E ECONOMETRIC ANALYSIS Introduction E.1 This annexe is in three parts. Part One presents our econometric methodology, which is unchanged from the methodology we adopted in the Proposed Decision. It also includes tables of regression results, which were included in the Proposed Decision but which we subsequently revised in the Additional Note on Price Concentration. We include those original tables of results in Part One only for completeness: we do not rely upon them. E.2 Part Two is the Additional Note on Price Concentration, which was published on 9 October but which was provided to Frontier Economics, who reviewed it on behalf of four major bus operators, in advance of its publication. The note includes our revised regressions on which we rely for our findings. Part Two reproduces the note as it was originally published. E.3 Part Three contains our response to the report submitted by Frontier Economics (Frontier) in relation to our econometric analysis. It discusses the issues raised by Frontier and presents a number of robustness tests that we have conducted in the light of Frontier's report. E.4 Part One includes the tables and text from Annexe C of the Proposed Decision exactly as they were published in the Proposed Decision. For consistency we use the same paragraph and table numbering in Part One as was used in the Proposed Decision. Therefore, references to Annexe C of the Proposed Decision or paragraphs and tables within it can be read as also being references to Part One of this annexe. E.5 Similarly, and for the same reason, references to the Additional Note on Price Concentration can be read as being references to Part Two of this annexe. E.6 Taken together the three parts of this annexe present our methodology, findings and robustness checks with respect to our OFT1158a | 125 econometric analysis: to that extent they should be read in combination with each other. OFT1158a | 126 PART ONE: REPRODUCTION OF ANNEXE C FROM THE PROPOSED DECISION C Impact of market structure on bus fares Introduction C.1 This section examines how bus fares vary across local markets in relation to the number and the identity of bus operators providing local bus services. In particular, we test the hypothesis, which was put to us in the course of this study, that the local bus markets are contestable so that an operator which is a sole provider of commercial bus services in a local area is prevented from increasing prices above competitive level by threat of potential entry. C.2 The data which we have obtained in the course of this study rejects the strong version of this hypothesis. Our analysis suggests that bus fares are higher when there is only one national operator providing services in a LTA after controlling for a range of factors which can be expected to influence pricing of bus services. These factors include competition from the car, local area socio-demographics, service quality, traffic density and operators’ cost. We also find some evidence that the move from monopoly to duopoly may have a stronger negative effect on bus fares than the effect of any additional entry. C.3 Because of data limitations we are not able to say much about the nature of the competitive constraint imposed by rival operators on each other when they provide services in the same LTA. In particular, we have not been able to establish whether fares are lower when rivals are engaged in head to head competition, or when they serve overlapping inter-urban services, or indeed, as put to us by some operators, whether a mere presence of rival operators nearby act as an effective constraint on pricing. C.4 The operators have raised various issues about the quality of some of the underlying data which we used in our study. We have considered their points very carefully. After carrying out additional analysis we concluded that, on balance, our findings are sufficiently robust for OFT1158a | 127 the purpose of a consulting on our proposed decision to make a market investigation reference to the Competition Commission. C.5 The reminder of this annex is structured as follows: • methodology • data • exploratory data analysis • regression results and • robustness and endogeneity checks. Methodology C.6 For the purpose of testing the contestability hypothesis, we use an empirical technique called price-concentration analysis. This technique investigates the relationship between price and the market concentration using multiple regression analysis. C.7 The basic intuition for using price-concentration analysis in this context is that if bus markets are contestable fares should be independent of market concentration. A finding that fares depend on concentration shows that markets are not perfectly contestable (it does not however rule out the possibility that potential competition exerts some influence on pricing). C.8 Our measure of price is the average fare charged by the subsidiaries of national operators in LTAs across the country. We relate this variable to the number of national operators providing commercial services in a particular LTA. We also consider the impact of smaller operators on the fares charged by national operators. C.9 When conducting a price-concentration study, in addition to the impact of market concentration which is the main focus of interest, it is important to control for factors which may affect firms' pricing behaviour. If these factors are omitted from the analysis, and they OFT1158a | 128 are correlated with concentration measures, the regression of price on concentration variables may result in biased parameter estimates. C.10 In deciding which control variables to consider in our analysis, we were guided by the literature and by bus operators’ own views which we have elicited in the course of this study. Specifically, we consider the following factors: • competition from the car • quality of bus service • local cost differences • local socio-demographics • traffic density and • average journey distance. C.11 A more detailed description of how we measure these variables is provided below at paragraphs C.22 to C.26. Data Sources C.12 The main data used in our analysis comes from the STATS100 database held by the DfT. This database is compiled from financial year survey returns to the DfT from bus operators licensed for 20 or more vehicles. The principal aim of the survey is to collect information from the industry in order to monitor national and regional trends and inform policy development. C.13 Permission was obtained from the four national operators to have access to their survey returns to the DfT.104 The data contains information on passenger boardings and receipts, revenue support, concessionary fares and vehicle miles which is provided at LTA level. 104 These are First, Stagecoach, Arriva and Go-Ahead. OFT1158a | 129 The data also contains information on operators’ fleet size, type of vehicles used, operating and administrative costs, depreciation and profitability. C.14 DfT told us that they have made some adjustments to the raw data supplied by the operators to account for under-recording of ticketless passengers by the operators. DfT also told us that although passenger boardings and revenue are collected at LTA level, the survey is designed to provide estimates which are robust at national and regional level and the figures at LTA level are of lesser quality. C.15 We have supplemented DfT’s data with two additional data sources. We obtained information on competition from the car and socio- demographics at LTA level from the 2001 census data compiled by the Office for National Statistics (ONS) in England and Wales and by the General Register Office for Scotland in Scotland. We also obtained a list of names, addresses and the number of vehicles for all bus operators in the UK from Vehicles & Operator Service Agency (VOSA). Variable definitions Dependent variable C.16 As mentioned in paragraph C.8, our measure of price is the average fare charged by subsidiaries of national operators in LTAs across the country. We have calculated this measure by dividing total passenger receipts by our estimate of the number of paying passenger boardings which are reported by the operators to the DfT for each LTA in which they operate. We have based our analysis on the data for 2006/07.105 This is the last year for which the revenue dataset was made available to us by the DfT. C.17 We did not have the corresponding paying passenger numbers as these were first reported by the operators in 2007/08. This meant that we had to make an estimate of the paying passenger boardings for 2006/07. We did this by calculating the proportion of the paying 105 In 2006/07, data was reported for 133 LTAs outside London. OFT1158a | 130 passenger boardings in the total passenger boardings in 2007/08 and then applying this proportion onto the total number of passenger boardings reported in 2006/07 to estimate the number of paying passenger boardings in 2006/07. C.18 This procedure may introduce measurement error in our analysis which under certain circumstance may cause parameter estimates to be biased.106 We discuss this possibility, and explain how we dealt with it, at paragraphs C.35 to C.45 below. Concentration measures C.19 We use two measures of market concentration for national bus operators. One is a binary indicator variable which distinguishes between cases when there is only one national provider of commercial bus services in an LTA area, and cases where there are two or more national operators. The other measure is a count of national operators providing commercial services in a particular LTA. When there are two or more subsidiaries from the same parent company operating in the same LTA, we count this as only one competitor.