Agricultural Productivity in India – UPSC

• Agricultural productivity is the quantitative measure of the capacity of land in relation to crop yield. It signifies the total output from a given piece of land.
• Agricultural geography also uses it more widely, relating money value of output to land farmed, workers engaged or inputs applied. These give land, labour and capital productivity.
• India’s yields remain well below the best in the world, and they differ sharply across its own regions, which is why productivity is measured region by region.

Agricultural Productivity

The Concept

• Productivity is not simply the physical quality of land that gives greater yield per hectare. It is the product of both physical and technological factors.
• Per-hectare yield, the simplest measure, depends on:
  • Physical factors: soil, climate and the agricultural ecology.
  • Technological factors: the degree of mechanisation, and the use of modern inputs and technology.
• So productivity measures the capacity of the soil and farm ecology, and also the inputs and technology used on it.
• Regional differences arise partly from natural advantage (soil and climate) and partly from farming efficiency, shaped by the human setting.
  • Productivity is at heart a relationship between output and the main inputs of land, labour and capital.
  • The level of productivity shows how far economic, cultural, technical and organisational variables manage to draw output from the area’s natural resources.
• Why compute it:
  • It shows the relative standing of the units of a region.
  • It picks out weak areas of low productivity.
  • It helps assess past development.
  • It gives a sound base for future planning.

Agricultural Efficiency

• Agricultural efficiency is often used as a synonym of productivity, yet it is different.
• It is the input-output ratio in a farm operation.
  • It reflects the impact of modern inputs and technology, and depends on how the soil and farm ecology respond to them.
  • It measures the rise in output for a given rise in inputs, which raises profit. That extra profit is what efficiency captures.
• It depends on the physical quality of land, measured as Potential Productivity per Unit (PPU).
• An example. Lands A and B each cover 100 ha and each yield 150 kg of rice in a year. A needs an investment of ₹100, and B only ₹50.
  • Agricultural productivity of A = agricultural productivity of B.
  • Agricultural efficiency of A < agricultural efficiency of B.

Why India’s Yields Lag

• India’s crop yields are low by international standards, in spite of the rise since the Green Revolution.
• The chart compares FAO data for 2024. FAO counts rice as paddy, so its Indian figure runs above the official one, which counts milled rice.

• Main reasons, each treated under the determinants of agriculture:
  • Rainfed land, which leaves large areas open to the failure of the monsoon.
  • Small and fragmented holdings, which restrict the use of machines and the scale of investment.
  • Uneven use of inputs, from unbalanced fertilizer use to limited supply of quality seed.
  • Soil degradation and falling groundwater in the very tracts that lead on yield.
  • Weak extension, credit and marketing in the low-yield eastern and central regions.
• The answer lies across regions: irrigation efficiency, diversification and soil health in the north-west, and better water control and technology in the east and on the plateaus.

Measuring Productivity

• No single method gives a flawless result, and the methods differ widely.

1. Per-Hectare Yield

• It is the most accepted method, but it does not give a correct assessment on its own.
• Crop choice matters as much as the land. Paddy in a sub-humid tract short of water may yield less than a millet suited to the moisture there, so the same land scores differently according to the crop.

2. Per Capita Output of Male Workers

• This is also imperfect, because it does not give the total value of farm output from a given piece of land.
• Each crop of coffee fetches a higher money value per male worker than paddy does, whatever the land is like.
• It is hard to apply, since inputs of family labour are poorly recorded.

3. Jasbir Singh’s Method

• Jasbir Singh measures productivity as the money value earned from farming per unit of labour employed.
• It is the sum of the product of each crop’s output and its market price, less the cost of production:
  • Agricultural productivity = ∑(Pij × Mij) − Cop
  • Here P is the quantity of output of the crop, M its market price, and Cop the cost of production.
• A later form, tried in Haryana, reads productivity from net farm income, in rupees, for each hectare cropped or each adult male unit of family labour.
  • Two children aged 7–15, or 1.5 women aged 15–59, count as one adult male unit.
  • Productive regions recorded the highest net income per hectare, and net income generally rose with farm size.
• An earlier approach of his treated carrying capacity per unit area as a percentage of the whole region’s, after deducting about 16.8 per cent of output for seed, feed and waste.

4. Kendall’s Ranking Coefficient Method

• Maurice Kendall (1939) worked out the method on the yields of ten leading crops in 48 English counties.
• Stamp (1960) used it to compare twenty countries on nine crops, and Mohammad Shafi (1960) to rate Uttar Pradesh on eight food crops.
• It rests on statistics and has wide acceptance across the world.
• It was applied to India in 1991 and again in 2005–06.
• Steps:
  • Divide a region into units, and list the crops grown. For example, a region X may have 50 units and 8 crops: rice, wheat, cotton, oilseeds, sugarcane, pulses, jowar and bajra.
  • Rank each unit by yield per hectare for each crop.
  • Average each unit’s ranks by the formula below.

• For Punjab, the working runs as below.

• The average ranked position of all units is arranged in an ascending or descending array, which is cut into five equal parts: very low, low, medium, high and very high productivity. Punjab is the example here, and the whole of India is treated the same way.
• The lower the index value, the greater the productivity or efficiency. A unit at the top of every list scores one.
• For India the method used 80 regions and 8 crops in 1991, and 120 regions and 11 crops in 2005–06.

Other Measures

• Grain equivalents. Buck argued that money values mean little where crops are grown for home use, as in a subsistence economy like China’s or India’s. So he converted all farm output into grain, counting all grains as equal.
  • Egbert de Vries refined it into milled-rice equivalents per head, using local prices. Its weakness is that it divides by the total population, and not by the rural workers who actually produce.
  • Clark and Haswell used wheat equivalents per person per year.
• Input-output. Khusro favoured output against paid-out cost, leaving out the imputed value of family labour. It suits comparison between farm-size classes.
  • It has little validity in a subsistence economy, where foodgrains form 75–85 per cent of output, most of it is kept at home and the farmer supplies most inputs.
• Weighted ranks. Sapre and Deshpande weighted Kendall’s ranks by each crop’s share of cropland.
• Yield index. Shyam S. Bhatia assumed that hectare yields capture all physical and human factors, and that shares of cropland reflect land-use choices. He weighted crop yield indices by cropland share.
  • Yield index of a crop = (yield in the unit ÷ yield in the region) × 100
• Carrying capacity. Stamp turned crops into calories, and read productivity from how many people the land can support.
• Enyedi’s index. It compares a unit’s share of a crop’s output with its share of cropped area, on the national scale. Shafi (1972, 1974) applied it to twelve food crops of India.
  • Productivity index = (Y ÷ Yn) ÷ (T ÷ Tn)
  • Y and Yn are the crop’s production in the unit and the nation, and T and Tn the total cropped areas.
• Yield and concentration ranks. Jasbir Singh (1976) averaged a crop’s yield rank and its concentration rank. A lower coefficient means higher productivity.

Regional Pattern in India

• The all-India index divides the country into 5 regions, as the table shows.

• Region I (very high): the Punjab-Haryana plains, Ganganagar and Hanumangarh districts, the Rohilkhand plains, the Ganga-Yamuna doab, Shahbad district, the lower Bengal delta, and the Krishna-Godavari and Kaveri deltas.
  • Reasons match those behind high cropping intensity: assured irrigation, high-yielding seed, fertilizer and machinery.
• Region II (high): the river valleys of the Peninsula, the eastern coastal plains, the northern Bengal delta, the middle Gangetic plain, the Kaveri basin and the Malabar coast.
• Region III (moderate): the Chhattisgarh basin, and the river basins of Maharashtra and Karnataka, such as the Tungabhadra, Khandesh, Vidarbha and Rayalaseema, with the Gujarat plains, Baghelkhand and the Malwa plateau.
• Region IV (low): Jharkhand, eastern Rajasthan, the Purvanchal hills, and the rain-shadow plateaus of south India such as Telangana.
• Region V (very low): Jammu and Kashmir, the Himalayan region and western Rajasthan.

• This map groups India into four classes (high, medium, low and very low) from district yields of the 2003–06 period, and leaves some north-eastern hill areas as data not available. It therefore does not match the five regions line for line.
  • High: the Satluj-Ganga plain, the Brahmaputra valley, and the Godavari, Krishna and Kaveri deltas. Farming here has moved towards agri-business in Punjab, Haryana and western Uttar Pradesh.
  • Medium: scattered patches in Andhra Pradesh, Gujarat, Karnataka, Maharashtra, Madhya Pradesh, Odisha, Tamil Nadu and West Bengal, with limited irrigation and mostly subsistence farming.
  • Low: dry and rainfed tracts of the plateau and hills, prone to drought or flood, with low-intensity farming.
  • Very low: large parts of Rajasthan, Jharkhand and Chhattisgarh, because of high rainfall variability and rural poverty.