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• Investigating the sustainability of remarkable GDP growth in emerging economies. • Highlighting the roles of energy and environment in economic growth. • STFP is decomposed to identify the drivers of sustainable development. • Regional disparities are compared by incorporating regional heterogeneities. • Providing implications to promote sustainable development by technology spillover. The remarkable GDP growth along with the dramatic increases in energy consumption and pollution emissions in emerging economies raise the concerns for the sustainability of their development pattern. However, the precise role of how energy and environment contribute to economic growth in emerging economies is still unknown. This paper explores the sustainability of remarkable GDP growth in emerging economies by using non-radial directional distance function (NDDF) to identify the sustainable total-factor productivity (STFP) growth in the emerging economies and comparing it with that in developed economies. Our research extends previous literature by highlighting the roles of energy and environment in economic growth. The results raise the concerns on the sustainability of the remarkable GDP growth (especially after 2000) in emerging economies due to their slow STFP growth after excluding the contributions from energy and environment. Furthermore, it is also found that compared with developed economies, the slower STFP growth in emerging economies is mainly caused by their disadvantages in innovation, although they are able to utilize existing technology by catch-up effect. Besides, analysis from the group heterogeneity among Asia, Eastern Europe and Latin America gives a better grasp of implications for stimulating the sustainable growth in emerging economies by promoting technology spillover from developed economies. [ABSTRACT FROM AUTHOR]

Subseasonal predictions of the regional summer rainfall over several tropical Asian ocean and land domains are examined using hindcasts by the NCEP CFSv2. Higher actual and potential forecast skill are found over oceans than over land. The forecast for Arabian Sea (AS) rainfall is most skillful, while that for Indo-China (ICP) rainfall is most unskillful. The rainfall-surface temperature (ST) relationship over AS is characterized by strong and fast ST forcing but a weak and slow ST response, while the relationships over the Bay of Bengal, the South China Sea (SCS), and the India subcontinent (IP) show weak and slow ST forcing, but apparently strong and rapid ST response. Land-air interactions are often less noticeable over ICP and southern China (SC) than over IP. The CFSv2 forecasts reasonably reproduce these observed features, but the local rainfall-ST relationships often suffer from different degrees of unrealistic estimation. Also, the observed local rainfall is often related to the circulation over limited regions, which gradually become more extensive in forecasts as lead time increases. The prominent interannual differences in forecast skill of regional rainfall are sometimes associated with apparent disparities in forecasts of local rainfall-ST relationships. Besides, interannual variations of boreal summer intraseasonal oscillation, featured by obvious changes in frequency and amplitude of certain phases, significantly modulate the forecasts of rainfall over certain regions, especially the SCS and SC. It is further discussed that the regional characteristics of rainfall and model's deficiencies in capturing the influences of local and large-scale features are responsible for the regional discrepancies of actual predictability of rainfall. [ABSTRACT FROM AUTHOR]