ENERGY SUSTAINABILITY AND COMPETITIVE MARKETS

Transcription

1 INTERNATIONAL ACADEMIC SYMPOSIUM ENERGY SUSTAINABILITY AND COMPETITIVE MARKETS Parc Científic de Barcelona. Auditorium Barcelona, January 29, 2013 Organising institutions: Sponsor: CHAIR OF ENERGY SUSTAINABILITY AT THE UB

2 Thank you, Funseam and the Chair of Energy Sustainability, for inviting me to speak here today; and thank you, Paulina Beato, for such a comprehensive introduction. My talk looks at the switching behaviour of UK consumers and is based on the policy premise underpinning the liberalisation of the British electricity market: namely, that offering consumers a choice of supplier can promote market competition. My intention is to determine whether we can move beyond a simple measure of success, which is the number of consumers switching, and define a more comprehensive measure of market engagement in terms of the psychological difficulties and other difficulties consumers need to overcome to make informed choices that stimulate suppliers to behave competitively. First, a brief institutional overview of the UK market. In 1990, competition was introduced at the generation level of the market and initially there was unbundling between generation and supply. After 1998 and accompanied by certain financial difficulty to generate companies, a more liberal policy towards vertical integration was introduced and we saw integration between generators and suppliers. The focus of my discussion is on the supply to consumers, so the next set of pointers are about the fact that in 1999 competition in supply was complete for the electricity market. In 2001, the regulator deemed the direct debit market sufficiently competitive to forego price controls, and in 2002 the whole market was deregulated, meaning that from then on prices were set by supplying companies with no intervention from the regulator. Note that my last point of reference is 2006, the final year in our analysis because of a change in energy supplier behaviour during that year, characterised by increasing range and complexity of tariff. Note too that this led the regulator to investigate the market, and because it found that this complexity of tariffs might hamper market engagement, after the energy supply probe in 2008 it decided to promote a simplification in tariffs and, ideally, a reduction in number. These decisions are currently being implemented in the British market. In terms of supply-side note the intense initial activity, which included 14 regional suppliers, British Gas and various independent companies. Since late 2002, however, various processes of consolidation have led the market to become dominated by six retailers. At least during the period under examination, these retailers have not been allowed special agreements with any single consumer and must treat all consumers equally; in terms of consumer behaviour and according to a government survey by Ofgem (Office of Gas and Electricity Markets), more than two-thirds of the consumers who switched supplier did so for a price differential, seeking a better price offer. Examining retail pricing can therefore tell us about both consumer behaviour and supplier reaction to the opportunities offered by retail competition. As I suggested earlier, the success of these pro-competitive policies can be evaluated by examining how many people switched electricity supplier. The UK is considered to be a successful example of switching and if we look at the final year of our analysis, 2005, we see that a total of 4.5 million consumers or approximately one-quarter of the total number of UK consumers had switched. Of this total figure, 40% were moving from the incumbent supplier to the entrant, 23% were returning from the entrant to the incumbent, and 40% were changing across new entrants. As these figures suggest, the market was very active; but at the same time there was a persistent differential in prices that didn t seem to be an indication of effective competition in the market, and this is what we decided to investigate. In a market with homogeneous products, a reasonable number of players and competition based mostly on price we d 1

3 expect prices to quickly converge; but we don t seem to see this type of behaviour and Slide 6 illustrates this with these two figures. The first shows us the difference between the bill charged by an incumbent and the median bill that can be found in the market, and the blue line indicates the difference between the incumbent price and the lowest available market price. And in percentage terms the dispersion reaches levels of about 12%. The bottom of the picture describes what was happening with new entrants and indicates that even within the new suppliers in the market, there s a whole range of different prices on offer over the whole period. Our basic explanation for this price dispersion goes back to economic theory, which argues that price dispersion is an equilibrium solution to market interaction when there are opposing forces in supplier decision-making. Once the new entrants have acquired a reasonable number of consumers, when they set their prices they re dealing with a tradeoff: on the one hand, they charge lower prices to attract new customers, and on the other they charge high prices to earn revenue from the consumers they ve acquired. And this means that they tend to behave like incumbents: they ve acquired loyal customers and they can exploit their position. Actually, company pricing strategy is mixed: companies randomise their offering so that they sometimes offer their best deal and sometimes don t, and the best deal is never being offered by the same company over a period of time. The way in which we then evaluate this phenomenon of price dispersion goes back to the theory of consumer search and we rely on results of non-sequential search with an unequal distribution of consumers. This is because we basically want to remember that there s an incumbent in the market with a relatively stronger position and a group of entrants with different strategic incentives. There are various empirical studies on this (mutual fund or car insurance, for example), but there s been no attempt to evaluate the size of the search cost. So we still need to understand the monetary value of this effort we need to make to identify our best deal as consumers, and if this value is high enough we won t bother to carry out the search. A brief description of our modelling framework. Here we use a distribution of search cost, assuming there are different consumers with different levels of search cost, and their decision to search is informed by the difference between the potential gains from searching (H) and the marginal cost of making one extra search based on the reservation price. In terms of suppliers, we represent the market with one incumbent and asymmetric entrants and assume that the incumbent serves more of the market than any entrant does. Prices decisions are made by taking consumer search and switching behaviour as given, and other firms prices also as given. Everything revolves around a distribution of prices that you can actually observe. Finally, just to highlight the tradeoff that an entrant company has to face when setting its prices, the profit that an entrant can make is based on extracting rent from local consumers that are prepared to pay the price offered by the entrant, from switchers that come from other entrants, from switchers from the incumbent and, if the entrant we re considering has the lowest price, from anyone else whose reservation price below the lowest price, which converts into this rather ugly relationship. In our analysis we were looking at the bills for medium levels of consumption over the period between February 2002 and December 2005, when there were no price controls and the number of tariffs on offer was limited. Comparing the companies should have been relatively straightforward: we re looking at direct debit consumers who represented 40% of the market, over 14 areas, and between 11 and seven companies. We also took into account 2

4 company costs, which might differ across regions, and the fact that an incumbent s market share was differed from the others. Over time, we examined how this market share evolved in our calculation of results. Slide 14 estimates price distribution type in the presence of different levels of incumbent power. The pink line represents the situation where there is just a monopolist and as we move towards lambda = 0 we have different levels of market power by the incumbent, so the entrants are earning market shares. Under specific assumptions about the shape of this function, prices are lowest when there s only an incumbent supplier because all the entrants have an incentive to price down. As they acquire more market share, there s a price-low or price-high tradeoff and slightly more price dispersion that is sustainable as a profitable strategy. Setting aside the estimation strategy, we look at search cost size across regions and over time. On the one hand, we see a decrease over the period in question, possibly because of greater consumer awareness that an option could be chosen and nothing would actually go wrong (consumers don t stop receiving electricity just because they change supplier) and there s an increasing use of the internet to find information about good deals. Generally speaking, however, the search costs over this period are high (up to about one-quarter of the size of the bill) and so high for a large number of consumers that it s not even worth them starting the search. Slide 16 describes the decrease in search cost distribution over time, indicating that it becomes less burdensome to find a good price level. Slide 17 illustrates that the monetary value of the cost associated with finding a good deal decreases but differs considerably across regions (from approximately 38 to over 50, with a bill size of between 250 and 300). This would indicate that price policies are compatible with a level of price dispersion that makes it relatively costly for consumers to find the best deal, and that obfuscation helps maintain a wide price range. Because this initially conflicts with our observation about how the UK market had experienced substantial switching, we verified the search costs over time and by region. Based on data on savings over our chosen time period, we predicted the number of switchers. From the data available from average bill to lowest possible bill, we predict between 75% and 125%, but from average bill to second lowest i.e., the possibility that consumers don t find the best deal we predict between 55% and 90% and therefore propose that the type of search cost we re measuring reflects the behaviour observed in terms of switching. At the regional level, we tried to predict the pattern of people moving away from the incumbent supplier; and because at the regional level we only knew the market share, we tried to predict the market share of the incumbent and we found a good level of correlation in terms of the positions of the different companies. Here we list the regional companies, their market share and the predicted market share. The ranking of most or least successful retailers predicts reasonably well that customer loyalty in Scotland is better, for example, than it is in London or the East Midlands. Our conclusions, therefore, are that despite evidence of intense switching the UK electricity market remains characterised by a persistent level of price dispersion that can in part be explained by customer confusion about best deals. Finally, the values we estimate are relatively high but remain consistent with the switching behaviour both over time and at the regional level. 3

5 CÀTEDRA DE SOSTENIBILITAT ENERGÈTICA DE LA UB CÁTEDRA DE SOSTENIBILIDAD ENERGÉTICA DE LA UB CHAIR OF ENERGY SUSTAINABILITY AT THE UB