This paper presents a methodology to draw causal inference in a non-experimental setting subject to network interference. Specifically, we develop a generalized propensity score-based estimator that allows us to estimate both direct and spillover effects of a continuous treatment, which spreads through a network with weighted and directed edges. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of producers’ support in agricultural markets. Our results show that, in this context, neglecting interference may lead to a downward bias when assessing policy effectiveness.
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The international fragmentation of production processes is dramatically deepening the structural interdependence of the world economy. Recent literature has shown that global value chains are modifying countries’ incentives to impose import protection. However the complex structure of their connections entails the existence of specific direct and indirect effects that affect the price domestic suppliers receive. The aim of this paper is to show that final goods tariffs tend to decrease in the domestic content of foreign-produced final goods but at a different pace when distinguishing the direct partner country from third countries. To get the two separate contributions, we decompose the Leontief inverse matrix into its direct and indirect connections and recompute the domestic and foreign valued added content embodied in final goods. Our results show that both direct and indirect flows play a crucial role in shaping trade policy.
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