Understanding location and neighbourhood effects: An analysis of the housing submarkets in Accra – Ghana
Creators: name: Gavu, Emmanuel Kofi
Publisher: name: TU Dortmund
Year: 2020
Subjects: subject: Rental
subject: Housing
subject: Submarket
subject: Location
subject: Neighbourhood
subject: Ghana
subject: 710
subject: Accra
subject: Immobilienmarkt

description: Housing is a global phenomenon and is the heartbeat of almost everyone. It is seen as one of the fundamental needs of mankind and the long term focus of many developments across the world. In housing markets research it has been long established that location does matter. That suggests that real estate goods and services place a premium on location. Although this is the case, such location and neighbourhood characteristics are not traded explicitly and their contribution cannot be directly observed. However the contribution of location characteristics on housing markets research to professionals both in Valuation practice and planning authorities cannot be over-emphasised. This research focuses on analysing rental values at the neighbourhood level which has been neglected by researchers. The main goal of this thesis was to develop a model that could be used to disaggregate residential rental housing values and use it to explain location and neighbourhood effects of housing sub-markets in Accra. The thesis empirically highlights the perception of stakeholders in Accra’s housing market in order to identify and conceptualise commonalities and differences in variables that determine Residential Rental Values (RRVs); the empirical conceptualisation of rental values in Accra; determinants of RRVs; empirical examination of submarket existence; and the determination of the price premium of location and neighbourhood attributes on rental values. The thesis adopts a mixed research approach. Two approaches are broadly operationalised in achieving objectives in this thesis. The first is a perception survey to understand stakeholder views on the rental housing market, and the second was an empirical survey to understand price movements within the market. The dataset for the perception survey adopted a relative importance index to rank 38 different variables that have been utilised in the extant literature to determine RRVs. Using the stratified sampling technique, the population of experts and stakeholders with knowledge in the rental market space were identified and categorised into six distinct strata. The sample frame was drawn from landlords; tenants; real estate agents; academic staff from real estate teaching departments in universities; valuation and estate surveyors; and a group labelled as ‘others’. Purposive sampling was then used to identify respondents within each stratum. The findings of the perception survey suggest that electricity and piped water connection, type of house, property condition and number of bedrooms are the most significant determinants of RRVs in Accra. Contrariwise, the least significant variables include storeroom availability, proximity to recreational facilities, proximity to place of worship, landscape quality and number of storeys. The first part of the thesis contextualises RRVs by identifying variables that reflect characteristics of the rental housing market in Accra. This serves as a guide in understanding rental market dynamics in a typical African city where access to data remains a challenge. The dataset for the empirical study is based on 536 rental transaction data collected during field study in Accra. Such data is not readily available, as Ghana’s housing market lacks the existence of an established data bank where such information could be obtained even at a fee. Some institutions may have some of the information (i.e. the Lands Commission), but such databases do not have all the required variables to model the market comprehensively as was attempted in this research. Moreover, there is no list of residential rental houses sample frame to draw sub-samples from. So the snowball technique served as the most practical means to select rental houses within each a priori submarket group during the field work. The thesis finds that submarket definition is a critical aspect in housing market analysis, and this is very useful in understanding market dynamics and making market predictions at a lower level of disaggregation. Using spatial, structural and nested definitions, submarket existence was tested using the Kruskal-Wallis H test (non-parametric), the Jonckheere-Terpstra test (non-parametric) and the hedonic pricing model (parametric). The results suggests that when pairwise comparisons are analysed, distinct submarkets existed within the aggregate market. The thesis further finds that variables such as electricity availability, real estate type, water availability, physical condition of property and number of bedrooms, are the top five determinants of rental value as perceived by market stakeholders; while on the other side, properties in high income neighbourhood, landscape quality, construction quality, bus stop availability and total floor area, are the highest contributors (51.85%) to rental value per empirical results. There seem to be a disconnect between these two groups of variables. The results suggests that the five highly ranked variables as perceived by market stakeholders was not confirmed by empirical analysis. The thesis also tested the hypothesis that, location and neighbourhood attributes determine to a larger extent residential rental values in Ghana than structural attributes does. Separate hedonic models were computed for both the aggregate market and submarket constructs. Using statistically significant model coefficients and the adjusted R2, the effects of location and neighbourhood are specifically analysed. The empirical results suggest that statistically significant structural variables contribute 43% to rental values, whereas location and neighbourhood variables contribute 20% and 25% respectively within the aggregate market. Similar trends are observed within submarket constructs. The findings have practical and policy implications; and methods utilised in this thesis can be replicated in similar cities in a developing country context where access to reliable data is a challenge. Findings also provide stakeholder investors in the rental space an understanding of market dynamics for profit maximisation, and end-users to maximise utility in deciding where to live – and as such households could benefit from making informed investment decisions on housing. The thesis finds that there exists several potential applications of quantifying the specific contributions of variables within the aggregate market as well as submarket constructs. The results of the quantification is influenced by the quality of data. It is further recommended that a national housing data bank is established by real estate teaching and research institutions of higher learning in Ghana to facilitate the acquisition of housing related data for research purposes. This thesis is one of the first attempts to empirically identify and test for submarkets existence; and to quantify the price premiums of structural, location and neighbourhood attributes in Ghana’s residential rental housing market.