These channels are central to the success of introduction of innovations such as improved varieties, machinery, and other agricultural practices. Therefore, such networks not only help in improving productivity levels but also facilitate resilience through coordinated actions that yield higher overall benefits.
In India, agriculture is paramount for the economy, employing roughly 42% of the labour force, and accounting for 14% of GDP. The agricultural production structure is not characterized by intensive agriculture, rather, most agricultural output comes from several million small farming families.
The state of Odisha (also known as Orissa) is a good example of a region with a long history of struggle with food scarcity, famine and malnutrition , where smallholders account for the vast majority of production. Rice is the staple food-crop of the state. Through all stages of its production, (germination, seedling, tillering, panicle initiation, flowering and harvesting) the access to resources such as nutrients, machinery, and labour are vital to secure a successful crop.
However, the poverty of the typical smallholder creates a serious challenge when they try to access the many and varied inputs or resources needed throughout the production process. In recent decades, efforts from government, farmers and research organisations have successfully increased overall productivity of the sector throughout India; however, ensuring food security still remains a major challenge.
Capital investment and technical change have played a big role explaining increments and differences in agricultural productivity between Asian countries. For instance, during the Green Revolution (1986–2000), increments in rice productivity in India have been related to the development and adoption of machinery, irrigation systems, high yielding varieties, and hybrids. In addition, mineral fertilisers and pesticides have become widely used (unfortunately at the expense of soil degradation).
However, productivity increments from these inputs require financial investment and access to 3 specialized knowledge. But agricultural markets from villages usually have poor access to the formal institutions that in other places provide credit, information and education. Consequently, farmers tend to rely on other ‘informal channels’ to access both knowledge and resources.
In India, many small farmers tend to produce surplus crops which they sell in local markets. However, not all farmers are able to produce high marketable surplus to make it remunerative. For instance, our agricultural data on rice farmers in Odisha show, many only produce for self-consumption with little surplus. The difference between those who do and those who do not produce high surpluses, lies largely not in their willingness to sell on the market, rather in their capacity to generate a high enough yield.
These capacity constraints arise not only from a lack of awareness of better agricultural practices and productivity enhancing inputs (knowledge and technology constraints) but also, when awareness is present, financial inability to purchase those inputs (liquidity constraints). In this regard, Odisha is particularly striking. We argue that with a growing population and thus a growing demand, poorly developed credit and input markets, and a lack of access to formal institutions, farmers will access both information and inputs through informal channels. In other words, farmers benefit by using knowledge and resources from their peers.
Studies in different agricultural settings have provided evidence on flows of resources and knowledge from informal networks. We expect that rural farmers benefit from networks, provided that networks carry relevant resources for agricultural production. That is, connections from networks can be beneficial as a channel to access knowledge, information or capital: provided some agents have access to those resources, networks can mitigate production constraints, market and institutional inefficiencies.
Therefore, in our study we define networks based on what flows through them. In this regard, we account for two informal networks that potentially carry information and financial flows. The information network serves as an informal source of knowledge about agricultural technologies, inputs, and improved practices that can enhance productivity directly. The credit network is a channel for obtaining informal loans (“hand loans”) from network members and therefore acts as a potential provider of resources. Specifically, it eases liquidity constraints and provides timely access to credit.
Our credit network only indicates potential sources of credit the farmers have, and we do not have information on actual borrowing. Secondly, the existing social relationship (interpersonal relationships) between individuals are shown in the literature to catalyse the network flows through trustworthiness, loyalty, reciprocity, and such links are characterized as voluntary strong ties.
To capture this, friendship networks can be seen as the relevant facilitator of resource flows. The friendship network enhances social cohesion or bonding and facilitates the exchange of information and resources among network members, and thus reduces transaction costs involved in information search and provision of credit.
Moreover, a farmer’s production is most likely to benefit from resourceful connections, and hence we argue that the friendship network (or network of interpersonal relationships) has to be studied jointly with other networks that carry resources.
Therefore, while we investigate the effect of all three networks, viz. information, credit and friendship networks, independently on agricultural productivity, we also consider the mediating effect of friendship in facilitating the flow of information and resources.
Since the information, credit, and friendship networks are likely to be mutually embedded, the core of our paper is not only to measure individual network effects but to understand how the overlap and interaction of connections among individuals between these networks affect agricultural productivity.
In this study, we investigate the role of social networks on rice productivity by using unique primary data that provides information on multiple networks.
Our econometric analysis generated several results. First, among the three networks considered individually, only the information network is found to influence rice productivity. This shows that households who have direct links with a higher number of advisors (information providers) on agricultural matters benefit in terms of their production. This is in line with the consensus in the literature which assumes that social network effects on agriculture reflect information sharing or learning. However, by looking at networks separately, the absence of other networks’ effects may tempt one to conclude that they are irrelevant, this may be too hasty.
Second, there are mediating effects of friendship. Interpersonal relationships are known to ease barriers of interaction among individuals. In our data, the friendship network has no direct influence on productivity, but we ask whether it might serve as a factor in effective utilization of other relationships, and we find that it does: the effect of a connection in the information network is made stronger if that connection also exists in the friendship network.
This indicates the possibility of two things: in the first place, it reflects the importance of the strength of relationship (due to closeness or acquaintance) between households, and stronger relationships facilitate faster and more efficient flow of information. Our measure of friendship is based on closeness of ties and therefore, friendship ties may serve as a better proxy for capturing strength of ties compared to measures like frequency of contacts. Secondly, one can expect higher trust in such relationships and trust within a tie is thought to be a good proxy for the tie strength.
Therefore, the trustworthiness of information or advice from a friend may be higher due to the potential ramifications on friendship dynamics had the advice gone wrong. This allows for the exchange of more credible and valuable information across ties. The social exchange of information and informal dissemination of agricultural technologies between friends are very common in rural areas , and given the strong social norms prevailing in the community such networks are valued highly.
For example, the majority of farmers in the study region rely on informal sources for seeds rather than the seed market or other formal sources or sale points. Such interpersonal relationships therefore can help in facilitating transfer of information and technological inputs with lower transaction costs.
Third, we examine the interaction of networks (or network multiplexity). Our estimations from the multiplex network suggests the presence of complementarity across all three networks which produces synergistic effects on rice productivity. It indicates that some networks which may not influence productivity independently show their effects when included jointly with other networks.
Further, by using weights we account for the relative importance of each network on productivity, and this allows us to construct a multiplex network measure which captures more relevant information that we can derive from such complex interactions.
Our analysis has defined different layers of the network based on what flows from household to household within a layer. This has permitted us to see how the different layers, or types of inter-household relations interact. Specifically, we have evidence for how friendship helps in enhancing the effect of information flow. A study on how mobile technologies help individuals to better access information found that the links of information-communication and the links based on interpersonal relationships were intertwined. That is, different links were formed in a multiplex fashion.
The identification of causal effects and the application of multiplex networks provides a crucial input for the better and holistic representation and understanding of the role of social networks in influencing agriculture productivity. It also provides evidence for the existing potential channels for information and resource flows in villages. These channels are central to the success of introduction of innovations such as improved varieties, machinery, and other agricultural practices.
Farmers in developing countries face several challenges due to weak institutional and technological developments threatening the productivity levels. Therefore, such networks not only help in improving productivity levels but also facilitate resilience through coordinated actions that yield higher overall benefits.
Read the study:
Konda B, Sauri MG, Cowan R, Yashodha Y, and Veettill PC. (2021). Social networks and agricultural performance: A multiplex analysis of interactions among Indian rice farmers. Maastricht Economic and social Research Institute on Innovation and Technology Working Papers.
