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)     

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.

     

Estimation of rare and clustered population variance in adaptive cluster sampling

Abstract

Many researchers used auxiliary information together with survey variable to improve the efficiency of population parameters like mean, variance, total and proportion. Ratio and regression estimation are the most commonly used methods that utilized auxiliary information in different ways to get the maximum benefits in the form of high precision of the estimators. Thompson first introduced the concept of Adaptive cluster sampling, which is an appropriate technique for collecting the samples from rare and clustered populations. In this article, a generalized exponential type estimator is proposed and its properties have been studied for the estimation of rare and highly clustered population variance using single auxiliary information. A numerical study is carried out on a real and artificial population to judge the performance of the proposed estimator over the competing estimators. It is shown that the proposed generalized exponential type estimator is more efficient than the adaptive and non adaptive estimators under conventional sampling design.     

A comparative study of health delivery systems of India and China

The medical systems which most of the developing countries have, are ad hoc adoptions inherited from their colonial masters and have met with little success in making health planning as part of their national planning. Very few countries have been able to overcome the resistance of the medical profession and the bureaucratic inertia which is a major obstacle in the transformation of this system to a broad based social service and integrating it with the process of socio-economic development planning. The adoption of this system by developing countries is a typical example of technological misfit. A cheap and labour intensive model for developing countries shall be a proper solution for the development of a health care delivery system for the masses. A solution to this problem is a mix or hybrid of the traditional and modern medicines which very recently have been exploited both in India and China. How far India and China have been successful and what is needed to be done is the subject matter of this paper.     

Differential community and the perception of urban green spaces and their contents in the megacity of Karachi, Pakistan

Urban green spaces (UGS) denote the chief representative of biodiversity and provider of ecosystem services (especially social and cultural) in urban landscapes. Socio-economic circumstances of individuals are significantly derived from their psychometric settings–which ultimately affect their preferences in urban landscapes–more so for multicultural and multifaceted social environments. This paper investigates the coupling of distinct socio-economic (life quality) standards and urban natural spaces (and their content) in the megacity of Karachi, Pakistan. The main research question was how the socio-economic conditions of the differentiated and multicultural community influence their preferences of urban green spaces. It was tested at three systematically selected research sites of distinct structural and functional characteristics but the results and discussion are presented in an integrative form. The study sites were selected using Karachi’s urban-rural gradient to deduce representative samples from different land use and urbanization zones. Public interviews of 340 respondents were conducted with a structured questionnaire. The findings contradict generalizations made in other international studies. Results show that the presumption of tightly coupled social settings and nature space preferences could not be validated empirically for varying types of cities in the world. This is because people perceive their heterogeneous natural and artificial environment differently in different regional settings. The multicultural environment dissembles the choices of people and vice versa. This is true regardless of the sampling strategy for such studies that had been the focus in the past. Community revitalization is deemed necessary for better design, facilities and functions of UGS to foster social wellbeing of residents as well as sustainable urban development.     

Impact of demographic variables on women’s economic empowerment: An ordered probit model

The present study aimed to empirically examine the demographic variables that determine women’s economic empowerment. A sample of 500 married women between 21 and 49 years old (M_age = 35.49, SD = 7.66) was conveniently selected from district Multan (Pakistan). Control over economic resources was used as a proxy for women’s economic empowerment. Ordered probit regression was run to assess the demographic determinants (i.e., age, education, paid job, income, and property) of economic empowerment of the least empowered, moderately empowered, and highly empowered women. Paid job, age, income, and property appeared as positive and significant predictors of women’s economic empowerment. Implications of the study were also discussed.