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Preliminary Results

This section presents key findings from the analysis of renewable energy usage between 2012 and 2013. Unfortunately, due to data limitations, poverty rate changes could not be included in the current results.

Descriptive Statistics

A total of 190 countries had available data for renewable energy usage in both 2012 and 2013. On average, countries increased their renewable energy share by approximately 2.3 percentage points, suggesting modest global progress toward cleaner energy.

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Methods

1. Sample

The dataset used in this study was drawn from the World Bank’s global development indicators database. The original dataset includes over 150 countries with data on various economic, environmental, and social indicators from 1960 to 2021. For this analysis, we subset the data to focus on two specific indicators: renewable energy consumption (% of total final energy consumption) and poverty headcount ratio at $1.90 a day (2011 PPP) (% of population).

The sample selection criteria included:

Only countries with available data for the years 2012 and 2013 for either or both of the target indicators.

Countries missing values for both indicators in either of the years were excluded.

After applying the above criteria, our final sample consisted of X countries for renewable energy analysis and Y countries for poverty analysis (sample sizes to be determined based on the cleaned dataset). The dataset includes a diverse range of countries across income levels and geographic regions, enabling a broad comparison of developmental progress.

2. Measures

The main variables used in this study are:

Renewable energy consumption (% of total final energy consumption) (indicator code: EG.FEC.RNEW.ZS)

Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) (indicator code: SI.POV.DDAY)

To analyze change over time, we calculated the year-over-year difference from 2012 to 2013 for both indicators:

ΔRenewable Energy = Value in 2013 − Value in 2012

ΔPoverty Rate = Value in 2012 − Value in 2013

(Note that the poverty rate difference is inverted to reflect improvement as a positive change.)

Countries were then ranked based on these differences to identify:

The countries with the largest increase in renewable energy usage, and

The countries with the largest decrease in poverty rate.

We also created a categorical variable to flag the top 10 performing countries in each indicator for potential deeper analysis or visualization.

3. Analyses

We employed descriptive statistics and ranking-based analysis to identify countries with the greatest improvements in renewable energy usage and poverty reduction between 2012 and 2013. The primary statistical approach included:

Computing differences in indicator values between 2012 and 2013

Ranking countries based on the computed change

Visualizing the top-performing countries using bar charts

No inferential statistical tests or predictive modeling were conducted, and thus the dataset was not split into training and test sets, nor was cross-validation applied. This study focused solely on historical trend comparison.

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"A Cross-Country Analysis of Changes in Renewable Energy Usage and Poverty Rates between 2012 and 2013 using World Bank Indicators"

Research Question:

"Which countries experienced the largest increase in renewable energy usage or the greatest reduction in poverty rates between 2012 and 2013, and what insights can be drawn from these changes?"

Motivation/rationale:

This study aims to highlight countries that made notable progress in renewable energy usage and poverty reduction between 2012 and 2013. Understanding where and how such improvements occurred can offer insights into effective development strategies and support global efforts toward achieving the UN Sustainable Development Goals, particularly in energy and poverty alleviation.

Implications:

Encourages the use of empirical data in evaluating development performance rather than relying solely on assumptions or narratives.