Impact of natural disasters on biodiversity: evidence using quantile regression approach

Harpaljit Kaur, Muzafar Shah Habibullah, Shalini Nagaratnam

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)67-81
Number of pages15
JournalJurnal Ekonomi Malaysia
Volume53
Issue number2
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Biodiversity loss
  • Quantile regression
  • Species

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