scholarly journals EXAMINING THE IMPACT OF ETF INVESTMENTS ON DIFFERENT CHARACTERISTICS OF THE UNDERLYING STOCKS IN THE US

2021 ◽  
Vol 21 (1) ◽  
pp. 49-69
Author(s):  
Dinakar Prabhu ◽  
Rishabh Soni ◽  
Mridul Mishra ◽  
Sankarshan Basu
2018 ◽  
Vol 43 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Carina Van Rooyen ◽  
Ruth Stewart ◽  
Thea De Wet

Big international development donors such as the UK’s Department for International Development and USAID have recently started using systematic review as a methodology to assess the effectiveness of various development interventions to help them decide what is the ‘best’ intervention to spend money on. Such an approach to evidence-based decision-making has long been practiced in the health sector in the US, UK, and elsewhere but it is relatively new in the development field. In this article we use the case of a systematic review of the impact of microfinance on the poor in sub-Saharan African to indicate how systematic review as a methodology can be used to assess the impact of specific development interventions.


Author(s):  
Aref Emamian

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States


Author(s):  
Kumari Anshu ◽  
Loveleen Gaur ◽  
Arun Solanki

Chatbot has emerged as a significant resolution to the swiftly growing customer caredemands in recent times. Chatbot has emerged as one of the biggest technological disruption. Simply speaking, it is a software agent facilitating interaction between computers and humans in natural language. So basically, it is a simulated, intellectual dialogue agent functional in a range of consumer engagement circumstances. It is the easiest and simplest means enable interaction between the retailers and the customers. </p><p> • Purpose- Most of the research work done in this field is concerned with their technical aspects. The recent research on chatbot pay little attention to the impact it is creating on users’ experience. Through this work, author is making an effort to know the customer-oriented impact that the chatbot bear on the shoppers. The purpose of this study is to develop and empirically test a framework that identify the customer oriented attributes of chatbot and impact of these attributes on customers. </p><p> • Objectives- The study intends to bridge the gap between concepts and actual attributes and applications on the subject of Chatbot. The following research objectives can address the various aspects of Chatbot affecting the different characteristics of consumers shopping behaviors: a) Identify the various attributes of chatbot that bears an impression on consumer shopping behavior. b) Evaluate the impact of chatbot on consumer shopping behavior that leads to the development of chatbot usage and adoption among the customer. </p><p> • Design/Methodology/Approach – For the purpose of analysis, author has administered Factor analysis and Multiple regression using SPSS version 23 for identification of various attributes of Chatbot and knowing their impact on shoppers. A self-administered questionnaire from the review of literature is developed. Industry experts in the field of retailing and academician evaluate the questionnaire. Primary information from the respondents is gathered using this questionnaire. The questionnaire comprises of Likert scale on a scale of 1 to 5 where 1 stands for strongly disagree and 5 stands for strongly agree. Data is collected from 126 respondents, out of which 111 respondents were finally considered for study and analysis purpose. </p><p> • Findings – The empirical results show that the study identifies various attributes of chatbot like Trust, Usefulness, Satisfaction, Readiness to Use and Accessibility. It is also found that chatbot is really influencing the customers in providing them with shopping experience, which can be very helpful to the businesses for increasing the sales and creating repurchase intention among the customers. </p><p> • Originality/value – The recent research on chatbot pay little attention to the impact it is creating on customers who are actually interacting with it on regular basis. The research paper extends information for understanding and appreciating the customer oriented attributes of artificially intelligent Chatbot. In this regard, the author has developed a model framework and proposed the attributes identified. Through the work, author is also making an effort to test empirically the impact of the identified attributes on the shoppers.


Author(s):  
Asfandyar Mir ◽  
Dylan Moore

Abstract We investigate the impact of the US drone program in Pakistan on insurgent violence. Using details about US-Pakistan counterterrorism cooperation and geocoded violence data, we show that the program was associated with monthly reductions of around nine to thirteen insurgent attacks and fifty-one to eighty-six casualties in the area affected by the program. This change was sizable, as in the year before the program, the affected area experienced around twenty-one attacks and one hundred casualties per month. Additional quantitative and qualitative evidence suggests that this drop is attributable to the drone program. However, the damage caused in strikes during the program cannot fully account for the reduction. Instead, anticipatory effects induced by the program played a prominent role in subduing violence. These effects stemmed from the insurgents’ perception of the risk of being targeted in drone strikes; their efforts to avoid targeting severely compromised their movement and communication abilities, in addition to eroding within-group trust. These findings contrast with prominent perspectives on air-power, counterinsurgency, and US counterterrorism, suggesting select drone deployments can be an effective tool of counterinsurgency and counterterrorism.


Horticulturae ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 82
Author(s):  
Amandeep Kaur ◽  
Louise Ferguson ◽  
Niels Maness ◽  
Becky Carroll ◽  
William Reid ◽  
...  

Pecan is native to the United States. The US is the world’s largest pecan producer with an average yearly production of 250 to 300 million pounds; 80 percent of the world’s supply. Georgia, New Mexico, Texas, Arizona, Oklahoma, California, Louisiana, and Florida are the major US pecan producing states. Pecan trees frequently suffer from spring freeze at bud break and bloom as the buds are quite sensitive to freeze damage. This leads to poor flower and nut production. This review focuses on the impact of spring freeze during bud differentiation and flower development. Spring freeze kills the primary terminal buds, the pecan tree has a second chance for growth and flowering through secondary buds. Unfortunately, secondary buds have less bloom potential than primary buds and nut yield is reduced. Spring freeze damage depends on severity of the freeze, bud growth stage, cultivar type and tree age, tree height and tree vigor. This review discusses the impact of temperature on structure and function of male and female reproductive organs. It also summarizes carbohydrate relations as another factor that may play an important role in spring growth and transition of primary and secondary buds to flowers.


2009 ◽  
Vol 24 (4) ◽  
pp. 214-222 ◽  
Author(s):  
Jeffrey D. Kline ◽  
Alissa Moses ◽  
David Azuma ◽  
Andrew Gray

Abstract Forestry professionals are concerned about how forestlands are affected by residential and other development. To address those concerns, researchers must find appropriate data with which to describe and evaluate rates and patterns of forestland development and the impact of development on the management of remaining forestlands. We examine land use data gathered from Landsat imagery for western Washington and evaluate its usefulness for characterizing low-density development of forestland. We evaluate the accuracy of the satellite imagery‐based land use classifications by comparing them with other data from US Forest Service's Forest Inventory and Analysis inventories and the US census. We then use the data to estimate an econometric model describing development as a function of socioeconomic and topographic factors and project future rates of development and forestland loss to 2020. We conclude by discussing how best to meet the land use data needs of researchers, forestry policymakers, and managers.


Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.


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