nep-net New Economics Papers
on Network Economics
Issue of 2024‒05‒13
five papers chosen by
Alfonso Rosa García, Universidad de Murcia


  1. Network regressions in Stata By Jan Ditzen; William Grieser; Morad Zekhnini
  2. The Impact of COVID-19 on Peer Relationships: Insights from Classroom Social Networks By Yusuf Agus; Betul Turkum
  3. Antinetwork among China A-shares By Peng Liu
  4. Portfolio management using graph centralities: Review and comparison By Bahar Arslan; Vanni Noferini; Spyridon Vrontos
  5. A Comment on Bai, Jia &, Yang (2023) Web of Power: How Elite Networks Shaped War and Politics in China By Buchot, Tom; Couttenier, Mathieu; Laugerette, Lucile; Mougin, Elisa; Verlet, Alexandre

  1. By: Jan Ditzen (Free University of Bozen-Bolzano); William Grieser (Free University of Bozen-Bolzano); Morad Zekhnini (Free University of Bozen-Bolzano)
    Abstract: Network analysis has become critical to the study of social sciences. While several Stata programs are available for analyzing network structures, programs that execute regression analysis with a network structure are currently lacking. We fill this gap by introducing the nwxtregress command. Building on spatial econometric methods (LeSage and Pace 2009), nwxtregress uses MCMC estimation to produce estimates of endogenous peer effects, as well as own-node (direct) and cross-node (indirect) partial effects, where nodes correspond to cross-sectional units of observation, such as firms, and edges correspond to the relations between nodes. Unlike existing spatial regression commands (for example, spxtregress), nwxtregress is designed to handle unbalanced panels of economic and social networks. Networks can be directed or undirected with weighted or unweighted edges, and they can be imported in a list format that does not require a shapefile or a Stata spatial weight matrix set by spmatrix. A special focus of the presentation will be put on the construction of the spatial weight matrix and integration with Python to improve speed.
    Date: 2023–09–10
    URL: http://d.repec.org/n?u=RePEc:boc:lsug23:21&r=net
  2. By: Yusuf Agus (European University Institute); Betul Turkum (Aix-Marseille Univ., CNRS, AMSE, Marseille, France)
    Abstract: We analyze the impact of the COVID-19 outbreak on classroom peer relationships using a unique field dataset collected from 3rd and 4th-grade students in Turkey. Using data from both pre-pandemic and pandemic cohorts, we find significant changes in social interactions among the pandemic cohort after prolonged school closures. We observe varying effects contingent upon the nature of peer relationships. While friendship relationships deteriorated, some facets of academic support relationships among classmates display enhancement. However, this progress is exclusively observed among native students, as opposed to refugees. Additionally, we uncover significant improvements in inter-ethnicity and inter-gender relationships in classrooms after COVID-19.
    Keywords: Peer relationships; COVID-19; classroom social networks; refugees
    JEL: D85 I21 I24 I28 J15 J16
    Date: 2024–04
    URL: http://d.repec.org/n?u=RePEc:aim:wpaimx:2415&r=net
  3. By: Peng Liu
    Abstract: The correlation-based financial networks, constructed with the correlation relationships among the time series of fluctuations of daily logarithmic prices of stocks, are intensively studied. However, these studies ignore the importance of negative correlations. This paper is the first time to consider the negative and positive correlations separately, and accordingly to construct weighted temporal antinetwork and network among stocks listed in the Shanghai and Shenzhen stock exchanges. For (anti)networks during the first 24 years of the 21st century, the node's degree and strength, the assortativity coefficient, the average local clustering coefficient, and the average shortest path length are analyzed systematically. This paper unveils some essential differences in these topological measurements between antinetwork and network. The findings of the differences between antinetwork and network have an important role in understanding the dynamics of a financial complex system. The observation of antinetwork is of great importance in optimizing investment portfolios and risk management. More importantly, this paper proposes a new direction for studying complex systems, namely the correlation-based antinetwork.
    Date: 2024–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2404.00028&r=net
  4. By: Bahar Arslan; Vanni Noferini; Spyridon Vrontos
    Abstract: We investigate an application of network centrality measures to portfolio optimization, by generalizing the method in [Pozzi, Di Matteo and Aste, \emph{Spread of risks across financial markets: better to invest in the peripheries}, Scientific Reports 3:1665, 2013], that however had significant limitations with respect to the state of the art in network theory. In this paper, we systematically compare many possible variants of the originally proposed method on S\&P 500 stocks. We use daily data from twenty-seven years as training set and their following year as test set. We thus select the best network-based methods according to different viewpoints including for instance the highest Sharpe Ratio and the highest expected return. We give emphasis in new centrality measures and we also conduct a thorough analysis, which reveals significantly stronger results compared to those with more traditional methods. According to our analysis, this graph-theoretical approach to investment can be used successfully by investors with different investment profiles leading to high risk-adjusted returns.
    Date: 2024–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2404.00187&r=net
  5. By: Buchot, Tom; Couttenier, Mathieu; Laugerette, Lucile; Mougin, Elisa; Verlet, Alexandre
    Abstract: Bai et al. (2023) examine the impact of individual networks on state building, focusing on the role of the leader Zeng Guofan during the Taiping Revolution in China between 1850 and 1864. In their main results, the authors demonstrate that being connected to Zeng increases the number of fatalities during the war after his assumption of power, with point estimates being significant at the 1% or 5% level. They also find a positive and significant effect of connections to Zeng among Hunan people on the number of national-level office positions, with point estimates significant at the 1% level. First, we reproduce the paper's main findings and identify minor inaccuracies in the codes that need fixing for the proper reproduction of some tables. However, these issues do not significantly impact the overall results. Second, we conduct additional checks and argue that the results are robust to variations in the number of fixed effects but highly dependent on the choice of econometric specification. We employ alternative models more suitable for data with a substantial number of zeros, revealing a decrease in the magnitude and significance of the estimates. Last, we perform spatial robustness checks, confirming the absence of spatial correlation between Hunan county and its neighboring regions, as suggested by the authors.
    Date: 2024
    URL: http://d.repec.org/n?u=RePEc:zbw:i4rdps:115&r=net

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