4 resultados para pollution sources
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
In this paper we attempt an empirical application of the multi-region input-output (MRIO) method in order to enumerate the pollution content of interregional trade flows between five Mid-West regions/states in the US –Illinois, Indiana, Iowa, Michigan and Wisconsin – and the rest of the US. This allows us to analyse some very important issues in terms of the nature and significance of interregional environmental spillovers within the US Mid-West and the existence of pollution ‘trade balances’ between states. Our results raise questions in terms of the extent to which authorities at State level can control local emissions where they are limited in the way some emissions can be controlled, particularly with respect to changes in demand elsewhere in the Mid-West and US. This implies a need for policy co-ordination between national and state level authorities in the US to meet emissions reductions targets. The existence of an environmental trade balances between states also raises issues in terms of net losses/gains in terms of pollutants as a result of interregional trade within the US and whether, if certain activities can be carried out using less polluting technology in one region relative to others, it is better for the US as a whole if this type of relationship exists.
Resumo:
Untreated wastewater being directly discharged into rivers is a very harmful environmental hazard that needs to be tackled urgently in many countries. In order to safeguard the river ecosystem and reduce water pollution, it is important to have an effluent charge policy that promotes the investment of wastewater treatment technology by domestic firms. This paper considers the strategic interaction between the government and the domestic firms regarding the investment in the wastewater treatment technology and the design of optimal effluent charge policy that should be implemented. In this model, the higher is the proportion of non-investing firms, the higher would be the probability of having to incur an effluent charge and the higher would be that charge. On one hand the government needs to impose a sufficiently strict policy to ensure that firms have strong incentive to invest. On the other hand, it cannot be too strict that it drives out firms which cannot afford to invest in such expensive technology. The paper analyses the factors that affect the probability of investment in this technology. It also explains the difficulty of imposing a strict environment policy in countries that have too many small firms which cannot afford to invest unless subsidised.
Resumo:
Much attention in recent years has turned to the potential of behavioural insights to improve the performance of government policy. One behavioural concept of interest is the effect of a cash transfer label on how the transfer is spent. The Winter Fuel Payment (WFP) is a labelled cash transfer to offset the costs of keeping older households warm in the winter. Previous research has shown that households spend a higher proportion of the WFP on energy expenditures due to its label (Beatty et al., 2011). If households interpret the WFP as money for their energy bills, it may reduce their willingness to undertake investments which help achieving the same goal, such as the adoption of renewable energy technologies. In this paper we show that the WFP has distortionary effects on the renewable technology market. Using the sharp eligibility criteria of the WFP in a Regression Discontinuity Design, this analysis finds a reduction in the propensity to install renewable energy technologies of around 2.7 percentage points due to the WFP. This is a considerable number. It implies that 62% of households (whose oldest member turns 60) would have invested in renewable energy but refrain to do so after receiving the WFP. This analysis suggests that the labelling effect spreads to products related to the labelled good. In this case, households use too much energy from sources which generate pollution and too little from relatively cleaner technologies.
Resumo:
We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.