In this paper, the concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analys...

/pdf/social-capital-in-the-creation-of-human-capital-1836wo2872.pdf

Social Capital in the Creation of Human Capital

http://individual.utoronto.ca/zheli/sa1.pdf

On the mechanics of economic development

This paper examines whether the Solow growth model is consistent with the international variation in the standard of living. It shows that an augmented Solow model that includes accumulation of human as well as physical capital provides an excellent description of the cross-country data. The paper also examines the implications of the Solow model for convergence in standards of living, that is, for whether poor countries tend to grow faster than rich countries. The evidence indicates that, holding population growth and capital accumulation constant, countries converge at about the rate the augmented Solow model predicts. This paper takes Robert Solow seriously. In his classic 1956 article Solow proposed that we begin the study of economic growth by assuming a standard neoclassical production function with decreasing returns to capital. Taking the rates of saving and population growth as exogenous, he showed that these two vari- ables determine the steady-state level of income per capita. Be- cause saving and population growth rates vary across countries, different countries reach different steady states. Solow's model gives simple testable predictions about how these variables influ- ence the steady-state level of income. The higher the rate of saving, the richer the country. The higher the rate of population growth, the poorer the country. This paper argues that the predictions of the Solow model are, to a first approximation, consistent with the evidence. Examining recently available data for a large set of countries, we find that saving and population growth affect income in the directions that Solow predicted. Moreover, more than half of the cross-country variation in income per capita can be explained by these two variables alone. Yet all is not right for the Solow model. Although the model correctly predicts the directions of the effects of saving and

/pdf/a-contribution-to-the-empirics-of-economic-growth-27cl5gkqam.pdf

A Contribution to the Empirics of Economic Growth

Background Global and regional projections of mortality and burden of disease by cause for the years 2000, 2010, and 2030 were published by Murray and Lopez in 1996 as part of the Global Burden of Disease project. These projections, which are based on 1990 data, continue to be widely quoted, although they are substantially outdated; in particular, they substantially underestimated the spread of HIV/AIDS. To address the widespread demand for information on likely future trends in global health, and thereby to support international health policy and priority setting, we have prepared new projections of mortality and burden of disease to 2030 starting from World Health Organization estimates of mortality and burden of disease for 2002. This paper describes the methods, assumptions, input data, and results. Methods and Findings Relatively simple models were used to project future health trends under three scenarios—baseline, optimistic, and pessimistic—based largely on projections of economic and social development, and using the historically observed relationships of these with cause-specific mortality rates. Data inputs have been updated to take account of the greater availability of death registration data and the latest available projections for HIV/AIDS, income, human capital, tobacco smoking, body mass index, and other inputs. In all three scenarios there is a dramatic shift in the distribution of deaths from younger to older ages and from communicable, maternal, perinatal, and nutritional causes to noncommunicable disease causes. The risk of death for children younger than 5 y is projected to fall by nearly 50% in the baseline scenario between 2002 and 2030. The proportion of deaths due to noncommunicable disease is projected to rise from 59% in 2002 to 69% in 2030. Global HIV/AIDS deaths are projected to rise from 2.8 million in 2002 to 6.5 million in 2030 under the baseline scenario, which assumes coverage with antiretroviral drugs reaches 80% by 2012. Under the optimistic scenario, which also assumes increased prevention activity, HIV/AIDS deaths are projected to drop to 3.7 million in 2030. Total tobacco-attributable deaths are projected to rise from 5.4 million in 2005 to 6.4 million in 2015 and 8.3 million in 2030 under our baseline scenario. Tobacco is projected to kill 50% more people in 2015 than HIV/AIDS, and to be responsible for 10% of all deaths globally. The three leading causes of burden of disease in 2030 are projected to include HIV/AIDS, unipolar depressive disorders, and ischaemic heart disease in the baseline and pessimistic scenarios. Road traffic accidents are the fourth leading cause in the baseline scenario, and the third leading cause ahead of ischaemic heart disease in the optimistic scenario. Under the baseline scenario, HIV/AIDS becomes the leading cause of burden of disease in middle- and low-income countries by 2015. Conclusions These projections represent a set of three visions of the future for population health, based on certain explicit assumptions. Despite the wide uncertainty ranges around future projections, they enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, the continued spread of HIV/AIDS in many regions, and the continuation of the epidemiological transition in developing countries. The results depend strongly on the assumption that future mortality trends in poor countries will have a relationship to economic and social development similar to those that have occurred in the higher-income countries.

/pdf/projections-of-global-mortality-and-burden-of-disease-from-16p7emcopm.pdf

Projections of Global Mortality and Burden of Disease from 2002 to 2030

/pdf/discretion-versus-policy-rules-in-practice-564eovjuxn.pdf

Discretion versus policy rules in practice

Driving cessation can be one of the adjustments made following a diagnosis of dementia. Little is known about the views and opinions of people living with dementia about this. The study aimed to gather a broad idea of the expectations, impacts and the process of driving cessation from the perspective of those living with dementia.

Driving following a diagnosis of dementia: Exploring the views and experiences of people with dementia—A UK survey

/pdf/islam-and-economic-growth-2353e7tfbx.pdf

Islam and Economic Growth


 A Digital Twin has been developed for the Glen Lyon FPSO to maintain vessel integrity and ensure operation within the allowable design limits. At the core of this Digital Twin are two components: the Integrated Marine Monitoring System (IMMS) installed on the FPSO, and BMT DEEP, a cloud-based platform that stores, manages, integrates, post-processes and displays the vast data sets collected by the IMMS as well as other data sources. This paper focuses on harnessing the benefits of Digital Twin Technology, by bringing in data from all sources and enabling to synthesize and monitor the FPSO in near real-time from any remote location. This Digital Twin is designed to allow rapid query of the data by filtering with any time window in terms of hour, day, month, quarter, and year of data collection for the life of the asset.
 Several sensors feed data to the Glen Lyon IMMS. The sensors include FPSO motion, stress response monitoring, and metocean monitoring. In addition to the FPSO based measurements, metocean data is also available from Met Office weather buoy K7, and wind measurements from the nearby Clair platform. A composite of the measured metocean parameters is generated from the quality control of the data. This quality-controlled data is visualized on DEEP as a time series, as well as comparisons with the basis of design data for the facility in terms of several statistical charts that form the metocean and structural dashboards. Some key insights and findings from these comparisons are presented.

Generating a Digital Twin of the Glen Lyon FPSO

/pdf/beseri-sermaye-ve-buyume-3l9ase9tan.pdf

Beşeri Sermaye ve Büyüme

A safe asset’s real value is insulated from shocks, including declines in GDP from rare macroeconomic disasters. However, in a Lucas-tree world, the aggregate risk is given by the process for GDP and cannot be altered by the creation of safe assets. Therefore, in the equilibrium of a representative-agent version of this economy, the quantity of safe assets will be nil. With heterogeneity in coefficients of relative risk aversion, safe assets can take the form of private bond issues from low-risk-aversion to high-risk-aversion agents. The model assumes Epstein-Zin/Weil preferences with common values of the intertemporal elasticity of substitution and the rate of time preference. The model achieves stationarity by allowing for random shifts in coefficients of relative risk aversion. We derive the equilibrium values of the ratio of safe to total assets, the shares of each agent in equity ownership and wealth, and the rates of return on safe and risky assets. In a baseline case, the steady-state risk-free rate is 1.0% per year, the unlevered equity premium is 4.2%, and the quantity of safe assets ranges up to 15% of economy-wide assets (comprising the capitalized value of GDP). A disaster shock leads to an extended period in which the share of wealth held by the low-risk-averse agent and the risk-free rate are low but rising, and the ratio of safe to total assets is high but falling. In the baseline model, Ricardian Equivalence holds in that added government bonds have no effect on rates of return and the net quantity of safe assets. Surprisingly, the crowding-out coefficient for private bonds with respect to public bonds is not 0 or -1 but around -0.5, a value found in some existing empirical studies.

Safe Assets

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Robert J. Barro

Author Tools

Chat about Author