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    Foreign direct investment and ecological efficiency in Pakistan: a new perspective on the pollution haven hypothesis
    (Springer Nature, 2024) Özkan O.; Olasehinde-Williams G.; Usman O.
    Questions surrounding the kind of foreign direct investment that Pakistan attracts become important, especially with the unending debates that such investment can pose environmental challenges for the nation in particular and the world at large. While investment inflows are a prerequisite for economic growth, the environmental consequences are also vital for the quality of life of citizens. This study thus contributes to the debate on the trade-off between cross-border investment flows and environmental status in Pakistan, using annual time-series data spanning 1971–2018. The dynamic connection between foreign direct investment and ecological efficiency is scrutinized while controlling for the effects of environmental determinants—financial integration, economic growth, energy intensity and international trade—by employing dynamic autoregressive distributed lag simulations. The estimated elasticities as well as the counterfactual simulations show that even if ecological efficiency is used as the alternative measure of environmental performance within a dynamic framework, the pollution haven hypothesis still holds in Pakistan. Moroever, while economic growth, financial integration and international trade promote ecological efficiency, energy intensity condenses it. The robustness checks conducted using multivariate Quantle and Quantitle-on-Quantile Regressions also provide similar outcomes to that of the dynamic autoregressive distributed lag simulations.
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    Is there a net economic loss from employing reference class forecasting in the appraisal of hydropower projects?
    (Elsevier Ltd, 2022) Jenkins G.; Olasehinde-Williams G.; Baurzhan S.
    This paper investigates the potential effects of the use of reference class forecasting on the World Bank's financing decisions, and quantifies the net economic impact of such decisions in the long run. A set of 57 World Bank-financed hydropower projects constructed between 1975 and 2015 was selected based on data availability. The findings show that reference class forecasting can help reduce net losses by preventing some hydropower projects with negative economic net present values from being executed. However, it also leads to the forfeiture of even larger amounts of net economic benefits by causing the rejection of some projects that are found, from ex-post analysis, to be economically worthwhile. Furthermore, because of the increased ex-ante rejection of projects, the loss of potentially economically positive projects from the portfolio of hydro dam projects is greatly increased. The errors in the estimation of economic net present values of these hydropower projects are highly positively correlated to the errors in the estimation of the benefits and only weakly negatively correlated to the errors in the estimation of costs.