We provide evidence of the role of community networks in emergence of Indian entrepreneurship in early stages of cotton and jute textile industries in the late 19th and early 20th century respectively, overcoming lack of market institutions and government support. From business registers, we construct a yearly panel dataset of entrepreneurs in these two industries. We find no evidence that entry was related to prior upstream trading experience or price shocks. Firm directors exhibited a high degree of clustering of entrepreneurs by community. Consistent with a model of network-based dynamics, the stock of incumbent entrepreneurs of different communities diverged non-linearly, controlling for year and community fixed effects.
There are many economic environments in which an object is offered sequentially to prospective buyers. It is often observed that once the object for sale is turned down by one or more agents, those that follow do the same. One explanation that has been proposed for this phenomenon is that agents making choices further down the line rationally ignore their own assessment of the object’s quality and herd behind their predecessors. Our research adds a new dimension to the canonical herding model by allowing agents to di er in their ability to assess the quality of the offered object. We develop novel tests of herding based on this ability heterogeneity and also examine its efficiency consequences, applied to organ transplantation in the U.K. We nd that herding is common but that the information lost due to herding does not substantially increase false discards of good organs or false acceptances of bad organs. Our counter-factual analysis indicates that this is due (in part) to the high degree of heterogeneity in ability across transplant centers. In other settings, such as the U.S., where organ transplantation is organized very differently and the ability distribution will not be the same, the inefficiencies due to herding might well be substantial.
The frictions that restrict migration are among the largest sources of inefficiency in the global economy. The first step in designing policies to address these frictions is to understand the fundamental forces that drive migration. However, the Roy model—the workhorse model of migration in economics—does a poor job of explaining many important features of this phenomenon. This limitation can be rectified by adding migrant networks to the Roy model. A rich qualitative literature in the social sciences has documented the role played by social networks in supporting migrants in their new locations. Economists have advanced this literature by identifying and quantifying the contribution of these networks to migration. Although much progress has been made over the past two decades, important gaps in the literature remain: Migrant assimilation has received little theoretical or empirical attention, and a richer characterization of the social interactions that support these networks is needed to tie research on migration to the economic literature on networks.
Caste plays a role at every stage of an Indian's economic life, in school, university, the labor market, and into old age. The influence of caste extends beyond private economic activity into the public sphere, where caste politics determine access to public resources. The aggregate evidence indicates that there has been convergence in education, occupations, income, and access to public resources across caste groups in the decades after independence. Some of this convergence is likely due to affirmative action, but caste-based networks could also have played an equalizing role by exploiting the opportunities that became available in a globalizing economy. Ethnic networks were once active in many advanced economies but ceased to be salient once markets developed. With economic development, it is possible that caste networks will cease to be salient in India. The affirmative action programs may also be rolled back, and (statistical) discrimination in urban labor markets may come to an end if and when there is convergence across caste groups. In the interim period, however, it is important to understand the positive and negative consequences of caste involvement across a variety of spheres in the Indian economy.