Minimum Wages in Ghana increased to 19.97 GHS/Day in 2025 from 18.15 GHS/Day in 2024. This dataset includes a chart with historical data for Ghana Daily Minimum Wage.

In 2019, the individual living wage in Ghana amounted to 900 Ghana cedis (GHS) (approximately 154.78 U.S. dollars) per month, which was an increase of 40 GHS (around 6.87 U.S. dollars) compared to the previous year. Overall, the individual monthly living wage in the country grew from 880 GHS (roughly 151.12 U.S. dollars) in 2015 to 900 GHS in 2018.

As of 2022, the daily minimum wage in Ghana stood at ***** Ghanaian cedis (GHS) (approximately *** U.S. dollars), representing an increase of one cedi (around **** U.S. dollars) from the previous year. The minimum wage in the country progressively increased from 2010 onwards. Moreover, in 2022, the base pay in Ghana increased along with the minimum wage. Overall, the 2003 Labor Act mandates the Ghana National Tripartite Committee to determine the national daily minimum wage.

This dataset provides values for MINIMUM WAGES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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.

In 2022, the base pay in Ghana amounted to 11.34 Ghanaian cedis (GHS) (approximately 0.92 U.S. dollars), registering an increase of 0.74 GHS (around 0.06 U.S. dollars) compared to 2021. Overall, contrary to the period between 2010 and 2013 which recorded a daily base pay higher than the daily minimum wage in Ghana, the period from 2014 to 2022 registered a base salary lower than the minimum wage.

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.

This paper examines gender earnings gaps in Ghana using data from the Ghana Living Standards Survey (GLSS7). Focusing on both the formal and informal sectors, we apply Oaxaca–Blinder decompositions and Recentered Influence Function (RIF) regressions to investigate mean and distributional disparities in log earnings between men and women. The evidence points towards a long-term gender pay gap, with females receiving significantly less than males, particularly in the informal economy. RIF regressions along the wage distribution show that the gender wage gap is more substantial in the upper quantiles in the informal sector. In contrast, the formal sector has narrower or even reversed gaps at specific quantiles.

BackgroundIn many developing nations, including Ghana, access to contraceptive services, remains a critical concern where urban areas face unique challenges in healthcare delivery. Despite various interventions, the financial burden of assessing these contraceptive services continues to hinder adoption by women especially those with economic challenges. This study explored the costs incurred by women seeking contraceptive services in urban communities by estimating the direct, indirect, and intangible costs in Ghana.MethodsA facility-based cross-sectional study was conducted using the patient perspective; to gather data on direct medical and non-medical costs, indirect costs and intangible costs that were associated with women seeking contraceptive services. A structured questionnaire was used to collect data from three Planned Parenthood Association of Ghana (PPAG) facilities in the Accra metropolitan, Suame municipal and Sagnarigu districts in the Greater Accra, Ashanti, and Northern Regions respectively. A total of 125 women accessing contraceptive services were randomly selected and included in the study. Data was analyzed descriptively and reported in frequency tables, pie, and bar charts. All costs were reported in Ghana Cedi and US dollar.ResultsThe average direct cost of contraceptive services was GHS 18.37 ± 22.11 (US$ 1.53 ± 1.84) per visit. This comprised an average direct medical cost of GHS 8.50 ± 7.18 (US$ 0.71 ± 0.60) and non-medical cost of GHS 9.84 ± 20.23 (US$ 0.82 ± 1.69). Clients, on average, lost 52.1 minutes due to traveling and waiting, resulting in an average productivity loss of GHS 1.62 per visit. The average economic cost of contraceptive service was GHS 19.99 (US$ 1.67) per patient. About 92% of the economic cost was made up of direct cost. 71.2% of respondents consulted their partners before accessing contraceptive services, and 94% believed that their decision to use contraceptives did not negatively affect their relationships, however, many reported pains during the procedure.ConclusionThe study highlights the considerable direct and indirect costs associated with accessing modern contraceptive services, indicating a potential barrier to access when compared to daily minimum wage and prevailing economic conditions. Addressing these economic challenges is crucial for ensuring access to contraceptive services. Innovative strategies such as service delivery outreaches and deployment of digital health interventions to expand self-care is recommended to help reduce travel time to and from the service delivery point for contraceptive services.

Cost distribution per choice of contraceptive method.