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Unveiling the non-linear impact of sectoral output on environmental pollution in Malaysia

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Abstract

This paper investigates the non-linear impacts of the agricultural, industrial, financial, and service sectors on environmental pollution in Malaysia during the 1980–2018 period. It employs the extended STIRPAT model and two indicators of environmental pollution (carbon dioxide emissions and ecological footprints). It uses the autoregressive distributed lag (ARDL) technique to estimate the parameters. Evidence from the study indicate that the agricultural, industrial, and service sectors have inverted U-shaped non-linear impacts on carbon dioxide emissions and ecological footprints, while the financial sector has a U-shaped non-linear relationship with carbon dioxide emissions and ecological footprint. These empirical outcomes are robust to diagnostic tests, structural breaks, and alternative estimation technique and proxies. The economic implication of this paper is that, at the early stage of sectoral growth, the pollution intensity of sectoral output increases, but after a certain turning point, a further increase in sectoral output will reduce environmental pollution. Precisely, environmental pollution will reduce if the agricultural, industrial, and service sectors exceed threshold levels of 11%, 44%, and 49% of GDP, respectively, while environmental pollution will be aggravated if financial sector exceeds a threshold level of 94%. Therefore, efforts to mitigate environmental pollution in Malaysia should integrate sectoral growth to attain sustainable development.

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Notes

  1. All data were obtained from World Development Indicators published by the World Bank in 2020. Available online: https://databank.worldbank.org/source/world-development-indicators.

  2. We also experiment with agricultural land area (as share of total land area) as an alternative proxy (Haider et al. 2020).

  3. We also experiment with manufacturing value added relative to GDP as alternative proxy (Rudolph and Figge 2017).

  4. We experiment with stock market (market capitalization relative to GDP) as alternative proxy (Shahbaz et al. 2016).

  5. In a separate regression, we add all the sectors in one model and run the analysis.

  6. For detailed information on how to compute the ecological footprint, see https://www. footprintnetwork.org/.

  7. The structural change hypothesis posits that a country initially shifts from a low-emission agriculture sector to a high-emission industrial sector and eventually to a low-emission service sector (Hashmi et al. 2020).

  8. The results are not reported for want of space, but available upon request.

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Availability of data and materials

The data used for our paper are available in World Development Indicators published by the World Bank in 2020 and the Global Footprint Network published in 2020.

Available online: https://databank.worldbank.org/source/world-development-indicators

https://www.footprintnetwork.org/our-work/ecological-footprint/.

Funding

This research has been carried out under project FRGS/1/2020/SS0/TAYLOR/03/1 funded by the Ministry of Higher Education of Malaysia.

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Authors and Affiliations

  1. School of Accounting and Finance, Taylor’s University, Subang Jaya, Selangor, Malaysia

    Kizito Uyi Ehigiamusoe

  2. Economics Program, School of Social Sciences, Universiti Sains Malaysia, Gelugor, Penang, Malaysia

    Hooi Hooi Lean

  3. School of Management and Marketing, Taylor’s University, Subang Jaya, Selangor, Malaysia

    Sotheeswari Somasundram

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  1. Kizito Uyi Ehigiamusoe
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  2. Hooi Hooi Lean
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  3. Sotheeswari Somasundram
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Contributions

All the authors contributed to the paper.

Dr. Kizito Uyi Ehigiamusoe: conceptualization, data collection, data analysis, writing

Prof. Hooi Hooi Lean: supervision, review, editing

Dr. Sotheeswari Somasundram: literature review, data analysis

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Correspondence to Kizito Uyi Ehigiamusoe.

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Appendix 1

Appendix 1

Fig. 2
figure 2figure 2

The trends in environmental pollution and sectoral growth in Malaysia

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Table 7 ARDL estimations using alternative proxies of sectoral growth
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Ehigiamusoe, K.U., Lean, H.H. & Somasundram, S. Unveiling the non-linear impact of sectoral output on environmental pollution in Malaysia. Environ Sci Pollut Res 29, 7465–7488 (2022). https://doi.org/10.1007/s11356-021-16114-4

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