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Purpose - study aims to investigate the relationships between global value chain (GVC)-and transportation-related determinants and economic performance. Also, moderating effects of COVID-19 on the relationships are theoretically and empirically discussed. A limitation of previous studies includes their over-reliance on the opportunities of GVC participation and larger transportation. This study represents the challenges associated with them. Also, it shows how GVC and logistics can be difficult in case of a market fluctuation such as COVID-19.Design/methodology - The sample for this study includes 828 observations from 138 countries. A semi-panel data set has been used. Six observations for each country are used to empirically test the hypotheses and a Two-way cluster model is conducted.Findings - It is confirmed that GVC forward participation contributes more than the backward participation to enhance performance. Transportation infrastructure is critical, but large scales of marine and air transportations are not positive in terms of economic performance. Stricter government response to COVID-19 negatively moderates economic performance by GVC backward participation and transportation infrastructure.Originality/value - The spread of COVID-19 is causing a severe collapse of GVC and transportation. This study empirically verifies the moderating effects of the government stringency on GVC and transportation. Previous studies usually discuss a positive impact of GVC and transportation size on economic performance. However, this study aims to show various challenges behind GVC participation and large scale transportation.
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PurposeThe empirical analysis dealt in this paper emphasizes on the impact of military expenditures on out of pocket (OOP) healthcare payments. A sizeable body of defence economics literature has investigated the trade-off between military and public health expenditure, by testing the crowding-out or growth-stimulating hypothesis;does military expenditure scaling up crowd-out or promote governmental resources for social and welfare programs, including also state health financing?Design/methodology/approachIn this study, panel data from 2000 to 2018 for 129 countries is used to examine the impact of military expenditure on OOP healthcare payments. The dataset of countries is categorized into four income-groups based on World Bank's income-group classification. Dynamic panel data methodology is applied to meet study objectives.FindingsThe findings of this study indicate that military expenditure positively affects OOP payments in all the selected groups of countries, strongly supporting in this way the crowding-out hypothesis whereby increased military expenditure reduces the public financing on health. Study econometric results are robust since different and alternative changes in specifications and samples are applied in our analysis.Practical implicationsUnder the economic downturn backdrop for several economies in the previous decade and on the foreground of a potential limited governmental fiscal space related to the Covid-19 pandemic adverse economic effects, this study provides evidence that policy-makers have to adjust their government policy initiatives and prioritize Universal Health Coverage objectives. Consequently, the findings of this study reflect the necessity of governments as far as possible to moderate military expenditures and increase public financing on health in order to strengthen health care systems efficiency against households OOP spending for necessary healthcare utilization.Originality/valueDespite the fact that a sizeable body of defence economics literature has extensively examined the impact of military spending on total and public health expenditures, nevertheless to the best of our knowledge there is no empirical evidence of any direct effect of national defence spending on the main private financing component of health systems globally;the OOP healthcare payments.
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Greenhouse gas emissions, including carbon dioxide and non-CO2 gases, are mainly generated by human activities such as the burning of fossil fuels, deforestation, and agriculture. These emissions disrupt the natural balance of the global ecosystem and contribute to climate change. However, by investing in renewable energy, we can help mitigate these problems by reducing greenhouse gas emissions and promoting a more sustainable future. This research utilized a panel data model to explore the impact of carbon dioxide and non-CO2 greenhouse gas emissions on global investments in renewable energy. The study analyzed data from 63 countries over the period from 1990 to 2021. Firstly, the study established a relationship between greenhouse gas emissions and clean energy investments across all countries. The findings indicated that carbon dioxide had a positive effect on clean energy investments, while non-CO2 greenhouse gas emissions had a negative impact on all three types of clean energy investments. However, the impact of flood damage as a representative of climate change on renewable energy investment was uncertain. Secondly, the study employed panel data with random effects to examine the relationship between countries with lower or higher average carbon dioxide emissions and their investments in solar, wind, and geothermal energy. The results revealed that non-CO2 greenhouse gas emissions had a positive impact on investments only in wind power in less polluted countries. On the other hand, flood damage and carbon dioxide emissions were the primary deciding factors for investments in each type of clean energy in more polluted countries.
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This study aims to reveal the impacts of Covid-19 vaccination on Covid-19 based deaths in countries with different income levels. In this context, the study investigated data between 01.03.2021 and 08.08.2021 by Panel data analysis. In the research, firstly, countries were divided into three different categories according to income groups: low-income level, middle-income level and high-income level. Therefore, each country group was examined separately and three different econometric models were produced. According to the results of the research, a 1% increase in the population vaccinated will result in a 2.1% decrease in the number of deaths from Covid-19 in low-income countries, a 0.5% decrease in middle-income countries and a 13% decrease in high -income countries. According to the results of the research, it was concluded that vaccination will significantly reduce deaths from Covid-19. For this reason, it is recommended that people complete their vaccine doses as fast as possible.
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This article attempts to examine the recent developments that have amplified the consequences of uncertainty regarding trade between Brazil, Russia, India, China, and South Africa (BRICS) countries under global economic turmoil such as occurred in the 2008 financial crisis and trade wars sparked by the USA and the COVID-19 pandemic. These events severely affected intraBRICS trade and investment. For this purpose, we employed the Westerlund and Edgerton cointegration approach to check for cointegration under structural breaks and the procedure for the asymmetric Granger non-causality test to assess the causal relationship between the custom tariff and export variables of BRICS countries with regard to the panel data methodology for the 2000-2020 period using annual data. The empirical results for cointegration indicate the presence of a long-term relationship;in other words, they are seen to move together under investigation. The estimated breakpoints correspond with 2008 and the ongoing financial turmoil and with the 2018-2020 period and the rising trade disputes between USA and China. In addition, the Granger non-causality test provides enough evidence to show opposite directions (signs) for the causal links between the variables that run from tariffs to exports for BRICS countries.
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The role of Information and Communications Technology (ICT) cannot be ignored in today's era of working. Its effects are studied in several sectors by various researchers. This study covers the impact of ICT on the profitability of banks. Thirty-three banks are operating in India. A sample period of 10 years (2010 to 2019) was studied. The study also provides insight into how ICT helps the banks' profitability during and post-COVID-19. A panel data analysis is performed to estimate the results. This study found that ICT adversely impacts banks' profitability (NIM) in India in a linear association. However, the quadratic association indicates a positive U-curved relationship between ICT and profitability. In addition, the Net of Non-Performing Assets significantly but negatively impacts the connectivity of ICT and profitability. The findings imply that banks should invest in ICT to maximize the long run. The findings have no significant implication on all stakeholders, including policymakers, shareholders, and managers, to consider implementing ICT tools as an essential factor in enhancing a bank's profitability in the long run. In addition, the level of otherwise lowered investments in ICT cannot be a fruitful step. The current study augments the existing literature on banking by providing novel evidence on the association of ICT with profitability under the influence of NPA. This study argues for the application of ICT in banks in order to increase their profitability. ICT helps the bank maintain transparency, accountability, and even the reach of financial services increases. This situation again leads to the enhancement of the country's economy.
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Digital transformation of public administration creates opportunities for transparency, accountability, efficiency, and better tax collection. Benefits are even more critical considering the coronavirus crisis when millions of people worldwide engage in online solutions. Our research paper offers clear insights into the public administrations' strategic management when it comes to the impact of digitalization upon local tax revenues collection. In this setting, we investigate the effects of the digitalization of the Romanian public sector, focusing on local tax revenues collection covering the period 2015–2021. The data was collected from the national platform for e-payments – ghiseul.ro. To assess the impact of digitalization, we opted for the panel data analysis, complemented by reliability and robustness tests. The local tax revenues are settled as the dependent variable and analysed in relationship with the number of payments made via the above-mentioned platform (assigned as a proxy for digitalization). Gross domestic product per capita, Unemployment rate, and Average net earnings are control variables. Our outcomes show that digitalization impacts local tax revenues, but it differs across the country, the highest impact being registered in the case of macro-region 3. All independent variables are statistically significant, leading to the assumption that the empirical model is accurate. © 2023 The Author(s).
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Alongside economic development, trade enhancement and digitalization, both e-commerce and m-commerce have increased gradually over the last decade and are forecasted to increase further over the following years. In the latest years, one of the most important catalyzers of these evolutions was the emergence of the COVID-19 pandemic. Within this paper, we aim at assessing the impact of some structural economic and social factors upon m-commerce. Specifically, we test the relationship between m-commerce and digitalization, education, economic growth, unemployment and income inequalities within three different clusters of countries of the European Union, for the period 2010 - 2020, using panel date regression models. Our results confirm a positive relationship between m-commerce and digitalization, education and economic growth, while showing a negative link between m-commerce and unemployment in all clusters. On the other hand, our empirical analysis concludes upon quite different results across the three clusters, when considering the relationship between m-commerce and income inequalities. © 2022, Bucharest University of Economic Studies. All rights reserved.
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Voluntary shelter-in-place directives and lockdowns are the main nonpharmaceutical interventions that governments around the globe have used to contain the Covid-19 pandemic. In this paper, we study the impact of such interventions in the capital of a developing country, Santiago, Chile, that exhibits large socioeconomic inequality. A distinctive feature of our study is that we use granular geolocated mobile phone data to construct mobility measures that capture (1) shelter-in-place behavior and (2) trips within the city to destinations with potentially different risk profiles. Using panel data linear regression models, we first show that the impact of social distancing measures and lockdowns on mobility is highly heterogeneous and dependent on socioeconomic levels. More specifically, our estimates indicate that, although zones of high socioeconomic levels can exhibit reductions in mobility of around 50%-90% depending on the specific mobility metric used, these reductions are only 20%-50% for lower income communities. The large reductions in higher income communities are significantly driven by voluntary shelter-in-place behavior. Second, also using panel data methods, we show that our mobility measures are important predictors of infections: roughly, a 10% increase in mobility correlates with a 5% increase in the rate of infection. Our results suggest that mobility is an important factor explaining differences in infection rates between high- and low-incomes areas within the city. Further, they confirm the challenges of reducing mobility in lower income communities, where people generate their income from their daily work. To be effective, shelter-in-place restrictions in municipalities of low socioeconomic levels may need to be complemented by other supporting measures that enable their inhabitants to increase compliance. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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Most cross-country empirical studies on economic growth ignore ambiguity. We argue that ambiguity should matter a priori, given the open-endedness of growth theories. Moreover, ambiguity has received a lot of attention since the great financial crisis (GFC) of 2008, and more recently after COVID-19 and the war in East Europe. Using annual data from the Penn World Table covering 12 East Asian economies from 1954 to 2019, we show that beyond economic factors documented in the current debate about the East Asian miracle, economic agents' confidence shocks about the global economy (one dimension of ambiguity) have a significant negative impact on total factor productivity (TFP) growth. However, correlation uncertainty (another dimension of ambiguity) is low in the region given the persistent high level of connectedness of its productivity network. The empirical results are policy-relevant given that ambiguity, unlike rational expectations, implies that economic agents' beliefs are not policy invariant.
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Russia is one of the few countries in the world that has opted for almost no policy measures involving the strong suppression of economic activity in the face of the epidemic disaster brought about by the new coronavirus (COVID-19). This makes Russia a valuable subject of social experiments through which the association between economic activity and the spread of the virus can be explored. This paper presents a dynamic panel data analysis to examine the extent to which different types of economic activity contribute to the spread of COVID-19 infection using monthly and quarterly panel data of Russian regions between March 2020 and April 2021. The results strongly supported our expectation that economic activities have a greater impact on the levels of COVID-19 transmission when they involve a larger number of inhabitants or stimulate greater consumption or social activities among citizens. It was also revealed that Russian regions vary greatly in terms of the routes that link economic activity to the spread of COVID-19. These results have important policy implications for current and future epidemic control.
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The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.
Subject(s)
COVID-19 , Health Communication , Humans , United States , Search Engine , Communicable Disease Control , QuarantineABSTRACT
Banks, which are important actors of the overall economy and the financial system, are directly and indirectly affected by the developments in the global and national economy and continue their activities by being exposed to various risks. Therefore, the risks that banks are exposed to and the management of these risks are important. Liquidity risk, which is among the risks mentioned above, is of vital importance for banks and requires proactive management. In this context, this study aims to reveal the internal and external determinants of the Liquidity Coverage Ratio, which is an indicator of the liquidity level of banks in the Turkish banking sector, covering the Covid-19 period. The quarterly data of 19 commercial and 4 participation banks operating in Turkey between 2015/12 and 2021/9 were analysed by panel data analysis method within the scope of the established models. As a result of the analysis, it was concluded that there are statistically significant relationships between the liquidity level of the Turkish banking sector, which consists of deposit and participation banks within the scope of the sample, and bank-specific deposits, loan deposit ratio, return on equity, capital adequacy ratio, equity and asset size and macroeconomic factors money supply, credit default swap, control variable Covid period. (English) [ FROM AUTHOR]
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Environmental sustainability is essential in tourism literature, and sun-and-beach tourism (SBT) is one of the most popular subsections of the tourism field. The appropriate policies and strategies during the COVID-19 pandemic to revive SBT growth through the lens of the regulatory dimension (RED) and risk dimension (RID) of environmental sustainability are gaining timely ground to conduct this research. The current study examined the nexus between SBT, RED, and RID utilizing three novel indexes (i.e., weighted sun-and-beach tourism index, weighted regulatory dimension index, and weighted risk dimension index) by employing the principal component analysis within the framework of six stages of empirical estimation strategy. These three novel indexes combine the most commonly used SBT, RED, and RID indicators. This research tested the CSD and homogeneous, then employed the second generation CIPS-CADF panel unit root test, used an AMG estimator, and employed the panel Toda-Yamamoto (PTY) causality test. The findings revealed that the RED positively influences SBT while the RID mitigates SBT. Results also indicate bidirectional causality between SBT, RID, and RED. In other words, changes in RID and RED have predictive power for the SBT, which further highlights the role of SBT on the RID and RED. Therefore, concerned authorities can focus on environmental sustainability design initiatives and appropriate policy/strategy implications to boost SBT.
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The main objective of this study was to analyze the effect of COVID-19 on social welfare in the case of Afar regional, state, Ethiopia using panel data collected from a sample of 384 in Asyaita, Dubti Samara-Logia, and Awash town. Both descriptive statistics and econometric models were used to analyze the data. The descriptive analysis results revealed that the main source of income emanated from self-employment (81.67%), from the total households 70% of them were engaged in the service sector, due to COVID-19 the income trends of 81% of households decreased, increase expenditure on food & food items (13%) and service delivering (15%). After conducting necessary pre and post-estimation tests, the econometric model found that the three basic policy variables (number of COVID-19 victims, number of days with the COVID-19 disease and transportation ban) adversely affected the welfare of the society by lessening the income of households and growing their expenditures. Finally, considering regional experience, econometric and descriptive results, this study recommends that the government and the concerned policy maker should give more attention and subsidize the service sector, support those self-employee and daily laborers, make awareness to the society about COVID-19 epidemic, place an alternative mechanism to fill potential trade gaps.
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This paper quantitatively analyzes the trade-off between job losses and the spread of COVID-19 in Japan. We derive an empirical specification from the social planner's resource constraint under the susceptible, infected, recovered, and deaths (SIRD) model and estimate how job losses and the case growth rate are related to people's mobility using the Japanese prefecture-level panel data on confirmed cases, involuntary job losses, people's mobility, and teleworkability. Our findings are summarized as follows. First, we find that a decrease in mobility driven by containment policies is associated with an increase in involuntary job separations, but the high teleworkability mitigates the negative effect of decreased mobility on job losses. Second, estimating how the case growth is related to people's mobility and past cases, we find that the case growth rate is positively related to an increase in people's mobility but negatively associated with past confirmed cases. Third, using these estimates, we provide a quantitative analysis of the trade-off between job losses and the number of confirmed cases. Taking Tokyo in July 2020 as a benchmark, we find that the cost of saving 1 job per month is 2.3 more confirmed cases per month in the short run of 1 month. When we consider a trade-off for 3 months from July to September of 2020, protecting 1 job per month requires 6.6 more confirmed cases per month. Therefore, the trade-off becomes worse substantially in the longer run of 3 months, reflecting the exponential case growth when the people's mobility is high.
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Purpose The empirical analysis dealt in this paper emphasizes on the impact of military expenditures on out of pocket (OOP) healthcare payments. A sizeable body of defence economics literature has investigated the trade-off between military and public health expenditure, by testing the crowding-out or growth-stimulating hypothesis;does military expenditure scaling up crowd-out or promote governmental resources for social and welfare programs, including also state health financing? Design/methodology/approach In this study, panel data from 2000 to 2018 for 129 countries is used to examine the impact of military expenditure on OOP healthcare payments. The dataset of countries is categorized into four income-groups based on World Bank's income-group classification. Dynamic panel data methodology is applied to meet study objectives. Findings The findings of this study indicate that military expenditure positively affects OOP payments in all the selected groups of countries, strongly supporting in this way the crowding-out hypothesis whereby increased military expenditure reduces the public financing on health. Study econometric results are robust since different and alternative changes in specifications and samples are applied in our analysis. Practical implications Under the economic downturn backdrop for several economies in the previous decade and on the foreground of a potential limited governmental fiscal space related to the Covid-19 pandemic adverse economic effects, this study provides evidence that policy-makers have to adjust their government policy initiatives and prioritize Universal Health Coverage objectives. Consequently, the findings of this study reflect the necessity of governments as far as possible to moderate military expenditures and increase public financing on health in order to strengthen health care systems efficiency against households OOP spending for necessary healthcare utilization. Originality/value Despite the fact that a sizeable body of defence economics literature has extensively examined the impact of military spending on total and public health expenditures, nevertheless to the best of our knowledge there is no empirical evidence of any direct effect of national defence spending on the main private financing component of health systems globally;the OOP healthcare payments.
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Purpose>In this paper, the authors assess the responsiveness of OOP healthcare expenditure to macro-fiscal factors, as well as to tax-based, SHI, mixed systems and voluntary PHI financing. Although the relationship between OOP expenditure, macroeconomy, aggregate public and PHI financing is well documented in the existing empirical literature, little is known for the impact of several macro-fiscal drivers and the existing health financing arrangements associated with voluntary PHI on OOP expenditure.Design/methodology/approach>The authors gather panel data by applying three official organizations’ databases. They elaborate static and dynamic panel data methodology to a dataset of 49 European and OECD countries from 2000 to 2015.Findings>The authors’ findings do not indicate a considerable impact of GDP growth and general government debt as a share of GDP on OOP payments. Unemployment rate presents as a positive driver of OOP payments in all three compulsory national health systems post to the 2008 economic crisis. OOP payments are significantly influenced by countries’ fiscal capacity to increase general government expenditure to GDP in SHI and mixed health systems. Additionally, study findings present that government health financing, irrespective of the different health systems structure characteristics, and OOP healthcare payments follow different directions. Voluntary PHI financing considerably counteracts OOP payments only in tax-based health systems.Practical implications>In the backdrop of a new economic crisis associated to the COVID-19 epidemic, health policy planners have to deal with the emerging unprecedented challenges in financing of health systems, especially for these economies that have to face the fiscal capacity constraints owing to the 2008 financial crisis and its severe recession.Originality/value>To the best of authors’ knowledge, there is no empirical consensus on the effects of macro-fiscal parameters, different compulsory health systems financing associated with the parallel voluntary PHI institution funding on OOP expenditure, for the majority of European and OECD settings.
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Purpose>This paper aims to investigate and provide an objective appraisal of the impact of the COVID-19 outbreak on Islamic and conventional financial institutions and Islamic windows in the Gulf Cooperation Council (GCC) countries.Design/methodology/approach>The panel data techniques are conducted country-wise in each financial institution type: random-effect model, fixed-effect model and Hausman test.Findings>The results of the first phase analysis that extends from 1 January 2020 to 30 October 2020 show that Islamic financial institutions are less exposed to the repercussions of the COVID-19 outbreak than the conventional and Islamic window financial institutions in Bahrain, Oman, Qatar, Saudi Arabia and UAE. Moreover, the Islamic financial institutions in Saudi Arabia and Oman have not been affected by the COVID-19 outbreak. The second phase analysis for the COVID-19 outbreak that extends from 1 November 2020 to 17 March 2021 confirms the disappearance of the negative impact of COVID-19 on Islamic financial institutions in Bahrain and Oman.Practical implications>The findings present that Islamic banks are not as resilient in the COVID-19 pandemic as in the 2008 financial crisis. It can be suggested that regulatory authorities, financial institutions and other key policymakers in the GCC countries should focus on implementing regulatory reforms related to human capital, innovative products, research and development to further develop individuals, societies and institutions within the framework of Islamic ontology to be more resilient in such crises.Originality/value>This paper provides a different perspective from existing literature on the pandemics and financial institutions by comparing the stock prices in Islamic and conventional financial institutions and Islamic windows in GCC countries during the COVID-19 pandemic. Therefore, this paper should be considered as a contribution to filling a gap in the literature.
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This paper addresses the issue of fruit and vegetable purchases in the UK during the COVID-19 pandemic. The study is motivated by the importance of fruit and vegetables for human nutrition, health and reduction of population obesity, especially in the UK where per capita consumption is still below recommended levels. A rich panel dataset was used reporting actual shopping places and quarterly expenditure for at-home consumption of fruit and vegetable purchases of 12,492 households in years 2019 and 2020. The unique dataset allowed us to compare expenditure for fruit and vegetables before and after the COVID-19 outbreak and to identify the main drivers of changes in purchases. Regression analysis found that expenditure increased ~3% less than what expected given the overall increase in the numbers of at-home meals during lockdown. Also, Online shopping was found to be an alternative source for fruit and vegetables purchase during the pandemic. However, the expenditure for processed products grew more than the one for fresh products, resulting in a reduction of the relative share of the latter and possible deterioration of the diet quality.