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Although the developed world has almost completed the process of urbanization, developing countries are still rapidly urbanizing. Applying the extended stochastic regression on population, affluence, and technology (STIRPAT) model for the period 2000–2019, this article is an endeavor to explore the consequences of urbanization along with gross domestic product (GDP) per capita, foreign direct investment (FDI) inflow, trade openness, and mobile phone penetration on carbon dioxide emissions in 68 low-income and lower-middle-income countries across Asia, Africa, Middle East, and South America. Initially, the study used a panel unit root test to identify whether the variables are stationary or not. Subsequently, by using the co-integration test, a long-run association among the variables was seen. Finding a long-run relationship, the fully modified ordinary least squares method was applied to examine the impact of urbanization and other explanatory variables on carbon dioxide emissions. Results showed that urbanization followed by GDP per capita are the key promoters of CO2 emissions across all countries, whereas the direction and significance of inward FDI and trade openness varied across regions. Furthermore, it was observed that mobile phone penetration (as an indicator of information and communication technology [ICT]) has a significant and negative relationship with CO2 emissions, showing that ICT-based technologies might be the answer to decoupling economic growth from emissions growth. [ABSTRACT FROM AUTHOR]

This study is an attempt to gauge the effect of remittances on Real Effective Exchange Rate (REER) with the help of a panel of 18 selected Asian countries. The period considered for this study is from 1998 to 2016. To achieve the objective of the study, along with Pedroni panel cointegration technique, 'Fully Modified Ordinary Least Square' and 'Dynamic Ordinary Least Square' methods were applied. The results of the study suggest that remittances exert upward pressure on REER. In case of both the estimators (FMOLS and DOLS), the coefficient of remittances is negative and statistically significant at 1% level. Impulse response functions (IRFs) derived from the Panel Vector Auto Regressive model (PVAR) exhibits similar kind of results. The results obtained from this study raise the concerns similar to the ones raised by the Dutch disease or discoveries of natural resources leading to the appreciation of REER. [ABSTRACT FROM AUTHOR]