Nighttime light data derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) in conjunction with the Soumi National Polar-Orbiting Partnership Visible ...Infrared Imaging Radiometer Suite (NPP-VIIRS) possess great potential for measuring the dynamics of Gross Domestic Product (GDP) at large scales. The temporal coverage of the DMSP-OLS data spans between 1992 and 2013, while the NPP-VIIRS data are available from 2012. Integrating the two datasets to produce a time series of continuous and consistently monitored data since the 1990s is of great significance for the understanding of the dynamics of long-term economic development. In addition, since economic developmental patterns vary with physical environment and geographical location, the quantitative relationship between nighttime lights and GDP should be designed for individual regions. Through a case study in China, this study made an attempt to integrate the DMSP-OLS and NPP-VIIRS datasets, as well as to identify an optimal model for long-term spatiotemporal GDP dynamics in different regions of China. Based on constructed regression relationships between total nighttime lights (TNL) data from the DMSP-OLS and NPP-VIIRS data in provincial units (R2 = 0.9648, P < 0.001), the temporal coverage of nighttime light data was extended from 1992 to the present day. Furthermore, three models (the linear model, quadratic polynomial model and power function model) were applied to model the spatiotemporal dynamics of GDP in China from 1992 to 2015 at both the country level and provincial level using the extended temporal coverage data. Our results show that the linear model is optimal at the country level with a mean absolute relative error (MARE) of 11.96%. The power function model is optimal in 22 of the 31 provinces and the quadratic polynomial model is optimal in 7 provinces, whereas the linear model is optimal only in two provinces. Thus, our approach demonstrates the potential to accurately and timely model long-term spatiotemporal GDP dynamics using an integration of DMSP-OLS and NPP-VIIRS data.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with ...economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980–2015, and health spend data from 1995–2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9·21 trillion in 2014 to $24·24 trillion (uncertainty interval UI 20·47–29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1–6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8–4·9). High-income countries are expected to grow at 2·1% (UI 1·8–2·4) and low-income countries are expected to grow at 1·8% (1·0–2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133–181) per capita in 2030 and $195 (157–258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157–258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential. Funding Bill & Melinda Gates Foundation.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Purpose
The hospitality industry experienced an unanticipated challenge from the COVID-19 pandemic. However, research in this area is scarce. Accordingly, this study aims to unfold a three-angled ...research agenda to intensify the knowledge advancement in the hospitality sector. It proposes a theoretical framework by extending the protection motivation theory (PMT) to explain the guest’s intent to adopt artificial intelligence (AI) and robotics as a protective measure in reaction to COVID-19.
Design/methodology/approach
The research is centered on outlining the pertinent literature on hospitality management practices and the guest’s transformed behavior during the current crisis. This study intends to identify a research agenda based on investigating hospitality service trends in today’s changing times.
Findings
The study sets out a research agenda that includes three dimensions as follows: AI and robotics, cleanliness and sanitation and health care and wellness. This study’s findings suggest that AI and robotics may bring out definite research directions at the connection of health crisis and hospitality management, taking into account the COVID-19 crisis.
Practical implications
The suggested research areas are anticipated to propel the knowledge base and help the hospitality industry retrieve the COVID-19 crisis through digital transformation. AI and robotics are at the cusp of invaluable advancement that can revive the hotels while re-establish guests’ confidence in safe hotel practices. The proposed research areas are likely to impart pragmatic lessons to the hospitality industry to fight against disruptive situations.
Originality/value
This study stands out to be pioneer research that incorporated AI and robotics to expand the PMT and highlights how behavioral choices during emergencies can bring technological revolution.
Biological invasions continue to threaten the stability of ecosystems and societies that are dependent on their services. Whilst the ecological impacts of invasive alien species (IAS) have been ...widely reported in recent decades, there remains a paucity of information concerning their economic impacts. Europe has strong trade and transport links with the rest of the world, facilitating hundreds of IAS incursions, and largely centralised decision-making frameworks. The present study is the first comprehensive and detailed effort that quantifies the costs of IAS collectively across European countries and examines temporal trends in these data. In addition, the distributions of costs across countries, socioeconomic sectors and taxonomic groups are examined, as are socio-economic correlates of management and damage costs. Total costs of IAS in Europe summed to US$140.20 billion (or €116.61 billion) between 1960 and 2020, with the majority (60%) being damage-related and impacting multiple sectors. Costs were also geographically widespread but dominated by impacts in large western and central European countries, i.e. the UK, Spain, France, and Germany. Human population size, land area, GDP, and tourism were significant predictors of invasion costs, with management costs additionally predicted by numbers of introduced species, research effort and trade. Temporally, invasion costs have increased exponentially through time, with up to US$23.58 billion (€19.64 billion) in 2013, and US$139.56 billion (€116.24 billion) in impacts extrapolated in 2020. Importantly, although these costs are substantial, there remain knowledge gaps on several geographic and taxonomic scales, indicating that these costs are severely underestimated. We, thus, urge increased and improved cost reporting for economic impacts of IAS and coordinated international action to prevent further spread and mitigate impacts of IAS populations.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Understanding strategic commitments and policy responses to overcome antimicrobial resistance at the national, regional, and global levels is required to evaluate current progress and direct future ...planning. National action plans (NAPs) are the primary mechanism for guiding national strategy and action for antimicrobial resistance governance. Although several NAPs have been developed, no comprehensive content analysis of these plans exists. Using a governance framework, we aimed to assess all publicly available NAPs on antimicrobial resistance.
We systematically reviewed the contents of NAPs on antimicrobial resistance from 114 countries, applying a governance framework containing 18 domains and 54 indicators in three integral areas: policy design, implementation tools, and monitoring and evaluation. As well as manually searching NAPs and doing online and literature searches that were relevant to specific indicators from repository inception to June 1, 2022, several data sources were used to generate scores, including the Tripartite Antimicrobial Resistance Country Self-Assessment Survey, the Global Antimicrobial Resistance and Use Surveillance System, the Global Antimicrobial Resistance Research and Development Hub, and various WHO datasets. NAPs were included if the country had also submitted the NAP to the Tripartite Antimicrobial Resistance Country Self-Assessment Survey 2020–21, if the NAP was retrievable through a publicly accessible database or website, and if the NAP was either published in English or eligible for machine translation. Three researchers independently reviewed each NAP and were initially blinded to the evaluations of other researchers. They generated a score using a quantification system for each of 54 indicators. The Cochrane protocol for ensuring reliability was followed. The three researchers were then unblinded and met to resolve any disagreements in scoring to reach a consensus agreement. In each case of discrepancy, consensus was reached between the researchers. We developed criteria to standardise the process of quantifying each indicator. We also weighted and collated relevant national data from various sources to generate composite scores concordant with the key governance areas. We transformed these data to a scale of 0 (worst) to 100 (best), ranked countries on the basis of their mean scores, and used descriptive statistics to analyse global and regional trends.
306 NAPs were identified and 114 were eligible for analysis. Between 2020 and 2021, the mean antimicrobial resistance governance score was 51 (SD 14). Norway had the highest governance score (mean 85 SD 32), and the Federated States of Micronesia had the lowest governance score (28 37). The highest scoring domain was participation (83 16), and the lowest scoring domains were accountability (30 18) and feedback mechanism (30 25). Domains relating to policy design (55 13) and implementation tools (54 17) scored similarly, whereas monitoring and evaluation (38 20) efforts were lower.
International efforts to control antimicrobial resistance varied considerably between countries. Monitoring and evaluation efforts need improving for continuous understanding of national and international progress. International response might not be commensurate with the scale and severity of antimicrobial resistance.
None.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Air transport increases economic Growth, validating the TLGH in the US between 1981 and 2017.•The connection between foreign direct investment and ICTs enhances economic growth in the US.•Coal rents ...and ICTs promote economic growth ins US.•Energy-led growth hypothesis affirmed as coal energy spurs economic growth.
This study analyses the causal and long-run linkage between air transport and economic growth. It was conducted to validate the tourism-led growth hypothesis for the United States (US) during the period 1981–2017 and includes Information and Communication Technologies (ICTs) alongside coal rents in the tourism-led growth hypothesis. This study presents a new direction for future studies by considering the relevance of the fourth industrial revolution (Industry 4.0), particularly in the US. To achieve the stated claim, this study considers as additional explanatory variables how ICTs moderate the impact of Foreign Direct Investment (FDI) on GDP. The empirical result confirms a connection between the Industry 4.0 era and the role of ICTs, which promotes substantial changes in the way of life and productivity. This has led to a vast technological advancement, which is in line with but at a faster pace than the technological advancement of previous revolutions. From empirical results, the study provides relevant policy recommendations related to the role of natural resources, new technologies and tourism on US GDP, while it also provides evidence of the positive effect of ICTs over FDI under the Industry 4.0 era.
Display omitted
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The statement of sustainability in the sustainable development goals (SDGs) framework needs to be supplemented by a formal proof that intergenerational well-being also improves. This is the first ...study that aims to provide empirical evidence that links the progress of the SDGs and the changes in well-being, which are proxied by the SDG Index and the Inclusive Wealth (IW) Index, respectively. We propose an SDGs-wealth model which was analyzed using a machine learning method involving a balanced panel of 147 countries for 2000-2019. We find a strong correlation between wealth and the SDGs, with Goals 12, 13, and 7 being the most significant predictors of wealth. In contrast to Goals 12 and 13, we find a positive correlation between Goal 7 and the per capita IW Index, suggesting that promoting affordable and clean energy is beneficial for wealth accumulation. Quite the opposite, fostering responsible consumption and production and climate actions might be detrimental to wealth. We also find an alarming result for 50 countries in our study since they have deviated from the sustainable development trajectories either in the short or long run. Our study suggests that to achieve sustainable development, instead of focusing on the complex interactions among the SDGs, policymakers should put a stronger focus on improving IW.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
499.
ENTREPRENEURSHIP AND THE BUSINESS CYCLE Koellinger, Philipp D.; Thurik, A. Roy
The review of economics and statistics,
11/2012, Volume:
94, Issue:
4
Journal Article
Peer reviewed
Open access
We find new empirical regularities in the business cycle in a cross-country panel of 22 OECD countries for the period 1972 to 2007; entrepreneurship Granger-causes the cycles of the world economy. ...Furthermore, the entrepreneurial cycle is positively affected by the national unemployment cycle. We discuss possible causes and implications of these findings.
Full text
Available for:
BFBNIB, CEKLJ, INZLJ, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK, ZRSKP
Corresponding to increased realization of the impacts of natural hazards in recent years and the need for quantification of disaster risk, there has been increasing demand from the public sector for ...openly available disaster risk profiles. Probabilistic disaster risk profiles provide risk assessments and estimates of potential damage to property caused by severe natural hazards. These profiles outline a holistic view of financial risk due to natural hazards, assisting governments in long-term planning and preparedness. A Country Disaster Risk Profile (CDRP) presents a probabilistic estimate of risk aggregated at the national level. A critical component of a CDRP is the development of consistent and robust exposure model to complement existing hazard and vulnerability models. Exposure is an integral part of any risk assessment model, capturing the attributes of all exposed elements grouped by classes of vulnerability to different hazards, and analyzed in terms of value, location and relative importance (e.g. critical facilities and infrastructure).
Using freely available (or available at minimum cost) datasets, we present a methodology for an exposure model to produce three independent geo-referenced databases to be used in national level disaster risk profiling for the public sector. These databases represent aggregated economic value at risk at 30 arc-second spatial resolution (approximately 1×1-km grid at the equator) using a top-down (or downscaling) approach. To produce these databases, the models used are: 1) a building inventory stock model which captures important attributes such as geographical location, urban/rural classification, type of occupancy (e.g. residential and non-residential), building typology (e.g. wood, concrete, masonry, etc.) and economic (replacement) value; 2) a non-building infrastructure density and value model that also corresponds to the fiscal infrastructure portion of the Gross Capital Stock (GCS) of a country; and 3) a spatially and sectorially disaggregated Gross Domestic Product (GDP) model that relates to the production (flow) of goods and services of a country. These models can be adapted to produce - independently or cohesively - a composite exposure database. Finally, we provide an example of the model's use in economic loss estimation for the reoccurrence of the 1882 Mw 7.8 Panama earthquake.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
You have reached the maximum number of search results that are displayed.
For better performance, the search offers a maximum of 1,000 results per query (or 50 pages if the option 10/page is selected).
Consider using result filters or changing the sort order to explore your results further.
PDF
