scholarly journals Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter

2019 ◽  
Vol 26 (6) ◽  
pp. 1291-1328 ◽  
Author(s):  
Annette Alstadsæter ◽  
Wojciech Kopczuk ◽  
Kjetil Telle
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Causal Effect ◽  
Behavioral Responses ◽  
Tax Avoidance ◽  
Capital Gains ◽  
Family Networks ◽  
Tax Shelter ◽  
Tax Shelters ◽  
Set Up

AbstractIn 2005, over 8% of Norwegian shareholders transferred their shares to new (legal) tax shelters intended to defer taxation of capital gains and dividends that would otherwise be taxable in the aftermath of a reform implemented in 2006. Using detailed administrative data, we identify family networks and describe how take-up of tax avoidance progresses within a network. A feature of the reform was that the eligibility to set up a tax shelter changed discontinuously with individual shareholding of a firm and we use this fact to estimate the causal effect of availability of tax avoidance for a taxpayer on tax avoidance by others in the network. We find that eligibility in a social network increases the likelihood that others will take-up. This suggests that taxpayers affect each other’s decisions about tax avoidance, highlighting the importance of accounting for social interactions in understanding enforcement and tax avoidance behavior, and providing a concrete example of optimization frictions in the context of behavioral responses to taxation.

Social Networks and Patterns of Social Interaction among Ever-Single and Separated/Divorced Elderly Canadians

1992 ◽  
Vol 11 (1) ◽  
pp. 31-53 ◽  
Author(s):  
Laurel A. Strain ◽  
Barbara J. Payne
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Living Arrangements ◽  
General Social Survey ◽  
Social Survey ◽  
Family Networks ◽  
Education And Health ◽  
The Social ◽  
Gender Education ◽  
Statistics Canada

AbstractThis paper examines the social networks and patterns of social interactions of two relatively neglected marital status groups of elders, namely the ever-single and the separated/divorced. Drawing on data from the 1985 General Social Survey conducted by Statistics Canada, comparisons are made both between and among the 224 ever-single and 126 separated/divorced Canadians aged 65 and over. When controlling for age, gender, education and health status, ever-single individuals tend to have smaller family networks, a similar number of friends, and similar living arrangements as the separated/divorced. In-person contact with siblings is significantly associated with being ever-single while no differences emerge for contact with other relatives or with friends. Differences among the ever-single and among the separated/divorced are also assessed.

A Cross-Species Application of Bott's Hypothesis on Role Segregation and Social Networks

1991 ◽  
Vol 34 (4) ◽  
pp. 403-425 ◽  
Author(s):  
Alexandra Maryanski ◽  
Masako Ishii-Kuntz
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Structural Dynamics ◽  
Social Relations ◽  
Causal Effect ◽  
Network Density ◽  
Primate Research ◽  
Family Networks ◽  
Representative Species ◽  
Network Overlap

Elizabeth Bott's hypothesis that the degree of role-segregation between husbands and wives is a function of the density in family networks is applied to a review of social relations among representative species from seven genera of Old World primates. On the whole, the hypothesis is supported. In seeking to apply Bott's ideas to primate research, her theory is formalized and stated more abstractly, with the result that its structural dynamics are highlighted. These structural processes revolve around three phenomena: (a) the negative causal effect of network overlap on density of each actor's networks; (b) the positive causal effect of network density on the degree of social support provided by, and a normative elaboration of, each actor's networks; and (c) the causal effect of social support and normative elaboration on the segregation of each actor's activities.

Investment Opportunity Sets, Operating Uncertainty, and Capital Market Pressure: Determinants of Investments in Tax Shelter Activities?

2013 ◽  
Vol 36 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Sean T. McGuire ◽  
Thomas C. Omer ◽  
Jaron H. Wilde
Keyword(s):  
Capital Market ◽  
Tax Avoidance ◽  
Investment Strategy ◽  
Data Availability ◽  
Investment Behavior ◽  
Investment Opportunity ◽  
Opportunity Sets ◽  
Tax Shelter ◽  
Tax Shelters ◽  
Market Pressure

ABSTRACT Prior research documents substantial variation in firms' tax avoidance activities and questions why some firms choose not to take advantage of the apparent benefits of tax planning (i.e., the “undersheltering puzzle”). We provide additional insight into the undersheltering puzzle by investigating the decision to invest in a tax shelter from the perspective of a firm's overall investment strategy. We examine whether three factors associated with traditional investment behavior (firms' investment opportunity sets, operating uncertainty, and capital market pressure) are also associated with investments in tax shelter activities. Our results suggest that firms with large investment opportunity sets and higher operating uncertainty are less likely to invest in tax shelters. We also find that firms with greater capital market pressure are more likely to invest in tax sheltering activities. Overall, we find that factors that influence firms' investment behavior help to explain why more firms do not invest in tax shelters. Data Availability: All data used in this study are available from publicly available sources identified in the manuscript. JEL Classifications: H25, H26, M41

scholarly journals Social Networks and Tax Avoidance: Evidence from a Well-Defined Norwegian Tax Shelter

2018 ◽  
Author(s):  
Annette Alstadsæter ◽  
Wojciech Kopczuk ◽  
Kjetil Telle
Keyword(s):  
Social Networks ◽  
Tax Avoidance ◽  
Tax Shelter

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

scholarly journals Optimization Algorithms for Detection of Social Interactions

Algorithms ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 139 ◽  
Author(s):  
Vincenzo Cutello ◽  
Georgia Fargetta ◽  
Mario Pavone ◽  
Rocco A. Scollo
Keyword(s):  
Social Networks ◽  
Local Search ◽  
Social Interactions ◽  
Community Detection ◽  
Experimental Analysis ◽  
Search Strategy ◽  
Random Search ◽  
Optimization Methods ◽  
Research Areas ◽  
Greedy Optimization

Community detection is one of the most challenging and interesting problems in many research areas. Being able to detect highly linked communities in a network can lead to many benefits, such as understanding relationships between entities or interactions between biological genes, for instance. Two different immunological algorithms have been designed for this problem, called Opt-IA and Hybrid-IA, respectively. The main difference between the two algorithms is the search strategy and related immunological operators developed: the first carries out a random search together with purely stochastic operators; the last one is instead based on a deterministic Local Search that tries to refine and improve the current solutions discovered. The robustness of Opt-IA and Hybrid-IA has been assessed on several real social networks. These same networks have also been considered for comparing both algorithms with other seven different metaheuristics and the well-known greedy optimization Louvain algorithm. The experimental analysis conducted proves that Opt-IA and Hybrid-IA are reliable optimization methods for community detection, outperforming all compared algorithms.

scholarly journals Can Dogs’ Origins and Interactions with Humans Affect Their Accomplishments? A Study on the Responses of Shelter and Companion Dogs during Vocal Cue Training

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1360
Author(s):  
Maria Luiza A. Fonseca ◽  
Angélica S. Vasconcellos
Keyword(s):  
Social Interactions ◽  
Social Deprivation ◽  
Behavioral Responses ◽  
The Other ◽  
Influential Factor ◽  
Vocal Cues ◽  
Companion Dogs ◽  
Shelter Dogs ◽  
Tone Of Voice ◽  
Neutral Tone

The inclusion of life history as a possible influential factor is pivotal in studies on behavior, welfare, and cognition. Shelter dogs have usually experienced a life involving poor social interactions with humans. Thus, we aimed to investigate the behavioral responses of shelter dogs (SDs) and companion dogs (CDs) during the training of two vocal cues (“sit”, “paw”), as well as the possible associations between their responses and the behaviors of trainers. We studied 15 SDs and 15 CDs in up to eight five-minute training sessions. Dogs’ and trainers’ behaviors were recorded and analyzed (through GLM, GLMM, correlation and Mann–Whitney tests). Shelter dogs responded to more cues per session, with shorter latencies and fewer repetitions of cues. Moreover, SDs spent more time wagging their tails. Dogs’ sex and trainers’ behaviors were also associated with differences in dogs’ responses. The use of a reproachful tone of voice was associated with a greater number of cues responded to, shorter latencies, and fewer repetitions of cues. However, this type voice/discourse was also linked to a greater exhibition of non-training behaviors (e.g., exploring the room or jumping on the trainer), and to dogs spending less time next to the trainer and wagging their tails. On the other hand, the use of a neutral tone of voice and laughter, besides being linked to performance, was also associated with longer durations of tail wagging. Furthermore, the duration of the trainers’ orientation to dogs was correlated with the orientation of the dogs to the trainers. Our data suggest that, even when having experienced social deprivation from humans, SDs’ capacities to learn vocal cues were preserved, possibly due to ontogenic homeostasis processes. Shelter dogs’ greater interest in the sessions may be also credited to their socially-deprived routine. Our outcomes also point to an association between friendly interactions during training and dog performance and excitement, which suggests that such interactions may have the potential to improve SD welfare.

scholarly journals The switching mechanisms of social network densification

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Context ◽  
Social Interactions ◽  
Regime Switching ◽  
Face To Face ◽  
The Social ◽  
Switching Property ◽  
Distinctive Type ◽  
Insight Into

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.

scholarly journals Emergence and evolution of social networks through exploration of the Adjacent Possible space

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Enrico Ubaldi ◽  
Raffaella Burioni ◽  
Vittorio Loreto ◽  
Francesca Tria
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Social Interactions ◽  
Clustering Coefficient ◽  
Human Beings ◽  
Broad Distribution ◽  
Phone Calls ◽  
Dynamical Features ◽  
Twitter Users ◽  
American Physical

AbstractThe interactions among human beings represent the backbone of our societies. How people establish new connections and allocate their social interactions among them can reveal a lot of our social organisation. We leverage on a recent mathematical formalisation of the Adjacent Possible space to propose a microscopic model accounting for the growth and dynamics of social networks. At the individual’s level, our model correctly reproduces the rate at which people acquire new acquaintances as well as how they allocate their interactions among existing edges. On the macroscopic side, the model reproduces the key topological and dynamical features of social networks: the broad distribution of degree and activities, the average clustering coefficient and the community structure. The theory is born out in three diverse real-world social networks: the network of mentions between Twitter users, the network of co-authorship of the American Physical Society journals, and a mobile-phone-calls network.

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