Macroeconomic drivers of financial performance in power generation firms across emerging and developed marketsERATION FIRMS ACROSS EMERGING AND DEVELOPED MARKETS
DOI:
https://doi.org/10.18041/1900-3803/entramado.2.12885Keywords:
Financial performance, Energy firms, Multiple factor analysisAbstract
This study examines the impact of macroeconomic factors on the financial performance of power generation firms, comparing emerging Latin American economies with those of a developed market. Based on panel data from 106 companies across six countries (2018–2022), multilevel modeling is used to assess firm- and country-level effects, complemented by Dual Multiple Factor Analysis (DMFA) to identify latent relationships among financial and macroeconomic variables. The results indicate that exchange rate fluctuations and inflation are significant determinants of return on equity (ROE), with coefficients of 0.57 and −0.32, respectively. Internal indicators, such as gross profit margin (β = 0.30) and quick ratio (β = 0.22), also exhibit strong positive associations with ROE. Differences in macroeconomic sensitivity between developed and emerging markets underscore the importance of context-specific financial strategies in the energy sector.
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1. AKHTAR, Shehla, JAVED, Benish, MARYAM, Atiya, SADIA, Haleema. Relationship between Financial Leverage and Financial Performance: Evidence from Fuel & Energy Sector of Pakistan. In: European Journal of Business and Management. 2012. https://core.ac.uk/download/pdf/234624292.pdf
2. AL ASBAHI, Ahmed; GANG, Feng; IQBAL, Wasim; ABASS, Qasier; MOSHIN, Muhammad; IRAM Robina. Novel approach of Principal Component Analysis method to assess the national energy performance via Energy Trilemma Index. In: Energy Reports. 2019. vol. 5, p. 704-713. https://doi.org/10.1016/j.egyr.2019.06.009
3. ALIANZA DEL PACÍFICO. Alianza del Pacífico. El poder de la integración. 2022. https://alianzapacifico.net/
4. AMAT RODRIGO, José. Análisis de Componentes Principales (Principal Component Analysis, PCA) y t-SNE. In: Ciencia de Datos. June 2017. https://cienciadedatos.net/documentos/35_principal_component_analysis
5. APAN, Mehmet; ISLAMOĞLU, Mehmet. Determining the impact of financial characteristics on firm profitability: An empirical analysis on Borsa Istanbul energy firms. In: WSEAS Transactions on Business and Economics. 2018. vol. 15, p. 547-559. https://d1wqtxts1xzle7.cloudfront.net/81166018/b085107-683-libre.pdf
6. ASIMAKOPOULOS, Ioannis; SAMITIS, Dimitrios. Firm-specific and economy wide determinants of firm profitability: Greek evidence using panel data. In: Managerial Finance. 2009. vol. 35, no. 11, p. 930-939.
7. BALTAGI, Badi Hani. Econometric analysis of panel data. 4 ed. Chichester: John Wiley & Sons, 2008.
8. BANCO INTERAMERICANO DE DESARROLLO. El sector energético: Oportunidades y desafíos. 2016. https://publications.iadb.org/es/publicacion/17152/el-sector-energetico-oportunidades-y-desafios
9. BARAKAT, Mahmoud; ELGAZZAR, Sara; HANAFY, Khaled. Impact of macroeconomic variables on stock markets: Evidence from emerging markets. In: International Journal of Economics and Finance. 2015. vol. 8, no. 1, p. 195. https://doi.org/10.5539/ijef.v8n1p195
10. BASTIDAS ORREGO, Lina María. ¿Hacia dónde irán los sectores eléctricos de los países de la región Andina? Tendencias posibles. In: Cuadernos de Administración. 2008. vol. 21, no. 35. https://revistas.javeriana.edu.co/index.php/cuadernos_admon/article/view/4009
11. CAPECE, Francesco; DI PILLO, Francisca; LEVIALDI, Nathan. The Performance Assessment of Energy Companies. In: APCBEE Procedia. 2013. vol. 5, p. 265-270. https://doi.org/10.1016/j.apcbee.2013.05.046
12. CHANG, Ting-Huan; HUANG, Chien-Ming; LEE, Ming-Chih. Threshold effect of the economic growth rate on the renewable energy development from a change in energy price: Evidence from OECD countries. In: Energy Policy. 2009. vol. 37, no. 12, p. 5796-5802. https://doi.org/10.1016/j.enpol.2009.08.049
13. DELEN, Dursun; KUZEY, Cemil; UYAR, Ali. Measuring firm performance using financial ratios: A decision tree approach. In: Expert Systems with Applications. 2013. vol. 40, p. 3970-3983. https://doi.org/10.1016/j.eswa.2013.01.012
14. DOPIERAŁA, Łukasz; MOSIONEK-SCHWEDA, Magdalena; LASKOWICZ, Tomasz. Financial performance of renewable energy producers: A panel data analysis from the Baltic Sea Region. In: Energy Reports. 2022. vol. 8, p. 11492-11503. https://doi.org/10.1016/j.egyr.2022.09.009
15. EMBER. Global Electricity Review. 2021. https://ember-climate.org/app/uploads/2021/03/Global-Electricity-Review-2021-translation-spanish-high-res.pdf
16. FAZEKAS, András; BATAILLE, Chris; VOGT-SCHILB, Adrien. Achieving Net-Zero Prosperity: How Governments Can Unlock 15 Essential Transformations. Inter-American Development Bank. 2022. https://doi.org/10.18235/0004364
17. GADEA LARA, Tomás. Cuáles son las oportunidades y desafíos que tiene la Argentina para avanzar en la urgente transición hacia energías renovables. In: RED/ACCIÓN. 2022. https://www.redaccion.com.ar/como-se-compone-la-matriz-energetica-argentina
18. GUPTA, Kusum. Do economic and societal factors influence the financial performance of alternative energy firms? In: Energy Economics. 2017. p. 172-182. https://doi.org/10.1016/j.eneco.2017.05.004
19. HERVÉ, Abdi; LYNNE, Williams; DOMINIQUE, Valentin. Multiple factor analysis: principal component analysis for multitable and multiblock data sets. In: Wiley Interdisciplinary Reviews: Computational Statistics. 2013. vol. 5, no. 2, p. 149-179. https://doi.org/10.1002/wics.1246
20. INTERNATIONAL ENERGY AGENCY – IEA. Global Energy Review 2021. Assessing the effects of economic recoveries on global energy demand and CO2 emissions in 2021. 2021. https://iea.blob.core.windows.net/assets/d0031107-401d-4a2f-a48b-9eed19457335/GlobalEnergyReview2021.pdf
21. JOAQUI-BARANDICA, Orlando; OROZCO-CERÓN, Oscar. Relación predictiva no lineal entre el PIB per cápita y la tasa de mortalidad: caso de estudio Reino Unido. In: Revista Desarrollo y Sociedad. 2023. no. 93, p. 177-206. https://doi.org/10.13043/DYS.93.5
22. LONG, Jason A. panelr: Regression Models and Utilities for Repeated Measures and Panel Data. 2020. https://cran.r-project.org/package=panelr
23. MINISTERIO DE RELACIONES EXTERIORES DEL PERÚ. Pacific Alliance Business and Investment Guide 2018 / 2019. 2018. https://alianzapacifico.net/download/pacific-alliance-business-and-investment-guide-2018-2019/
24. MORENO, Luis Fernando. Regulación del mercado de energía eléctrica en América Latina: La convergencia entre libre competencia e intervención estatal. Bogotá D.C.: Universidad Externado de Colombia, 2012. https://doi.org/10.4000/books.uec.125
25. MORINA, Fatbardha; ERGÜN, Uğur; HYSA, Eglantina. Understanding Drivers of Renewable Energy Firm’s Performance. In: Environmental Research, Engineering and Management. 2021. vol. 77, no. 3, p. 32-49. https://doi.org/10.5755/j01.erem.77.3.29230
26. MULLER, Rafael; REGO, Ezequiel. Privatization of electricity distribution in Brazil: Long-term effects on service quality and financial indicators. In: Energy Policy. 2021. vol. 159, p. 112602. https://doi.org/10.1016/j.enpol.2021.112602
27. MURILLO, Javier. Los modelos multinivel como herramienta para la investigación educativa. In: Revista Internacional de Investigación en Educación. 2008. vol. 1, no. 1, p. 45-62. https://revistas.javeriana.edu.co/index.php/MAGIS/article/view/3355
28. ORGANIZACIÓN LATINOAMERICANA DE ENERGÍA – OLADE. Panorama Energético de América Latina y El Caribe. 2021. https://biblioteca.olade.org/opac-tmpl/Documentos/old0442a.pdf
29. ORGANIZACIÓN LATINOAMERICANA DE ENERGÍA – OLADE. Generación eléctrica mundial y para América Latina y el Caribe (ALC) y su impacto en el sector energético por la pandemia producida por el COVID-19. 2021. https://www.olade.org/wp-content/uploads/2021/01/Generacion-electrica-mundial-y-para-America-Latina-y-el-Caribe-ALC_01-12-2020.pdf
30. OVIEDO-GÓMEZ, Andres; LONDONO-HERNANDEZ, Sandra; MANOTAS-DUQUE, Diego. Electricity Price Fundamentals in Hydrothermal Power Generation Markets Using Machine Learning and Quantile Regression Analysis. In: International Journal of Energy Economics and Policy. 2021. vol. 11, no. 5, p. 66–77. https://doi.org/10.32479/ijeep.11346
31. PWC MÉXICO. La Alianza del Pacífico. Una nueva era para América Latina. PricewaterhouseCoopers México, 2014. https://pacificallianceblog.com/wp-content/uploads/2018/01/2014-Pwc-La-Alianza-Pacifico-Una-Nueva-Era-para-América-Latina.pdf
32. PWC MÉXICO. El futuro de la Alianza del Pacífico: Integración para un crecimiento productivo. PricewaterhouseCoopers México S.C., 2016. http://pacificallianceblog.com/wp-content/uploads/2018/01/2016-Pwc-El-Futuro-de-la-Alianza-del-Pacífico-Integración-para-un-Crecimiento-Productivo.pdf
33. ROSSO MURILLO, John; RODRÍGUEZ RAMOS, Yeny. La rentabilidad de los servicios de electricidad, petróleo y gas en las Américas. Un análisis enfocado. In: Revista Facultad de Ciencias Económicas. 2021. vol. 29, no. 1, p. 27-48. https://doi.org/10.18359/rfce.4525
34. S&P DOW JONES INDICES. S&P Dow Jones Indices. 2022. https://www.spglobal.com/spdji/en/index-family/equity/emerging-equity/emerging-americas/#overview
35. SCHABEK, Tomasz. The financial performance of sustainable power producers in emerging markets. In: Renewable Energy. 2020. vol. 160, p. 1408-1419. https://doi.org/10.1016/j.renene.2020.06.067
36. TOMCZAK, Sebastian-Kamil. Comparison of the financial standing of companies generating electricity from renewable sources and fossil fuels: A new hybrid approach. In: Energies. 2019. vol. 12, no. 20, p. 3856. https://doi.org/10.3390/en12203856
37. UNIDAD DE PLANEACIÓN MINERO-ENERGÉTICA – UPME. Proyección de demanda de energía eléctrica y gas natural 2021-2035. 2020. https://www1.upme.gov.co/DemandayEficiencia/Paginas/Proyecciones-de-demanda.aspx
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