The World Bank has warned that each percentage point increase in food prices would push an additional 10 million people in the world into extreme poverty. This is a significant concern, given that food prices can be highly volatile due to factors such as climate change, trade policies, and market speculation.

The impact of higher food prices on poverty is especially acute in low-income countries, where a significant proportion of people’s incomes are spent on food. When food prices rise, households may have to cut back on other essential expenses, such as healthcare or education, in order to afford food. This can have long-term negative effects on the health and well-being of households, and can also limit opportunities for economic growth and development.

The World Bank has therefore emphasized the importance of investing in measures to improve food security, such as supporting smallholder farmers, improving agricultural productivity, and investing in social safety nets to protect vulnerable households from the effects of food price shocks. By addressing the root causes of food insecurity, it may be possible to prevent food price increases from leading to increased poverty and vulnerability in the world’s most vulnerable populations.

The old adage “what doesn’t get measured, doesn’t get done” is well suited to the agriculture sector, particularly in the context of policy measures aimed at improving food security and mitigating price shocks.

If policymakers do not have accurate and reliable data on key aspects of the agriculture value chain, including crop production, market demand, and supply chain logistics, it can be challenging to make informed decisions and design effective policies.

Without data, policymakers may not have a clear understanding of the challenges facing the sector, such as the impact of climate change on crop yields, the prevalence of food waste and loss, or the factors driving price volatility.

As a result, policy interventions may be inadequate or poorly targeted, leading to inefficiencies and vulnerabilities in the food system. For example, policies that focus on increasing production without considering market demand can result in oversupply and food waste, while policies that prioritize price stability over supply chain efficiency may lead to shortages and higher prices.

In contrast, when policymakers have access to accurate and reliable data, they can design policies that are tailored to specific challenges and that prioritize efficiency, resilience, and sustainability. By measuring key indicators and tracking progress over time, policymakers can ensure that their policies are effective and that they are making progress toward their goals.

Indian food prices have indeed been increasing at an unprecedented rate in recent times, and there are several factors that have contributed to this trend. Some of the major factors are:

Weather-related events: Weather-related events, such as droughts, floods, and cyclones, can have a significant impact on agricultural production and food prices. For example, the severe drought in 2015-16 in many parts of India led to a decline in crop yields and higher food prices.
Supply chain disruptions: Supply chain disruptions, such as transportation bottlenecks, storage capacity constraints, and trade restrictions, can disrupt the flow of food from production centers to consumption centers. This can result in higher food prices, particularly for perishable goods such as fruits and vegetables.
Input costs: The cost of inputs such as seeds, fertilizers, and labor can also impact food prices. For example, the increase in diesel prices can lead to higher transportation costs, which can be passed on to consumers in the form of higher food prices.
International prices: International prices for commodities such as oil, wheat, and soybean can also have an impact on domestic food prices in India. For example, a rise in international oil prices can increase transportation costs, which can increase the prices of food products.
Policy decisions: Policy decisions related to trade, subsidies, and minimum support prices can also impact food prices. For example, a decision to reduce subsidies for fertilizer can lead to an increase in the cost of production, which can be passed on to consumers in the form of higher food prices.

Overall, the increase in Indian food prices in recent times has been driven by a complex interplay of factors. Addressing this issue requires a multifaceted approach that addresses both short-term supply disruptions and longer-term structural issues, such as improving agricultural productivity, strengthening supply chains, and promoting sustainable agricultural practices.

Accurate and reliable data is crucial for establishing effective policy measures that can ensure long-term food security and help absorb price shocks in the agricultural sector. Here are some of the ways in which reliable data is important in this regard:

Food demand and supply analysis: Accurate data on food demand and supply is essential for identifying potential food shortages and surpluses. This information can help policymakers determine the most effective measures for stabilizing food prices and ensuring a steady supply of food to consumers.
Market monitoring: Reliable data on food prices, production levels, and inventory levels can help policymakers monitor market trends and identify potential supply and demand imbalances. This information can help them take proactive measures to stabilize prices and prevent food shortages.
Agricultural productivity analysis: Accurate data on agricultural productivity is essential for identifying potential areas for improvement and implementing effective measures to increase production levels. This information can help policymakers identify ways to improve the efficiency of the agricultural sector and increase food production.
Climate change adaptation: Reliable data on weather patterns and climate change can help policymakers identify potential threats to food security and develop effective measures to mitigate the impact of climate change on the agricultural sector.
Risk management: Accurate data on food price volatility and other risks to the agricultural sector is essential for developing effective risk management strategies. This information can help policymakers identify potential risks and develop measures to absorb price shocks and other disruptions to the food supply chain.

Overall, accurate and reliable data is essential for establishing effective policy measures that can ensure long-term food security and help absorb price shocks in the agricultural sector. Without reliable data, policymakers may be unable to make informed decisions that can effectively address the challenges facing the agricultural sector and ensure food security for the future.

Reliable and accurate data are essential for policymakers to make informed decisions that can positively impact the low-income population and prevent economic misery. Here are some key reasons why:

Identifying problems: Reliable and accurate data can help policymakers identify the most pressing problems that low-income populations face. For example, data on unemployment rates, income levels, and poverty rates can help policymakers understand the challenges that low-income individuals and families are facing and develop policies that can address these issues.
Targeting resources: Reliable and accurate data can also help policymakers target resources more effectively. With accurate data, policymakers can determine which areas or communities are most in need of support and direct resources accordingly. This can ensure that resources are used where they can have the greatest impact, rather than being spread too thin across many different areas.
Monitoring progress: Reliable and accurate data can help policymakers track the effectiveness of their policies and programs over time. By monitoring progress, policymakers can identify which interventions are working well and which ones need to be improved or changed. This can help ensure that resources are being used effectively and efficiently and that policies are having the desired impact.
Improving accountability: Finally, reliable and accurate data can help improve accountability for policymakers. By having access to data on outcomes and impact, policymakers can be held accountable for their decisions and actions. This can help ensure that policies and programs are being implemented as intended and that they are having the desired impact on low-income populations.

Overall, reliable and accurate data are essential for policymakers to make informed decisions that can help prevent economic misery in low-income populations. By using data to identify problems, target resources, monitor progress, and improve accountability, policymakers can develop policies that are more effective, efficient, and equitable for all members of society.

Reliable and accurate data analysis is essential for developing production and food security-centric policies that can be implemented in different phases of agricultural growth in India. Here are some key ways in which reliable data analysis can inform policy decisions in this area:

Understanding production trends: Reliable data on crop yields, land use patterns, and other key production indicators can help policymakers understand production trends and identify areas where productivity can be improved. This can inform policies related to crop selection, soil management, and other production-related factors that can impact food security.
Assessing food security needs: Accurate data on food consumption patterns, nutritional status, and other factors can help policymakers assess food security needs at the national, regional, and local levels. This can inform policies related to food distribution, storage, and other interventions that can help ensure that all populations have access to sufficient and nutritious food.
Identifying supply chain bottlenecks: Reliable data can help identify bottlenecks in the agricultural supply chain, such as inadequate storage or transportation infrastructure. This can inform policies related to supply chain development and investment in infrastructure that can help improve the efficiency and effectiveness of agricultural production and distribution.
Evaluating policy impacts: Accurate data can help policymakers evaluate the impact of different policies on agricultural production and food security. For example, data on the adoption rates of new technologies or the effectiveness of subsidies can help policymakers understand which policies are having the desired impact and which ones need to be adjusted or scrapped.

In each phase of agricultural growth in India, reliable and accurate data analysis is crucial for developing effective policies that can promote production and food security. By using data to inform policy decisions, policymakers can help ensure that agricultural growth in India is sustainable, equitable, and responsive to the needs of all stakeholders.

To Know to Act Better- Importance and Relevance of Data
US- The World Agricultural Supply and Demand Estimates (WASDE) are prepared and released by the World Agricultural Outlook Board (WAOB). The report is released monthly and provides annual forecasts for the supply and use of U.S. and world wheat, rice, coarse grains, oilseeds, and cotton.

The WAOB chairs the Interagency Commodity Estimates Committees (ICECs), which include analysts from key USDA agencies who compile and interpret information from USDA and other domestic and foreign sources to produce the report. (Source: USDA)

Kind of reports

Supply Demand Estimates
World markets and Trade reports
Export Sales reports
Global Main Market Reports

China the Big Consumer:
CASDE like USDA’s World Agricultural Supply and Demand Estimates (WASDE) Report, CASDE provides monthly supply, demand, prices, and trade data (including forecasts), for corn, soybeans, cotton, vegetable oils, and sugar from the Chinese Ministry of Agriculture. Data goes back to 2014 and reports are released in the second week of each month.

India Production – Supply and Demand Estimates:
In India Production estimates are released 4 times a year and the tracking history of Production targets and Final Crop estimates, most of the time Final crop numbers just try and better the production Target set by the government of India.

The Indian government doesn’t issue any robust Demand Estimates, thus over-emphasizing production numbers for Planning and Policy Making.

Whenever GOI needs to reduce production numbers it is done with a big lag leading to domestic price inflation in which the rural and BOP population suffers the most.

India needs more robust and responsive production estimates and better estimated on-demand numbers.

Monthly and timely updating of Data points acts as Prism for Policy Making-
India Case Study of Wheat and Pulses- 2016

28-Jun-06	The import duty on wheat was reduced from 50% to 5%
09-Sep-06	The Import duty was further reduced to ZERO percent
08-Oct-07	Import of wheat (HS code- 10011900 and 10019910) made free till further order
09-Sep-11	Removal of ban on export of wheat.
07-Aug-15	The import duty on wheat has been imposed @ 10%
19-Oct-15	The import duty on wheat has been increased to 25%
23-Sep-16	Import duty on wheat has been reduced from 25% to 10%
08-Dec-16	The Import duty on wheat was brought down to Zero
28-Mar-17	Import duty on Wheat has been increased from Zero to 10%
08-Nov-17	Import duty on Wheat has been increased from 10% to 20%
23-May-18	Import duty on Wheat has been increased from 20% to 30%
26-Apr-19	Import duty on Wheat has been increased from 30% to 40%
13-May-22	Wheat Export Prohibited : Amendment in Export Policy of Wheat

In 2015-16 Wheat import duty was increased – leading to a shortage and Price rally in Domestic markets. 2016-17 Wheat Import duty was reduced to zero from 25% acknowledging wheat crop shortages in the country.

The timely availability of accurate data is crucial for enabling producers and consumers to respond to the volatile commodity market over time.

Better Agri statistics with Government will help in:

Market transparency: Timely and accurate data can help promote market transparency by providing information on prices, supply, and demand. This allows producers and consumers to make informed decisions about when to buy and sell, and can help prevent market manipulation and price gouging.
Risk management: Producers and consumers can use data to manage risks associated with price volatility. For example, farmers can use data on weather patterns and commodity prices to make planting decisions, while consumers can use data on food prices to make budgeting decisions. Access to accurate and timely data can help mitigate the impact of price fluctuations on livelihoods and food security.
Planning and investment: Timely data can also help support planning and investment decisions in agriculture. For example, investors can use data on production trends and market demand to make decisions about where to invest in agriculture infrastructure or technology. Similarly, policymakers can use data to identify areas of potential growth and prioritize investments in agriculture.
Policy analysis and evaluation: Finally, accurate and timely data is essential for policymakers to analyze the impact of policies and evaluate their effectiveness over time. For example, policymakers can use data on production trends and market prices to evaluate the impact of subsidies or other policy interventions. This can help ensure that policies are effective, efficient, and equitable for all stakeholders.

The timely availability of accurate data is critical for enabling producers and consumers to respond to the volatile commodity market over time. It can help promote market transparency, support risk management, facilitate planning and investment decisions, and enable policy analysis and evaluation. By ensuring that data is accessible, reliable, and up-to-date, stakeholders can make informed decisions that help promote stability and sustainability in agriculture.

In conclusion, accurate and reliable data is crucial for establishing effective policy measures aimed at achieving long-term food security in India and absorbing price shocks. Without accurate data, policymakers cannot make informed decisions and may end up implementing measures that do not address the root causes of food insecurity or price fluctuations. In addition, reliable data can help policymakers to monitor the effectiveness of their interventions and adjust their policies accordingly. Therefore, it is imperative for the Indian government to invest in data collection and analysis, including through the use of modern technologies, in order to achieve food security and stability in the agricultural sector. By doing so, India can ensure that its population has access to sufficient and nutritious food and that its agricultural sector is sustainable and resilient to future shocks.