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Affiliation(s)

1. Department of Economics, Faculty of Economics and Administrative Science, Near East University, Nicosia 99138, North Cyprus
2. Data Scientist, Knowledge Corporation, Business Center No 310, Al Hilal Bank Buildingm AI Tawar Area, Al Qusais 2, Dubai, UAE
3. Senior Scientific Officer – Climatology and Environment Section, Ministry of Climate Change, Islamabad 44000, Pakistan
4. Department of Business Administration, University of Sindh, Jamshoro, Sindh 76060, Pakistan
5. Department of English Literature and Linguistics, University of Sindh, Jamshoro, Sindh 76060, Pakistan

ABSTRACT

Climate change has become a global phenomenon and is adversely affecting agricultural development across the globe. Developing countries like Pakistan where 18.9% of the GDP (gross domestic product) came from the agriculture sector and also 42% of the labor force involved in agriculture. They are directly and indirectly affected by climate change due to an increase in the frequency and intensity of climatic extreme events such as floods, droughts and extreme weather events. In this paper, we have focused on the impact of climate change on farm households and their adaptation strategies to cope up the climatic extremes. For this purpose, we have selected farm households by using multistage stratified random sampling from four districts of the Potohar region i.e. Attock, Rawalpindi, Jhelum and Chakwal. These districts were selected by dividing the Potohar region into rain-fed areas. We have employed logistic regression to assess the determinants of adaptation to climate change and its impact. We have also calculated the marginal effect of each independent variable of the logistic regression to measure the immediate rate of change in the model. In order to check the significance of our suggested model, we have used hypothesis testing.

KEYWORDS

Climate change, multistage stratified random sampling, impacts, adaptation strategies, logistic regression, marginal effect, Hypothesis testing.

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