Listing 1 - 10 of 11 | << page >> |
Sort by
|
Choose an application
Choose an application
Choose an application
Choose an application
Choose an application
Choose an application
Choose an application
Pricing greenhouse gas emissions is a risk management problem. It involves making trade-offs between consumption today and unknown and potentially catastrophic damages in the (distant) future. The optimal carbon price is based on society's willingness to substitute consumption across time and across uncertain states of nature. A large body of work in macroeconomics and finance has attempted to infer societal preferences using the observed behavior of asset prices, and has concluded that the standard preference specifications are inconsistent with observed asset valuations. This literature has developed a richer set of preferences that are more consistent with asset price behavior. In this paper, we explore the implications of these richer preference specifications for the Social Cost of Carbon (SCC), the expected discounted damage of each marginal ton of carbon emissions at an optimal emissions reductions pathway. We develop a simple discrete-time model in which the representative agent has an Epstein-Zin preference specification, and in which uncertainty about the effect of carbon emissions on global temperature and on eventual damages is gradually resolved over time. In our model the SCC is equal to the value of the carbon emissions price at any given point in time that maximizes the utility of the representative agent at that time. We embed a number of features including tail risk, the potential for technological change, and backstop technologies. When coupled with the potential for low-probability, high-impact outcomes, our calibration allows us to decompose the SCC into the expected damages and the risk-premium. In contrast to most modeled carbon price paths, our calibration suggests a high SCC today that is expected to decline over time. It also points to the importance of backstop technologies and, in contrast to standard specifications, to potentially very large deadweight costs of delay. We find, for example, that with damage distributions calibrated to an SCC of $40, a value associated with only a small risk premium, the deadweight loss in utility associated with delaying the implementation of optimal pricing by 15 years is equivalent to a 6% loss of consumption.
Choose an application
Using optimal control theory and a vector autoregressive representation of the relationship between money and interest rates, one can derive a feedback control procedure which defines the best possible tradeoff between interest rate volatility and money supply fluctuations and which could be used to reduce both from their current levels.
Choose an application
This paper reexamines both monthly and quarterly U.S. postwar data to investigate if the observed comovements between money, real interestrates, prices and output are compatible with the money-real interest-output link suggested by existing monetary theories of output, which include both Keynesian and equilibrium models.The major empirical findings are these;1) In both monthly and quarterly data, we cannot reject the hypothesis that the ex ante real rate is exogenous, or Granger-causally prior in the context of a four-variable system which contains money, prices, nominal interest rates and industrial production.2) In quarterly data, there is significantly more information con-tained in either the levels of expected inflation or the innovationof this variable for predicting future output, given current and lagged output, than in any other variable examined (money, actualinflation, nominal interest rates, or ex ante real rates). The effect of an inflation innovation on future output is unambiguously negative. The first result casts strong doubt on the empirical importance of existing monetary theories of output, which imply that money should have a causal role on the ex ante real rates. The second result would appear incompatible with most demand driven models of output.In light of these results, we propose an alternative structural model which can account for the major dynamic interactions among the variables.This model has two central features: i) output is unaffected by money supply;and ii) the money supply process is motivated by short-run price stability.
Choose an application
Pricing greenhouse gas emissions involves making trade-offs between consumption today and unknown damages in the (distant) future. This setup calls for an optimal control model to determine the carbon dioxide (CO2) price. It also relies on society's willingness to substitute consumption across time and across uncertain states of nature, the forte of Epstein-Zin preference specifications. We develop the EZ-Climate model, a simple discrete-time optimization model in which uncertainty about the effect of CO2 emissions on global temperature and on eventual damages is gradually resolved over time. We embed a number of features including potential tail risk, exogenous and endogenous technological change, and backstop technologies. The EZ-Climate model suggests a high optimal carbon price today that is expected to decline over time as uncertainty about the damages is resolved. It also points to the importance of backstop technologies and to very large deadweight costs of delay. We decompose the optimal carbon price into two components: expected discounted damages and the risk premium.
Listing 1 - 10 of 11 | << page >> |
Sort by
|