Download Overview

Regulation and the Long-term Security of Supply in the Argentinian Gas Market
Ricardo Ponzo, YPF, [email protected]
Erik Larsen, University of Lugano, +41.58.666.4639, [email protected]
Isaac Dyner, CeiBA complexity, National University of Colombia, [email protected]
Santiago Arengo , Ceiba Complexity, National University of Colombia, [email protected]
Overview
Gas markets are increasing important around the world and the long term evolution of these markets are of strategic importance
for many countries. This makes it important to understand how regulation and intervention in these markets affects the long
term prospect for the secure supply of gas. We use Argentina as a case to illustrate some of the issues and consequences of gas
regulation. Argentina is a country which has had a rapid increase in the use of gas over recent years, and where a potential gas
shortage looms large in the future. Based on a simulation model developed to understand the supply of gas in Argentina we
discuss how regulation will influence the long term supply of gas in Argentina, and surrounding countries. Using the model, we
develop a series of scenarios to highlight the consequences of different current and possible interventions in the market by the
Regulator. Finally we discuss the best option that the regulator has for securing the long term supply of gas in Argentina.
Methods
We developed a model of the Argentinean gas market using the system dynamics method (Sterman, 2000, Forrester, 1961).
System dynamics has a number of advantages in this type of modelling, as its aggregation allows for a relatively compact
representation of a very complex situation (Dyner and Larsen, 2001). Furthermore, its focus on modelling lags and feedback
explicitly make it idea, as a tool, to investigate the macro evolution of markets, where one is interested in capturing the (lagged)
effects of interventions. Interventions which in many cases have long term consequences for the future evolution of the market,
although the consequencei in many cases can take years to emerge and are often not well understood (Sterman, 2000).. Systen
dynamics has an added value in that it can be participative, i.e. a number of people can be involved in the development of the
model. This was also important in this situation, as we needed input from a several different experts to develop a credible
model of the Argentinean gas markets, spanning from exploration and development of gas fields to trading and experts in the
regulation.
It is also important to mention, that we, in this project were not concerned with developing a forecasting model, but rather a
model which can be used to understand the consequences of different regulatory options, e.g. we are not interested in a model
which can be used as a basis for short term trading. System dynamics is well suited to this type of “modelling for learning”
(Morecroft and Sterman, 1994).
System dynamics has for a long time been used successfully for modelling energy systems, such as coal (Wolstenholm, 1986),
deregulated electricity markets (Bunn and Larsen, 1992; Bunn et al. 1997, Ford, 2002), whole energy sectors (Nail, 1978;
1992), oil markets (Davidson et al, 1990) and more recently gas markets (Olaya & Dyner, 2005).
Results
Until 1992 the gas sector in Argentina was state owned and controlled. This changed in 1992 when parts of the gas market
were liberalized and privatized through Law 23.696. This process was started in 1989 and ended in 1993 with an allocation of
shares to the central Government and some provinces, as well as an IPO of 59% of the company (Bondorevsky and Petrecolla,
2004). The results of the reform were that the gas industry was split into four sectors, production, distribution, transport, and
commercialization. They introduced competition into two of these sectors, production and commercialization, while the other
two remained regulated monopolies. The monopoly was established as two transport companies and eight regional distribution
companies. A Regulator ENARGAS was created at the same time to oversee the monopolies and the market in general. The
Government sold all its shares in the production company YPF in 1999 (Bondorevsky and Petrecolla, 2004). Also, Argentina
had already started in the seventies to integrate its gas market with neighbouring countries; the first pipeline followed an
agreement with Bolivia. Argentina has continued since then to increase the connection with other countries in the Southern
Cone.
Argentina had a major financial crisis in 2002 which also had a significant impact on the energy sector. Previously the
exchange rate of Argentinean Pesos had been peaked to the US Dollar. This could not be maintained as the crisis evolved and
the value of the Argentinean Peso fell dramatically, at one point to almost 4 Pesos / Dollar in mid-2002, it has since been
approximately 3 Pesos to the Dollar. This had a dramatic influence on the price of imported energy which is generally traded in
US Dollars. The price for internal fuel, mainly gas, was regulated and not allowed to increase at the same rate. This led to an
increasing use of gas as the energy of choice, a change supported by the Government.
We use the model to develop number of scenatios for the future gas production and consumption in Argentina. Our Base case
represents a non-sustainable solution, as the gas deficit needs to be covered in some way. The base case and the following
scenarios provide several options which might in some cases work individually but more likely will be more effective if
combined. Lower the demand for gas, by promoting other energy sources and increase the regulated price. A price increase will
also provide an incentive to explore for new gas deposits, as well as develop further existing fields. Another option, although
only likely to buy time for making the other option become effective, is to build a pipeline to Bolivia, this will postpone the
shortage which might occur in Argentina. The political trade-off is then to balance the increase in price with the social
implications on the one hand and the price of having blackouts in electricity or shortage of gas if nothing is done. This is clearly
a difficult trade-off but can be alleviated if the price changes are done in a socially responsible way.
The model allows us to test the alternative possibilities outlined above and compare them to create a better understanding of the
long term consequences of different regulatory options and the timing of them. However, in this paper we will not perform
these alternative scenarios due to space constraints and the on-going development of the model.
Conclusions
This paper has discussed the development and use of a model of the long term evolution of the Argentinean gas sector. The
main purpose of the model was to create a way to investigate the effect of regulatory options for the evolution of the gas
market, from a financial, as well as a supply security point of view. This will allow us to test a number of different regulatory
options and thereby gain understanding of which combination of regulation and timing will provide the best results for the
country as a whole. While we at the moment have only preliminary results we expect that the model will have significant
potential for increasing the understanding of the option facing Argentina.
As discussed above the model gives a clear indications for the best regulatory policy in the Argentinean market, if the focus is
on the long term security of supply. However, it is equally important to see how general the insight and recommendations for
the Argentinean market is, for example what can we learn about other gas markets from the model and analysis we performed
here. We will however, try not to generalize these insights before we have the full analysis performed with the model.
References
Bondorevsky, D., Petrecolla, D Argentina from growth to crisis. In Beato P., Benavides, J. (eds.) (2004) Gas market
integration in the Southern cone. Washington, USA: Inter-American Development Bank, 3-34
Bunn, D. W. and Larsen, E.R. (1992) Sensitivity of reserve margin to factors influencing investment behavior in the electricity
market of England and Wales. Energy Policy, 20: 420-429
Bunn, D.W., Dyner, I., Larsen, E.R (1997) Modelling latent market power across gas and electricity markets. System Dynamics
Dyner, I., Larsen, E.R. (2001) From planning to strategy in the electricity industry. Energy Policy, 29: 1145-1154
Ford. A (2002) Boom and bust in the power plant construction. Journal of Industry, Competition and Trade 2: 59-74
Forrester, J.W, (1961) Industrial Dynamics. Cambridge, MA: MIT-Press
Morecroft, J. D. W. and J. D. Sterman, (1994) Modeling for learning organizations. Portland, OR: Productivity Press.
Review, 13: 271-288
Nail, R., (1977) Managing the energy transition, Cambridge, MA: Ballinger Publishing Co.
Nail, R. (1992) A system dynamics model for national energy policy planning. System Dynamics Review 8(1) 1-20.
Olaya, Y., and Dyner, I., 2005. Modelling for policy assessment in the natural gas industry. Journal of the Operational
Research Society,
Sterman, J. D., (2000) Business dynamics. New York, NY: McGraw Hill
Wolstenholme, E.F. (1986) Algorithmic control for system dynamics models. System Dynamics Review, 2(1) 1-19.