Pakistan is among the most vulnerable countries in the South Asian region given still overwhelming dependence of its population on agriculture which in turn mainly depends on the Indus Basin River System. The intensity and frequency of extreme climate events have increased in Pakistan during the recent decades.
In rural Pakistan, women and elderly are likely to suffer the most from adverse impacts of climate change as majority of them are engaged in/dependent on agriculture which is highly climate sensitive. Women and children are already an underpaid, overworked and exploited resource‘ and climate change will further increase this workload and accentuate their vulnerability. Yet, the gender vulnerability is one of the most ignored areas in the climate research.
This research explores the impact of climate change and gender differentiated socio-economic factors on household vulnerability. The study is based on the Climate Change Impact Survey (CCIS), 2013 data collected from 3430 farm households located in 16 districts of Pakistan representing all the major cropping systems and various categories of farms by tenancy and size of operational holding.
The results regarding health vulnerability regression model are suggestive that family composition by gender and age as well as literacy among females are important determinants of health vulnerability. It is observed that the households with higher number of younger family members are more health vulnerable. The farm households which have higher female ratio in their families are found to be more health vulnerable; whereas the households with greater ratio of educated females in the family are less health vulnerable. Finally, the results suggest that almost all climatic factors except Rabi season deviation of precipitation are important determinant of the health vulnerability and all the climatic variables enhance household level health vulnerability except the long run norm of the Kharif precipitation and Rabi-temperature which reduces health vulnerability.
The results of binary logit model estimated for food security are suggestive that family size and literacy among female members of the household are important determinants of the food security both affecting it positively and significantly. However, the composition of family by gender (female ratio) is not an important determinant of household food security. Finally, deviation of Rabi temperature from the long run norm and that of Rabi precipitation and Kharif precipitation have statistically significant effect on food security. The deviation in Rabi temperature has the adverse impact on food security as it affects wheat productivity, a staple food in Pakistan. The precipitation deviations in both the seasons have a positive impact on food security.