Nine in every *** households in Ghana owned mobile phones as of 2018. However, only roughly ** percent had access to the internet at home in the same period. Around ** percent of the households owned a television, while ** percent had a radio.

In 2018, the average internet access rate was at **** percent among the surveyed households in Ghana. The highest concentration of internet access within households was reported in the Greater Accra region, at **** percent, while the lowest concentration was reported in the Upper East region, at *** percent.

Dataset Description

This dataset contains rental property listings scraped from Tonaton.com, one of Ghana's leading online classifieds platforms. It provides valuable information on rental prices across various regions in Ghana, along with other property details. The dataset is designed to support analysis, visualization, and modeling of rental prices in the Ghanaian real estate market.

Research paper: https://arxiv.org/abs/2501.06241 Analysis source code: https://github.com/epigos/house-prices-prediction

Features

The dataset includes the following columns:
- url: The link to the listing.
- name: The headline or title of the rental property listing.
- price: The rental price of the property in Ghanaian Cedis (GHS).
- category: The type of rental property (e.g., apartment, house, room, office).
- bedrooms: The number of bedrooms available in the property.
- bathrooms: The number of bathrooms available in the property.
- floor_area: The floor area of the property in square meters.
- location: The address location where the property is located.
- condition: Condition of the property e.g new, used, off-plan etc. - amenities: Amenities provided in the property. - region: Geographic administrative region of the property location. - locality: Represent the town or city where the property is located. - parking_space: Indicates if there is parking space available. - is_furnished: Indicates if the property is furnished. - lat: Longitude location of the property. - lng: Latitude location of the property.

Potential Use Cases

1. Real Estate Market Analysis: Analyze rental price trends across different locations and property types in Ghana.
2. Price Prediction Models: Train machine learning models to predict rental prices based on features like location, property type, and number of bedrooms.
3. Geographical Insights: Investigate how location impacts rental prices across urban and rural areas in Ghana.
4. Consumer Trends: Study patterns in rental property preferences, such as the most popular types of properties or regions.

Source

The data was scraped from Tonaton.com as of November, 2024. Please note that this dataset reflects the listings available during that period and may not include all rental properties in Ghana.

Disclaimer

This dataset is shared for educational and research purposes only. It is not intended for commercial use or to reproduce Tonaton.com’s proprietary information. Users are responsible for ensuring their use complies with Tonaton.com’s terms and conditions.

Conflict of Interest

There are no conflicts of interest associated with the creation or use of this dataset.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A structurally separate and independent place of abode. It could be a building or some form of space or shelter arranged for human habitation which was occupied at the time of the Census (e.g. a hut or group of huts). It may conatin one or more households. Living quarters originally intended for habitation and used wholly for other purposes at the time of the census must be excluded from the census coverage, while shelters not intended for habitation but occupied at the time of the census must be included. - Households: A household consists of a person or a group of persons, who live together in the same house or compound, share the same house-keeping arrangements and are catered for as one unit. It is important to remember that members of a household are not necessarily related (by blood or marriage) because nonrelatives (e.g. house helps) may form part of a household. - Group quarters: Group quarters include educational institutions such as boarding schools and student hostels; seminaries, convents, etc.; children's homes, orphanages, nurseries; homes for the elderly; hospitals and healing centers, including mental hosptials, maternity homes, divine healers' camps, herablists' establishments; hotels, motels, hostels, and guest houses; prisons, including borstal institutions, remand homes, industrial schools, and police, immigration, and military cells; service barracks, including army camps, military academies, police training schools and colleges; soldiers on field exercise; and the floating population.

Universe

All persons in households and all persons in institutions and in transit in Ghana at midnight on the night of September 26-27, 2010, inlcuding the floating population Floating population: Outdoor sleepers, hunting and fishing groups, relatives of patients sleeping on in hospital waiting rooms, on hospital grounds, or in prayer or healing camps, beggars, and vagrants (mentally sick or otherwise).

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Ghana Statistical Service

SAMPLE SIZE (person records): 2466289.

SAMPLE DESIGN: Systematic Sample of every 10th dwelling with a random start, drawn by the country Floating population: Outdoor sleepers, hunting and fishing groups, relatives of patients sleeping on in hospital waiting rooms, on hospital grounds, or in prayer or healing camps, beggars, and vagrants (mentally sick or otherwise).

Mode of data collection

Face-to-face [f2f]

Research instrument

Seprate forms were used to enumerate the household population and the non-household population. The household form requested information on individual charactersitics, emigration and mortality of household members, agricultural activity of the household, and housing conditions. The non-household form requested information on type of residence and individual characteristics only.

In 2018, the average ownership rate of radios was at **** percent among the surveyed households in Ghana. The highest concentration of radios within households was reported in the Eastern region, at **** percent, while the lowest concentration was reported in the Northern region, at **** percent.

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In 2018, the ownership rate of computers was at ** percent among the surveyed households considered to be the wealthiest in Ghana. However, only *** percent of those households considered the poorest were able to possess a computer at home.

Ghana GH: Time Required to Register Property data was reported at 47.000 Day in 2017. This stayed constant from the previous number of 47.000 Day for 2016. Ghana GH: Time Required to Register Property data is updated yearly, averaging 47.000 Day from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 182.000 Day in 2006 and a record low of 47.000 Day in 2017. Ghana GH: Time Required to Register Property 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: Company Statistics. Time required to register property is the number of calendar days needed for businesses to secure rights to property.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Abstract

Following the pattern set in the first two rounds of the Ghana Living Standards Survey (GLSS), the questionnaire used for the third round again covered a wide spectrum of topics such as education, health, housing, employment, income and expenditure, which affect the living standards of households. GLSS III thus provides data on various aspects of Ghanaian household economic and social activities, which are of help for monitoring the impact of the Government's Economic Recovery Programme.

GLSS III differed from the two previous rounds, however, in concentrating particularly on the income, consumption and expenditure of households at a much more disaggregated level than previously. As a result, GLSS III provides more accurate estimates of income and expenditure, including the imputed value of home produced food which is consumed by households. The data on household expenditure are also being used to derive the weights needed for rebasing the Consumer Price Index. The GLSS data on income, consumption and expenditure, together with other individual, household and community level data collected in GLSS III, will also provide a valuable database for national and regional planning purposes. Detailed anthropometric data had been collected in GLSS I and GLSS II, involving the need to include an anthropometrist in each survey team. This topic had to be dropped from GLSS III, so that the expanded income, consumption and expenditure data could be collected.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage sampling technique was used in selecting the GLSS sample. Initially, 4565 households were selected for GLSS III, spread around the country in 407 small clusters. in general, 15 households were taken in an urban cluster and 10 households in a rural cluster. The actual achieved sample was 4552 households. Because of the sample design used, and the very high response rate, the sample can be considered as being self-weighting, though in the case of expenditure data, weighting of the expenditure values is required.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used for GLSS III: a household questionnaire, a community questionnaire and a price questionnaire.

• The household questionnaire consists of two parts. Part A collected information on household composition, education, health and fertility, employment and time use, migration, and housing characteristics, and it was also used to identify the respondents for Part B. Part B covered agricultural activities, including the consumption of home produce, household expenditure, non-farm enterprises, other income and expenditure, and credit, assets, and savings.

• All urban households were given a special diary, and requested to record on a separate page each day all the expenses they incurred. This had to be done by a literate member of the household who had already been identified during the listing exercise. In the case of illiterate households the supervisor or the supplementary interviewer visited them and did the recording. Although to a large extent the use of diaries seems to have served its intended purpose of facilitating the recording of expenditures for many urban households, some caution has to be taken in interpreting the results and estimates derived from the diaries. In particular, while most of the expenses incurred by the household as a unit are likely to have been recorded fairly accurately, it is possible that some of the expenses made by individual members of the household outside the home may have been missed.

• Details of infrastructure and other facilities available to rural communities were recorded in the community questionnaire. This questionnaire was usually administered at a meeting with the community chief, along with his elders and other knowledgeable people in the community.

• The price questionnaire was used to collect information on prices in the local market. This information is needed for comparing prices in different parts of the country, which would allow the construction of regional price indexes and the adjustment of household expenditures to a common base so as to take account of regional variations in purchasing power.

Cleaning operations

The data collected in this survey were entered directly onto microcomputers which had been installed in the eight regional capitals. Kumasi and Accra had two PCs each, while Tamale, Sunyani, Koforidua, Ho, Cape Coast and Sekondi/Takoradi had one each. Special interactive software programs had been prepared for data entry and checking, using the software package Rode-PC. Data entry was done in two rounds. In both urban and rural clusters interviewers completed Part A of the questionnaire by the end of the fifth visit to each household; and after checking them, the supervisor took these questionnaires straight away to the regional capital, where the data entry operator began keying in. Once Part B had been completed, the supervisor took these questionnaires to the regional capital, and returned with the Part A questionnaires, plus detailed printouts showing what errors had been discovered by the editing program during the keying in operation. These errors were then corrected in the field. By the time the data entry operator had finished keying in the second batch of questionnaires (Part B), the team would have moved from those clusters to the next set of clusters. However, the next set of clusters were very close to the previous ones, so going back to correct errors detected in the second round involved travelling only a short distance. This arrangement made field reconciliation fairly easy. In addition, each set of clusters had been chosen close together so as to make supervision relatively easy. Finally, clusters in areas that were hardly accessible during the rainy season were scheduled to be covered during the dry season. At regular intervals during the fieldwork the diskettes containing the GLSS III data for each completed cycle were returned to the headquarters in Accra. Final tabulations were produced using the SAS software package.

Ghana GH: Procedures to Register Property data was reported at 6.000 Number in 2017. This stayed constant from the previous number of 6.000 Number for 2016. Ghana GH: Procedures to Register Property data is updated yearly, averaging 6.000 Number from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 7.000 Number in 2006 and a record low of 6.000 Number in 2017. Ghana GH: Procedures to Register Property 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: Company Statistics. Number of procedures to register property is the number of procedures required for a businesses to secure rights to property.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Summary statistics of household’s income and expenditure.

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