Media Response Archive ...
Physical Climate Change Risks and the Sovereign Creditworthiness of Emerging Economies
IWH Discussion Papers,
I show that rising temperatures can detrimentally affect the sovereign creditworthiness of emerging economies. To this end, I collect long-term monthly temperature data of 54 emerging countries. I calculate a country’s temperature deviation from its historical average, which approximates present day climate change trends. Running regressions from 1994m1-2018m12, I find that higher temperature anomalies lower sovereign bond performances (i.e. increase sovereign risk) significantly for countries that are warmer on average and have lower seasonality. The estimated magnitudes suggest that affected countries likely face significant increases in their sovereign borrowing costs if temperatures continue to rise due to climate change. However, results indicate that stronger institutions can make a country more resilient towards temperature shocks, which holds independent of a country’s climate.
A Model for the Valuation of Carbon Price Risk
Antes, R.; Hansjürgen, B.; Letmathe, P.; Pickl, S. (Hrsg.), Emissions Trading - Institutional Design, Decision Making and Corporate Strategies (Second Edition),
Modeling the price risk of CO2 emission allowances is an important aspect of integral corporate risk management related to emissions trading. In this paper, a pricing model is developed which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is determined by the expected marginal CO2 abatement costs in the current trade period as well as by the long-term marginal abatement costs. The price risk is modeled on the basis of a mean reversion process. Due to uncertainties about the future state of the environment, we suppose that within one trade period erratic changes in the expected marginal abatement costs may occur leading to shifts in the price level. In addition to the parameter estimation, it is also an objective of this work to modify the mean reversion process so that such abrupt changes in the expected reversion level can be displayed. Because of the possibility of transferring spare allowances to a subsequent period we take into account the fact that the expected long run marginal abatement costs act as a lower limit for the price in the trading period.
Stochastic Income Statement Planning as a Basis for Risk Assessment in the Context of Emissions Trading
Greenhouse Gas Measurement and Management,
The introduction of the European emissions trading system means that those enterprises taking part have a new planning risk factor to consider – emissions allowance prices. In this article, we analyse how risk emerging from emissions trading can be considered in the stochastic income statement planning of corporations. Therefore, we explore which planned figures are affected by emissions trading. Moreover, we show an approach that models these positions in a planned profit and loss account, taking into account uncertainties and dependencies. Consequently, this model provides a basis for risk assessment and investment decisions in the uncertain environment of emissions trading.
Forecasting the CO2 certificate price risk
IWH Discussion Papers,
Modeling the price risk of CO2 certificates is one important aspect of integral corporate risk management related to emissions trading. The paper presents a risk model which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is determined by the expected marginal CO2 abatement costs prevailing at the current trade period and stochastically fluctuates around the respective level as returned from the mean reversion process. Due to uncertainties about future environmental states we suppose that within one trade period, erratic changes in the expected marginal abatement costs may occur leading to shifts in the price level. The aim of the work is to model the erratic changes of the expected reversion level and to estimate the parameters of the mean reversion process.