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on Network Economics |
| By: | Engdahl, Mattias (IFAU - Institute for Evaluation of Labour Market and Education Policy); Willis, Sébastien (Uppsala University and Uppsala Center for Labor Studies); Åslund, Olof (Uppsala University, IFAU, UCLS, CReAM, IZA.) |
| Abstract: | We study how professional networks are related to immigrant labour market integration. Matched employer-employee data for Sweden show that networks grow with time in the host country and that their composition changes from immigrant toward native network members. A firm-dyadic analysis of re-employment of displaced workers suggests that conational connections have a much larger positive effect than native connections. However, the employment effect of native connections grows with years since migration. Furthermore, native connections tend to be associated with higher earnings and increased hires in connected local industries. After 20 years in Sweden, the built-up connections raise immigrant re-employment rates by 0.7 to 1.1 percentage points, amounting to 10–20 percent of the observed difference by years since migration. Our findings indicate complete assimilation in the total productivity of professional connections for displaced workers. |
| Keywords: | labour market integration of immigrants; networks; job search |
| JEL: | J15 J20 J60 |
| Date: | 2024–03–21 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:ifauwp:2024_009&r=net |
| By: | Spiros Bougheas; David I. Harvey; Alan Kirman; Douglas Nelson; Alan P. Kirman; Douglas R. Nelson |
| Abstract: | We develop a dynamic computational network model of the banking system where fire sales provide the amplification mechanism of financial shocks. Each period a finite number of banks offers a large, but finite, number of loans to households. Banks with excess liquidity also offer loans to other banks with insufficient liquidity. Thus, each period an interbank loan market is endogenously formed. Bank assets are hit by idiosyncratic shocks drawn from a thin tailed distribution. The uneven distribution of shocks across banks implies that each period there are banks that become insolvent. If insolvent banks happen also to be heavily indebted to other banks, their liquidation can trigger other bank failures. We find that the distribution across time of the growth rate of banking assets has a ‘fat left tail’ that corresponds to rare economic disasters. We also find that the distribution of initial shocks is not a perfect predictor of economic activity; that is some of the uncertainty is endogenous and related to the structure of the interbank network. |
| Keywords: | systemic risk, fire sales, banking network, macroeconomic shocks |
| JEL: | E44 G01 G21 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10991&r=net |
| By: | Yuichi Kitamura; Louise Laage |
| Abstract: | In the standard stochastic block model for networks, the probability of a connection between two nodes, often referred to as the edge probability, depends on the unobserved communities each of these nodes belongs to. We consider a flexible framework in which each edge probability, together with the probability of community assignment, are also impacted by observed covariates. We propose a computationally tractable two-step procedure to estimate the conditional edge probabilities as well as the community assignment probabilities. The first step relies on a spectral clustering algorithm applied to a localized adjacency matrix of the network. In the second step, k-nearest neighbor regression estimates are computed on the extracted communities. We study the statistical properties of these estimators by providing non-asymptotic bounds. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2402.16322&r=net |
| By: | Daixin Wang; Zhiqiang Zhang; Yeyu Zhao; Kai Huang; Yulin Kang; Jun Zhou |
| Abstract: | User financial default prediction plays a critical role in credit risk forecasting and management. It aims at predicting the probability that the user will fail to make the repayments in the future. Previous methods mainly extract a set of user individual features regarding his own profiles and behaviors and build a binary-classification model to make default predictions. However, these methods cannot get satisfied results, especially for users with limited information. Although recent efforts suggest that default prediction can be improved by social relations, they fail to capture the higher-order topology structure at the level of small subgraph patterns. In this paper, we fill in this gap by proposing a motif-preserving Graph Neural Network with curriculum learning (MotifGNN) to jointly learn the lower-order structures from the original graph and higherorder structures from multi-view motif-based graphs for financial default prediction. Specifically, to solve the problem of weak connectivity in motif-based graphs, we design the motif-based gating mechanism. It utilizes the information learned from the original graph with good connectivity to strengthen the learning of the higher-order structure. And considering that the motif patterns of different samples are highly unbalanced, we propose a curriculum learning mechanism on the whole learning process to more focus on the samples with uncommon motif distributions. Extensive experiments on one public dataset and two industrial datasets all demonstrate the effectiveness of our proposed method. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.06482&r=net |
| By: | Fabian Dvorak; Urs Fischbacher |
| Abstract: | Despite strong evidence for peer effects, little is known about how individuals balance intrinsic preferences and social learning in different choice environments. Using a combination of experiments and discrete choice modeling, we show that intrinsic preferences and social learning jointly influence participants' decisions, but their relative importance varies across choice tasks and environments. Intrinsic preferences guide participants' decisions in a subjective choice task, while social learning determines participants' decisions in a task with an objectively correct solution. A choice environment in which people expect to be rewarded for their choices reinforces the influence of intrinsic preferences, whereas an environment in which people expect to be punished for their choices reinforces conformist social learning. We use simulations to discuss the implications of these findings for the polarization of behavior. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2402.18452&r=net |