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This study aims to investigate Granger-causal relations between the Ringgit-USD exchange rate and selected domestic and international economic variables after the flotation of the Ringgit beginning with 25 July 2005.

The study uses lag-augmented vector autoregression (LA-VAR) developed by Toda and Yamamoto (1995) to test for Granger-causality. To visualize short-run dynamics in the Malaysian Ringgit (RM)-USD exchange rate to shocks in predictor variables, generalized impulse-response functions (Pesaran and Shin, 1998) are derived from the estimated LA-VAR models.

Results based on LA-VAR generalized impulse responses and data measured in daily frequency indicate strong Granger-causal relationships with the Dow Jones Industrial Average and oil prices. Evidence is also indicative for a causal relationship with the Shanghai Composite Index. Positive shocks in these three variables lead an appreciation of the Ringgit.

These results provide insights for policymakers in East Asia in their attempt to manage the floating of their currency.

The paper adds to existing empirical literature in three ways. First, it investigates the RM-USD exchange rate after its managed flotation beginning with 25 July 2005. Second, the study provides results for exchange rates measured in two frequencies, namely, daily and monthly. Third, the empirical LA-VAR model applied includes variables capturing economic and financial conditions in China. Prior literature puts a focus on macroeconomic conditions in the USA. Yet, since 2009, China has been the largest trading partner of Malaysia.

This paper aims to study the financial vulnerability of the Spanish households derived from their primary residence mortgage debt payments. This paper shown as the economic and financial crisis triggered after the burst of the housing bubble brought an unemployment shock and a fall in the disposable family income, which alarmingly aggravated the financial vulnerability of the mortgaged households. Consequently, the number of financially vulnerable households almost doubled.

Econometric model of discrete election.

The most vulnerable households – and therefore those with a higher risk of mortgage payment default – are those whose family head is a married and self-employed female. In contrast, in social housing the mortgaged households have been less vulnerable in the context of economic and financial crisis and unlike what would have been initially expected, higher education levels have not acted as a protective factor against households’ financial vulnerability.

There is a great need to understand how the financial health of the mortgaged families that bought their primary residence has deteriorated in a context of significant changes in macroeconomic conditions. This need is specially pressing in a country such as Spain which is one of the OECD’s countries with a higher rate of household property and which shows a sector of highly mortgaged households.

This study aims to identify the impact of foreign direct investment (FDI) on economic growth in Morocco depending on each origin country, including Spain. This study uses a linear model to measure the marginal impact of FDI on the growth of Morocco. This marginal effect allows to compare the different effects of FDI among countries of origin. Also, the marginal effect helps to measure the rate of substitution between FDI in an easier way than the other specifications of the model. The second step determines the substitute for Spain in case he decides to divest its FDI from Morocco to maintain the economic growth.

Using data of FDI from 13 countries of origin from 1995 to 2020 and two estimation methods (Dynamic Ordinary Least Squares and Autoregressive model), this study aims to measure the marginal impact of the divestment of FDI from Spain on growth. Then this study estimates how much Morocco should attract FDI from other countries when Spain divests. This study uses the differential calculus, assuming a perfect substitution between FDI from different countries. This calculus implies an indifference curve between FDI from Spain and FDI from another country where we deduct the substitution rates between FDI.

The results indicate that the FDI from Spain and France are the only ones to impact positively Moroccan economic growth. The FDI coming from Germany, Holland, China and Turkey have a negative impact, whereas those from the USA, Italy, UK, Switzerland and Gulf countries: Saudi Arabia, Kuwait and UAE have an insignificant effect. Second, using the differential calculus, the result indicates that when Spain divests 1m dirhams of its investments from Morocco, France would have to increase its own by 0.1509m dirhams so that Morocco could maintain its economic growth.

The research focuses only on economic growth, neglecting the impact on other aggregates, such as total factor productivity, technology transfer and employment. Also, this research marginalized the sectorial analysis of FDI by the source to better understand the divergent effects.

This paper fills a research gap when analyzing the effect of FDI on the host economy depending on country-of-origin. In addition, it contributes to the body of literature by constructing the rate of substitution between the different sources of FDI to adapt to divestment policy.

This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana.

Due to the reality of a household using one or more financial products or services, this study uses the generalised Poisson model applied to GLSS6 and GLSS7 data collected in 2012/2013 and 2016/2017 respectively, to estimate the determinants of the intensity of use of financial inclusion. To deepen the analysis, a multinomial probit model is also applied.

Results show that infrastructural variables such as roads, public transport and banks stimulate the intensity of financial inclusion. In addition, agricultural development characteristics such as markets and cooperatives are essential for the intensity of inclusion.

There is a need to incorporate how many services or depth of services that people use as part of the conceptualisation of financial inclusion, as this can provide more policy-relevant evidence to enhance priority setting in financial inclusion policies. Also, micro-level financial inclusion studies in agrarian economies should consider exploring agricultural development and infrastructure variables in the modelling framework. As lead to further studies, count models of financial inclusion should consider exploring cross-country analysis, the use of panel data, or other methodological approaches to provide more robust evidence.

Previous studies have not modelled financial inclusion based on a count model as a means of measuring intensity though conceptualisations highlight the fact that people use varied financial products or services. Following from this angle, to the best of the authors’ knowledge, this study provides the first attempt at analysing the underlying determinants of the number of financial products or services used by households.

This study aims at evaluating the technical efficiency (TE) of healthcare systems in the Arab region and exploring the key factors that affect the efficiency performance.

The study applies a two-stage Data Envelopment Analysis (DEA) approach to a sample of 20 Arab countries. In the first stage, a DEA model is used to calculate the TE scores of the examined healthcare systems in 2019 and 2010, following both the output and input orientations of efficiency. In the second stage, a censored Tobit model is estimated to investigate the determinants of healthcare efficiency.

DEA results of 2019 indicate that achievable efficiency gains of the Arab countries range from 0.4% to 16% under the output and input orientations, respectively. Six countries are efficient under both orientations. Although the average efficiency scores of the Arab countries have deteriorated between 2010 and 2019, Djibouti and Sudan had the greatest efficiency improvements between the two years. Bahrain, Mauritania, Morocco and Qatar proved to be efficient in 2010 and 2019 under the two orientations of efficiency and according to the two DEA specifications followed. The Tobit model reveals that corruption and government health expenditure tend to have an adverse impact on healthcare efficiency.

The author evaluates healthcare efficiency and healthcare's efficiency determinants in the Arab countries. Regardless Arab countries' diversity, these countries are facing common health challenges, including diminishing role of governments in healthcare financing; increased out-of-pocket healthcare spending; poor healthcare outputs and prevalence of health inequities resulting from weak governance institutions. Comparing the efficiency of healthcare systems between 2010 and 2019 gives insights on the potential impact of the Arab spring uprisings on healthcare efficiency. Moreover, examining the determinants of healthcare efficiency allows for better understanding of how to improve the efficiency of healthcare systems in the region.

This study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed. Additionally, the study aims to determine whether the effect of the news changes according to time and volatility level.

The general autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models consist of the energy reserve exploration news in Turkey for the period 2009–2022 and the volatility of 14 energy stocks.

The results indicate energy exploration news's negative and significant effect on volatility. According to empirical results, energy stock volatility is most affected in the first ten days. Besides, the results show that the significant models of energy reserve news in low-volatility stocks are proportionally higher than in high-volatility stocks.

Only unproved reserve news is included in the analysis, as sufficient confirmed reserves could not be reached during the sampling period. Further studies can compare proven and unproved reserve news effects. Additionally, a similar analysis can be conducted between Turkey and another country with a similar socio-economic character to examine different investor behaviors.

This research includes indications on managing investors' reactions to unproven energy reserve news.

This study contributes to the literature by analyzing unproven reserves. Contrary to previous studies, examining stock volatility also makes the study unique.

The current pandemic is difficult to model – and thus difficult to control. In contrast to the previous epidemics, whose dynamics were smooth and well described by the existing models, the statistics of the current pandemic are highly oscillating. The purpose of this paper is to explain these oscillations and to see how this explanation can be used to fight the epidemic.

The authors use an analogy with economic systems.

The authors show that these oscillations can be explained if we take into account the disease’s long incubation period – as a result of which our control measures are determined by outdated data, showing number of infected people two weeks ago. To better control the pandemic, the authors propose to use the experience of economics, where also the effect of different measures can be observed only after some time. In the past, this led to wild oscillations of the economy, with rapid growth periods followed by devastating crises. In time, economists learned how to smooth the cycles and thus to drastically decrease the corresponding negative effects. The authors hope that this experience can help fight the pandemic.

To the best of our knowledge, this is the first explanation of the highly oscillatory nature of this epidemic’s dynamics.

Infrastructure deficiency in Southeast Asian countries is ever growing and touched to a level where it harms the local economy as well as the international sector of the country. The gap between demand and supply for infrastructure is constantly on the upswing. The purpose of this study to investigate the effect of infrastructure on exports and foreign direct investment (FDI) inflow in selected Southeast Asian economies.

This study employs the pooled mean group (PMG) technique to velaborate that how the infrastructure affects export and FDI in the short run and long run during 1990–2018. For cointegration, Pedroni and Kao tests are used. Dynamic ordinary least square (DOLS) and the fully modified least squares (FMOLSs) estimators are employed for robustness check.

The findings support that aggregate and sub-indices of infrastructure significantly promote the export and FDI inflow in the long run. Also infrastructure, export and FDI inflow are cointegrated in the long run. FMOLS and DOLS found the most robust results.

Infrastructure development in determining trade and FDI has established a significant deal of attention in the modern era where a plethora of research studies encourage the opinion that better infrastructure attracts FDI and enhances export. However, this study uses a global infrastructure index, which comprises the sub-indices like transport, telecommunication, energy and financial sector, which gives us a clear picture regarding how Southeast Asia can catch up FDI and export benefits through infrastructure.

By combining econometrics and multifractal methods, utilizing a financial framework, this paper will examine with objectivity the economic, financial and social impact of coronavirus disease 2019 (COVID-19) on society.

Through Granger causality, the authors test the effect of the COVID-19 pandemic on excessive gaming and gambling activities, and through econometrics and multifractal methods, they combine the results to analyze a possible long-run relationship.

The COVID-19 confirmed cases Granger cause all examined stocks. Based on the co-integration technique, and the multifractal cross-correlation analysis, a long-run relationship exists between all examined stocks and COVID-19.

This is an empirical examination of a very important subject in the field of economics, namely, the consequences of the COVID-19-related events on the behavior of global citizens. It proposes a different and more objective approach (than the interviews and questionnaires) in the examination of this specific subject, through a financial framework, depicting the stock performance of the gaming and online gambling-related companies, and reflecting on the activity of these companies. It combines two different approaches from two different disciplines, namely econometrics and multifractal analysis, to test and describe the causal and the long-run relationship between the phenomena examined, combining the results to an overall and multidimensional view of this occurrence.