scholarly journals Using big data to map the relationship between time perspectives and economic outputs

2019 ◽  
Vol 42 ◽  
Author(s):  
Christopher Y. Olivola ◽  
Helen Susannah Moat ◽  
Tobias Preis

Abstract Recent studies have shown that population-level time perspectives can be approximated using “big data” on search engine queries, and that these indices, in turn, predict the per-capita Gross Domestic Product of countries. Although these findings seem to support Baumard's suggestion that affluence makes people more future-oriented, they also reveal a more complex relationship between time perspectives and economic outputs.

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Rajesh Vedanthan ◽  
Mondira Ray ◽  
Valentin Fuster ◽  
Ellen Magenheim

Introduction: Hypertension is the leading global risk for mortality and its prevalence is increasing in many low- and middle-income countries. Hypertension treatment rates are low worldwide, potentially in part due to insufficient human resources. However, the relationship between health worker density and hypertension treatment rates is unknown. Objective: To conduct an econometric analysis of the relationship between health worker density and hypertension treatment rates worldwide. Methods: Hypertension treatment rates were collected from published reports between 1980 and 2010. Data on health worker (physician and nurse) density were obtained from the World Health Organization (WHO). Data for potential confounding variables--per capita gross domestic product, hospital bed density, burden of infectious diseases, land area and urban population--were obtained from WHO and World Bank databases. Potential interaction by per capita gross domestic product was evaluated. Multivariable logistic-logarithmic regression analysis was performed using Stata. Results: Full data were available from 146 countries spanning all World Bank income classification categories. Health worker density was significantly associated with hypertension treatment rate in the unadjusted model (beta = 0.23; p < 0.005). In the fully adjusted model, the association remained positive but was not statistically significant (beta = 0.30; p = 0.078) (Figure). Hypertension treatment rates were more strongly related to physician than nurse density (beta = 0.21 vs 0.08; p = 0.10 vs 0.49). Conclusion: Hypertension treatment rates across the world appear to be related to health worker density, although the relationship does not achieve strict statistical significance. Our results suggest that a 10% increase in health worker density is associated with a 2-3% increase in hypertension treatment rate. Given the global burden of hypertension and other chronic diseases, WHO guidelines for health workforce staffing may need to be reconsidered.


2021 ◽  
Vol 52 (3) ◽  
pp. 640-646
Author(s):  
Ali S. Shukr ◽  
Basim H. Hameed

The research aims to study the most important factors affecting carbon dioxide emissions Co2, through a model. Explanatory variables were used in the model, which are the average per capita gross domestic product (GDP), the square per capita gross domestic product (GDPSQ), per capita energy consumption (CONS), and the POP population for the period 2000-2017 via using  double logarithmic formula  which is more suitable for economic, statistical and econometric  logic in this type of studies, the results of the research showed that all the explanatory variables were statistically significant at the level of 1% and that the model was significant as a whole according to the statistic F and the value of R2=0.99. Economically, we find that the parameter of the average per capita GDP was 0.46 and it came with a positive signal consistent with the methodology of the Environmental Curve Kuznets ECK, the parameter of per capita energy consumption was 0.04, and it came with a negative sign that contradicts the Kuznets methodology,  the reason may belong to the conditions that   affected the country after 2003. The research recommended to go to investing in renewable energy, because it is environmentally friendly, such as sun energy, and to reduce the size of the gas in the sectors emitting to it, such as the transport sector, factories, the extraction sector, and manufacturing industries, in order to preserve the integrity of the environment and the plant and animal wealth it contains ,to a better environment in Iraq.


2021 ◽  
pp. 139156142110390
Author(s):  
Fahmida Khatun ◽  
Syed Yusuf Saadat

Inequality in the distribution of income can be beneficial or detrimental for economic growth depending on the level of inequality. This study advocates that when income inequality is low, increase in income inequality increases economic growth, whereas when income inequality is high, increase in income inequality decreases economic growth. The level of inequality that maximizes economic growth is defined as the optimum level of income inequality. This article attempts to determine the optimum level of income inequality for South Asia through an econometric analysis. It uses panel data from Bangladesh, India, Nepal, Pakistan and Sri Lanka, over a 34-year period to undertake a systematic investigation using panel instrumental variables techniques. The results of this study confirm that an optimum level of income inequality does exist, and occurs at a Gini coefficient value of 0.4492. Thus, this research empirically confirms that the relationship between income inequality and economic growth is non-linear. Further calculations show that for an economy that is at the optimum level of income inequality, the per capita gross domestic product can be expected to double within approximately 13 years, provided all other factors are held constant. However, a change in the Gini coefficient by 0.10 units in either direction—higher or lower—away from the optimum level, can increase the number of years for the per capita gross domestic product to double by 55 to 57 years, depending on the method of approximation. JEL: D31, D63, O15, O40


2018 ◽  
Vol 4 ◽  
pp. 237802311877362 ◽  
Author(s):  
Xiaorui Huang ◽  
Andrew K. Jorgenson

The authors examine the potentially asymmetrical relationship between economic development and consumption-based and production-based CO2 emissions. They decompose economic development into economic expansions and contractions, measured separately as increases and decreases in gross domestic product per capita, and examine their unique effects on emissions. Analyzing cross-national data from 1990 to 2014, the authors find no statistical evidence of asymmetry for the overall sample. However, for a sample restricted to nations with populations larger than 10 million, the authors observe a contraction-leaning asymmetry whereby the effects of economic contraction on both emissions outcomes are larger in magnitude than the effects of economic expansion. This difference in magnitude is more pronounced for consumption-based emissions than for production-based emissions. The authors provide tentative explanations for the variations in results across the different samples and emissions measures and underscore the need for more nuanced research and deeper theorization on potential asymmetry in the relationship between economic development and anthropogenic emissions.


2003 ◽  
Vol 92 (2) ◽  
pp. 426-426 ◽  
Author(s):  
David Lester

Individualism ratings for 27 nations were not associated with suicide or homicide rates after controls for per capita gross domestic product.


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