Testing the Stochastic Convergence of Ecological Indicators in BRICS in the Perspective of Public Health.

This paper assesses the stochastic convergence of relative per capita ecological footprints within BRICS countries over the period 1961-2017 in the field of Public Health. Our initiatives have targeted ecological Indicator and health behaviors. Using the local Whittle estimator and some of its variants we assess whether relative per capita ecological footprints are long memory processes which, although highly persistent, may revert to their mean/trend in the long run thereby indicating evidence of stochastic convergence, or divergent processes in nutshell. Furthermore, we test whether (possibly) slow convergence or the complete lack of it may be the result of structural changes to the deterministics of each of the relative per capita footprint series by means of the tests of Berkes et al. (1) and Mayoral (2). For the ease of comparison, this paper assesses the stochastic convergence of relative per capita ecological capacities for BRICS as well. Our results show relatively strong evidences against stochastic convergence of ecological footprints. Furthermore, with regard to China and Russia, our results also decisively indicate that a slow or lack of convergence is the results of a structural break in the relative per capita ecological footprint series. However, our empirical researches support stochastic convergence of relative per capita ecological capacities for BRICS. In addition, we can conclude whether the per capita ecological footprints converge or not is dependent on the level of economic development, and the stochastic convergence occurs in those rich countries more probably, indicating that public health is becoming a more serious concern in developing countries.

Rural Light Pollution from Shale Gas Development and Associated Sleep and Subjective Well-Being.

The shale oil and gas boom has had large economic, environmental, and social impacts on rural communities in the United States. This study provides novel estimates of the impacts of shale oil and gas development on light pollution in rural areas of the United States. Using nationwide, time-calibrated DMSP-OLS database from 2000 to 2012, we find robust evidence that the shale oil and gas boom significantly increased light pollution in rural areas. We then assess associations between horizontal drilling and subjective self-rated health using nationwide data from the Behavioral Risk Factor Surveillance System (BRFSS) from 2000 to 2012. Our findings suggest that insufficient sleep and poor health (physical or mental) are associated with increased drilling in rural areas. These results provide support for drilling-related light pollution as an additional environmental pathway of concern for public health beyond the mechanisms of air or water pollution.

INTRODUCTION TO THE EMF 32 STUDY ON U.S. CARBON TAX SCENARIOS.

This paper is an introduction to, "The EMF 32 Study on U.S. Carbon Tax Scenarios," part of the Stanford Energy Modeling Forum (EMF) Model Inter-comparison Project (MIP) number 32. Eleven modeling teams participated in this study examining the economic and environmental impacts of various carbon tax trajectories and differing uses of carbon tax revenues. This special issue of Climate Change Economics documents the results of this study with four crosscutting papers that summarize results across models, and ten papers from individual modeling teams.