M. Battaglini, V. Leone Sciabolazza, E. Patacchini, S. Peng (2018), An R Package for the Estimation of Parameter-Dependent Network Centrality Measures [R&R Journal of Statistical Software]

The R package econet provides methods for estimating parameter-dependent network centrality measures with linear-in-means models. Both nonlinear least squares and maximum likelihood estimators are implemented. The methods allow for both link and node heterogeneity in network effects, endogenous network formation and the presence of unconnected nodes. The routines also compare the explanatory power of parameter-dependent network centrality measures with those of standard measures of network centrality. Benefits and features of the econet package are illustrated using data from Battaglini and Patacchini (2018), which examine the determinants of US campaign contributions when legislators care about the behavior of other legislators to whom they are socially connected.

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D. Del Prete, L. Forastiere, V. Leone Sciabolazza, Causal Inference on Networks under Continuous Treatment Interference: an application to trade distortions in agricultural markets, F.R.E.I.T. Working Paper, 1532.

Causal inference often neglects the presence of interference. This takes place when treatment exposure of one unit also affects other units connected through physical, social or economic interactions in a network structure. Extensive work has been done to assess the role played by spillover effects in policy evaluations, but most of the literature focuses on randomized experiments under cluster interference.
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 to estimate both direct and spillover effects of a continuous treatment.
Spillover effects are defined by the exposure to the network treatment, that is, a summary of the treatment received by connected units.
Our estimator also allows to consider asymmetric network connections characterized by heterogeneous intensities. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of policy interventions in agricultural markets. Our results show that, in this context, neglecting interference may underestimates the degree of policy effectiveness.

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D. Del Prete, V. Leone Sciabolazza, G. Santoni, Trade Policy and the Network of Global Value Chains, in preparation.

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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