| dc.description.abstract | This study, conducted in the Kigoma district of Tanzania, aimed to assess the effects of
climate change on coffee production, a critical economic and agricultural activity in the
region. Utilizing a sample size of 384 respondents, including coffee farmers, farmer groups,
and various stakeholders involved in the coffee production value chain. A descriptive
statistical analysis was performed to determine the frequencies and percentages of
quantitative data, which were collected through a structured questionnaire. The qualitative
data collected through in-depth interviews, open-ended questions, observation, and document
review was analyzed using thematic analysis, identifying and analyzing patterns and themes
in the data, categorizing the data, and interpreting the findings. The findings of the study are
presented clearly and concisely using tables and graphs.
A multinomial Probit model was employed on the collected data and analyzed using the
statistical software STATA version 18. The P-values for a Probit Model, analyzing the
significance of variables y_hat and y_hat_square, were examined. The p-value for y_hat is
0.000, indicating its statistical significance and suggesting it has a substantial impact on the
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model's dependent variable. Conversely, y_hat_square has a p-value of 0.824, signifying its
lack of statistical significance, which implies that this variable does not meaningfully
contribute to the model's predictive ability. The results show a notable relationship between
perceptions of changes in rainfall patterns and their reported influence on coffee cultivation.
Respondents who acknowledged changes in rainfall patterns tended to link them with
negative consequences on coffee production. Changes in sunshine patterns and soil quality
were also considered important factors influencing coffee production outcomes.
Additionally, demographic data provided insights into the community's capacity to adapt and
mitigate its effects. Factors such as age, educational background, and experience were
essential in determining resilience and adaptability to changing environmental conditions.
The gender distribution highlighted the significant role of women in coffee farming and their
potential impact on adaptation strategies. | en_US |
