Impact of Indias Export on Indian GDP after Liberalisation

Economic and political policy interventions were reflected on the economic development of the countries with respect to improving economic and social well-being of poor, market productivity and considerable growth rate in GDP. Specifically, in Indian context, these economic decisions have been a considerable influence on inclusive growth of the nation. It is evidence that India embarked on economic reforms in July, 1991, from the effect of a balance of payment crisis. The government initiated economic reforms basically is to provide an environment of sustainable growth and stability. Thereby the LPG (Liberalization, Privatization and Globalization) system has come to the picture for economic progress of the country. Thepresent study investigates the linkage between foreign trade trends of India and its economic development in the light of economic reforms in India since 25 years (1991-2016). The outcomes of the study strongly support that there is a causal relationship between exports to GDP and GDP to exports and also causality between imports to exports in India.

Dynamic Computational Models and Simulations of the Opioid Crisis: A Comprehensive Survey

Opioids have been shown to temporarily reduce the severity of pain when prescribed for medical purposes. However, opioid analgesics can also lead to severe adverse physical and psychological effects or even death through misuse, abuse, short- or long-term addiction, and one-time or recurrent overdose. Dynamic computational models and simulations can offer great potential to interpret the complex interaction of the drivers of the opioid crisis and assess intervention strategies. This study surveys existing studies of dynamic computational models and simulations addressing the opioid crisis and provides an overview of the state-of-the-art of dynamic computational models and simulations of the opioid crisis. This review gives a detailed analysis of existing modeling techniques, model conceptualization and formulation, and the policy interventions they suggest. It also explores the data sources they used and the study population they represented. Based on this analysis, direction and opportunities for future dynamic computational models for addressing the opioid crisis are suggested.

“Are you safe to talk?”: Perspectives of Service Providers on Experiences of Domestic Violence During the COVID-19 Pandemic

This study aimed to better understand the factors driving reported trends in domestic violence during the COVID-19 pandemic, particularly the effect of the pandemic on survivors’ experiences of violence and ability to seek support. We conducted semi-structured qualitative interviews with 32 DV service providers operating in organizations across 24 U.S. cities. The majority of providers described a decrease in contact volume when shelter-in-place orders were first established, which they attributed to safety concerns, competing survival priorities, and miscommunication about what resources were available. For most organizations, this decrease was followed by an increase in contacts after the lifting of shelter-in-place orders, often surpassing typical contact counts from the pre-pandemic period. Providers identified survivors’ ability to return to some aspects of their pre-pandemic lives, increased stress levels, and increased lethality of cases as key factors driving this increase. In addition, providers described several unique challenges faced by DV survivors during the pandemic, such as the use of the virus as an additional tool for control by abusers and an exacerbated lack of social support. These findings provide insight into the lived experiences driving observed trends in DV rates during COVID-19. Understanding the impact of the pandemic on survivors can help to shape public health and policy interventions to better support this vulnerable population during future crises.

A framework for inserting visually-supported inferences into geographical analysis workflow: application to road safety research

Road safety research is a data-rich field with large social impacts. Like in medical research, the ambition is to build knowledge around risk factors that can save lives. Unlike medical research, road safety research generates empirical findings from messy observational datasets. Records of road crashes contain numerous intersecting categorical variables, dominating patterns that are complicated by confounding and, when conditioning on data to make inferences net of this, observed effects that are subject to uncertainty due to diminishing sample sizes. We demonstrate how visual data analysis approaches can inject rigour into exploratory analysis of such datasets. A framework is presented whereby graphics are used to expose, model and evaluate spatial patterns in observational data, as well as protect against false discovery. The framework is supported through an applied data analysis of national crash patterns recorded in STATS19, the main source of road crash information in Great Britain. Our framework moves beyond typical depictions of exploratory data analysis and helps navigate complex data analysis decision spaces typical in modern geographical analysis settings, generating data-driven outputs that support effective policy interventions and public debate.

The temporal and spatial scales of arable land loss and its impact in Guangxi, China: A Commentary

Cropland abandonment because of rural depopulation or policy interventions has become a key issue in Chinese mountainous areas. One such region is the Guangxi Karst Mountainous Area (GKMA), a zone where more than 59% of total land area is hilly and arable land of a commercially viable size is almost non-existent. The rugged terrain and land fragmentation in upland karst areas result in the scarcity of land suitable for cultivation. Although depopulation and declining agriculture since 2000 within the GKMA have led to vast areas of abandoned cropland, the spatiotemporal distribution that underlies this pattern as well as its causes remain little understood. Geomorphic features also bring about differences in the distribution of settlements. Settlements with different degrees of distribution are accompanied by spatial differences in cultivated land resources, which lead to differences in the sufficiency of cultivated land resources. In this paper we provide an overview of the magnitude of the problem of arable land loss. settlements and analyze the spatial distribution and the spatial agglomeration of the cultivated land.

Sensing pedestrian flows for real-time assessment of non-pharmaceutical policy interventions during the COVID-19 pandemic

IntroductionTo combat and mitigate the transmission of the SARS-CoV-2 virus, reducing the number of social contacts within a population is highly effective. Non-pharmaceutical policy interventions, e.g. stay-at-home orders, closing schools, universities, and (non-essential) businesses, are expected to decrease pedestrian flows in public areas, leading to reduced social contacts. The extent to which such interventions show the targeted effect is often measured retrospectively by surveying behavioural changes. Approaches that use data generated through mobile phones are hindered by data confidentiality and privacy regulations and complicated by selection effects. Furthermore, access to such sensitive data is limited. However, a complex pandemic situation requires a fast evaluation of the effectiveness of the introduced interventions aiming to reduce social contacts. Location-based sensor systems installed in cities, providing objective measurements of spatial mobility in the form of pedestrian flows, are suited for such a purpose. These devices record changes in a population’s behaviour in real-time, do not have privacy problems as they do not identify persons, and have no selection problems due to ownership of a device. ObjectiveThis work aimed to analyse location-based sensor measurements of pedestrian flows in 49 metropolitan areas at 100 locations in Germany to study whether such technology is suitable for the real-time assessment of behavioural changes during a phase of several different pandemic-related policy interventions. MethodsSpatial mobility data of pedestrian flows was linked with policy interventions using the date as a unique linkage key. Data was visualised to observe potential changes in pedestrian flows before or after interventions. Furthermore, differences in time series of pedestrian counts between the pandemic and the pre-pandemic year were analysed. ResultsThe sensors detected changes in mobility patterns even before policy interventions were enacted. Compared to the pre-pandemic year, pedestrian counts were 85% lower. ConclusionsThe study illustrated the practical value of sensor-based real-time measurements when linked with non-pharmaceutical policy intervention data. This study’s core contribution is that the sensors detected behavioural changes before enacting or loosening non-pharmaceutical policy interventions. Therefore, such technologies should be considered in the future by policymakers for crisis management and policy evaluation.

Innovation and borrower discouragement in SMEs

In this paper, we investigate whether innovative small- and medium-sized enterprises (SMEs) are more likely to be discouraged from applying for external finance than non-innovators. These so-called discouraged borrowers are credit worthy SMEs who choose not to apply for external finance despite the fact that this is needed. We find that SMEs undertaking pure product and joint product and process innovation have a significantly higher incidence of borrower discouragement than non-innovative counterparts. Moreover, radical and incremental product innovators are more likely to be discouraged relative to non-innovative counterparts. Innovative activity can increase borrower discouragement for a myriad of reasons including fear of rejection, reluctance to take on additional risk, negative perceptions of the funding application process and perceived negative economic conditions. Overall, our results suggest a need for targeted policy interventions in order to alleviate borrower discouragement within innovative SMEs, as well as a closer alignment between innovation and SME finance policy.

Bullying Victims in Rural Primary Schools: Prevalence, Correlates, and Consequences

School bullying is a widely recognized problem in developed countries, but remains under-investigated in developing countries, especially in remote rural areas. In this paper, we examine the prevalence, correlates, and consequences of bullying victimization and its relation to educational performance and creative attitudes. Using data from 10,528 students across 120 primary schools in rural China, we find an alarmingly high prevalence of bullying victimization and that several individual, family, and school characteristics are correlated with bullying victimization. Analyses indicate students who are bullied frequently score lower in Chinese, reading, and math tests and creative attitudes. Taken together, the results demonstrate a need for further research and policy interventions to reduce bullying in schools.