Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications focused on pollution emissions. Yet, previous research suggests that it is more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. We examine the role of income, convergence, and time related factors in explaining changes in PM2.5 pollution in a global panel of 158 countries between 1990 and 2010. We find that economic growth has positive but relatively small effects, time effects are also small but larger in wealthier and formerly centrally planned economies, and, for our main dataset, convergence effects are small and not statistically significant. There is no insample income turning point for regressions that include both the convergence variables and a set of control variables.

Though the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications focused on pollution emissions. Yet, previous research suggests that it is more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. We examine the role of income, convergence, and time related factors in explaining changes in PM2.5 pollution in a global panel of 158 countries between 1990 and 2010. We find that economic growth has positive but relatively small effects, time effects are also small but larger in wealthier and formerly centrally planned economies, and, for our main dataset, convergence effects are small and not statistically significant. There is no insample income turning point for regressions that include both the convergence variables and a set of control variables. AbstractThough the environmental Kuznets curve (EKC) was originally developed to model the ambient concentrations of pollutants, most subsequent applications focused on pollution emissions. Yet, previous research suggests that it is more likely that economic growth could eventually reduce the concentrations of local pollutants than emissions. We examine the role of income, convergence, and time related factors in explaining changes in PM2.5 pollution in a global panel of 158 countries between 1990 and 2010. We find that economic growth has positive but relatively small effects, time effects are also small but larger in wealthier and formerly centrally planned economies, and, for our main dataset, convergence effects are small and not statistically significant. There is no in-sample income turning point for regressions that include both the convergence variables and a set of control variables.

Through a choice experiment conducted among 995 Swiss respondents, we studied the linkages between prior investment decisions and the choice of travel mode. Our experimental design and empirical framework aimed to identify the impact of electric vehicles (EVs) and to test for two behavioral deviations from rationally optimal usage. Prior investment in a car or public transport pass could be used ex ante as a commitment device for overcoming self-control issues, or could affect mode choices ex post through the regret effect of sunk costs. We found no evidence to support the sunk cost hypothesis, but our findings provided partial evidence in favor of commitment mechanisms. A prior investment decision decreased the consumer’s responsiveness to variation of travel time. However, such commitments did not seem to influence responses to changes in marginal travel costs. Further, we found that EV adoption in the experiment did not result in a significant step-change in hypothetical usage patterns above rational marginal cost reactions. Our results thus reinforced the importance of financial incentives in policies aimed at a behavioral change in travel mode choices.

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We document non-linear stock effects in the relationship linking emerging technology adoption and network infrastructure increments. We exploit 2010–2017 data covering nascent to mature electric vehicle (EV) markets across 422 Norwegian municipalities together with two complementary identification strategies: control function regressions of EV sales on flexible polynomials in the stock of charging stations and charging points, and synthetic control methods to quantify the impact of initial infrastructure provision in municipalities that previously had none. Our results are consistent with indirect network effects and the behavioral bias called “range anxiety,” and support policies targeting early infrastructure provision to incentivize EV adoption.