scholarly journals Non- $$\hbox {CO}_2$$ CO 2 Generating Energy Shares in the World: Cross-Country Differences and Polarization

2014 ◽  
Vol 61 (3) ◽  
pp. 319-343 ◽  
Author(s):  
Adolfo Maza ◽  
José Villaverde ◽  
María Hierro
2017 ◽  
Vol 33 (S1) ◽  
pp. 210-211
Author(s):  
Songul Cinaroglu ◽  
Onur Baser

INTRODUCTION:Increasing access to surgical care is crucial in improving the general health status of a population. Despite studies indicating the cross-country differences of general health indicators, there is a scarcity of knowledge focusing on the cross-country differences of surgical indicators. This study aims to classify countries according to surgical care indicators and identify risk predictors of catastrophic surgical care expenditures.METHODS:For this study, data were used from the World Health Organization and the World Bank on 177 countries. The following variable groups were chosen: total density of medical imaging technologies, surgical workforce distribution, number of surgical procedures, and risk of catastrophic surgical care expenditures. The k-means clustering algorithm was used to classify countries according to the surgical indicators. The optimal number of clusters was determined with a within-cluster sum of squares and a scree plot. A Silhouette index was used to examine clustering performance, and a random forest decision tree approach was used to determine risk predictors of catastrophic surgical care expenditures.RESULTS:The surgical care indicator results delineated the countries into four groups according to each country's income level. The cluster plot indicated that most high-income countries (for example, United States, United Kingdom, Norway) are in the first cluster. The second cluster consisted of four countries: Japan, San Marino, Marshall Islands, and Monaco. Low-income countries (for example, Ethiopia, Guatemala, Kenya) and middle-income countries (for example, Brazil, Turkey, Hungary) are represented in the third and fourth clusters, respectively. The third cluster had a high Silhouette index value (.75). The densities of both surgeons and medical imaging technology were risk determiners of catastrophic surgical care expenditures (Area Under Curve = .82).CONCLUSIONS:Our results demonstrate a need for more effective health plans if the differences between countries surgical care indicators are to be overcome. We recommend that health policymakers reconsider distribution strategies for the surgical workforce and medical imaging technology in the interest of accessibility and equality.


2019 ◽  
Vol 19 (179) ◽  
Author(s):  
Jorge Alvarez ◽  
Claudia Berg

A large share of cross-country differences in productivity is explained by differences in agricultural productivity. Using a combination of sub-national agricultural statistics and geospatial datasets on crop-specific potential yields, we study the main drivers of this variation from a macroeconomic perspective. We find that differences in geographically-induced crop-specific comparative advantages can explain a substantial share of the variation in yields across the world. Data reveal substantial gaps between potential and observed yields in most countries. When decomposing these within country gaps, we find that crop selection gaps are on average larger than those induced by input usage alone. The results highlight the importance of understanding the interaction of geography and crop selection drivers in assessing aggregate agricultural productivity differences.


2020 ◽  
Author(s):  
Fariborz Moshirian ◽  
Nguyen Thi Thuy ◽  
Jin Yu ◽  
Bohui Zhang

2020 ◽  
pp. 002202212098237
Author(s):  
Wolfgang Messner

The past few decades have seen an explosion in the interest in cultural differences and their impact on many aspects of business management. A noticeable feature of most academic studies and practitioner approaches is the predominant use of national boundaries and group-level averages as delimiters and proxies for culture. However, this largely ignores the significance that intra-country differences and cross-country similarities can have for identifying psychological phenomena. This article argues for the importance of considering intra-cultural variation for establishing connections between two different cultures. It uses empirical distributions of cultural values that occur naturally within a country, thereby making intracultural differences interpretable and actionable. For measuring cross-country differences, the Gini/Weitzman overlapping index and the Kullback-Leibler divergence coefficient are used as difference measures between two distributions. The properties of these measures in comparison to traditional group-level mean-based distance measures are analyzed, and implications for cross-cultural and international business research are discussed.


2009 ◽  
Vol 2 (1/2) ◽  
pp. 112 ◽  
Author(s):  
Chunyan Li ◽  
Roberta J. Cable ◽  
Patricia Healy

Kyklos ◽  
2007 ◽  
Vol 60 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Sara Connolly ◽  
Shaun P. Hargreaves Heap

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