The University of Buckingham Press Journals
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The Role of the University of Buckingham's Public Health Society in being Socially Accountable: Raising awareness on public health issues, supporting local authorities in addressing health inequalities and exploring COVID-19 vaccine hesitancy amongst vulnerable groups.
Get PDFSee Letter to the Editor attached above
Exchange rate policy, structural breaks, and predictability of sugarcane prices
No full textSugarcane price uncertainty has been a contentious issue in Fiji’s sugar industry for the past few decades. We study the predictability of sugarcane prices by examining time-series properties of the historical prices data over the sample period 1975 to 2019 allowing for structural breaks. We employ the unit root test of Zivot-Andrews (1992) and the structural break test of Bai and Perron (1998) and find robust evidence that sugarcane prices are characterized as stationary (mean-reverting) processes with structural breaks occurring in 1986 and 2011. The estimated break dates coincide with exchange rate policy decisions such as the devaluation of the Fijian dollar by the Reserve Bank of Fiji. Our findings provide new insights that given concerns of price uncertainty in Fiji's sugar industry, historical data is useful for forecasting sugarcane prices, implying that sugarcane prices, in fact, are predictable. The results also reveal that shocks only have transitory effects on sugarcane prices, and devaluation is an important source of shock to sugarcane prices
Does the Value-at-Risk legal framework lead to inaccurate and procyclical risk estimations? Empirical Evidence from the EU countries.
No full textThis analysis tests whether the quantitative requirements of the law (Basel and Committee of European Securities Regulators) regarding the Value at Risk (VaR) framework may lead to inaccurate and procyclical VaR estimations. We apply two of the most popular VaR models, the Historical (HVaR) and the Exponential Weighted Moving Average (EWMA VaR) models, to a wide sample of 13 European Indices during the period 2002-2019. The empirical evidence confirms our assumptions that the legal framework in many cases leads to inaccurate and procyclical VaR estimations. Moreover, we show that the limitation on the required data inputs does not really contribute to a more stable financial environment. Further, we show that the current framework does not examine the procyclicality issue. The evidence in this study shows that the current legal framework needs some reforms: (a) the guideline on the minimum number of data inputs for the VaR estimations should be removed, taking provided that the accuracy of the applied VaR model is often evaluated, and (b) the current backtesting procedure does not examine whether VaR estimations are representative of the financial conditions. An additional backtesting procedure at a lower that the 99% confidence level could resolve this issue
On the Dynamic Relationship between the Housing Market, Stock Market, and Macroeconomic Variables in Hong Kong
Get PDFThe relationship between the housing market, stock market, and macroeconomic variables has long been a topic of concern to both academics and practitioners. This paper examines the short-run dynamics and long-run relationships between the residential property price index and the stock market index and four selected macroeconomic variables in Hong Kong. The Johansen (1991) cointegration approach and the Vector Error Correction Model (VECM) approach are used to examine the monthly time series during the sample period from 2004 to 2019. Our results show that there is a cointegration relationship between the residential property price index and the stock market index and selected macroeconomic variables. There is evidence that the Hang Seng index, money supply (M3), total loans, and unemployment rate are significantly associated with the residential property price index, while the consumer price index has no significant impact on the residential property price index in the short-run dynamics. Also, only the Hang Seng index and two macroeconomic variables have a long-run cointegration relationship with the housing market. This is the first attempt to shed light on both short-run and long-run relationships between two capital markets and macroeconomic variables in the context of Hong Kong. Our findings provide important implications for relevant government departments to stabilise the housing market and help practitioners form effective investment strategies
Understanding the Professional Learning of Beginning Teachers: Maximising Learning in a Context of Systemic Contraints
Get PDFThis article considers the processes involved in the professional learning of beginning teachers in England. In discussing the processes involved, this article considers the nature of professional knowledge needed to be learned by beginning teachers and the processes by which they may learn. Representing beginning teacher learning is framed in terms of a learning trajectory in contrast to the Teachers’ Standards (DfE, 2011) which describe a restrictive and technicist perspective. This draws from the novice / expert discourse but with the understanding that while there are a number of typical features in a beginning teacher’s development (Burn, Hagger, & Mutton, 2014) there is variation between individuals. Finally, implications are drawn for those involved in the training of beginning teachers
Early Days of the Department of Education at the University of Buckingham: A Personal View
Get PDFEarly Days of the Department of Education at the University of Buckingham: A Personal Vie
Exploring medical students’ understanding of non-technical skills: a thematic analysis: Exploring medical students’ understanding of NTS
No full textIntroduction
Non-technical skills (NTS) are a developing area of clinical education, partly due to the recognition that poor NTS can contribute to adverse patient events. Simulation is an appropriate teaching environment to consider these skills. Post-scenario discussions often focus on specific NTS, but these may not necessarily be what the participants think of when considering NTS. The aim of this study was therefore to analyse what one group of healthcare professionals, medical students, focused on when observing the NTS of their colleagues in simulated clinical scenarios.
Method
Medical students from two English universities were asked to observe simulated acute medicine scenarios. They were instructed to document their observations on written worksheets focusing on specific NTS comprising communication, teamwork, task management, decision making, situational awareness and, for the last scenario, a general worksheet asking the students to consider all the NTS discussed so far. These worksheets were then transcribed and analysed using thematic analysis to elicit themes that best outlined the students’ perceptions.
Results
Five themes were discovered from analysis of the five NTS from all six worksheets: team dynamics, team communication, awareness of self and events, coping under pressure and misinterpretation of NTS. These themes showed a difference between what the students concentrated on compared to what they were asked to consider. Analysis of these themes gave us an initial understanding of the prior knowledge and assumptions medical students bring with them to discussions on NTS.
Conclusions
Understanding prior assumptions and interpretations of NTS can better help us understand how to teach the skills effectively and build upon what our students consider important, to help construct new knowledge and skills. As analyses of adverse events in clinical practice often point to errors of NTS as causative factors, improving these skills is an essential aspect of clinical education
Prediction for the 2020 United States Presidential Election Using Machine Learning Algorithm: Lasso Regression
No full textThis paper aims at determining the various economic and non-economic factors that can influence the voting behaviour in the forthcoming United States Presidential Election using Lasso regression, a Machine learning algorithm. Even though contemporary discussions on the subject of the United States Presidential Election suggest that the level of unemployment in the economy will be a significant factor in determining the result of the election, in our study, it has been found that the rate of unemployment will not be the only significant factor in forecasting the election. However, various other economic factors such as the inflation rate, rate of economic growth, and exchange rates will not have a significant influence on the election result. The June Gallup Rating, is not the only significant factor for determining the result of the forthcoming presidential election. In addition to the June Gallup Rating, various other non-economic factors such as the performance of the contesting political parties in the midterm elections, Campaign spending by the contesting parties and scandals of the Incumbent President will also play a significant role in determining the result of the forthcoming United States Presidential Election. The paper explores the influence of all the aforementioned economic and non-economic factors on the voting behaviour of the voters in the forthcoming United States Presidential Election.
The proposed Lasso Regression model forecasts that the vote share for the incumbent Republican Party to be 41.63% in the 2020 US presidential election. This means that the incumbent party is most likely to lose the upcoming election
COVID-19 and Cryptocurrency Market: Impact on Return, Volatility and Liquidity
No full textIn this study, we examine the impact of COVID-19 pandemic on the return, volatility and liquidity of the cryptocurrencies using panel data analysis. We consider the four variables related to the COVID-19 pandemic: (i) percentage change in total confirmed cases, (ii) percentage change in total recovered cases, (iii) percentage change in total death cases, and (iv) the investor’s attention towards the COVID-19 pandemic. The findings indicate that percentage change in recovered cases and investor attention towards COVID-19 have a significant positive impact on returns of cryptocurrencies. The volatility in cryptocurrencies is negatively influenced by the percentage change in recovered cases. Moreover, the percentage change in recovered cases has a significant negative impact and investor attention towards COVID-19 has a significant positive impact on the liquidity of cryptocurrencies.