The Dynamic Relationship Between Technology Innovation and Human Development in Technologically Advanced Countries: Fresh Insights from Quantiles-on-Quantile Approach

Our study investigates the relationship between technology innovation and human development in technologically advanced countries using data from quarterly observations from the last decade of the twentieth century to the first two decades of the twenty-first century. This objective of this study is to implement Quantile-on-Quantile regression (QQ) technique that as formulated by Sim and Zhou (J Bank Finance 55:1–8, 2015) and the renowned Granger-causality in quantiles as proposed by Troster (Econom Rev 37(8):850–866, 2018) examine the basic relationship between the given quantiles of technology innovation and their effects on the quantiles of human development. Therefore, the outcomes of this study explain the overall interdependence of technology innovation and affect the overall human development index. It is enumerated that the empirical results indicate that a significant positive relationship exists between technology innovation and human development in all selected technologically advanced countries, predominantly in both low and high tails. Moreover, the outcomes of Granger causality quantiles indicate a bi-directional fundamental relationship between these two variables in the dataset of all countries. The outcomes of the observations are extended to the recent findings on these two variables’ nexus and imply a differential impact on the technologically advanced countries. This causality guides us to offer some specific policy recommendations to each group of countries.

     

Rare and clustered population estimation using the adaptive cluster sampling with some robust measures

The use of robust measures helps to increase the precision of the estimators, especially for the estimation of extremely skewed distributions. In this article, a generalized ratio estimator is proposed by using some robust measures with single auxiliary variable under the adaptive cluster sampling (ACS) design. We have incorporated tri-mean (TM), mid-range (MR) and Hodges-Lehman (HL) of the auxiliary variable as robust measures together with some conventional measures. The expressions of bias and mean square error (MSE) of the proposed generalized ratio estimator are derived. Two types of numerical study have been conducted using artificial clustered population and real data application to examine the performance of the proposed estimator over the usual mean per unit estimator under simple random sampling (SRS). Related results of the simulation study show that the proposed estimators provide better estimation results on both real and artificial population over the competing estimators.     

ACADEMIC PROBATION,STUDENT PERFORMANCE,AND STRATEGIC COURSE‐TAKING

We use a regression discontinuity design to study how academic probation affects outcomes and course‐taking behaviors at a large public university in the United States. Consistent with past work, students placed on probation improve their grade point average (GPA) in the subsequent semester. We document that part of this GPA improvement is attributable to strategic course‐taking, and there is significant heterogeneity in these behaviors across race. Non‐minority students placed on probation attempt fewer credits, easier courses, and are more likely to withdraw from courses in the following term. In contrast, underrepresented minorities exhibit few of these behaviors, consistent with past work that suggests black and Hispanic students are less likely to possess helpful institutional knowledge and use available support systems such as academic counseling. (JEL I20, I23)     

Rebates, inventories, and intertemporal price discrimination

We demonstrate that universally redeemed rebates can increase manufacturer profits by reducing the incentives of downstream retailers to hoard inventories when optimal wholesale prices vary predictably over time. By bypassing retailers and making direct contracts with buyers, the manufacturer can increase the variations in effective prices paid by consumers without concomitantly creating larger incentives for retailers to hold inventories. During profitable, high-demand periods, manufacturer revenues are ordinarily constrained by'competition'from retailer inventories, thus limiting profits. However, by selectively offering rebates to consumers while maintaining high wholesale prices, low-demand periods can be accommodated without inducing retailer hoarding.     

Habitat selection by an avian top predator in the tropical megacity of Delhi: human activities and socio-religious practices as prey-facilitating tools

Research in urban ecology is growing rapidly in response to the exponential growth of the urban environment. However, few studies have focused on tropical megacities, and on the interplay between predators’ habitat selection and human socio-economic aspects, which may mediate their resilience and coexistence with humans. We examined mechanisms of breeding habitat selection by a synanthropic raptor, the Black Kite Milvus migrans, in Delhi (India) where kites mainly subsist on: (1) human refuse and its associated prey-fauna, and (2) ritualised feeding of kites, particularly practised by Muslims. We used mixed effects models to test the effect of urban habitat configuration and human practices on habitat selection, site occupancy and breeding success. Kite habitat decisions, territory occupancy and breeding success were tightly enmeshed with human activities: kites preferred areas with high human density, poor waste management and a road configuration that facilitated better access to resources provided by humans, in particular to Muslim colonies that provided ritual subsidies. Furthermore, kites bred at ‘clean’ sites with less human refuse only when close to Muslim colonies, suggesting that the proximity to ritual-feeding sites modulated the suitability of other habitats. Rather than a nuisance to avoid, as previously portrayed, humans were a keenly-targeted foraging resource, which tied a predator’s distribution to human activities, politics, history, socio-economics and urban planning at multiple spatio-temporal scales. Many synurbic species may exploit humans in more subtle and direct ways than was previously assumed, but uncovering them will require greater integration of human socio-cultural estimates in urban ecological research.

     

The Emerging Problems of Alcohol and Substance Abuse in Late Life

Treatment of substance abuse among older adults will become increasingly important as the number of aged Americans increases. The abuse of psychoactive substances is a major contributor to excess morbidity, mortality, and homelessness among persons of all ages and socioeconomic strata regardless of race or ethnicity. Alcohol and tobacco accountfor the majority of substance abuse-related death and disability in the United States; the former through cerebrovascular and hepatic disease, accidents and violence, the latter through chronic pulmonary disease and malignancy. Patterns of substance abuse in late life are substantially different from those observed among younger adults. However, treatment may be less challenging. Effective diagnosis and treatment requires a nonpunitive, supportive, but persistent approach. This means the capacity to collect a substance intake history and the ability to formulate a treatment plan or referral strategy to an addiction specialist or residential treatment setting. It is also important for the practitioner to manage negative feelings toward patients who decline treatment or who are chronic abusers.     

Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements

In this paper, measurements from experiments and results of a finite element analysis (FEA) are combined in order to compute accurate empirical models for the temperature distribution before a thermomechanically coupled forming process. To accomplish this, Design and Analysis of Computer Experiments (DACE) is used to separately compute models for the measurements and the functional output of the FEA. Based on a hierarchical approach, a combined model of the process is computed. In this combined modelling approach, the model for the FEA is corrected by taking into account the systematic deviations from the experimental measurements. The large number of observations based on the functional output hinders the direct computation of the DACE models due to the internal inversion of the correlation matrix. Thus, different techniques for identifying a relevant subset of the observations are proposed. The application of the resulting procedure is presented, and a statistical validation of the empirical models is performed.     

Gesture in Instruction: Evidence from Live and Video Lessons

Previous studies have shown that teachers’ gestures are beneficial for student learning. In this research, we investigate whether teachers’ gestures have comparable effects in face-to-face live instruction and video-based instruction. We provided sixty-three 7–10 year old students with instruction about mathematical equivalence problems (e.g., 3 + 4 + 5 = __ + 5). Students were assigned to one of four experimental conditions in a 2 × 2 factorial design that varied (1) instruction medium (video vs. live), and (2) instruction modality (speech vs. speech + gesture). There was no main effect of medium: The same amount of learning occurred whether instruction was done live or on video. There was a main effect of modality: Speech instruction accompanied by gesture resulted in significantly more learning and transfer than instruction conveyed through speech only. Gesture’s effect on instruction was stronger for video instruction than live instruction. These findings suggest that there may be a limit to gesture’s role in communication that results in student learning.     

Enhanced adaptive CUSUM charts for process mean

A statistical quality control chart is an important tool of the statistical process control, which is widely used to control and monitor a production process. The CUSUM chart is designed to detect a specific shift, provided that the shift size is known in advance. In practice, however, shift sizes are rarely known. It is then customary to use an adaptive CUSUM chart, which can effectively detect a range of shift sizes. In this paper, we enhance the sensitivities of the improved adaptive CUSUM mean charts using an auxiliary-information-based (AIB) mean estimator. The run length performances of the proposed charts are compared with those of the AIB adaptive and non-adaptive CUSUM charts in terms of the average run length (ARL), extra quadratic loss, and integral relative ARL. These run length comparisons reveal that the proposed charts are more sensitive than the existing charts when detecting different kinds of shift in the process mean. An example is given to demonstrate the implementation of existing and proposed charts.