African Real Estate Research - UCT Open Access Journals

Welcome to part five, the second issue of the Journal of African Real Estate Research (JARER). In this paper, we highlight the establishment of the Future Leaders of the African Real Estate Association (FLAfRES).

A Brief History of FLAfRES

Wakefield/Broll; Samuel Azasu – Associate Professor at the University of the Witwatersrand and former editor of the Journal of African Real Estate Research;. Emmanuel Kofi Gavu as the vice chairman is a lecturer at the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

Conclusion

Career development for early career academics: The benefits of networking and the role of professional associations. Nurturing Generations: The American Society of Mammalogists' Role in Supporting Students and Early Career Scientists.

The Executive Committee shall determine issues to be brought before the AfRES Board and the general membership at the annual meetings of the

The Executive Committee shall review, and tentatively approve, the report which will be submitted to the AfRES Board of Director’s meeting(s),

The Executive Committee shall consist of the chairperson (voting), vice chairperson (voting), program chairperson (voting) and immediate past

Approving ‘‘Mentoring Program Acceptance Criteria’’ to assure fair and equal treatment to all members, for guidance of program chairperson

Officers

Chairperson

Sit on the AfRES Meeting Committee

Chair the meetings of the FLAfRES committee

Bring important issues to the attention of the FLAfRES officers, at least seven days prior to the annual meeting

Chair the general membership meeting at the AfRES annual meeting

Vice chairperson / Mentoring Program Chairperson

The vice chairperson is responsible for coordinating the mentoring program, and carrying out other functions as requested and / or delegated by

Contact all mentors and indicate whether they are linked and, if necessary, to whom.

The vice chairperson shall make a summary report about the program to the FLAfRES board to be included in the chairperson’s report to the AfRES

Program Chairperson

The program chairperson may be removed by a majority vote of the board of directors for non-performance as evidence by the chairperson and

Any subcommittee chairperson is charged to maintain a record of all events and activities in which such subcommittee is involved, which record

The duties of the secretary are primarily those of recordkeeping and include

Immediate Past-Chairperson

The importance of prior service to the Society by nominees, as evidenced by attendance and presentations at previous meetings, editorial board activity, and committee activity should be emphasized, especially for vice presidential candidates.

A member must be present to make a nomination. A member must be present to be nominated (and elected)

Speeches supporting nominees for elected offices shall be limited to one minute

Introduction

Accordingly, real estate data is important to the operation and efficiency of the Nigerian real estate market. This is followed by a definition of property data and an explanation of the concept in the Nigerian context.

Literature Review

The Importance of Data in Property Markets

He also wants to clarify that real estate data is not synonymous with real estate market data. However, it is appropriate to distinguish here between formally accumulated real estate data (which is considered in this study) and valuation data, the sources of which are identified by RICS (2017: p. 17) as: “customer; reviews;

Table 1: A Broader Conception of Property Data

Approach

In these many respects, it becomes undeniably necessary, important and appropriate to examine the real estate data situation in Nigeria. Assessing the feasibility of the recommendation(s) with a view to proposing a holistic solution that addresses all issues relevant to solving the real estate data challenge in Nigeria.

Overview of Property Data Research in Nigeria

Feasibility, Modality and Achievability of a Central Data Bank Other research identifies conditions in, and characteristics of, Nigeria’s
Recommendations Arising from the Review

The last three points are issues explained in the process of defining the real estate data challenge. In Britain, the RICS is a private data source, while “in terms of public sources of property value data… the Inland Revenue provides online tables of property transactions (Calhoun (2001: p.18).

Conclusion

However, the study did not take into account the factors that influence the increase in the rental value of student housing. On the other hand, Aluko (2011) assessed the condition of student housing in the University of Lagos as well as the level of satisfaction students felt with the condition of the facilities.

Research Methodology

Under normal circumstances, and according to the literature, there should be a positive correlation between satisfaction with student housing facilities and the rent paid for the use of these facilities. The authors were unable to prove whether student housing satisfaction is a function of student satisfaction with housing facilities. Thus, the current study deviates from previous studies and examines student satisfaction with the rent paid for off-campus housing in relation to on-campus facilities in the study area.

Next, Spearman's Rank Correlation, which measures the strength of association between two variables, was used in measuring the relationship between students' rental satisfaction and their satisfaction with the facilities provided in off-campus hostels. Regression analysis deals with the contribution of independent variables to changes or variations in the dependent variable.

Data Analysis and Discussion of Results

Over two-thirds (67.7%) of the respondents live in houses with running water in the building (toilets, bathrooms and kitchens). In other words, they are paying not only for the accommodation but also for the enjoyment of the accommodation facilities. It was found that not all students are satisfied with the rent they pay because they are not satisfied with some of the facilities offered in private hostels.

An Evaluation of the Management of Student Hostels of Tertiary Institutions in Owerri, Imo State. Therefore, the choice of an appropriate technique is a fundamental determinant in the forecasting of the total return of investments.

Table 3 below identifies the characteristics of the housing facilities in the study area

Research Methods

In addition, the issue of the absence of a data bank has also prompted the purchase of rental values and capital values directly from estate agents. In addition, little consideration has been given to measuring the overall return on investment performance. As such, a simple time series regression methodology is adopted to forecast total returns.

The methodology used by the study starts with the purchase of rental and capital values, determination of the total return. The total returns are tested for their predictive validity, then the predicted values are evaluated for accuracy using forecast evaluation techniques.

Results and Findings

A time series regression for the total returns for each of the locations is determined using ordinary least squares regression. This coefficient is an indication that the data set was not fit and is due to the fluctuations observed in the total returns in the sample. The predictive validity of total returns in sub-markets of the Lagos metropolis varied from sub-market to sub-market as well as from time lag to time lag.

In general, the autocorrelation results suggest that the total returns observed in the sample will not follow the same pattern in the future. The accuracy test gave poor results for all investment options except stores in Lagos Island, indicating that the expected total return does.

Table 1: Average Annual Total returns for Shops and Offices in Selected Areas of Lagos Metropolis

Conclusion and Recommendations

Available at: https://www.jll.com.co/en/trends-and-insights/research/2020-global-real-estate-transparency-index. Walters, Sietchiping and Haile (2011) also argue that if there was no real estate development, there would be little need for the services to be financed through taxes, as real estate users carrying out activities that use sanitation, roads, etc. create demand after these public services. In general, infrastructure has distinct and significant values for building users, and their immediate accessibility has a significant impact on property prices and value (Johnson-Gardner, 2007).

In Germán and Bernstein's (2018) study, property taxes were shown to be an important form of LVC because well-functioning property tax systems base liabilities on the market value of real estate. The concept of 'land value capture' has thus become a standard argument for implementing or reforming property-based taxes (Walters, 2013).

Land Value Capture and Municipal Infrastructure

McGaffin, Napier and Gavera (2014) looked at two elements of the LVC process, namely the 'capture of value' and 'the use of funds arising from the captured value'. It is the point at which the fit line/best fit line crosses the Y-axis. Easily accessible” in terms of neighborhood safety as a variable is when the agency (i.e. the Lagos… Neighborhood Safety Corps security force) has at least one representative available to patrol the streets daily.

As for the 'standard deviation', the values are low, showing that the distribution of the individual values around the 'mean' is low. The regression results show that a significant part of the value of apartments in the study can be attributed to municipal infrastructure.

Table 1 below shows the variables used for the study, their measurement indices, and their code

Rates Schedule

Based on the studies of Parsons and Noially (2004) it has been argued that the implied prices of location infrastructure in property values will fall steadily and proportionally with increasing distance to location-specific infrastructure and vice versa. Thus, the impact of a site infrastructure located more than 4 km from a property is considered 'zero' for that property. The impact of location infrastructure is represented as 'L1, L2, L3, L4,…LN, where L is derived from the regression coefficients for location infrastructure.

For example, L1' would be the regression coefficient (implicit price) for location infrastructure for 'bus stop'. The implicit price of each location infrastructure coefficient would be estimated based on its proximity to the property in question (i.e.

Concluding Comments

Theoretical background of housing location choice and optimality The theoretical work on housing location dynamics is deeply rooted in utility

Designing land value capture tools in the context of complex land use and scarcity regulatory regimes in Accra, Ghana. Use of land value capture in urban rail transit public private partnerships: Retrospective analysis of Delhi Airport Express Metro. Value capture in South Africa - the conditions for their successful use in the current legal context.

A value-added property tax to finance beach nourishment projects: an application to Delaware's open beaches. Available at: https://www.lincolninst.edu/key-issues/value-capture-property-tax (Accessed: 12 January 2020).

Methodology 1. Study Area

Index of the level of household well-being or satisfaction derived in choosing a house from a range of alternatives (expressed as a percentage). But since the household income is fixed, the share allocated to each individual will vary according to the household's choice. Pw is the price per hectare for the workplace location (also the rack rent/bud rent for w of household i), and N is the market value of the quality of location j.

From Bolton (2005), PEjc is the unit price of a composite good on which the rest of the household income is spent. OPTi is a measure of the level of fulfillment, satisfaction or satisfaction that a household (i) whose primary workplace is (w) can achieve from a house choice (c) in a neighborhood (j).

Findings and Discussion

Residential location preferences and urban form. 2012), Housing Markets, Signals and Search, Journal of Property Research, Vol. 2011), Housing market choices, Housing, theory and society, vol. 1978), Modeling Residential Location Choice, Transportation Institute. 2002), The path to discrete-choice models, Access Magazine, Vol. 1969), Cities and Housing (Chicago, University of Chicago Press. 1969), A Competitive Theory of the Housing Market, American Economic Review, Vol. 2011), Modeling Transport, Wiley, UK.

2014), Towards a multimodal city of the future?: Multi-stakeholder scenarios for urban mobility, Technology Forecasting and Social Change, Vol. connection with residential land prices and location selection. 2013), Cultural heritage and location choice of Dutch households in a residential sorting model, Journal of Economic Geography, Vol. 2000), assessing marginal willingness to pay for commuting.