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Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

Individuals who are exploited and manipulated by criminal gangs are often wrongly labelled, stereotyped, and blamed (to varying levels) for the vulnerable positions that they find themselves in. Individuals who perpetrate violence towards others have often also been victims of violence and crime themselves. Teaching about these groups and trying to represent their position and experiences is a difficult and sensitive area. Building on current research, experiences of teaching professionals and students about the exploitation of marginalised groups, serious violence, and crime during COVID-19, are reflected upon. In doing so, what is important for students to understand about marganilised groups is set out, and recommendations for improvements to teaching practice are discussed. Firstly, it is argued that where educators seek to help students learn about marginalised groups, there needs to be preparation to put the work in at the front end and reflect on their own assumptions, beliefs and learning needs. Secondly, they also need to think about the ‘active’ and ‘passive’ (Seddon, 2005) aspects of individual agency and to be as authentic as they can to the lived experiences of marginalised communities as community members engage in types of behaviours and access services. Finally, it is then important for them to open up opportunities for students to reflect on the more detailed aspects and wider social, economic, and structural factors that marginalised communities face as they endeavour to articulate their own needs in society.

Neuromarketing is a marketing communication field that applies neuroscience and physiological research tools to study consumer behavior toward stimuli, viz., ads and brands. This study aims to assess research trends in the neuromarketing field on the most influential journals, authorships, countries, citations and co-occurrences. The Scopus database is used to analyze identified articles from 2013 to 2022 and for the eligible research articles, a “systematic methodological review” (SMR) on consumer behavior through neuromarketing approach was done. “Visualization of Science (VOS)” viewer and “Biblioshiny” by R-studio software have been used for mapping the keyword analysis, co-citation analysis and author occurrence analysis. It was further found that of the top 10 academic institutions, the list is dominated by the six Asian institutions. It was further witnessed that journal “Physiology and Behavior” is trending as the most dedicated and emerging journals on neuromarketing and consumer behavior. Asian nations such as Bangladesh, China, India, Indonesia, etc., are turning out to be an emerging collaborators and publishers in this niche area of research, thereby giving tough competition to most developed countries. The findings of the thematic mapping show that neuromarketing is itself a very novel and newest area of study and topics such as “human marketing,” “neuromarketing,” “consumer behavior” and “electroencephalography” are new dimensions that can be looked upon in future.

This empirical research intends to examine factors influencing the adoption of renewable energy (RE) using a conceptual model of the consumer decision-making process.

This study uses a primary response-based survey to collect data from 668 respondents interested in adopting RE for their daily usage. The sample respondents were chosen through a multi-stage random stratified technique. The responses were analyzed through structural equation-based modeling techniques to discuss the findings and suggest further implications.

The findings suggest that factors like knowledge, policy incentives, sustainable development goals (SDGs-7, 11 and 13), socio-economic benefits and risk perception significantly impact the adoption of RE. Besides, risk perception mediates between environmental concerns and the adoption of RE. Also, age has a significant role in RE adoption.

The study finds the critical role of government in introducing financial incentives to reduce the initial cost of renewable adoption. Doing so will also promote clean and equitable energy access to society leading to further fulfillment of SDGs. Additionally, steps like knowledge enrichment, designing suitable policies for a manufacturer and public-friendly renewable market development will further facilitate renewable adoption in society.

With an objective to study the public perception and attitude towards renewable adoption, this empirical research is the first of its kind to carry out a real-time survey of the Indian population and suggest policy implications which would benefit all the concerned stakeholders.

The purpose of this paper is to discuss the need to establish linkages between tourism, intangible cultural heritage and creativity in Egypt and also diversifying tourism through creativity; and to analyze and explain the impact of intangible cultural heritage on tourism experience in Egypt and the opportunities to generate added value from integrating tourism and creativity. It also suggests some practical steps for developing intangible cultural heritage-based tourism models in Egypt.

The paper proposes a conceptual framework for integrating intangible cultural heritage with tourism in Egypt and its impact on tourism experience. To apply this framework, a case study was conducted focused on the tourism experience derived from intangible cultural heritage in Alexandria. The authors collected primary data by directly observing and experiencing tourism in Egypt, providing valuable firsthand experiential data. These observations offered insights into the practical aspects of intangible cultural heritage-based tourism in Egypt. In addition, secondary data sources such as academic research papers, reports and publications related to tourism and intangible cultural heritage experiences were utilized to support and complement the primary data.

Findings suggest the need for a different approach in intangible heritage based tourism promotion and consumption, an approach that may differ from the conventional and typical considerations in cultural tourism planning and management. In addition, findings emphasized that tourism-based intangible heritage in Egypt can be a constructive platform and sustainable tool to promote the country’s rich culture and traditions while providing employment opportunities for the local population.

This study provides an exploratory overview of integrating intangible heritage with tourism in Egypt, through exploring Egypt’s intangible heritage and proposing a framework of its inclusion, in order to create an intangible cultural heritage tourism experience. However, the proposed framework and packages should be analyzed and examined on the ground through the heritage, administrative, social and tourist aspects of the destination, to assess the viability of the study.

The practical implications of this study should be addressed to the decision makers working on management action plans in tourist destinations in Egypt, such as site mangers as well as tour operators. It could contribute to adopting a new approach in developing and implementing a mutually beneficial partnership between intangible heritage and tourism in Egypt.

It is the first study that presents practical steps to develop new models for linking intangible heritage to tourism in Egypt.