Addis Ababa, in Ethiopia, ranked as the most expensive city to live in Africa as of 2024, considering consumer goods prices. The Ethiopian capital obtained an index score of ****, followed by Harare, in Zimbabwe, with ****. Morocco and South Africa were the countries with the most representatives among the ** cities with the highest cost of living in Africa.

Detailed cost of living comparison between United Kingdom and South Africa

Damascus in Syria was ranked as the least expensive city worldwide in 2023, with an index score of ** out of 100. The country has been marred by civil war over the last decade, hitting the country's economy hard. Other cities in the Middle East and North Africa, such as Tehran, Tripoli, and Tunis, are also present on the list. On the other hand, Singapore and Zurich were ranked the most expensive cities in the world.

Detailed cost of living comparison between Sierra Leone and South Africa

This dataset provides an analysis of average monthly prices for four essential food items, namely Eggs, Milk, Bread, and Potatoes, in five different countries: Australia, Japan, Canada, South Africa, and Sweden. The dataset spans a five-year period, from 2018 to 2022, offering a comprehensive overview of how food prices have evolved over time in these nations.

The dataset includes information on the average monthly prices of each food item in the respective countries. This information can be valuable for studying and comparing the cost of living, assessing economic trends, and understanding variations in food price dynamics across different regions.

Use Cases:

Comparative Analysis: Researchers and analysts can compare food prices across the five countries over the five-year period to identify patterns, trends, and variations. This analysis can help understand differences in purchasing power and economic factors impacting food costs.

Cost of Living Studies: The dataset can be used to examine the cost of living in different countries, specifically focusing on the expenses related to basic food items. This information can be beneficial for individuals considering relocation or policymakers aiming to evaluate living standards.

Economic Studies: Economists and policymakers can utilize this dataset to analyze the impact of economic factors, such as inflation or currency fluctuations, on food prices in different countries. It can provide insights into the stability and volatility of food markets in each region.

Forecasting and Planning: Businesses in the food industry can leverage the dataset to forecast future food price trends and plan their operations accordingly. The historical data can serve as a foundation for predictive models and assist in optimizing pricing strategies and supply chain management.

Note: The dataset is based on average monthly prices and does not capture individual variations or specific regions within each country. Further analysis and interpretation should consider additional factors like seasonal influences, local market dynamics, and consumer preferences.

Detailed cost of living comparison between Liberia and South Africa

Detailed cost of living comparison between South Africa and Bangladesh

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.

Detailed cost of living comparison between South Africa and Nauru

Detailed cost of living comparison between South Africa and Sudan

Detailed cost of living comparison between South Africa and Samoa

Detailed cost of living comparison between Nigeria and South Africa

Abstract

The Measuring Living Standards in Cities (MLSC) survey is a new instrument designed to enhance understanding of cities in Africa and support evidence based policy design. The instrument was developed under the World Bank’s Spatial Development of African Cities Program, and was piloted in Dar es Salaam (Tanzania) and Durban (South Africa) over the course of 2014/15. These geo-referenced surveys provide information on urban living standards at an unprecedented level of granularity: they can be compared across different geographic levels within the cities, and between areas of ‘regular’ and ‘irregular’ settlement patterns. They also respond to the need to increased understanding of specifically ‘urban’ dimensions of quality of living: housing attributes, access to basic services, and commuting patterns, among others.

Geographic coverage

The survey covered households in Dar es Salaam, Tanzania.

Analysis unit

• Household

• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE FRAME

16,000 EAs generated by the Tanzania National Bureau of Statistics (NBS) for the 2012 Census.

STAGE ONE

200 EAs sorted into four strata. The central strata was divided into ‘central core, shanty’ and ‘central core, non-shanty’. Two EAs were replaced with reserve EAs as the original EAs were found to be inaccessible.

STAGE TWO

12 households randomly selected by systematic equal-probability from updated listing of each EA.

LISTING METHODOLOGY

The listing exercise took place between the first and the second stage of sampling. The household listing operations were implemented with computer assisted paperless interviewing (CAPI) techniques, which generates electronic files directly. Enumerators collected basic information about household: the name of the household head name, phone number and total number of household members living in the dwelling. Enumerators also recorded the GPS location of all structures,18 defined the type of structure, and aimed to provide measurement of structure size.

Listing was preceded by community sensitisation in both cities. In Dar es Salaam, enumerators visited the local chief (Mjumbe) of their assigned EA two days in advance of listing and on the day of listing.

Enumerators were equipped with maps created on Google My Maps to display shapefiles for the listing exercise. Hardcopies of their respective EA maps were also provided to be use in case of network failure. In Dar es Salaam, enumerators conducted a listing of all households in each of the selected EAs.

The listing exercise was conducted by 30 enumerators, each of which was assigned between 3 and 9 EAs for listing (enumerators were selected on the basis of performance from a group of 35 that were trained for listing). Enumerators were allocated EAs based on: (i) distance from enumerators’ homes in order to minimize transport time and cost; (ii) distance between the EAs; and (iii) safety and response rate considerations.

SURVEY IMPLEMENTATION

The surveys were fielded over the course of several months. The Dar es Salaam survey was implemented between November 2014 and January 2015.

Cases were assigned to interviewers using Survey Solutions. Interviewers were provided with both an electronic and hardcopy map, as well as a printed completion form, and could contact the listing manager through email, WhatsApp, or google hangouts if they were unable to find the assigned house.

Completing the survey often required repeat visits. This is because the survey required input from up to three separate respondents: the main respondent, who could be any present household member, and answered questions on household composition, basic information on members, assets, remittances, grants, housing, properties and consumption; the household head, who answered questions on residential history, satisfaction, employment, time use and commuting; and a random respondent, who was randomly selected from household members over the age of 12 (not including the head), who responded questions on satisfaction, employment, time use and commuting. Enumerators visited each house at least twice before a component could be marked as unavailable - in many cases, however, more than two visits were conducted.

Quality assurance procedures included: (i) In-interview feedback from CAPI, which provided a check that modules or questions were not missing, and alerted interviewers to mistakes and inconsistencies in given answers, so that these could be addressed while the interviewer was still with the respondent; (ii) Aggregate checks conducted using the Survey Solutions Supervisor application, which allows supervisors to identify common mistakes (applied to all initial interviews, and then through spot checks); interviewer performance and completion monitoring conducted by the implementing firm, through interviewer and EA level summaries of response rates, interview completion, and progress; (iii) weekly summaries of key indictors provided by the World Bank team (following each data delivery); (iv) direct observation of fieldwork; and (v) back check interviews. A key lesson learned is that the portion of back check interviews should be agreed in advance with the implementing firm: in Dar es Salaam back checks were conducted on 5% of the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

Non-response rate: 13%

Detailed cost of living comparison between South Africa and Canada

Estimated cost implications of multi-month home-delivered and standard clinic-based ART refills and monitoring as-observed by the South African National Department of Health with South African government salaries, under the programmatic scenario with 3-, 6-, and 12-month ART refill scripts.

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.

Caregivers of adolescents living with HIV encounter multiple economic and psycho-social challenges which impair their wellbeing and provision of optimal care. Cash transfers combined with short message service (SMS) nudges may address the financial and mental barriers to caregiver wellbeing in sub-Saharan Africa. We examined the preliminary effectiveness and feasibility outcomes of this multipronged approach for improving caregiver wellbeing. We piloted the Caregiver Wellbeing intervention in the eThekwini municipality, KwaZulu-Natal, South Africa. Participants were randomly assigned to one of the following groups: (i) the intervention arm (n = 50) received three cash payments (of ZAR 350, approximately 21 USD), coupled with behaviourally-informed mobile SMS nudges over a 3-month period; (ii) the control arm (n = 50) received a standard SMS encouraging linkage to health services. The primary outcome was change in psychological wellbeing at four-months follow-up. Secondary outcomes were changes in depressive symptoms and caregiver burden scores, recruitment pace, retention, uptake, acceptability and costs. Trial Registraion Number: PACTR202203585402090. The n = 100 caregivers (mean age = 42.3 years, 87% female) enrolled at baseline were recruited within six weeks. Compared to controls, there was a non-significant increase in psychological wellbeing (β = 3.14, p = 0.319). There was a 1.32 unit (p = 0.085) decrease in depressive symptoms and a reduction in caregiver burden (β = -1.28, p = 0.020) in the intervention arm. Participant retention was 85%, with high intervention uptake (95%). Caregivers expressed appreciation for the intervention as the cash component allowed them to fulfil their carer responsibilities and the SMS brought a sense of belonging and self-acceptance. Total societal cost of the intervention was US$13,549, and the incremental cost per increase in wellbeing score was US$1,080. Results suggest a cash transfer plus SMS nudge package, whilst feasible and acceptable, may require longer duration and an economic empowerment component to enhance caregiver wellbeing as part of post-pandemic recovery efforts.

Detailed cost of living comparison between Kenya and South Africa

Detailed cost of living comparison between South Africa and Mexico

Detailed cost of living comparison between South Africa and Marshall Islands