A Review on the Leading Indicator Approach towards Economic Forecasting

Economic cycle is defined as the fluctuation of an economy via expansion and contraction periods, influenced by varies kinds of macroeconomic indicators. The repeatable movement of economic indicators enables the accurate detection of these cycles with a forecasting approach that aims to improve economic development, especially by specific industries. Thus, economists and researchers have focused on the usefulness of the composite leading indicator in economic forecasting. It is regarded as a good illustration of an economic cycle or trend. This is due to its ease of use during the interpretation process, as several indicators can be aggregated and explained at once. This may provide useful insights for policy planning, risk monitoring and community development using the information gained from macroeconomic aggregates

Evaluation of the partnership histories in the Centre for Population Change GHS time series dataset

A combined time series of the General Household Survey datasets from 1979 to 2007 has been compiled by the Centre for Population Change (CPC). This dataset includes, along with socio-economic variables, the demographic histories collected in the Family Information section of the GHS questionnaire over the GHS rounds covered, in harmonised form. The present paper evaluates both the internal consistency of the marriage and cohabitation histories and their correspondence with external sources.The data are weighted using new weights generated by CPC for the analysis of these data. Overall, cumulative proportions married by each age for the cohorts of 1951-55 to 1966-70 correspond well with ONS figures for England and Wales, though there are some systematic disparities in selected years. As found in an earlier study, retrospective estimates from the 2000-07 histories of the proportions cohabiting at a point in time are somewhat above the cross-sectional estimates at survey 5 and 10years before

Responsible Recovery from COVID-19: An Empirical Overview of Tourism Industry

Over the past few decades, the world has seen a stunning transformation of the tourism industry. The tourism industry is one of the world's largest and fastest growing economic sectors. Thus, it is one of the key economic drivers in most developed and developing countries. Despite the rapid growth of the tourism industry, it is considered a vulnerable industry because it must accommodate the demand changes of tourists, shifts in economic environmental and other unexpected factors such as natural disasters and crises, especially the recent COVID-19 pandemic. Therefore, this paper aims to review the key determinants affecting tourism demand. In general, the tourist arrivals and tourism receipts have been chosen to proxy tourism demand in the existing literatures. In modelling tourism demand model, the independent variables consist of f income level of the tourists, tourism price, exchange rate, transportation cost, word of mouth and other key parameters. Various techniques such as ARDL, Markov-switching, and panel analysis have been utilized in previous studies to investigate the dynamic relationship between the variables in tourism demand model. The recent outbreak, COVID-19 is leaving tremendous impacts to the world economy, especially the tourism industry. In sum, the research on pre-crisis, mid-crisis, and post-crisis are equally important in gathering information for future tourism recovery and development plans

What constitutes brilliant aged care? : a qualitative study of practices that exceed expectation

Aim: This study aimed to explore what constitutes brilliant aged care. Background: Although many aged care services do not offer the care that older people and carers need and want, some perform better. Rather than focus on problems with aged care, this study examined brilliant aged care—practices that exceeded expectation. Design: The methodology for this study was informed by grounded theory, under-pinned by constructionism to socially construct meaning. Methods: This study invited nominations for a Brilliant Award via a survey, and inter-views with the nominees via web conference. After receiving survey responses from 10 nominators, interviews were conducted with 12 nominees. Data were analysed using reflexive thematic analysis and documented according to COREQ guidelines to optimise rigour and transparency. Results: According to participants, brilliant aged care involved being relationally at-tuned to older people, a deep understanding of the older person, recognition of aged care as more than a job, innovative practices and permission to reprioritise. Conclusions: This study suggests that, in aged care, brilliance happens. It emphasises the importance of meaningful connections and relationships in aged care, where thoughtful acts acknowledge an older person's value and humanity as well as creativity and innovation. Relevance to Clinical Practice: For those who manage and deliver aged care, the findings suggest that small practice changes can make a positive difference to older people. Brilliant aged care can involve acts of empathy; enthusiasm for aged care; innovative practices, even those that are small scale; and reprioritising workplace tasks to spend time with older people. For policymakers, this study highlights the need to recognise and raise the profile of the pockets of brilliance within the aged care sector. This might be achieved via awards and other initiatives that serve to celebrate and learn from brilliance in its myriad forms. Patient or Public Contribution: The nominees, who included carers, were invited to participate in workshops with other carers and older people to co-design a model of brilliant aged care, during which workshop participants discussed and critiqued the findings constructed from the data

Non-sedative cortical EEG signatures of allopregnanolone and functional comparators

Neurosteroids that positively modulate GAB

A Bibliometric Analysis of Tourism Sustainable Competitiveness Research

The present bibliometric review of research intends to document and synthesize research trends in the domain of sustainable competitiveness over the past decade. Through bibliographical analysis of 1,259 Scopus-indexed documents, the literature published from 2010 to 2020 have been identified. Publication output analysis, citation analysis, journal analysis, geographical distribution analysis, and co-occurrence keywords network analysis are utilised in this study to identify the trending research and future direction of this specific field of study using VOSviewer software and Harzing’s Publish and Perish software. Findings revealed that the literature on both tourism sustainability and tourism competitiveness solely is in its growth stage. The most productive countries in this domain are the United States, China, and the United Kingdom. In the retrieved documents, the sustainable competitiveness indeed plays a pivotal part in the evolution of the tourism field and laid a solid foundation for future research. As this paper provides an understanding on the possible mutual reinforcing relationship between two concepts, a stronger linkage on sustainable competitiveness that may catalyst the tourism development can offer reference for future research through in-depth analysis

Forecasting Tourism Demand with Composite Indicator Approach for Fiji

This study attempts to scrutinize the fluctuations of the Fijian tourism market and forecast the early warning signals of tourism market vulnerability using the tourism composite indicator (TCI). The data employed on a monthly basis from 2000M01 to 2017M12 and the indicator construction steps were adopted from the ideology of the National Bureau of Economic Research (NBER). A parsimonious macroeconomic and non-economic fundamental determinant are included for the construction of TCI. Subsequently, the procedure then employed the seasonal adjustment using Census X-12, Christiano-Fitzgerald filtering approach, and Bry-Boschan dating algorithm. Empirical evidence highlighted the signalling attributes against Fijian tourism demand with an average lead time of 2.75 months and around 54 percent of directional accuracy rate, which is significant at 5 percent significance level. Thus, the non-parametric technique can forecast the tourism market outlook and the constructed TCI can provide information content from a macroeconomic perspective for policymakers, tourism market players and investors