Gains from Agricultural Market Reform: Role and Size of Intermediaries (Job Market Paper)

Abstract: How does market structure and presence of intermediaries impact the cropping pattern and agricultural trade within a country? The difference between farm-gate and consumer prices points towards the presence of large margins charged by the intermediaries but it is difficult to isolate the effect of market structure from other phenomenon. This paper exploits a pro-competitive policy reform from India, that allowed free entry of intermediaries in the agricultural markets, to quantify the size of these margins. I develop a Ricardian style comparative advantage model of intra-national trade in agricultural crops, which embeds intermediaries and is suitable to study market structure change. The model gives a structural equation that allows me to estimate the change in intermediary margin due to this reform. I find that post reform the intermediary margin decreased by 16% for Groundnut, one of the major crops in this region. I then connect the model with rich micro datasets on farm productivity and land use to estimate relevant parameters to run counter-factual experiments which reveal that the reform increased average welfare by 1.3%.

Shock Diffusion: Does inter-sectoral network structure matter?

Abstract: This paper introduces the concept of diffusion of shocks in a macroeconomic network consisting of inter-sectoral production linkages. I show that if sectors have different reaction horizons it would lead to diffusion of shocks through the network over time which prevents the inter-sectoral linkages to form the feedback loop structure essential to generate aggregate volatility. This result is different from other recent papers which have single period models with contemporaneous production linkages between different sectors thus generating sectoral shock amplification as one sector reacts to another contemporaneously resulting in bigger aggregate fluctuations. In contrast if sectors have different production horizons due to varying complexity of their production process or supply chain, it would break down the feedback architecture present in single period models. I further show that if the diffusion rate is heterogeneous across sectors, the contribution of network structure to aggregate volatility can be insignificant. Also, it is no longer sufficient to characterize contribution of inter-sectoral production network to aggregate volatility by just looking at input-output matrix or its summary statistics like out-degree distribution. In the end, I propose lead time indicator as a possible proxy for measuring differential sectoral diffusion rates and use it to decompose volatility arising from aggregate and sectoral shocks.

Value Added in Network Economies (in progress, joint with Francois de Soyres)