13 resultados para Climate Forecast
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.
Resumo:
This paper examines the optimal design of climate change policies in the context where governments want to encourage the private sector to undertake significant immediate investment in developing cleaner technologies, but the carbon taxes and other environmental policies that could in principle stimulate such investment will be imposed over a very long future. The conventional claim by environmental economists is that environmental policies alone are sufficient to induce firms to undertake optimal investment. However this argument requires governments to be able to commit to these future taxes, and it is far from clear that governments have this degree of commitment. We assume instead that governments cannot commit, and so both they and the private sector have to contemplate the possibility of there being governments in power in the future that give different (relative) weights to the environment. We show that this lack of commitment has a significant asymmetric effect. Compared to the situation where governments can commit it increases the incentive of the current government to have the investment undertaken, but reduces the incentive of the private sector to invest. Consequently governments may need to use additional policy instruments – such as R&D subsidies – to stimulate the required investment.
Resumo:
Using a theoretical framework, we explain the impact of the Clean Development Mechanism (CDM) on emissions in Annex I and non-Annex I countries. We show that on one hand, emissions in the non-Annex I country decline because of abatement sponsored by the Annex I country under the CDM; on the other hand, emissions may increase because (i) the Annex I country increases emissions in its own country, and (ii) the non-Annex I country crowds out the bene ts from the CDM projects by increasing its domestic emissions. For the CDM to be e¤ective in reducing global emissions, we show that partial Certi ed Emissions Reduction credits should be given to the Annex I country that sponsors CDM projects in the non-Annex I country. We also suggest that the CDM Executive Board should not allow the CDM projects to be hosted by non-Annex I countries that are too conscious about their emission levels.
Resumo:
Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.
Resumo:
The quintessence of recent natural science studies is that the 2 degrees C target can only be achieved with massive emission reductions in the next few years. The central twist of this paper is the addition of this limited time to act into a non-perpetual real options framework analysing optimal climate policy under uncertainty. The window-of-opportunity modelling setup shows that the limited time to act may spark a trend reversal in the direction of low-carbon alternatives. However, the implementation of a climate policy is evaded by high uncertainty about possible climate pathways.
Resumo:
This paper examines the impact of Knightian uncertainty upon optimal climate policy through the prism of a continuous-time real option modelling framework. We analytically determine optimal intertemporal climate policies under ambiguous assessments of climate damages. Additionally, numerical simulations are provided to illustrate the properties of the model. The results indicate that increasing Knightian uncertainty accelerates climate policy, i.e. policy makers become more reluctant to postpone the timing of climate policies into the future.
Resumo:
The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.
Resumo:
The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.
Resumo:
The standard approach to the economics of climate change, which has its best known implementation in Nordhaus's DICE and RICE models (well described in Nordhaus's 2008 book, A Question of Balance) is not well equipped to deal with the possibility of catastrophe, since we are unable to evaluate a risk averse representative agent's expected utility when there is any signi cant probability of zero consumption. Whilst other authors attempt to develop new tools with which to address these problems, the simple solution proposed in this paper is to ask a question that the currently available tools of climate change economics are capable of answering. Rather than having agents optimally choosing a path (that differs from the recommendations of climate scientists) within models which cannot capture the essential features of the problem, I argue that economic models should be used to determine the savings and investment paths which implement climate targets that have been suggested in the physical science literature.
Resumo:
Using survey expectations data and Markov-switching models, this paper evaluates the characteristics and evolution of investors' forecast errors about the yen/dollar exchange rate. Since our model is derived from the uncovered interest rate parity (UIRP) condition and our data cover a period of low interest rates, this study is also related to the forward premium puzzle and the currency carry trade strategy. We obtain the following results. First, with the same forecast horizon, exchange rate forecasts are homogeneous among different industry types, but within the same industry, exchange rate forecasts differ if the forecast time horizon is different. In particular, investors tend to undervalue the future exchange rate for long term forecast horizons; however, in the short run they tend to overvalue the future exchange rate. Second, while forecast errors are found to be partly driven by interest rate spreads, evidence against the UIRP is provided regardless of the forecasting time horizon; the forward premium puzzle becomes more significant in shorter term forecasting errors. Consistent with this finding, our coefficients on interest rate spreads provide indirect evidence of the yen carry trade over only a short term forecast horizon. Furthermore, the carry trade seems to be active when there is a clear indication that the interest rate will be low in the future.
Resumo:
We investigate the causes of a conflict by adding ambient climate factors to the existing bundle of most significant variables. It turns out that – controlling for possible associations – temperature could actually induce a conflict. We emphasise that temperature could not be a dominant reason in starting a conflict; however, it could escalate the chances when other factors are present. This paper references some of the related psychological studies to support this claim. We also show that grievance factors could actually be rightfully effective in starting an internal conflict alongside greed based reasons. In the end, we believe that it could be informative to study ambient factors more often in economics.
Resumo:
Domestic action on climate change is increasingly important in the light of the difficulties with international agreements and requires a combination of solutions, in terms of institutions and policy instruments. One way of achieving government carbon policy goals may be the creation of an independent body to advise, set or monitor policy. This paper critically assesses the Committee on Climate Change (CCC), which was created in 2008 as an independent body to help move the UK towards a low carbon economy. We look at the motivation for its creation in terms of: information provision, advice, monitoring, or policy delegation. In particular we consider its ability to overcome a time inconsistency problem by comparing and contrasting it with another independent body, the Monetary Policy Committee of the Bank of England. In practice the Committee on Climate Change appears to be the ‘inverse’ of the Monetary Policy Committee, in that it advises on what the policy goal should be rather than being responsible for achieving it. The CCC incorporates both advisory and monitoring functions to inform government and achieve a credible carbon policy over a long time frame. This is a similar framework to that adopted by Stern (2006), but the CCC operates on a continuing basis. We therefore believe the CCC is best viewed as a "Rolling Stern plus" body. There are also concerns as to how binding the budgets actually are and how the budgets interact with other energy policy goals and instruments, such as Renewable Obligation Contracts and the EU Emissions Trading Scheme. The CCC could potentially be reformed to include: an explicit information provision role; consumption-based accounting of emissions and control of a policy instrument such as a balanced-budget carbon tax.
Resumo:
The possibility of low-probability extreme natural events has reignited the debate over the optimal intensity and timing of climate policy. In this paper, we contribute to the literature by assessing the implications of low-probability extreme events on environmental policy in a continuous-time real options model with “tail risk”. In a nutshell, our results indicate the importance of tail risk and call for foresighted pre-emptive climate policies.