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on Network Economics |
| By: | Squintani, Francesco (University of Warwick) |
| Abstract: | This paper brings together two major research streams in economic theory : information transmission in networks and strategic communication. The model embeds persuasion games of strategic disclosure by Milgrom (1981) into the communication network framework by Jackson and Wolinsky (1996). I find that the unique optimal network is a line in which players are ordered according to their bliss points. This ordered line is also pairwise-stable. This …nding stands in sharp contrast to previous results in network studies, that identify stars as the optimal and pairwise-stable networks when communication is non-strategic and subject to technological constraints. While stars are the most centralized minimally-connected networks, the line is the most decentralized one. These results may be especially relevant to political economy applications, such as networks of policymakers, interest groups, or judges |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:wcreta:88 |
| By: | Marc Claveria-Mayol; Pau Milán; Nicolás Oviedo Dávila |
| Abstract: | We study the problem of a principal designing wage contracts that simultaneously incentivize and insure workers. Workers’ incentives are connected through chains of productivity spillovers, represented by a network of peer-effects. We solve for the optimal linear contract for any network and show that optimal incentives are steeper for more central workers. We link firm profits to organizations’ structure via the spectral properties of the co-worker network. When production is modular, the incentive allocation rule is sensitive to the link structure across and within modules. When firms can’t write personalized con- tracts, better connected workers extract rents and total surplus is reduced. In this case, unemployment emerges endogenously because large within-group differences in centrality can decrease firm’s profits. |
| Keywords: | Incentives, Organizations, contracts, Networks, moral hazard |
| JEL: | D21 D23 D85 D86 L14 L22 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1457 |
| By: | Rhys Murrian; Paul A. Raschky; Klaus Ackermann |
| Abstract: | This paper empirically investigates how an individual's network influences their purchase and subsequent use of experience goods. Utilising data on the network and game-ownership of over 108 million users from the world's largest video game platform, we analyse whether a user's friendship network influences their decision to purchase single-player video games. Our identification strategy uses an instrumental variable (IV) approach that employs the temporal lag of purchasing decisions from second degree friends. We find strong peer effects in the individual game adoption in the contemporary week. The effect is stronger if the friend who purchased the game is an old friend compared to a key player in the friendship network. Comparing the results to adoption decisions for a major label game, we find peer effects of a similar size and duration. However, the time subsequently spent playing the games is higher for players who were neither influenced by a peer who is a key player nor an old friend. Considering the increasing importance of online networks on consumption decisions, our findings offer some first insights on the heterogeneity of peer effects between old and key player friends and also provide evidence in consumers' biases in social learning. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.14351 |
| By: | Paola Conconi (University of Oxford, CEP, CESifo and CEPR); Fabrizio Leone (Université Libre de Bruxelles (ECARES) and CESifo.); Glenn Magerman (Université Libre de Bruxelles (ECARES), CESifo and CEPR); Catherine Thomas (London School of Economics, CEP, CESifo and CEPR) |
| Abstract: | This paper provides a novel explanation for the dominant role of multinational corporations (MNCs) in international trade: after being acquired by an MNC, firms face lower trade frictions in and around the network of countries in which their parent has a presence. We provide a model of firms’ export and import choices that isolates “MNC network effects” from other channels through which multinational ownership can affect trade participation. We bring the model to the data by combining rich information on the universe of Belgian firms and on MNCs’ global networks. We find that acquired firms are more likely to start trading with countries that belong to—or that are exogenously added to—their parental network. Network effects extend beyond MNC boundaries and dominate traditional firm-level channels in explaining affiliates’ entry in new markets. Our analysis suggests that the growth rate of acquired firms is more than twice as large as that of the median domestic firm due to MNC network effects. |
| Keywords: | Multinational Firms, International Business, Firm Behavior: Empirical Analysis.s |
| JEL: | F23 D22 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:nbb:reswpp:202409-456 |
| By: | Liang Zhong |
| Abstract: | In social networks or spatial experiments, one unit's outcome often depends on another's treatment, a phenomenon called interference. Researchers are interested in not only the presence and magnitude of interference but also its pattern based on factors like distance, neighboring units, and connection strength. However, the non-random nature of these factors and complex correlations across units pose challenges for inference. This paper introduces the partial null randomization tests (PNRT) framework to address these issues. The proposed method is finite-sample valid and applicable with minimal network structure assumptions, utilizing randomization testing and pairwise comparisons. Unlike existing conditional randomization tests, PNRT avoids the need for conditioning events, making it more straightforward to implement. Simulations demonstrate the method's desirable power properties and its applicability to general interference scenarios. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.09243 |
| By: | Krishna Dasaratha (Boston University); Santosh S. Venkatesh (University of Pennsylvania); Rakesh Vohra (University of Pennsylvania) |
| Abstract: | Widespread default involves substantial deadweight costs which could be countered by injecting capital into failing firms. Injections have positive spillovers that can trigger a repayment cascade. But which firms should a regulator bailout so as to minimize the total injection of capital while ensuring solvency of all firms? While the problem is, in general, NP-hard, for a wide range of networks that arise from a stochastic block model, we show that the optimal bailout can be implemented by a simple policy that targets firms based on their characteristics and position in the network. Specific examples of the setting include core-periphery networks. |
| JEL: | C62 D85 F65 G32 G33 G38 |
| Date: | 2024–09–14 |
| URL: | https://d.repec.org/n?u=RePEc:pen:papers:24-026 |
| By: | Teodoro Criscione |
| Abstract: | Transaction data from digital payment systems can be used to study economic processes at such a detail that was not possible previously. Here, we analyse the data from Sarafu token network, a community inclusion currency in Kenya. During the COVID-19 emergency, the Sarafu was disbursed as part of a humanitarian aid project. In this work, the transactions are analysed using network science. A topological categorisation is defined to identify cyclic and acyclic components. Furthermore, temporal aspects of circulation taking place within these components are considered. The significant presence of different types of strongly connected components as compared to randomized null models shows the importance of cycles in this economic network. Especially, indicating their key role in currency recirculation. In some acyclic components, the most significant triad suggests the presence of a group of users collecting currency from accounts active only once, hinting at a misuse of the system. In some other acyclic components, small isolated groups of users were active only once, suggesting the presence of users only interested in trying out the system. The methods used in this paper can answer specific questions related to user activities, currency design, and assessment of monetary interventions. Our methodology provides a general quantitative tool for analysing the behaviour of users in a currency network. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.13674 |
| By: | Minyu Shen; Feng Xiao; Weihua Gu; Hongbo Ye |
| Abstract: | When making route decisions, travelers may engage in a certain degree of reasoning about what the others will do in the upcoming day, rendering yesterday's shortest routes less attractive. This phenomenon was manifested in a recent virtual experiment that mimicked travelers' repeated daily trip-making process. Unfortunately, prevailing day-to-day traffic dynamical models failed to faithfully reproduce the collected flow evolution data therein. To this end, we propose a day-to-day traffic behavior modeling framework based on the Cognitive Hierarchy theory, in which travelers with different levels of strategic-reasoning capabilities form their own beliefs about lower-step travelers' capabilities when choosing their routes. Two widely-studied day-to-day models, the Network Tatonnement Process dynamic and the Logit dynamic, are extended into the framework and studied as examples. Calibration of the virtual experiment is performed using the extended Network Tatonnement Process dynamic, which fits the experimental data reasonably well. We show that the two extended dynamics have multiple equilibria, one of which is the classical user equilibrium. While analyzing global stability is intractable due to the presence of multiple equilibria, local stabilities near equilibria are developed analytically and verified by numerical experiments. General insights on how key parameters affect the stability of user equilibria are unveiled. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.11908 |
| By: | Sagade, Satchit; Scharnowski, Stefan; Theissen, Erik; Westheide, Christian |
| Abstract: | We examine the impact of increasing competition among the fastest traders by analyzing a new low-latency microwave network connecting exchanges trading the same stocks. Using a difference-in-differences approach comparing German stocks with similar French stocks, we find improved market integration, faster incorporation of stock-specific information, and an increased contribution to price discovery by the smaller exchange. Liquidity worsens for large caps due to increased sniping but improves for mid caps due to fast liquidity provision. Trading volume on the smaller exchange declines across all stocks. We thus uncover nuanced effects of fast trader participation that depend on their prior involvement. |
| Keywords: | Latency, Market Fragmentation, Arbitrage, Liquidity, Price Efficiency, High-Frequency Trading |
| JEL: | G10 G14 G15 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewp:303051 |
| By: | Bhattacharjee, Arnab; Ditzen, Jan; Holly, Sean |
| Abstract: | The literature on panel models has made considerable progress in the last few decades, integrating non-stationary data both in the time and spatial domain. However, there remains a gap in the literature that simultaneously models non-stationarity and cointegration in both the time and spatial dimensions. This paper develops Granger representation theorems for spatial and spatio-temporal dynamics. In a panel setting, this provides a way to represent both spatial and temporal equilibria and dynamics as error correction models. This requires potentially two different processes for modelling spatial (or network) dynamics, both of which can be expressed in terms of spatial weights matrices. The first captures strong cross-sectional dependence, so that a spatial difference, suitably defined, is weakly cross-section dependent (granular) but can be nonstationary. The second is a conventional weights matrix that captures short-run spatio-temporal dynamics as stationary and granular processes. In large samples, cross-section averages serve the first purpose and we propose the mean group, common correlated effects estimator together with multiple testing of cross-correlations to provide the short-run spatial weights. We apply this model to house prices in the 375 MSAs of the US. We show that our approach is useful for capturing both weak and strong cross-section dependence, and partial adjustment to two long-run equilibrium relationships in terms of time and space. |
| Keywords: | Spatio-temporal dynamics, Error Correction Models, Weak and strong cross sectional dependence, US house prices, Spatial weight matrices, Common Correlated Effects estimator |
| JEL: | C21 C22 C23 R3 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:hwuaef:303043 |
| By: | Tejas Ramdas; Martin T. Wells |
| Abstract: | In this study, we leverage powerful non-linear machine learning methods to identify the characteristics of trades that contain valuable information. First, we demonstrate the effectiveness of our optimized neural network predictor in accurately predicting future market movements. Then, we utilize the information from this successful neural network predictor to pinpoint the individual trades within each data point (trading window) that had the most impact on the optimized neural network's prediction of future price movements. This approach helps us uncover important insights about the heterogeneity in information content provided by trades of different sizes, venues, trading contexts, and over time. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.05192 |
| By: | Vainora, J. |
| Abstract: | This paper proposes to use the Generalized Random Dot Product Graph model and the underlying latent positions to model parameter heterogeneity. We discuss how the Stochastic Block Model can be directly applied to model individual parameter heterogeneity. We also develop a new procedure to model pairwise parameter heterogeneity requiring the number of distinct latent distances between unobserved communities to be low. It is proven that, asymptotically, the heterogeneity pattern can be completely recovered. Additionally, we provide three test statistics for the assumption on the number of distinct latent distances. The proposed methods are illustrated using data on a household microfinance program and the S&P 500 component stocks. |
| Keywords: | Networks, Spectral Embedding, Clustering, Generalized Random Dot Product Graph, Stochastic Block Model |
| JEL: | C10 C55 |
| Date: | 2024–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2455 |