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Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis

Author

Listed:
  • Waweru David

    (Technical University of Kenya)

  • Mose Naftaly

    (University of Eldoret)

Abstract

This study applied a logistic regression model to determine the odds ratio of selecting clean versus unclean energy as the main household fuel choice. This study also undertook to establish the coefficients of the factors determining household fuel energy choice. A large microeconomic dataset from KIPPRA’s comprehensive study and analysis on fuel use patterns in Kenya (2010) was employed to carry out the analysis. This study employed a multinomial logit regression model to determine the fuel choices and patterns of cooking fuels in urban Kenyan households. The results showed that in addition to income, there are several socio-demographic factors such as education, gender, and age that were important in determining household fuel choice. To encourage clean fuel use, the authorities should carry out public education campaigns, and ensure the availability of these fuels in all areas to avoid harmful effects of biomass fuels and kerosene, and more modern and efficient appliances should be made available at affordable rates to ensure more efficient use of these forms of clean energy.

Suggested Citation

  • Waweru David & Mose Naftaly, 2022. "Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 18(2), pages 30-41, June.
  • Handle: RePEc:vrs:finiqu:v:18:y:2022:i:2:p:30-41:n:1
    DOI: 10.2478/fiqf-2022-0011
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    Cited by:

    1. Oyeniran, Ishola Wasiu & Isola, Wakeel Atanda, 2023. "Patterns and determinants of household cooking fuel choice in Nigeria," Energy, Elsevier, vol. 278(PA).

    More about this item

    Keywords

    fuel; choices; households; energy; cooking; urban; logit;
    All these keywords.

    JEL classification:

    • D15 - Microeconomics - - Household Behavior - - - Intertemporal Household Choice; Life Cycle Models and Saving
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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