In its budget 2017-18, the government has taken up several measures to revive the country’s agriculture economy. The emphasis on agricultural insurance through higher allocation for the Pradhan Mantri Fasal Bima Yojana (PMFBY), and other major allocations for the sector, are expected to boost credit flow to farmers apart from expanding crop insurance and irrigation coverage.
The commitment shown towards agricultural insurance is an important step by the government, as it will help to provide financial stability for farmers. Agriculture is risky business and is susceptible to volatility in production and commodity prices. Hence, it’s important to encourage farmers to use innovative agriculture services and technology, which in turn will improve farm productivity and income, and help them deal with post-harvest challenges.
Until a decade or so, agricultural insurance was a sector that developed mainly outside Asia. This started to change after 2005, when India and China began expanding their own agriculture insurance plans. Since then, we have seen a dramatic development, so much so that India is one of the largest agriculture markets in the world today, with index-based crop insurance covering a wide variety of crops in major provinces of the country.
Still, there has been low penetration of agriculture insurance in India, with challenges like insufficient risk coverage, delayed and inaccurate claim assessment, and leakage.
The banking channel continues to drive distribution of agriculture insurance, but there is a need for insurance companies to reach rural markets through new marketing mechanisms apart from the traditional bancassurance model. The challenges of infrastructure and distribution can be overcome with careful planning, innovative use of technology and favourable government policies.
The government, through the PMFBY, is trying to bring more farmers (targeting 50% by 2018) under the scheme’s ambit. However, several key challenges need to be addressed to achieve this goal.
Firstly, it is important that forecasts for seasonal crop productions are made with the highest possible accuracy, and field warnings detected early so that an action plan may be implemented for irrigation, agri-credit and agri-inputs.
Secondly, stakeholders such as the government, insurers and agricultural research agencies need to be adequately equipped with the necessary technological know-how to deal with some of the farming issues.
The introduction of new technology services into agriculture can provide a more detailed picture of risk at the farm level without the costs of collecting data manually. In addition to technological intervention, it is necessary to keep time lags in publishing crop yield statistics for the cropping period to a minimal.
Historically, government officials in India have conducted random-sample crop-cutting experiments (CCEs) to arrive at estimations of yield at the sub-district level or at even finer granularity. The process is resource-heavy, and prone to sampling and non-sampling errors and manual subjectivities. It is, therefore, essential to bring in inclusive models that take into account ancillary data sets like weather and soil parameters to predict yield with more accuracy.
The Internet of Things (IoT) here finds increased relevance. The IoT promises increased yields, reduced costs and other efficiencies, with the deployment of sensors, connectivity and analytics. Soil sensors as an IoT technology can also be used to broadcast real-time information on the state of the soil. This can be combined with other data to forecast crop yields.
Another possible solution could be to use satellite images to map the crop types, identify potential yield categories, calculate the area under each category, find locations with the maximum area and then select the number of samples for CCEs. Based on the data received, from remote sensing techniques, climate and other weather parameters, one can even try to conduct a large number of CCEs in the area where the probability of loss is high. This can be complemented with hand-held devices and smartphones to procure multiple images, which capture the heterogeneity of different field conditions in a village.
The use of drones to take images, recreate and analyse individual leaves from close-enough heights, assist in pest control, mid-season crop health monitoring, assess the soil-water-holding capacity and create weed maps or frost damage maps is another option.
In addition, mobile apps can also help provide evidence of canopy coverage or estimate the amount of fertilizer needed. They can also be used to collect information on insured area, insurance coverage and farmer profiles, which can help insurers develop customized products for farmers.
A promising outlook for crop insurance, aided by data and technology
The budget allocation of Rs10,000 crore to the BharatNet Project and the set target of reaching nearly 150,000 gram panchayats with high-speed Internet will also lay the foundation for a digital revolution in agriculture in India.
The core focus of the budget allocation is boosting agriculture credit.
To ensure flow of credit to small farmers, all functional primary agriculture credit societies (Pacs) will be integrated with the core banking system of district cooperative banks. Banks are the core distribution channel for the PMFBY and digitization will ensure penetration increases and that each farmer having access to credit is protected. Easy Internet access will allow farmers to learn and implement the latest technologies available in the field of agriculture. The finance minister has proposed that e-NAM (the National Agriculture Market) would be linked to the commodities market to allow farmers to access better prices for their produce.
For insurers too, the potential clearly exists for using technology to ensure implementation of agriculture insurance schemes in a sustainable manner. Insurers are always seeking ways to provide granular and objective risk profiles of individual farmers without the prohibitive costs of visiting and assessing single farms. Advances in technology and data processing may provide them with the means of doing so.
Recent Posts
- In the Large States category (overall), Chhattisgarh ranks 1st, followed by Odisha and Telangana, whereas, towards the bottom are Maharashtra at 16th, Assam at 17th and Gujarat at 18th. Gujarat is one State that has seen startling performance ranking 5th in the PAI 2021 Index outperforming traditionally good performing States like Andhra Pradesh and Karnataka, but ranks last in terms of Delta
- In the Small States category (overall), Nagaland tops, followed by Mizoram and Tripura. Towards the tail end of the overall Delta ranking is Uttarakhand (9th), Arunachal Pradesh (10th) and Meghalaya (11th). Nagaland despite being a poor performer in the PAI 2021 Index has come out to be the top performer in Delta, similarly, Mizoram’s performance in Delta is also reflected in it’s ranking in the PAI 2021 Index
- In terms of Equity, in the Large States category, Chhattisgarh has the best Delta rate on Equity indicators, this is also reflected in the performance of Chhattisgarh in the Equity Pillar where it ranks 4th. Following Chhattisgarh is Odisha ranking 2nd in Delta-Equity ranking, but ranks 17th in the Equity Pillar of PAI 2021. Telangana ranks 3rd in Delta-Equity ranking even though it is not a top performer in this Pillar in the overall PAI 2021 Index. Jharkhand (16th), Uttar Pradesh (17th) and Assam (18th) rank at the bottom with Uttar Pradesh’s performance in line with the PAI 2021 Index
- Odisha and Nagaland have shown the best year-on-year improvement under 12 Key Development indicators.
- In the 60:40 division States, the top three performers are Kerala, Goa and Tamil Nadu and, the bottom three performers are Uttar Pradesh, Jharkhand and Bihar.
- In the 90:10 division States, the top three performers were Himachal Pradesh, Sikkim and Mizoram; and, the bottom three performers are Manipur, Assam and Meghalaya.
- Among the 60:40 division States, Orissa, Chhattisgarh and Madhya Pradesh are the top three performers and Tamil Nadu, Telangana and Delhi appear as the bottom three performers.
- Among the 90:10 division States, the top three performers are Manipur, Arunachal Pradesh and Nagaland; and, the bottom three performers are Jammu and Kashmir, Uttarakhand and Himachal Pradesh
- Among the 60:40 division States, Goa, West Bengal and Delhi appear as the top three performers and Andhra Pradesh, Telangana and Bihar appear as the bottom three performers.
- Among the 90:10 division States, Mizoram, Himachal Pradesh and Tripura were the top three performers and Jammu & Kashmir, Nagaland and Arunachal Pradesh were the bottom three performers
- West Bengal, Bihar and Tamil Nadu were the top three States amongst the 60:40 division States; while Haryana, Punjab and Rajasthan appeared as the bottom three performers
- In the case of 90:10 division States, Mizoram, Assam and Tripura were the top three performers and Nagaland, Jammu & Kashmir and Uttarakhand featured as the bottom three
- Among the 60:40 division States, the top three performers are Kerala, Andhra Pradesh and Orissa and the bottom three performers are Madhya Pradesh, Jharkhand and Goa
- In the 90:10 division States, the top three performers are Mizoram, Sikkim and Nagaland and the bottom three performers are Manipur and Assam
In a diverse country like India, where each State is socially, culturally, economically, and politically distinct, measuring Governance becomes increasingly tricky. The Public Affairs Index (PAI 2021) is a scientifically rigorous, data-based framework that measures the quality of governance at the Sub-national level and ranks the States and Union Territories (UTs) of India on a Composite Index (CI).
States are classified into two categories – Large and Small – using population as the criteria.
In PAI 2021, PAC defined three significant pillars that embody Governance – Growth, Equity, and Sustainability. Each of the three Pillars is circumscribed by five governance praxis Themes.
The themes include – Voice and Accountability, Government Effectiveness, Rule of Law, Regulatory Quality and Control of Corruption.
At the bottom of the pyramid, 43 component indicators are mapped to 14 Sustainable Development Goals (SDGs) that are relevant to the States and UTs.
This forms the foundation of the conceptual framework of PAI 2021. The choice of the 43 indicators that go into the calculation of the CI were dictated by the objective of uncovering the complexity and multidimensional character of development governance
The Equity Principle
The Equity Pillar of the PAI 2021 Index analyses the inclusiveness impact at the Sub-national level in the country; inclusiveness in terms of the welfare of a society that depends primarily on establishing that all people feel that they have a say in the governance and are not excluded from the mainstream policy framework.
This requires all individuals and communities, but particularly the most vulnerable, to have an opportunity to improve or maintain their wellbeing. This chapter of PAI 2021 reflects the performance of States and UTs during the pandemic and questions the governance infrastructure in the country, analysing the effectiveness of schemes and the general livelihood of the people in terms of Equity.
Growth and its Discontents
Growth in its multidimensional form encompasses the essence of access to and the availability and optimal utilisation of resources. By resources, PAI 2021 refer to human resources, infrastructure and the budgetary allocations. Capacity building of an economy cannot take place if all the key players of growth do not drive development. The multiplier effects of better health care, improved educational outcomes, increased capital accumulation and lower unemployment levels contribute magnificently in the growth and development of the States.
The Pursuit Of Sustainability
The Sustainability Pillar analyses the access to and usage of resources that has an impact on environment, economy and humankind. The Pillar subsumes two themes and uses seven indicators to measure the effectiveness of government efforts with regards to Sustainability.
The Curious Case Of The Delta
The Delta Analysis presents the results on the State performance on year-on-year improvement. The rankings are measured as the Delta value over the last five to 10 years of data available for 12 Key Development Indicators (KDI). In PAI 2021, 12 indicators across the three Pillars of Equity (five indicators), Growth (five indicators) and Sustainability (two indicators). These KDIs are the outcome indicators crucial to assess Human Development. The Performance in the Delta Analysis is then compared to the Overall PAI 2021 Index.
Key Findings:-
In the Scheme of Things
The Scheme Analysis adds an additional dimension to ranking of the States on their governance. It attempts to complement the Governance Model by trying to understand the developmental activities undertaken by State Governments in the form of schemes. It also tries to understand whether better performance of States in schemes reflect in better governance.
The Centrally Sponsored schemes that were analysed are National Health Mission (NHM), Umbrella Integrated Child Development Services scheme (ICDS), Mahatma Gandh National Rural Employment Guarantee Scheme (MGNREGS), Samagra Shiksha Abhiyan (SmSA) and MidDay Meal Scheme (MDMS).
National Health Mission (NHM)
INTEGRATED CHILD DEVELOPMENT SERVICES (ICDS)
MID- DAY MEAL SCHEME (MDMS)
SAMAGRA SHIKSHA ABHIYAN (SMSA)
MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE SCHEME (MGNREGS)