The gross national income (GNI) per capita in Ghana reached 2,340 U.S. dollars in 2023, decreasing by 40 U.S. dollars from the preceding year. Generally, the GNI per capita increased in the country compared to 2010, when it stood at 1,200 U.S. dollars.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Key information about Ghana Household Expenditure per Capita

• Ghana Annual Household Expenditure per Capita reached 1,161.488 USD in Dec 2018, compared with the last update number of 1,648.827 USD in Dec 2013.
• Ghana Annual Household Expenditure per Capita data is updated yearly, available from Dec 2006 to Dec 2018, with an averaged value of 1,161.488 USD.
• The data reached an all-time high of 1,648.827 USD in Dec 2013 and a record low of 1,008.625 USD in Dec 2006.

Ghana GH: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 20.600 % in 2016. This records an increase from the previous number of 18.000 % for 2012. Ghana GH: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 16.300 % from Dec 1987 (Median) to 2016, with 7 observations. The data reached an all-time high of 20.600 % in 2016 and a record low of 13.000 % in 1988. Ghana GH: 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 Ghana – Table GH.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).

Abstract

The Annual Household Income and Expenditure Survey (AHIES) is the first nationally representative high-frequency household panel survey in Ghana. The AHIES is being conducted to obtain quarterly and annual data on household final consumption expenditure and a wide scope of demographic, economic and welfare variables including statistics on labour, food security, multi-dimensional poverty and health status for research, policy, and planning. Some of the key macroeconomic indicators to be generated include quarterly GDP, regional GDP, quarterly unemployment, underemployment, inequality, consumption expenditure poverty, multidimensional poverty and food security. The data from the AHIES is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various development programs at the national and community levels and also to monitor targets under the Sustainable Development Goals.

Geographic coverage

Nation - Wide

Analysis unit

Individuals, Households

Universe

The universe covers the population living within individual households in Ghana. However, such population which is defined as institutionalised population as persons living at elderly houses, rest homes, correction facilities, military baracks, and hospitals with special characteristics, nursery,and also nomadic population are excluded.

Sampling procedure

With the sampling procedure, 10,800 households in 600 EAs, consisting of 304 (50.67%) urban and 296 (49.33%) rural households were drawn from the 2021 Population and Housing Census listing frame to form the secondary sampling units. A random sampling methodology was adopted to select eighteen (18) households per selected EAs in all regions to form the full sample for the fieldwork to be able to produce regionally representative expenditures for GDP.

Mode of data collection

Computer Assisted Personal Interview [CAPI]

Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at -0.200 % in 2016. Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging -0.200 % from Dec 2016 (Median) to 2016, with 1 observations. Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. 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. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Abstract

The Ghana Living Standards Survey (GLSS), with its focus on the household as a key social and economic unit, provides valuable insights into living conditions in Ghana. The survey was carried out by the Ghana Statistical Service (GSS) over a 12-month period (April 1998 to March 1999). A representative nationwide sample of more than 5,998 households, containing over 25,000 persons, was covered in GLSS IV.

The fourth round of the GLSS has the following objectives: · To provide information on patterns of household consumption and expenditure disaggregated at greater levels. · In combination with the data from the earlier rounds to serve as a database for national and regional planning. · To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country. · To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender.

Additionally, the survey will enable policy-makers to · Identify vulnerable groups for government assistance; · Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households; · Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

A nationally representative sample of households was selected in order to achieve the survey objectives. For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.

In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.

A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected. It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households. At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labor force focus of the survey.

NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because: - given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates. - The listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main questionnaire used in the survey was the household questionnaire. In addition to this, there were community and Price questionnaires.

• Household Questionnaire: The household questionnaire was used to collect information on various topics some of which pertain to eligible individual household members. The questionnaire is in two parts, A and B.
• Community Questionnaire: The main aim of the community questionnaire was is to identify the economic infrastructure, education and health facilities existing in the villages, as well as any related problems that affects their welfare. The questionnaire was administered in the rural EAs only.
• Price Questionnaire: As part of the survey a price questionnaire was designed to collect prices of most essential commodities in the local markets.

Cleaning operations

Training: The project had 3 experienced computer programmers responsible for the data processing. Data processing started with a 2-weeks training of 15 data entry operators out of which the best 10 were chosen and 2 identified as standby. The training took place one week after the commencement of the fieldwork.

Data entry: Each data entry operator was assigned to one field team and stationed in the regional office of the GSS. The main data entry software used to capture the data was IMPS (Integrated Microcomputer Processing System). The data capture run concurrently as the data collection and lasted for 12 months.

Tabulation/Analysis: The IMPS data was read into SAS (Statistical Analysis System), after which the analysis and generation of the statistical tables were done using SAS.

Response rate

Out of the selected 6000 households 5999 were successfully interviewed. One household was further dropped during the data cleaning exercise because it had very few records for many of the sections in the questionnaire. This gave 5998 household representing 99.7% coverage. Overall, 25,694 eligible household members (unweighted) were covered in the survey.

Developing countries generally exhibit low ‘saving’ (flow concept) and ‘savings’ (stock concept) rates. The factors underlying household positive or negative saving behaviours in developed and developing countries are not new in the macroeconomic literature. Whereas some determinants are theoretically generic, others are country- or community-specific and worth investigating. In this study, the determinants of household saving behaviour are examined. We obtain the results using primary data from a household survey and a logit econometric model with its associated average marginal effects. Our evidence shows that household income, level of education completed, employment status, and households with launching children (or transitioning older adults) are primary drivers of household saving behaviour in Ghana. Further heterogeneous analysis shows that saving behaviour does not statistically differ by gender but by poverty headcount. In line with the findings of this study, relevant policy prescriptions are discussed. This study contributes to the ongoing discourse on household saving behaviour, specifically within the context of developing countries, by providing empirical evidence from Ghana. Utilising primary household survey data, the research identifies key factors such as income, education level, employment status, and household lifecycle stages (e.g., families with launching children or transitioning older adults) as critical determinants of saving behaviour. The findings offer actionable insights for policymakers in developing economies aiming to boost saving rates, reduce poverty, and promote financial stability. By demonstrating that household saving behaviour varies by poverty headcount rather than gender, the study underscores the need for targeted financial inclusion and education policies. The results are particularly relevant for economic development strategies in countries with similar socio-economic structures, offering a foundation for tailored interventions that can foster more resilient household financial practices. This paper’s insights can shape future research and policy development aimed at addressing the unique saving dynamics in developing nations, ultimately contributing to improved macroeconomic stability and individual financial security.

The Ghana Living Standards Survey (GLSS), with its focus on the household as a key social and economic unit, provides valuable insights into living conditions in Ghana. The survey was carried out by the Ghana Statistical Service (GSS) over a 12-month period (April 1998 to March 1999). A representative nationwide sample of more than 5,998 households, containing over 25,000 persons, was covered in GLSS IV. The fourth round of the GLSS has the following objectives: · To provide information on patterns of household consumption and expenditure disaggregated at greater levels. · In combination with the data from the earlier rounds to serve as a database for national and regional planning. · To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country. · To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender. Additionally, the survey will enable policy-makers to · Identify vulnerable groups for government assistance; · Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households; · Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.

Ghana GH: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data was reported at 1.270 % in 2016. Ghana GH: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data is updated yearly, averaging 1.270 % from Dec 2016 (Median) to 2016, with 1 observations. Ghana GH: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. 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. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Ghana Labour Force: Urban data was reported at 8,097,964.000 Person in Sep 2023. This records a decrease from the previous number of 8,120,057.000 Person for Jun 2023. Ghana Labour Force: Urban data is updated quarterly, averaging 7,389,914.000 Person from Mar 2022 (Median) to Sep 2023, with 7 observations. The data reached an all-time high of 8,120,057.000 Person in Jun 2023 and a record low of 6,951,319.000 Person in Jun 2022. Ghana Labour Force: Urban data remains active status in CEIC and is reported by Ghana Statistical Service. The data is categorized under Global Database’s Ghana – Table GH.G004: Labour Force: Annual Household Income and Expenditure Survey.

Abstract

The Millennium Development Authority (MiDA) financed the construction of a new irrigation scheme in Kpong and the renovation of two irrigation schemes in Botanga and Golinga. This data contains baseline information for the impact evaluation of this activity.

Treatment groups involve households with farmers who belong to FBOs within the geographic perimeters of the new/renovated irrigation schemes; these treatment groups are provided contracted access to an anchor farm that will enable them to receive irrigation. Comparison groups are households outside the water supply perimeters provided by the new/renovated irrigation scheme with characteristics similar to those of households in the treatment groups.

The three main research questions this evaluation will try to answer (once endline data is collected), presented in form of hypotheses to be tested, are: i) new irrigation schemes will raise production from 2 to 3 crops per year; ii) irrigation will allow for diversification of crops and potentially higher yields; and iii) irrigation will increase labor requirements. From these three hypotheses, there are five indicators that can be used to measure the impact of these irrigation activities: (1) total household income; (2) total household income from crop production; (3) paid employment per household; (4) crop mix - annual production output (kilograms) for each of the five most imported crops per household (i.e. want to observe move from low to high-value crops); and (5) crop yield (i.e. monitor output per unit, kilogram/hectare per crop cycle).

To evaluate this program, once endline data is collected, NORC proposed to use a difference-in-difference approach and an IV approach based on a distance indicator (i.e. instrument treatment with “farmer's distance from anchor farm” if we can assume small farms closer to anchor farms are more likely to benefit from activity).

In terms of descriptive statistics there is no clear evidence that households in the treatment group are better or worse off than households in the comparison group at baseline. There are, however, important differences to consider. While the household head in the treatment group is more likely to be female, slightly less educated, and live in an informal dwelling, they were more likely to have children currently attending school. Households within the treatment group also had, on average, higher income, though the variance was high (as is the case with income in general), and the difference was not statistically significant. With respect to farming activities, there are two important differences to highlight across experimental groups. First, households in comparison groups were more likely to own their own plots. This is important because the impact of irrigation activities could be confounded if the households in the treatment group are less likely to make long-term investments than households in the comparison group. Second, households in the treatment group owned smaller plots of land in terms of area, on average.

Geographic coverage

The baseline data includes information from three irrigation schemes in Ghana and their vicinities: Kpong Left Bank, Bontanga and Golinga.

Analysis unit

Households

Universe

Farmer households.

Sampling procedure

Farmers in the treatment group are those that belong to FBOs that operate within the geographic perimeters of the irrigation scheme, and will be able to receive irrigation. Farmers in the comparison group are outside the water supply perimeters, meaning they do not receive the benefits of the irrigation schemes, but are similar in characteristics to the treatment farmers. In total we have 656 farmer households in our sample.

Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data was reported at 2.340 Intl $/Day in 2016. This records a decrease from the previous number of 2.360 Intl $/Day for 2012. Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data is updated yearly, averaging 2.350 Intl $/Day from Dec 2012 (Median) to 2016, with 2 observations. The data reached an all-time high of 2.360 Intl $/Day in 2012 and a record low of 2.340 Intl $/Day in 2016. Ghana GH: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2011 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Poverty. Mean consumption or income per capita (2011 PPP $ per day) 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) circa 2010-2015 (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 PovcalNet. 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.

Ghana GH: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 5.090 Intl $/Day in 2016. This records an increase from the previous number of 4.840 Intl $/Day for 2012. Ghana GH: Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 4.965 Intl $/Day from Dec 2012 (Median) to 2016, with 2 observations. The data reached an all-time high of 5.090 Intl $/Day in 2016 and a record low of 4.840 Intl $/Day in 2012. Ghana GH: Survey Mean Consumption or Income per Capita: Total 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 Ghana – Table GH.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;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.

Ghana GH: Revenue and Grants: Revenue: Taxes on Income: Profits and Capital Gains: % of Revenue data was reported at 23.831 % in 2010. Ghana GH: Revenue and Grants: Revenue: Taxes on Income: Profits and Capital Gains: % of Revenue data is updated yearly, averaging 23.831 % from Dec 2010 (Median) to 2010, with 1 observations. Ghana GH: Revenue and Grants: Revenue: Taxes on Income: Profits and Capital Gains: % of Revenue data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank: Government Revenue, Expenditure and Finance. Taxes on income, profits, and capital gains are levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains, whether realized or not, on land, securities, and other assets. Intragovernmental payments are eliminated in consolidation.; ; International Monetary Fund, Government Finance Statistics Yearbook and data files.; Median;

Ghana GH: Adequacy: Social Protection & Labour Programs: % of Total Welfare of Beneficiary Households data was reported at 96.405 % in 2012. This records an increase from the previous number of 1.828 % for 2005. Ghana GH: Adequacy: Social Protection & Labour Programs: % of Total Welfare of Beneficiary Households data is updated yearly, averaging 49.116 % from Dec 2005 (Median) to 2012, with 2 observations. The data reached an all-time high of 96.405 % in 2012 and a record low of 1.828 % in 2005. Ghana GH: Adequacy: Social Protection & Labour Programs: % of Total Welfare of Beneficiary Households data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Social Protection. Adequacy of social protection and labor programs (SPL) is measured by the total transfer amount received by the population participating in social insurance, social safety net, and unemployment benefits and active labor market programs as a share of their total welfare. Welfare is defined as the total income or total expenditure of beneficiary households. Estimates include both direct and indirect beneficiaries.; ; ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/); Simple average;