Marketed tax avoidance: an economic analysis Li, Jiao; Gamannossi degl'Innocenti, Duccio; Rablen, Matthew D.
The Scandinavian journal of economics,
July 2023, Volume:
125, Issue:
3
Journal Article
Peer reviewed
Open access
Recent years have witnessed the growth of mass‐marketed tax avoidance schemes aimed at the middle (not top) of the income distribution, with significant implications for tax revenue. We examine the ...consequences for the structure of income tax, and for tax authority anti‐avoidance efforts, of tax avoidance of this type. In a model that allows for both demand‐ and supply‐side considerations, we find that: there is an endogenous threshold income below which taxpayers do not avoid, and above which they avoid maximally; the per‐dollar price of tax avoidance is decreasing in income under progressive taxation; endogenous adjustments in the price of avoidance make supply less responsive to anti‐avoidance activity than thought previously; and avoidance may drive a non‐monotone relationship between tax rates and tax revenue. These findings suggest that new approaches to anti‐avoidance, beyond legal enforcement, might be needed.
This paper presents an efficient 3D collision avoidance algorithm for fixed wing Unmanned Aerial Systems (UAS). The algorithm increases the ability of aircraft operations to complete mission goals by ...enabling fast collision avoidance of multiple obstacles. The new algorithm, which we have named Fast Geometric Avoidance algorithm (FGA), combines geometric avoidance of obstacles and selection of a critical avoidance start time based on kinematic considerations, collision likelihood, and navigation constraints. In comparison to a current way-point generation method, FGA showed a 90
%
of reduction in computational time for the same obstacle avoidance scenario. Using this algorithm, the UAS is able to avoid static and dynamic obstacles while still being able to recover its original trajectory after successful collision avoidance. Simulations for different mission scenarios show that this method is much more efficient at avoiding multiple obstacles than previous methods. Algorithm effectiveness validation is provided with Monte Carlo simulations and flight missions in an aircraft simulator. FGA was also tested on a fixed-wing aircraft with successful results. Because this algorithm does not have specific requirements on the sensor data types it can be applied to cooperative and non-cooperative intruders.
The experience of justice is a dynamic phenomenon that changes over time, yet few studies have directly examined justice change. In this article, we integrate theories of self-regulation and group ...engagement to derive predictions about the consequences of justice change. We posit that justice change is an important factor because, as suggested by self-regulation theory, people are particularly sensitive to change. Also consistent with self-regulation, we posit that experiencing justice change will influence behavior via separate approach and avoidance systems. Across three multiwave and multisource field studies, we found that justice change predicts employees' engagement in work via perceived insider status along an approach path, whereas it predicts employees' withdrawal from work via exhaustion along an avoidance path, after controlling for the effects of static justice level. Moreover, these approach and avoidance effects are bounded by employees' perception of their employment situation, consistent with a regulatory fit pattern. As expected, employees' perceptions of employment opportunity, which correspond to gains, strengthen the effects along the approach path. Meanwhile, their perceptions of threat of job continuity, which correspond to losses, strengthen the effects along the avoidance path. Importantly, our set of studies highlight the unique influence of justice change incremental to static justice level.
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Abstract Background context Psychological factors including fear avoidance beliefs are believed to influence the development of chronic low back pain (LBP). Purpose The purpose of this study was to ...determine the prognostic importance of fear avoidance beliefs as assessed by the Fear Avoidance Beliefs Questionnaire (FABQ) and the Tampa Scale of Kinesiophobia for clinically relevant outcomes in patients with nonspecific LBP. Design/setting The design of this study was a systematic review. Methods In October 2011, the following databases were searched: BIOSIS, CINAHL, Cochrane Library, Embase, OTSeeker, PeDRO, PsycInfo, PubMed/Medline, Scopus, and Web of Science. To ensure the completeness of the search, a hand search and a search of bibliographies was conducted and all relevant references included. A total of 2,031 references were retrieved, leaving 566 references after the removal of duplicates. For 53 references, the full-text was assessed and, finally, 21 studies were included in the analysis. Results The most convincing evidence was found supporting fear avoidance beliefs to be a prognostic factor for work-related outcomes in patients with subacute LBP (ie, 4 weeks–3 months of LBP). Four cohort studies, conducted by disability insurance companies in the United States, Canada, and Belgium, included 258 to 1,068 patients mostly with nonspecific LBP. These researchers found an increased risk for work-related outcomes (not returning to work, sick days) with elevated FABQ scores. The odds ratio (OR) ranged from 1.05 (95% confidence interval CI 1.02–1.09) to 4.64 (95% CI, 1.57–13.71). The highest OR was found when applying a high cutoff for FABQ Work subscale scores. This may indicate that the use of cutoff values increases the likelihood of positive findings. This issue requires further study. Fear avoidance beliefs in very acute LBP (<2 weeks) and chronic LBP (>3 months) was mostly not predictive. Conclusions Evidence suggests that fear avoidance beliefs are prognostic for poor outcome in subacute LBP, and thus early treatment, including interventions to reduce fear avoidance beliefs, may avoid delayed recovery and chronicity.
Avoidance is a well-documented risk factor for poor mental and physical health outcomes. However, limited research has explored this relationship specifically among trauma-exposed veterans, a ...population known to be particularly prone to avoidance behavior. Conceptually, avoidance is often divided into two distinct but overlapping constructs - experiential avoidance (resisting distressing internal states) and behavioral avoidance (avoiding or changing experiences that elicit distress). In this exploratory survey study, we examined associations between behavioral and experiential avoidance and mental, physical, and cognitive functioning, as well as quality of life.INTRODUCTIONAvoidance is a well-documented risk factor for poor mental and physical health outcomes. However, limited research has explored this relationship specifically among trauma-exposed veterans, a population known to be particularly prone to avoidance behavior. Conceptually, avoidance is often divided into two distinct but overlapping constructs - experiential avoidance (resisting distressing internal states) and behavioral avoidance (avoiding or changing experiences that elicit distress). In this exploratory survey study, we examined associations between behavioral and experiential avoidance and mental, physical, and cognitive functioning, as well as quality of life.Veterans with a trauma history (N = 89) completed a 121-item survey containing validated assessments to examine several mental and physical health and wellness-related variables. Correlations between experiential avoidance and outcome measures, and behavioral avoidance and outcome measures, were explored. Multivariable linear regression analyses were conducted to explore the association between experiential and behavioral avoidance on mental health outcomes. In addition, we conducted exploratory analyses in which we investigated these correlations in those who screened positive for PTSD versus those who did not, and between different types of behavioral avoidance and major outcomes.METHODSVeterans with a trauma history (N = 89) completed a 121-item survey containing validated assessments to examine several mental and physical health and wellness-related variables. Correlations between experiential avoidance and outcome measures, and behavioral avoidance and outcome measures, were explored. Multivariable linear regression analyses were conducted to explore the association between experiential and behavioral avoidance on mental health outcomes. In addition, we conducted exploratory analyses in which we investigated these correlations in those who screened positive for PTSD versus those who did not, and between different types of behavioral avoidance and major outcomes.Experiential avoidance was moderately correlated with distress from depressive symptoms, distress related to past trauma, and health-related and cognitive dysfunction. Experiential Avoidance was weakly correlated with distress from anxiety symptoms and poorer quality of life. Behavioral avoidance was moderately correlated with distress from depressive and anxiety symptoms, distress related to past trauma, and cognitive dysfunction, and was weakly correlated with health-related dysfunction and poorer quality of life. Results from multivariable analyses revealed that experiential avoidance was associated with greater distress related to depressive symptoms and past trauma, and behavioral avoidance was associated with greater distress related to anxiety symptoms, depressive symptoms, and past trauma.RESULTSExperiential avoidance was moderately correlated with distress from depressive symptoms, distress related to past trauma, and health-related and cognitive dysfunction. Experiential Avoidance was weakly correlated with distress from anxiety symptoms and poorer quality of life. Behavioral avoidance was moderately correlated with distress from depressive and anxiety symptoms, distress related to past trauma, and cognitive dysfunction, and was weakly correlated with health-related dysfunction and poorer quality of life. Results from multivariable analyses revealed that experiential avoidance was associated with greater distress related to depressive symptoms and past trauma, and behavioral avoidance was associated with greater distress related to anxiety symptoms, depressive symptoms, and past trauma.Results suggest that avoidance negatively influences major domains of mental and physical health as well as functioning and health-related quality of life in trauma-exposed veterans. They further indicate that behavioral and experiential avoidance may be differentially linked to mental health outcomes. The results support the idea that avoidance may be an important marker for psychosocial functioning and may serve as a treatment target in trauma-exposed veterans.CONCLUSIONSResults suggest that avoidance negatively influences major domains of mental and physical health as well as functioning and health-related quality of life in trauma-exposed veterans. They further indicate that behavioral and experiential avoidance may be differentially linked to mental health outcomes. The results support the idea that avoidance may be an important marker for psychosocial functioning and may serve as a treatment target in trauma-exposed veterans.
•The present study Mapping online hate.•Symbolic avoidance is a significant predictor of App hate.•Relationship quality Avoidance is a significant predictor of App hate.•Moral Avoidance is a ...significant predictor of App hate.•App hate is negatively related with negative word of mouth and App switching Behavior.
According to Lee’s emergent brand avoidance theoretical framework and self-congruity theory, this research conceptualizes and examines the application (App) hate framework. Data are collected from Chinese smartphone users who provided the possible reasons for hating a specific App. This study first validates Lee’s brand avoidance framework in relation to App hate. The empirical investigation certifies that four key determinants, namely, symbolic, relationship quality, moral, and deficit-value avoidance, are responsible for App hate among online users. Moreover, findings show that App hate is positively and significantly related to negative word of mouth and switching App behavior. This study also discusses the theoretical and managerial implications of Apps.
We examined tracking accuracy and bias (mean-level and projection) in people's perceptions of their romantic partner's relationship approach and avoidance motives, similarity in partners' motives, ...and positive and negative emotions as potential cues used to make judgments about a partner's daily motives and motives during shared activities. Using data from 2 studies, 1 using daily diaries (N = 2,158 daily reports), the other using reports of shared activities (N = 1,228 activity reports), we found evidence of tracking accuracy and projection across samples; we also found evidence of mean-level bias such that people underperceived their partner's approach (daily) and avoidance motives (daily and in shared activities). Partners had similar daily approach and avoidance motives but were not similar in their motives during shared activities. Further, our studies indicated that emotions often serve as relevant, available, and detectable cues for judging a partner's motives. The results demonstrate that accuracy and bias are both present in judgments of a romantic partner's approach and avoidance motives, and that people often, but not always, use their partner's emotions to make such judgments.
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•This study aims to examine the factors leading to information avoidance behavior on social network sites.•Information irrelevance directly leads to information avoidance behavior.•Social network ...fatigue partially mediates the impact of information overload on information avoidance behavior.•Social network fatigue fully mediates the impact of social overload on information avoidance behavior.•Time pressure strengthens the effect of social network fatigue on information avoidance behavior.
Drawing on the stressor-strain-outcome framework, this study investigates how information irrelevance and overload induce social network fatigue, and the relationship of these variables to users’ information avoidance behavior. It also examines the conditions under which social network fatigue is more likely to be translated into information avoidance behavior. The analysis of data collected from 341 users of WeChat Moments suggests that information irrelevance directly leads to information avoidance behavior, and social media fatigue as a mediator partially mediates the impact of information overload on information avoidance behavior and fully mediates the impact of social overload on information avoidance behavior. Furthermore, time pressure strengthens the effect of social network fatigue on information avoidance behavior. This study fulfills the identified need for an in-depth investigation of actual discontinuous behavior in social network services (SNSs) by investigating information avoidance behavior and its antecedents. The findings provide SNSs providers with guidelines on how to manage users’ behavior so that they remain active users of the SNSs.
•The ship encounter identification model is formed based on AIS historical data.•A two-stage collision avoidance behavior extraction algorithm is constructed to obtain the collision avoidance ...scheme.•A novel path planning method is established by fusion the collision avoidance trajectory in similar scenarios.
AIS data include ship spatial-temporal and motion parameters which can be used to excavate the deep-seated information. In this article, an interpretable knowledge-based decision support method is established to guide the ship to make collision avoidance decisions with good seamanship and ordinary practice of seamen using AIS data. First, AIS data is preprocessed and trajectory reconstructed to restore the ship historical navigation state, and a ship encounter identification model is constructed according to the encounter characteristics; Second, a two-stage collision avoidance behavior extraction algorithm is formed to build a behavior knowledge base, and the scenario similarity model is constructed to measure and match similar scenarios based on ship position, motion tendency and collision risk. Then, the Delaunay Triangulation Network is used to fuse ship trajectories of similar scenario to form the collision avoidance path. Finally, a case study is performed using the real AIS data outside Ningbo-Zhoushan Port waters, China, and the effectiveness of the planned path is verified by setting the head-on and crossing situations and comparison between the planned and real paths. Results indicate that the proposed model can extract the ship collision avoidance behavior accurately, and the planned path can ensure navigation safety.
