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Principal component regression analysis of electricity consumption factors in Madagascar

Author

Listed:
  • Ramaharo, Franck M.
  • Rajaonarison, Njakanasandratra R.

Abstract

We carry out principal component regression analysis on a dataset consisting of selected relevant economic and energy indicators in order to identify the main driving factors impacting the electricity consumption in Madagascar. Our results show that in accordance with the country's current energy profile, factors related with rural electrification have the most influence on electricity consumption in Madagascar.

Suggested Citation

  • Ramaharo, Franck M. & Rajaonarison, Njakanasandratra R., 2023. "Principal component regression analysis of electricity consumption factors in Madagascar," MPRA Paper 116142, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:116142
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    File URL: https://mpra.ub.uni-muenchen.de/116142/1/MPRA_paper_116142.pdf
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    Cited by:

    1. Ramaharo, Franck Maminirina & RANDRIAMIFIDY, Michael Fitiavana, 2023. "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," AfricArxiv pfrhx, Center for Open Science.

    More about this item

    Keywords

    principal component analysis; principal component regression; electricity consumption;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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