Economies

Corporate social responsibility (CSR) has become an innovative strategic management tool of socially and environmentally conscious business organizations in the 21st century. Although external CSR activities are better researched, firms’ internal CSR activities such as workplace health promotion and its impact on employee wellbeing are less understood, especially during a pandemic where job security is relatively lower in many sectors of employment. Additionally, wellbeing and good health have been recognized as important targets to achieve as part of the United Nation’s Sustainable Development Goal 3. Therefore, this study investigates the relationship between health-related work benefits and employee wellbeing, satisfaction and loyalty to their workplace. Large scale survey research was performed with responses from 537 employees in Hungary and 16 hypotheses were tested. Data analysis and path modelling using PLS-SEM (Partial Least Squares Structural Equation Modelling) reveal two-layers of factors that impact employee wellbeing, satisfaction and loyalty. We term this as ‘internal locus of control’ and ‘external locus of control’ variables. Internal locus of control variables such as mental and emotional health leads to wellbeing at the workplace but do not directly impact employee satisfaction and loyalty. In contrast, external locus of control factors such as healthcare support leads to wellbeing, satisfaction and loyalty. Employer commitment to healthcare support system is found pertinent especially during the pandemic. We discover wellbeing as a unique standalone construct in this study, which is vital as is it formed by mental and emotional wellbeing of employees, albeit not a determinant of employee workplace satisfaction and loyalty. We theorize workers’ self-reliance and preservation as possible explanations to the disassociation between employee wellbeing and loyalty to workplace during times of crisis and the pandemic.

Facing the current complicated situation of the COVID-19 pandemic, in addition to medical efforts on disease prevention and treatment, governments of countries also have to come up with solutions to deal with the negative impacts of the pandemic on the economy. This study aims to provide specific, comprehensive, and scientific estimates of the impact of the COVID-19 pandemic on the Vietnamese economy. By using the Bayesian method to estimate DSGE models, research results show that a shock increase by one standard deviation (about 1.49% increase in the probability of a COVID-19 outbreak) to the COVID status variable immediately reduces the output gap by 0.94%. However, this effect only lasts for one quarter, and the output gap widens again. Meanwhile, refinancing interest rates, inflation, and exchange rate changes also have an immediate decline in response to this shock, but the magnitude of the reduction is relatively small.

Certain features of socioeconomic models can be distinctly determined in different countries and regions. However, such models are quite flexible under external and internal influences. Their changes can be observed under the impact of unpredictable factors, the COVID-19 pandemic being one. The aim of the work is to identify differences in the structure of socioeconomic models under the influence of the pandemic. The object of the study is the socioeconomic models of various states. The subject of the study is the transformation of socioeconomic models at different stages of the pandemic. Research methods include analysis of statistical data, correlation and comparative analysis, and graphical methods of presenting results. A comparison of data from the most well-known socioeconomic models was carried out for the first time. It is determined that the countries of the Chinese model adopted restrictive measures of high Stringency Index. The countries of the Japanese model used unique crowd management methods, and the countries of the Scandinavian, German and Anglo-Saxon models resorted to unprecedented monetary injections into the social and economic spheres. It was revealed that quarantine measures eventually cost countries less than monetary injections. It was shown that a decrease in the Pandemic Uncertainty Index stabilized the economic behavior of the population and businesses and increased the volume of export-import operations. It was found that the pandemic affected the economy indirectly through the level of uncertainty and rigidity of preventive measures. It is assumed that the intensity and severity of measures could be influenced by global trends leading to certain types of preventive measures rather than by the COVID-19 statistics of a particular country.

The COVID-19 pandemic has put immense pressure on the fiscal situation. Central revenues have decelerated while expenditures had to be increased to facilitate economic recovery. Local governments faced even harder challenges as intergovernmental transfers were reduced and room for mobilizing alternative finances was limited. This paper employs qualitative and secondary data analysis on local budget and fiscal capacities at the subnational level in Indonesia to find insights into the implications and responses of the provincial government in a decentralized economy during the pandemic. Provinces with a high dependence on intergovernmental transfer are struggling to adopt a countercyclical mitigative fiscal policy. However, provinces with high local own-source revenue have suffered the most during the crisis as low economic activity reduced tax revenues and indirectly lead to lower fiscal space. As fiscal policy is critical to containing the pandemic and facilitating recovery, this paper proposes several strategies toward a more sustainable fiscal policy for rebuilding local government capacity in the medium-to-long term in the aftermath of the crisis.

Systematic momentum trading is a prevalent risk premium strategy in different portfolios. This paper focuses on the performance of the managed futures strategy based on the momentum signal across different economic regimes, focusing on the COVID-19 pandemic period. COVID-19 had a solid but short-lived impact on financial markets, and therefore gives a unique insight into momentum strategies’ performance during such critical moments of market stress. We offer a new approach to implementing momentum strategies by adding macroeconomic variables to the model. We test a managed futures strategy’s performance with a well-diversified futures portfolio across different asset classes. The research concludes that constructing a portfolio based on academically/economically sound momentum signals with its allocation timing based on broader economic factors significantly improves managed futures strategies and adds significant diversification benefits to the investors’ portfolios.

We evaluated the movement in the daily number of COVID-19 cases in response to the real GDP during the COVID-19 pandemic in Thailand from Q1 2020 to Q1 2021. The aim of the study was to find the number of COVID-19 cases that could maintain circulation of the country’s economy. This is the question that most of the world’s economies have been facing and trying to figure out. Our theoretical model introduced dynamic stochastic general equilibrium (DSGE) models with a special emphasis on Bayesian inference. From the results of the study, it was found that the most reasonable number of COVID-19 cases that still maintains circulation of the country’s economy is about 3000 per month or about 9000 per quarter. This demonstrates that the daily number of COVID-19 cases significantly affects the growth of Thailand’s real GDP. Economists and policymakers can use the results of empirical studies to come up with guidelines or policies that can be implemented to reduce the number of infections to satisfactory levels in order to avoid Thailand lockdown. Although the COVID-19 outbreak can be suppressed through lockdown, the country cannot be locked down all the time.

The purpose of this research is to determine the organizational support and role played by MSME owners who have businesses based on financial technology during the COVID-19 and earlier periods. It also aims to determine the priorities that need to be considered in organizations in various conditions through fintech-based training. This is an experimental research with training given to the experimental group and none to the control. A paired-samples t-test analysis technique was used to determine the significant differences in the same group under different conditions. The result showed that fintech-based training is important in supporting organizations in the business groups that received training and those that have significant differences. Therefore, this training is needed, especially during crises such as the COVID-19 pandemic.

The COVID-19 pandemic has upset everyone’s normal daily activities, generating psychiatric disorders and changing consumers’ preferences. Among others, the agri-food sector has experienced strong changes and, during the lockdown period, Italian consumers modified their purchasing habits in response to the fear and uncertainty generated by the spread of the virus. In order to find out the main consequences of the shock suffered during the period and to understand which factors have affected purchasing choices, an online survey was conducted on 286 Italian consumers. The results show that ethnocentrism has been the factor that most has influenced consumers’ behavior during the lockdown period and that consumers will continue to prefer national agri-food products when pandemic will be over, constituting a deep change to future eating habits.

In recent decades, the emergence of global value chains (GVCs) has changed international trade patterns. Today, the production of goods involves international production sharing, which allows countries to trace the value-added distribution to international trade. However, the COVID-19 pandemic has lowered the trade intensity between countries and can disrupt many sectors. This study uses a dynamic panel approach with the generalized method of moments estimator to investigate the pandemic’s impact on GVC participation. We also investigate whether gross domestic product (GDP) per capita may influence GVC participation, and use institutional quality as control variables. We used the Asian Development Bank Multi-Regional Input-Output (ADB MRIO) data for the 2010–2020 period. We employ backward and forward linkage approaches based on value-added exports to address the overvaluation problems in gross exports. The empirical results illustrate that the COVID-19 pandemic led to a decrease in GVC participation, on average. Furthermore, GDP per capita plays a significant role in GVC participation in backward and forward linkages with higher-quality institutions.

Fiscal policies are one of the most important instruments of government to guide the progress of the country’s economic development. They find significant use in cases where the economy is experiencing a period of recession, such as the current one caused by COVID-19. This study aims to assess the multiplier effects that budget revision has on the economy for the case of Albania, and more specifically by referring to the initial and revised budget scenario for the year 2020 which is characterized by significant changes caused by the presence of COVID-19. Referring to the multipliers from the input–output tables (IOT) the total effect that the state budget brings to the economy for a certain year is derived. From this paper, it appears that the budget restructuring that takes place during the year does not take into account the multiplier effect in the economy, but is mostly done for specific purposes related to certain government functions. In this context, it is very important that various options during budget revision are evaluated, concluding with the option that has the highest returns for the economy.

We examine the effectiveness of sub-national actions to control a novel disease, such as COVID-19, in the absence of national policy. Evidence shows that countries where sub-national governments have undertaken unilateral social distancing measures to combat the pandemic with little or no coordination have performed less well in controlling the spread of the disease. We explore analytically whether agreement on a common social distancing policy among sub-national governments, i.e., states or provinces, can lead to a better outcome than if each state or province pursues its own social distancing policy in isolation. A key feature of our model is that it accounts for the inter-jurisdictional spillover effects of each sub-national jurisdiction’s policy choice with respect to social distancing. Our results show that, in the absence of a national mandatory agreement, a sub-national agreement with sufficient coordination of social distancing policy among states yields a more effective and efficient control of a pandemic compared to states choosing policy unilaterally. These findings strongly support calls for greater cooperation among and assistance for sub-national governments to improve the effectiveness of their social distancing efforts in controlling the pandemic.

This study examines the relationship between COVID-19, government response measures, and stock market volatilities for 11 developed and developing economies within the Asia-Pacific region. Our period of study is between 15 February–30 May 2020. Using the continuous wavelet transformation (CWT) analysis and plots and GJR-GARCH analysis, we examined the effects of the COVID-19 public health crisis and the corresponding government measures on the respective domestic equity markets volatilities. The CWT plots showed a varying level of market volatilities at different investment horizons. All the sample countries, except Japan, experienced very low or low volatility over the short-term horizons. In contrast, Vietnam, Malaysia, and Laos experienced medium volatility over the medium-term horizons. Finally, China, Japan, South Korea, Malaysia, and the Philippines experienced high volatility over the long-term horizons. The GJR-GARCH results further ascertain that market volatilities are affected by domestic events, notably, the COVID-19 government intervention measures. In most sample countries, the government measures significantly reduce market volatility in the domestic equity markets. Additionally, international events have also triggered market volatilities. Overall, our study offers several contributions and implications for practitioners and policymakers.

Today, online Muslim clothing providers in Indonesia are faced with increasing competition in business openness. This condition requires online Muslim clothing providers to be more creative, innovative, effective and efficient by offering Muslim clothing products that are more valuable than competitors’. Therefore, a sophisticated and smart technology planning concept is needed for Muslim fashion consumers and to continue to achieve the benefits obtained by online Muslim clothing providers. This study aims to determine: (1) the influence of attitudes on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis (2) the influence of subjective norm on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis (3) the influence of perceived behavioral control on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis (4) the effect of attitudes on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis moderated by religious belief, (5) the effect of subjective norm on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis moderated by religious belief, and (6) the effect of perceived behavioral control on the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis moderated by religious belief. This study uses 1. independent variables, namely: attitudes, subjective norms, and perceived behavioral control. 2. The dependent variable is: Purchase intention. 3. The moderating variable is: religion. The data in this study are obtained from questionnaires distributed to 762 respondents. The method used is purposive sampling to all respondents who shopped online. The method is through the LISREL 8.7 program and t-test. These results indicate that the variables of attitude, subjective norm and perceived behavioral control influence the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis. They also find that the religious belief variable can moderate the variable of attitude towards the online buying intention of Muslim clothing in Indonesia during the COVID-19 crisis but not the subjective norm and perceived behavioral control variables.

Emerging stock markets provide great opportunities for investment growth and risk diversification. However, they are more vulnerable to extreme market events. This study examines the effects of the COVID-19 pandemic on stock performance in sub-Saharan African stock markets. An event study method was used to determine whether there was any significant difference in sector returns before and during the pandemic, and panel data regression was used to determine the causal relationship between COVID-19 events and the abnormal returns observed. Four stock exchanges were chosen, including the two largest and two fastest-growing markets in sub-Saharan Africa. According to the study’s findings, the information technology, consumer staples, and healthcare sectors outperformed during the pandemic, while the industrials, materials, and real estate sectors underperformed. The financial and consumer discretionary proved to be the most stable sectors during the pandemic. We also observed that the imposition of lockdown had a negative impact on the performance of most sectors in sub-Saharan African markets, whereas government assistance in the form of economic stimulus packages had no significant positive impact on stock performance except in the South African market. Furthermore, we find that increases in COVID-19 cases and deaths had no negative impact on capital markets, where stocks have responded positively to economic recovery aid. The study concludes that during the COVID-19 pandemic, stocks reacted more to government actions than the occurrence of the pandemic itself.

Coronavirus (COVID-19), which hit in early 2020, changed the way people live and work, and affected industries and organizations all over the world. Many organizations have begun to deliver a new way of working to adapt to these shifts effectively using teleworking or a work from home policy. The purpose of this study was to fill the gaps by investigating several potential predictors of job satisfaction during working from home from the impact of COVID-19 such as work–life balance and work stress. Using a quantitative approach, 472 workers who were forced to work from home all over Indonesia participated, and the responses were analyzed using Smart-PLS software. The study revealed that working from home, work–life balance, and work stress have a significant effect, both directly and indirectly, on job satisfaction. Working from home as a new pace of work can sustain job satisfaction as the current working atmosphere for Indonesian workers. In response to the collectivist setting, working from home can be a positive sign that needs to be paid attention to for the organization.

This paper uses firm level data from World Bank Enterprise surveys conducted in 2019, and COVID-19 follow-up surveys conducted in 2020, in ten European countries to investigate the link between the gender of the firm’s owner and the firm’s survival until 2020. The empirical investigation uses econometric models that control for the firm’s characteristics that are known to be related to firm survival. The estimated effect of female ownership is positive ceteris paribus. Furthermore, the size of this estimated effect can be considered to be large on average. Having a female owner helped firms to survive.

The COVID-19 pandemic has introduced significant uncertainty across various economic sectors, most notably in the industrial sector due to the high volatility in copper futures markets. These markets play a crucial role in the construction, electrical networks, electronic products, and industrial machinery industries. Therefore, the aim of this study is to evaluate the impact of the COVID-19 pandemic on the volatility of copper futures returns from 2 January 2018 to 30 December 2022 using an extended ARMA(m,n)–GARCH(p,q) framework. According to the results, the occurrence of the pandemic nearly doubled the long-run equilibrium volatility of returns compared to the values obtained in the pre-pandemic period. Hence, we conclude that the COVID-19 pandemic has a significant influence on the volatility in the copper futures market.

In this study, we utilize an input–output (I–O) model to perform an ex-post analysis of the COVID-19 pandemic workforce disruptions in the Philippines. Unlike most disasters that debilitate physical infrastructure systems, the impact of disease pandemics like COVID-19 is mostly concentrated on the workforce. Workforce availability was adversely affected by lockdowns as well as by actual illness. The approach in this paper is to use Philippine I–O data for multiple years and generate Dirichlet probability distributions for the Leontief requirements matrix (i.e., the normalized sectoral transactions matrix) to address uncertainties in the parameters. Then, we estimated the workforce dependency ratio based on a literature survey and then computed the resilience index in each economic sector. For example, sectors that depend heavily on the physical presence of their workforce (e.g., construction, agriculture, manufacturing) incur more opportunity losses compared to sectors where workforce can telework (e.g., online retail, education, business process outsourcing). Our study estimated the 50th percentile economic losses in the range of PhP 3.3 trillion (with telework) to PhP 4.8 trillion (without telework), which is consistent with independently published reports. The study provides insights into the direct and indirect economic impacts of workforce disruptions in emerging economies and will contribute to the general domain of disaster risk management.

The first stream of economic studies on public policy responses during the COVID-19 pandemic focused on the stringency, the effectiveness, and the impact of the countries’ interventions and paid rather little attention to the corresponding means used to support them. The present paper scrutinizes the lockdown measures and, particularly, examines the optimality of the lockdown fines imposed by countries worldwide towards ensuring citizens’ compliance. Initially, a triad of fine stringency indicators are compiled, and the stringency of fines is evaluated in a comparative context, among the countries considered. Consequently, the fine stringency is incorporated into a regression analysis with various epidemiological, socioeconomic, and policy factors to reveal any drivers of fine variability. Finally, theoretical approaches behind fine optimality are capitalized and real data are used towards estimating the optimal fine for each country considered. The objectives of the paper are, first, to check for any drivers of fine stringency around the world and, second, to develop and test a formula that could be used in order to assist policy makers to formulate evidence-based fines for confronting the pandemic. The findings of the paper highlight that fines do not seem to have been imposed with any sound economic reasoning and the majority of countries considered imposed larger real fines, compared to the optimal ones, to support the lockdowns. The paper stresses the need for the imposition of science-based fines that reflect the social cost of non-compliance with the lockdown measures.

The COVID-19 pandemic and pandemic-induced lockdowns and quarantine establishments have inevitably affected individuals, businesses, and governments. At the same time, the spread of the COVID-19 pandemic had a dramatic impact on financial markets all over the world and caused an increased level of uncertainty; the stock markets were no exception either. Most of the studies on the impact of the COVID-19 pandemic on stock markets are based either on the analysis of a relatively short period (the beginning of pandemic) or a longer period, which, in turn, is very heterogeneous in terms of both the information available on the COVID-19 virus and the measures taken to contain the virus and address the consequences of the pandemic. However, it is very important to assess the impact not only at the beginning of the pandemic but also in the subsequent periods and to compare the nature of this impact; the studies of this type are still fragmentary. Therefore, this research aims to investigate the impact of the COVID-19 pandemic on stock markets of two of the most severely affected European countries—Italy and Spain. To reach the aim of the research OLS regression models, heteroscedasticity-corrected models, GARCH (1,1) models, and VAR-based impulse response functions are employed. The results reveal that the stock market reaction to the spread of the COVID-19 pandemic differs depending on the country and period analyzed: OLS regression and heteroscedasticity-corrected models have not revealed the statistically significant impact of the spread of the COVID-19 pandemic, while impulse response functions demonstrated the non-zero primary response of analyzed markets to the COVID-19 shock, and GARCH models (in the case of Spain) confirmed that the COVID-19 pandemic increased the volatility of stock market return. This research contributes to the literature by providing a comprehensive impact assessment both during the whole pre-vaccination period of the pandemic and during different stages of this period.

Credit is considered as an essential tool to make informal labor’s income better. In order to improve quality of their life, the state should have some supports them in credit access. This study analyzes factors causing credit access of informal labors to be changed in the time of COVID-19 pandemic. Using survey data collected from 2020 VHSSL (2019–2020), this approach has two models including a binary logit model and a multinomial logit model (MLM). The results revealed that the positive factors including education, material, collateral, credit size, credit source, credit debt which are likely to affect to credit access, however age, family size, ethnicity, interest, paid money are negative. Besides, it also concludes that quality of life of informal labor is considerably influenced by credit access, collateral, credit source, credit debt from the observed samples. Additionally, this paper recommends some policies to enhance informal labor’s access to credit and their quality of life.

One of the most difficult problems analysts and decision-makers may face is how to improve the forecasting and predicting of financial time series. However, several efforts were made to develop more accurate and reliable forecasting methods. The main purpose of this study is to use technical analysis methods to forecast Jordanian insurance companies and accordingly examine their performance during the COVID-19 pandemic. Several experiments were conducted on the daily stock prices of ten insurance companies, collected by the Amman Stock Exchange, to evaluate the selected technical analysis methods. The experimental results show that the non-parametric Exponential Decay Weighted Average (EDWA) has higher forecasting capabilities than some of the more popular forecasting strategies, such as Simple Moving Average, Weighted Moving Average, and Exponential Smoothing. As a result, we show that using EDWA to forecast the share price of insurance companies in Jordan is good practice. From a technical analysis perspective, our research also shows that the pandemic had different effects on different Jordanian insurance companies.

Okun’s law is formulated as the ratio between GDP and unemployment (UE): β = f(GDP/UE). It is used to investigate the relations between output and labor input across regions or across business cycles. Based on results by James D. Hamilton we replaced the United States UE with employment (EM) for the years 1977 to 2021 and examined how employment changed relative to output during recessions and recoveries. We found that (i) EM was leading GDP before and lagging GDP after all recessions, except the 2020 recession. (ii) The βE(9) = GDP/EM for rolling ordinary linear regression over 9 months decreases just after a recession and then recovers over 2- to 4-year periods. (iii) The two series showing that EM → GDP and βE(9) < 0.5 coincided in the 34 months that partly preceded and partly followed five of six NBER recession dates, providing a probability of ≈0.0002 to coincide with the recessions by chance. Thus, the two series may be used to support forecasts of coming recessions. Since EM precedes GDP and labor productivity declines before recessions, a policy recommendation for avoiding “jobless recovery” is that employment should not increase more rapidly than the real economy.

This paper examines the indirect effect of democracy on economic growth using a dataset of 17 MENA countries from 1990 to 2015. Democracy is assumed to affect growth through a series of channels: education, health, physical capital accumulation per labor, government consumption, and trade openness. A system of six simultaneous equations using 3SLS, is used to estimate the effect of democracy on growth through these channels. For further analysis, the countries are classified into groups according to the democratic status on the one side, and the level of income on the other. The results indicate that democracy enhances growth through its positive effect on health in all classifications of countries within the MENA region. However, the effect of democracy on growth through education and physical capital/labor is non-monotonic. Democracy hinders growth through government size and trade openness. Once all of these indirect effects are accounted for, the overall effect of democracy on growth is negative in less democratic countries and poor countries, but positive in more democratic countries and rich countries.

This paper examines the factors that influence the effectiveness of fiscal governance in the EU through a panel of 19 Eurozone countries for the period 1999–2019 using an OLS method. The results show the positive effects of economic growth, inflation and the change in the general government balance on the fiscal forecast error. Furthermore, the fiscal forecast error is negatively affected by the level of public debt and by elections. Fiscal transparency is integrated into the analysis through independent financial institutions, which positively influence the general government balance forecast error. Finally, Economic Adjustment Programs have a positive effect on the fiscal forecast error, thus improving the efficiency of fiscal governance. This paper suggests that independent budgetary institutions, such as fiscal councils, and the delegation of further responsibilities to them increase countries’ sustainability of public finances.

The official data in relation to salaries paid in Spain from 1999 to 2014 has been analyzed. The inadequate data format does not reflect the whole salary distribution. Frechet distributions have been fitted to the data. This simple distribution has similar accuracy in relation to the data when compared to other distributions (Log-Normal, Gamma, Dagum, GB2). Analysis of the data through the fitted Frechet distributions reveals a tendency towards more balanced (i.e., less skewed) salary distributions from 2002 to 2014 in Spain.

In recent decades, China has experienced rapid economic growth and rising health inequality. The government has introduced a nationwide health care reform aimed at achieving affordable and equitable basic health care for all. This paper investigates income-related inequality in health care utilization and out-of-pocket (OOP) payments and explores the underlying factors that drive the inequalities. Using data running from 2000 to 2015 and covering nine of thirty-one provinces in China, we calculate indices to measure income-related inequality and adopt a regression-based decomposition approach to explore the sources of inequality. We find pro-rich inequality in the use of preventive care and pro-poor inequality in the use of folk doctors. In addition, the better-off have preferential access to higher level hospitals, while the use of primary care facilities is more concentrated among the poor. The poor are also found to face a heavier financial burden since they tend to spend a larger share of their income on OOP payments. Education, employment and geographic regions all appear to contribute to the total inequality. Our results indicate that affordability remains a common barrier for the poor to access health care, and that the inequality is largely driven by socio-economic factors.

We investigate the evolution of multidimensional inequality of well-being in Vietnam in the period 2002–2012 using household survey data. Our study focuses on four crucial dimensions of human welfare: consumption, education, health and housing. We measure inequality by means of the multidimensional Atkinson index, which belongs to the Atkinson family of relative inequality indices. The choice of the values of two crucial parameters, with respect to the aversion to inequality on the one hand and the degree of substitutability between dimensions on the other hand, has a significant influence on the perceived trends of inequality. We consider different combinations of dimensions (two, three and four dimensions) and a wide variety of values of the parameters, with the aim of arriving at a robust understanding of the extent of inequality in Vietnam. Our results suggest that the level of multidimensional inequality in Vietnam has decreased, albeit that this is not the case for all combinations of the parameter values. Our study shows that looking at multidimensional rather than one-dimensional inequality leads to a richer understanding of the evolution of inequality, and indicates that it is important to be aware of the influence of value judgments on the assessment of inequality.

As in many transition economies, Vietnam has experienced a multiple exchange rate system with three exchange rates having co-existed. This paper uses the Vector-Error-Correction model and the Granger tests to investigate the relationship between the official and black market exchange rates from January 2005 to April 2011. The results confirm a long-run relationship between the official and parallel market rates of the Vietnam dong against the U.S. dollar. The short-run dynamics of two exchange rates suggest that the official exchange rate causes the black exchange rate, but not vice versa. This conclusion is valid for both a sub-period of stability and a sub-period of vibrant fluctuations, with February 2008 as the cut-off. The findings also reject the efficiency hypothesis of the black market for foreign exchange and support the policy choice of the State Bank of Vietnam not to follow black market signals in managing official exchange rates for macroeconomic stability.

This article studies how electoral processes and internal factors of the Ecuadorian economy affect the dynamics of the country’s business expectations. The hypothesis that the free market and socialist political models in an economy generate different reactions in the expectations of the agents, according to the prevailing macroeconomic context, is tested. The empirical analysis is based on time series tools on quarterly data between 2006 and 2021. The results show that the dynamics of investment adjustment to the relationships of internal factors, electoral processes, and other variables explain 84% of this behavior. This is more accelerated in political contexts that promote the free market and maintain social, political, and economic stability, showing an overreaction of agents to negative economic news following the loss-aversion hypothesis.

This paper investigates the impact of inflation in different states of unemployment: evidence with the Phillips curve in South Africa. The contribution of this paper is to examine the impact of inflation on different states of unemployment in South Africa. The Paper employs Markov-switching dynamic regression and data from 2008 to 2022. It was found that there are 2 states of unemployment mean rates of 25.55% and 33.59%, expected to run for 67 and 7 quarters, respectively. There is a 98.51% and 86.99% chance of a move and then returning to the same state, respectively. In states 1 and 2, a 1% increase in inflation results in a 2.61% increase and a 0.06% decrease in unemployment, respectively. There are times when the Phillips curve rationale is not holding. The government needs to increase the channels of employment opportunities. There is a need to re-look at the trade-offs between inflation and unemployment in the economy.

The environmental benefits from the eco-innovation activities of enterprises have the nature of reduced material or water use per unit of output, less pollution and waste, better CO2 ‘footprint’ in production and subsequent business processes. The socioeconomic impacts are associated with circular economy benefits like reduced energy use, decreased pollution and waste, and well-organized recycling possibilities of the product after use. The goal of this paper is to evaluate this innovative approach in the Czech economy. The hypotheses are aimed at the localization of enterprises, appropriability, and characteristics of enterprises that introduce eco-innovations to markets. The dataset is provided by the Czech Statistical Office and contains observations about the innovation activities of firms. Eco-innovation was surveyed in 2008 and 2014. This paper utilizes the estimation principles of CDM (Crépon, Duguet, and Mairesse) method at the firm level. The results suggest that rural–urban separation has no impact on the financial R&D intensity but urban enterprises have a higher probability to engage in innovation activities. The probability to introduce new-to-the-market innovations and eco-innovations is not dependent on localization. High-tech and knowledge-intensive industries have a lower probability to introduce eco-innovations to the market. The change in localization of enterprises to rural areas contributed to the higher sales form innovated goods and services. Higher appropriability was also observed in product eco-innovators. This paper offers a synthesis of factors that stimulate eco-innovation and shows that eco-innovation is a viable and sustainable innovative approach for rural and urban enterprises and identifies directions for future research.

Islands are frequently characterised by an economic structure centred on tourism and the service sector. This specialisation has taken different forms and characterisations concerning the chosen or spontaneously developed model. To understand the development choices and patterns, this article analyses sixteen islands and archipelagos in the European Union over ten years from 2010 to 2019. A panel data analysis was based on critical variables identifying the tourism industry model from those that could represent a proxy of the community-based tourism model. The principal component analysis was adopted to compare the evolutionary trends of these two different ways of choosing the island’s tourism model. Findings identified before the COVID-19 pandemic crisis include two island clusters. One group of islands followed a spontaneous tourism model based on the local community and small or micro hospitality systems, with auto-entrepreneurship in tourism. The second group of islands followed a planning and industry-based tourist model with an employment system and a relevant hospitality industry. Both paradigms have limitations and identify two different tourism evolutionary scenarios useful for the EU’s future island tourism policies.

In 2010, Georgians voted on a proposed constitutional amendment that would have increased motor vehicle licensing fees by USD 10 with the proceeds dedicated to maintaining and expanding the state’s trauma care centers. This paper examines voter support for the referendum across counties and finds (1) that counties located near trauma centers in neighboring states had significantly lower support for the amendment and (2) that counties already having trauma centers had higher support for the amendment. These results are, respectively, consistent with free-riding and rent-seeking on the part of voters.

The financial crisis of 2008 has caused a series of drawbacks to economies around the world. Greek economy has been hit twice at 2009, since its credibility worsened, provoking the implication of harsh fiscal measures from the 2010 Memorandum of Understanding (MoU). The effects of these measures to Greek macroeconomic figures have been widely criticized. Authors aim to estimate these effects at the macroeconomic figures of Greece through utilization of Decision Support Systems, and propose accurate insights regarding their efficacy. By capitalizing on regression analysis and Fuzzy Cognitive Mapping processes, specific results from 2010 Memorandum’s measures arise. It has been calculated that measures implied by 2010 Memorandum have been harsh and posed a negative effect on key Greek macroeconomic figures like GDPR, public debt, etc., especially with the ongoing 2008 financial crisis.

The editors of Economies would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...]

After more than half a year of elections (yielding three voting stages and nine voting rounds), the 2017 Rector election at Ghent University (Belgium) resulted in a victory for the duo leading all nine voting rounds, and in a resounding defeat for the electoral system. Significant regulation changes were needed in order to break the institutional deadlock in which Ghent University found itself. In this paper, we follow the timeline of the election and dissect what went wrong in the election planning.

The article is devoted to identifying the impact of factors on the increasing labour productivity in the economies of the European Union-27 (EU-27) and Ukraine. The system of influencing factors that must be taken into account in the assessment of the labour productivity indicator was substantiated. The factors are based on the most significant indicators of innovative development (innovative activity; formation and the use of personnel; the state of use of fixed capital; the composition of the payroll budget; investment activity; and the use of working time). Based on the use of the method of linearization of the labour productivity model, the rating coefficients of the influence of factors for the economies of the EU-27 and Ukraine were determined. It has been proven that the following factors have a significant positive impact on labour productivity: an increase in the costs of scientific research and development; the growth of enterprises expenditures on research and development (R&D) in high-tech sectors; the increase in the share of scientific research personnel and researchers in the total number of the employed population; the growth of costs for the innovation of industrial enterprises; an introduction to the production of new technological processes and innovative types of products; the purchase of machinery, equipment, and software; an increase in the share of the employed population that has a basic higher education (bachelor’s degree); the growth in the share of the employed population that has a full higher education (master’s degree); the increase in the share of enterprises providing training; the increase in the capital–labour ratio; the technological equipment of labour; the machine equipment of labour; the renewal of fixed capital; and the increase in the level of intellectualization of fixed capital. The available reserves for increasing the labour productivity in EU-27 economies and Ukraine were clarified, and recommendations for managing the labour productivity in the conditions of innovative development have been provided. This study gains relevance when Ukraine has assumed the official status of an EU candidate country and the advantages and potential difficulties in the membership process should be evaluated. Labour productivity will be one of the key factors in the post-conflict recovery of the economy.

The use of location quotients for the estimation of regional input–output tables has been found to be a useful and efficient tool to estimate intraregional production coefficients and multipliers. This paper considers some regionalisation methodologies based on location quotients for the estimation of input–output tables—some of which have hitherto not been analysed at the regional level—and studies which one provides the best estimation (best goodness of fit). We focus the analysis mainly on the accuracy of Flegg’s location quotient (FLQ) and two-dimensional location quotient (2D-LQ). The analysis makes use of the multiregional input–output table for Korea for the year 2015 to evaluate the accuracy of the 2D-LQ method against FLQ. A novel proposal for the determination of the parameters corresponding to the 2D-LQ method is presented. This proposal is evaluated in Korean regions and is also applied to Spanish regions. The results obtained from the research conclude the general superiority of the 2D-LQ method, thus corroborating the results of other studies at the national level as well as the validity of our proposal.

Accelerating demand for energy and its consumption has become a credible threat to the sustainable ecosystem due to the exploitation of scarce natural resources and environmental hazards. The adoption of renewable energy sources for sustainable development has been gaining traction among researchers and practitioners alike. Considering its hot climate, Pakistan has a huge potential to meet its energy requirements by tapping into renewable energy resources, especially through the use of solar photovoltaic (SPV) technologies. However, the adoption rate of this technology remains still quite scant among consumers. In this regard, the present research explores the factors that affect households’ purchase intention of SPV technology in Pakistan. The study has developed a comprehensive research framework by decomposing the technology acceptance model (DTAM) into second-order sub-constructs. Afterward, Structural equation modeling (SEM) was employed to analyze the data by decomposing perceived usefulness (PU) into social, economic, and environmental usefulness and perceived ease of use (PEOU) into discomfort and insecurity and to assess their cumulative effects on consumer attitude. Moreover, the moderating role of policy and propaganda was also investigated. Empirical results assert that PU and PEOU positively and significantly shape the consumer attitude toward SPV adoption. Subsequently, consumer attitude has a positive and significant impact on the actual purchase intention of SPV technology. Furthermore, the moderating role of governmental policy and propaganda between the consumer attitude and actual purchase intention was also confirmed. The policy implications of these results are discussed. Finally, the limitations and future directions of the research are also elaborated.

This study explores the challenges facing the current e-payment systems and investigates the main factors that support using the e-payment system. This study used a cross-sectional approach. An online survey was conducted on Yemeni consumers as part of the collection of data. The data from 486 questionnaires were analyzed using smartPLS4 and Jamovi software for structural model analysis and statistical analysis. According to the PLS-SEM results, the structural model shows that R2 is 0.757, which explains the variances in behavioral intention via all the constructs. Statistically, the intention to use e-payment systems is significantly and positively influenced by performance and effort expectancies and social influence. In contrast, facilitation conditions are significantly and negatively correlated with behavioral intention. This is attributed to consumers’ view of the infrastructure of Internet services, which does not contribute to the behavioral intention and acceptance of using electronic payment in Yemen. Contrary to expectations, age does not moderate the relationship between performance expectancy, social influence, and intention to use e-payment systems; hence, the related hypothesis was not supported. This study provides valuable suggestions for policymakers, designers, developers, and researchers, enabling them to better understand the critical aspects of using the electronic payment system. This study developed a model for predicting the likelihood of acceptance of electronic payments in a country that has not given adequate attention to this issue. An application and evaluation of the UTAUT model in Yemen are presented in this study.

This paper aims to better understand the relationship between HIV knowledge and media exposure in India. We use a two-stage hurdle model to estimate the effect of media sources such as newspapers, radios and television on AIDS-related knowledge among Indian men and women using demographic health survey data. Overall, access to newspapers, radio, or television increases the likelihood of better HIV knowledge in both males and females by an order between 2% and 12%. These findings, albeit quantitatively small, suggest, even if indirectly, possible problems faced by AIDS campaigns and government programs in combating the HIV epidemic in India.

The Asia-Pacific region has recorded the sharpest increase in human development progress globally and has seen shrinking gaps in basic standards and capabilities. However, inequalities around technology remain a cause for concern for the region, especially when countries with lower human development reportedly have limited access to technologies compared to countries with higher human development. Therefore, this study investigated the effects of information and communication technology (ICT), electricity access, and governance on human development in the Asia-Pacific region. A panel dataset of 46 countries from 2010 to 2019 was estimated using the Driscoll–Kraay standard error regression approach. Our findings revealed that ICT has a strong positive impact on human development for countries with high and medium human development. Internet usage is particularly significantly correlated with human development for both country groups, while mobile cellular subscriptions emerged as significant only for countries with high human development. The study also revealed significant positive effects of electricity access and governance on human development. The findings suggest that increased ICT adoption and electricity access, coupled with good governance, are crucial in improving people’s quality of life, thereby promoting greater human development. Limitations of the study include omission of the low human development group and a limited number of indicators used to measure ICT and governance.

Economies (ISSN 2227-7099) is a new international, peer-reviewed open access journal for the academic fields of development economics and macroeconomics. While the latter seems to be clearly defined, development economics is not, because it is related to nearly all traditional economic sub-disciplines such as macroeconomics, international trade and finance, as well as microeconomics and public finance. Typically, academic field journals of development economics cover all those economic sub-disciplines. Economies instead focuses mainly on the macroeconomic perspective of economic development and it intends to publish academic research that is of strong macroeconomic policy relevance. In general, contributions in Economies should foster understanding of the macroeconomic process of economic development, with the process of development not exclusively being reserved to what we typically call developing countries. Also, the group of developed economies is still developing in the sense of improving their living standards further.

There is a general belief that the distribution of tourist activity in space does not respond to a random pattern, so having a thorough knowledge of said activity will require analyzing and understanding its distribution pattern. At the same time, the adequate planning of this sector requires exhaustive knowledge, on the one hand to be able to enhance the positive effects of concentrations in the space, and on the other hand to avoid those possible adverse effects. Therefore, various studies focus on providing information on the random pattern of these activities, especially in developing destinations with a great interest in generating a model of sustainable tourism development. This paper aims to contrast the results achieved by previous studies at the destination while describing the pattern identified through the use of alternative statistical techniques rather than those commonly used. In particular, an intensity function is estimated using three different methods: quadrant counting, K-function, and kernel smoothing. The results achieved allow the identification of the areas with the greatest tourist intensity while describing the practical implications of the results achieved.

As tourism products are not necessities for people’s livelihood, zero consumption data are usually observed while conducting studies on topics that are relevant to tourism expenditure using cross-sectional research data, and a similar problem exists in tourist accommodation expenditure. This study adopts a two-stage process to examine the factors influencing tourist accommodation decisions in the domestic market, applying the dependent double-hurdle (DDH) model while using the dataset on Survey of Travel by R.O.C. (Taiwan) Citizens for the years 2014–2018. The findings reveal that, in the two decision-making equations, the social stratum, family life cycle, residential area, tourism behavior, vacation policy, and economic variables have different degrees and directions of influence on the intention to use and expenditure on tourist accommodation. Such information presents the processes involved in deciding to accommodate and how much to spend on accommodation, thereby indicating that it is inappropriate to use the single-equation analysis consisting of zero consumption expenditure data and to assume that the same variables influence the participation and consumption decisions.

Improving the accuracy of cash flow forecasting in the TSA is key to fulfilling government payment obligations, minimizing the cost of maintaining the cash reserve, providing the absence of outstanding debt accumulation and ensuring investment in financial instruments to obtain additional income. This study aims to improve the accuracy of traditional methods of forecasting the time series compiled from the daily remaining balances in the TSAbased on prior decomposition using a discrete wavelet transform. The paper compares the influence of selecting a mother wavelet out of 570 mother wavelet functions belonging to 10 wavelet families (Haar;Dabeshies; Symlet; Coiflet; Biorthogonal Spline; Reverse Biorthogonal Spline; Meyer; Shannon; Battle-Lemarie; and Cohen–Daubechies–Feauveau) and the decomposition level (from 1 to 8) on the forecast accuracy of time series compiled from the daily remaining balances in the TSA in comparison with the traditional forecasting method without prior timeseries decomposition. The model with prior time series decomposition based on the Reverse Biorthogonal Spline Wavelet [5.5] mother wavelet function, upon the eighth iteration, features the highest accuracy, significantly higher than that of the traditional forecasting models. The choice of the mother wavelet and the decomposition level play an important role in increasing the accuracy of forecasting the daily remaining balances in the TSA.

This paper makes use of the Markov Switching model and the K-Means Cluster analysis to estimate the transition probabilities of social mobility and to analyze the impact of social inequalities on intergenerational social mobility. The dataset is a sample of 44 countries and comprises the 2018 social mobility indices, and the 2018 or latest income inequality measures. The data are collected from the OECD Income and Wealth Distribution Databases, and from the world economic forum. It was found that the likelihood of moving upward or downward the social ladder is minimal in both developed and emerging countries. In addition, the paper found that the hypothesis according to which high-income countries have a higher relative social mobility is not necessarily true. The United States, a high-income country, was found to have a lower social mobility, similar to that of Turkey and South Africa. Furthermore, it was found that when poverty decreases, intergenerational social mobility increases in both lower and higher mobility countries. Policies that promote equality of opportunities at all stages of life are therefore recommended to improve intergenerational social mobility.

The discussion in recent decades about sustainable development issues has given rise to a new accounting dimension: social accounting. Currently, this issue remains an emerging theme. Although there are some studies and literature reviews, none include disclosure of social accounting information or the analysis of research paradigms. This article reviews the research on social accounting disclosure and tries to answer the following research questions: What research streams have been followed? Which theories and research paradigms have been used? The search for articles to be included in the literature review was performed through the Web of Science. The 126 articles obtained were later analyzed using Bibliometrix software. Results expose the growing interest in this theme and identify three distinct research lines (three clusters): Cluster 1—Social accounting disclosures, Cluster 2—Legitimacy vs. disclosure of social accounting, and Cluster 3—Motivations for disclosure of social accounting. The main contribute of this article resides, on the one hand, in the fact that no literature review articles have been found that include the theme of the disclosure of information on social accounting and, on the other hand, the treatment of data has been done with innovative software, an R package for bibliometric and co-citation analysis called Bibliometrix. As well as mapping the literature, another theoretical contribution of this study was identifying the main research approaches used in the studies. Within the paradigmatic plurality of social accounting research, the results suggest that social accounting research can also be critically addressed when addressing the sustainability challenges posed by climate change or carbon emissions, among many other aspects. This study is, to our knowledge, the first bibliometric review done about social accounting information disclosure.

This paper examines the association between environmental uncertainty, accounting information relevance, and organizational performance. From a contingency approach, this paper attempts to contribute to a stream of research that investigates the relationship between accounting information relevance and organizational performance. The presence of environmental uncertainty in this relationship has not been fully established. This paper contributes to this area by suggesting a framework to study and explain this connection. An online questionnaire-based survey was conducted, which produced 119 valid responses (a response rate of 23%) from large manufacturing companies operating in Portugal. The results suggest that in contexts of environmental uncertainty, the relevance of non-financial information increases. However, the relevance of financial information continues to outstrip that of non-financial information. The results also suggest that financial information and non-financial information are complementary, and not substitutes, and can be used simultaneously in different situations. These results have several implications for professionals involved in decision-making activities. It offers findings which are potentially useful for both theory and practice. The study addresses an identified gap in the literature and adds to the existing body of work analyzing the association between environmental uncertainty, accounting information relevance for decision-making purposes, and organizational performance.