Deforestation: An implication of high rates of unemployed and low-Income household members in rural communities in Kebbi, Nigeria
Creators: name: Uba, Matthew
Publisher: name: Zenodo
Year: 2021

description: Deforestation has been a major environmental issue in Northern Nigeria and despite several advocacy, yet such practice has continued to endure. A root course factors are unemployment and low-income among households in Northern Nigeria. As a result of low social/financial status of the household, they depend highly on cutting down trees to make fuel wood (firewood) and charcoal (gotten from burnt wood) for the source of energy for their domestic and commercial activities. This was proven by the analysis of a secondary dataset using R-Programming, sourced from the World Bank Microdata Library, a survey carried out in 2015 in Kebbi, Nigeria titled Nigeria-Feed the Future Livelihood Project 2015, Baseline Survey worldbank.org. The dataset contains 3976 households observed and 296 values were found missing which resulted to analyzing 3758 household after the missing values were omitted. Variables describing the employed members of the household, energy sources for lighting fuel and energy sources for cooking fuel for the households were extracted from the secondary dataset. Results revealed that there are over 3000 households dependent on fuel wood as an energy source. Also, results (ANOVA) revealed that annual income of the households has significant impact on cooking fuel sources (0.0104&lt;0.05) and has a very strong significance on lighting fuel sources (0.000&lt;0.05). The low-income rate of households was evident showing the relationship between employed members of the households with a very strong significance on annual income of the households (0.000375&lt;0.05). This revealed that unemployed members of the households results to low-income of the households in Kebbi make them to highly depend on the use of fuel wood (firewood) and charcoal (gotten from burnt wood) on a dialy bases as a source of energy for cooking and lighting fuel. They also export and sell fuel wood and charcoal for financial gain to neighboring countries.
description: In the process of analyzing the dataset <strong>Kebbi.csv</strong> having 3976 observations, 269 values were discovered missing and was omitted. A new data frame Kebbitable.1 with 3758 observations was created. <strong>Variables</strong> -<strong>Employed_members:</strong> These are a numeric data describing how many members of the household in Kebbi worked in a business or in a self-employment in the past 12 month which is ranked (No = 0, Yes = 1) to determine the number of members of each household is employed. -<strong>Annual_income:</strong> These are numeric data on annual income of households ranked from 1 Naira (N1) to 20 Naira (N20) which is used to grade income level. Naira is the currency name for Nigeria with symbol (N). To determine the deforestation rate which one of its courses is the use of fuel wood and charcoal for source of energy for domestic (cooking, lighting, ironing), commercial (ironing, bakery, street fast food) and economic gain (selling of fuel wood and charcoal) purposes by households, the following variables were also analyzed. -<strong>Lighting_fuel_source:</strong> Ranked from 1 to 10 in the category of collected firwood, purchased firewood, grass, kerosene, phcn electricity, generator, gas, battery, candles, and others. -<strong>Cooking_fuel_source:</strong> Ranked from 1 to 9 in the category of collected firewood, purchased firewood, coal, grass, kerosene, phcn electricity, generator, gas, and others.
description: <strong>Method of Data Collection</strong> Survey method of data collection was conducted by the World Bank in the collection of data from 3976 household in the rural communities in Kebbi, Nigeria. 4 variables were extracted from the original dataset to form a new dataset (<strong>Kebbi.csv</strong>).Below are the description of the extracted variables. <strong>Method of Data Analysis</strong> Different analytical models were applied to analyze the variables using R Programming. The frequencies and the mean of each variable were determined respectively by histogram and boxplot. The null hypothesis (H<sub>0</sub>)(H<sub>0</sub>) was tested using One-Way Analysis of Variance (ANOVA) and will be rejected if (p&lt;0.05)(p&lt;0.05).