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on Industrial Organization |
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Issue of 2019‒05‒06
five papers chosen by |
| By: | Berger, Philip G. (University of Chicago Booth School of Business); Choi, Jung Ho (Stanford Graduate School of Business); Tomar, Sorabh (Southern Methodist University Cox School of Business) |
| Abstract: | Does decomposing cost of goods sold entail significant competitive costs? We examine this question using a relaxation of disaggregated manufacturing cost disclosure requirements in Korea. Our survey evidence indicates managers perceive these disclosures to provide a competitive edge to competitors. Using archival data, we find firms with distinctive cost structures and high market shares are less willing to disclose, consistent with a desire to protect cost-leadership advantages embedded in production and sourcing. Firms experience higher gross profits and lower liquidity after withholding manufacturing cost details, suggesting these disclosure decisions involve trading off competitive costs (and not managers’ self-interests) against capital market benefits. At the aggregate level, industries with more nondisclosing firms subsequently experience greater profitability dispersion, suggesting uncertainty about competitors’ cost of goods sold helps drive the widely studied performance dispersion observed within industries. |
| JEL: | D40 D80 L15 M40 |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:stabus:3774&r=all |
| By: | Richard Baron (Univ Lyon, UJM Saint-Etienne, GATE UMR 5824, F-42023 Saint- Etienne, France); Magali Chaudey (Univ Lyon, UJM Saint-Etienne, GATE UMR 5824, F-42023 Saint- Etienne, France) |
| Abstract: | This paper is interested in the analysis of Blockchains and Smart-contracts applied to inter-firms relationships, in particular the franchise networks. After defining the Blockchain technology and the Smart-contract as a particular type of contract stored in blockchains, we question the theory of contracts and its conception(s) of transactions, information asymmetries, firm or inter-firm relations. To better understand the challenges of blockchain for franchise networks and identify opportunities for implementation in these networks, we present some relevant applications of this technology. We identify different ways where blockchain technology could improve the network management and therefore their performance: the supply-chain, the brand-name protection, security and transparency in the payment of fees and royalties, access to reliable information via an oracle. |
| Keywords: | Blockchain, Smart-Contract, Transaction cost, Network, Franchise |
| JEL: | D86 L14 L81 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:gat:wpaper:1917&r=all |
| By: | Díez, Federico; Fan, Jiayue; Villegas-Sanchez, Carolina |
| Abstract: | Using a new firm-level dataset on private and listed firms from 20 countries, we document five stylized facts on market power in global markets. First, competition has declined around the world, measured as a moderate increase in average firm markups during 2000-2015. Second, the markup increase is driven by already high-markup firms (top decile of the markup distribution) that charge increasing markups. Third, markups increased mostly among advanced economies but not in emerging markets. Fourth, there is a non-monotonic relation between firm size and markups that is first decreasing and then increasing. Finally, the increase is mostly driven by increases within incumbents and also by market share reallocation towards high-markup entrants. |
| Keywords: | firm size; market power; Markups; TFP |
| JEL: | D2 D4 E2 L1 L4 |
| Date: | 2019–04 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13696&r=all |
| By: | Caroline Paunov; Sandra Planes-Satorra |
| Abstract: | How are OECD countries supporting digital innovation and ensuring that benefits spread across the economy? This paper explores the current landscape of strategies and initiatives implemented in OECD countries to support innovation in the digital age. It identifies common trends and differences in national digital, smart industry and artificial intelligence (AI) strategies. The paper also discusses policy instruments used across OECD to support digital innovation targeting four objectives: First, policies aimed at enhancing digital technology adoption and diffusion, including demonstration facilities for SMEs. Second, initiatives that promote collaborative innovation, including via the creation of digital innovation clusters and knowledge intermediaries. Third, support for research and innovation in key digital technologies, particularly AI (e.g. by establishing testbeds and regulatory sandboxes). Fourth, policies to encourage digital entrepreneurship (e.g. through early-stage business acceleration support). |
| Keywords: | digital innovation, digital technologies and artificial intelligence (AI), innovation and research policy, innovation strategies |
| JEL: | O30 O31 O33 O38 O25 I28 |
| Date: | 2019–05–06 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:71-en&r=all |
| By: | Grant, Everett (Federal Reserve Bank of Dallas); Yung, Julieta (Bates College) |
| Abstract: | We develop a multi-sector DSGE model to calculate upstream and downstream industry exposure networks from U.S. input-output tables and test the relative importance of shocks from each direction by comparing these with estimated networks of firms’ equity return responses to one another. The correlations between the upstream exposure and equity return networks are large and statistically significant, while the downstream exposure networks have lower — but still positive — correlations that are not statistically significant. These results suggest a low short-term elasticity of substitution across inputs transmitting shocks from suppliers, but more flexible ties with downstream firms. Additionally, both the DSGE model and simulations of our empirical approach highlight the importance of accounting for common factors in network estimation, which become more important over our 1989-2017 sample period, explaining 11.7% of equity return variation over the first ten years and 35.0% over the final ten. |
| Keywords: | upstream versus downstream; input-output linkages; firm networks; shock propagation; aggregate shocks |
| JEL: | C32 D85 E23 E44 G01 |
| Date: | 2019–04–12 |
| URL: | http://d.repec.org/n?u=RePEc:fip:feddgw:360&r=all |