Real income convergence and the patterns of financial integration in the EU

We analyse real income convergence among the EU28 countries throughout 1995–2017 and the relationship with the convergence patterns of financial systems. We apply the nonlinear latent factor model of Phillips and Sul (2007, 2009) to real incomes and the IMF financial development indices for financial markets and financial institutions (Svirydzenka, 2016), and identify convergence clubs endogenously. We have several results. First, income disparities narrowed significantly over the last twenty years; yet, the growth convergence process lost momentum triggered by the global financial crisis and countries legacies shaped up asymmetries that have crystallised. Second, countries' financial systems exhibit high fragmentation, especially for financial markets, with the new EU member states at a lower financial development, confirming the existence of a two-tier Europe. Overall, the convergence patterns for real incomes and financial development are strongly correlated. Finally, the financial structure matters and market-oriented economies feature higher long-run growth, indicating the need to implement pan-European policy actions that increase the opportunities of risk diversification, enhance capital raising and channel large-scale financing to firms.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.     

Tourism and community resilience in the Anthropocene: accentuating temporal overtourism

Abstract

Global tourism growth is unprecedented. Consequently, this has elevated the sector as a key plank for economic development, and its utility is deeply embedded in political, economic and social-ecological discourse. Where the expansion of the sector leverages natural and cultural landscapes, this applies pressure to social and ecological underpinnings that if not reconciled, can become problematic. The way this plays out in Australia’s Shipwreck Coast and the wider Great Ocean Road region, especially the implications for community resilience, is the focus. Emphasis is placed on the vulnerability of peripheral coastal areas to development that withdraws from destination endowments, yet fails to provide commensurate economic yield as a suitable trade-off. This is obvious where tourism intensification has led to concerns about the breach of normative carrying capacities. Temporal overtourism driven by seasonal overcrowding is countenanced as emblematic of tourism in the Anthropocene where focus tends to be largely growth-oriented, with much less attention given to bolstering social-ecological resilience, especially community resilience. At stake is the resilience of regional areas and their communities, who in the absence of garnering commensurate economic returns from tourism expansion find themselves in social and ecological deficit.     

Determinants of the allocative,cost and scope efficiencies of Indian banks

ABSTRACT

This study aims to investigate the impact of competition on determinants of allocative, scope and cost efficiencies of Indian scheduled commercial banks (SCBs). Specifically, the study, analyzes the impact of the second round of licensing on the efficiency of Indian SCBs. This is the first paper to measure scope efficiency of Indian banks and analyze its determinants. A two-stage analysis is performed on a balanced panel dataset of Indian SCBs for the period 1999–2016. In the first stage, the allocative, cost and scope efficiencies for each bank are estimated following the data envelopment analysis approach. In the second stage, internal determinants of the stated efficiency measures are estimated following the system of the generalized method of moments approach. The findings suggest that competition has not resulted in enhancing the efficiency of Indian SCBs. Among factors that can influence efficiency, it is seen that size does matter. Larger banks can enhance the efficiency of SCBs. It is also seen that having more foreign banks improves the overall efficiency of SCBs. However, before embarking on further rounds of licensing, the study posits that market-driven correction to succeed, it is imperative to address sunspots in the form of investor or borrower repression.     

Developing smart service concepts: morphological analysis using a Novelty-Quality map

Among many techniques for generating new service ideas, morphological analysis has been used due to the advantage of decomposing the system into dimensions and shapes and bringing creative results in the process of recombining them. However, with the rise of smart service systems, the determination of dimensions and shapes has become a critical problem, particularly as both their structure and components become complex. This research focuses on a data-driven approach by incorporating mobile app service documents to increase objectivity and diversity in the construction of a morphology matrix. To this end, firstly, the novelty-quality map is developed to identify innovative data based on quantitative indicators. Secondly, morphological analysis is employed along with experts’ judgment in order to generate new smart service concepts. Finally, the feasibility and effectiveness of the proposed approach are shown based on a comparative analysis with conventional approaches and real services through a case study of smart home.     

Tourists’ hotel event experience and satisfaction: an integrative approach

ABSTRACT

Tourists’ hotel event experiences have received little attention in tourism research. By proposing an integrated model of expectation–confirmation theory (ECT) and the experience economy concept, this research explores the relationship between tourists’ event experience and their satisfaction regarding the hotel event setting. The hypothesized model was empirically validated using a sample of 663 tourists who experienced a holiday event at a resort hotel. Results confirmed that the integration of the experience economy and ECT provided a better understanding of tourists’ post-satisfaction in a pleasure-driven setting. This affective–cognitive approach advances the knowledge of tourists’ experiences and satisfaction at hotel events.     

Dress for success: the effect of exhibitors’ dress conformity and self-construal on attendees’ approach behavior

ABSTRACT

The purpose of the current study is to investigate how attendees’ approach behavior is influenced by exhibitors’ dress conformity. A 2 × 2 between-subjects quasi-experimental design was utilized for this study. Our results showed that conforming dress for exhibitors can lead to a higher level of approach behavior of trade show attendees as compared with nonconforming dress, and the effect of exhibitors’ dress styles on approach behavior is moderated by attendees’ self-construal. Findings of this study provide significant insights for trade show exhibitors and attendees.     

Volatility dynamics under an endogenous Markov-switching framework: a cross-market approach

This study uses an endogenous Markov-switching framework to examine the interrelatedness of the volatility dynamics of the US and Korean markets. Previous literature assumes that the US market implied volatility index is exogenous to the Korean implied volatility index. Here, we allow for correlations between the US and Korean variables and suggest two types of endogeneity, namely endogeneity in the regressors and in the regime-switching probabilities. The estimation results show that both types of endogeneity are present in the US variables and that the parameter estimates are quite different when endogeneity is considered, indicating a serious endogeneity bias in the parameter estimates. The results of the endogeneity test for the regressors show that the effects of global shocks are often persistent and may last for as long as six periods. Sub-period analyses indicate that the degrees of endogeneity were especially strong during the global financial crisis.     

A practical road map for assessing cyber risk

The increase in interconnectivity and developments in technology have caused cyber security to become a universal concern. This paper highlights the dangers of the evolution of cyber risk, the challenges of quantifying the impact of cyber-attacks and the feasibility of the traditional actuarial methodologies for quantifying cyber losses. In this paper, we present a practical roadmap for assessing cyber risk, a roadmap that emphasizes the importance of developing a company and culture-specific risk and resilience model. We develop a structure for a Bayesian network to model the financial loss as a function of the key drivers of risk and resilience. We use qualitative scorecard assessment to determine the level of cyber risk exposure and evaluate the effectiveness of resilience efforts in the organization. We highlight the importance of capitalizing on the knowledge of experts within the organization and discuss methods for aggregating multiple assessments. From an enterprise risk management perspective, impact on value should be the primary concern of managers. This paper uses a value-centric/reputational approach to risk management rather than a regulatory/capital-centric approach to risk.     

Why cryptocurrency markets are inefficient: The impact of liquidity and volatility

In this research, we study the multifractality, long-memory process, and efficiency hypothesis of six major cryptocurrencies (Bitcoin, Ethereum, Monero, Dash, Litecoin, and Ripple) using the time-rolling MF-DFA approach. For an in-depth analysis, this study uses the quantile regression approach to examine the determinants of efficient markets. The results show that all markets present evidence of long-memory property and multifractality. Furthermore, the inefficiency of cryptocurrency markets is time-varying, and Dash is the least inefficient market while Litecoin is the most inefficient. Finally, we find that higher liquidity improves but higher volatility weakens the efficiency of cryptocurrencies, depending on the quantiles. Therefore, we conclude that high liquidity with low volatility helps active traders to arbitrage away opportunities, resulting in market efficiency.