Robust inference for predictability in smooth transition predictive regressions

This article provides a novel test for predictability within a nonlinear smooth transition predictive regression (STPR) model where inference is complicated due not only to the presence of persistent, local to unit root, predictors, and endogeneity but also the presence of unidentified parameters under the null of no predictability. In order to circumvent the unidentified parameters problem, t? statistic for the predictor in the STPR model is optimized over the Cartesian product of the spaces for the transition and threshold parameters; and to address the di?culties due to persistent and endogenous predictors, the instrumental variable (IVX) method originally developed in the linear cointegration testing framework is adopted within the STPR model. Limit distribution of this statistic (i.e., sup?t^IVX test) is shown to be nuisance parameter-free and robust to the local to unit root and endogenous regressors. Simulations show that sup?t^IVX has good size and power properties. An application to stock return predictability reveals presence of asymmetric regime-dependence and variability in the strength and size of predictability across asset-related (e.g., dividend/price ratio) vs. other (e.g., default yield spread) predictors.     

Risk-taking behavior and academic self-efficacy as variables accounting for problematic internet use in adolescent university students

Objective

This study investigated the relationship between risk-taking behavior and academic self-efficacy and problematic internet use in adolescent university students and whether problematic internet use varies according to the variables of gender, possession of a computer and living with the family.

Methods

The study was performed with 556 students from the Karadeniz Technical University Fatih Faculty of Education in Turkey. The Problematic Internet Use Scale, the Adolescent Risk-Taking Questionnaire, the Academic Self-Efficacy Scale and Personal Information Collection Form were used in the collection of data.

Results

Pearson correlation analysis revealed a significant positive correlation between problematic internet use and risk-taking behavior (r = .37, p < .01) and a significant negative correlation between problematic internet use and academic self-efficacy (r = − .12, p < .05). Multiple regression analysis revealed that risk-taking behavior and academic self-efficacy accounted for 14% of total problematic internet use variance (F_(2,553) = 46.11, p < .05). The individual contribution to the model of risk-taking (β = .37) and academic self-efficacy (β = − .09) is significant. Our results also showed that university adolescents' problematic internet use scores vary by gender (t = − 4.90, p < .05) and possession or otherwise of a computer (t = 3.10, p < .05), but not on the basis of whether they live with their families (t = − .13, p > .05).

Conclusions

Risk-taking behavior and academic self-efficacy emerged as significant predictors of problematic internet use.     

Testing for a unit root in a stationary ESTAR process

This article develops a statistic for testing the null of a linear unit root process against the alternative of a stationary exponential smooth transition autoregressive model. The asymptotic distribution of the test is shown to be nonstandard but nuisance parameter-free and hence critical values are obtained by simulations. Simulations show that the proposed statistic has considerable power under various data generating scenarios. Applications to real exchange rates also illustrate the ability of our test to reject null of unit root when some of the alternative tests do not.     

A transnational practice between fractured homes: Second-generation Turkish–German migrants’ experiences of visiting and being visited

The paper explores the multiple ways in which visits affect the understanding of home for the Turkish–German second generation who have relocated to Turkey. Based on thematic–narrative analysis of 116 life-story interviews with second-generation ‘returnees’ in five regions of Turkey, three types of visits are identified: (i) family visits to Turkey whilst growing up in Germany; (ii) visits to Germany after the second generation has ‘returned’ to Turkey; (iii) visits to Turkey by the second generation's Germany-residing relatives and friends. Each type has different meanings for the visitors and the visited, creating fluid reflections on the meaning of home, which, especially for the second-generation ‘returnees’, tends to become fractured. Constantly comparing their two home(-land)s since childhood, they often simultaneously feel both ‘here’ and ‘there’ as a result of changing attachments and a mix of positive and negative experiences in both locales with their families, friends and the dominant others.     

An ant colony optimization approach for the proportionate multiprocessor open shop

Multiprocessor open shop makes a generalization to classical open shop by allowing parallel machines for the same task. Scheduling of this shop environment to minimize the makespan is a strongly NP-Hard problem. Despite its wide application areas in industry, the research in the field is still limited. In this paper, the proportionate case is considered where a task requires a fixed processing time independent of the job identity. A novel highly efficient solution representation is developed for the problem. An ant colony optimization model based on this representation is proposed with makespan minimization objective. It carries out a random exploration of the solution space and allows to search for good solution characteristics in a less time-consuming way. The algorithm performs full exploitation of search knowledge, and it successfully incorporates problem knowledge. To increase solution quality, a local exploration approach analogous to a local search, is further employed on the solution constructed. The proposed algorithm is tested over 100 benchmark instances from the literature. It outperforms the current state-of-the-art algorithm both in terms of solution quality and computational time.

     

Exploring the co-movements between COVID-19 pandemic and international air traffic: A global perspective based on wavelet analysis

The travel and tourism industry was one of the fastest-growing industries before the onset of the COVID-19 pandemic. However, to avoid COVID-19 spread, the government authorities imposed strict lockdown and international border restrictions except for some emergency international flights that badly hit the travel and tourism industry. The study explores the nexus between international air departures and the COVID-19 pandemic in this strain. We use a novel wavelet coherence approach to dissect the lead and lag relationships between international flight departures and COVID-19 deaths from January 2020 to September 2020 (COVID-19 first wave period). The results reveal that international flights cause the spread of COVID-19 spread during May 2020 to June 2020 worldwide. The overall findings suggest asymmetries between daily international flight departures and COVID-19 deaths globally at different time-frequency periods due to uncertainty surrounding the COVID-19 pandemic. The study will be conducive for the policymakers to control the upsurge of COVID-19 spread worldwide.