Members of the RCEM at ESCP Europe Business School regularly publish their research findings in leading academic journals. Below you can find a list of RCEM experts' published papers.
Members of the RCEM at ESCP Europe Business School regularly publish their research findings in leading academic journals. Below you can find a list of RCEM experts' published papers.
For over forty years energy expectations have been riddled with internal contradictions, and all too often a failure to recognise complexity, the nature and scale of the challenges to be faced, and resultant uncertainty. Key elements of Shell’s “World of Internal Contradictions” scenario, issued
Given the widely acknowledged negative impacts of fossil fuels, both on human health and on potential climate change,it is of interest to compare the impacts of low carbon alternative energy sources such as nuclear energy, hydropower, solar, wind and biomass.
The links between economic prosperity, or lack thereof, and the exploitation and use of energy and other natural resources go back to the earliest records of the human species - and in important respects even further back to when hunting and foraging characterised the earliest humanoid species. This paper surveys the challenges of resource exploitation and use, reﬂecting that as we exploit the most readily and cheapest resources, and extraction technology, available at the time, so the marginal returns of each tend to decline as the highest quality is depleted, costs rise, and alternatives are increasingly sought. There are few resources where this is truer than the various forms of energy which have been exploited down the ages. Many complex societies in the past have failed to make a successful transition, and the historic record demonstrates clearly the inadequacies of Solow-type growth theory. Scenarios of global energy prospects for the 21st Century need to consider the past and, in the light of it, ask whether the end of the Anthropocene Age is in sight or whether some kind of Promethean leap will come to the rescue.
This paper reproduces the performance of an international market capitalization shipping stock index and two physical shipping indexes by investing only in US stock portfolios. The index-tracking problem is addressed using the differential evolution algorithm and the genetic algorithm. Portfolios are constructed by a subset of stocks picked from the shipping or the Dow Jones Composite Average indexes. To test the performance of the heuristics, three different trading scenarios are examined: annually, quarterly and monthly rebalancing, accounting for transaction costs where necessary. Competing portfolios are also assessed through predictive ability tests. Overall, the proposed investment strategies carry less risk compared to the tracked benchmark indexes while providing investors the opportunity to efficiently replicate the performance of both the stock and physical shipping indexes in the most cost-effective way.
Following the importance of gold in the global economy and the high interest that has attracted recently, the objective of this paper is twofold: to predict the price of gold by using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and compare its forecasting accuracy with various time-series forecasting methods and the 'Buy and Hold' (B&H) strategy. The results show that the ANFIS's accuracy is far superior to the performance of all compared methods and therefore ANFIS demonstrates the potential of neuro fuzzy-based modelling for predicting the gold's price.
We show that the application of flexible semi-parametric statistical techniques enables significant improvements in model fitting of macroeconomic models. As applied to the explanation of the past economic growth (since 1900) in US, UK and Japan, the new results demonstrate quite conclusively the non-linear relationships between capital, labour and useful energy with economic growth. They also indicate that output elasticities of capital, labour and useful energy are extremely variable over time. We suggest that these results confirm the economic intuition that growth since the industrial revolution has been driven largely by declining energy costs due to the discovery and exploitation of relatively inexpensive fossil fuel resources. Implications for the 21st century, which are also discussed briefly by exploring the implications of an ACEGES-based scenario of oil production, are as follows: (a) the provision of adequate and affordable quantities of useful energy as a pre-condition for economic growth and (b) the design of energy systems as 'technology incubators' for a prosperous 21st century.
Due to the increasing importance of natural gas for modern economic activity, and gas's non-renewable nature, it is extremely important to try to estimate possible trajectories of future natural gas production while considering uncertainties in resource estimates, demand growth,production growth and other factors that might limit production. Inthisstudy, we develop future scenarios for natural gas supply using the ACEGES computational laboratory. Conditionally on the currently estimated ultimate recover-able resources, the 'Collective View' and 'Golden Age' Scenarios suggest that the supply of natural gas is likely to meet the increasing demand for natural gas until at least 2035. The 'Golden Age' Scenario suggests significant 'jumps' of natural gas production - important for testing the resilience of long-term strategies.
The chapter presents a new approach to address energy policy and security based upon the ACEGES (Agent-based Computational Economics of the Global Energy System) model and the SPT (stochastic portfolio theory).
The ACEGES model is an agent-based model for exploratory energy policy by means of controlled computational experiments. The ACEGES model is designed to be the foundation for large custom-purpose simulations of the global energy system by modeling explicitly 216 countries.
In this article the financial/ownership structures of agribusiness cooperatives are analyzed to examine whether new cooperative models perform better than the more traditional ones. The assessment procedure introduces a new financial decision-aid approach, which is based on data-analysis techniques in combination with a preference ranking organization method of enrichment evaluations (PROMETHEE II). The application of this multicriteria decision-aid approach allows the rank ordering of cooperatives based on the most prominent financial ratios. The financial ratios were selected using principal component analysis. This analytical procedure reduces the dimensionality of large numbers of interrelated financial performance measures. We assess the financial success of Dutch agribusiness cooperatives for the period 1999-2010. Results show that there is no clear-cut evidence that cooperative models used to attract extra members' investments and/or outside equity perform better than the more traditional models. This suggests that ownership structure of cooperatives is not always a decisive factor for their financial success. [EconLit citations: Q130, G320, C440].
This paper illustrates the power of modern statistical modelling in estimating measures of market risk, here applied to the Brent and WTI spot price of oil. Both Value-at-Risk (VaR) and Expected Shortfall (ES) are cast in terms of conditional centiles based upon semiparametric regression models. Using the GAMLSS statistical framework, we stress the important aspects of selecting a highly flexible parametric distribution (skewed Student's t distribution) and of modelling both skewness and kurtosis as nonparametric functions of the price of oil futures. Furthermore, an empirical application characterises the relationship between spot oil prices and oil futures - exploiting the futures market to explain the dynamics of the physical market. Our results suggest that NYMEX WTI has heavier tails compared with the ICE Brent. Contrary to the common platitude of the industry, we argue that 'somebody knows something' in the oil business.
This article provides evidence regarding the performance of momentum investment strategies that is consistent with the Neoclassical Theory. More specifically, while momentum investment returns appear orthogonal to systematic risk in the extant literature, this article illustrates that they are due to correlated changes of hedge portfolio systematic risk exposures with market conditions. Momentum portfolios are excellent market timers in both expanding and contracting markets. Their returns however are generally not abnormal when timing is considered in an augmented unconditional Capital Asset Pricing Model (CAPM), while the standard version erroneously considers them to be so, possibly explaining why momentum studies have so far rejected the Neoclassical Theory.
Oil and related products continue to be prime enablers of the maintenance and growth of nearly all of the world's economies. The dramatic increase in the price of oil through mid-2008, along with the coincident (and possibly resultant) global recession, highlight our continued vulnerability to future limitations in the supply of cheap oil. The very large differences between the various estimates of the original volume of extractable conventional oil present on earth (EUR) have, at best, fostered uncertainty of the risk of future supply limitations among planners and policy makers, and at worse lulled the world into a false sense of security. In 2002 we modeled future oil production in 46 nation-units and the world by using a threephase, Hubbert-based approach that produced trajectories dependent on settings for EUR (extractable ultimate resource), demand growth, percent of oil resource extracted at decline, and maximum allowable rates of production growth. We analyzed the sensitivity of the date of onset of decline for oil production to changes in each of these input parameters. In this current effort, we compare the last eleven years of empirical oil production data to our earlier forecast scenarios to evaluate which settings of EUR and other input parameters had created the most accurate projections. When combined with proper input settings, our model consistently generated trajectories for oil production that closely approximated the empirical data at both the national and the global level. In general, the lowest EUR scenarios were the most consistent with the empirical data at the global level and for most countries, while scenarios based on the mid and high EUR estimates overestimated production rates by wide margins globally. The global production of conventional oil began to decline in 2005, and has followed a path over the last 11 years very close to our scenarios assuming low estimates of EUR (1.9 Gbbl). Production in most nations is declining, with historical profiles generally consistent with Hubbert's premises. While new conventional oil discoveries and production starts are expected in the near term, the magnitudes necessary to increase our simulated production trajectories by even 1.0% per year over the next 10 years would represent a large departure from current trends. Our now well-validated simulations are at significant variance from many recent "predictions" of extensive future availability of conventional oil.
This article appeared in a journal published by Elsevier.
This paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on NYMEX. We consider two types of models, a mean-reverting model, and a spike model with mean reversion that incorporates two different speeds of mean reversion; one for the fast mean-reverting behaviour of prices after a jump occurs, and another for the slower mean reversion rate of the diffusive part of the model. We also extend these models to incorporate time-varying volatility in their specification, modelled as a GARCH and an EGARCH process. We compare the relative goodness of fit of the different modelling variations both in sample, using Monte Carlo simulations, as well as out-of-sample, in a Value-at-Risk (VaR) setting.
Our results indicate the presence of a "leverage effect" for WTI, Heating Oil and Heating Oil-WTI crack spread, whereas for the remaining energy markets we find the presence of an "inverse leverage" effect. Also, the addition of the EGARCH specification for the volatility process improves both the in-sample fit as well as the out-of-sample VaR performance for most energy markets that we examine.
As the world economy highly depends on crude oil, it is important to understand the dynamics of crude oil production and export capacity of major oil-exporting countries. Since crude oil resources are predominately located in the OPEC Middle East, these countries are expected to have significant leverage in the world crude oil markets by taking into account a range of uncertainties. In this study, we develop a scenario for crude oil export and production using the ACEGES model considering uncertainties in the resource limits, demand growth, production growth, and peak/decline point. The results indicate that the country-specific peak of both crude oil export and production comes in the early this century in the OPEC Middle East countries. On the other hand, they occupy most of the world export and production before and after the peak points. Consequently, these countries are expected to be the key group in the world crude oil markets. We also find that the gap between the world crude oil demand and production broadens over time, meaning that the acceleration of the development of ultra-deep-water oil, oil sands, and extra-heavy oil will be required if the world continuous to heavily rely on oil products.
Multiattribute additive value functions constitute an important class of models for multicriteria decision making. Such models are often used to rank a set of alternatives or to classify them into pre-defined groups. Preference disaggregation techniques have been used to construct additive value models using linear programming techniques based on the assumption of monotonic preferences. This paper presents a methodology to construct non-monotonic value function models, using an evolutionary optimization approach. The methodology is implemented for the construction of multicriteria models that can be used to classify the alternatives in pre-defined groups, with an application to credit rating.
The sustainability agenda is becoming an important element in business education. This is because there is a growing understanding of the need to develop strategic thinking that safeguards the long-term sustainability of business. To that end the Agent-based Computational Economics of the Global Energy System (ACEGES) project is introduced as a novel framework for developing a new generation of long-term decision scenarios. At a more general level, the project raises awareness of sustainable thinking in long-term business planning by means of controlled computational experiments. This paper describes the ACEGES tool, which has been introduced at a business school in the UK to educate students in the art and science of sustainable strategic thinking.
We all know that the wind is intermittent. As a rough measure, wind turbines can only operate when
wind speeds are between 4 metres per second and 24 metres per second. There is a further technical limit,
which need not concern us here, Betz's Law - the maximum theoretical efficiency of a wind turbine is
the ratio of the maximum power obtained from the wind to the total power available from the wind. This
ratio is 0.593, thus under Betz's Law wind turbines can never be more than 59.3% efficient.
Here, however, we focus on 'capacity factor' (sometimes termed 'load factor'). This is the ratio of the
actual output of a wind energy development (an array of wind turbines at a particular location, or locations
if a country is under consideration as is the case in this paper) to the installed capacity. We will be
considering actual wind energy performance in the UK, sub-divided for England, Scotland, Wales, and
Northern Ireland against claims that in general have been grossly exaggerated. The implications of the
actual performance against claims will finally be considered.
In times of uncertainties scenarios offer a solution. Starting with Royal Dutch Shell by the late 1960s, corporate scenarios are intended to challenge managers' "personal microcosms" and to reflect the present and the past, before structuring the uncertainties of the future. Therefore, scenarios act as 'early warning systems' by focusing on the driving forces that makes a difference to decision-makers.
Oil scenarios, ACEGES, energy scenarios, Shell's scenarios, oil strategies
1. This evidence is presented to the Select Committee to provide a perspective in terms of the threats, vulnerability and consequences of the UK Energy Supply System within a global-national context characterized by unprecedented uncertainties and increasingly complex intertwines. This contribution is based upon the ACEGES project (www.aceges.org). ACEGES stands for Agent-based Computational Economics of the Global Energy System. The ACEGES models the energy demand and supply of 216 countries.
2. The aim is not to present another set of quantifications for policymaking, as there are a number of reports and papers published in recent years. Rather the aim is to provide a coherent overview of i) the assumptions of the energy models used to produce the published quantifications and ii) the approach used to develop energy scenarios for the assessment of the UK's Energy Supply.
3. I am a specialist in the modelling of fuzzy phenomena and complex adaptive systems such as the Energy System. My research work aims to support evidence-based energy policy by means of controlled computational experiments. Currently, I am the Deputy Director of the Centre for International Business and Sustainability (CIBS) at the London Metropolitan Business School. I am also the organise of the "UK Energy Day: Sustainable Supply" which is part of the European network of events led by the Intelligent Energy Europe (IEE) agency of the European Commission (EC).
4. It is evident today that the long-term sustainability of the UK's energy system is under acute strain. Therefore the comments that follow mainly deal with the need to enhance:
a. The existing energy models to assess the sensitivity of the UK's energy supply.
b. The way of developing multidimensional global-national continuous scenarios for long-term assessment of the resilient of the UK energy system to international events.
I will start with the latter.
This paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on
NYMEX. We consider two types of models, a mean-reverting model, and a spike model with mean
reversion that incorporates two different speeds of mean reversion; one for the fast mean-reverting behaviour
of prices after a jump occurs, and another for the slower mean reversion rate of the diffusive part of
the model. We also extend these models to incorporate time-varying volatility in their specification, modelled
as a GARCH and an EGARCH process. We compare the relative goodness of fit of the different modelling
variations both in sample, using Monte Carlo simulations, as well as out-of-sample, in a Value-at-Risk (VaR)
setting. Our results indicate the presence of a "leverage effect" for WTI, Heating Oil and Heating Oil-WTI crack
spread, whereas for the remaining energy markets we find the presence of an "inverse leverage" effect. Also,
the addition of the EGARCH specification for the volatility process improves both the in-sample fit as well as
the out-of-sample VaR performance for most energy markets that we examine.
This paper reproduces the performance of a geometric average Spot Energy Index by investing only in a subset of stocks from the Dow Jones Composite Average, the FTSE 100 and Bovespa Composite indexes, and in two pools including only stocks of the energy sector from the US and the UK respectively. Daily data are used and the index-tracking problem for passive investment is addressed with two innovative evolutionary algorithms; the differential evolution algorithm and the genetic algorithm, respectively. The performance of the suggested investment strategy is tested under three different scenarios: buy-and-hold, quarterly, and monthly rebalancing;accounting for transaction costs where necessary.
The fusion of agent-based and geospatial models represents an exciting new synthesis for social science and economics. It has the potential to improve the theory and the practice of modelling complex real-world phenomena. Yet, to date, there has been little systematic analysis at the conceptual and logical levels of how to fuse agent-based and geospatial models for the representation and reasoning of socioeconomic phenomena. Here both sets of issues are explored. In particular, it will be argued that the development of synthetic models requires autonomous agents and flexible organisational structures that can complete their objectives while situated in a dynamic and uncertain geoenvironment represented by the concept of Elementary_geoParticle. As an example of the concept, I present a preliminary conceptual model of global energy to demonstrate the validity and possible uses of the proposed technique.
At the 1992 Rio Earth Summit, great emphasis was placed on energy efficiency in the Opening Session. That message, and indeed the subject of energy more generally, largely disappeared in the forty chapters and 600 pages of Agenda 21 that emerged from Rio. This situation has largely remained in subsequent UN deliberations. Closer focus on climate change, deforestation, and poverty has failed to produce significant benefits.
By 2010, world carbon dioxide emissions from the use of fossil fuels had risen over 46% from 1990 levels. Renewable energy projects have been pursued with scant regard for efficiency or costs to users. Still 2.7 billion people-some 40% of the World's population-rely overwhelmingly on traditional biomass; 1.5 billion others have no electricity supply; and a further 1 billion only have sporadic supply. Fossil fuels continue to provide nearly 85% of the World's primary energy, while renewable energy sources provide about 13%-of which traditional biomass accounts for 10.2% and all other renewable resources for only 2.8%. Of this 2.8%, hydropower accounts for 2.3%, wind power for 0.2%, and direct solar energy and geothermal for 0.1% each.
Not one of the eight Millennium Development Goals (MDG) produced in 2000 refers to energy. Then in 2005 UNDP, together with the World Bank and ESMAP, produced "Energy Services for the Millennium Development Goals", which pointed out that "failure to include energy considerations in national MDG strategies and development planning frameworks will severely limit the ability to achieve the MDGs." It also stated: "Increased energy efficiency-whether during generation/production, transport/ transmission, or end-use-can have wide-ranging benefits." In 2010, the UN Advisory Group on Energy and Climate Change (AGECC) report "Energy for a Sustainable Future" referred to improving energy access and strengthening energy efficiency as the "two priorities". AGECC's Chairman (and Head of UNIDO) stated that "a vast potential for energy efficiency improvements across the supply and delivery chain remains largely untapped." Also in 2010, the UN's General Assembly proclaimed 2012 the International Year for Sustainable Energy. Will there be a new, and more effective, focus on energy and efficiency in its provision and use?