International Journal of Computational Economics and Econometrics (9 papers in press)

Special Issue on: ICOAE2023 Applied Economics and Competition

• Correlations and volatility spillovers across cryptocurrency and stock markets: linking gold, bonds, and FRX  
  by Mirzat Ullah, Kazi Sohag 
  Abstract: This study examines the correlation among Bitcoin, gold, equity, bonds, and dollar to ruble exchange rate volatility in the context of new developments during Russia Ukraine conflict using daily data from January 1, 2018, to May 30, 2023. Three GARCH estimation models are utilised to capture the hedging, diversification, and safe haven properties of Bitcoin in Russian financial market. The results indicate that the Bitcoin exhibits hedging ability that enables investors to diversify the risk among the underline financial assets. In addition, VaR and CVaR estimations are employed to estimate potential losses in the portfolio during the crisis, where we observe significant increase in Bitcoin investments during crisis, where negative news has a stronger impact compared to positive news which underscores the importance of prudent asset allocation for risk mitigation. The study provides notable policy implications within the context of the ongoing crisis between Russia and Ukraine.
  Keywords: Bitcoin; gold; equity; bonds; USD/RUB exchange rate: Russian financial market; GARCH estimation; hedging and diversification.
  
  
• The global inflation cycle and the dollarisation system with the interlink with commodities: an application of the Bayesian network analysis  
  by Amira Hakim 
  Abstract: This paper investigates the dollarisation of the international monetary system within the catalyst of global inflation using the commodities under the connectedness of the selected aggregates as an intermediary within the Bayesian network model and over a time horizon during the period Q1 1984 to Q4 2020. The Bayesian network approach results reveal that energy and gold act as hedges for the financialisation of the economy and therefore for stabilising global inflation. Our findings also indicate that the capital market and cryptocurrencies do not have significant impacts on the dollarisation of the monetary system. Moreover, the findings of the study show that the significant impact of commodities stabilising the global inflation cycle seems to be significant for the dollarisation of the monetary system.
  Keywords: global inflation; dollarisation; oil; gold; Bayesian network.
  
  
• Unpacking customer feedback and brand equity dynamics in the hospitality industry through machine learning techniques  
  by T.D. Dang, M.T. Nguyen 
  Abstract: This study utilises Latent Dirichlet allocation (LDA) and latent semantic analysis (LSA) for advanced topic modelling in the hospitality sector, analysing customer feedback from Booking.com in Ho Chi Minh City, Vietnam. It highlights crucial aspects influencing brand equity: ambient noise levels, room standards, facility provisions, staff interactions, and strategic location advantages. Further, the research integrates an extensive suite of machine learning (ML) and deep learning (DL) techniques, including logistic regression (LR), random forest (RF), multinomial Naive Bayes (NB), long short-term memory (LSTM), convolutional neural network (CNN), and notably, the dense model. The dense model stands out, demonstrating remarkable performance with an accuracy rate of 0.95 and an F1-score of 0.97, validating the effectiveness of data-driven methodologies in extracting nuanced customer sentiments. These insights offer a multifaceted understanding, serving as a valuable resource for practitioners to refine service strategies, elevate customer satisfaction, and strengthen market presence.
  Keywords: customer feedback; brand equity; sentiment analysis; topic modelling; hospitality industry; machine learning.
  
  
• Application of Bayesian methods in the analysis of dynamic conditional correlation multivariate GARCHmodels  
  by Dechassa Obsi Obsi 
  Abstract: The study investigates the use and performance of the multivariate generalised autoregressive conditional heteroscedastic (MGARCH) model, specifically the dynamic conditional correlation (DCC)-MGARCH model in Bayesian frame work. It uses a Markov chain Monte Carlo strategy and the Metropolis-Hastings algorithm for effective posterior sampling. The model is found to be more flexible and can describe uncertainties and volatilities of the error distribution. The sensitivity test shows that posterior results are more reliable when prior parameters are randomly sampled from the beta distribution.
  Keywords: Bayesian inference; dynamic conditional correlation; DCC; generalised error distribution; GED; Markov chain Monte Carlo; MCMC; Metropolis-Hastings; generalised autoregressive conditional heteroscedastic; skewed distributions.
  
  
• Minimum wage as the determinant of productivity in EU countries  
  by Jana Kopecká, Lenka Viskotová, David Hampel 
  Abstract: When introducing and setting minimum wages, primarily to reduce poverty and avoid undesirable phenomena in the labour market, it is necessary to monitor the impact on various aspects of the real economy. This paper focuses on demonstrating the positive impact of nominal minimum wage growth on productivity in EU countries. A cluster analysis is used to divide countries into two distinguished clusters. Using panel regression, the effect of a minimum wage is found to be significant and positive. To rule out spurious regressions and to demonstrate the robustness of the performed analyses, appropriate covariates are included in the models, different forms of productivity are modelled, and the models are also estimated independently for each cluster.
  Keywords: cluster analysis; company production process; EU27; human capital; labour costs; low-wage employees; minimum wage; productivity of labour; panel regression model; training of employees.
  DOI: 10.1504/IJCEE.2024.10062965
   
  
• Heterogeneous impacts of the COVID-19 pandemic on financial performance among European hotels  
  by Tomáš Heryán, Petra Růčková, Jana Šimáková 
  Abstract: The purpose of the paper is to investigate whether there would have been differences in the change of shareholders’ funds caused by the COVID-19 pandemic in Europe among medium-sized hotels. Annual data for 17 European countries have been obtained from the Bureau van Dijk Orbis database and clustered with epidemiological data from NUTS-3 regions among selected countries. Using heterogeneous difference-in-differences with cohorts, the average treatment effect on treated has been estimated with panel data. Specifically, differences between the levels of shareholders’ funds and the impact of the moderation effect between return on equity and dividends during the pandemic considering the morbidity among pandemic patients in selected regions. The results have suggested that the impact of the pandemic varies between hotels with a high concentration of ownership structure having a major owner and those with a low concentration and dispersed ownership structure.
  Keywords: heterogeneous impacts; COVID-19 pandemic; European hotels; financial performance; heterogeneous DiD models; difference-in-differences; cohorts.
  DOI: 10.1504/IJCEE.2024.10063831
   
  
• Tourism product life cycle dynamics: a computational approach to identifying tourism stages in Italy and Greece  
  by Zacharoula Kalogiratou, Theodoros Monovasilis, Nicholas Tsounis, Gerassimos Bertsatos 
  Abstract: An adaptation of the tourist area life cycle model is used to computationally identify each stage of the tourism product life cycle to explain the dynamics of tourist arrivals to Italy and Greece. It was found that the first stage of the cycle started considerably earlier in Italy than in Greece, well before WWII, while in Greece, it started during the 1950s. A new life cycle began in Greece in 2012. Italy is still in the consolidation stage and has shown growth, and this stage will continue until 2044. However, if suitable policies are applied in terms of investments in infrastructure and human capital and in marketing, this cycle can be interrupted, and a new cycle could begin directly from the development stage, where the growth rates of the number of tourist arrivals are exponential. Investing and providing services in alternative tourism may lead to this result.
  Keywords: tourism; product life cycle; Italy; Greece.
  DOI: 10.1504/IJCEE.2024.10064668
   
  

Special Issue on: Economic Analysis and the Current Real-World Situation Exploring New Trends in Applied Economics. Special Issue in Honour of Prof. George Agiomirgianakis

• Investment analytics using association rule mining (Finassociations)  
  by Elif Kartal, M. Erdal Balaban, Zeki Özen 
  Abstract: This study aims to discover financial associations (relations) in (foreign) exchange rates, cryptocurrencies, and stocks using Association Rule Mining (ARM). It demonstrates the applicability and success of ARM on alternative investment instruments over desired periods. A dynamic web application called “Finassociations” was developed in this scope, allowing investors to use and discover ARM. They can use the desired filters to make investment decisions by generating rules for which investment instruments rise or fall together. The application dynamically retrieves current data from Yahoo Finance. This study is a dynamic and expanded update on the existing ones. The exemplary analyses utilized data spanning various periods, up to two years preceding October 9, 2022. According to the study results, significant and strong financial associations in three different investment groups can be obtained. Also, the results show that short-term financial data can be preferred over long-term financial data when examining associations between investment instruments.
  Keywords: association rule mining; ARM; association rules; data mining; apriori; investment decisions; financial associations; finance; foreign exchange rates; cryptocurrencies; stocks.
  
  
• Current account dynamics in selected Southeast Asian economies, using a PSVAR model  
  by Minoas Koukouritakis 
  Abstract: The present paper explores the impact of budget balance shocks, as well as output shocks, on the current account balance of four high-income Southeast Asian countries, namely China, Japan, Republic of Korea and Singapore. For performing this analysis, a panel structural VAR model has been implemented, using an extended sample of a more than 40-year period. The estimated impulse-response functions and variance decompositions for common and idiosyncratic shocks provide an indication regarding the way that fiscal and output shocks affect the current account balance. In brief, they imply that, in the short run, the twin divergence hypothesis holds. In other words, an expansionary fiscal policy will improve the current account balance. However, in the long run, the empirical evidence seems to validate the new classical Ricardian equivalence theorem.
  Keywords: current account balance; budget balance; panel SVAR model; impulse responses; structural variance decompositions.