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This paper attempts to analyze the variations in technical efficiency of the individual farmers of distinct (small, medium and large) size of land holdings and different types (family and hired) of labor with given set of input variables for the agricultural production across different Agro-Climatic Zones. A field survey was conducted to collect the information from a randomly stratified sample of 300 farmers operating in six districts falls under Trans-Gangetic Plains and Semi Sandy Desert zones of the states of Punjab and Haryana in India. A model of stochastic frontier analysis for cross sectional data with half normal truncated features has been used to measure the technical efficiency under the assumptions of Cobb-Douglas production function. The model comprises eight dummy variables for the farmers owning distinct size of land and using distinct type of labor in their production. The results for the estimates of technical inefficiency with family and hired labor depict; small farmers are 50.30 and 68.11 per cent, medium farmers are 61.09 and 67.75 per cent, large farmers are 71.03 and 56.67 per cent and average farmers are 71.94 and 70.07 per cent inefficient respectively. This paper helps the farmers and the policy makers in identifying the second best-alternative crop for obtaining the sustainable agricultural production. [Display omitted] • Ratio of land to labor applied by farmers lead to loss of income and productivity. • The demand for food is increasing, motivating the importance of farmers for sustainable agricultural production and development. • Sustainable agricultural production can deal with help is required to meet the growing demand for food. • Kernel density function measures variations in technical inefficiency of individual farmers. • Second-best alternative crops must be suggested to farmers for cultivation. [ABSTRACT FROM AUTHOR]

When on March 24, 2020 the Government of India ordered a complete lockdown of the country as a response to the COVID-19 pandemic, it had serious unwanted implications for farmers and the supply chains for agricultural produce. This was magnified by the fact that, as typically in developing countries, India's economy is strongly based on farming, industrialization of its agricultural systems being only modest. This paper reports on the various consequences of the COVID-19 lockdown for farming systems in India, including the economy, taking into account the associated emergency responses of state and national governments. Combining quantitative and qualitative sources of information with a focus on the Indian state of Uttar Pradesh, including expert elicitation and a survey of farmers, the paper identifies and analyzes the different factors that contributed to the severe disruption of farming systems and the agricultural sector as a whole following the lockdown. Among other issues, our study finds that the lack of migrant labor in some regions and a surplus of workers in others greatly affected the April harvest, leading to a decline in agricultural wages in some communities and an increase in others, as well as to critical losses of produce. Moreover, the partial closure of rural markets and procurement options, combined with the insufficient supply of products, led to shortages of food supplies and dramatically increased prices, which particularly affected urban dwellers and the poor. We argue that the lessons learned from the COVID-19 crisis could fuel the development of new sustainable agro-policies and decision-making in response not only to future pandemics but also to the sustainable development of agricultural systems in India and in developing countries in general. • The lockdown in response to COVID-19 has seriously disrupted Indian farms. • Farms have been less profitable amid rising food prices, putting pressure on food security. • A lack of migrant labor has led to a loss of produce and affected the spring harvest. • Experience and relief packages may help to develop Indian agriculture sustainably. [ABSTRACT FROM AUTHOR]

Indian agriculture is experiencing under-performance despite increased attention given to it in the recent past. This paper analyzes the disparities in agricultural growth across Indian states and explores the determinants of agricultural growth, using Panel Corrected Standard Error approach. Analysis using beta convergence shows that the disparities across the state's agricultural growth are narrowing down for the period 1980–1981 to 2011–2012. However, to stimulate growth in the states where agriculture is lagging behind, a higher emphasis on increasing the area under irrigation, expenditure on agricultural research, area under fruits and vegetables, number of regulated markets, length of roads, cold storage facilities and institutional credit for investment purposes is needed. Private sector should be involved in public–private-partnership mode for improving the infrastructure in this sector. [ABSTRACT FROM AUTHOR]

• I compare the process of structural transformation in both national data and household panel data in India. • The national data provides evidence that India is in the midst of structural transformation. • Household data tells a similar story, though rural households lag behind in key indicators. • The results have implications for using stylized facts to set policy agenda. This paper compares national-level data from India with 40 years of household panel data from rural India to track sectoral changes in employment and income as well as examine the hypothesis of induced innovation in agricultural production. In the national data, India appears to be in the midst of a structural transformation. The share of agriculture in GDP and employment has shrunk while agricultural output continues to grow. This productivity growth appears to adhere to the induced innovation hypothesis, as productivity per hectare has increased more rapidly than productivity per worker. Many of the same patterns exist in the household data. Tracking households across time, I observe agricultural output has increased, despite more households engaging in off-farm labor. Household agricultural production is highly specialized and has increased its reliance on improved inputs. However, while agricultural income has grown, industrial and service income has remained stagnant, and the relative income of these households has declined in recent years. [ABSTRACT FROM AUTHOR]