Key Features:
- No of Pages: 104
- No of Chapters: 6
Abstract:
This study was undertaken to assess the impact of Human Immuno-deficiency virus/Acquired Immuno-deficiency syndrome scourge on Farm labour productivity and welfare of infected and non infected farmers in Federal Capital Territory, Abuja. A multistage selection involving purposive and stratified random sampling techniques was used in selecting respondents. A total sample size of 180 respondents was purposively selected from four communities. Data were collected using a well structured questionnaires and interview techniques. Data were analyzed using descriptive statistics and multiple regression.
The results revealed that majority of the respondents (88.9 %of infected farmers) and (55.6 % of non infectedfarmers) were males. It futher revealed that majority of the respondents were married (51.1% of infected farmers) and (60.0% of non infected farmers) with mean education of 8 and 9 years respectively. The mean household size was approximately 9 persons each, while the mean age was 38 and 39 years; for infected and non infected farmers respectively. The mean non farm income (42000 and 42700 Naira) for infected and non infected farmers respectively. The study further revealed that 59% and 66 % of the variation of farm labour productivity were explained by age, farm size; distance of treatment centre; time lost and cost of treatment respectively for infected farmers and non infected farmers.Specifically, for infected farmers; the coefficients of farming experience (0.19 %) and household size (0.11 %) were positive and significantly determine labour productivity at 1 % respectively. In contrast, the coefficient of time lost (-2.54%) was negative and significantly determine labour productivity at 5% level of probability. As for non infected farmers the coefficients of farming experience (0.06 %), household size (2.29%), and farm size (3.27%) were positive and significantly determine labour productivity at 1 % respectively, while the coefficient of cost of treatment(-0.30%) was negative and significantly determine labour productivity at 5 % level of probability The Chow testresults(Fcal=5.65) revealed that there was a significant difference between farm labour productivity of infected farmers and non infected farmerThe result of the study further revealed that 59 and 54 % of the variation of income was explained by cost of labour; cost of treatment; cost of transportation, cost of feeding and output for infected and non infected farmers.
Specifically, for infected farmers the coefficients of time lost(-2.43%), cost of treatment (-0.97%) were negative and significant at 1 % level of probability implying that unit increase in the time lost and cost of treatment will decrease income of infected farmers by the value of their estimated coefficients respectively. Also, the estimated coefficient of cost of labour (-3.27%) was negatively significant at 5% level, implying that a unit increase in the cost of labour will decrease income of infected farmers by the value of their coefficient. While the estimated coefficients of cost of output (0.64%) was positive and significant at 1 % level of probability.For non infected farmers, the estimated coefficients of cost of treatment (-0.75%) and cost of labour(-2.85%) were negative and significant at 5% level of probability implying that unit increase of cost of labour and cost of treatment will decrease income of non infected farmers by the value of their estimated coefficients.
The Chow test result (Fcal=3.84) further revealed that there was significant difference between income of infected farmers and non infected farmers. It was also found that, the Pearson product moment correlation coefficient (0.03%) of the relationship between income and farm labour productivity of non infected farmers was significant at 5 % level of probability. In addition, the result also indicated that 88.33 % of farmers were faced with the problem of high cost of agrochemical while 40.55 were faced with the constraints of lack of extension agents. It was recommended that community-oriented programmes, free educational talk on HIV/AIDS should be put in place by government and NGO’s to empower farmers economically and socially.
Table of Content:
CONTENTS
TITLE PAGE ii
DECLARATION iii
CERTIFICATION PAGE iv
DEDICATION. v
ACKNOWLEDGEMENT. vi
TABLE OF CONTENTS vii
LIST OF TABLES xi
LIST OF FIGURES xii
ABSTRACT xiii
INTRODUCTION 1
1.1 Background of the Study 1
1.2 Statement of the Problem 4
1.3 Research Question 6
1.4 Objective of the Study 7
1.5 Statement of Hypotheses 8
1.6 Significance of the Study 8
1.7 Scope and Limitation of the Study 9
1.8 Operational Definition of terms 9
LITERATURE REVIEW 10
2.1 Introduction 10
2.2 Review of Related Studies 10
2.2.1 Socio-economic characteristics of HIV farmers. 10
2.2.2Factors affecting labour productivity of HIV farmers 12
2.2.3 Effect of HIV/AIDS on cost of treatment and welfare of farmer 15
2.2.4Relationship between labour productivity and welfare of HIV/AIDS farmer 18
2.2.5 Constraints faced by HIV farmers 22
2.2.6 HIV/AIDS prevalence rate 22
2.3 Theoretical Framework 23
2.3.1Theory and Concept of production 26
2.3.2 Theory on labour productivity 28
2.3.3 Concept of Welfare 28
2.4 Analytical framework 29
2.4.1 Linear Regression Model 28
2.5 Conceptual Framework 31
3.0 METHODOLOGY 34
3.1 Research Design 34
3.3 Population and Sampling techniques 37
3.4 Sample size and sampling Techniques 37
3.5 Instrument Data Collection 39
3.6 Validation and Reliability of Instrument 39
3.7 Method of data collection 39
3.8 Model Specification 40
3.10 Data Analysis Techniques 41
4.0 RESULTS AND DISCUSSION 43
4.1 Socio-Economic Characteristics of Respondents 43
4.2 Influence of HIV/AIDScourge on Farm Labour Productivity of Infected and
Non Infected Farmers 49
4.3Result of hypothesis 1 53
4.4Influence of Human Immunodeficiency Virus/Acquired ImmunoDeficiency
SyndromeScourge on Income of Infected and Non Infected farmer 55
4.5 Result of hypothesis 2 58
4.6 Relationship between Farm Labour Productivity and Income of Infected and Non Infected farmers 61
4.7 Constraints faced by infected and non-infected farmers 64
5.0 CONCLUSION AND RECOMMENDATIONS 66
5.1 Conclusion 66
5.2 Recommendation 67
5.3Contribution to knowledge 67
5.4 Suggestion for Further Study 68
REFERENCES 69-76
APPENDIX 77
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