دانلود مقاله ISI انگلیسی شماره 7921
عنوان فارسی مقاله

انتقال قیمت ها و نوسانات قیمت در بازارهای لحظه ای برق استرالیا : تجزیه و تحلیل چند متغیره GARCH

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
7921 2005 14 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Economics, Volume 27, Issue 2, March 2005, Pages 337–350

کلمات کلیدی
- بازار قیمت برق لحظه ای - نوسانات متوسط ​​و سرریز - چند متغیره
پیش نمایش مقاله
پیش نمایش مقاله انتقال قیمت ها و نوسانات قیمت در بازارهای لحظه ای برق استرالیا : تجزیه و تحلیل چند متغیره GARCH

چکیده انگلیسی

This paper examines the transmission of spot electricity prices and price volatility among the five regional electricity markets in the Australian National Electricity Market: namely, New South Wales, Queensland, South Australia, the Snowy Mountains Hydroelectric Scheme and Victoria. A multivariate generalised autoregressive conditional heteroskedasticity model is used to identify the source and magnitude of price and price volatility spillovers. The results indicate the presence of positive own mean spillovers in only a small number of markets and no mean spillovers between any of the markets. This appears to be directly related to the physical transfer limitations of the present system of regional interconnection. Nevertheless, the large number of significant own-volatility and cross-volatility spillovers in all five markets indicates the presence of strong autoregressive conditional heteroskedasticity and generalised autoregressive conditional heteroskedasticity effects. This indicates that shocks in some markets will affect price volatility in others. Finally, and contrary to evidence from studies in North American electricity markets, the results also indicate that Australian electricity spot prices are stationary.

مقدمه انگلیسی

The Australian National Electricity Market (NEM) was established on 13 December 1998. It currently comprises four state-based (New South Wales (NSW), Victoria (VIC), Queensland (QLD) and South Australia (SA)) and one non-state based (Snowy Mountains Hydroelectric Scheme (SNO)) regional markets operating as a nationally interconnected grid. Within this grid, the largest generation capacity is found in NSW, followed by QLD, VIC, the SNO and SA, while electricity demand is highest in NSW, followed by VIC, QLD and SA. The more than 70 registered participants in the NEM, encompassing privately and publicly owned generators, transmission and distribution network providers and traders, currently supply electricity to 7.7 million customers with more than $8 billion of energy traded annually (for details of the NEM's regulatory background, institutions and operations, see NEMMCO, 2001, NEMMCO, 2002, ACCC, 2000 and IEA, 2001). Historically, the very gradual move to an integrated national system was predated by substantial reforms on a state-by-state basis, including the unbundling of generation, transmission and distribution and the commercialisation and privatisation of the new electricity companies, along with the establishment of the wholesale electricity spot markets (Dickson and Warr, 2000). Each state in the NEM initially developed its own generation, transmission and distribution network and linked it to another state's system via interconnector transmission lines. However, each state's network was (and still is) characterised by a very small number of participants and sizeable differences in electricity prices were found. The foremost objective in establishing the NEM was then to provide a nationally integrated and efficient electricity market, with a view to limiting the market power of generators in the separate regional markets (for the analysis of market power in electricity markets, see Brennan and Melanie (1998), Joskow and Kahn (2001), Wilson (2002) and Robinson and Baniak (2002)). However, a defining characteristic of the NEM is the limitations of physical transfer capacity. QLD has two interconnectors that together can import and export to and from NSW, NSW can export to and from the SNO and VIC can import from the SNO and SA and export to the SNO and to SA. There is currently no direct connector between NSW and SA (though one is proposed) and QLD is only directly connected to NSW. As a result, the NEM itself is not yet strongly integrated with interstate trade representing just 7% of total generation. During periods of peak demand, the interconnectors become congested and the NEM separates into its regions, promoting price differences across markets and exacerbating reliability problems and the market power of regional utilities (IEA, 2001, ACCC, 2000 and NEMMCO, 2002). While the appropriate regulatory and commercial mechanisms do exist for the creation of an efficient national market, and these are expected to have an impact on the price of electricity in each jurisdiction, it is argued that the complete integration of the separate regional electricity markets has not yet been realised. In particular, the limitations of the interconnectors between the member jurisdictions suggest that, for the most part, the regional spot markets are relatively isolated. Nevertheless, the Victorian electricity crisis of February 2000 is just one of several shocks in the Australian market that suggests spot electricity pricing and volatility in each regional market are still potentially dependent on pricing conditions in other markets. These are, of course, concerns that are likely to be just as important in any other national or sub-NEM comprised of interconnected regions. In the US, for example, De Vany and Walls (1999a) used co-integration analysis to test for price convergence in regional markets in the US Western Electricity Grid. On the whole the findings were suggestive of an efficient and stable wholesale power market, though De Vany and Walls (1999a) argued that the lack of cointegration in some markets provided evidence of the impact of transfer constraints within the grid. Later, De Vany and Walls used vector autoregressive modelling techniques and variance decomposition analysis to examine a smaller set of these regional markets. They concluded +IBggJg-the efficiency of power pricing on the western transmission grid is testimony to the ability of decentralised markets and local arbitrage to produce a global pattern of nearly uniform prices over a complex and decentralised transmission network spanning vast distances+IBk (De Vany and Walls, 1999b: p. 139). Unfortunately, no comparable evidence exists concerning the interconnected regional electricity markets in Australia, or indeed elsewhere outside the US for that matter. This is important for two reasons. First, unlike the US the Australian NEM represents the polar case of a centrally co-ordinated and regulated national market. It is, therefore, likely to throw light on the efficiency of pricing and the impact of interconnection within centralised markets still primarily composed of commercialised and corporatised public sector entities. Second, a fuller understanding of the pricing relationships between these markets will enable the benefits of interconnection to be assessed as a step towards the fuller integration of the regional electricity markets into a NEM. This provides policy inputs into both the construction of new interconnectors and guidelines for the reform of existing market mechanisms. At the same time, the manner in which volatility shocks in regional electricity markets are transmitted across time arouses interest in modelling the dynamics of the price volatility process. This calls for the application of autoregressive conditional heteroskedasticity (ARCH) and generalised ARCH (GARCH) models that take into account the time-varying variances of time series data (suitable surveys of ARCH modelling may be found in Bollerslev, et al. (1992), Bera and Higgins (1993) and Pagan (1996)). More recently, the univariate GARCH model has been extended to the multivariate GARCH (MGARCH) case, with the recognition that MGARCH models are potentially useful developments regarding the parameterisation of conditional cross-moments. Although, the MGARCH methodology has been used extensively in modelling financial time series (see, for instance, Dunne (1999), Tai (2000), Brooks et al. (2002) and Tse and Tsui (2002)), to the authors+IBk knowledge a detailed study of the application of MGARCH to electricity markets has not been undertaken. Since this approach captures the effect on current volatility of both own innovation and lagged volatility shocks emanating from within a given market and cross innovation and volatility spillovers from interconnected markets it permits a greater understanding of volatility and volatility persistence in these interconnected markets. It is within the context of this limited empirical work that the present study is undertaken. Accordingly, the purpose of this paper is to investigate the price and price volatility interrelationships between the Australian regional electricity markets. If there is a lack of significant interrelationships between regions then doubt may then be cast on the ability of the NEM to overcome the exercise of regional market power as its primary objective, and on its capacity to foster a nationally integrated and efficient electricity market. The paper itself is divided into four sections. The second section explains the data employed in the analysis and presents some brief summary statistics. The third section discusses the methodology employed. The results are dealt with in the fourth section. The paper ends with some brief concluding remarks.

نتیجه گیری انگلیسی

This paper highlights the transmission of prices and price volatility among five Australian electricity spot markets during the period 1998+IBM-2001. All of these spot markets are member jurisdictions of the recently established NEM. At the outset, unit root tests confirm that Australian electricity spot prices are stationary. A MGARCH model is then used to identify the source and magnitude of spillovers. The estimated coefficients from the conditional mean price equations indicate that despite the presence of a national market for electricity, the regional electricity spot markets are not integrated. In fact, only two of the five markets exhibit a significant own mean spillover. This also would suggest, for the most part, that Australian spot electricity prices could not be usefully forecasted using lagged price information from either each market itself or from other markets in the national market. However, own-volatility and cross-volatility spillovers are significant for nearly all markets, indicating the presence of strong ARCH and GARCH effects. Conventionally, this is used to indicate that markets are not efficient. Strong own- and cross-persistent volatility are also evident in all Australian electricity markets. This indicates that while the limited nature of the interconnectors between the separate regional markets prevents full integration, shocks or innovations in particular markets still exert an influence on price volatility. Thus, during periods of abnormally high demand for example, the NEM may be at least partially offsetting the ability of regional participants to exert market power. Nonetheless, the results mainly indicate the inability of the existing network of interconnectors to create a substantially integrated NEM and that, for the most part, the sizeable differences in spot prices between most of the regions will remain, at least in the short term. This provides validation for new regional interconnectors currently under construction and those that are proposed, and the anticipated inclusion of Tasmania as a sixth region in the NEM. As a general rule, the less direct the interconnection between regions, the less significant the cross-innovation and volatility spillover effects between these regions. This suggests that main determinant of the interaction between regional electricity markets is geographical proximity and the number and size of interconnectors. Accordingly, it maybe unreasonable to expect that prices in electricity markets that are geographically isolated market will ever become fully integrated with +IBg-core+IBk or geographically proximate markets. The results also indicate that volatility innovations or shocks in all markets persist over time and that in all markets this persistence is more marked for own-innovations or shocks than cross-innovations or shocks. This persistence captures the propensity of price changes of like magnitude to cluster in time and explains, at least in part, the non-normality and non-stability of Australian electricity spot prices. Together, these indicate that neither the NEM nor the regional markets are efficiently pricing electricity and that changes to the market mechanism maybe necessary. It may also reinforce calls for the privatisation of some electricity market participants to improve competition, given that the overwhelming majority of these remain under public sector control. Of course, the full nature of the price and volatility interrelationships between these separate markets could be either under or overstated by mis-specification in the data, all of which suggest future avenues for research. One possibility is that by averaging the half-hourly prices throughout the day, the speed at which innovations in one market influence another could be understated. For instance, with the data as specified the most rapid innovation allowed in this study is a day, whereas in reality innovations in some markets may affect others within just a few hours. Similarly, there has been no attempt to separate the differing conditions expected between peak and off-peak prices. For example, De Vany and Walls, 1999a and De Vany and Walls, 1999b found that there were essentially no price differentials between trading points in off-peak periods because they were less constrained by limitations in the transmission system. Another possibility is that the occurrence of time-dependent conditional heteroskedasticity could be due to an increased volume of trading and/or variability of prices following the arrival of new information into the market. It is well known that financial markets, for instance, can still be efficient but exhibit GARCH effects in price changes if information arrives at uneven intervals. One future application of modelling would then include, say, demand volume as a measure of the amount of information that flows into the electricity market. This would provide definitive proof of whether the GARCH effects are really evidence of market inefficiency, or the result of the irregular flow of market information. Research into Australian electricity markets could be extended in a number of other ways. One useful extension would be to examine each of the five electricity markets individually and in more detail. For example, while the sample for this study is determined by the period of tenure of the NEM wholesale electricity spot markets in the separate regions pre-date this by several years. An examination of the connection between the long-standing electricity spot markets in NSW and VIC would be particularly useful. Another suggestion concerns the electricity strip contracts offered by the SFE (2002) on several of Australia's NEM jurisdictions. An examination of the relationships between Australian spot and derivative electricity prices would then be interesting.

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