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on Network Economics |
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Issue of 2019‒02‒25
five papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Johannes Boehm (Département d'économie); Jan Sonntag (Département d'économie) |
| Abstract: | This paper studies the prevalence of vertical market foreclosure using a novel dataset on U.S. and international buyer-seller relationships, and across a large range of industries. We find that relationships are more likely to break when suppliers vertically integrate with one of the buyers’ competitors than when they vertically integrate with an unrelated firm. This relationship holds also, among other things, when conditioning on mergers that follow exogenous downward pressure on the supplier’s stock prices, suggesting that reverse causality is unlikely to explain the result. In contrast, the relationship vanishes when using rumored or announced but not completed integration events. Firms experience a substantial drop in sales when one of their suppliers integrates with one of their competitors. This sales drop is mitigated if the firm has alternative suppliers in place. |
| Keywords: | Mergers and acquisitions; Market foreclosure; Vertical integration; Production networks |
| JEL: | L14 L42 |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/44gofgf80399mp5fq5q50vv5t6&r=all |
| By: | Bernard, Andrew B.; Dhyne, Emmanuel; Magerman, Glenn; Manova, Kalina; Moxnes, Andreas |
| Abstract: | This paper quantifies the origins of firm size heterogeneity when firms are interconnected in a production network. Using the universe of buyer-supplier relationships in Belgium, the paper develops a set of stylized facts that motivate a model in which firms buy inputs from upstream suppliers and sell to downstream buyers and final demand. Larger firm size can come from high production capability, more or better buyers and suppliers, and/or better matches between buyers and suppliers. Downstream factors explain the vast majority of firm size heterogeneity. Firms with higher production capability have greater market shares among their customers, but also higher input costs and fewer customers. As a result, high production capability firms have lower sales unconditionally and higher sales conditional on their input prices. Counterfactual analysis suggests that the production network accounts for more than half of firm size dispersion. Taken together, our results suggest that multiple firm attributes underpin their success or failure, and that models with only one source of firm heterogeneity fail to capture the majority of firm size dispersion. |
| Keywords: | firm size heterogeneity; production networks; productivity |
| JEL: | F10 F12 F16 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13429&r=all |
| By: | de Janvry, Alain; Emerick, Kyle; Kelley, Erin; Sadoulet, Elisabeth |
| Abstract: | Can agents in a social network be induced to obtain information from outside their peer groups? Using a field experiment in rural Bangladesh, we show that demonstration plots in agriculture - a technique where the first users of a new variety cultivate it in a side-by-side comparison with an existing variety - facilitate social learning by inducing conversations and information sharing outside of existing social networks. We compare these improvements in learning with those from seeding new technology with more central farmers in village social networks. The demonstration plots - when cultivated by randomly selected farmers - improve knowledge by just as much as seeding with more central farmers. Moreover, the demonstration plots only induce conversations and facilitate learning for farmers that were unconnected to entry points at baseline. Finally, we combine this diffusion experiment with an impact experiment to show that both demonstration plots and improved seeding transmit information to farmers that are less likely to benefit from the new innovation. |
| Keywords: | agriculture; Social learning; Technology adoption |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13507&r=all |
| By: | Guy Tchuente |
| Abstract: | The identification of the network effect is based on either group size variation, the structure of the network or the relative position in the network. I provide easy-to-verify necessary conditions for identification of undirected network models based on the number of distinct eigenvalues of the adjacency matrix. Identification of network effects is possible; although in many empirical situations existing identification strategies may require the use of many instruments or instruments that could be strongly correlated with each other. The use of highly correlated instruments or many instruments may lead to weak identification or many instruments bias. This paper proposes regularized versions of the two-stage least squares (2SLS) estimators as a solution to these problems. The proposed estimators are consistent and asymptotically normal. A Monte Carlo study illustrates the properties of the regularized estimators. An empirical application, assessing a local government tax competition model, shows the empirical relevance of using regularization methods. |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.06143&r=all |
| By: | Xintong Han (Concordia University); Lei Xu (Toulouse School of Economics) |
| Abstract: | This paper investigates the role of network structure in technology adoption. In particular, we study how the network of individual agents can slow down the speed of adoption. We study this issue in the context of the Python programming language by modeling the decisions to adopt Python version 3 by software packages. Python 3 provides advanced features but is not backward compatible with Python 2, which implies adoption costs. Moreover, packages form an input-output network through dependency on other packages in order to avoid writing duplicate code, and they face additional adoption costs from dependencies without Python 3 support. We build a dynamic model of technology adoption that incorporates the input-output network. With a complete dataset of package characteristics for historical releases and user downloads, we draw the input-output network and develop a new estimation method based on the dependency relationship. Estimation results show the average cost of one incompatible dependency is one-third the fixed cost of updating a package’s code. Simulations show the input-output network contributes to 1.5 years of adoption inertia. We conduct counterfactual policies of promotion in subcommunities and find significant heterogeneous effects on the adoption rates due to differences in network structure. Length: 43 pages |
| Keywords: | dynamic adoption, network dependency, structural estimation |
| Date: | 2019–01–22 |
| URL: | http://d.repec.org/n?u=RePEc:crd:wpaper:19001&r=all |