ACEGES Presentation at UCL Energy Istitute

UK Energy Day 2011

The Centre for International Business and Sustainability at LondonMet Business School is organising the UK Energy Day: Sustainably Supply. The UK Energy Day 2011 is part of an European network of events led by the Intelligent Energy Agency of the European Commis- sion. The event will promote the awareness of the significance of sustainable energy supply, particularly the need to balance home-grown energy and energy imports. During the day, talks and demonstrations will take place to increase awareness of sustain- able methods of energy production at the global, regional, local and industrial levels.

The brochure and registration form of the event is available here: http://www.londonmet.ac.uk/lmbs/research/cibs/energyday.cfm

ACEGES: Launching the ACEGES demo

We released the ACEGES demo as a Java applet. The most reliable web browser for the ACEGES demo seems to be Google Chrome (both for Mac and Windows). Please let me know if something is in need of revision or what kind of functionality you would like to see by emailing me at v.voudouris@londonmet.ac.uk

To access the ACEGES demo, select the "ACEGES Applet" tab from here: http://www.londonmet.ac.uk/lmbs/research/cibs/aceges

The ACEGES laboratory for energy policy: Exploring the production of conventional oil

I am giving a talk at the UCL Energy Institute on January 25th. In case, you are interested to attend.

Abstract:
For exploratory energy policy by means of controlled computational experiments, I propose an agent-based computational laboratory, termed the ACEGES (Agent-based Computational Economics of the Global Energy System). In particular, I show how agent-based modelling and simulation can be applied to understand better the challenging outlook for oil production by accounting for uncertainties in resource estimates, demand growth, production growth and peak/decline point. This approach emphasises the idea that the oil system is better modelled not as black-box abode of 'the invisible hand' but as a complex system whose macroscopic explananda emerges from the interactions of its constituent components. The simulated scenarios, paints of plausible futures satisfying the generative explanation, show that the peak of world oil production is likely to happen in the region of 2020 and 2040 with a global minimum of remaining reserve/production ratio between 20 and 40. Using the proposed petroleum market diversity, I also observe a global minimum of market diversity in the broad vicinity of the peak year.

For details, please see http://www.eventbrite.com/event/1182949233

Conrad Wolfram: Math with Computers

This is really just want we need. Worth looking at it.



Thanks Carlo for bring this to my attention.

The Joy of Stats: Hans Rosling

this is certainly something worth watching.



and this is a sample of what will be presented today at 21:00 at BBC Four



Vlasios

New Article: Towards a unifying formalisation of geographic representation: the object-field model with uncertainty and semantics

Abstract: The need for a conceptually unifying data model for the representation of geographic phenomena is widely understood. Although some successes have been reported, progress has been slow, especially at the conceptual and logical levels of abstraction. Drawing on and combining existing successes, this article suggests the object-field model with uncertainty and semantics at the conceptual and logical levels of abstraction. The logical level has been formalised in the Unified Modelling Language (UML) class diagram. It is shown that the concepts required to better represent geographic phenomena can be derived from a single foundation that is termed the Elementary_geoParticle with associated uncertainty and semantics by means of aggregation. The town centre phenomenon is used as an application of the conceptual framework being proposed.

To download the paper: http://www.informaworld.com/smpp/content~db=all~content=a930247080~tab=content

Video of oil production

The data has been generated in ACEGES and animated in R.

ACEGES Software: The Interaface

Below is the latest interface of the ACEGES 1.1 software, with the emphasis on the development of exploratory scenarios for oil and gas production.

Screen 1


Screen 2

Benoit Mandelbrot 1924-2010

Benoit Mandelbrot, the mathematician, the father of fractal mathematics, and advocate of more sophisticated modelling in quantitative economics and finance, died on 14th October 2010 aged 85.



For a compilation of videos see: Benoit Mandelbrot

Sustainability and Business

Although the video is not directly related with the aims of the blog, I really like it. That is why it is here.




Maybe, novel modelling tools can help us see things differently.

PhD Opportunities at LondonMet

There are a number of PhD opportunities at LondonMet. Please see here: http://www.londonmet.ac.uk/londonmet/research/the-graduate-school/vice-chancellors-phd-scholarships.cfm

In particular, see the following proposals ( http://www.gamlss.com/papers/PHDoportunities.pdf) :

i) Data Mining Models for the Flexible Modelling of the Location, Scale and Shape Parameters of a Response Distribution
ii) Comparison, Evaluation and Development of Stochastic Volatility Models
iii) Energy-Economy-Investment Modelling
iv) Individual decision-making and social interaction at the movies: The Philadelphia Story

Fusing the agent-based and Object – Field models

One of my recent works appeared as an advance online publication at the Environment and Planning B: Planning and Design. The url of the paper is: http://www.envplan.com/abstract.cgi?id=b36001

Abstract. 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.

The modelling framework discussed above has been used in the ACEGES project discussed here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1652361. A new paper is currently under review in an energy journal (i will not name the specific journal until the review process completes).

If you are interested in the topic of agent-based and geospatial models, see the gisagents blog ( http://gisagents.blogspot.com/ ) by Dr Andrew Crooks.

Simulated Scenarios of Convetional Oil Production

I will present a paper at the 4th International Conference on Computational and Financial Econometrics hosted by University of London & London School of Economics. See here for details: http://www.cfe-csda.org/cfe10/ The paper may also appear at the Computational Statistics & Data Analysis journal.


Abstract:
The ACEGES (Agent-based Computational Economics of the Global Energy System) model is an agent-based model of conventional oil production. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This work provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term scenarios of conventional oil production. Because the ACEGES model has been developed using the Agent-based Computational Economics (ACE) modelling paradigm, the macro-phenomenon of interest (world oil production) grows from sets of micro-foundations (country-specific decision of oil production). The simulated data is analyzed in GAMLSS (Generalised Additive Models for Location Scale and Shape). GAMLSS is a general framework of modelling where the response variable (oil production) can have a very general (up to four parameters) distribution and all of the parameters of the distributions are modelled as linear or smooth function of the explanatory variable (e.g., time). From a methodological perspective, ACEGES and GAMLSS are applied to help leaders in government, business and civil society better understand the challenging outlook for energy through controlled computational experiments.

Probabilistic forecasts of oil production

Following from my last posting, see the two "improved" figures (analysis conducted with Mikis Stasinopoulos and Bob Rigby).

The H-H scenario:


The L-M scenario:

L-M and H-H Scenarios of oil forecasting

I have created two scenarios of conventional oil production and below you can see the simulated results and the the historical production from 2000 to 2009 (black dots). Given the four key uncertainties (demand growth, production growth, EUR and peak/decline point):

1)The L-M case uses estimates from the demand growth, production growth, EUR and the Monte Carlo process for the peak/decline point (this is the low-medium heterogeneity)

2) All key uncertainties are drawn from the Monte Carlo process (this is the high heterogeneity case)


Note: the simulation is initialized with the 2001 data. Thus, the first simulated year is 2002.

Benoit Mandelbrot: Fractals and the art of roughness

I hope you will enjoy the video as I did:

Presentation of ACEGES at the CEF 2010

This is the presentation that I have at the Society for Computational Economics, 16th International Conference on Computing in Economics and Finance, London, UK.

The ACEGES 1.0 Documentation

We have recently completed the first draft of The ACEGES 1.0 Documentation: Simulated Scenarios of Conventional Oil Production.

Abstract: The ACEGES model is an agent-based model of conventional oil production for 93 countries. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This documentation provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term (discrete and continuous) scenarios of conventional oil production.

The documentation can be accessed from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1652361

Citation:
Voudouris, V. and Di Maio, C. (2010), The ACEGES 1.0 Documentation: Simulated Scenarios of Conventional Oil Production, Centre for International Business and Sustainability (London Metropolitan Business School): Working Paper 12, London, UK.

VC PhD Scholarships: ACEGES project

Proposal 1- Energy-Economy-Investment Modelling: Volatility of oil prices and oil supply
Applications are invited in the area of Energy-Economy-Investment Modelling. The applications should be within the scope of the ACEGES project (http://www.londonmet.ac.uk/lmbs/research/cibs/cibs-scenario-planning/cibs-scenario-planning_home.cfm).

In particular, we encourage applications that aim to investigate the relationships between:
i) Spot price of crude oil,
ii) Expectations of future oil prices
iii) Price of crude oil futures
iv) Oil futures spread (defined as the percent deviation of the oil futures price from the spot price of oil)
v) Oil supply shocks.

The overall research aim is to investigate what determines the spot and futures price of crude oil and the importance of the evolution of the price of oil in explaining oil production of OPEC and non-OPEC countries.

Applicants are expected to have a Master’s degree with a strong quantitative, mathematical or statistical focus. Programming experience in Java and/or R is desirable but not essential.

References:
1) Hamilton, J. (2003), What is an Oil Shock? Journal of Econometrics, vol. 113(2), 363-398
2) Alquist, R and Kilian, L. (2010), What Do We Learn from the Price of Crude Oil Futures? Journal of Applied Econometrics, 25(4), 539-573.
3) Kaufmann, R.K. (1991), Oil production in the lower 48 states: Reconciling curve fitting and econometric models. Resources and Energy, 13(1), 111-127

In the first instance, contact me at v.voudouris@londonmet.ac.uk

Proposal 2 - Consumer decision-making and social interaction at the movies: The Philadelphia Story
When faced with choices between new products and services, the properties of which are uncertain, how do individuals behave? Economists commonly distinguish between social and private information available to the consumer - social learning takes place through social networks, while private learning is the consequence of past experience. In factoring both into the decision-making process it is possible to model consumer behaviour - in this instance film consumer behaviour.

To do this I propose developing an agent-based model, which allows the researcher to investigate the microscopic behaviour of individual film consumers who watched particular films at particular cinemas at particular moments in time in order to a) grow the macroscopic environment manifest in the long tail distribution of revenue, b) chart the pattern of diffusion from box-office rich to box-office poor cinemas, and c) forecast the closing box-office of films that opened in the first-run cinemas from the opening Saturday night of the release.

The dataset that forms the basis of this proposal is drawn from the city of Philadelphia for the years 1935-36. Housed in the Warner Bros. Archive at the University of Southern California, I have recently uncovered the weekly billing sheets of 91 cinemas located in the city belonging to the Stanley Warner chain. The sheets provide micro data of an unparalleled nature about audience choices, consisting of daily box-office returns generated by the films screened at the 91 cinemas. This body of data has never previously been accessed. Once transcribed onto a database and analysed, it will make possible a much fuller understanding of audiences and the choices they made. Furthermore, the work will be directly applicable to contemporary consumer behaviour concerning experience goods.

I am looking for a graduate student that has an excellent quantitative historical background, who is excited about executing detailed fieldwork in the city of Philadelphia; building a dataset from archive materials using relational database software; and finally modelling the data to investigate consumer behaviour. Knowledge of a programming language is desirable.