IDEAS home Printed from https://ideas.repec.org/a/ukm/jlekon/v53y2019i2p67-81.html
   My bibliography  Save this article

Impact of Natural Disasters on Biodiversity: Evidence Using Quantile Regression Approach

Author

Listed:
  • Kaur, Harpaljit

    (Taylor’s Business School Taylor’s University 47500 Subang Jaya MALAYSIA)

  • Habibullah, Muzafar

    (Institute of Agricultural and Food Policy Studies Universiti Putra Malaysia 43400 UPM Serdang Selangor MALAYSIA Putra Business School 43400 UPM, Serdang Selangor MALAYSIA)

  • Nagaratnam, Shalini

    (Universiti Putra Malaysia 43500 Serdang Malaysia)

Abstract

Biodiversity is vital as it supports major economic activities and employment but it is at risk and is declining rapidly in many parts of the world. This study examines the impact of total natural disasters on the number of endangered species (fish, mammal, bird and plants) for a sample of 110 countries in the year 2015. Ordinary least squares and quantile regression are employed to explain the relationship between occurrences of total disasters and species in danger for these countries. The OLS results suggest that the occurrences of natural disasters exhibit positive relationship with biodiversity loss. Our further analysis using quantile regression study suggest that countries with lower biodiversity loss are more likely to experience decrease of endangered plants with the increasing number of natural disaster occurrences as compared to countries with higher biodiversity loss. These countries will also experience more loss in birds in danger when the population grows. In addition, countries with higher biodiversity loss are more likely to face decrease in threatened birds due to the increase in the percentage of the protected area and income per capita as compared to countries with lower biodiversity loss. However, all the variables have no significance influence on the threatened fish species. Urban population growth effect on threatened mammals is greater at higher quantiles whereas the effect of income per capita is much greater in the countries with higher biodiversity loss but after a certain point, the income per capita decreases with higher biodiversity loss.

Suggested Citation

  • Kaur, Harpaljit & Habibullah, Muzafar & Nagaratnam, Shalini, 2019. "Impact of Natural Disasters on Biodiversity: Evidence Using Quantile Regression Approach," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 53(2), pages 67-81.
    • Handle: RePEc:ukm:jlekon:v:53:y:2019:i:2:p:67-81
    DOI: http://dx.doi.org/10.17576/JEM-2019-5302-6
    as

    Download full text from publisher

    File URL: http://www.ukm.my/jem/wp-content/uploads/2021/06/jeko_532-6.pdf
    Download Restriction: no
    File URL: https://libkey.io/http://dx.doi.org/10.17576/JEM-2019-5302-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Costanza, Robert & Fisher, Brendan & Mulder, Kenneth & Liu, Shuang & Christopher, Treg, 2007. "Biodiversity and ecosystem services: A multi-scale empirical study of the relationship between species richness and net primary production," Ecological Economics, Elsevier, vol. 61(2-3), pages 478-491, March.
    2. Halkos, George E., 2011. "Nonparametric modelling of biodiversity: Determinants of threatened species," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 618-635, July.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Strobl, Eric, 2012. "The economic growth impact of natural disasters in developing countries: Evidence from hurricane strikes in the Central American and Caribbean regions," Journal of Development Economics, Elsevier, vol. 97(1), pages 130-141.
    5. Hansen, Casper Worm, 2013. "Life expectancy and human capital: Evidence from the international epidemiological transition," Journal of Health Economics, Elsevier, vol. 32(6), pages 1142-1152.
    6. Nicholas Stern, 2008. "The Economics of Climate Change," American Economic Review, American Economic Association, vol. 98(2), pages 1-37, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Halkos, George E., 2011. "Nonparametric modelling of biodiversity: Determinants of threatened species," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 618-635, July.
    2. Chen, Xia & Fu, Qiang & Chang, Chun-Ping, 2021. "What are the shocks of climate change on clean energy investment: A diversified exploration," Energy Economics, Elsevier, vol. 95(C).
    3. Halkos, George, 2010. "Modelling biodiversity," MPRA Paper 39075, University Library of Munich, Germany.
    4. Muzafar Shah Habibullah* & Badariah Haji Din & Wei-Chong Choo & Siow-Hooi Tan, 2018. "The Number of Tourist Arrivals, Governance and Their Impact on Threatened Bird Species: Worldwide Evidence," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 28-36:6.
    5. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    6. Molyneux, Philip & Pancotto, Livia & Reghezza, Alessio & Rodriguez d'Acri, Costanza, 2022. "Interest rate risk and monetary policy normalisation in the euro area," Journal of International Money and Finance, Elsevier, vol. 124(C).
    7. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    8. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    9. Georgios Bertsatos & Plutarchos Sakellaris & Mike G. Tsionas, 2022. "Extensions of the Pesaran, Shin and Smith (2001) bounds testing procedure," Empirical Economics, Springer, vol. 62(2), pages 605-634, February.
    10. Salimata Sissoko, 2011. "Working Paper 03-11 - Niveau de décentralisation de la négociation et structure des salaires," Working Papers 1103, Federal Planning Bureau, Belgium.
    11. Korom, Philipp, 2016. "Inherited advantage: The importance of inheritance for private wealth accumulation in Europe," MPIfG Discussion Paper 16/11, Max Planck Institute for the Study of Societies.
    12. Daniele, Vittorio, 2007. "Criminalità e investimenti esteri. Un’analisi per le province italiane [The effect of organized crime on Foreign Investments. An Empirical Analysis for the Italian Provinces]," MPRA Paper 6417, University Library of Munich, Germany.
    13. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    14. Cuesta, Lizeth & Ruiz, Yomara, 2021. "Efecto de la globalización sobre la desigualdad. Un estudio global para 104 países usando regresiones cuantílicas [Effect of globalization on inequality. A global study for 104 countries using quan," MPRA Paper 111022, University Library of Munich, Germany.
    15. Dutta, Anupam & Bouri, Elie & Rothovius, Timo & Uddin, Gazi Salah, 2023. "Climate risk and green investments: New evidence," Energy, Elsevier, vol. 265(C).
    16. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    17. Cowling, Marc & Ughetto, Elisa & Lee, Neil, 2018. "The innovation debt penalty: Cost of debt, loan default, and the effects of a public loan guarantee on high-tech firms," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 166-176.
    18. Guili Liao & Qimeng Liu & Rongmao Zhang & Shifang Zhang, 2022. "Rank test of unit‐root hypothesis with AR‐GARCH errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 695-719, September.
    19. Shweta Bahl & Ajay Sharma, 2021. "Education–Occupation Mismatch and Dispersion in Returns to Education: Evidence from India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 251-298, January.
    20. Nguyen, Thao & Bai, Min & Hou, Greg & Vu, Manh-Chien, 2020. "State ownership and adjustment speed toward target leverage: Evidence from a transitional economy," Research in International Business and Finance, Elsevier, vol. 53(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ukm:jlekon:v:53:y:2019:i:2:p:67-81. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Muhammad Asri Abd Ghani (email available below). General contact details of provider: https://edirc.repec.org/data/feukmmy.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.