Past and prospective electricity scenarios in Madagascar: The role of government energy policies

Praene, Jean-Philippe; Rasamoelina, Rindrasoa Miangaly; Ayagapin, Leslie

doi:10.1016/j.rser.2021.111321

Cited by 6 publications

(7 citation statements)

References 48 publications

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“…The second target of the NEP takes into account the high potential for renewable energy sources on the island (hydro, solar, wind, and biomass) and aims to fully harness these resources to supply clean and sustainable energy. Various projection scenarios and investment plans have been proposed to assess the feasibility of such a project [23,58,61,71,72,80,81].…”

Section: Introductionmentioning

confidence: 99%

Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms

Ramaharo,

RANDRIAMIFIDY

2023

Preprint

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The aim of this note is to identify the factors influencing renewable energy consumption in Madagascar. We tested 12 features covering macroeconomic, financial, social, and environmental aspects, including economic growth, domestic investment, foreign direct investment, financial development, industrial development, inflation, income distribution, trade openness, exchange rate, tourism development, environmental quality, and urbanization. To assess their significance, we assumed a linear relationship between renewable energy consumption and these features over the 1990–2021 period. Next, we applied different machine learning feature selection algorithms classified as filter-based (relative importance for linear regression, correlation method), embedded (LASSO), and wrapper-based (best subset regression, stepwise regression, recursive feature elimination, iterative predictor weighting partial least squares, Boruta, simulated annealing, and genetic algorithms) methods. Our analysis revealed that the five most influential drivers stem from macroeconomic aspects. We found that domestic investment, foreign direct investment, and inflation positively contribute to the adoption of renewable energy sources. On the other hand, industrial development and trade openness negatively affect renewable energy consumption in Madagascar.

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Section: Introductionmentioning

confidence: 99%

Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms

Ramaharo,

RANDRIAMIFIDY

2023

Preprint

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“…Research on the drivers of electricity intensity in Madagascar is limited, but the available literature provides valuable insights. In a detailed analysis of past and prospective electricity scenarios in Madagascar, Praene et al (2021) employed the LMDI decomposition method to decompose the electricity consumption of Madagascar from 1987 to 2015 into and activity effect (determined by the number of subscribers), structure effect (determined by the percentage of subscribers by sector) and intensity effect (determined by the electricity consumption per subscriber). The different sector categories considered are industrial, residential, Small and medium-sized enterprises/services, and public lighting.…”

Section: Index Decomposition Of Energy Demandmentioning

confidence: 99%

“…One of the primary motivations is the need to mitigate the environmental impact of energy consumption (Kabeyi and Olanrewaju, 2022). Indeed, the country's heavy reliance on fossil fuels contributes to greenhouse gas emissions, air pollution, and environmental degradation (Praene et al, 2019). As of 2017, fossil fuels accounted for 53% of electricity production, with 27% coming from heavy fuel oil and 26% from diesel fuel (MEH, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, there is a paucity of studies exploring the underlying drivers and trends shaping electricity-, or more generally energy-related metrics in the country. Notable exceptions include studies specific to the case of Madagascar by Praene et al (2017Praene et al ( , 2019Praene et al ( , 2021, as well as panel-based studies by Aboagye and Alagidede (2016), Akhmetov and Vundo (2018), Nkalu et al (2020), and Dokas et al (2022). To address this knowledge gap, this study employs a two-stage approach to investigate the determinants of electricity intensity in Madagascar.…”

Section: Introductionmentioning

confidence: 99%

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LMDI decomposition and macroeconomic drivers of electricity intensity in Madagascar

Ramaharo

2024

Preprint

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This study employs the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyze the drivers of overall electricity intensity in Madagascar over the period 2007-2022. The decomposition results reveal that the residential sector is the primary driver of overall electricity intensity, followed by the service and industry sectors. Notably, the industry sector has contributed to a decrease in intensity. Furthermore, the results indicate that the intensity effect has had a significant impact on increasing overall electricity intensity, whereas the structure effect has played a role in reducing total intensity. Building on these findings, we investigate the impact of key macroeconomic factors on the observed electricity intensity trend using the Auto Regressive Distributed Lag (ARDL) bounds testing approach with quarterly data over the same study period. The ARDL cointegrating approach estimation results reveal a long-run association between financial development, foreign direct investment, industry development, consumer energy inflation, and trade openness. Moreover, the long-run coefficients, which are further supported by the Dynamic Ordinary Least Squares (DOLS) estimates, indicate that financial development and trade openness have a positive and significant impact on electricity intensity in Madagascar, while foreign direct investment, industry development, and consumer energy inflation have a negative and significant impact, suggesting that these factors contribute to electricity efficiency. The Toda-Yamamoto non-causality approach uncovers unidirectional causal relationships, specifically from financial development, industrial development, and consumer energy inflation to electricity intensity, as well as from electricity intensity to foreign direct investment. These causal directions are further corroborated by the forecast-error variance decomposition, providing strong evidence for these relationships. These findings provide valuable insights for policymakers and stakeholders in Madagascar's energy sector, highlighting the importance of promoting energy efficiency initiatives.

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“…Electricity share, energy consumption intensity, economic structure, economic activity, and population are often considered to be influencing factors on electricity consumption in a country or region [26][27][28]. Praene et al [29] obtained three different effects related to the number of consumers that influenced the variation in electricity consumption: activity effect, structural effect, and intensity effect. Fang et al [30] decomposed China's electricity consumption into four factors: economic scale, economic geographical structure, electricity consumption intensity, and industrial electricity consumption structure.…”

Section: Literature Reviewmentioning

confidence: 99%

Decomposition Analysis of Regional Electricity Consumption Drivers Considering Carbon Emission Constraints: A Comparison of Guangdong and Yunnan Provinces in China

Chen,

Liu,

Kuang

et al. 2023

Energies

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Electricity consumption is closely linked to economic growth, social development, and carbon emissions. In order to fill the gap of previous studies on the decomposition of electricity consumption drivers that have not adequately considered carbon emission constraint, this study constructs the Kaya extended model of electricity consumption and analyzes the effects of drivers in industrial and residential sectors using the Logarithmic Mean Divisia Index (LMDI) method, and empirically explores the temporal and spatial differences in electricity consumption. Results show that: (1) During 2005–2021, the total final electricity consumption growth in Guangdong was much higher than that in Yunnan, but the average annual growth rate in Guangdong was lower, and the largest growth in both provinces was in the industrial sector. (2) The labor productivity level effect is the primary driver that increases total final electricity consumption (Guangdong: 78.5%, Yunnan: 87.1%), and the industrial carbon emission intensity effect is the primary driver that decreases total final electricity consumption (Guangdong: −75.3%, Yunnan: −72.3%). (3) The year-to-year effect of each driver by subsector is overall positively correlated with the year-to-year change in the corresponding driver, and declining carbon emission intensity is a major factor in reducing electricity consumption. (4) The difference in each effect between Guangdong and Yunnan is mainly determined by a change in the corresponding driver and subsectoral electricity consumption. Policy implications are put forward to promote energy conservation and the realization of the carbon neutrality goal.

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Past and prospective electricity scenarios in Madagascar: The role of government energy policies

Cited by 6 publications

References 48 publications

Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms

Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms

LMDI decomposition and macroeconomic drivers of electricity intensity in Madagascar

Decomposition Analysis of Regional Electricity Consumption Drivers Considering Carbon Emission Constraints: A Comparison of Guangdong and Yunnan Provinces in China

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