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on Network Economics |
| By: | Dziubiński, M.; Goyal, S.; Zhou, J. |
| Abstract: | We study a model of conflict with multiple battlefields and the possibility of investments spillovers between the battlefields. Results of conflicts at the individual battlefields are determined by the Tullock contest success function based on efforts assigned to a battlefield as well as efforts spilling over from the neighbouring battlefields. We characterize Nash equilibria of this model and uncover a network invariance result: equilibrium payoffs, equilibrium total expenditure, and equilibrium probabilities of winning individual battlefields are independent of the network of spillovers. We show that the network invariance holds for any contest success function that is homogeneous of degree zero and has the no-tie property. We define a network index that characterizes equilibrium efforts assignments of the players. We show that the index satisfies neighbourhood inclusion and can, therefore, be considered a network centrality. |
| Keywords: | Conflict, Investments, Models, Networks |
| Date: | 2024–02–21 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2408&r=net |
| By: | Choi, S.; Goyal, S.; Guo, F.; Moisan, F. |
| Abstract: | Social interactions shape individual behaviour and public policy increasingly uses networks to improve effectiveness. It is therefore important to understand if the theoretical predictions on the relation between networks and individual choice are empirically valid. This paper tests a key result in the theory of games on networks: an individual’s action is proportional to their (Bonacich) centrality. Our experiment shows that individual efforts increase in centrality but at a rate of increase that is lower than the theoretical prediction. Moreover, efforts are higher than predicted in some cases and lower than predicted in other cases. These departures from equilibrium have large effects on individual earnings. We propose a model of network based imitation decision rule to explain these deviations. |
| JEL: | C92 D83 D85 Z13 |
| Date: | 2024–01–16 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2401&r=net |
| By: | Bramoullé, Y.; Ghiglino, C. |
| Abstract: | We introduce loss aversion into a model of conspicuous consumption in networks. Agents allocate heterogeneous incomes between a conventional good and a status good. They interact over a connected network and compare their status consumption to their neighbors’ average consumption. We find that aversion to lying below the social reference point has a profound impact. If loss aversion is large relative to income heterogeneity, a continuum of conformist Nash equilibria emerges. Agents have the same status consumption, despite differences in incomes and network positions, and the equilibrium is indeterminate. Otherwise, there is a unique Nash equilibrium and status consumption depends on the interplay between network positions and incomes. Our analysis extends to homothetic and heterogeneous preferences. |
| Keywords: | Conspicuous Consumption, Loss Aversion, Social Networks |
| Date: | 2024–03–12 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2414&r=net |
| By: | Gergely Horvath; Mofei Jia |
| Abstract: | We study whether competition for social status induces higher effort provision and efficiency when individuals collaborate with their network neighbors. We consider a laboratory experiment in which individuals choose a costly collaborative effort and their network neighbors. They benefit from their neighbors' effort and effort choices of direct neighbors are strategic complements. We introduce two types of social status in a 2x2 factorial design: 1) individuals receive monetary benefits for incoming links representing popularity; 2) they receive feedback on their relative payoff ranking within the group. We find that link benefits induce higher effort provision and strengthen the collaborative ties relative to the Baseline treatment without social status. In contrast, the ranking information induces lower effort as individuals start competing for higher ranking. Overall, we find that social status has no significant impact on the number of links in the network and the efficiency of collaboration in the group. |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2403.05830&r=net |
| By: | Chiplunkar, Gaurav (University of Virginia); Kelley, Erin (World Bank); Lane, Gregory (University of Chicago) |
| Abstract: | We study how job-seekers share information about jobs within their social network, and its implications for firms. We randomly increase the amount of competition for a job and find that job-seekers are less likely to share information about the job with their high ability peers. This lowers the quality of applicants, hires, and performance on the job - suggesting that firms who disseminate job information through social networks may see lower quality applicants than expected for their most competitive positions. While randomly offering higher wages attracts better talent, it is not able to fully overcome these strategic disincentives in information sharing. |
| Keywords: | job information, social networks, labor markets |
| JEL: | L14 M51 O12 |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp16840&r=net |
| By: | Arun G. Chandrasekhar; Paul Goldsmith-Pinkham; Tyler H. McCormick; Samuel Thau; Jerry Wei |
| Abstract: | Network diffusion models are used to study things like disease transmission, information spread, and technology adoption. However, small amounts of mismeasurement are extremely likely in the networks constructed to operationalize these models. We show that estimates of diffusions are highly non-robust to this measurement error. First, we show that even when measurement error is vanishingly small, such that the share of missed links is close to zero, forecasts about the extent of diffusion will greatly underestimate the truth. Second, a small mismeasurement in the identity of the initial seed generates a large shift in the locations of expected diffusion path. We show that both of these results still hold when the vanishing measurement error is only local in nature. Such non-robustness in forecasting exists even under conditions where the basic reproductive number is consistently estimable. Possible solutions, such as estimating the measurement error or implementing widespread detection efforts, still face difficulties because the number of missed links are so small. Finally, we conduct Monte Carlo simulations on simulated networks, and real networks from three settings: travel data from the COVID-19 pandemic in the western US, a mobile phone marketing campaign in rural India, and in an insurance experiment in China. |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2403.05704&r=net |
| By: | Gianluca Pallante; Mattia Guerini; Mauro Napoletano; Andrea Roventini |
| Abstract: | We extend the Schumpeter meeting Keynes (K+S; see Dosi et al., 2010, 2013, 2015) to model the emergence and the dynamics of an interbank network in the money market. The extended model allows banks to directly exchange funds, while evaluating their interbank positions using a network- based clearing mechanism (NEVA, see Barucca et al., 2020). These novel adds on, allow us to better measure financial contagion and systemic risk events in the model and to study the possible interactions between micro-prudential and macro-prudential policies. We find that the model can replicate new stylized facts concerning the topology of the interbank network, as well as the dynamics of individual banks’ balance sheets. Policy results suggest that the economic system at large can benefit from the introduction of a micro-prudential regulation that takes into account the interbank network relationships. Such a policy decreases the incidence of systemic risk events and the bankruptcies of financial institutions. Moreover, a trade-off between financial stability and macroeconomic performance does not emerge in a two-pillar regulatory framework grounded on i) a Basel III macro-prudential regulation and ii) a NEVA-based micro-prudential policy. Indeed, the NEVA allows the economic system to achieve financial stability without overly stringent capital requirements. |
| Keywords: | Financial contagion, Systemic risk, Micro-prudential policy, Macro-prudential policy, Macroeconomic stability, Agent-based computational economics |
| Date: | 2024–03–25 |
| URL: | https://d.repec.org/n?u=RePEc:ssa:lemwps:2024/08&r=net |
| By: | Agostino Capponi; Chuan Du; Joseph E. Stiglitz |
| Abstract: | We show that supply networks are inefficiently, and insufficiently, resilient. Upstream firms can expand their production capacity to hedge against supply and demand shocks. But the social benefits of such investments are not internalized due to market power and market incompleteness. Upstream firms under-invest in capacity and resilience, passing-on the costs to down-stream firms, and drive trade excessively towards the spot markets. There is a wedge between the market solution and a constrained optimal benchmark, which persists even without rare and large shocks. Policies designed to incentivize capacity investment, reduce reliance on spot markets, and enhance competition ameliorate the externality. |
| JEL: | D21 D24 D25 D43 D85 E23 L13 |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32221&r=net |
| By: | Berger, Thor (Department of Economics and Statistics); Prawitz, Erik (Department of Economics and Statistics) |
| Abstract: | Why has collaboration become increasingly central to technological progress? We document the role of lowered travel costs by combining patent data with the rollout of the Swedish railroad network in the 19th and early-20th century. Inventors that gain access to the network are more likely to produce collaborative patents, which is partly driven by long-distance collaborations with other inventors residing along the emerging railroad network. These results suggest that the declining costs of interacting with others is fundamental to account for the long-term increase in inventive collaboration. |
| Keywords: | Innovation; Collaboration; Transport infrastructure; Railroads |
| JEL: | L91 N73 O18 O31 |
| Date: | 2023–03–28 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:vxesta:2023_002&r=net |
| By: | Khizar Qureshi; Tauhid Zaman |
| Abstract: | Pairs trading, a strategy that capitalizes on price movements of asset pairs driven by similar factors, has gained significant popularity among traders. Common practice involves selecting highly cointegrated pairs to form a portfolio, which often leads to the inclusion of multiple pairs sharing common assets. This approach, while intuitive, inadvertently elevates portfolio variance and diminishes risk-adjusted returns by concentrating on a small number of highly cointegrated assets. Our study introduces an innovative pair selection method employing graphical matchings designed to tackle this challenge. We model all assets and their cointegration levels with a weighted graph, where edges signify pairs and their weights indicate the extent of cointegration. A portfolio of pairs is a subgraph of this graph. We construct a portfolio which is a maximum weighted matching of this graph to select pairs which have strong cointegration while simultaneously ensuring that there are no shared assets within any pair of pairs. This approach ensures each asset is included in just one pair, leading to a significantly lower variance in the matching-based portfolio compared to a baseline approach that selects pairs purely based on cointegration. Theoretical analysis and empirical testing using data from the S\&P 500 between 2017 and 2023, affirm the efficacy of our method. Notably, our matching-based strategy showcases a marked improvement in risk-adjusted performance, evidenced by a gross Sharpe ratio of 1.23, a significant enhancement over the baseline value of 0.48 and market value of 0.59. Additionally, our approach demonstrates reduced trading costs attributable to lower turnover, alongside minimized single asset risk due to a more diversified asset base. |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2403.07998&r=net |