Journal IssueIFPRI3; CRP2; ISIPIM; SAOPRCGIAR Research Program on Policies, Institutions, and Markets (PIM

Rural households in developing countries often depend on agriculture for their livelihoods. However, many also pursue off‐farm economic activities either to complement their farm income or because they lack access to agricultural land. Rural off‐farm employment is often informal and temporary. Searching for jobs can be associated with high transaction costs, which may be a constraint on some households’ participation in off‐farm employment. The increasing spread of mobile phones may help to reduce these transaction costs. Here, we test the hypothesis that mobile phone ownership increases rural households’ participation in off‐farm employment and—through this mechanism—also improves household income. We use nationally representative panel data from rural India and regression models with household fixed effects to control for confounding factors and unobserved heterogeneity. We find that mobile phone ownership is positively associated with the likelihood of participating in various types of off‐farm employment, including casual wage labour, salaried employment and non‐agricultural self‐employment. This association is larger in female‐headed than in male‐headed households. The estimates also show that mobile phone ownership is positively associated with household income, partly channelled through the off‐farm employment mechanism.

Productivity growth in smallholder agriculture is an important driver of rural economic development and poverty reduction. However, smallholder farmers often have limited access to information, which can be a serious constraint for increasing productivity. One potential mechanism to reduce information constraints is the public agricultural extension service, but its effectiveness has often been low in the past. Digital technologies could enhance the effectiveness of extension by reducing outreach costs and helping to better tailor the information to farmers’ individual needs and conditions. Using primary data from India, this study analyses the association between digital extension services and smallholder agricultural performance. The digital extension services that some of the farmers use provide personalized information on the types of crops to grow, the types and quantities of inputs to use, and other methods of cultivation. Problems of selection bias in the impact evaluation are reduced through propensity score matching (PSM) combined with estimates of farmers’ willingness to pay for digital extension. Results show that use of personalized digital extension services is positively and significantly associated with input intensity, production diversity, crop productivity, and crop income.

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Agriculture dominates Bihar’s economy, providing employment to 53.6% of the total workforce, higher than the national average of 46.9% (Labour Bureau 2015–16).

In many developing and emerging economies, better employment opportunities in the non-farm sector have increased rural wages due to labour shortages during the peak agricultural season. Increasing wages often cause a substitution of labour for mechanical power, but extensive use of labour-saving technologies may cause labour displacement and have serious equity concerns. Using the household and individual fixed effect estimation approach, this paper analyses the relationship between different types of farm machines and labour requirements in India. The results suggest that a unit increase in the level of farm mechanization increases the demand for hired labour by 12%. Moreover, we find that the level of farm mechanization has a positive effect on women’s participation in farm work, while it decreases the probability of children participating in agriculture-related work. Disaggregated analysis based on types of farm machinery suggests that water-lifting equipment, draft power and tractors increase the probability of male household members working on their farms, while all types of farm machines, except tractors, have a positive effect on female farm labour participation. We also find that the effect of farm mechanization on the demand for hired labour decreases as the size of the farm increases.

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Madhya Pradesh emerged as the state with the highest growth rate in agriculture. Long clubbed with the so-called BIMARU group of poor northern, central and eastern states, MP successfully broke ranks to set a scorching pace of growth, which has been unparalleled in the past quarter-century. Understanding the factors that helped to drive this growth and drawing lessons for other states at similar levels of development is the main objective of this chapter. Madhya Pradesh’s agricultural GDP increased at 8.1% per annum during 2005–06 to 2016–17, surpassing even record holder Gujarat’s 6% agricultural growth in the same period. The last three years have been even more spectacular: agricultural GDP increased at 11.8% per annum. Keeping this background in mind, this chapter has used secondary data published by the government to study the composition, sources and drivers of agriculture growth in Madhya Pradesh and the lessons that can be drawn for developing states. Although MP has recorded a significant decline in poverty rates from 53.6% in 2004–05 to 35.7% in 2011–12, there is still much to be done to improve the livelihood of the rural population. Moreover, MP’s per capita income is low, standing at Rs. 51,798 per annum (FY14 at current prices) as compared to the national annual average income of Rs. 74,380. Although it is much better than that of Bihar (Rs. 31,199) and Uttar Pradesh (Rs. 36,250), it remains way below top-performing states like Sikkim (Rs. 176,491), Maharashtra (Rs. 114,392), Haryana (Rs. 133,427) and Gujarat (Rs. 106,831). Therefore, the study also makes policy suggestions to bolster agricultural growth in MP.