Housing, or more general living spaces, is a fundamental aspect of existence, giving shelter, protection, warmth, and a place to rest for human beings. This study aimed at analyzing changes in rental price with particular emphasis on Voi town and its environs. In our study, we wished to determine the common types of houses rented in Voi, the amount paid as rent and the key determinants of house rent in Voi
Structured questionnaires executed on a Kobo-Collect mobile data collection platform was used to gather data. A sample size of 384 households was obtained from 23 locations within Voi and its environs. The data was analyzed using both qualitative and quantitative methods. A Multiple linear regression model was employed to identify the determinant of house rent prices in Voi and its environs.
Table of Contents
CHAPTER ONE: INTRODUCTION
1.1 Background
1.2 Statement of the problem.
1.3 Significance of the study.
1.4 Objectives
1.4.1 General objective
1.4.2 Specific objectives
CHAPTER TWO: LITERATURE REVIEW
2.1 Theoretical review
2.1.1 Smith's gap theory
2.1.2 Information asymmetry theory
2.1.3 Maximum housing expenditure theory
2.1.4 The residual income approach
2.1.5 Heterogeneity theory
2.2 Conceptual framework
2.3.1 Type of house and its influence on rental price
2.3.2 Housing demand and its influence on rental growth
2.3.3 Structural characteristics and their influence on rental prices
2.3.4 Household income and its relation to rental prices
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Overview
3.2 Research Design
3.3 Target population and sampling
3.4 Data collection methods and instruments
3.4.1 Source of data
3.4.2 Collection of data
3.5 Data management
3.6 Ethical consideration
3.7 Data analysis strategies
CHAPTER FOUR: DATA ANALYSIS, PRESENTATION, INTERPRETATION, AND DISCUSSION
4.1 Introduction
4.2 Descriptive statistics
4.2.1 Distribution of households by the place of residence.
4.2.2 Distribution of type of the house.
4.2.3 Average rent by type of house.
4.2.5 Status of the floor
4.2.6 Main wall Material
4.3 Inferential Statistics.
4.3.1 Multiple linear regression analysis.
4.3.2 Model summary
4.3.3 Coefficients
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS
5.1 Introduction
5.2 Discussions from findings obtained
5.3 Conclusion
5.4 Recommendations
5.5 Challenges for the study
5.6 Suggestions for further research
Research Objectives & Key Focus Areas
The primary goal of this research is to analyze the variations in rental prices within Voi town and its environs to understand the determinants of housing rent. By employing a statistical model, the study seeks to quantify how factors such as household income and the specific type of housing influence rental costs for residents in the region.
- Analysis of housing rent dynamics and rental price variations.
- Determination of common house types by location within Voi.
- Investigation into the influence of household income on rental payments.
- Application of multiple linear regression to model rent determinants.
- Assessment of structural housing characteristics (floor status and wall materials).
Extract from the Book
2.1.5 Heterogeneity theory
Urban housing units vary so much in many dimensions that households' choice greatly demonstrates the essential elements of consumer choice. The taste for different housing features and components differs for every household; for instance, households can be sensitive about the house structure to the details such as architectural designs, fittings, condition (whether newly constructed), and the like. Therefore, they have carryout an extensive valuation and search for their perfect or rather suitable unit. The difference in consumer tastes is what we term as heterogeneity. However, housing heterogeneity is distinct as the demand for the housing unit may also be affected by external forces. A good example of these external forces is the neighborhood and location factors.
The neighborhood factor can be viewed in 2 different dimensions. One the supplier for housing units may have no control of their immediate neighbor. For instance, if the housing units neighbors factories or industries producing loads of unmanaged dump waste or gases, it may heavily limit the occupancy of the housing units. In addition, the households may choose to dwell in a place because of the neighborhood. Comparatively, if a household has good and friendly neighbors and environment, it may overshadow other factors affecting their stay in a housing unit.
Summary of Chapters
CHAPTER ONE: INTRODUCTION: This chapter provides background information on global and local housing trends, outlines the research problem, states the significance of the study, and defines the research objectives.
CHAPTER TWO: LITERATURE REVIEW: This section reviews existing theoretical perspectives and conceptual frameworks regarding rent dynamics, housing demand, and the impact of structural and economic characteristics on rental pricing.
CHAPTER THREE: RESEARCH METHODOLOGY: This chapter details the descriptive research design, target population, systematic random sampling techniques, data collection via Kobo-Collect, and the use of multiple linear regression analysis.
CHAPTER FOUR: DATA ANALYSIS, PRESENTATION, INTERPRETATION, AND DISCUSSION: This chapter presents the empirical findings through descriptive statistics and regression analysis, interpreting how household income and house type correlate with rental prices.
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS: This final chapter synthesizes the results, draws conclusions about the determinants of rent in Voi, and offers recommendations to the government and future researchers.
Keywords
Housing, Rent, Voi, Rental Dynamics, Household Income, Regression Analysis, Urbanization, Housing Affordability, Property Valuation, Statistical Modeling, Kenya, Tenant, Infrastructure, Socioeconomic Status, Housing Demand
Frequently Asked Questions
What is the core focus of this research project?
The research fundamentally investigates the dynamics of housing rents in Voi town, Kenya, aiming to identify the primary factors that influence how much residents pay for their rental accommodations.
Which key thematic areas are addressed in this study?
The study covers the influence of housing types, the impact of household income, structural characteristics of buildings, and geographic distribution across different residential areas in Voi.
What is the primary objective of this investigation?
The primary objective is to analyze variations in rental prices and develop a statistical model to determine how specific variables—namely house type and household income—predict rental pricing.
What scientific methodology was applied?
The researchers utilized a descriptive study design with a quantitative approach, employing systematic random sampling of 384 households and using multiple linear regression analysis to evaluate data gathered via a mobile platform.
What aspects are covered in the main body of the work?
The main body integrates a literature review of relevant housing theories, a detailed methodological description, and a comprehensive analysis of field data, including descriptive statistics and a regression model summary.
What are the main keywords that characterize this work?
Key terms include Housing, Rent, Voi, Rental Dynamics, Household Income, Regression Analysis, Urbanization, and Housing Affordability.
How does the type of house influence rent in Voi according to the study?
The study identifies a positive relationship between house size/type (such as self-contained units) and rental costs, with self-contained 3-bedroom houses commanding the highest average rents compared to single rooms.
What role does household income play in the rental market of Voi?
Household income is identified as a significant determinant; the regression model demonstrates that as household income increases, there is a corresponding impact on rental expenditure, highlighting the economic constraints of the local population.
- Citation du texte
- Reuben Madava (Auteur), 2022, Housing Rent Dynamics in Voi Town and its Environs, Munich, GRIN Verlag, https://www.grin.com/document/1195499
