The Mahila Jagat Lihaaz Samiti (https://lnkd.in/dV-nhpBz), a Bhil Adivasi farmers' organisation in Madhya Pradesh, conducted a survey to determine the economics of agriculture among 50 Adivasi marginal farmers spread over the districts of Dewas, Indore and Alirajpur in Madhya Pradesh, asking them about their performance in the 2021-22 agricultural year over the two seasons of Kharif and Rabi. In addition to the farming details the respondents were also asked about their monthly food consumption. The results of this survey are disturbing to say the least - Average Daily Per Capita Calories Consumed (Calories) - 2092 Average Daily Per Capita Food Cons. Exp. (Rs) - 43 Average Daily Per Capita Total Cons. Exp. (Rs) - 87 Average Daily Per Capita Farm Income (Dividing Total Net Farm Income by 365 days and number of workers in the household) (Rs) - 14 Average Household Labour Wage (Dividing Total Net Farm Income by No. of days of Household Labour actually put in) (Rs) - 72 Average Agricultural Income Per Acre (Rs) - 11950 Average Annual Per Capita days of farm Work (Days) - 54 Thus, the farm income is able to cover only 16 percent of total household expenditure and 32 percent of food expenditure. No wonder then that the average daily per capita calorie consumption of the sample is only 2092 which is well below the benchmark of 2400 calories for good nutrition as determined by the World Health Organisation. This has to be compared with the poverty line determined by the World Bank which is $1.9 per capita per day which works out to Rs 42 per day in India in purchasing power parity terms (World Bank, 2021). As is evident from the results above, this poverty line income is not sufficient to even provide a minimum necessary food intake of 2400 calories per day let alone take care of other household expenditures. Therefore, the determination of the poverty line income is itself faulty and it needs to be at least trebled to ensure that people get adequate nutrition and other benefits. If that is done then the proportion of people below the poverty line will increase substantially from the 28 per cent that is officially quoted now. One more disconcerting aspect is that these farmers are getting on an average only 54 days of work per capita annually from their farms. Whereas, accounting for holidays they should be getting at least 250 days of work on par with salaried workers in permanent jobs. Moreover, in 2021-22 the statutory minimum wage in agriculture was Rs 220 per day but the farmers on an average got only Rs 72 per day for the number of days they worked. If the farmers are to get Rs 220 per day for 250 days then the income per acre has to increase to a huge Rs 1,65,000 assuming three workers per household, from the paltry Rs 11,950 they are getting now due to adverse market conditions. Consequently, all the surveyed farmers are also doing wage labour either locally or by migrating to cities like Indore and Surat to make ends meet.
Farmer Socioeconomic Data Analysis
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Summary
Farmer socioeconomic data analysis involves studying the incomes, expenses, working conditions, and living standards of farm households to better understand the challenges they face, especially among small and marginal farmers. This type of analysis combines information about crop yields, market prices, food consumption, and access to resources like credit, revealing the true financial and social realities behind rural agricultural life.
- Examine real incomes: Compare farmers’ actual earnings from their land with household expenses and food needs to uncover gaps that limit well-being and nutrition.
- Consider credit access: Recognize the role of affordable credit in helping farmers manage input costs and avoid high-interest informal lending, which can deepen financial struggles.
- Value meaningful work: Assess both farm labor opportunities and off-farm income sources to understand how rural families can build more secure and resilient livelihoods.
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Smallholder farmers remain the backbone of rural economies, yet small farm sizes and limited off-farm opportunities continue to constrain their chances of achieving a living income. Our new paper co-authored with Yeshwas Admasu and Benjamin Davis draws on harmonized household data from 37 countries and panel data from Ethiopia, Nigeria, Tanzania, and Uganda to explore how farm size shapes livelihood strategies and incomes. 🔹 Key insights of the study: - Land still matters where labour markets are thin: larger farms enable agricultural specialization and higher farm incomes. - As markets deepen and labour mobility expands, land becomes less decisive and education and urban connectivity drive diversification and income growth. - Land expansion or consolidation alone cannot reduce poverty; inclusive transformation requires investing in rural education, infrastructure, and off-farm labour markets. - The real challenge is to link productivity growth with diversification, enabling rural households to secure living incomes and resilient livelihoods. 📄 Read the full paper here: https://lnkd.in/dMi8Q7R7 #RuralTransformation #FamilyFarming #AgrifoodSystems #InclusiveGrowth #DevelopmentEconomics #Smallholders #FAO #Research #LivingIncome
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I did the "dirty work" so the data community doesn't have to. 🛠️🇵🇰 If you’ve ever tried to analyze Pakistan’s Agricultural Census data, you know the pain. The official reports from the Pakistan Bureau of Statistics (PBS) are often locked in irregular, static PDFs, not exactly "analysis-ready." For a recent side project a couple of months ago, I decided to fix that. I cleaned, preprocessed, and transformed the 6th and 7th Pakistan Agriculture Census (2010 & 2024) into a analysis ready format. What makes this different? I didn't just stop at flat CSVs. I took it a step further and architected a Galaxy Schema: ✅ Fact Tables: Quantitative metrics for Crop Production, Livestock, and Farm Size. ✅ Dimension Tables: Harmonized lookups for Provinces (Punjab, Sindh, KPK, Balochistan, ICT) and Crop Types. ✅ Longitudinal Ready: 14 years of data (2010 vs 2024) standardized for direct comparison. The Engineering Logic: PDF to CSV: Handled the extraction from messy, irregular document structures. Smart Aggregation: Grouped low-frequency crops into an "Others" category to ensure statistical stability across decades. Normalization: Standardized naming conventions to bridge the gap between two different census cycles. I’ve uploaded the complete dataset and a starter Python notebook to my Kaggle profile. Whether you are into Data Visualization, Econometrics, or Supply Chain analysis, this is for you. Check out the dataset here: https://lnkd.in/dnmi7Wyn Pakistan Bureau of Statistics #DataEngineering #Pakistan #Agriculture #Kaggle #DataScience #OpenData #Analytics #GalaxySchema #PakistanBureauOfStatistics
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#Record Harvests. Low #Inflation. But Farmers Are Still Under Stress. India’s agriculture achieved a historic milestone in 2024–25, yet the farmer’s income story remains worrying. What went right? 👉#Foodgrain production touched a record 357.7 million tonnes (up from 332.3 MT last year) 👉#Horticulture output rose to 369 million tonnes #Goodmonsoon, subsidised fertilisers, MSP operations, PM-Kisan transfers and crop insurance supported production 👉#Foodinflation stayed low, helping consumers and macro stability What went wrong for farmers? 🔴#Farmgate prices collapsed despite record output 🧅🧅#Onion prices fell 38% 🥔🥔#Potato prices down 34% 🍅🍅#Tomato prices declined ~24% YoY Many crops, including #soyabean, #pulses and #oilseeds, traded below #MSP Liberal imports of #edibleoils and #pulses, combined with higher domestic output, led to oversupply and weak price realisation 👉#Income vs #output mismatch 🟧#Agriculture GVA growth slowed to 3.7% and 3.5% in the first two quarters of FY26 🟨#Farm sector growth in FY26 may fall below 4% (FY25 was 4.6%) 🟩#Crop segment (≈55% of agri GVA) is losing share, while livestock is growing faster Rural income recovery remains uneven and fragile As experts rightly point out: Focusing only on production creates gluts. Without strong value chains, farmers pay the price. 👉 Low inflation is good for the economy. But agriculture will be truly successful only when record production also delivers stable and fair incomes to farmers. This is the real challenge India must address next.
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85% of India's farmers are small and marginal farmers owning land less than 2 hectares. What is a reasonable amount of income to expect from one's farmland? Let's take the case of wheat for reference. One acre of land can mean up to 20 quintals of wheat in a good year. At the current MSP of Rs.2,585 per quintal, this comes to Rs. 51,700 per acre. Assuming a land holding of 5 acres, you would now be quick to point out that the income will be Rs.2.5 lakhs for half a year given a good harvest. So where's the catch? The catch is in the input costs. Fertiliser, urea, zinc, pesticide, watering and manual harvesting along with tractor/fuel costs can cost up to Rs.10-12,000 per acre. That leaves us with an actual profit of Rs.38,500 per acre (for a crop grown over 6 months). But let's not forget this boils down to Rs.7,600 per month. If a farmer has a land holding of 2 acres, this is Rs.15,200 per month. At 4-5 acres which is the higher end of marginal farming, this is Rs.38,000 per month. These numbers are earnings for usually an entire family that works on the farm. Now add to all this the cruel prevalence of informal moneylending that farmers need for credit so they can buy seeds and farm inputs. Informal moneylenders lend at rates as high as 10-15% per month. Are not the odds stacked against 85% of Indian farmers? At Rang De - we're solving for one part of this equation by giving farmers access to credit at rates as low as 8% per annum. Just like you, the reader reading this, 11,000+ people from all over India (and NRIs) have enabled farmers starting with Rs.500. They have created impact while getting repaid with interest. All the while giving farmers a lifeline of accessible credit. If you want to be a part of this solution and enable credit for farmers and create huge impact, visit https://lnkd.in/dUENu6Vj to make a social investment today. Let's back our farmers!
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We keep debating MSP, subsidies, and loan waivers. But we’re avoiding the real question: Are farmers earning enough to live with dignity? Let’s look at the numbers—carefully. 👉 The latest official estimate (NSSO 2019) puts average farm household income at ₹8,337/month—and India still doesn’t have updated national data. 👉 A dignified living benchmark? The Seventh Pay Commission (2016) set ₹18,000/month as the minimum salary— which translates to roughly ₹25,000/month in today’s terms. So whether today’s farm income is ₹10,000 or ₹12,000… it is still less than half of what counts as a basic dignified income. This is not a productivity problem. It’s an income design problem. For decades, we’ve focused on: • Prices (MSP) • Inputs (subsidies) • Crisis response (loan waivers) But none of these guarantee one simple outcome: 👉 A stable, adequate income for farming households Maybe it’s time to shift the frame. 💡 From “Which scheme?” → to “What outcome?” 💡 From “Support” → to “Income security” Because farmers don’t just produce food. They manage risk, sustain ecosystems, and anchor rural economies. And yet, their income remains the most uncertain. If 42% of our workforce depends on agriculture, income security isn’t welfare—it’s economic stability. The real question is no longer whether we can afford it. It’s whether we can afford to ignore it. Read my analysis on how India can ensure income security for its farming households through a policy shift Centre for Sustainable Agriculture | Grameen Academy | Sahaja Aharam | Deccan Development Society #Agriculture #Farmers #IncomeSecurity #PublicPolicy #RuralIndia #Sustainability #AgriReform #FoodSecurity #ClimateAction #India
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