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The development of sharia tourism in Indonesia has some extraordinary challenges and obstacles throughout 20202022 due to the Covid-19 pandemic. On the other hand, the 2019 gMtI data shows that by 2030, the number of Muslim tourists is projected to exceed 230 million worldwide. The opportunities, challenges, and obstacles shown in the development of sharia tourism require stakeholder follow-up as part of the growth of the sharia economy in the country. This study offers a theoretical framework for economic growth built on dynamic cycle theory because very few studies investigate it. Even though it is imperative to consider an analysis of economic growth with a dynamic cycle that focuses on the halal tourism sector because it is known to make a significant contribution that supports sustainable development conditions and vice versa. This study investigates one of the Islamic tourism development models originating from Ibn Khaldun's thoughts regarding the concept of the state relating to justice to obtain wealth in economic activity (through trade). The research method used is a literature study using content analysis that focuses on the thoughts of Ibn Khaldun as contained in his work entitled Muqadimmah and several relevant previous literatures. The findings reveal that there are two important points. First, Ibnu Khaldun proposes a framework to help countries face challenges of growth or problems of back-and-forth economic development including a dynamic cycle. The framework is based on a proposition of eight principles from a policy known as the eight wise principles or sentence hikammiyah consisting of sovereign power (al-mulk), sharia, human resources (ar-rijal), property (al-mal), development (al-imarah), justice (al-adl), a yardstick (al-mizan), and responsibility are cycles that occur with different durations. So in the end created three generations. Second, if Ibn Khaldun's thoughts about the eight principles of justice policy are embodied in sharia tourism development policies that are supported by the role of human resources, it will affect the reversal of sharia economic growth. It can be concluded that the dynamic cycle can support the development of sharia tourism and have an impact on sharia economic growth as long as the eight policy principles are implemented correctly according to sharia. Stakeholders need to consider the dynamic cycle for future sharia tourism development policies.
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When it comes to supplying oxygen, current standard hospitals in Iran have proven inadequate in the face of the COVID-19 pandemic, particularly during infection peaks. Power disruptions drastically reduce the oxygen pressure in hospitals, putting patients' health at risk. The present study is the first to attempt to power an oxygen concentrator with a solar-energy-based system. The HOMER 2.81 package was used for technical–economic–environmental–energy analysis. The most notable aspects of this work include evaluating different available solar trackers, using up-to-date equipment price data and up-to-date inflation rate, considering the temperature effects on solar cell performance, sensitivity analysis for the best scenario, considering pollution penalties, and using a three-time tariff system with price incentives for renewable power. The study has been carried out at Hajar Hospital, Shahrekord, Chaharmahal and Bakhtiari Province, Iran. The study showed that, by supplying 60% of the power demand, the dual-axis solar tracking system offered the highest annual power output (47,478 kWh). Furthermore, generating power at—$0.008/kWh due to selling power to the grid, the vertical-axis tracker was found to be the most economical design. Comparing the configuration with a vertical-axis tracker with the conventional scenario (relying on the power distribution grid), the investment is estimated to be recovered in three years with $234,300 in savings by the end of the 25th year. In the best economic scenario, 6137 kg CO2 is produced, and the analysis revealed the negative impact of a temperature rise on the performance and solar power output.
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The objective of this research is to develop a monthly indicator that synthesizes the economic acti-vity of the construction sector in Valle del Cauca, as a tool for analyzing the production cycle and as a single, public measure that contributes to decision-making. Dynamic factorial models, the Kalman filter and the Litterman method are used, also employed in the Monthly Index of Economic Activity (IMAE), in order to capture signals, changes in the productive cycle of construction and compile the sectoral economic facts that affect production. In the results, the dynamics of the sectoral and economic variables are observed that explain the behavior of the sector in Valle del Cauca during 2009-2020. A change of slope is observed in 2020, as a direct consequence of the crisis generated by COVID-19 and the restrictive measures taken by the government to contain its advance.
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The concept and practicalities of sustainable business development attract increasing interest of general public, companies, legislators, activists, academics and many others. Our understanding of what constitutes sustainability is evolving, especially nowadays when the pandemic and digitalization caused major shifts globally. In such conditions, it is no wonder that managers and business owners may face difficulties in implementation and evaluation of sustainable practices. Therefore, The objective: of the paper is to examine theoretical foundations of the concept of business sustainability and propose an up-to-date model for its appraisal. The paper is divided into two primary parts in addition to introduction and conclusion. The first part is dedicated to the examination of the terms 'stability' and 'sustainability' universally and in business environment. The second part includes description of our suggested evaluation model of economic, social and environmental sustainability perspectives using relevant indicators. Methods/Analysis: the research includes review of academic literature and empirical research on the topic of business sustainability and analytical consolidation of existing approaches to its appraisal. Findings: theoretical contribution to perception and development of the conditions of business stability and sustainability, and evaluation model including specific indicators across the three primary sustainability directions. Application/Improvements: the research is useful to general public, but is of special interest to business leaders interested in implementation of sustainable practices.
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PurposeThe main motivation of the present study is to understand the severity of the effect of health shock on Iran's oil economy and analyze the role of government under these conditions.Design/methodology/approachDynamic stochastic general equilibrium (DSGE) models can show the precise interactions between market decision-makers in the context of general equilibrium. Since the duration of the virus outbreak and its effect on the economy is not known, it is more appropriate to use these models.FindingsThe results of the survey of hands-on policies scenarios compared to the state of hands-off policy indicate that the effect of government expending shocks on the economy under pandemic disease conditions has much less feedback on macroeconomic variables.Originality/valueAs a proposed policy, it is recommended that the government play a stabilizing role under pandemic disease conditions.Key messages There is no study regarding health shock and its economic effects in Iran using DSGE models. Also, in foreign studies, the health shock in an oil economy has not been modeled.The general idea in the present study is how the prevalence of a pandemic infectious disease affects the dynamics of macroeconomic variables.In three different scenarios, according to the persistence of health disaster risk and the deterioration rate of health capital due to this shock, the model is simulated.In modeling pandemic diseases, quarantine hours are considered as part of the total time of individuals.According to the research findings, it is recommended that the government, as a policy-maker, play a stabilizing role under pandemic crises conditions.
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This event study examines the stock price reaction to the merger announcement of three major Islamic banks in Indonesia, namely BNIS, BRIS, and BSM to become Indonesia Islamic Bank (ticker code BRIS). This study analyzes whether there is an abnormal return around the merger announcement on 14 days window period. Using a daily stock price of BRIS, market index, and trading volume we calculated abnormal return and risk using market model Sharpe 's single index model. Analysis of the 14 days window period found that there is an insignificant abnormal return before and after the Islamic banking merger and Indonesia Stock Exchange has been categorized as weak-form efficiency. The results of statistical tests reveal that stock returns and trading volume react positively after the merger announcement and are significant at 5% alpha.
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Disturbance such as COVID-19, pollution or policy variation to the economic and financial system has significant effect in the big data applications. Hence to study the effect of the disturbance on the related time series plays important role in further applying the big data in economic and financial system. Generalized Weierstrass-Mandelbrot Function is presented to study the complexity of the related time series theoretically and simultaneously. The results show that the disturbance indicated as the exponential form can generate multifractal features for the related time series. And the irregularity and long memory are also simulated by this model and described by the R/S method and multifractal analysis. © 2023 IEEE.
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The lack of public spaces, recreational areas, and sports facilities in older city neighborhoods, as well as the importance of people's social and economic well-being, have been exposed by the COVID-19 pandemic. Revitalization is used to update the physical environment of old neighborhoods;it improves not only the physical environment of the neighborhood, but also contributes to ensuring the social and economic well-being of the residents. The article aims to identify which typical revitalization project solutions, only referring to physical environmental improvement projects, improve the social and economic well-being of the residents. To achieve this goal, a statistical analysis of the Žirmūnai triangle residents was performed with obtained survey data. The hypothesized connections between typical revitalization solutions and changes in the social and economic well-being of the population were verified using Pearson's Chi-Square test. The results showed that the public spaces, sports, and playgrounds provided by revitalization were directly related to the social and economic well-being of the residents. As a result of this typical revitalization solution, 17% of the residents experienced an improvement in their economic well-being, 17% of the residents got to know their neighbors, and 95% of the residents indicated that they enjoy living in the neighborhood.
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During the COVID-19 pandemic, more than 24 billion pieces of surgical mask waste (WM) were generated in the EU region, with an acute shortage of their management and recycling. Pyrolysis and gasification are among the most promising treatments that were proposed to dispose of WMs and convert them into pyrolysis oil and hydrogen-rich syngas. This work aimed to investigate the techno-economic analysis (TEA) of both treatments in order to assess the feasibility of scaling up. The TEA was carried out using a discounted cash flow model and its data were collected from practical experiments conducted using a fluidised bed pyrolysis reactor and bubbling fluidised bed gasifier system with a capacity of 0.2 kg/h and 1 kg/h, respectively, then upscaling to one tonne/h. The technological evaluation was made based on the optimal conditions that could produce the maximum amount of pyrolysis oil (42.3%) and hydrogen-rich syngas (89.7%). These treatments were also compared to the incineration of WMs as a commercial solution. The discounted payback, simple payback, net present value (NPV), production cost, and internal rate of return (IRR) were the main indicators used in the economic feasibility analysis. Sensitivity analysis was performed using SimLab software with the help of Monte Carlo simulations. The results showed that the production cost of the main variables was estimated at 45.4 EUR/t (gate fee), 71.7 EUR/MWh (electricity), 30.5 EUR/MWh (heat), 356 EUR/t (oil), 221 EUR/t (gaseous), 237 EUR/t (char), and 257 EUR/t (syngas). Meanwhile, the IRR results showed that gasification (12.51%) and incineration (7.56%) have better economic performance, while pyrolysis can produce less revenue (1.73%). Based on the TEA results, it is highly recommended to use the gasification process to treat WMs, yielding higher revenue. [ 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.)
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We examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Assuming that social distancing measures can substantially reduce contacts among individuals, we find net benefits of about $5.2 trillion in our benchmark case. We examine the magnitude of the critical parameters that might imply negative net benefits, including the value of statistical life and the discount rate. A key unknown factor is the speed of economic recovery with and without social distancing measures in place. A series of robustness checks also highlight the key role of the value of mortality risk reductions and discounting in the analysis and point to a need for effective economic stimulus when the outbreak has passed.
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The aim of the article is to present the financial condition of selected dairy cooperatives using ratio analysis and selected discriminant models. The main objective of the paper is to assess the overall financial condition of dairy cooperatives during the COVID-19 pandemic (2020-2021) and earlier years (2017-2019). The author focused, on the one hand, on the assessment of the financial condition of a selected group and, on the other hand, on the link between the financial situation of selected dairy cooperatives and state aid during the changing economic reality caused by the SARS CoV-2 virus. The financial analysis for dairy cooperatives also reveals a broader comparative context in the time span before and during the COVID-19 pandemic. The research shows that the analysed dairy cooperatives, with the exception of OSM Jasienica Rosielna, did not have a negative financial results.
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The severity of the COVID-19 pandemic on overall welfare depends on the resilience of microeconomic units, particularly households, to cope and recover from the shocks created by the pandemic. In Sub-Saharan Africa, where the pandemic has been less pervasive, the pandemic is expected to increase food insecurity, vulnerability, and ultimately poverty. To accurately measure the welfare impact of the pandemic on the macroeconomy, it is important to account for the distributional impact on households and the ability of households to cope with it, which reflects their microeconomic resilience. In this paper, we seek to determine the differential impacts of the COVID-19 pandemic on household microeconomic resilience in Sub-Saharan Africa. We use direct measurements of economic indicators to measure the impact of the pandemic on 6249 households across Ethiopia and Nigeria. Given that resilience is a latent variable, the FAO's Resilience Index Measure Analysis (RIMA) framework is utilized to construct the resilience index. We hypothesize that the pandemic created differential economic impacts among households and ultimately household microeconomic resilience. Study findings show that government containment measures improved household microeconomic resilience, while self-containment measures lowered microeconomic resilience. Additionally, households that relied on wage employment and non-farm businesses as their main source of livelihood were found to be more microeconomic resilient.
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This paper studies quantile regression for spatial panel data models with varying coefficients, taking the time and location effects of the impacts of the covariates into account, i.e., the implications of covariates may change over time and location. Smoothing methods are employed for approximating varying coefficients, including B-spline and local polynomial approximation. A fixed-effects quantile regression (FEQR) estimator is typically biased in the presence of the spatial lag variable. The wild bootstrap method is employed to attenuate the estimation bias. Simulations are conducted to study the performance of the proposed method and show that the proposed methods are stable and efficient. Further, the estimators based on the B-spline method perform much better than those of the local polynomial approximation method, especially for location-varying coefficients. Real data about economic development in China are also analyzed to illustrate application of the proposed procedure.
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The COVID-19 pandemic resulted in a dramatic increase in the utilization of telerheumatology. However, the economics of telerheumatology have not been comprehensively explored, and optimal approaches to its implementation and appropriate use have not been determined. A survey of the available health economic literature on telerheumatology is presented and reveals a paucity of studies with limited data of poor quality. The knowledge gaps and limitations in the available literature are summarized in the context of prior recommendations that improved the methodology of economic studies of telemedicine in other medical specialties. Telerheumatology-specific recommendations for health economic analyses are presented with the goal of generating actionable data for use in policy and coverage decisions. An approach to stakeholder-specific telerheumatology value analysis is presented including the application of patient-reported metrics of experience and outcome, awareness of the pivotal role of clinicians as gatekeepers for telerheumatology adoption, the impact of implementation strategies on programmatic value and sustainability, and the importance of value-driven coverage determination to engender a sense of legitimacy across stakeholder groups. Novel approaches to the evaluation of programmatic value that combine value-based healthcare and health economic analysis and capture divergent stakeholder value perspectives are presented. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
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Under the development pattern of the "double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city's affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks;(2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow;(3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience;and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size.
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Through fiscal policy, the government can influence businesses and individuals in order to regulate their behaviour. The research used panel data from all 27 EU countries covering the period 2008–2020 to investigate the impact of direct taxation on economic growth at the level of two main clusters of countries concerning fiscal efficiency. Therefore, the analysis employed cluster methods to classify the main EU countries in both groups of countries with a high level of fiscal efficiency and those with a rather limited level of fiscal efficiency. The study employs fixed effect models and dynamic GMM methods to investigate the effect of direct taxation components (personal and corporate income taxes) on economic growth. The analysis also considers the informal economy's role in relation to the official economy. The empirical results revealed that corporate income taxes significantly negatively impact economic growth for both clusters of high- and limited fiscal efficiency countries. Additionally, personal income tax was associated with lower economic growth for countries in the limited fiscal efficiency group. Thus, from the perspective of policymakers, lowering direct taxation can increase disposable income, stimulate consumption and economic growth, encourage investment leading to job creation, increase competitiveness, and reduce tax evasion and avoidance, thereby leading to a more efficient tax system.
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Last year, Chile updated its Nationally Determined Contributions, moving from intensity-based emissions reductions to an effective emissions target. This paper aims to assess the economic and environmental impacts of this change in the current context of high uncertainty Chile faces with social protests and the COVID-19 pandemic. Using the computable general equilibrium model GEMINI-E3, we performed a sensitivity analysis assuming different levels of economic growth through 2030. Though at first glance the revised commitments appear more ambitious, we found that they could lead to higher emissions in low-growth scenarios. The results show that intensity-based emissions targets indeed become less stringent when assuming high levels of economic growth and thus may result in highly uncertain effective emissions in 2030. On the other hand, given the uncertainty surrounding Chilean economic growth, the updated commitments would be politically more amenable as it would lead to lower welfare losses. In addition, we analyze different redistribution schemes of a CO2 tax and we show that a per capita redistribution rule makes the CO2 tax more progressive and thus fiscally more acceptable.
ABSTRACT
The objective of this research is to develop a monthly indicator that synthesizes the economic acti-vity of the construction sector in Valle del Cauca, as a tool for analyzing the production cycle and as a single, public measure that contributes to decision-making. Dynamic factorial models, the Kalman filter and the Litterman method are used, also employed in the Monthly Index of Economic Activity (IMAE), in order to capture signals, changes in the productive cycle of construction and compile the sectoral economic facts that affect production. In the results, the dynamics of the sectoral and economic variables are observed that explain the behavior of the sector in Valle del Cauca during 2009-2020. A change of slope is observed in 2020, as a direct consequence of the crisis generated by COVID-19 and the restrictive measures taken by the government to contain its advance.
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Non-pharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic (and previous health crises) have included measures to restrict interaction between people and minimize non-essential mobility. Therefore, tourism travel is one of the main areas affected by the restrictions. Even when the majority of the population is vaccinated, some risk of infection will remain, and governments are obliged to consider NPI measures that balance the health risk of outbreaks against the economic and social benefits of resuming tourist activity. This study analyzes the effect of each of four categories of NPIs (Social Distancing;Public Healthcare-System Improvements;Tourist Controls;and Capacity and Opening-Hours Regulation) on three major objectives (the resumption of tourism activity;tourist travel intention;and the minimization of public health risk), taking a triangular perspective (destination managers, domestic tourists, and public healthcare managers, respectively). While it is difficult to fulfil public healthcare objectives while simultaneously responding to the economic interests of tourism-industry stakeholders, the study finds that, under vaccinated-population conditions, tourist controls (e.g. COVID Certificate) alongside improvements to the public healthcare system (e.g. adequate resourcing and an efficient epidemiological monitoring system) could constitute a viable combination of measures.
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In increasingly energy-dependent world, there is a question mark over the viability of fossil fuel resources. To tackle this issue, an integrated poly-generation system based on concentrated solar power is proposed to feed in the city grid and produce hydrogen as a clean energy carrier. Concerning the COVID-19 outbreak, all countries are in dire need of oxygen. Therefore, the produced oxygen in this system can be considered as an added value. The introduced scheme applies solar energy to supply thermal energy to a Brayton cycle. Two bottoming Rankine cycles are employed to empower a PEM electrolyzer using the residual heat from the gas turbine. The system is modelled using the Engineering Equations Solver for a comprehensive thermo-economic analysis. The exergy destruction analysis proved a significant loss of exergy by the solar field, illustrating the necessity to address this in future research. Afterwards, six design variables were selected and then optimized for the proposed system using the NSGA-II. Based on the TOPSIS approach, exergy efficiency, and capital cost rate, the objective functions were 22.2% and 272.6 $/h, respectively. Finally, a case study was performed to investigate the impact of solar irradiation and ambient temperature on system outputs. © 2021 The Author(s)