Dimensionality reduction analysis of the renewable energy sector in Azerbaijan: nonparametric analyses of large datasets

Ibrahim Niftiyev

doi:https://doi.org/10.59170/stattrans-2024-016

Dimensionality reduction analysis of the renewable energy sector in Azerbaijan: nonparametric analyses of large datasets

Ibrahim Niftiyev Department of International Economics and Business, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan ORCID:https://orcid.org/0000-0003-3437-9824 Statistics in Transition new series, vol. 25, 2024, 2, pages: 81-102 Published online: 5 June 2024 https://doi.org/10.59170/stattrans-2024-016 Citation: Niftiyev, I., 2024. Dimensionality reduction analysis of the renewable energy sector in Azerbaijan: nonparametric analyses of large datasets. Statistics in Transition new series, 25(2), pp. 81-102. https://doi.org/10.59170/stattrans-2024-016

211 Views 26 Downloads

ARTICLE

(English) PDF

ABSTRACT

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. These findings are of great interest to policymakers, businesses and academics who wish to gain deep insight into the Azerbaijani economy in terms of renewable energy production. The practical value of the present work also lies in the fact that it analyses a multidimensional and relatively longitudinal dataset (1990–2022), which is an example of a methodological application of two nonparametric approaches.

KEYWORDS

Azerbaijani economy, energy transition, multiple correspondence analysis (MCA), nonparametric analysis, renewable energy, principal component analysis (PCA).

REFERENCES

Acar, S., Altintaş, N., Haziyev, V., (2023). The effect of financial development and economic growth on ecological footprint in Azerbaijan: An ARDL bound test approach with structural breaks. Environmental and Ecological Statistics, 30(1), pp. 41–59.

Al-Sarihi, A., Mansouri, N., (2022). Renewable energy development in the Gulf cooperation council countries: Status, barriers, and policy options. Energies, 15(5), 1923.

Aydin, U., (2019). Energy insecurity and renewable energy sources: Prospects and challenges for Azerbaijan. ADBI Working Paper Series No. 992.

Baxter, M. J., Cool, H. E. M., Heyworth, M. P., (1990). Principal component and correspondence analysis of compositional data: some similarities. Journal of Applied Statistics, 17(2), pp. 229–235.

Brown, J. D., (2009). Choosing the right type of rotation in PCA and EFA. JALT Testing & Evaluation SIG Newsletter, 13(3), pp. 20–25.

Butenko, V., (2022). EU external energy policy: The case of Azerbaijan. Przegląd Europejski, 1, pp. 61–71.

Cherp, A., Vinichenko, V., Jewell, J., Brutschin, E., Sovacool, B., (2018). Integrating techno-economic, socio-technical and political perspectives on national energy transitions: A meta-theoretical framework. Energy Research & Social Science, 37, pp. 175–190.

Eichberger, S., Hajiyeva, G. E., Leow, W. J., Damianova, A. J., Golub, E. S., Govorukha, K., … Bagirov, F., (2022). Azerbaijan: Towards green growth-issues Note. World Bank Group, USA.

Eurobserv-er., (2023). Photovoltaic barometer 2023. Eurobserv-er, Available at: https://www.eurobserv-er.org/photovoltaic-barometer-2023/ [Accessed 22.01.2024].

Evwind., (2023). Exploring the Untapped Potential of Wind Energy in Lithuania’s Energy Market. REVE, Available at: https://www.evwind.es/2023/07/05/exploring-theuntapped-potential-of-wind-energy-in-lithuanias-energy-market/92629 [Accessed 22.01.2024].

Guliyeva, S., (2023). Energy consumption, economic growth and CO2 emissions in Azerbaijan. Multidisciplinary Science Journal, 5(4), 2023052.

Hamid, H., Aziz, N., Huong, P. N. A., (2016). Variable extractions using principal component analysis and multiple correspondence analysis for large number of mixed variables classification problems. Global Journal of Pure and Applied Mathematics, 12(6), pp. 5027–5038.

Hamidova, L., (2018). Diversification of the economy of Azerbaijan: How to overcome resource dependence. In Sosyoekonomik Boyutlariyla Inovasyon, Manisa Celal Bayar Üniversitesi Yayinlari, No. 34, pp. 11–18.

Ibadoghlu, G., (2022). Problems and prospects of transition to alternative energy in Azerbaijan. SSRN Electronic Journal, Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4249068 [Accessed 26.09.2023].

Ibadoghlu, G., (2023). Is the increase in gas exports from Azerbaijan to Europe an illusion or a reality?. SSRN Electronic Journal, Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4361366 [Accessed 26.09.2023].

International Energy Agency–IEA., (2023). Azerbaijan Energy Profile. IEA Publications. Available at: https://iea.blob.core.windows.net/assets/0528affc-d2ba-49c9-ac25-17fc4e8724f7/AzerbaijanEnergyProfile_2023.pdf [Accessed 22.01.2024].

International Renewable Energy Agency., (2019). Renewables Readiness Assessment Republic of Azerbaijan. Available at: https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2019/Dec/IRENA_RRA_Azerbaijan_2019.PDF [Accessed 22.01.2024].

Jebli, M. B., Farhani, S., Guesmi, K., (2020). Renewable energy, CO2 emissions and value added: Empirical evidence from countries with different income levels. Structural Change and Economic Dynamics, 53, pp. 402–410.

Joint Research Centre-European Commission., (2008). Handbook on constructing composite indicators: Methodology and user guide. OECD publishing.

Jolliffe, I. T., (2002). Principal component analysis for special types of data. Springer, New York, pp. 338–372.

Jolliffe, I. T., Cadima, J., (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202.

Kalayci, Ş., (2005). Faktör analizi. In Kalayci, Ş. (Ed.), SPSS Uygulamali Çok Degişkenli Istatistik Teknikleri. Asil Yayin Dagitim Ltd. Şti., Ankara, Türkiye.

Kroonenberg, P. M., Greenacre, M. J. (2004). Correspondence analysis. Encyclopedia of statistical sciences, Wiley, Chichester.

Mammadli, N., (2022). Azerbaijan Pushes Ahead with Plan to Increase Renewables Share in Energy Mix to 30% by 2030. Available at: https://caspiannews.com/newsdetail/azerbaijan-pushes-ahead-with-plan-to-increase-renewables-share-in-energymix-to-30-by-2030-2022-6-21-0/ [Accessed 01.10.2023].

Mehdiyev, M., (2022). Azerbaijan Pushes for Renewables Expansion with Major Projects. Available at: https://caspiannews.com/news-detail/azerbaijan-pushes-for-renewablesexpansion-with-major-projects-2022-2-15-0/ [Accessed 01.10.2023].

Mukhtarov, S., Aliyev, J., Maharramli, S., (2022). Does institutional quality affect renewable energy in oil-rich developing countries? Evidence from Azerbaijan. In: Circular economy and the energy market: Achieving sustainable economic development through energy policy, pp. 173–184, Cham: Springer International Publishing.

Ostrom, E., (2007). A diagnostic approach for going beyond panaceas, National Academy of Sciences, 104(39), pp. 15181–15187,

Ostrom, E., (2008). Doing institutional analysis: Digging deeper than markets and hierarchies. In: Claude Ménard, Mary M. Shirley (Eds.), Handbook of New Institutional Economics, Springer, Berlin, Heidelberg, pp. 819–848.

Sarstedt, M., Mooi, E., (2014). A concise guide to market research. The Process, Data, and Methods Using IBM SPSS Statistics. Springer, Berlin, Heidelberg.

Tastan, M., Yilmaz, K., (2008). Organizational citizenship and organizational justice scales’ adaptation to Turkish. Egitim ve Bilim, 33(150), pp. 87–96.

Van Rijckevorsel, J. L., De Leeuw, J., (1988). Component and correspondence analysis. Dimension reduction by functional approximation. Wiley Series in Probability and Mathematical Statistics, Wiley, Chichester.