey data [ssd]

Sampling procedure

Employment and Earnings Survey 2013 sample was based on a sampling frame obtained from the Central Register of Establishments (CRE) maintained by the NBS. The existing sampling frame was developed on the basis of International Standard Industrial Classification Revision 4 (ISIC Rev.4). 10

Employment and Earnings Survey 2013 covered all establishments of public and all private sector establishments employing at least 50 employees. For all private sector establishments employing 5 - 49 employees, multistage sampling technique was used. The first stage within a region included stratification of all private establishments employing 5 - 49 employees into two strata namely 5 - 9 employees and 10 - 49 employees. Then, the sample size for each stratum was developed in each region. Finally, probability proportional to size (PPS) was used to draw the sample within each industry.

A similar approach was used in all the 25 regions to draw the sample size across all industrial major divisions in the two strata separately to enhance representation of all economic activities to the economy.

Sampling deviation

No deviation from the sample

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Annual Employment and Earnings Survey uses an English Questionnaire which devided into several sections namely, Identification, Regular Employees. Employment and Earnings, Casual Workers, Number of Workers Recruited during the last 12 Months and Job Vacancies.

Cleaning operations

After questionnires received to Head Quarters, Labour and Price Statistics Department recruits temporary editors for editing and coding the filled questionnaires before data entered to the computer to continue with further data processing steps. Completion of data entry followed by computer data editing for consistent and data entry error checks.

Response rate

The accuracy of the statistical data provided in the tables is dependent on the rate of response, especially where a few establishments are dominant in the industry. On average, the response rate was about 89.2% for Employment and Earnings Survey 2013.

Sampling error estimates

No sampling errorestimates

Data appraisal

No Forms of other Data Appraisal

The national gross income per capita in Mozambique increased by 40 U.S. dollars (+8 percent) in 2023 in comparison to the previous year. In total, the national gross income amounted to 540 U.S. dollars in 2023. Gross national income (GNI) per capita is the total amount of money received by a country (regardless of whether it originates in the country or abroad) divided by the midyear population. The World Bank uses a conversion system known as the Atlas method, which uses a price adjusted, three year moving average, which smooths out exchange rate fluctuations.Find more key insights for the national gross income per capita in countries like Tanzania and Kenya.

The gross domestic product (GDP) per capita in Tanzania was estimated at about 1.23 thousand U.S. dollars in 2024. Between 1980 and 2024, the GDP per capita rose by approximately 626.12 U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The GDP per capita will steadily rise by around 500.44 U.S. dollars over the period from 2024 to 2030, reflecting a clear upward trend.This indicator describes the gross domestic product per capita at current prices. Thereby, the gross domestic product was first converted from national currency to U.S. dollars at current exchange rates and then divided by the total population. The gross domestic product is a measure of a country's productivity. It refers to the total value of goods and service produced during a given time period (here a year).

Tanzania TZ: Wage And Salaried Workers: Modeled ILO Estimate: % of Total Employment data was reported at 13.684 % in 2017. This records an increase from the previous number of 13.663 % for 2016. Tanzania TZ: Wage And Salaried Workers: Modeled ILO Estimate: % of Total Employment data is updated yearly, averaging 10.017 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 17.527 % in 2013 and a record low of 4.854 % in 1993. Tanzania TZ: Wage And Salaried Workers: Modeled ILO Estimate: % of Total Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Employment and Unemployment. Wage and salaried workers (employees) are those workers who hold the type of jobs defined as 'paid employment jobs,' where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

Abstract

The Household Budget Survey (HBS) was carried out to get information from private households on economic activities, household income, expenditure, housing characteristics as well as asset ownership. HBS outlined the final poverty statistics for 2011/12. The aspect of comparison of poverty trends with previous HBS's was presented in the survey taking into account the improvements that were made to the HBS 2011/12.The basic needs approach is used to measure absolute poverty in mainland Tanzania . The data collection for the survey lasted for a period of one year and covered 10,400 randomly selected households in mainland Tanzania. The survey was carried out by the National Bureau of Statistics (NBS) in collaboration with the Poverty Eradication Division in the Ministry of Finance in Mainland Tanzania.

The objectives of the HBS included: 1. To acquire data on households levels of consumption and expenditure which can be used for poverty mapping and analyzing the changes in standard of living over time when HBS is repeated. 2. To constitute a platform in order to specify a set of basic economic and social welfare indicators to be monitored at regular time intervals. 3. To obtain macro estimates of household consumption and expenditure patterns to construct the weighting system for the Consumer Price Index (CPI) 4. To provide macroeconomic estimates, on the household consumption for the National Accounts. 5. To obtain household consumption and expenditure patterns to make market analysis. 6. Ownership of durable goods and income generating facilities 7. To obtain data on non-expenditure consumption, i.e. consumption of own production, payments in kind and barter, which can only be measured by a survey like HBS.

Geographic coverage

National Coverage

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Budget Survey (HBS) was administered to a representative sample of households. A total of 10,400 households were selected and 10,186 households completed the interview. The survey was based on the 2002 Population and Housing Census (PHC) frame. Sampling weights were used to make estimates representative of population. This survey provided estimates for mainland Tanzania as a whole. A stratified multi-stage sample design was used for this survey. At the first stage the primary sampling units (PSUs) selected 400 enumeration areas (EAs). At the second stage the EAs had an average of 133 households each, (155 for rural EAs and 94 for urban EAs), this was an effective size for conducting a new listing of households. In each enumeration area 26 households were covered for one year.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HBS was comprised of a set of survey instruments. These were the following questionnaires: 1. Individual Demographics Questionnaire 2. Dwelling and Household Expenditure Questionnaire 3. Labor Status and Individual Questionnaire 4. Agriculture, Land and Livestock Questionnaire 5. Household Diary Questionnaire 6. Sheet for recording Purchase Questionnaire 7. Data Dictionary Questionnaire 8. Enumeration Area Questionnaire

Tanzania TZ: Households: Gross Disposable Income data was reported at 6,573,877.320 TZS mn in Dec 2015. This records a decrease from the previous number of 6,688,497.802 TZS mn for Sep 2015. Tanzania TZ: Households: Gross Disposable Income data is updated quarterly, averaging 6,731,337.322 TZS mn from Mar 2015 (Median) to Dec 2015, with 4 observations. The data reached an all-time high of 6,986,663.993 TZS mn in Mar 2015 and a record low of 6,573,877.320 TZS mn in Dec 2015. Tanzania TZ: Households: Gross Disposable Income data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Tanzania – Table TZ.IMF.FSI: Sectoral Financial Statement: Income and Expense: Quarterly.

Tanzania TZ: Adjusted Net National Income per Capita: USD: 2015 Price data was reported at 870.917 USD in 2020. This records a decrease from the previous number of 889.173 USD for 2019. Tanzania TZ: Adjusted Net National Income per Capita: USD: 2015 Price data is updated yearly, averaging 572.838 USD from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 889.173 USD in 2019 and a record low of 286.866 USD in 1993. Tanzania TZ: Adjusted Net National Income per Capita: USD: 2015 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Gross Domestic Product: Real. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.;World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).;Weighted average;

Tanzania TZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 1.430 Intl $/Day in 2018. This records a decrease from the previous number of 1.440 Intl $/Day for 2011. Tanzania TZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 1.435 Intl $/Day from Dec 2011 (Median) to 2018, with 2 observations. The data reached an all-time high of 1.440 Intl $/Day in 2011 and a record low of 1.430 Intl $/Day in 2018. Tanzania TZ: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.