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on Network Economics |
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Issue of 2017‒04‒16
five papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Richard Holden (UNSW Australia Business School); Michael Keane (Oxford University and UNSW Australia Business School); Matthew Lilley (Harvard University) |
| Abstract: | Using data on essentially every US Supreme Court decision since 1946, we estimate a model of peer effects on the Court. We consider both the impact of justice ideology and justice votes on the votes of their peers. To identify these peer effects we use two instruments. The first is based on the composition of the Court, determined by which justices sit on which cases due to recusals or health reasons for not sitting. The second utilizes the fact that many justices previously sat on Federal Circuit Courts and are empirically much more likely to affirm decisions from their “home” court. We find large peer effects. Replacing a single justice with one who votes in a conservative direction 10 percentage points more frequently increases the probability that each other justice votes conservative by 1.63 percentage points. In terms of votes, a 10 percentage point increase in the probability that a single justice votes conservative leads to a 1.1 percentage increase in the probability that each other justice votes conservative. Finally, a single justice becoming 10% more likely to vote conservative increases the share of cases with a conservative outcome by 3.6 percentage points–excluding the direct effect of that justice–and reduces the share with a liberal outcome by 3.2 percentage points. In general, the indirect effect of a justice’s vote on the outcome through the votes of their peers is typically several times larger than the direct mechanical effect of the justice’s own vote |
| Date: | 2017–02–03 |
| URL: | http://d.repec.org/n?u=RePEc:nuf:econwp:1702&r=net |
| By: | Raphael Auer; Andrei A Levchenko; Philip Sauré |
| Abstract: | We document that observed international input-output linkages contribute substantially to synchronizing producer price inflation (PPI) across countries. Using a multi-country, industry-level dataset that combines information on PPI and exchange rates with international and domestic input-output linkages, we recover the underlying cost shocks that are propagated internationally via the global input-output network, thus generating the observed dynamics of PPI. We then compare the extent to which common global factors account for the variation in actual PPI and in the underlying cost shocks. Our main finding is that across a range of econometric tests, input-output linkages account for half of the global component of PPI inflation. We report three additional findings: (i) the results are similar when allowing for imperfect cost pass-through and demand complementarities; (ii) PPI synchronization across countries is driven primarily by common sectoral shocks and input-output linkages amplify co-movement primarily by propagating sectoral shocks; and (iii) the observed pattern of international input use preserves fat-tailed idiosyncratic shocks and thus leads to a fat-tailed distribution of inflation rates, i.e., periods of disinflation and high inflation. |
| Keywords: | international inflation synchronization, globalisation, inflation, input linkages, monetary policy, global value chain, production structure, input-output linkages, supply chain |
| Date: | 2017–04 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:623&r=net |
| By: | Huber, Martin (University of Fribourg); Steinmayr, Andreas (University of Munich) |
| Abstract: | This paper suggests a causal framework for disentangling individual level treatment effects and interference effects, i.e., general equilibrium, spillover, or interaction effects related to treatment distribution. Thus, the framework allows for a relaxation of the Stable Unit Treatment Value Assumption (SUTVA), which assumes away any form of treatment-dependent interference between study participants. Instead, we permit interference effects within aggregate units, for example, regions or local labor markets, but need to rule out interference effects between these aggregate units. Borrowing notation from the causal mediation literature, we define a range of policy-relevant effects and formally discuss identification based on randomization, selection on observables, and difference-in-differences. We also present an application to a policy intervention extending unemployment benefit durations in selected regions of Austria that arguably affected ineligibles in treated regions through general equilibrium effects in local labor markets. |
| Keywords: | treatment effect, general equilibrium effects, spillover effects, interaction effects, interference effects, inverse probability weighting, propensity score, mediation analysis, difference-in-differences |
| JEL: | C21 C31 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp10648&r=net |
| By: | Jorge Abad; Marco D’Errico; Neill Killeen; Vera Luz; Tuomas Peltonen; Richard Portes; Teresa Urbano |
| Abstract: | This paper provides a unique snapshot of the exposures of EU banks to shadow banking entities within the global financial system. Drawing on a rich and novel dataset, the paper documents the cross-sector and cross-border linkages and considers which are the most relevant for systemic risk monitoring. From a macroprudential perspective, the identification of potential feedback and contagion channels arising from the linkages of banks and shadow banking entities is particularly challenging when shadow banking entities are domiciled in different jurisdictions. The analysis shows that many of the EU banks’ exposures are towards non-EU entities, particularly US-domiciled shadow banking entities. At the individual level, banks’ exposures are diversified although this diversification leads to high overlap across different types of shadow banking entities. JEL Classification: F65, G21, G23 |
| Keywords: | shadow banking, interconnectedness, financial stability, macroprudential policy |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:srk:srkwps:201740&r=net |
| By: | Katarzyna Growiec; Jakub Growiec; Bogumil Kaminski |
| Abstract: | Based on a novel computational multi-agent model, we identify the keymechanisms allowing the social network structure, summarized by four key socialcapital dimensions (network degree, centrality, bridging and bonding social capital), to affect individuals' social trust, willingness to cooperate, social utility and economicperformance. We then trace how the individual-level outcomes aggregate up to thesociety level. Model setup draws from socio-economic theory and empirical findings based on our novel survey dataset. Results include aggregate-level comparative staticsand individual-level correlations. We find, inter alia, that societies that either arebetter connected, exhibit a lower frequency of local cliques, or have a smaller share offamily-based cliques, record relatively better economic performance. As long as familyties are sufficiently valuable, there is a trade-off between aggregate social utility andeconomic performance, and small world networks are then socially optimal. |
| Keywords: | social network structure, social trust, willingness to cooperate, economicperformance, computational multi-agent model |
| JEL: | C63 D85 J31 L14 Z13 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:sgh:kaewps:2017026&r=net |