Impact of global smoking prevalence on mortality: a study across income groups.

BACKGROUND: Smoking significantly contributes to the mortality rates worldwide, particularly in non-communicable and preventable diseases such as cardiovascular ailments, respiratory conditions, stroke, and lung cancer. This study aims to analyse the impact of smoking on global deaths, and its association with mortality across the main income groups. METHODS: The comprehensive analysis spans 199 countries and territories from 1990 to 2019. The study categorises countries into four income groups: high income, upper middle income, lower middle income, and low income. RESULTS: The findings underscore the profound impact of global tobacco smoking on mortality. Notably, cardiovascular disease mortality is notably affected in both upper-middle-income and high-income groups. Chronic respiratory disease mortality rates show a significant impact across all income groups. Moreover, stroke-related mortality is observed in the lower-middle, upper-middle, and high-income groups. These results highlight the pervasive influence of smoking prevalence on global mortality, affecting individuals across various socioeconomic levels. CONCLUSION: The study underscores the critical implications of smoking on mortality rates, particularly in high-income countries. It emphasises the urgency of targeted interventions in these regions to address the specific challenges posed by tobacco smoking on public health. Policy recommendations include implementing prohibitive measures extending to indoor public areas such as workplaces and public transportation services. Furthermore, allocating funds for research on tobacco and health, is imperative to ensure policymakers are consistently informed about emerging facts and trends in this complex domain.

Factors influencing IMF assistance in the Sub-Saharan African region.

This study examines the determinants influencing the likelihood of Sub-Saharan African (SSA) countries seeking assistance from the International Monetary Fund (IMF). The IMF, as a global institution, aims to promote sustainable growth and prosperity among its member countries by supporting economic strategies that foster financial stability and collaboration in monetary affairs. Utilising panel-probit regression, this study analyses data from thirty-nine SSA countries spanning from 2000 to 2022, focusing on twelve factors: Current Account Balance (CAB), inflation, corruption, General Government Net Lending and Borrowing (GGNLB), General Government Gross Debt (GGGD), Gross Domestic Product Growth (GDPG), United Nations Security Council (UNSC) involvement, regime types (Closed Autocracy, Electoral Democracy, Electoral Autocracy, Liberal Democracy) and China Loan. The results indicate that corruption and GDP growth rate have the most significant influence on the likelihood of SSA countries seeking IMF assistance. Conversely, factors such as CAB, UNSC involvement, LD and inflation show inconsequential effects. Notable, countries like Sudan, Burundi, and Guinea consistently rank high in seeking IMF assistance over various time frames within the observed period. Sudan emerges with a probability of more than 44% in seeking IMF assistance, holding the highest ranking. Study emphasises the importance of understanding SSA region rankings and the variability of variables for policymakers, investors, and international organisations to effectively address economic challenges and provide financial assistance.

Renewable energy as a solution to climate change: Insights from a comprehensive study across nations.

Without fundamentally altering how humans generate and utilise energy, there is no effective strategy to safeguard the environment. The motivation behind this study was to analyse the effectiveness of renewable energy in addressing climate change, as it is one of the most pressing global issues. This study involved the analysis of panel data covering 138 nations over a 27 year period, from 1995 to 2021, making it the latest addition to the existing literature. We examined the extent of the impact of renewable energy on carbon dioxide over time using panel, linear, and non-linear regression approaches. The results of our analysis, revealed that the majority of countries with the exception of Canada, exhibited a downward trend, underscoring the potential of increasing renewable energy consumption as an effective method to reduce carbon dioxide emissions and combat climate change. Furthermore, to reduce emissions and combat climate change, it is advisable for nations with the highest carbon dioxide emissions to adopt and successfully transition to renewable energy sources.

Examining the influence of global smoking prevalence on stroke mortality: insights from 27 countries across income strata.

BACKGROUND: This study investigates the influence of Global Smoking Prevalence (GSP) on Stroke Death Rates (SDR) across 27 countries categorized into High-Income Countries (HIC), Upper Middle-Income Countries (UMIC), Lower Middle-Income Countries (LMIC), and Low-Income Countries (LIC). METHODS: Analysing data from two distinct periods (1990-1999 and 2010-2019), countries exhibiting an increased SDR were selected. The study uses a polynomial regression model, treating income groups as cross-sectional and years as time series data. RESULTS: Results from the regression model reveal that 17 countries observed a significant impact of GSP on SDR, with only Turkey, Solomon Islands, and Timor-Leste resulting in negative values. However, the study emphasises that out of all 27 countries, the highest occurrence of the impact of GSP on SDR has been reported in the LMIC stratum for the period under review. CONCLUSION: It is evident that GSP affects the risk of incidence of stroke death, specifically in the LMIC stratum. Furthermore, it has been identified that GSP is a major preventable risk factor affecting global mortality. To mitigate the risk of stroke death attributable to smoking prevalence, necessary preventive steps should be adopted to encourage smoking cessation, and essential policies should be implemented to reduce the burden of SDR.

Unveiling Sri Lanka's brain drain and labour market pressure: A study of macroeconomic factors on migration.

The purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study's implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country's migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making.

Forecasting weekly dengue incidence in Sri Lanka: Modified Autoregressive Integrated Moving Average modeling approach.

Dengue poses a significant and multifaceted public health challenge in Sri Lanka, encompassing both preventive and curative aspects. Accurate dengue incidence forecasting is pivotal for effective surveillance and disease control. To address this, we developed an Autoregressive Integrated Moving Average (ARIMA) model tailored for predicting weekly dengue cases in the Colombo district. The modeling process drew on comprehensive weekly dengue fever data from the Weekly Epidemiological Reports (WER), spanning January 2015 to August 2020. Following rigorous model selection, the ARIMA (2,1,0) model, augmented with an autoregressive component (AR) of order 16, emerged as the best-fitted model. It underwent initial calibration and fine-tuning using data from January 2015 to August 2020, and was validated against independent 2000 data. Selection criteria included parameter significance, the Akaike Information Criterion (AIC), and Schwarz Bayesian Information Criterion (SBIC). Importantly, the residuals of the ARIMA model conformed to the assumptions of randomness, constant variance, and normality affirming its suitability. The forecasts closely matched observed dengue incidence, offering a valuable tool for public health decision-makers. However, an increased percentage error was noted in late 2020, likely attributed to factors including potential underreporting due to COVID-19-related disruptions amid rising dengue cases. This research contributes to the critical task of managing dengue outbreaks and underscores the dynamic challenges posed by external influences on disease surveillance.

Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness.

The purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specific contributions of each country to the study variables and their impact on carbon emissions. The findings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly significant impact (p < 0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development, and international cooperation within Asia to reach the goal of being carbon neutral by 2050.

Factors affecting job performance of Sri Lankan IT professionals working from home.

This study investigated the influence of the physical work environment, work life balance, work flexibility, and effective communication on the job performance of IT professionals in Sri Lanka's IT industry who work from home (WFH). A standard questionnaire was used to collect data from 293 IT specialists in 50 different IT organizations in Sri Lanka, and a stepwise probit model was employed for data analysis. According to the findings, both the physical work environment and work life balance had a significantly positive effect on job performance. A one-unit increase in the physical work environment and work life balance increased the likelihood of high job performance by 0.21% and 0.19%, respectively. In contrast, work flexibility had a negative effect on job performance, with an increase of one unit resulting in a 0.18% decrease in the likelihood of high job performance. The positive impact of effective communication on job performance was less significant. The study emphasises the significance of providing a conducive work environment and promoting work life balance to enhance the job performance of IT professionals in Sri Lanka's IT industry who WFH.

From short to long term: Dynamic analysis of FDI and net export in global regions.

It is crucial to examine the impact between foreign direct investment (FDI) and net exports (NE) for unveiling international trade dynamics, and the economic development of different geographical regions. It yields sharp insights into how FDI inflows, driven by theories such as backward linkage, export platform, and knowledge transfer, enhance a host country's export capacity and contribute to economic growth. Moreover, studying the reciprocal linkages between FDI and NE helps recognise the aspects of domestic factors, such as productivity and the product life cycle, in attracting FDI and increasing export performance. Based on those theories, the study aims to ascertain the dynamic causality or correlation between FDI and NE across all regions with the utilisation of panel data gathered from 110 countries, considering the period from 2002 to 2020. The Wavelet coherence method is used to investigate the relationship between these variables across different frequencies and periods, followed by a Granger causality test. The findings demonstrated that FDI and NE have a significant relationship in most regions, with a bidirectional relationship between FDI and NE across all continents. The results could assist respective governments and policymakers in formulating policies related to FDI flows and offer insights into how a host country can attract more FDI and boost NE.

Impact of economic globalisation on value-added agriculture, globally.

Economic globalisation is the integration of national economies into the global economy through the increasing flow of goods, services, capital, and technology across borders and it has contributed to garnering a significant portion of most nations' national income, although its agricultural value-added aspect has yet to be maximised. This pioneering study explores the impact of economic globalisation on value-added agriculture in a global context based on countries' income levels. Panel data regression with the stepwise method was employed to quantify the impact of economic globalization on agriculture value added in 101 countries between 2000 and 2021. The findings of our study reveal that economic globalisation, through various channels such as fertilizer consumption, employment in agriculture, agriculture raw materials export and import, exchange rate, and foreign direct investment, significantly influences the agricultural value-added factor globally and across different income levels. Furthermore, the results show that agricultural employment significantly impacts the agricultural value-added factor globally and across all income levels. Also, countries with low and lower-middle-income levels significantly affect agricultural value-added due to exchange rates. In comparison, high-income and lower-middle-income levels have an impact due to foreign direct investment. Finally, the upper-middle-income countries have significantly affected agricultural value-added due to agricultural raw materials imports. This study confirms that employment in agriculture, exchange rate and foreign direct investments positively impact agriculture value-added on the global level and based on the income level of countries.

The cost of aging: Economic growth perspectives for Europe.

This study explores the causal relationship between the economy and the elderly population in 15 European countries. The economy was measured by the Per Capita Gross Domestic Product growth rate, while the population aged above 65 as a percentage of the total was considered the elderly population. The data were obtained from a time series dataset published by the World Bank for six decades from 1961 to 2021. The Granger causality test was employed in the study to analyse the impact between the economy and the elderly population. An alternate approach, wavelet coherence, was used to demonstrate the changes to the relationship between the two variables in Europe over the 60 years. The findings from the Granger causality test indicate a unidirectional Granger causality from the economy to the elderly population for Luxembourg, Austria, Denmark, Spain, and Sweden, while vice versa for Greece and the United Kingdom. Furthermore, for Belgium, Finland, France, Italy, Netherlands, Norway, Portugal, and Turkey, Granger causality does not exist between the said variables. Moreover, wavelet coherence analysis depicts that for Europe, the elderly population negatively affected the economic growth in the 1960s, and vice versa in the 1980s.

Nexus between carbon emissions, energy consumption, and economic growth: Evidence from global economies.

Renewable energy holds a remarkable role in clean energy adaptation due to the much lower carbon footprint it releases compared to other fossil fuels. It also has a positive impact by slowing down the rate of climate change. The study has examined the links between renewable and non-renewable energy use, CO2 emissions and economic growth in developed, developing, and LDCs and Economies in Transition between 1990 and 2019 in 152 countries. Granger-causality has been used as the methodology to investigate the link between the variables. The findings of the existing studies on the relationship between the consumption of renewable and non-renewable energy sources and economic growth are inconsistent, indicating that there may or may not be a relationship between the two factors. Apart from having a few empirical studies so far have examined the link between the above-mentioned variables, analysis has yet to encompass all the regions in the four sub-groups discussed above. The results indicated that no Granger-causal relationship exists between GDP and REC outside of Economies in Transition. Additionally, the GDP and CO2 of all countries have a one-way relationship. Nevertheless, research indicates that GDP and CO2 have a bi-directional link in Economies in Transition, a uni-directional relationship in developing countries, and no meaningful association in developed and LDCs. Therefore, it is essential to emphasise actions to lower CO2 emissions and develop renewable energy while also stimulating the economy. Ultimately, more nations should choose renewable energy sources to build a more sustainable future.

Asian ageing: The relationship between the elderly population and economic growth in the Asian context.

The elderly population and economic growth have been a contentious topic among researchers. Regardless of the economic growth rate, the population and its growth have a stimulating influence on economic development. This study aims to explore the relationship between the elderly population and economic growth in 15 Asian countries, based on secondary data gathered from the WDI (World Development Indicators) from 1961 to 2021. This research contributes to filling the empirical gap, capturing the Granger causality concerning the relationship between the elderly population and economic growth in the Asian context in a single study. The empirical findings highlighted a one-way Granger causality from economic growth to the elderly population for India, Japan, Malaysia, and Singapore while vice versa for Bangladesh, China, and Pakistan. Furthermore, for Nepal, there is a two-way Granger causality, while there is no Granger causality for remaining countries. To the best of the authors' knowledge, this study has been the first to investigate the relationship between the elderly population and economic growth for Asian nations, using a lengthy data series and a Granger causality test. The main findings will assist the governments, policymakers, and foreign investors in effective decision-making in this regard.

Can visual impairment impact your income potential?

People's quality of life (QOL) has been disrupted globally in the wake of the pandemic in recent times. This was mainly due to global economic crises fuelled by the coronavirus (COVID- 19) and other related factors. Sri Lanka, too, was facing major social and economic constraints in the period 2021-2022. Thus, all communities islandwide have been economically disturbed. Among others, people with Visual Impairment and Blindness (VIB) have been pushed to severely disadvantageous positions, financially and otherwise. A sample from three geographical locations in Sri Lanka; and eleven individuals representing diverse cadres in Sri Lankan society were purposively selected for the study based on the existence of the majority of the visually impaired community using a mixed approach. Descriptive statistics were utilised to analyse the identified socio-economic characteristics. Ordered probit regression was employed to determine the mediating effect of socio-economic status on income levels. Word Cloud illustrates the factors affecting the QOL. Most severely impaired individuals are more likely to earn a lower rate of income. This situation has degraded their lives and poor QOL. Participants' responses elucidate that facilities, resources, education, opportunities, income, employment, and government activities would enhance their QOL. The study adds value to society by recognising VIB people, helping them gain financial independence and strengthening them without marginalising the impaired community. The proposed policies in this study would be valuable for these social groups to address their wealth concerns.

Is the best option still in low adoption? An investigation on factors affecting the adoption of online school education in rural areas in Sri Lanka.

This research investigates rural area students' online adoption during the fourth wave of the coronavirus 2019 (COVID-19) pandemic. The main objective of this study was to identify the factors affecting the adoption of online education in rural areas in Sri Lanka. This case study was carried out based on data gathered from the online survey during the pandemic covering 16 districts in Sri Lanka. Using the ordered probit regression model through the stepwise technique, the study investigates the factors affecting the adoption of online education in rural areas in Sri Lanka. According to the results generated, attitude, perceived use, awareness, and new technology adoption have a positive impact on student adoption of online education in Sri Lanka. Online education so far is one of the effective and feasible solutions for providing education in a pandemic situation in any country. These findings are helpful for responsible educational institutions to address and contribute to key issues such as low perceived use, poor attitude, low awareness, and poor technology adoption. The study will also assist policymakers in preparing a roadmap, at the policy level with the perceived benefits of online education during similar future crises in Sri Lanka. Supplementary Information: The online version contains supplementary material available at 10.1007/s11423-023-10201-8.

Factors impacting employee turnover intentions among professionals in Sri Lankan startups.

Employee turnover is one of the topical issues worldwide. The impact of factors affecting employee turnover varies occasionally and new factors are considered. Many countries have examined various factors that affect employee turnover. The main objective of this research is to consider psychographics and socio-demographic factors in one study and analyse the impact on employee turnover. A Probit regression model through the stepwise technique was used to analyse the collected data. Using ventures in Sri Lanka as a case study, this study demonstrates that employee turnover occurs in different stages and independent factors impact differently in each stage. The study population was professionals who have been a key part of Sri Lankan startups, which involved 230 respondents. Data analysis was performed through a forward stepwise technique through STATA. The results verified that job satisfaction and co-worker support negatively impact employee turnover, whereas leader member exchange positively impacts employee turnover. This study also proved a significant positive relationship between male employees in their thirties and high employee turnover. This study's findings help to identify the areas management should focus on to minimise employee turnover to retain experienced and skilled employees.

Determining the influence of LPI, GCI and IR on FDI: A study on the Asia and Pacific Region.

This study examines the impact of the Logistics Performance Index (LPI), Global Competitiveness Index (GCI) and Interest Rates (IR) on Foreign Direct Investment (FDI) for the Asia & Pacific region. The study is original as extensive evidence on the impact of LPI, GCI and IR on FDI in the Asia & Pacific region are examined initially. For the years 2007, 2010, 2012, 2014, 2016 and 2018, data was gathered for 33 nations in the Asia and Pacific area. Data analysis was performed using a panel regression model and multiple linear regression. The findings of the study reveal that LPI, GCI and IR are the three major factors influencing FDI inflows into the economies. However, the impact of these factors varies from country to country. The results concluded that LPI positively impacts FDI in India, Korea, Lebanon, and Oman. In contrast, a negative influence was observed for China, Kuwait and the Philippines. GCI positively impacts FDI in China, Korea, Kuwait, Pakistan and the Philippines, while a negative impact was observed in Armenia, India, Lebanon. Furthermore, IR has a positive impact on FDI flows in China and Egypt while in Korea and Lebanon, a negative impact was observed. Therefore, policymakers should focus more on improving the infrastructural requirements and macroeconomic factors while considering the other country-level variables that influence the FDI in flow.

Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study.

The aim of this study is to explore the causal relationship between the economy and the elderly population globally as well as continent-wise. This research was designed as a continent-wide study to investigate the differences between several regions simultaneously. The economy was measured by the Gross Domestic Product (GDP) per capita growth rate while the population aged above 65 as a percentage of the total was considered the elderly population. A panel dataset published by the World Bank for a period of six decades from 1961 to 2020 covering 84 countries was used as data for the analysis. Wavelet coherence was the methodology used for the study since it was considered suitable to present causality as well as the causal direction between the two variables for different sections during the six decades. Thereafter, Granger causality was applied for a cross-country analysis to gain further insights on the causality of individual countries over the years. Findings of the study reveal that the causality and its direction have been changing over time for most continents. Negative correlations with the leading variable interchanging with time are evident for the majority of the regions. Nevertheless, results indicate that in a global perspective, elderly population predominantly leads the economic growth with a positive correlation. Research approach allows ascertaining the short-term and medium-term changes that occurred concerning the direction of the relationship throughout the stipulated period of the study, which could not be drawn by any previous study. Even though region-wise literature is available on this topic, global studies for decades have not been conducted yet.

Macroeconomic factors affecting FDI in the African region.

Foreign Direct Investment (FDI) occurs when one country invests in another. Multiple factors have contributed to fluctuations in FDI flows globally. This study investigates the impact of the Logistics Performance Index (LPI), Global Competitiveness Index (GCI) and Interest Rates (IR) on FDI in the African region. The study is significant because the African region is underdeveloped and with an unstable macroeconomic environment. Data were collected for 26 countries in the African region for the years 2007, 2010, 2012, 2014, 2016 and 2018 and analysed using Panel Regression and Multiple Linear Regression models. The study's findings concluded that LPI, GCI, and IR are three major macroeconomic factors impacting FDI inflows. The results indicated that LPI positively impacts FDI in Gambia, Lesotho and Rwanda, while in contrast, LPI impacts FDI negatively in Mauritius. GCI has a positive impact on FDI in Algeria and Lesotho with a negative impact in Rwanda, Mauritius and Namibia. Moreover, IR has a negative impact on FDI in Algeria, Rwanda and Mauritius with a positive impact in Lesotho. Policymakers should pay more attention to the infrastructure development and management of macroeconomic and other factors affecting FDI.

Exploring the growth direction: the impact of exchange rate and purchasing managers index on economic growth in Sri Lanka.

Numerous studies have been conducted, globally and locally, on the impact of the exchange rate on economic growth. In the local context, only a handful of research have investigated this area of study to determine the extent to which the Purchasing Managers' Index influence economic growth with the exchange rate, with limited research have been performed in Sri Lanka. This study explores the impact of exchange rate and Purchasing Managers' Index on economic growth. Consequently, adopting an applied research methodology, the present study was based on secondary data published quarterly by the Central Bank of Sri Lanka reports and the Department of Census and Statistics of Sri Lanka from 2015 to 2021. The Vector autoregression model and Granger Causality Wald test were performed in this study. The empirical findings highlighted that economic growth and Purchasing Managers' Index have a significant negative impact on the economic growth, while the exchange rate had a significant positive impact on the economic growth. Furthermore, the exchange rate and the Purchasing Managers' Index did not help to predict the exchange rate. The implications of the study demonstrate the relevance of the exchange rate and manufacturing Purchasing Managers' Index as indicators of changes in overall economic growth activities at the macro level. The findings will assist the Sri Lankan Government, policymakers, and foreign investors for effective decision making.