nep-net New Economics Papers
on Network Economics
Issue of 2017‒05‒21
three papers chosen by
Pedro CL Souza
Pontifícia Universidade Católica do Rio de Janeiro

  1. Monetary Policy through Production Networks: Evidence from the Stock Market By Ali Ozdagli; Michael Weber
  2. Spatio-Temporal Patterns of the International Merger and Acquisition Network By Marcos Duenas; Rossana Mastrandrea; Matteo Barigozzi; Giorgio Fagiolo
  3. Sectoral interlinkages in global value chains: spillovers and network effects By Frohm, Erik; Gunnella, Vanessa

  1. By: Ali Ozdagli (Federal Reserve Bank of Boston); Michael Weber (University of Chicago Booth School of Business)
    Abstract: Monetary policy shocks have a large impact on aggregate stock market returns in narrow event windows around press releases by the Federal Open Market Committee. We use spatial autoregressions to decompose the overall effect of monetary policy shocks into a direct (demand) effect and an indirect (network) effect. We attribute 50%-85% of the overall effect to indirect effects. The decomposition is robust to different sample periods, event windows, and types of announcements. Direct effects are larger for industries selling most of the industry output to end-consumers compared to other industries. We find similar evidence of large indirect effects using ex-post realized cash-fundamentals. A simple model with intermediate inputs guides our empirical methodology. Our findings indicate that production networks might be an important propagation mechanism of monetary policy to the real economy.
    Keywords: Input-output linkages, Spillover effects, Asset prices, High frequency identification
    JEL: E12 E31 E44 E52 G12 G14
    Date: 2017
  2. By: Marcos Duenas; Rossana Mastrandrea; Matteo Barigozzi; Giorgio Fagiolo
    Abstract: This paper analyzes the world web of mergers and acquisitions (M&As) using a complex network approach. We use data of M&As to build a temporal sequence of binary and weighted-directed networks, for the period 1995-2010 and 224 countries. We study different geographical and temporal aspects of the international M&As network (IMAN), building sequences of filtered sub-networks whose links belong to specific intervals of distance or time. Given that M&As and trade are complementary ways of reaching foreign markets, we perform our analysis using statistics employed for the study of the international trade network (ITN), highlighting the similarities and differences between the ITN and the IMAN. In contrast to the ITN, the IMAN is a low density network characterized by a persistent giant component with many external nodes and low reciprocity. Clustering patterns are very heterogeneous and dynamic. High-income economies are the main acquirers and are characterized by high connectivity, implying that most countries are targets of a few acquirers. Like in the ITN, geographical distance strongly impacts the structure of the IMAN: link-weights and node degrees are strongly non-linear, and an assortative pattern is present at short distances.
    Keywords: International Economics; Mergers and Acquisitions; Network Analysis; Geographical Distance
    Date: 2017–07–05
  3. By: Frohm, Erik; Gunnella, Vanessa
    Abstract: This paper studies the role of global input-output linkages in transmitting economic disturbances in the international economy. Our empirical results suggest that these sectoral spillovers are both statistically significant and of economic importance. We also provide evidence that it is not the interlinkages per se that matter for the international transmission but rather the presence of global hub sectors that are either large suppliers or purchasers of other sectors' inputs. When the links between these sectors and the rest of the global value chain are severed, the spillovers diminish strongly and eventually become statistically insignificant. This highlights the importance of the structure of the network for enabling spillovers and the prominent role played by hub sectors in the global economy. JEL Classification: E30, E32, F44, F62
    Keywords: global value chains, input-output linkages, networks, spillovers
    Date: 2017–05

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