Time Bomb Ticking

Time Bomb Ticking

According to the Economic Survey 2017-18, Volume-1 (released in January, 2018), please click here to read more:


• The volatility of agricultural growth in India has declined substantially over time: from a standard deviation of 6.3 percent between 1960 and 2004 to 2.9 percent since 2004. In particular, production of cereals has become more robust to drought. &*

• The broad pattern of rising temperatures post 1970s is common to both seasons. The average increase in temperature between the most recent decade and the 1970s is about 0.45 degrees and 0.63 degrees in the kharif and rabi seasons, respectively. These trends are consistent with those reported in Rajeevan (2013). Between the 1970s and the last decade, kharif rainfall has declined on average by 26 millimeters and rabi rainfall by 33 millimeters. Annual average rainfall for this period has on average declined by about 86 millimeters.

• The proportion of dry days (rainfall less than 0.1 mm per day), as well as wet days (rainfall greater than 80 mm per day) has increased steadily over time since 1970. Thus, the imprint of climate change is clearly manifest in the increasing frequency of extreme weather outcomes.

• Temperature increases have been particularly felt between the last decade (2005-2015) and the period 1950-1980 in the North-East, Kerala, Tamil Nadu, Kerala, Rajasthan and Gujarat. Parts of India, for example, Punjab, Odisha and Uttar Pradesh have been the least affected. In contrast, extreme deficiencies in rainfall between the last decade (2005-2015) and the period 1950-1980 are more concentrated in Uttar Pradesh, North-East, and Kerala, Chattisgarh and Jharkhand. 

• Extreme temperature shocks, when a district is significantly hotter than usual (in the top 20  percentiles of the district-specific temperature  distribution), results in a 4 percent decline in agricultural yields during the kharif season and a 4.7 percent decline in rabi yields. Similarly, extreme rainfall shocks - when it rains significantly less than usual (bottom 20 percentiles of the district-specific rainfall  distribution). The result is a 12.8 percent decline in kharif yields, and a smaller, but not insignificant decline of 6.7 percent in rabi yields.

Impact of weather shocks on agricultural yields

• Unirrigated areas – defined as districts where less than 50 percent of cropped area is irrigated -- bear the brunt of the vagaries of weather. For example, an extreme temperature shock in unirrigated areas reduces yields by 7 percent for kharif and 7.6 percent for rabi. Similarly, the effects of extreme rainfall shocks are 14.7 percent and 8.6 percent (for kharif and rabi, respectively) in unirrigated areas, much larger than the effects these shocks have in irrigated districts.

• Even after controlling for the level of rainfall, the number of dry days (defined as days during the monsoon with rainfall less than 0.1 millimetres) exerts a significant negative influence on productivity: holding the amount of rainfall constant, each additional dry day during the monsoon reduces yields by 0.2 percent on average and by 0.3 percent in unirrigated areas.

• Extreme temperature shocks reduce farmer incomes by 4.3 percent and 4.1 percent during kharif and rabi respectively, whereas extreme rainfall shocks reduce incomes by 13.7 percent and 5.5 percent.

Impact of weather shocks on farm revenue

• In a year where temperatures are 1 degree Celsius higher farmer incomes would fall by 6.2 percent during the kharif season and 6 percent during rabi in unirrigated districts. Similarly, in a year when rainfall levels were 100 millimetres less than average, farmer incomes would fall by 15 percent during kharif and by 7 percent during the rabi season.

• Swaminathan et. al. (2010) show that a 1degree Celsius increase in temperature reduces wheat production by 4 to 5 percent, similar to the effects found here.

• A study by the IMF, (2017) finds that for emerging market economies a 1 degree Celsius increase in temperature would reduce agricultural growth by 1.7 percent, and a 100 millimetres reduction in rain would reduce growth by 0.35 percent.

• Climate change models, such as the ones developed by the Inter-governmental Panel on Climate Change (IPCC), predict that temperatures in India are likely to rise by 3-4 degree Celsius by the end of the 21st century (Pathak, Aggarwal and Singh, 2012). These predictions combined with our regression estimates imply that in the absence of any adaptation by farmers and any changes in policy (such as irrigation), farm incomes will be lower by around 12 percent on an average in the coming years. Unirrigated areas will be the most severely affected, with potential losses amounting to 18 percent of annual revenue.

• Applying IPCC-predicted temperatures and projecting India’s recent trends in precipitation, and assuming no policy responses, give rise to estimates for farm income losses of 15 percent to 18 percent on average, rising to 20 percent-25 percent for unirrigated areas. At current levels of farm income, that translates into more than Rs. 3,600 per year for the median farm household.

• India pumps more than twice as much groundwater as China or United States (Shah, 2008). Indeed global depletion is most alarming in North India.

• Analysis of groundwater stations reveals a 13 percent decline in the water table over the past 30 years.

• Technologies of drip irrigation, sprinklers, and water management—captured in the “more crop for every drop” campaign—may well hold the key to future Indian agriculture (Shah Committee Report, 2016; Gulati, 2005) and hence should be accorded greater priority in resource allocation.

• Building on the current crop insurance program (Pradhan Mantri Fasal Bima Yojana), weather-based models and technology (drones for example) need to be used to determine losses and compensate farmers within weeks (Kenya does it in a few days).

• Inadequate irrigation, continued rain dependence, ineffective procurement, and insufficient investments in research and technology (non-cereals such as pulses, soyabeans, and cotton), high market barriers and weak post-harvest infrastructure (fruits and vegetables), and challenging non-economic policy (livestock).

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