Airline Price Competition: A Time Series Analysis of 'Low-Cost' Carriers.

This paper, after providing an introduction to the operating context of low cost carriers in Europe, examines the competitive pricing behaviour of airlines. Data is collected by route for cases where more than one airline is in direct competition. Data on fares is obtained from the internet for two airlines with competing services to Alicante, Prague and Malaga, departing from Nottingham East Midlands Airport in the UK, for the six working weeks up to and including the actual departure. These destinations represent leisure traffic. Two domestic business destinations were also selected to illustrate price competition on business demand where departure times were within a maximum of 20 minutes of each other and a further examination of competing services from London Gatwick (LGW) was made. Cross Correlation Analysis is used to examine whether, subject to a variety of lags, the prices offered by one airline can be seen to be both correlated with the other price series and to lead it. This provides some insight into the pricing strategy adopted by the competitors. Autocorrelation Functions (ACFs) and Partial Autocorrelation Functions (PACFs) can also be produced on the prices offered by each airline. These suggest the nature of the ARIMA model that can be fitted to the series and these models can show the degree to which series values are correlated with their own past values and whether a reasonable model could be based on an ARIMA approach. The relative strength of these two relationships is examined; are prices more closely explained by the competitor's actions or the airlines own past price setting?

Ryanair's Impact on Airline Market Share from the London Area Airports - a Time Series Analysis

Ryanair tends to operate to destinations from its UK bases that are not the main airports in the country being served and in this it differs from many other European low cost carriers. For example, it flies from London Stansted (STN) to Venice Treviso (TSF), whereas the competition flies from other London area airports to Venice Marco Polo (VCE). So although direct competition is not provided in the way that rival services operate between identical pairs of airports, indirect competition is provided. This raises the question, when Ryanair commence services, what is the impact on the market share of the incumbent airlines at these other airports? This can be shown by examining UK Civil Aviation Authority (CAA) data on scheduled passengers carried, along with OAG data on flight frequency, airline and aircraft type on a number of selected routes. The impact on market share can be shown and the conclusion suggested that total traffic is stimulated on these sectors so that incumbent's traffic might fall, be constant or even increase, whilst their share, and probably their yield, falls, as Ryanair exploits latent demand. These findings echo previous work, for example, Barrett (2000). These conclusions are really generated hypotheses and these can be tested more completely by a time series analysis on monthly passenger data from 1991- 2003

Ryanair’s impact on airline market share from the London area airports: a time series analysis.

Ryanair tends to operate to destinations from its UK bases that are not the main airports in the country being served and in this it differs from many other European low cost carriers. Although direct competition is not provided in the way that rival services operate between identical pairs of airports, indirect competition is provided. This raises the question, when Ryanair commence services, what is the impact on the market share of the incumbent airlines at these other airports? It seems that total traffic is stimulated on these sectors and that the incumbent's traffic generally falls whilst their share, and probably their yield, also falls as Ryanair competes. Ryanair appears to gain more market share than its initial stimulus to the market

The impact of the EU–US Open Skies Agreement and the resulting British Airway's Open Skies initiative: passenger numbers in London, Amsterdam and Paris

The advent of the EU–US Open Skies Agreement has been widely anticipated. A number of consequences have been predicted, for example, impacts on fares, passenger volumes, choice and consumer welfare. Airline costs are also predicted to fall as a result of increased competitiveness and increased cooperation among airlines. For the short period since the implementation of the Agreement, it is relatively easy to assess the supply-side changes that have been made, but more difficult to make wider judgements. This paper indicates the data that will be required to make these judgements and notes some methodological difficulties. Early estimates of the impact on passenger numbers are given using time series analysis focusing on London airports, in particular London Heathrow and airports served by British Airway's Open Skies Airline from Paris Orly and Amsterdam Schipol

Assessing the impact of open skies agreements

This chapter outlines the individual country open skies agreements between the USA and other countries as well as the EU-US Open Skies Agreement signed in 2007, which came into force in 2008. Evidence is provided on the impact of both the individual agreements as well as the EU-US Agreement by using time series analysis with intervention terms to estimate the impact on passenger numbers. The empirical focus is on British Airways (BA) and its Open Skies off shoot airline serving New York from Paris Orly. Comments are also made on the recently discontinued service from Amsterdam (AMS) as well as the impact on slots at airports, including London Heathrow, and on airline start ups given the change in ownership regulations, for example the case of Virgin America. The data requirements of a more widespread assessment looking at costs and pricing is reviewed, following the reports of the Brattle Group and Booz Allen Hamilton, as well as the difficulties of dealing with the counterfactual, if such data became available

Labour Migration and the Regional Problem in Britain, 1920-1939

Whilst reading for my first degree at the University of Bristol I became particularly interested in two diverse fields of study. An interest in Regional Economics was motivated by the sparse coverage given to the consideration of the spatial organisation of the economy in most standard works. The other interest was in British Economic History of the inter-war years. I am indebted to Dr, B.W.E. Alford for inspiring and developing my curiosity for this subject. In choosing a subject for research, I endeavoured to combine these two interests. Virtually no work has been done on the formative years of British regional policy. I thought this to be a particularly important gap to fill in that I could closely document regional policy in these years and give some insight into the processes of government policy formulation. In addition, the inter-war years is a unique period in the history of British regional policy. It is the only period when the objective of policy was to move 'workers-to-the-work', rather than 'work-to-the-workers'. Even less information is readily available on policies encouraging labour migration, than on the better known Special Areas policy. Consequently, my own interests and the gap in interpretation suggested the examination of the role of labour migration policies in the inter-war period as the subject for my research. The thesis is set out in three sections. The first section is an introduction. The regional problem is described, the pattern of labour flows documented and the factors influencing these flows is shown. The second section is concerned with regional policies. These are traced from the introduction of transference policy until, and including, the introduction and development of Special Areas policy. The effects of these policies are judged at a regional level and, in Chapter 8, at the micro-economic level. The final section describes the culmination of the inter-war year's experience of regional policies with the appearance of the Barlow Report and the discrediting of transference. The conclusion shows the importance of transference in the inter-war years and the paradox of the post- World War II situation where labour migration has been ignored as a policy tool

A time series analysis of the pricing behaviour of directly competitive 'low-cost' airlines

This paper, after providing an introduction to the operating context of low cost carriers in Europe, examines the competitive pricing behaviour of airlines. Data is collected by route for cases where more than one airline is in direct competition. Data on fares is obtained from the internet for two airlines with competing services to Alicante, Prague and Malaga, departing from Nottingham East Midlands Airport in the UK, for the six working weeks up to and including the actual departure. These destinations represent leisure traffic. Two domestic business destinations were also selected to illustrate price competition on business demand where departure times were within a maximum of 20 minutes of each other and a further examination of competing services from London Gatwick (LGW) was made. Cross Correlation Analysis is used to examine whether, subject to a variety of lags, the prices offered by one airline can be seen to be both correlated with the other price series and to lead it. This provides some insight into the pricing strategy adopted by the competitors. Autocorrelation Functions (ACFs) and Partial Autocorrelation Functions (PACFs) can also be produced on the prices offered by each airline. These suggest the nature of the ARIMA model that can be fitted to the series and these models can show the degree to which series values are correlated with their own past values and whether a reasonable model could be based on an ARIMA approach. The relative strength of these two relationships is examined; are prices more closely explained by the competitor's actions or the airlines own past price setting

The Southwest effect : a time series analysis on passengers carried by selected routes and a market share comparison

The Southwest effect has been known for some time in terms of the US airline’s impact on pricing, competition and traffic volumes. But recent estimates of the impact on traffic and market shares do not exist. This desideratum can be addressed by applying Autoregressive Integrated Moving Average (ARIMA) models with Intervention analysis to key domestic air routes in the USA where Southwest has started service. The paper first deals with the choice of routes to be examined and, after a preliminary statistical description of these, applies the ARIMA models. These results are examined for both their statistical qualities and their reasonableness and the impacts are compared to those previously determined in the same way for Ryanair’s routes from London

Airline Price Competition: A Time Series Analysis of 'Low-Cost' Carriers

This paper, after providing an introduction to the operating context of low cost carriers in Europe, examines the competitive pricing behaviour of airlines. Data is collected by route for cases where more than one airline is in direct competition. Data on fares is obtained from the internet for two airlines with competing services to Alicante, Prague and Malaga, departing from Nottingham East Midlands Airport in the UK, for the six working weeks up to and including the actual departure. These destinations represent leisure traffic. Two domestic business destinations were also selected to illustrate price competition on business demand where departure times were within a maximum of 20 minutes of each other and a further examination of competing services from London Gatwick (LGW) was made. Cross Correlation Analysis is used to examine whether, subject to a variety of lags, the prices offered by one airline can be seen to be both correlated with the other price series and to lead it. This provides some insight into the pricing strategy adopted by the competitors. Autocorrelation Functions (ACFs) and Partial Autocorrelation Functions (PACFs) can also be produced on the prices offered by each airline. These suggest the nature of the ARIMA model that can be fitted to the series and these models can show the degree to which series values are correlated with their own past values and whether a reasonable model could be based on an ARIMA approach. The relative strength of these two relationships is examined; are prices more closely explained by the competitor's actions or the airlines own past price setting