Weather Variability, Agricultural Revenues and Internal Migration: Evidence from Pakistan ,Working Paper 101 -15

Working Papers » Weather Variability, Agricultural Revenues and Internal Migration: Evidence from Pakistan

By : Heman D. Lohano

Migration is a widely used adaptation response to climate and weather variability. In this paper, we investigate how variability in weather affects migration through the agricultural channel. We estimate an instrumental variables regression model that allows us to isolate the impacts of weather from other drivers of migration and analyze the impact of weather-driven changes in the crop revenue per hectare on the in-migration rate. We use panel data for 50 districts of Pakistan
and four time periods, 1971-76, 1976-81, 1988-93, and 1993-98, and estimate a two-way error components model, controlling for unobserved district-specific and time-specific effects. Results show that temperature has a nonlinear effect, i.e., as temperature increases, the crop revenue per hectare initially increases and then declines. Furthermore, a 1 ˚C increase in the variability (standard deviation) of temperature reduces expected crop revenue per hectare by around 7.5 percent. The instrumental variables regression results show that a 1 percent weather-driven decrease in the crop revenue per hectare induces, on average, a 2 to 3 percent decrease in the in-migration rate into a district. Predicted increases in temperature and its variability during 2016-2035 (relative to 1971-1998) are likely to decrease crop revenues in relatively warm districts and increase them in cooler districts. These effects would decrease the in-migration rate in 18- 32 districts (36-64 percent) and increase the rate in the remaining 18-32 districts. Thus, the extent and scope of the impacts of weather variability on migration in Pakistan depend on a district's geographic location and the variability of temperature in the future.

Keywords :Migration, weather variability, climate change, agriculture, panel data model, instrumental variables regression, Pakistan

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