The Effect of the COVID-19 Pandemic on Dental Tourism in Croatia

Dental tourism is based on providing dental services outside the home country at more favourable prices but with added value in tourist offers and arrangements. Croatia has become a destination for affordable and at the same time quality dental tourism due to low prices, high quality, and natural beauties. In addition to dental services, most clinics offer transportation and accommodation. Dental tourists want to combine dental services with vacation, which makes Croatia a desirable destination precisely because of the natural beauty and abundance of rich content. For this reason, many Croatian dentists have recognized dental tourism as an additional source of income or as their primary business orientation. Although clinics operating within dental tourism are located throughout Croatia, the most significant number is in Zagreb, Rijeka, and Split. Patients mostly come from developed countries such as Italy, Austria, Germany, UK, Ireland, Japan, Canada, and the USA, where dental procedures are not as affordable. Dental tourism in Croatia had exponential growth until March 2020, when, for the first time, it faced a global problem and was challenged in the form of the COVID-19 pandemic.

A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affected by fluctuating spot LNG prices. This study aimed to use machine learning (ML) to predict the Japan Korea Marker (JKM), a spot LNG price index, to reduce price fluctuation risks for LNG importers such as the Korean Gas Corporation (KOGAS). Hence, price prediction models were developed based on long short-term memory (LSTM), artificial neural network (ANN), and support vector machine (SVM) algorithms, which were used for time series data prediction. Eighty-seven variables were collected for JKM prediction, of which eight were selected for modeling. Four scenarios (scenarios A, B, C, and D) were devised and tested to analyze the effect of each variable on the performance of the models. Among the eight variables, JKM, national balancing point (NBP), and Brent price indexes demonstrated the largest effects on the performance of the ML models. In contrast, the variable of LNG import volume in China had the least effect. The LSTM model showed a mean absolute error (MAE) of 0.195, making it the best-performing algorithm. However, the LSTM model demonstrated a decreased in performance of at least 57% during the COVID-19 period, which raises concerns regarding the reliability of the test results obtained during that time. The study compared the ML models' prediction performances with those of the traditional statistical model, autoregressive integrated moving averages (ARIMA), to verify their effectiveness. The comparison results showed that the LSTM model's performance deviated by an MAE of 15–22%, which can be attributed to the constraints of the small dataset size and conceptual structural differences between the ML and ARIMA models. However, if a sufficiently large dataset can be secured for training, the ML model is expected to perform better than the ARIMA. Additionally, separate tests were conducted to predict the trends of JKM fluctuations and comprehensively validate the practicality of the ML models. Based on the test results, LSTM model, identified as the optimal ML algorithm, achieved a performance of 53% during the regular period and 57% d during the abnormal period (i.e., COVID-19). Subject matter experts agreed that the performance of the ML models could be improved through additional studies, ultimately reducing the risk of price fluctuations when purchasing spot LNG. [ FROM AUTHOR] Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Transmission of broiler egg prices between surplus and deficit areas: exploring the dynamics

Broiler chicken eggs are one of the main and strategic foods for the people of Indonesia and contribute to regional and national inflation. Broiler egg production in Indonesia differs between regions. Areas with a surplus of eggs tend to have lower prices than areas with a deficit. This research is to measure the transmission of broiler egg prices between markets in surplus and deficit areas, using weekly price time series data for the period January 2018-December 2021. Areas of surplus broiler eggs, East Java Province (the highest broiler egg production in Indonesia) which become one of the main suppliers to the Province of East Nusa Tenggara as a deficit area. Using the Johannsen cointegration test it is found that there is no cointegration or there is no relationship between the surplus and deficit regions in the long term but not in the short term. Factors of marketing infrastructure, market information systems, and geographical conditions can be obstacles to the absence of cointegration. The VAR (Vector Auto-Regressive) Vector Error Correction model (VECM) test, found that price transmission occurred between surplus and deficit areas, meaning that between the two regions, there was market integration prior to Covid. The transmission has weakened, and due to the Covid situation, there have been restrictions on the movement of people and goods. The government and other market players need to study the response of the broiler egg market, in the short and long term so that market players can make the right policies.

Economic Aspects of a Resource Sharing Manufacturing Network under Turbulences

Nowadays, manufacturing companies face more difficulties than ever. Unrest in global supply chains triggered by fluctuating customer demand, raw material shortages and crises (Covid pandemic, global warming, wars) complicate the utilization of production resources necessary for economic success. Also, the rapidly changing environment causes existing production plans to be adapted, which results in order changes, causing additional costs for manufacturers. One solution to cope with these problems is cooperation and sharing resources: requesting capacity from partners when having shortages and offering them temporarily in case of excess capacity. In this paper, a platform-based resource sharing mechanism is investigated from the economic perspective. In the mechanism, requests and offers are matched by a central platform applying a complex matching logic. The platform provides valid alternatives based on the incoming ordersthat the requesting company can choose from. Companies are rating each other's performance after each interaction based on delivery accuracy;choosing between resource offers is made based on the cumulated rating about the offeror and the price of the offer. Within this paper, the aim is to investigate the resource sharing mechanism from the economic point of view based on an approach to the responsiveness of a supply chain structure to turbulence, to support decision-makers trying to cope with unexpected changes. For this purpose, here the mechanism is briefly introduced, and basic concepts about turbulences in supply chains are also presented. Cost types related to resource sharing manufacturing companies are distinguished, and the model is validated with agent-based simulation. A simulation experiment is performed to investigate the use-case of outsourced jobs having different price levels. Based on the experiment, it can be concluded that there is a price level limit in such a resource sharing federation, under which it is worth it to collaborate with partners by outsourcing certain jobs to them. © 2022 Authors. All rights reserved.

Informational inefficiency on bitcoin futures

This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.

COVID-19 income and price shocks effect on household food access in Malawi

The paper contributes to the scarce literature on the negative effect of coronavirus 2019-induced income and food price shocks on household economic access to food, focusing on Malawi during the first two pandemic waves and using a country representative sample. We find that household income reduction, as explained by income source shocks and health mitigation measures, has a wave-specific and persistent effect on ordinal categories of food security perception. Our evidence supports the implementation and monthly scaling-up of nutrition-sensitive social protection programmes and health measures at the household level to address these adverse effects. © 2022 The Author(s). Published by Oxford University Press on behalf of the Foundation for the European Review of Agricultural Economics. All rights reserved.

Model Construction and Empirical Study on Unsustainable Usage Behavior of Paid Knowledge Users

Knowledge payment is a new method of electronic learning that has developed in the era of social media. With the impact of the COVID-19 pandemic, the market for knowledge payment is rapidly expanding. Exploring the factors that influence users' sustained willingness is beneficial for better communication between knowledge payment platforms and users, and for achieving a healthier and more sustainable development of the knowledge payment industry. The model of unsustainable usage behavior of knowledge payment users was constructed on the basis of expectation inconsistency theory, price equilibrium theory, and perceived value theory, using the 'cognitive-emotional-behavioral' model framework of cognitive emotion theory. The data were collected from 348 users through a web-based questionnaire and analyzed using structural equation modeling. Findings show that expectation inconsistency, price equilibrium, and quality value, emotional value, and social value have significant effects on discontinuous use intentions. Discontinuous use intentions also significantly affect discontinuous use behavior. © 2013 IEEE.

Food and Nutrition Insecurity in Africa: The Primary Drivers and Sustainable Strategies to Improve the Current Status

Africa ranks second in the number of undernourished people globally and has the highest prevalence of food insecurity, twice the world's average. The continent could not meet the past Millennium Development Goals and targets for 2015, and the current projection shows that Africa is not on track to achieve Sustainable Development Goal 2 of Zero Hunger by 2030. Prospects for achieving these goals are dismal because of inherent primary drivers of food insecurity in each African region. This chapter identifies the primary drivers of food and nutrition insecurity in Africa and suggests strategies to attenuate its effect. Climate shocks (drought and flood) and insecurity are the primary agents driving food insecurity in Western, Central, and Southern Africa. Migratory pests (desert locusts) are a big challenge in Eastern and Southern Africa that have destroyed thousands of farmlands, while dependence on food subsidies, climate change, and political instability are the primary drivers of food insecurity in North Africa. In summary, the prevalence of food insecurity in Africa differs owing to the influence of food insecurity drivers in each region. Consequently, the COVID-19 widespread is expected to exacerbate Africa's current food insecurity. Sustainable strategies such as investing in the agricultural system through sustainable policies;reducing food prices;preventing localized desert locust outbreaks from attaining plague proportions and counterinsurgency;managing climate;and investing in food assistance in severe, catastrophic food insecurity that best fits each region would play a key role in mitigating food and nutrition insecurity in Africa. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

HOW FAR WILL EUROPEAN DRUG INDUSTRY 'COMMITMENTS' ON COVID RESONATE?

According to Jean-Christophe Tellier, EFPIA president and CEO of UCB Pharma, the industry is "continuing to donate money and in-kind support to health systems, governments, and organizations on the ground, pulling out every stop to ensure the safe supply of medicines to the patients that need them," and "working around the clock to find new vaccines, diagnostics and treatments." Industry is expanding its manufacturing capabilities and sharing available capacity to ramp up production "once a successful medicine or vaccine is developed," and in the meantime, it is directly linking with regulatory authorities to provide information about stock, manufacturing capacity, and market tensions so as to head off potential disruptions or shortages. [...]the industry commitment most likely to strike a chord with many of the industry's inveterate critics, who have not ceased to push for patent limitations and price controls in a post-COVID world, is "working with governments and health systems to ensure that when new treatments and vaccines are approved they are available and affordable."

Dynamic effects and driving intermediations of oil price shocks on major economies

Interest in oil price shocks' economic effects has grown in recent years. However, previous studies mostly failed to clarify the dynamic transmissions of oil price shocks on representative economies from global and driver perspectives, even ignoring oil price fluctuations when linking oil prices and economy together. This paper examines the dynamic relationships and driving intermediations between multiple oil price shocks and macroeconomy by applying Bayesian vector autoregressive models with stochastic volatility and time-varying parameters, using the USA, China, the Euro-19, and Japan as research objects. Results show that, in the whole sample, all oil prices have the strongest effects on Japan, followed by China, Euro-19, and the USA, with possible directional differences. All oil prices' economic effects intensified during the crisis and Covid-19, accompanying significant oil price fluctuations. Regarding asymmetry, in the whole sample and critical times, stronger effects of rising oil prices show in the short term, but opposite in the long term. Consumer price, interest rate, and exchange rate are the general intermediations of oil prices in China and the USA, Euro-19, and Japan, respectively, and exchange rate is the additional intermediation in China, Euro-19, and Japan during the crisis and Covid-19. Overall, the results are solid.

The Value-Based Price for a Bivalent COVID-19 Booster Vaccine in the United Kingdom

Objectives: The United Kingdom (UK) implemented an autumn 2022 booster programme that allowed those at higher risk from COVID-19, including those >= 50 years, to receive a booster to increase protection against infection and subsequent severe outcomes. As the UK transitions out of the pandemic, future booster campaigns may be required to maintain protection against such outcomes. The objective of this analysis was to estimate the value-based price (VBP) for a bivalent COVID-19 vaccine used in a future autumn 2023 campaign in the UK to protect people aged >= 50 years. Method(s): A Susceptible-Exposed-Infected-Recovered (SEIR) model was used to predict infections across a 1-year time horizon starting September 2023 with and without an autumn booster campaign. Initial effectiveness was predicted to be 89% and 97% against infection and hospitalization respectively based on BA.4/BA.5 antibody titers and correlates of protection. A monthly decline in protection of 1.4% and 4.8%, respectively, was assumed based on monovalent vaccine data. A decision tree was used to predict the quality-adjusted life-years (QALY) lost and costs associated with infections. Result(s): Considering a willingness-to-pay (WTP) threshold of 20,000/QALY, the VBP associated with an autumn 2023 booster campaign is 343/dose. Considering a WTP threshold of 30,000, the VBP increases to 476. In sensitivity analyses, excluding the post-infection costs (e.g., long COVID), reduces the VBP by 11%. Varying the hospitalization rates by +/-25% changes the VBP by +/- 6%. Varying hospitalization unit costs only impacts the VBP by 1%. Doubling the rate of waning for booster effectiveness increases the VBP by 54% because the effectiveness provided from past campaigns falls faster and an autumn 2023 booster becomes more valuable. Conclusion(s): While the trajectory of COVID-19 incidence is highly uncertain, pricing the bivalent booster lower than the VBP is expected to result in a cost-effective strategy for the UK.Copyright © 2023

The Three Dimensions of the Indian Wage Code (2019): Shifting Economic, Socio-political and Legal Values?

The value of work is intrinsically linked to its monetary equival ent expressed in wages. Changes in wage laws therefore impact a wide-ranging frontier of tensions inherent in the politics around remuneration, at the individual, the firm and the state level. In othe r words, wages do not form a single line of conflict, but in fact matters of payment unfold multiple struggles in the spheres of institutions, at the shop-floor and within the household. From thi s three-fold perspective, the paper analyses unravelling tensions in the economic, legal and sociopolitical constitution of wages in the Indian Wage Code of 2019. This evaluation shows the importance of strengthening need-based approaches to wages such as minimum wage pol i ci e s, not just to facilitate decent working standards, but also to guarantee adequate social safety nets, particularly in times of crisis such as the COVID-19 pandemic.

Economic Policy Uncertainty and Emerging Stock Market Volatility

This research examines the effect of economic policy uncertainty (EPU) indices on Pakistan's stock market volatility. Particularly, we examine the impact of the economic policy uncertainty index for Pakistan and bilateral global trading partner countries, the US, China, and the UK. We employ the GARCH-MIDAS model and combination forecast approach to evaluate the performance of economic uncertainty indices. The empirical findings show that the US economic policy uncertainty index is a more powerful predictor of Pakistan stock market volatility. In addition, the EPU index for the UK also provides valuable information for equity market volatility prediction. Surprisingly, Pakistan and China EPU indices have no significant predictive information for volatility forecasting during the sample period. Lastly, we find evidence of all uncertainty indices during economic upheaval from the COVID-19 pandemic. We obtained identical results even during the Covid-19. Our findings are robust in various evaluation methods, like MCS tests and other forecasting windows.

ANALYSIS OF THE EFFECT OF MACROPRUDENTIAL AND MACROPRUDENTIAL INDICATORS ON THE STOCK PRICE INDEX OF ISLAMIC BANKS IN INDONESIA USING THE ERROR CORRECTION MODEL

The experience of various crises that have occurred, including the impact of the Covid-19 pandemic, presents a challenge to implement macroprudential policies to ensure the financial system survives and continues to carry out its function in driving the economy. The existing macroprudential policies tend to be individual and focus on prudent banking and other financial institutions. Economic fluctuations that occur on the macro side will greatly impact, either directly or indirectly, the stock price index, as well as the company's internal indicators which are considered to have a major influence on the decisions of investors and potential investors to take action on the stock exchange. The type of research used in this research is quantitative research. The nature of this research is descriptive with a quantitative approach. The data collection technique in this research is Literature Study. The test carried out in this study is the multiple linear regression analysis test (multiple linear regression method), this study uses the ECM model to obtain the best model which includes the classical assumption test. The results of this study based on the partial short-term relationship test, it can be concluded that the Exchange Rate, Inflation, and TPF in the short term have no significant effect on the PNBS Stock Price Index. Meanwhile, short-term CAR has a significant positive effect on the PNBS Stock Price Index. Based on the results of the partial long-term relationship test, it can be concluded that in the long term, the Exchange Rate has a significant negative effect and TPF and CAR have a significant positive effect on the PNBS Stock Price Index while Inflation has no significant effect on the PNBS Stock Price Index. Based on the output results of the simultaneous short-term and long-term F test, it shows that all independent variables simultaneously have a significant effect on the PNBS Stock Price Index in the short term. Based on the provisions of the MUI DSN through the issued fatwas related to the Sharia capital market and Sharia shares, it is explained that Sharia stock investment to invest according to the perspective of Sharia economic law is allowed. [ FROM AUTHOR] Copyright of Jurnal Syntax Admiration is the property of Ridwan Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Two Major Economic Crises in the Early Twenty-First Century and their Impact on Central Bank Independence

Two major economic crises in the early twenty-first century have had a serious impact on monetary policy and CB independence. Disruption in financial intermediation and associated deflationary pressures caused by the global financial crisis of 2007–2009 and European financial crisis of 2010–2015 pushed central banks (CBs) in major currency areas towards adoption of unconventional monetary policy measures, including large-scale purchase of government bonds (quantitative easing). The same approach has been taken by CBs in response to the COVID-19 crisis in 2020 even if the characteristics of this crisis differ from the previous one. As a result of both crises, CBs have become major holders of government bonds and de facto – main creditors of governments. Against rapidly deteriorating fiscal balances, CBs have become hostages of fiscal policies, which compromises their independence. Risks to the CB independence also come from their additional mandates (beyond price stability) and populist political pressures.

THE DETERMINANTS OF HOUSE BUYERS' PURCHASE DECISIONS IN KOTA BHARU, KELANTAN

The issue of unsold homes in Malaysia has recently caused the housing developers great anxiety. The nationwide issue of unsold homes was caused by the fact that more homes were built than were purchased by customers. As a result, it is important to figure out what factors can influence potential homebuyers to make a purchase. In order to better understand this issue, the study's objective was to determine the factors that influence homebuyers' decisions in Kota Bharu, Kelantan. The study specifically sought to ascertain whether variables including quality, price, location, promotion, and corporate image had an effect on consumers' decisions to purchase homes. Since the nation was dealing with the Covid-19 outbreak, which made face-to-face questionnaire distribution on the ground nearly impossible to carry out, 382 respondents from Kota Bharu, Kelantan, participated in this study through questionnaires disseminated using the Google Form technique. This study used the Principal Axis Factor and Promax Rotation to evaluate the instruments. Before doing a bootstrapped regression analysis, all seven multiple regression assumptions were examined and verified. The findings showed that only location and promotion variables were positive and significantly influencing the house buying decision. These findings led to a number of strategy recommendations that helped the industry develop the best plans for boosting upcoming sales. It is hoped that by identifying the variables influencing homebuyers' purchasing decisions, housing developers can get an understanding of this phenomenon and be better able to plan and build homes that will live up to buyers' expectations. © 2023 by MIP.

The Bank of Japan's exchange traded fund purchases: a help or hindrance to market efficiency?

We examine the impact of the Bank of Japan's exchange traded fund (ETF) purchases on two aspects of market efficiency—long-range dependence and price delay—of the TOPIX and Nikkei 225 indices. An increase in ETF purchases results in lower long-range dependence for both indices while the impact on the price delay varies according to index and measure. A sub-period analysis shows that the impact on market efficiency varies over time, with the dominant pattern being a delayed harmful effect, followed by a positive impact and thereafter a negative effect. The implications of these findings are discussed.

Beyond Value Assessment: Payer Perceptions of ICER's Policy Initiatives

Objectives: To assess how the Institute for Clinical and Economic Review (ICER) has evolved its policy scope beyond value assessments in the last 7 years and explore payer perceptions of ICER's new policy initiatives. Method(s): Completed ICER assessments and policy papers published from 2016-2022 were counted to quantify ICER's activities and output. Double-blinded, web-based surveys of US healthcare payers were fielded through Xcenda's research panel, the Managed Care Network, in October 2020 (N=47) and June 2022 (N=51) to explore perceptions of ICER initiatives, including policy papers, Unsupported Price Increase (UPI) reports, and ICER Analytics. Result(s): ICER has published 65 value assessments and 17 policy papers since 2016. ICER's output of policy papers has increased in recent years (mean of 1.3 publications annually, 2016-2018 vs 3.7 annually, 2020-2022), whereas the number of value assessments has remained flat (mean of 9.3 assessments annually, 2016-2018 and 2020-2022). Payers perceive ICER's policy initiatives to be of varying degrees of usefulness. In 2020, the subset of payers reporting familiarity with ICER initiatives found the policy paper on valuing cures to be the most useful initiative (42% reporting extremely or very useful [n=38 reporting familiarity]), followed by the UPI report (40% [n=40]);the policy paper on COVID-19 pricing models was viewed as least useful (22% [n=37]). In 2022, the most useful initiatives among payers reporting familiarity were ICER Analytics (51% [n=49]) and the policy paper on orphan drugs (45% [n=47]);the policy paper on fair access was perceived as least useful (29% [n=44]). Conclusion(s): ICER's output of annual policy papers has increased over time, demonstrating ICER's growing investment in policy initiatives. Payer perceptions of the usefulness of ICER initiatives vary, with ICER Analytics being the most useful in 2022. Additional research is needed to better understand how payers use ICER's policy papers/initiatives to inform decision making.Copyright © 2023

The Nutrient Rich Food Price Index: a nutrition-relevant adaptation of the Laspeyres price index to track the cost of affordable nutrient density.

Background: The Laspeyres price index is the ratio of the current cost of a market basket of commodities or food groups relative to base period prices. Objective: To develop a nutrition-relevant version of the Laspeyres price index, using market baskets based on tertiles of the nutrient rich food (NRF9.3) nutrient density metric. Methods: Nutrient composition data for 151 foods from the 2012 Mexico national health and nutrition survey (ENSANUT) were merged with food prices and price indices from the national institute of geography and statistics (INEGI). Nutrient Rich Food Index (NRF9.3) was the measure of nutrient density. May 2012 was the base period. Nutrient rich food price index (NRFPI) values were calculated for each tertile of NRF nutrient density scores for each month between June 2011 and March 2022. Results: The market basket of foods in the top tertile of NRF nutrient density scores cost more per 100 kcal and had higher NRFPI values compared to foods in the bottom tertile. Higher NRF9.3 scores were correlated with greater monthly inflation. The NRFPI for foods in the top tertile of NRF9.3 scores was marked by seasonal price spikes, and greater volatility compared to foods in the bottom tertile. Conclusion: The present adaptation of the Laspeyres Index used market baskets defined by nutrient density tertiles instead of commodity groups. This approach allows for easier tracking of the cost of nutrient dense foods and healthful diets across geographic regions and over time. Applied to Mexico food prices prior to and during the Covid-19 pandemic, the NRFPI was sensitive to time trends, seasonality, and price fluctuations. The new tool may be useful in monitoring the rising cost of healthy foods worldwide.

New horizon in fuzzy distributions: statistical distributions in continuous domains generated by Choquet integral.

In this paper, some statistical properties of the Choquet integral are discussed. As an interesting application of Choquet integral and fuzzy measures, we introduce a new class of exponential-like distributions related to monotone set functions, called Choquet exponential distributions, by combining the properties of Choquet integral with the exponential distribution. We show some famous statistical distributions such as gamma, logistic, exponential, Rayleigh and other distributions are a special class of Choquet distributions. Then, we show that this new proposed Choquet exponential distribution is better on daily gold price data analysis. Also, a real dataset of the daily number of new infected people to coronavirus in the USA in the period of 2020/02/29 to 2020/10/19 is analyzed. The method presented in this article opens a new horizon for future research.