Azerbaijan's renewable energy and nonparametric analyses

What is it about?

Although the number of econometric analyses related to the renewable energy sector in Azerbaijan is increasing, studies on nonparametric dimensionality reduction are rather sparse. Principal component analysis (PCA) and multiple correspondence analysis (MCA) were chosen to fill this apparent research gap. As a result, a large dataset including the renewable energy sector and selected key macroeconomic indicators was evaluated. The PCA procedure yielded four distinct principle components reflecting the main macroeconomic variables, renewable energy production, industry-energy relations and natural resource revenues. The PCA method offers the possibility to examine the precise correlations and the underlying patterns between the displayed clusters of variables. Meanwhile, the MCA-based cross-country assessment of Azerbaijan’s wind, solar and hydropower has struck somewhat pessimistic notes, as the country lags behind neighbouring and other post-Soviet countries (e.g. Estonia, Iran, Latvia, Russia) in developing its green energy sector.

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Photo by Bozhin Karaivanov on Unsplash

Photo by Bozhin Karaivanov on Unsplash

Why is it important?

I offer both in-depth and comparative nonparametric statistical methods to analyze the renewable energy sector in relation to key macroeconomic indicators and to produce a composite nationwide index score.

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