Models developed for gross domestic product (GDP) growth forecasting tend to be extremely complex, relying on a large number of variables and parameters. Such complexity is not always to the benefit of the accuracy of the forecast. Economic complexity constitutes a framework that builds on methods developed for the study of complex systems to construct approaches that are less demanding than standard macroeconomic ones in terms of data requirements, but whose accuracy remains to be systematically benchmarked. Here we develop a forecasting scheme that is shown to outperform the accuracy of the five year forecast issued by the International Monetary Fund (IMF) by more than 25% on the available data. The model is based on effectively representing economic growth as a two-dimensional dynamical system, defined by GDP per capita and 'fitness', a variable computed using only publicly available product-level export data. We show that forecasting errors produced by the method are generally predictable and are also uncorrelated to IMF errors, suggesting that our method is extracting information that is complementary to standard approaches. We believe that our findings are of a very general nature and we plan to extend our validations on larger datasets in future works.
We document that aggregate accounting earnings growth is an incrementally significant leading indicator of growth in nominal Gross Domestic Product (GDP). Professional macro forecasters, however, do not fully incorporate the predictive content embedded in publicly available accounting earnings data. As a result, future nominal GDP growth forecast errors are predictable based on accounting earnings data that are available to professional macro forecasters in real time.
Data from the past 60 years for the U.S. economy as a whole and for health care expenditures reveal a robust relationship between the two. It seems premature to dismiss the sluggish economy as the major explanation for the recent slowdown in health care spending. How much will the United States spend on health care during the next decade or two? The answer matters greatly to physicians, federal and state governments, businesses, and the general public. The answer will determine the type and extent of care that physicians can provide to their patients, as well as the amount of physicians' take-home pay. It will also determine how much everyone else can consume or invest in other goods and services. Unfortunately, forecasting health care spending is extremely difficult. Future spending depends in part on developments within the health care sector and in part on developments in . . .
Maximizing science achievement is a critical target of educational policy and has important implications for national and international economic and technological competitiveness. Previous research has identified both science interest and socioeconomic status (SES) as robust predictors of science achievement, but little research has examined their joint effects. In a data set drawn from approximately 400,000 high school students from 57 countries, we documented large Science Interest × SES and Science Interest × Per Capita Gross Domestic Product (GDP) interactions in the prediction of science achievement. Student interest in science is a substantially stronger predictor of science achievement in higher socioeconomic contexts and in higher-GDP nations. Our results are consistent with the hypothesis that in higher-opportunity contexts, motivational factors play larger roles in learning and achievement. They add to the growing body of evidence indicating that substantial cross-national differences in psychological effect sizes are not simply a logical possibility but, in many cases, an empirical reality.
Medical goods and services are generally viewed as necessities. Even so, the latest recession had a dramatic effect on their utilization. US health spending grew more slowly in 2009 and 2010-at rates of 3.8 percent and 3.9 percent, respectively-than in any other years during the fifty-one-year history of the National Health Expenditure Accounts. In 2010 extraordinarily slow growth in the use and intensity of services led to slower growth in spending for personal health care. The rates of growth in overall US gross domestic product (GDP) and in health spending began to converge in 2010. As a result, the health spending share of GDP stabilized at 17.9 percent.
Objective:To analyse associations between the clinical status of patients with rheumatoid arthritis (RA) and the gross domestic product (GDP) of their resident country.Methods:The Quantitative Standard Monitoring of Patients with Rheumatoid Arthritis (QUEST–RA) cohort includes clinical and questionnaire data from 6004 patients who were seen in usual care at 70 rheumatology clinics in 25 countries as of April 2008, including 18 European countries. Demographic variables, clinical characteristics, RA disease activity measures, including the disease activity score in 28 joints (DAS28), and treatment-related variables were analysed according to GDP per capita, including 14 “high GDP” countries with GDP per capita greater than US$24 000 and 11 “low GDP” countries with GDP per capita less than US$11 000.Results:Disease activity DAS28 ranged between 3.1 and 6.0 among the 25 countries and was significantly associated with GDP (r = −0.78, 95% CI −0.56 to −0.90, r2 = 61%). Disease activity levels differed substantially between “high GDP” and “low GDP” countries at much greater levels than according to whether patients were currently taking or not taking methotrexate, prednisone and/or biological agents.Conclusions:The clinical status of patients with RA was correlated significantly with GDP among 25 mostly European countries according to all disease measures, associated only modestly with the current use of antirheumatic medications. The burden of arthritis appears substantially greater in “low GDP” than in “high GDP” countries. These findings may alert healthcare professionals and designers of health policy towards improving the clinical status of patients with RA in all countries.