The Demand for Information: More Heat than Light

This paper produces a comprehensive theory of the value of Bayesian information and its static demand. Our key insight is to assume 'natural units' corresponding to the sample size of conditionally i.i.d. signals -- focusing on the smooth nearby model of the precision of an observation of a Brownian motion with uncertain drift. In a two state world, this produces the heat equation from physics, and leads to a tractable theory. We derive explicit formulas that harmonize the known small and large sample properties of information, and reveal some fundamental properties of demand: (a) Value 'non-concavity': The marginal value of information is initially zero; (b) The marginal value is convex/rising, concave/peaking, then convex/falling; (c) 'Lumpiness': As prices rise, demand suddenly chokes off (drops to 0); (d) The minimum information costs on average exceed 2.5% of the payoff stakes; (e) Information demand is hill-shaped in beliefs, highest when most uncertain; (f) Information demand is initially elastic at interior beliefs; (g) Demand elasticity is globally falling in price, and approaches 0 as prices vanish; and (h) The marginal value vanishes exponentially fast in price, yielding log demand. Our results are exact for the Brownian case, and approximately true for weak discrete informative signals. We prove this with a new Bayesian approximation result.Value of information, Non-concavity, Heat equation, Demand, Bayesian analysis

Optimal Electoral Timing: Exercise Wisely and You May Live Longer

In many democratic countries, the timing of elections is flexible. We explore this potentially valuable option using insights from option pricing in finance. The paper offers three main contributions on this problem. First, we derive a rationally-based mean-reverting political support process for the parties, assuming that politically heterogeneous voters continuously learn over time about evolving party fortunes. We solve for the long-run density for this process and derive the polling process from it by adding polling noise. Second, we explore optimal timing using the political support process. The incumbent sees its poll support, and must call an election within five years of the last election to maximize its expected total time in office. This resembles the optimal exercise rule for an American financial option. This option is recursive, and the waiting and stopping values subtly interact. We prove the existence of the optimal exercise rule in this setting, and show that the expected longevity is a convex-thenconcave function of the political support. Our model is tractable enough that we can analytically derive how the exercise rule responds to parametric shifts. We calibrate our model to the Labour-Tory rivalry in the U.K., with polling data from 1943-2005 and the 16 elections after 1945. Excluding three elections essentially forced by weak governments, our maximizing story quite well explains when the elections were called, and beats simple linear regressions. We also measure the value of election options, finding that over the long run they should more than double the expected time in power of a fixed term electoral cycle.American option, European option, Brownian motion, Electoral timing

Implications of Limited Foresight and Sequential Decision Making for Long-term Energy System Planning: An Application of the Myopic MESSAGE Model

This paper presents the development and demonstration of a limited foresight energy system model. The presented model is implemented as an extension to a large, linear optimization model, MESSAGE. The motivation behind changing the model is to provide an alternative decision framework, where information for the full time frame is not available immediately and sequential decision making under incomplete information is implied. While the traditional optimization framework provides the globally optimal decisions for the modeled problem, the framework presented here may offer a better description of the decision environment, under which decision makers must operate. We further modify the model to accommodate flexible dynamic constraints, which give an option to implement investments faster, albeit with a higher cost. Finally, the operation of the model is demonstrated using a moving window of foresight, with which decisions are taken for the next 30 years, but can be reconsidered later, when more information becomes available. We find that the results do demonstrate some of the pitfalls of short term planning, e.g. lagging investments during earlier periods lead to higher requirements later during the century. Furthermore, the energy system remains more reliant on fossil based energy carriers, leading to higher greenhouse gas emissions. reliant on fossil based energy carriers, leading to higher greenhouse gas emi

Incorporating homeowners' preferences of heating technologies in the UK TIMES model

Hot water and space heating account for about 80% of total energy consumption in the residential sector in the UK. It is thus crucial to decarbonise residential heating to achieve UK's 2050 greenhouse gas reduction targets. However, the decarbonisation transitions determined by most techno-economic energy system models might be too optimistic or misleading for relying on cost minimisation alone and not considering households' preferences for different heating technologies. This study thus proposes a novel framework to incorporate heterogeneous households' (HHs) preferences into the modelling process of the UK TIMES model. The incorporated preferences for HHs are based on a nationwide survey on homeowners' choices of heating technologies. Preference constraints are then applied to regulate the HHs' choices of heating technologies to reflect the survey results. Consequently, compared to the least-cost transition pathway, the preference-driven pathway adopts heating technologies gradually without abrupt increases of market shares. Heat pumps and electric heaters are deployed much less than in the cost optimal result. Extensive district heating using low-carbon fuels and conservation measures should thus be deployed to provide flexibility for decarbonisation. The proposed framework can also incorporate preferences for other energy consumption technologies and be applied to other linear programming-based energy system models

Energy scenario choices: insights from a retrospective review of UK energy futures

Since the 1980s, there has been a shift in energy research. It has shifted from approaches that forecast or project the future to approaches which make more tentative claims and which explore several plausible scenarios. Due to multiple uncertainties in energy systems, there is an infinite amount of plausible scenarios that could be constructed and scenario developers therefore choose smaller, more tangible sets of scenarios to analyse. Yet, it is often unclear how and why this scenario choice is made and how such choices might be improved. This paper presents a retrospective analysis of twelve UK energy scenarios developed between 1978 and 2002. It investigates how specific scenarios were chosen and whether these choices captured the actual UK energy system transition. It finds that scenario choice reflected contemporary debates, leading to a focus on certain issues and limiting the insights gleaned from these exercises. The paper argues for multi-organisation and multi-method approaches to the development of energy scenarios to capture the wide range of insights on offer. Rather than focus on uncertainty in model parameters, greater reflection on structural uncertainties, such as shifts in energy governance, is also required

The Contribution of Renewable Energy to a Sustainable Energy System

This report provides an overview of the main results from the scenarios analysed in the CASCADE MINTS project to assess the role of renewables in solving global and European en-ergy and environmental issues. The main conclusion is that renewable energy can make a sub-stantial contribution to reducing greenhouse gas emissions and improving diversification of the European energy production portfolio, although other technologies will also be needed in order to achieve post Kyoto targets. The report outlines the impacts, costs and benefits of ambitious renewables targets for Europe in the medium term. It also presents lessons learned from taking the global perspective

Characterising the Evolution of Energy System Models Using Model Archaeology

In common with other types of complex models, energy system models have opaque structures, making it difficult to understand both changes between model versions and the extent of changes described in research papers. In this paper, we develop the principle of model archaeology as a formal method to quantitatively examine the balance and evolution of energy system models, through the ex post analysis of both model inputs and outputs using a series of metrics. These metrics help us to understand how models are developed and used and are a powerful tool for effectively targeting future model improvements. The usefulness of model archaeology is demonstrated in a case study examining the UK MARKAL model. We show how model development has been influenced by the interests of the UK government and the research projects funding model development. Despite these influences, there is clear evidence of a strategy to balance model complexity and accuracy when changes are made. We identify some important long-term trends including higher technology capital costs in subsequent model versions. Finally, we discuss how model archaeology can improve the transparency of research model studies. © 2014 The Author(s)

Impact of technology uncertainty on future low-carbon pathways in the UK

Energy and climate policy-making requires strong quantitative scientific evidence to devise robust and consistent long-term decarbonisation strategies. Energy system modelling can provide crucial insights into the inherent uncertainty in such strategies, which needs to be understood when designing appropriate policy measures. This study contributes to the growing research area of uncertainty analysis in energy system models. We combine consistent and realistic narratives on several technology dimensions with a global sensitivity analysis in a national, bottom-up, optimizing energy system model. This produces structured insights into the impact of low-carbon technology and resource availability on the long-term development of the UK energy system under ambitious decarbonisation pathways. We explore a variety of result metrics to present policy-relevant results in a useful and concise manner. The results provide valuable information on the variability of fuel and technology use across the uncertainty space (e.g. a strong variation in natural gas demand). We demonstrate the complementarities and substitutability of technologies (e.g. the dependency of hydrogen technologies on the availability of CCS). We highlight critical low-carbon options and hedging strategies (e.g. the early decarbonisation of the electricity sector or the stronger use of renewable sources as a hedging against failure in other technologies) and demonstrate timing and path dependencies (e.g. the importance of early decarbonisation action in the presence of multiple technology uncertainty). The results also show how the availability of a given technology can have wider impacts elsewhere in the energy system, thus complicating the management of a long-term energy transition