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Gauging the market potential for natural gas among Philippine manufacturing firms

Author

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  • Ravago, Majah-Leah V.
  • Fabella, Raul V.
  • Jandoc, Karl Robert L.
  • Frias, Renzi G.
  • Magadia, J. Kathleen P.

Abstract

Securing energy supply and pursuing low-carbon economic growth have become doubly challenging for the Philippines as it faces depletion of its indigenous natural gas. Importing liquefied natural gas is seen as the immediate solution. Our objective is to gauge the extent of the potential demand for natural gas among manufacturing firms. Specifically, we aim to determine the likelihood of switching to natural gas among firms in manufacturing ecozones, which takes the lion share of 85% of total exports. Using logistical regression, we find that the extent of the firms' knowledge about natural gas and their production process are the primary determinants of the likelihood to switch. For firms with heating component and those that perceived natural gas to be more cost-competitive, the predictive probability to switch is higher by 39.4 percentage points compared to their counterparts. More knowledgeable firms have 19.1 percentage points higher predictive probability of switching than less knowledgeable firms. The study is important for low-income countries as it sheds light on the measures its manufacturing industry can take to become cleaner and more competitive and the obstacles to transitioning to relatively cleaner natural gas and renewable sources, ultimately replacing the more expensive diesel fuel.

Suggested Citation

  • Ravago, Majah-Leah V. & Fabella, Raul V. & Jandoc, Karl Robert L. & Frias, Renzi G. & Magadia, J. Kathleen P., 2021. "Gauging the market potential for natural gas among Philippine manufacturing firms," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221018119
    DOI: 10.1016/j.energy.2021.121563
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    2. Zhou, Dengji & Jia, Xingyun & Ma, Shixi & Shao, Tiemin & Huang, Dawen & Hao, Jiarui & Li, Taotao, 2022. "Dynamic simulation of natural gas pipeline network based on interpretable machine learning model," Energy, Elsevier, vol. 253(C).

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    More about this item

    Keywords

    Liquefied natural gas use; Industry processes; Philippines; Logit regression; Lasso technique;
    All these keywords.

    JEL classification:

    • L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities
    • L6 - Industrial Organization - - Industry Studies: Manufacturing
    • N75 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Asia including Middle East
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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