Networks in Production: Asset Pricing Implications
No 378, 2015 Meeting Papers from Society for Economic Dynamics
This paper studies asset pricing in a multisector model in which sectors are connected to each other through an input-output network. Changes in the structure of the network are sources of systematic risk reflected in equilibrium asset prices. There are two key characteristics of the network that matter for asset prices: network concentration and network sparsity. Network concentration measures the degree to which equilibrium output is dominated by few large sectors while network sparsity measures the average input specialization of the economy. Furthermore, these two production-based asset pricing factors are determined by the structure of the network of production and can be computed from input-output data. By sorting stocks based on their exposure to the network factors, I find a return spread of 6% per year on portfolios sorted on sparsity-beta and ~4% per year on portfolios sorted on concentration-beta. These return gaps cannot be explained by standard asset pricing models such as the CAPM or the Fama French three-factor model. A calibrated model matches the network factor betas and return spreads alongside other asset pricing moments.
New Economics Papers: this item is included in nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:red:sed015:378
Access Statistics for this paper
More papers in 2015 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().