Global Hub Economic Impact Study

Transcription

1 Global Hub Economic Impact Study A REPORT PREPARED FOR THE GREATER TORONTO AIRPORTS AUTHORITY February 2014

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3 February 2014 Frontier Economics i Global Hub Economic Impact Study (GHEIS) Executive Summary 1 1 Introduction Background to the study What is the study s objective? How does this study differ from most others? How is the report structured? How does air connectivity facilitate economic value? What do we mean by economic value? What about causality? What is our approach? What is the significance of connecting passengers? How do we estimate economic value in the future? Why are our results additional to the DII approach? How do we quantify Toronto Pearson s contribution to economic value? What-if scenario Values for key assumptions What are our results? Economic value facilitated by Toronto Pearson today Combined results today Economic value facilitated by Toronto Pearson in Conclusion 39 Appendix 1: Methodology Economic value today 41 Appendix 2: Methodology Economic value in Appendix 3: Methodology Competitive scenarios in Appendix 4: Sensitivity tests 80 Appendix 5: References 82 Contents

4 ii Frontier Economics February 2014 Figure 1. Key relationships... 2 Figure 2. Overview of project scope... 7 Figure 3. Summary overview of our approach... 9 Figure 4. Drivers of economic value considered in analysis Figure 5. The virtuous circle between connectivity and economic value Figure 6. Key relationships Figure 7. How hub status enables more direct connections Figure 8. Passenger volumes to different continents in Figure 9. Passenger volumes to different continents in Figure 10. Overview of steps to calculate economic value facilitated today Figure 11. Illustration of differences in trade barriers Figure 12. Return on investment Figure 13. Outbound flights versus exports Figure 14. Trade and business travel by country Figure 15. Inbound flights versus inward FDI Figure 16. FDI differential between connected and unconnected countries Figure 17. Evidence on relationship between face-to-face meetings and trade Figure 18. Evidence on relationship between face-to-face meetings and FDI Figure 19. Impact of FDI on productivity Figure 20. Overview of methodology for future economic value Figure 21. World Bank Oil Price Forecast Figure 22. Share of total passenger volumes at Toronto Pearson and 11 hubs in the US Figure 23. Hub airports considered in our 'competitive scenarios' Figure 24. Growth in passenger volumes Figure 25. The distribution of 'contestable' passengers Figure 26. Network effect on a given route Contents

5 February 2014 Frontier Economics iii Figure 27. An example of capturing contestable connecting passengers Figure 28. Comparison of passenger volumes at Toronto Pearson Table 1. Total value facilitated by Toronto Pearson 5 Table 2. Economic value facilitated by trade, FDI and tourism spending 11 Table 3. Assumptions on passenger types 23 Table 4. Assumptions on Key Relationship 2 24 Table 5. Assumptions on Key Relationship 3 26 Table 6. Assumptions on Key Relationship 4 27 Table 7. Overview of key assumptions and selected values 29 Table 8. Economic value facilitated by Toronto Pearson today 32 Table 9. Economic value facilitated by Toronto Pearson in Table 10. Overview of economic input data - Trade and FDI links between Ontario and each geography 43 Table 11. Tourism spending per passenger-visit 56 Table 12. Summary of GDP growth assumptions 63 Table Passenger volumes at Toronto Pearson and 11 competitor hubs 64 Table 14. Connecting passengers at rival hubs in the US (m) Table 15. Frequency elasticities of demand (FEDs) 77 Table 16. Worked example of frequency elasticity of demand Peru Contents

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7 February 2014 Frontier Economics 1 Executive Summary Background and project objective Toronto Pearson currently serves 35 million passengers per year who fly to and from more than 180 destinations worldwide. 25 per cent of travel facilitated by Toronto Pearson is outside North America. As a significant and growing hub airport in North America, Toronto Pearson serves connecting as well as local passengers, thereby increasing the number of routes it is able to offer. The airport is closely linked to the local economy and contributes to economic value in several ways. It is common for studies on the economic impact of airports to focus on the role of airports as an employer, and to quantify the direct, indirect and induced benefits to the economy. This traditional approach to quantifying the economic value of an airport has been completed by HRD/HLB Decision Economics for Toronto Pearson and has revealed that in 2012 the airport generates the following within Ontario: 124,000 direct, indirect and induced jobs; $12.7 billion of Ontario s GDP; Total employment income of $6.3 billion; and $2.8 billion taxes paid to governments. However, in only focusing on the airport as an employer like any other business this traditional approach does not capture the unique activities that an airport facilitates, therefore, it only tells part of the economic value story. The challenge of this study is to find a way to quantify the airport s impact on the economy, focusing on the economic activities facilitated by the connectivity the airport provides. Our results, relating to the wider economy, can then be added to the traditional approach of quantifying the direct, indirect and induced impacts of the airport itself. The objective of this study is to quantify the economic benefits from air travel facilitated by Toronto Pearson today and in the future to the economy of Ontario. Our methodology estimates the contribution of Toronto Pearson to the economy based on business relationships and leisure spending facilitated by air connectivity. Our results demonstrate the economic value facilitated today (based on 2012 data) and in How does Toronto Pearson facilitate economic value? When we refer to economic value we mean the impact of the airport on Ontario s GDP and employment, as these two metrics are most closely related to Executive Summary

8 2 Frontier Economics February 2014 living standards. We acknowledge that there is a two-way relationship between air connectivity and economic growth, and that there are many other factors that influence both connectivity and economic value. As such, we interpret our results as the economic value facilitated by the airport rather than the economic value generated by the airport. The best way of thinking about this is a virtuous circle that links connectivity and economic growth. Toronto Pearson contributes to economic growth, but is not the only factor. At the same time, economic growth can create more demand for connectivity. There is extensive evidence to show that causation works both ways. Connectivity plays a key part in helping a well-functioning and open economy to achieve its full potential. Viewed in this way, it is clear that Toronto Pearson makes a vital contribution to the Ontario economy. Although connectivity does not itself create economic activity directly, economic activity would suffer if the connectivity provided by Toronto Pearson were removed or inhibited in some way. The way in which air travel relates to GDP and employment through trade, foreign direct investment and tourism is indirect. We estimate the link between connectivity and economic value by breaking the relationship down into a number of steps, as illustrated in Figure 1. Figure 1. Key relationships Executive Summary

9 February 2014 Frontier Economics 3 To develop a quantitative value for each of the key relationships, we undertook an extensive literature review. We considered academic papers, institutional reports, and industry expertise. Based on this evidence, we selected conservative assumptions to underpin our results. Section 3.2 and the Appendices provide a detailed justification of our assumptions. We estimated the value of Toronto Pearson as a hub airport by comparing the airport against a what-if scenario. Our what-if scenario assumes that Toronto Pearson does not provide direct flights, so all passengers have to take indirect flights via another hub airport to get to their final destinations. This what-if scenario measures the economic value of being directly connected to destinations. We concluded that this provides a realistic approach to valuing the Toronto Pearson s connectivity as a hub airport. This study just focuses on the economic value facilitated by passengers travelling through Toronto Pearson. As such, the economic value facilitated by air freight that passes through Toronto Pearson is beyond the scope of this study. Therefore the results can be considered conservative in this respect. What is the economic value facilitated by Toronto Pearson today? Based on our approach, we estimated that the economic value to Ontario facilitated by direct connections from Toronto Pearson today is equal to 3.6 per cent of Ontario s GDP, equivalent to $22.7 billion. Based on this estimate, Toronto Pearson currently facilitates 153,000 jobs. This is comparable to the total employment in the retail or service sectors in the City of Toronto as indicated by the 2012 employment survey (City of Toronto, 2012). Approximately 55 per cent of the results can be attributed to connections within Canada and to the US, and 45 per cent to connections with other countries. It is beyond the scope of this report to comment on the type of jobs and sectors facilitated by connectivity through Toronto Pearson. It is likely the jobs will be from trade and FDI intensive industries and will also depend largely on developments in the Ontario economy. We can combine our results with those from the direct, indirect and induced analysis because the latter effects relate to the impact of the airport itself and the spending by people employed in airport-related activities. Our estimates are additional as they consider the benefits facilitated to the wider economy by the use of the airport by passengers. Combining the results from the direct, indirect and induced analysis with our results, the total economic value facilitated by Toronto Pearson today is: 277,000 jobs or 4.2 per cent of total Ontario employment; and $35.4 billion or 5.6 per cent of Ontario GDP. Executive Summary

10 4 Frontier Economics February 2014 What is the economic value facilitated by Toronto Pearson tomorrow? Our baseline projections of travel demand at Toronto Pearson (based on income growth only) suggest that the airport will handle 60 million passengers in This is equivalent to average annual growth of 3 per cent. Our results suggest that Toronto Pearson will facilitate economic value to Ontario equal to 4.1 per cent of Ontario s GDP in 2030, equivalent to $37 billion. The result is slightly greater than for 2012, as demand for travel is partly based on GDP growth in high-growth economies, which are growing faster than Ontario GDP. We estimate that by 2030, Toronto Pearson will facilitate 247,000 jobs in Ontario. This is equivalent to the combined employment of the manufacturing and retail sectors in the City of Toronto s in 2012 (City of Toronto, 2012). Approximately 49 per cent of this result can be attributed to international connections (excluding the US), which is a slight increase from the results for today of around 45 per cent. This is because GDP growth in Canada and the US is expected to be relatively low compared to emerging markets, such as Brazil, India and China. Toronto Pearson has estimated that the direct, indirect and induced economic value facilitated by the airport in 2030 is 210,000 jobs and $21.6 billion of Ontario GDP. Combining these results with our results, we estimate that the total economic value facilitated by Toronto Pearson in 2030 is: 457,000 jobs; and $58.6 billion or 6.6 per cent of total Ontario GDP. In addition to the baseline results for 2030, we estimate the additional economic value that could be facilitated by Toronto Pearson if it increased its market share in the North American connecting passenger market. We estimate that there will be 131 million passengers connecting via one of the 11 North American hubs we examine that would consider Toronto Pearson as a substitute. The connecting passengers through a hub airport make a significant contribution to the number of direct connections and the frequency of flights that are viable. Therefore, the greater number of passenger s connecting via Toronto Pearson, the greater the economic value it will facilitate. As an illustrative example, we estimate the additional economic value if Toronto Pearson attracted 10 per cent of passengers that start or end their journey in North America, using a US hub (equivalent to 7.9 million passengers). In this case our approach suggests that Toronto Pearson would facilitate an additional 0.4 percentage points of Ontario s GDP alongside 17,000 jobs. Adding the results from the direct, indirect and induced analysis undertaken by Toronto Pearson for this scenario, the total economic value facilitated by Toronto Pearson under this scenario increases by Executive Summary

11 February 2014 Frontier Economics 5 19,000 jobs. This scenario illustrates that the success of Toronto Pearson as a hub airport has direct implications for Ontario s economy. Table 1 below summarises the total value facilitated by Toronto Pearson today and in The results combine the estimates of the HDR/HLB Direct, Indirect and Induced study with the results of the Global Hub Economic Impact Study. Table 1. Total value facilitated by Toronto Pearson with an additional 10% of passengers connecting that start or end their journey in North America GDP facilitated $35.4bn $58.6bn $ 62.1bn As % of Ontario GDP 5.6% 6.6% 7.0% Jobs 277, , ,000 Note: This table combined the results of HDR/HLB Direct, Indirect and Induced study with GHEIS study conducted by Frontier Economics. Executive Summary

12 6 Frontier Economics February Introduction 1.1 Background to the study Toronto Pearson currently connects 35 million passengers per year to more than 180 destinations worldwide. 25 per cent of travel facilitated by Toronto Pearson is outside North America. As a hub airport, Toronto Pearson serves connecting as well as local passengers, thereby increasing the number of routes it is able to offer. The airport is closely linked to the local economy to which it contributes in a number of ways. This ranges from concrete contributions, such as the number of employees at the airport, to less tangible impacts, such as the contribution of Toronto Pearson to the attractiveness of southern Ontario. It is common for airports to quantify their direct, indirect and induced economic impacts. This traditional approach to quantifying the economic value of an airport has been completed by HRD/HLB Decision Economics for Toronto Pearson and has revealed that in 2012 the airport generates the following within Ontario: 124,000 direct, indirect and induced jobs; $12.7 billion of Ontario s GDP; Total employment income of $6.3 billion; and $2.8 billion taxes paid to governments. However, in only focusing on the airport as an employer like any other business this traditional approach does not capture the unique activities that an airport facilitates, therefore, it only tells part of the economic value story. The challenge of this study was to find a way to quantify the impact of airport on the economy that focuses on the travel activities facilitated by the airport. Our results can then be added to the traditional approach of quantifying direct, indirect and induced impacts. Toronto Pearson already estimates direct, indirect and induced effect of the airport. This study completes the picture by considering the economic value facilitated by the air connectivity itself in addition to the employment generated by Toronto Pearson. 1.2 What is the study s objective? The objective of this study is to quantify the GDP and employment facilitated by air travel for business purposes and tourism spending. Our methodology estimates the contribution of Toronto Pearson to the economy from the business relationships and tourism spending facilitated by air connectivity. Our results Introduction

13 February 2014 Frontier Economics 7 demonstrate the economic value to Ontario facilitated today (based on 2012 data) and in For 2030, we also illustrate the opportunities for increasing economic value if Toronto Pearson can attract an increasing share of connecting passengers from other North American hubs. Figure 2 illustrates that our study is aimed at providing results for Toronto Pearson today and in the future. Our results estimate Toronto Pearson s contribution to Ontario s economy as the airport facilitates most of the economic value in the surrounding region. There are additional benefits from Toronto s connectivity to other provinces in Canada, but these cannot be quantified with the same level of certainty. Our results can therefore be interpreted as conservative estimates. Figure 2. Overview of project scope 1.3 How does this study differ from most others? Studies on the direct, indirect and induced impact of airports focus on the role of airports as an employer. Toronto Pearson has estimated that 124,000 jobs are generated by the airport. In contrast, this study focuses on the contribution of air travel to the economy by considering air travel as an input to business activities. We chose not to use an econometric model to estimate the relationship between flights and economic growth, as we acknowledge that the airport is not the only factor that contributes to economic growth, and it would be erroneous to suggest that the airport is the sole cause. Even though it is possible to account for this using a sophisticated econometric model, the available data is unlikely to provide robust results. Introduction

14 8 Frontier Economics February 2014 The best way of thinking about this is that connectivity represents an element in a virtuous circle of economic activity and growth. Air connectivity through Toronto Pearson contributes to economic growth, but is not the only factor. At the same time, economic growth creates more demand for connectivity. There is extensive evidence to show that the causation works both ways. Connectivity plays a key part in helping a well-functioning and open economy to achieve its full potential. We estimate the link between connectivity and economic value by breaking the relationship down into a number of steps illustrated in Figure 3. Our methodology is based on the following premises: a) Improved connectivity reduces travel times and hence travel costs, which has a positive impact on the number of business travellers connecting with Ontario. b) An increase in the number of business travellers to and from Toronto implies that they engage in a greater number of face-to-face meetings. This increases the likelihood of creating or maintaining a successful business relationship. c) More successful business relationships have a positive impact on closing deals, which increases trade and/or foreign direct investment (FDI). Both trade and FDI have a positive long-term impact on productivity and therefore GDP and employment. In addition to the impact of connectivity on economic value via trade and FDI, we also estimate the contribution to tourism spending. Tourism spending includes expenditures such as accommodation, food and beverages, entertainment and land transport. Introduction

15 February 2014 Frontier Economics 9 Figure 3. Summary overview of our approach CONNECTIVITY Number of routes and frequency of flights Ease of accessing more destinations (valued by monetising the value of time) Number of people travelling which has an impact on the likelihood of face-to-face meeting Likelihood of creating and/or maintaining successful business relationships Trade FDI Tourism spending ECONOMIC VALUE Output Productivity Employment 1.4 How is the report structured? This report is structured as follows: Section 2 provides an overview of the key concepts that underpin the methodology; Section 3 provides our detailed assumptions for quantifying economic value; Section 4 provides our results; Section 5 provides our conclusions. We have included more detail on our methodology in the Appendices. Appendix 1 provides an overview of our key assumptions and data sources for the estimation of economic value today. Appendix 2 details assumptions and data sources for our analysis in the year Appendix 3 provides more detail on how we estimated the potential market size for North American connecting passengers; Appendix 4 provides the results of our sensitivity tests; and Appendix 5 provides a list of references. Introduction

16 10 Frontier Economics February How does air connectivity facilitate economic value? This section provides an overview of the key elements of our approach. We first clarify how we define economic value in the context of connectivity and discuss the issue of causality. We also provide a detailed description of the key relationships that underpin our analysis. Lastly, we discuss the role of connecting passengers and our approach to estimating economic value in the future. 2.1 What do we mean by economic value? Our analysis is aimed at estimating the economic value facilitated by Toronto Pearson Airport. It is therefore useful to clarify what we mean by economic value. Ultimately we are interested in Toronto Pearson s contribution to Ontario s GDP and employment. GDP is generally defined as the sum of all goods and services produced in the economy, and is therefore closely related to living standards. Similarly, employment is one of the key factors that determine economic well-being. The way in which air travel relates to GDP and employment through trade, foreign direct investment and tourism is indirect. Figure 4. Drivers of economic value considered in analysis Table 2 provides an overview of the types of trade, FDI and tourism spending we include and the types of passengers to which they relate. How does air connectivity facilitate economic value?

17 February 2014 Frontier Economics 11 Table 2. Economic value facilitated by trade, FDI and tourism spending Trade FDI Tourism What is included? All traded goods regardless of whether they are transported by air, sea or road All FDI, for example, acquiring production facilities abroad or establishing a subsidiary abroad All types of visitor spending including accommodation, food and beverages, entertainment, land transport, etc. Type of passenger Passengers that travel for business purposes (regardless of their class of travel) All types of passengers Inward travel (originating outside of Ontario) Imports of goods and services facilitated by business travel, including international and interprovincial trade Investment by non- Canadians in Ontario (interprovincial investment is not included) Spending by visitors in Ontario Outward travel (originating in Ontario) Export of goods and services facilitated by business travel including international and interprovincial trade Investment by Ontarians in other countries (interprovincial investment is not included) Spending by Ontario travellers abroad Note: For more detail on the relevance on interprovincial investment, see Appendix 4 We have reviewed a number of Canadian government policy documents that advocate that trade and FDI are important drivers of future economic prosperity. Canada s State of Trade (2012), a report states that to further position Canada for long-term prosperity, the government aims to create new and deeper trade and economic relationships, particularly with large, dynamic and fast-growing economies. Advantage Ontario (2012), a report by Ontario s Jobs and Prosperity Council highlights key areas that should be targeted to maintain prosperity in the global economy. These include going global, driving productivity growth and encouraging innovation. The report recommends a shift in export activity to strategically target emerging economies and meet rising demand. Collaborating for Competitiveness (2013), a report by the City of Toronto discusses the importance of attracting companies and investment to Toronto How does air connectivity facilitate economic value?

18 12 Frontier Economics February 2014 to encourage business investment and formation. It also emphasizes the importance of establishing cross-border business partnerships and developing new markets and trade alliances. The City of Mississauga s International Marketing Strategy (2011) outlines its three key objective areas to increase its competitiveness on the global stage. This includes creating more global connections and marketing Mississauga s advantages to a broad global audience. All of the policy documents emphasize the importance of trade and investment, and imply that future economic growth depends partly on the ability to engage with high-growth potential countries such as Brazil, India and China. In all cases, the policies support diversifying Canada s trade links which are currently dominated by trans-border traffic. This is considered an important factor for future economic growth and resilience. Tourism also is considered an important sector, as evidenced by a range of policies such as Ontario s Tourism Investment Strategy and Implementation Plan (2011). Further, the City of Toronto s report on the Premier-Ranked Tourist Destination Project (2007) outlines the importance of tourism to the Toronto economy. It suggests tourism is a key export industry for Toronto that plays an important role in the growth of the economy by generating employment, foreign exchange earnings, investment and regional development. 2.2 What about causality? Studies on the relationship between connectivity and economic value are often criticized as there are a range of other factors that influence economic value. This implies that connectivity should be viewed as one of the factors contributing to economic value. While connectivity is one important factor that enables international business relationships to develop, alone connectivity is not a sufficient condition for economic growth. Clearly, other factors influence both connectivity and economic value. The best way to describe this relationship is a virtuous circle (shown in Figure 2 below). The relationship goes both ways: economic growth creates demand for connectivity, but connectivity enables growth. Both connectivity and economic value are also influenced by a range of other factors. In addition, studies on connectivity and economic value often do not take into account the issue of reverse causality. We acknowledge that there is a two-way relationship between connectivity and economic value. As such, we interpret our results as the economic value facilitated by the airport rather than the economic value generated by the airport. How does air connectivity facilitate economic value?

19 February 2014 Frontier Economics 13 We are aware of the two-way relationship between connectivity and economic value and have chosen not to use an econometric approach as this is unlikely to provide robust results. Instead we identify a number of key steps that link connectivity to economic value. But the fact that causation works both ways does not devalue the vital and unique contribution that an airport like Toronto Pearson makes to its local economy. The best way of thinking about this is that connectivity represents an element in a virtuous circle of economic activity and growth. The connectivity enabled by Toronto Pearson is not a sufficient condition on its own for creating economic activity, but the role the Airport plays in the economy is a necessary condition in helping a well-functioning and open economy to achieve its full potential. Figure 5. The virtuous circle between connectivity and economic value 2.3 What is our approach? In order to quantify Toronto Pearson s contribution to economic value, we divided the relationship between connectivity and economic value into a number of steps. Detail on each of the steps is in Appendix 1 and 2. Figure 6 summarizes the four key relationships we have identified. Each of the relationships is explained in detail below. How does air connectivity facilitate economic value?

20 14 Frontier Economics February 2014 Figure 6. Key relationships Key relationship 1 Macroeconomic trends and hub competition determine connectivity at Toronto Pearson We define connectivity at Toronto Pearson as the number of direct connections and the frequency of flights. The level of connectivity at Toronto Pearson is largely determined by two factors: a) Economic growth in Ontario and in the countries around the world that can be reached via Toronto Pearson. There is established literature on the income elasticity of air travel which shows how air travel demand increases with income. This includes, for example, the International Air Transport Association (IATA) (2007) and UK Department for Transport (2013). b) Different scenarios of competition with other North American hub airports have an impact on the number of passengers connecting through Toronto Pearson. Should Toronto Pearson capture a greater market share of the North American connecting passenger market the number of destinations served and the frequency of flights at Toronto Pearson would increase. Both of these factors influence the level of connectivity. How does air connectivity facilitate economic value?

21 February 2014 Frontier Economics 15 Key relationship 2 A change in connectivity has an impact on demand A change in connectivity has an impact on the travel times for local passengers. For example, an indirect flight may take an additional 2-3 hours in travel time when compared to a direct flight. A passenger makes a decision to travel based, in part, on the travel time. As a direct connection is always faster than flying indirect via another airport, some passengers will choose not to travel if there is no direct connection available or may travel less frequently. However, connectivity therefore has an impact on demand. More detail on this relationship is provided in Appendix 1. Key relationship 3 A change in the number of local passengers impacts tourism spending and international business deals A change in the number of local passengers has two impacts. The first impact is a direct effect on tourism spending: if fewer people visit Ontario (regardless of their travel purpose), tourism spending decreases. Tourism spending includes accommodation, food and beverages, entertainment and land transport. The second impact applies to business passengers only. A drop in the number of business passengers indicates a decrease the number of face-to-face meetings. While some face-to-face meetings can be substituted by using video or teleconferencing, face-to-face meetings still play an important role in facilitating business deals. They are a key mechanism for building trust, which is important for establishing new business relationships, and even more important when conducting business across different cultures. In situations where business partners do not share a common language or culture and where business regulations vary significantly, it is important to get to know the other parties to ensure a successful relationship. We reviewed a large body of literature from a range of sources that provides evidence on the importance of face-to-face meetings for business. Here are some examples. The World Travel and Tourism Council (WTTC) (2011) conducted a survey of business travellers and asked about the importance of personal contact which revealed that: 28 per cent of existing business could be lost without face-to-face meetings; and Sales conversion rates are estimated to be per cent higher with face-to-face meetings. How does air connectivity facilitate economic value?

22 16 Frontier Economics February 2014 Frankel (1997) illustrates the importance of face-to-face meetings as follows: Consider a kind of export important to the United States: high-tech capital goods. To begin sales in a foreign country may involve many trips by engineers, marketing people, higher ranking executives to clinch a deal, and technical support staff to help install the equipment or to service it when it malfunctions. A survey by the UK Institute of Directors (2008) asked about the impact on businesses if the amount of business travel by air was significantly curtailed. 30 per cent of respondents said that there would be significant adverse effect, while 44 per cent indicated small adverse effects. Poole (2010) finds that business travel to the United States by non-residents, non-citizens has a positive impact on the extensive export margin. Connectivity is also one of the factors that influence decisions on where to locate business headquarters. For example, Strauss-Kahn and Vives (2005) find that: Headquarters relocate to metropolitan areas with good airport facilities, low corporate taxes, low average wages, high levels of business services, and agglomeration of headquarters in the same sector of activity. The effects are quantitatively significant (airport facilities in particular). Overall this literature review suggests that a drop in the number of business passengers is likely to have an adverse effect on trade and FDI, as face-to-face meetings are an important factor in establishing and consolidating business relationships. More detail on this relationship is provided in Appendix 1. Key relationship 4 A change in trade, FDI and tourism spending has an impact on GDP and employment Changes in trade, foreign direct investment and tourism spending affect GDP and employment. Tourism spending directly impacts on GDP. Spending by Ontarians abroad has a negative impact on GDP, given that the economic benefits accrue outside of Ontario. Spending by visitors in Ontario positively impacts on GDP, given it involves an inward flow of economic value. With respect to trade and FDI, we have distinguished the short-term static impact on GDP and the long-term dynamic impact. The short-term view of trade is that exports have a positive impact on GDP and imports have a negative impact this is based on a country s trade balance in an accounting context. The same holds for inward and outward investment. An equal increase in exports and imports would therefore have no impact on GDP, as the positive impact of exports would cancel out the negative impact of imports. How does air connectivity facilitate economic value?

23 February 2014 Frontier Economics 17 However, this short-term view does not take account of the long-term dynamic effects of having an open economy. An open economy that trades with the rest of the world both importing and exporting is likely to be more productive in the long term. Productivity is one of the key drivers of GDP growth as it describes the efficiency of production. For example, if the same output can be produced with fewer inputs, productivity increases. We reviewed a large body of academic research that investigates the positive impact of imports and exports as well as inward and outward investment on long-term productivity. Most of the literature is focused on examining the impact of trade and FDI on productivity at the firm level. The literature suggests that not only do exports and inward investment have a positive impact on productivity growth but imports and outward investment also contribute to the level of openness of the economy, which has a positive impact on productivity. There are three main channels by which imports, exports, inward and outward investment can increase long-term productivity. a) Innovation Trade is one of the key transmitters of innovation as it exposes companies to a wider range of products and processes in other countries. FDI can provide access to new technologies and cheaper inputs, which has a positive impact on productivity. This is particularly true for imports and outward investment. b) Competition puts pressure on companies to be more efficient. Exporting companies are faced with more competition as they compete in a larger market. Imports also put more pressure on domestic firms as they compete with a greater number of competitors. c) Economies of scale Larger market sizes imply that production processes can benefit from economies of scale. Both trade and FDI can provide access to markets outside Ontario so that firms can reduce costs by realizing economies of scale. This is particularly true for exporting firms who can access foreign markets and therefore increase their size. For example, the OECD, (2012) finds that: A main channel through which trade increases income is productivity growth. Importing creates competition that forces domestic firms to become more efficient and provides access to inputs of international calibre; exporting creates incentives for firms to invest in the most modern technologies, scales of production and worker training. The combined effect is to spawn a process of continual resource reallocation, shifting capital and labour into activities with higher productivity. This illustrates the combined effect of exports and imports. Similarly, the Canadian federal government (2012) states that the US-Canada free trade agreement has increased productivity in Canadian manufacturing by 13.8 per cent, which is considered a remarkable trade-related achievement. This How does air connectivity facilitate economic value?

24 18 Frontier Economics February 2014 achievement is based on both exports and imports. relationship is provided in Appendix 1. More detail on this Instead of focusing on the short-term impact of trade and FDI on GDP our methodology emphasises the long-term benefit that trade and FDI generate by increasing openness of the economy. Therefore, our conclusion is that both exports, imports alongside inward and outward investment, have positive longterm effects on an economy. 2.4 What is the significance of connecting passengers? Connecting passengers often only spend a few hours at the airport while they wait for their connecting flight. It is therefore a common misperception that connecting passengers contribute little to economic value compared to local passengers. However, the traffic of connecting passengers through a hub airport makes a significant contribution to the number of direct connections and the frequency of flights. In order for a direct route to become viable, a minimum level of demand is required. If this level of demand cannot be met by local passengers, connecting passengers can play an important role as they can take the level of demand above the threshold needed for a direct flight. Connecting passengers can therefore contribute to route profitability. Local passengers then benefit from the availability of additional direct services that might not be viable without connecting passengers. Figure 7 illustrates how connecting passengers can facilitate economic value. An increase in connecting passengers may be the result of a new or expanded route or may be the result of an increase in demand for connecting via Toronto Pearson. A higher number of connecting passengers can result in a further increase in destinations served and in flight frequencies. In addition, airlines may also operate larger aircraft. As a result, travel time is reduced for local passengers which can have a positive impact on demand. As some of these are business passengers, they contribute towards FDI and trade, which have a positive impact on GDP. How does air connectivity facilitate economic value?

25 February 2014 Frontier Economics 19 Figure 7. How hub status enables more direct connections These additional local OD passengers create additional economic value (FDI, trade and tourism spending) Increase number of connecting passengers Increased number of direct connections (that were previously indirect) Increased frequency on routes (e.g. twice a week to daily) Reduced journey time for local travellers Reduced journey costs, improved access for local travellers Increase in number of local OD passengers 2.5 How do we estimate economic value in the future? For our analysis of the future, we assumed that demand for travel to and from Toronto Pearson grows in proportion with economic growth. We used GDP projections and income elasticities of demand for air travel as an input and then apply the same approach for the year Any projection of the future is inevitably uncertain. Our approach was a business as usual one in which traffic at Toronto Pearson grows at the expected rate, given economic growth, but not taking into account any changes in market share between hub airports that might come about as a result of the competitive interaction in the market over the next twenty years. This results in projected average annual growth of 3% which is in line with GTAA s experience over the past 20 years. To examine the potential impact of these competitive interactions, we also considered the opportunities for Toronto Pearson to grow over and above this business as usual scenario by attracting connecting passengers from other North American hubs. We estimated the potential size of the market for these connecting passengers by considering 10 other North American hubs: Atlanta, Charlotte, Denver, Dallas, Detroit, Newark, Houston, New York, Los Angeles, Miami and Chicago. We estimated the number of connecting passengers that could consider Toronto Pearson to be a substitute hub based on the differences in travel time (see Appendix 2 for more detail). We applied the conditions above to estimate the total size of the connecting passenger market for which Toronto Pearson competes. We then ran different types of scenarios of hub competition. Linking these scenarios to our economic How does air connectivity facilitate economic value?

26 20 Frontier Economics February 2014 value calculation enabled us to estimate the size of the opportunity for further growth. 2.6 Why are our results additional to the DII approach? The analysis of direct, indirect and induced benefits has been undertaken by HRD/HLB Decision Economics for Toronto Pearson and has revealed that in 2012 the airport generates the following within Ontario: 124,000 direct, indirect and induced jobs; $12.7 billion of Ontario s GDP; Total employment income of $6.3 billion; and $2.8 billion taxes paid to governments. In 2030, Toronto Pearson has estimated that the airport generates: 210,000 direct, indirect and induced jobs; $21.6 billion of Ontario s GDP. These measures record the contribution that Toronto Pearson Airport makes to the local economy as a major employer. Not only are there many people directly employed by the airport, but these individuals then spend a significant proportion of their incomes on Ontario and Canadian goods and services, which further contributes to local GDP and employment. However, these direct, indirect and induced effects can be computed for any employer in the region and are only one aspect of the contribution that the airport makes. The airport also plays a significant role as a facilitator of economic growth across the local economy. The airport helps to support growing output and employment in many sectors because businesses use the airport s services to develop trade and investment links with other businesses around the world. In addition the airport facilitates tourism, which results in visitor spending in the local economy. Without the connectivity provided by Toronto Pearson, Ontario would be less accessible to the global economy and, as a consequence, Ontario could miss out on significant opportunities for growth. This report quantifies the dynamic impact that Toronto Pearson has on Ontario s GDP and employment in addition to the direct, indirect and induced effects quantified by HRD/HLB Decision Economics. It does so by examining the links between connectivity, trade, investment and productivity growth. These impacts can then be added to the direct, indirect and induced impacts. How does air connectivity facilitate economic value?

27 February 2014 Frontier Economics 21 3 How do we quantify Toronto Pearson s contribution to economic value? This section describes our detailed approach to quantifying the economic value facilitated by Toronto Pearson. We first discuss how we developed the what-if scenario and then describe the values and justifications of our key assumptions. More detail on our assumptions is provided in Appendix What-if scenario To quantify Toronto Pearson s contribution to economic value today, we consider the economic value that would be lost if Toronto Pearson did not provide the current level of connectivity. The size of the loss can then be interpreted as the value facilitated by the current level of connectivity. There are a number of options for defining the what-if or counterfactual scenario. First, we considered a what-if scenario in which Toronto Pearson does not exist. In this scenario air connectivity to and from Toronto would be severely decreased and travel times would increase substantially. However, we do no not think this is a credible approach as it would lead to an unrealistically large estimate of Toronto Pearson s value. Instead, we took a more conservative approach. Our what-if scenario assumes that Toronto Pearson does not provide any direct flights, so all passengers have to take indirect flights via another hub airport to get to their final destinations. As such, our what-if scenario measures the economic value of being directly connected to destinations. We concluded that this provides a realistic approach to valuing Toronto Pearson s connectivity as a hub airport. To develop a realistic view of the alternative travel times of indirect connections, we selected four North American hub airports for indirect international connections from Toronto. These were: Chicago, Atlanta, New York and Los Angeles. For indirect connections in Canada we added 2.5 hours of travel time to reflect the availability of a range of airports that could be used for connections. In addition, we also considered road and rail alternatives to destinations within 800 kilometres of Toronto to capture the possibility that some passengers would use these modes of transport as an alternative to flying. We can illustrate the what-if scenario with the following example: passengers travelling on a direct flight from Toronto to London, UK take about 7 hours. In the what-if scenario the travel time increases by just less than three hours, as passengers would have to fly via New York. As a result, a small proportion of passengers would choose not to take the trip as the increase in travel time implies How do we quantify Toronto Pearson s contribution to economic value?

28 22 Frontier Economics February 2014 that the trip is not worthwhile. It is the impact of this reduction in passengers that measures the economic value of a direct connection to London, UK provided by Toronto Pearson. In addition to the reduction in passengers in the what-if scenario, there may also be loss of productivity for the remaining passengers who must spend more time on essential business travel. However, we do not attempt to measure this effect as it requires a number of assumptions on the effect of increased travel time on economic output. This can be considered a conservative assumption. 3.2 Values for key assumptions General assumptions To apply the key relationships outlined in section 2.3, we have quantified these relationships. We have undertaken an extensive literature review, including academic papers, industry research and Canadian as well as other government reports. This section provides an overview of the key values we have chosen for different assumptions. For more detail on the literature we have reviewed, see Appendix 1. All of the assumptions we made are based on the best available evidence and we chose conservative values in all cases. We acknowledge that the evidence base for some of the assumptions is still evolving, and therefore changes in the assumptions may be required in the future. We have attempted to show all of our assumptions in an open and transparent way. Business passengers To estimate the economic value facilitated by Toronto Pearson we need to distinguish different passenger types. Table 3 shows that we have assumed 40 per cent business passengers, based on survey data provided by Toronto Pearson. As detailed information on the split of Canadian and foreign passengers on each route is not available, we have used an aggregate figure from Statistics Canada that is applied to all routes. How do we quantify Toronto Pearson s contribution to economic value?

29 February 2014 Frontier Economics 23 Table 3. Assumptions on passenger types Parameter Assumed value Rationale / Source Business passengers 40 per cent Based on Toronto Pearson survey data Proportion of Canadian/ non-canadians on each route 70 per cent Canadian / 30 per cent non- Canadian Based on Statistics Canada this is an aggregate figure for all routes. Impact of connectivity on demand Table 4 provides the assumptions we made to quantify Key Relationship 2. If only indirect flights are available, passenger demand would drop as a response to the increase in travel time. First, we calculated the increase in travel time based on the additional distance travelled and added two hours of layover time at the connecting airport. Second, we monetized the additional travel time by applying a value of time to the additional journey time. This approach is commonly used in land transport evaluation. For business travellers, we assumed a value of time of $75 per hour and for leisure travellers we assumed a value of $22.50 per hour. These are based on average wage rates as shown in Table 4. We further assumed that there would be no change in ticket prices between direct and indirect routes. This assumption was informed by an analysis of price data from Sabre that shows no difference in average ticket prices for indirect and direct flights on the same route. Finally, we used price elasticities of demand to estimate the change in demand as a result of the price increasing due to an increase in travel time. We distinguish different price elasticities for different countries, based on a study by IATA (2007). How do we quantify Toronto Pearson s contribution to economic value?

30 24 Frontier Economics February 2014 Table 4. Assumptions on Key Relationship 2 Parameter Assumed value Rationale / Source Flight speed 500mph during flight, 250mph for takeoff/landing Based on industry standards. Average airport connecting time Travel Time Value Business Travellers Travel Time Value Leisure and VFR (visiting friends and relatives) 2 hours Based on a conservative estimate of the minimum connection time. $75 per hour Double the average wage rate of management occupations (Statistics Canada Table Labour force survey estimates (LFS), wages of employees by type of work) $22.50 per hour Based on average wage (Statistics Canada Table Labour force survey estimates (LFS), wages of employees by type of work) Price Increase for direct v. Indirect Routing Zero Based on data from Sabre on fares which revealed that there is no price difference between direct and indirect flights on the same route from/to Toronto Pearson Price elasticities Transatlantic: Transpacific: Based on IATA (2007) Intra America (including of North and South America): Relationship between connectivity and trade, FDI and tourism spending Table 5 presents the assumptions for Key Relationship 3. A change in the number of business passengers leads to a change in trade and FDI. We acknowledge that these two assumptions are the most difficult to evidence, as the literature focuses on qualitative evidence rather than quantitative data. We considered a range of sources and also analysed flights and trade and FDI in Ontario. We selected 0.3 as the elasticity for both trade and FDI, as we consider this to be at the conservative end of the scale. We have distinguished these elasticities for air travel between different countries, because the relationship between face-to-face meetings and trade and FDI is unlikely to be the same between Ontario and the US and other Canadian How do we quantify Toronto Pearson s contribution to economic value?

31 February 2014 Frontier Economics 25 provinces as it is with the rest of the world. Face-to-face meetings are likely to play a bigger role in overcoming trade barriers between economies that are more dissimilar. The most common trade barriers include: Product market regulation A range of different types of regulation (for example, product standards, safety regulation, etc.) can inhibit trade and FDI across borders. Tariffs and quotas, local content requirements Formal trade barriers such as tariffs also reduce the likelihood of trade. Exchange rate The risk of changes in the exchange rate can pose a significant barrier to trade and FDI as exchange rate volatility can increase the spread of potential returns. Cultural differences Language differences and different business cultures can impede business relationships across cultures as it is more difficult to build trust. Business travel is one way to reduce or overcome some of these barriers, as faceto-face meetings enable a better understanding of local product market regulation and formal trade barriers. Face-to-face meetings are also one of the key ways to build trust across cultures. Trade barriers between Ontario and the US are almost certainly lower than the trade barriers between Ontario and the rest of the world. This is because cultural differences are much smaller (for example, common language), formal trade barriers have been removed by NAFTA, and product marker regulations are more likely to be aligned. As a result, we think that faceto-face meetings facilitated by air travel in the US have a smaller impact on trade and FDI. Trade barriers between Ontario and other provinces in Canada are likely to be even lower, as there is no exchange rate risk and product market regulation is even more likely to be harmonized. We believe that similar reasoning applies to the relationship between air travel and FDI. Tourism spending per person is based on Statistics Canada and the Ontario Ministry of Tourism, Culture and Sport, and is distinguished by country. How do we quantify Toronto Pearson s contribution to economic value?

32 26 Frontier Economics February 2014 Table 5. Assumptions on Key Relationship 3 Parameter Assumed value Rationale / Source Business travel elasticity of trade - change in trade as a result of a 1 per cent drop in business travel 0.3 For travel between Ontario and international countries except the US. Based on literature review, see Appendix 1 for more detail 0.2 For travel between Ontario and the US. 0.1 For travel between Ontario and other provinces in Canada. Business travel elasticity of FDI - Change in FDI as a result of a 1 per cent drop in business travel. 0.3 For travel between Ontario and international countries except the US. Based on literature review, see Appendix 1 for more detail 0.2 For travel between Ontario and the US. 0.1 For travel between Ontario and other provinces in Canada. Tourism spending $460 - $1,280 $440 - $1,990 Average outward tourist spend per visit by Ontarians, depending on country visited Average inward tourist spend in Ontario per visit depending on country of origin Relationship between trade & FDI and long-run GDP Table 6 provides the assumptions underpinning Key Relationship 4. Trade and FDI have a positive impact on GDP. The relationship between trade and GDP is a well-established research topic and the value we use to relate openness to GDP is based on OECD research quoted by the Government of Canada. We have used a lower value for interprovincial trade as the impact on productivity is likely to be lower. For example, Therrien and Hanel (2012) provide evidence supporting the idea that the productivity gains from trade are stronger with trade to foreign markets compared to the domestic market. They find that Canadian firms who export to foreign markets have higher labour productivity. How do we quantify Toronto Pearson s contribution to economic value?

33 February 2014 Frontier Economics 27 It is more difficult to obtain evidence on the relationship between outbound and inbound FDI and GDP so our assumptions are based on the best available evidence. This includes research by the German Institute for Economics Research on outward FDI and economic growth and the Korea Institute for International Economic Policy on the impact of inward FDI in Ireland. Our assumption on Ontario s GDP per job is based on the same ratio that is used by the federal government in Free Trade Agreement impact assessments. Table 6. Assumptions on Key Relationship 4 Parameter Assumed value Rationale / Source Openness elasticity of GDP (Openness is defined as trade/gdp) Outbound FDI elasticity of GDP Inbound FDI elasticity of GDP 0.44 For international trade, based on OECD study quoted by Canada s State of Trade and Investment Update (2012) by Foreign Affairs and Trade International 0.2 For interprovincial trade, see Appendix 1 for more detail 0.19 Based on literature review, see Appendix 1 for more detail 0.24 Based on literature review, see Appendix 1 for more detail GDP per job $150,000 Based on Canadian government figures for free trade agreement impact assessments Assumptions specific to the 2030 analysis There are a number of assumptions that are specific to the analysis of projected future economic value. Table 7 summarizes the values and sources we have used for the analysis in First, we have used GDP projections by HSBC Bank for each country. We have used the HSBC source as it provides projections for a large number of countries up until There are few alternative sources that provide projections for so many counties over such a long time period. To ensure the robustness of the HSBC projections we have cross-checked them against projections by international institutions such as the International Monetary Fund. Appendix 4 provides a sensitivity test on the assumption about US and Ontario growth. Second, we assume that ticket prices do not increase in real terms. Our research indicates that oil prices are expected to fall over the medium-term (as a result of the ongoing global recession), so we have used zero real price increases as a conservative assumption. This assumes that nominal How do we quantify Toronto Pearson s contribution to economic value?

34 28 Frontier Economics February 2014 prices will increase in line with inflation, on average. Third, we assume that aircraft size is expected to increase on average at 1 per cent per year. Industry projections around this figure vary and we consider 1 per cent to be a conservative assumption. As passenger demand increases in the future, the route network can change in two ways: new direct connections become viable and the frequency of connections increases. If the demand on an indirect route from Toronto Pearson grows sufficiently to justify a new direct connection, we assumed that this direct connection would be provided by We then estimated an increase in passengers due to the reduced travel time. If demand increases on an existing direct route, frequency of flights can also increase. We used frequency elasticities to estimate additional demand generated by more frequent connections. We used two different frequency elasticities depending on the initial frequency, as there are likely to be diminishing returns to frequency. For example, increasing frequency from three times a week to daily is likely to have a larger impact than increasing frequency from once to twice daily. Our assumptions on income elasticities are based on IATA (2007). We distinguish different income elasticities for countries with different levels of income. Countries with high levels of income are likely to have lower income elasticities than countries with lower levels of income. How do we quantify Toronto Pearson s contribution to economic value?

35 February 2014 Frontier Economics 29 Table 7. Overview of key assumptions and selected values Parameter Assumed value Rationale / Source Annual GDP forecast by country Annual real ticket price change 0.4 per cent per cent depending on country Zero change HSBC (2012) growth forecasts, crosschecked against IMF forecasts The key input is oil prices (accounts for 34 per cent of total airline costs according to IATA), oil price forecast to decrease so we used zero as a conservative assumption. This is in line with Airbus assumption (Airbus, 2012). This assumes nominal prices will increase in line with inflation. Annual technology growth in aircraft size 1 per cent We expect aircraft size to grow and have used 1 per cent as a conservative assumption. Frequency elasticity Income elasticities For low-frequency countries: 0.8 For high-frequency countries: 0.6 Various between 1.22 and 2.03 The frequency elasticities are based on a literature review. Frequency cut-off (flights per day based on 2011 data): 0.5 Based on IATA (2007) To estimate the size of the North American connecting passenger market that could use Toronto Pearson airport as a substitute, we applied the following conditions: a) Connecting passengers who start and end their journey in the US who cannot connect via Toronto Pearson; b) To be a potential Toronto Pearson connecting passenger, the travel distance via Toronto Pearson must be less than the travel distance of any rival US hub airport that is active in the market; or c) If the travel distance via Toronto Pearson is longer than all the rival hubs that are active in the market, then the travel distance via Toronto Pearson must be within 10 per cent of the shortest travel distance. How do we quantify Toronto Pearson s contribution to economic value?

36 30 Frontier Economics February 2014 d) For routes that only have connections via one hub airport, the condition is that travel time is less than 10 per cent longer than the existing connection. We consider these assumptions to be reasonable, as Toronto Pearson is clearly not a substitute for all connecting passengers. For example, it would not be reasonable to assume that journeys from the western US to Asia could connect via Toronto Pearson. How do we quantify Toronto Pearson s contribution to economic value?

37 February 2014 Frontier Economics 31 4 What are our results? 4.1 Economic value facilitated by Toronto Pearson today Based on the approach described in section 2 and the assumptions described in section 3, the economic value to Ontario facilitated by Toronto Pearson today equates to 3.6 per cent of Ontario s GDP, equivalent to $22.3 billion. This is the value of having direct as opposed to indirect air connections from Toronto Pearson. Based on this estimate, Toronto Pearson currently facilitates 153,000 jobs within Ontario. If Toronto Pearson only provided indirect connections instead of direct connections, 153,000 jobs would be lost. This is comparable to the total employment in the retail or service services sectors in the City of Toronto as indicated by the 2012 employment survey (City of Toronto, 2012). Approximately 55 per cent of the results can be attributed to connections within Canada and to the US, and 45 per cent can be attributed to connections with other countries. GDP and jobs are driven by trade and FDI that is facilitated by connectivity to and from Toronto Pearson, as our results show: Exports: $9.7 billion exports, which is equivalent to 5.2 per cent of Ontario s total exports. Approximately, 65 per cent of those exports are to the US, 20 per cent to other international countries and 15 per cent to other provinces in Canada. Imports: $12.6 billion imports, which represents 4.8 per cent of Ontario s total imports. Approximately, 54 per cent of those exports are to the US, 33 per cent to other international countries and 13 per cent to other provinces in Canada. FDI: $40.3 billion of the total inward and outward FDI stock, which is close to 5 per cent of the Ontario s total FDI stock. GDP and jobs are also influenced by tourism spending. Tourism spending facilitated by Toronto Pearson has a net negative impact on GDP, as spending by Ontarians abroad is greater than spending by visitors in Ontario. The tourism spending facilitated by Toronto Pearson can be summarized as follows: $310 million of tourism spending by visitors in Ontario, which is equivalent to 4.3 per cent of total tourism spending in Ontario; and What are our results?

38 32 Frontier Economics February 2014 $807 million of tourism spending by Ontarians abroad, which is equivalent to 4.3 per cent of total tourism spending by Ontarians abroad. This is because Ontario has a negative tourism spending balance. In 2010, visitor spending in Ontario totalled $7.3 billion whereas spending by Ontarians abroad totalled $17.9 billion (Ontario Ministry of Tourism, Culture and Sport, 2010). Table 8 below shows a breakdown of our results for today. Table 8. Economic value facilitated by Toronto Pearson today $ million Exports 9,686 Imports 12,623 Total trade 22,300 GDP facilitated by trade 9,253 Outward FDI 20,672 Inward FDI 19,632 Total FDI 40,300 GDP facilitated by FDI 13,960 Tourism exports 310 Tourism imports 807 Net tourism GDP facilitated by tourism Total GDP facilitated 22,700 % of Ontario GDP 3.6% Jobs 153,000 Source: Frontier analysis, numbers may not add up due to rounding We have cross-checked our results against two econometric studies. The International Air Transport Association (IATA) (2007) estimates that a 10 per cent rise in connectivity relative to a country s GDP will increase What are our results?

39 February 2014 Frontier Economics 33 labour productivity levels by 0.07 per cent. Applying the IATA study results to our what-if scenario, IATA would suggest a much bigger impact of air travel on GDP than we have estimated. The World Travel and Tourism Council (WTTC) (2011) estimates that for each 1 per cent drop in business travel, GDP decreases by 0.12 per cent. Our results are in the same ballpark, as a 1 per cent drop in business travel would lead to a per cent decrease in GDP based on our results. Our cross-check implies that our results are conservative and reasonable. Recall, the above results are a quantification of the economic value facilitated by the airport as a result of air travel. The economic value generated by the airport as a result of employment is quantified by earlier, traditional economic modelling conducted by HRD/HLB Decision Economics on behalf of the Airport. Combined results today Combining our approach with the results of the direct, indirect and induced analysis, the total value facilitated by Toronto Pearson today is: 277,000 jobs or 4.2 per cent of total Ontario employment; and $35.4 billion or 5.6 per cent of Ontario GDP. 4.3 Economic value facilitated by Toronto Pearson in Passenger volumes in 2030 Our baseline projections of travel demand at Toronto Pearson (based on income growth only) suggest that the airport will handle 60 million passengers in This is equivalent to average growth of 3 per cent per year. Figure 8 and Figure 9 illustrate that growth is not evenly distributed across the world. Travel to and from high growth countries such as Brazil, India and China will increase faster than travel to and from North America and Europe. The baseline scenario only takes into account income growth, and it is assumed that Toronto Pearson s market share of the North American connecting passenger market remains unchanged. What are our results?

40 34 Frontier Economics February 2014 Figure 8. Passenger volumes to different continents in m pax 4.2m pax 1.7m pax 0.5m pax 2.5m pax Figure 9. Passenger volumes to different continents in m pax 7m pax 4m pax 1m pax 7m pax Results in 2030 Our results suggest that Toronto Pearson will facilitate economic value to Ontario equal to 4.2 per cent of Ontario s GDP in 2030, equivalent to $37.0 billion. The result is slightly bigger than for 2012, as demand for travel grows faster than Ontario s GDP growth as it is partly based on GDP growth in high growth economies. What are our results?

41 February 2014 Frontier Economics 35 We estimate that by 2030 that Toronto Pearson will facilitate 247,000 jobs in Ontario. This is equivalent to the combined employment of the manufacturing and retail sectors in the City of Toronto s in 2012 (City of Toronto, 2012). It is estimated that 49 per cent of this result can be attributed to international connections (excluding the US), which is a slight increase from 45 per cent in This is because GDP growth in Canada and the US is expected to be relatively low compared to some of the emerging markets, such as Brazil, India and China. Our results for the trade and FDI figures, that underpin the economic value results for 2030, are: Exports: $15.5 billion of exports; Imports: $21.8 billion of imports; and FDI: $67.5 billion of FDI stock. In 2030 the impact of tourism spending is still negative with the amount facilitated by Toronto Pearson estimated to be: $431 million of spending by visitors in Ontario; and $1,103 million of spending by Ontarians abroad. Table 9 below shows a breakdown of our results for What are our results?

42 36 Frontier Economics February 2014 Table 9. Economic value facilitated by Toronto Pearson in 2030 $ million Exports 15,501 Imports 21,846 Total trade 37,347 GDP facilitated by trade 15,428 Outward FDI 38,696 Inward FDI 28,837 Total FDI 37,347 GDP facilitated by FDI 23,302 Tourism exports 431 Tourism imports 1,103 Net tourism -671 GDP facilitated by tourism -671 Total GDP facilitated 37,058 % of Ontario GDP 4.12% Jobs 247,056 Source: Frontier analysis, numbers may not add up due to rounding Combined results in 2030 Combining our approach with the results of the direct, indirect and induced analysis, the total value facilitated by Toronto Pearson today is: 457,000 jobs; and $58.6 billion or 6.6 per cent of total Ontario GDP. What are our results?

43 February 2014 Frontier Economics Size of the opportunity Our baseline results for 2030 represent a business as usual projection of traffic at Toronto Pearson, assuming that it maintains its market share of connecting passengers relative to other North American hub airports. Clearly in a dynamic world this cannot simply be relied upon to happen. There are both threats to this position if other hub airports seek to win market share from Toronto Pearson, and opportunities if Toronto Pearson itself is successful in increasing its share. To illustrate the economic value associated with these competitive uncertainties we created an additional scenario in which we estimated the additional economic value that could be facilitated by Toronto Pearson if it increased its market share in the North American connecting passenger market by We estimate that by 2030 there will be 131 million passengers connecting via one of the ten North American hubs that could consider Toronto Pearson as a substitute. This market estimation is based on the two factors described in section 2.5. The results are based purely on the routing of passengers. They therefore include a number of Star Alliance hubs as the structure of the airline market may be changed in The market size of 131 million can be broken down as follows: 82 million connecting passengers are flying on routes that Toronto Pearson is already connected to; and 49 million connecting passengers are flying on routes that Toronto Pearson is not connected to. This implies that there are considerable growth opportunities for Toronto Pearson as a hub airport. As an illustrative example, we estimated the additional economic value if Toronto Pearson attracted an additional 10 per cent connecting passengers that use a rival hub in the US and originate in North America (equivalent to 7.9 million passengers). In this case Toronto Pearson would facilitate an additional 0.4 percentage points of Ontario s GDP and an additional 17,000 jobs. Adding the results from the direct, indirect and induced analysis undertaken by Toronto Pearson for this scenario, the total economic value facilitated by Toronto Pearson under this scenario increases by 21,000 jobs. This scenario illustrates that the success of Toronto Pearson as a hub airport has direct implications for Ontario s economy, and visa-versa. What are our results?

44 38 Frontier Economics February Factors that influence success This study does not seek to determine which competitive outcome is most likely. Rather, we have reviewed key lessons from three larger hub airports that are located in similar sized economies, and identified the following key success factors: a) Deregulated domestic and liberalized international air markets are key factors and provide the best opportunities for significant growth of a hub airport. b) Reliance on single dominant hub air carrier is good for the hub airport provided the commercial interests of the air carrier and the hub airport aligned, but risky if those interests change. c) The ability to diversify across carriers in liberalized markets is an important mechanism for sustainable hub airport growth. d) In a competitive hub market cost and quality competitiveness are essential. All of these factors should be considered to ensure that Toronto Pearson competes effectively in the market for connecting passengers. What are our results?

45 February 2014 Frontier Economics 39 5 Conclusion Our approach The objective of this study was to quantify the economic benefits to Ontario from air travel and air connectivity facilitated by Toronto Pearson today and in the future. We developed a methodology that allowed us to estimate the economic value facilitated by air travel. This approach is different from the most common studies of economic value, which tend to focus on the airport as an employer and determine the level of direct, indirect and induced employment. As noted, this traditional type of economic analysis has been completed by Toronto Pearson, and when considered together this the results of this study, paint a more complete picture of the total economic value of Toronto Pearson. In this analysis, our approach examines the value, in GDP and employment terms, facilitated by the activity of air connectivity. Our results can therefore be added to those from the direct, indirect and induced analysis. We acknowledge the two-way relationship between economic value and connectivity. We think that the relationship is best characterized by a virtuous circle. We acknowledge that there are a range of other factors that influence both connectivity and economic value. Our approach is based on breaking the relationship between connectivity and economic down into a number of steps. For each of the key relationships in our approach, we undertook an extensive literature review to develop conservative assumptions. We appreciate that the most appropriate assumptions for this analysis may change. Assumptions can be updated but we think that we have developed a sound framework to estimate the contribution of Toronto Pearson to the economy. Our results Overall, this study demonstrates that Toronto Pearson makes an important contribution to Ontario s economy as it facilitates a substantial number of jobs beyond direct and indirect employment. Our results show that Toronto Pearson facilitates economic value equivalent to: 3.6 per cent of GDP or 153,000 jobs in 2012; and 4.1 per cent of GDP or 247,000 jobs in the baseline scenario for We consider our results to be conservative, as they are similar or lower than those implied by previous studies by IATA and the WTTC. There is also a substantial opportunity to facilitate additional economic value in the future if Toronto Pearson can attract additional connecting passengers from Conclusion

46 40 Frontier Economics February 2014 other North American hub airports. By 2030, 131 million passengers that connect via other North American hubs could potentially to consider Toronto Pearson as a substitute airport. Combined results summary Combining our results with those of the direct, indirect and induced analysis undertaken by Toronto Pearson, the total economic value facilitated by Toronto Pearson is estimated to be: Today: 277,000 jobs or 5.6 per cent of Ontario GDP In the year 2030: 457,000 jobs or 6.6 per cent of Ontario GDP Policy implications This study demonstrates the important role that Toronto Pearson plays in facilitating strong business relationships with countries around the world. Many of the policies we reviewed imply that Canada s future economic prosperity partly depends on its ability to diversify trade links. Stronger trade and FDI relationships with fast-growing economies such as Brazil, India and China require face-to-face meetings between businesses from both sides. Toronto Pearson can play an important role in facilitating these relationships. Conclusion

47 February 2014 Frontier Economics 41 Appendix 1: Methodology Economic value today Section 2 provides an overview of our approach and section 3 provides the key assumptions that we had to make. This Appendix provides more detail on our methodology and the literature we reviewed to inform our assumptions. It is structured as follows: Overview of key steps in the methodology; Key relationship 2 detailed approach and evidence to underpin assumptions; Key relationship 3 number of passengers and trade/fdi detailed approach and evidence to underpin assumptions; and Key relationship 3 number of passengers and tourism spending detailed approach and evidence to underpin assumptions; Key relationship 4 trade and productivity: detailed approach and evidence to underpin assumptions; and Key relationship 4 FDI and productivity: detailed approach and evidence to underpin assumptions. The focus of this Appendix is on the method for calculating the economic value facilitated by Toronto Pearson today. Details of our method for determining the future value are in Appendix 2. Overview of methodology Our methodology follows the steps illustrated in Figure 10. Our starting point is the number of travellers on direct connections from Toronto Pearson to each country. The analysis is undertaken on a country rather than a city level as trade and FDI data is only provided at the country level. We determine the additional travel time for the indirect connection by considering the additional distance flown and connecting time at the airport. Distance is determined using a great circle route mapping tool. Switching from a direct to an indirect flight leads to a greater percentage increase in travel time for destinations that are closer to Toronto. For example, adding 3 hours of travel time to a 5 hour journey represents a bigger percentage increase than adding 3 hours of travel time to a 12 hour journey. As a result, the impact of an indirect flight is greater for destinations that are closer. Appendix 1: Methodology Economic value today

48 42 Frontier Economics February 2014 We convert the additional travel time into a monetary value by applying the value of time derived from hourly wage rates. The change in the price is then related to the price of the original ticket to determine the percentage change in the ticket price. Using a price elasticity of demand, we can determine the change in total demand for travel to each country. We relate the percentage drop in passengers to a change in trade, FDI and tourism spending by using the elasticities discussed below. Changes in trade, FDI and tourism spending can then be related to the impact on GDP and employment. Figure 10. Overview of steps to calculate economic value facilitated today Economic input data Table 10 provides an overview of our input data. Ontario trade data by country is available from the Conference Board of Canada. FDI by country is only available for Canada, so we have used 60 per cent of the FDI stock for Canada as an estimate for Ontario FDI data. This is based on Liang Liang (2008). There is no data on interprovincial investment available. Appendix 4 provides a sensitivity test that considers the impact on the results if an estimate for interprovincial investment in included. The table shows the input data for those countries with direct connections. This covers approximately 84 per cent and 74 Appendix 1: Methodology Economic value today

49 February 2014 Frontier Economics 43 per cent of total trade and FDI stock respectively. All our input data is currently based on Table 10. Overview of economic input data - Trade and FDI links between Ontario and each geography Connected countries/state/provinces only CAN$m (2012) Geography Exports per year Imports per year Outward FDI stock Inward FDI stock International (excl. US) 31,788 97, , ,109 US 124, , , ,994 Canada (excl. Ontario) 45,795 50,331 * * Total Connected 201, , , ,103 * Data for inter-provincial FDI is not available Key relationship 2: Travel time and passenger numbers A change in travel time impacts on the demand for travel as some passengers will choose not to travel. The relationship can be seen in the following formula: ((Additional travel time * Value of time)/ Ticket price) * Price elasticity of demand = Change in number of passengers The change in travel time is calculated on the basis of additional travel distance multiplied with average speed. We distinguish speed for take-off and landing from the speed during the flight and use the following assumptions: a) average speed during flight: 500 mph; and b) average speed for take-off and landing: 250mph. Distance is calculated on the basis of great circle routes. We add additional connecting time at the airport. Our results are based on an assumption of 2 hours of connecting time. This implies that passengers would need 2 hours between landing and take-off for their connecting flights. We consider this assumption to be conservative, as this is likely to be close to the minimum rather Appendix 1: Methodology Economic value today

50 44 Frontier Economics February 2014 than the average connecting time. The total additional connecting time is therefore equal to the additional flight time plus the connecting time. Our results show that the additional travel time varies from 2.4 hours to 3.5 hours. We monetize the value of time by using wage rates from Statistics Canada. There are a number of ways to put a value on travel time including stated preference 1 and revealed preference surveys. We have chosen to use wage rates as this is the most common approach for valuing in work time (see for example, UK Department for Transport, 2012). We use a similar approach for non-work time to ensure consistency. For business travellers our value of time is $75 which is informed by the wage rate of management occupations (Statistics Canada table ). We double the average wage rate as it is likely that international business travel is undertaken by more senior management. An hourly wage rate of $75 is equivalent to an annual pre-tax salary of $135,000. This is equivalent to the average income of the top 20 per cent (Human Resources and Skills Development Canada, 2013). We adjust wage rates for other countries using Purchasing Power Parity. For non-business passengers, we use $23 as the value of time which is equal to the average wage rate (Statistics Canada table ). Ticket prices are based on Sabre data. We reviewed a number of studies on the price elasticity of demand. The most disaggregated values are available from IATA (2007). Separate elasticities are provided for transatlantic, transpacific and intra-north America and values range from to Key relationship 3: Face-to-face meetings and trade and FDI Our analysis of the value of Toronto Pearson s connectivity requires us to make an assumption on the relationship between face-to-face meetings, trade and FDI. Face-to-face meetings increase the likelihood of closing business deals which has a positive impact on trade and FDI. Face-to-face meetings are also important to manage increasingly globalized supply chains. This relationship is supported by qualitative literature, but it is difficult to quantify the relationship. Concept Despite the rise of technologies such as videoconferencing, face-to-face meetings still play an important role in developing and maintaining successful business 1 Stated preference is based on what consumer s say their preferences are, whereas revealed preference measures consumers preferences based on their actual purchasing behaviour. For example, a passenger may say they would pay $100 to reduce their travel time by an hour (their stated preference), however, when buying a ticket they reveal they would only be willing to pay $70 for a flight with a travel time of one hour less (their revealed preference). Appendix 1: Methodology Economic value today

51 February 2014 Frontier Economics 45 relationships. Most relationships are built on trust between business partners and face-to-face meetings are still the most effective way to build and establish trust. In addition, in-person meetings can be used to inspect production sites and meet larger teams which cannot be done through videoconferencing. The relationship between face-to-face meetings and trade and FDI is unlikely to be the same for all of Ontario s business relationships. We think that the relationship is likely to differ for transactions between Ontario and other provinces, the US and other international countries. This is because face-to-face meetings are likely to play a bigger role in overcoming trade and FDI barriers between economies that are more dissimilar. The most common barriers include: a) Product market regulation a range of different types of regulation (product standards, safety regulation, etc.) can inhibit trade and FDI across borders; b) Tariffs and quotas, local content requirements formal trade barriers such as tariffs also reduce the likelihood of trade; c) Exchange rate the risk of changes in the exchange rate can pose a significant barrier to trade and FDI, as exchange rate volatility can increase the spread of potential returns; and d) Cultural differences language differences and different business cultures can impede business relationships across cultures as it is more difficult to build trust. Business travel can reduce or overcome some of these barriers, as face-to-face meetings enable a better understanding of local product market regulation and formal trade barriers. Face-to-face meetings are also one of the key ways to build trust across cultures. These barriers are much lower when considering trade and FDI between Ontario and the US compared to international transactions. This is because cultural differences are much smaller (for example, common language), formal trade barriers have been removed by NAFTA and product marker regulations are more likely to be aligned. Trade barriers between Ontario and other provinces in Canada are likely to be even lower as there is no exchange rate risk and product market regulation is even more likely to be harmonized. Figure 11 illustrates this concept. Appendix 1: Methodology Economic value today

52 46 Frontier Economics February 2014 Figure 11. Illustration of differences in trade barriers Review of evidence There is a range of qualitative, survey-based evidence that suggests face-to-face meetings play an important role in business relationships. We discuss these below. The importance of in-person meetings for trade facilitation is also supported by the existence of trade missions. For example, the Canada Trade Commissioner Service organizes a number of trade missions to different countries each year. These trade missions provide access to foreign markets, including networking opportunities, first-hand experiences and opportunities to initiate business relationships (Government of Canada, 2012). The World Travel and Tourism Council (2012) finds that sales conversion rates with an in-person meeting are 50 per cent, compared to conversion rates of 31 per cent without an in-person meeting. The results are based on surveys in Brazil, China, Germany, the UK and the USA and are consistent across these countries. In 2011, the WTTC conducted another survey on the importance of business travel and found that 28 per cent of existing business could be lost without face-to-face meetings and sales conversion rates are estimated to be per cent higher with face-to-face meetings. This is further supported by a range of qualitative studies. Frankel (1997) illustrates the importance of face-to-face meetings as follows: Consider a kind of export important to the United States: high-tech capital goods. To begin sales in a foreign country may involve many trips by engineers, marketing people, Appendix 1: Methodology Economic value today

53 February 2014 Frontier Economics 47 higher ranking executives to clinch a deal, and technical support staff to help install the equipment or to service it when it malfunctions. A survey by the UK Institute of Directors (2008) asked about the impact on businesses if the amount of business travel by air was significantly curtailed. 30 per cent of respondents said that there would be significant adverse effects while 44 per cent indicated small adverse effects. Poole (2010) finds that business travel to the United States by non-resident, non-citizens has a positive impact on export margins. Aradhyula & Tronstad (2003) find that their results support the hypothesis that both formal business exploration and casual exposure to cross-border business opportunities have a positive impact on trade. Strauss-Kahn & Vives (2005) find that headquarters relocate to metropolitan areas with good airport facilities, low corporate taxes, low average wages, high levels of business services, and an agglomeration of headquarters in the same sector of activity. The effects are quantitatively significant (for airport facilities in particular). The City of London (2008) surveyed finance and insurance companies on the importance of air travel. They found that 69 per cent of firms consider air travel to be critical for business travel by their staff, with only 2 per cent viewing it as not important. Boeh & Beamish (2012) demonstrate that travel time between different locations has a significant predictive power in firm governance and location decisions, as travel time could otherwise be employed for productive purposes. Napier University (2004) finds that [ ] air transport per se is not a necessary condition, but what is important are: the extent to which that area is plugged directly into other major international hubs - availability and efficiency of routes (direct, hubbed); costs and the level of competition in global transport market, and; perceived and actual interchange efficiencies. This is a key consideration in the level of foreign investment into an area and is most important for firms with international trading or contacts such as, hightech firms, financial services and pharmaceutical firms. Survey-based evidence also suggests that the importance of face-to-face meetings depends on differences between business partners. Evidence from the World Travel and Tourism Council (WTTC) and the Harvard Business Review indicates Appendix 1: Methodology Economic value today

54 48 Frontier Economics February 2014 that international business travel plays a more improtant role in generating and sustaining business than domestic travel. The WTTC (2012) found that: One extra dollar invested in international business travel would generate on average US$17 in trade; and One extra dollar invested in domestic US business travel by companies results in an increase in revenue of US$9.50. This implies that the return on investment for international travel is roughly half of domestic travel. Figure 12 illustrates the difference in the return on investment. Figure 12. Return on investment Source: World Travel and Tourism Council, 2011 Similarly the Harvard Business Review (2009) confirms the role of face-to-face meetings in facilitating and sustaining business deals and also provides some evidence for the specific role of business travel to overcome barriers to trade across different cultures. For example, it found that: a) 93 per cent of survey respondents agreed that in-person meetings are helpful in negotiating with people from different language and cultural backgrounds; b) One survey respondent said that Communicating with our Chinese partners is enough of a challenge without face-to-face, because it is very difficult to explain a difference in perspective without body language ; and c) A number of respondents described the need to work with clients in their own environment to get a full picture of the challenges and opportunities they face. There is a small amount of literature that supports this view. Appendix 1: Methodology Economic value today

55 February 2014 Frontier Economics 49 Cristea (2011) found robust evidence that the demand for business-class air travel is directly related to volume and composition of exports in differentiated products. The paper finds that trade in R&D intensive manufactures and goods facing contractual frictions is most dependent on face-to-face meetings. Contractual frictions are more likely to occur with higher trade barriers so this would support a lower elasticity for trade between Ontario and the US/Canada compared to the rest of the world. Poole (2010) finds that business travel for the purpose of communication acts as an input to international trade. The effect is stronger for differentiated products and for higher-skilled travellers, reflecting the information intensive nature of differentiated products. The effect is driven by travel from non-english speaking countries, for which communication with the U.S. by other means may be less effective. The findings therefore also confirm our view that business travel plays a bigger role when connecting firms from different cultural backgrounds. Selection of assumption values Quantitative evidence on the relationship between face-to-face meetings and trade/fdi is difficult to obtain. This is because it is difficult to pick out the impact of face-to-face meetings from the other factors that influence trade and FDI. Even though we know that a simple regression between flights and trade/fdi will not provide sufficient evidence for the quantitative relationship, we have performed this analysis for Toronto Pearson to establish an upper bound. The regression coefficient will be overstated as the regression omits other explanatory variables that influence trade and FDI. However, we can interpret the coefficient as the upper value elasticity, as introducing other variables would always reduce the coefficient. Figure 13 provides the results for outbound flights from Toronto Pearson and Ontario exports. The coefficient is 1.153, which implies that a 1 per cent increase in flights leads to a 1.15 per cent increase in exports. We consider this to be the upper bound of the relationship and acknowledge the issues of omitted variable bias and endogeneity. As a result, this analysis is only intended to provide additional evidence. Appendix 1: Methodology Economic value today

56 50 Frontier Economics February 2014 Figure 13. Outbound flights versus exports Note: Outbound flights are estimated based on the number of outbound passengers from Toronto Pearson airport and an assumption about aircraft size for long haul and short haul flights. The World Travel and Tourism Council (WTTC) performed a similar analysis for a range of countries as shown in Figure 14. The figure shows the correlation coefficient as well as the results of the Granger test for causality. The figure shows that the correlations vary between 0.17 for outbound business travel from Italy to 0.98 for outbound business travel from Brazil. Appendix 1: Methodology Economic value today

57 February 2014 Frontier Economics 51 Figure 14. Trade and business travel by country Source: WTTC, 2012 Figure 15 provides the same analysis for inbound flights and inward FDI. The coefficient suggests that a 1 per cent increase in flights leads to a 0.6 per cent increase in FDI. Again, we acknowledge issues of omitted variable bias and endogeneity and consider this analysis to provide an upper bound only. Appendix 1: Methodology Economic value today

58 52 Frontier Economics February 2014 Figure 15. Inbound flights versus inward FDI We also consider the FDI differential between connected and unconnected countries as shown in Figure 16. The figure shows that FDI with connected countries is approximately double the FDI with unconnected countries. We acknowledge that the causality between FDI and connections goes both ways. Figure 16. FDI differential between connected and unconnected countries Given the lack of robust quantitative evidence on this relationship, we first consider the elasticity for transactions between Ontario and international countries (excluding the US). Figure 17 and Figure 18 show that we considered a range of values. We conclude that an assumption of 0.3 is reasonable as this Appendix 1: Methodology Economic value today

59 February 2014 Frontier Economics 53 value is at the lower end of the spectrum. So we assume that a 1 per cent increase in face-to-face meetings increases trade and FDI by 0.3 per cent. Our evidence discussed above suggests that the elasticities should be lower for trade/fdi between Ontario and the US and even lower for trade/fdi between Ontario and other provinces as compared to the rest of the world. As there is little evidence on the magnitude of the difference, we consider the following assumptions to be conservative estimates: a) Ontario and rest of the world: 1 per cent increase in face-to-face meetings increases trade and FDI by 0.3 per cent; b) Ontario and US: 1 per cent increase in face-to-face meetings increases trade and FDI by 0.2 per cent; and c) Ontario and other Canadian Provinces: 1 per cent increase in face-to-face meetings increases trade and FDI by 0.1 per cent. These assumptions are broadly consistent with the WTTC findings. Figure 17. Evidence on relationship between face-to-face meetings and trade Appendix 1: Methodology Economic value today

60 54 Frontier Economics February 2014 Figure 18. Evidence on relationship between face-to-face meetings and FDI Key relationship 3: Number of passengers and tourism spending Concept Passengers who travel to and from Ontario will inevitably generate tourism spending regardless of their trip purpose. This suggests that a decrease in the number of passengers travelling to Ontario results in a decrease in inbound total tourism spending (or tourism exports). Likewise, a decrease in the number of outbound passengers from Ontario results in a decrease in outbound tourism spending (or tourism imports). In order to estimate the impact of connectivity on tourism spending we have obtained data on tourism spending per passenger-visit. We then multiply these values by our passenger reduction in the what-if scenario. This provides an estimate of the value of tourism spending facilitated by Toronto Pearson. Review of evidence Evidence on tourism spending on a country by country basis is limited. In general, most evidence is based on tourism surveys. We have reviewed the following sources: Appendix 1: Methodology Economic value today

61 February 2014 Frontier Economics 55 a) Statistics Canada, International Travel 2010 b) Ministry of Tourism, Culture and Sport, The Economic Impact of Tourism in Ontario and its Regions 2010 c) Canadian Tourism Commission, Tourism Snapshot: 2012 Year-in-review d) Ontario Ministry of Tourism, Culture and Sport, Outbound Visits and Spending statistics Spending by non-canadians in Ontario Our assumptions on tourism spending per passenger-visit by country are based on the Statistics Canada International Travel 2010 survey. It provides the most comprehensive country-level data. It provides data on a person s average spending per trip for 14 countries across four continents, as well as data by continent and region. We cross-checked our assumptions with the other sources to ensure they were consistent. Given that data on tourism spending by non-canadians in Ontario was not available for every country, we used either the respective continent and regional values or a geographically similar country where there was missing data. For example, for Taiwan we used China s average spending per person-trip and an Other European average for Albania. Spending by Ontarians abroad Tourism spending by Ontarians travelling to the rest of the world (excluding the US) is based on the Ministry of Tourism, Culture and Sport: The Economic Impact of Tourism in Ontario and its Regions This provides a figure of CAN$1,279 in Due to data limitations we have applied this uniformly to all outbound countries. For the US, we again used data from Statistics Canada International Travel 2010 survey which provides a figure of CAN$555 in Tourism spending in other provinces We use the Ontario Ministry of Tourism, Culture and Sport s visits and spending statistics for our assumption on tourism spending between different provinces. This provides an average tourism spend per visit for Ontarians to other provinces of CAN$461 and by Canadians from other provinces in Ontario of CAN$366, in Table 11 below summaries our assumptions on tourism spending per passengervisit. Appendix 1: Methodology Economic value today

62 56 Frontier Economics February 2014 Table 11. Tourism spending per passenger-visit Direction Location Average tourism spending per passenger visit Outbound (tourism imports) Ontario to Rest of World $1,280 Ontario to the US $550 Inbound (tourism exports) Ontario to Canadian provinces Rest of world (including US) to Ontario Canadian provinces to Ontario $460 $440 - $1,990 $360 Note: These figures are rounded and are in Canadian dollars Key relationship 4: Trade and productivity Concept A large body of academic research investigates the positive impact of trade on productivity at the firm level. At the economy-wide level, there are also some studies which suggest additional trade leads to higher productivity. The key mechanisms by which trade influences productivity can be characterized in three ways: a) Innovation trade is one of the key transmitters of innovation as it exposes companies to a wider range of products and processes in other countries. This applies regardless of whether the partner country is a developed or developing economy. b) Competition as trade increases the market size companies that export or import are faced with more intense competition. Competition puts pressure on companies to be more efficient. This applies to trade with any partner country. c) Economies of scale larger market sizes imply that production processes can benefit from economies of scale. This also applies to trade any partner country. For example, the OECD, (2012) found that: A main channel through which trade increases income is productivity growth. Importing creates competition that forces domestic firms Appendix 1: Methodology Economic value today

63 February 2014 Frontier Economics 57 to become more efficient and provides access to inputs of international calibre; exporting creates incentives for firms to invest in the most modern technologies, scales of production and worker training. The combined effect is to spawn a process of continual resource reallocation, shifting capital and labour into activities with higher productivity. Importantly, the impact of trade on productivity holds for both exports and imports. This is because we are considering the long-term impact on trade on productivity instead of the short-term. In the short-term import substitution can lead to structural changes in the economy that require some adjustments. However, once resources are allocated to more productive uses, imports have a long-term positive impact on productivity. The study that underpins our main assumption uses a measure of real openness which is the sum of exports and imports over GDP. Review of evidence The OECD has undertaken a study with data from 21 high-income countries over nearly 30 years controlling for other factors: every 10-percentage point increase in trade exposure (as measured by trade share of GDP) contributes a 4- percent increase in GDP per capita. This study is quoted by the Canadian government in The State of Trade 2012 and provides the main evidence source for our assumption. We have also reviewed evidence to suggest that the impact of trade on productivity may be lower when comparing domestic trade to international trade: a) Therrien and Hanel (2012) provide evidence supporting the idea that the productivity gains from trade are stronger with trade to foreign markets compared to the domestic market: they find that Canadian firms who export to foreign markets have higher labour productivity. Their results are based on the following steps. They find that Canadian firms who export to non-us markets and US markets are more likely to innovate than firms who do not. Canadian firms who innovate more have higher innovation-related sales. Finally, firms that have higher innovation-related sales also have higher labour productivity. b) Ito (2011) examines whether first-time Japanese exporters achieve productivity improvements through learning-by-exporting effects. The results suggest that exporting to North America or Europe has a strong positive effect on sales and employment growth, R&D activity, and productivity growth. On the other hand, exporting to Asia does not have any strong productivity enhancing effects. This would suggest that exporting to Appendix 1: Methodology Economic value today

64 58 Frontier Economics February 2014 countries that are more similar (or geographically close) has a lower impact on productivity. However, on the other hand we also found a range of papers that do not identify a difference. For example, Wagner (2012) undertakes a literature review of the impact of trade on productivity and finds that exporters are more productive than non-exporters but finds no difference to where you export. On the specific question of the impact of Canadian internal trade on productivity, we have found that: Agnosteva and Anderson (2013) estimate the existence and impact of intraprovincial trade barriers. They find that there is substantial intra-provincial home bias. Home bias is the tendency to trade much more within a region than to another region, and is often a sign of the presence of formal or informal trade barriers. This suggests that the Canadian provinces and territories are not fully integrated yet and there is significant scope for internal trade policy intervention. This would suggest that inter-provincial trade still has some impact on productivity. Selection of assumption values We have relied on the findings by the OECD (reported by the Canadian government) to assume that a 1 per cent increase in real openness increases GDP by 0.4 per cent. We apply this assumption to international trade. The evidence suggests that the impact of interprovincial trade is likely to be lower. We therefore assume that a 1 per cent increase in interprovincial trade increases GDP by 0.2 per cent. To convert the contribution of GDP into employment, we have used the same conversion rate as Foreign Affairs and International Trade in their analyses of free trade agreements: for every $150,000 of GDP, one full-time job is created. Key relationship 4: FDI and productivity Concept Both inward and outward FDI have a positive impact on productivity and competitiveness. Our research suggests that access to new markets, cheaper inputs and new technology or know-how boosts the scale and efficiency of domestic production. The underlying theory is similar to that applied to free trade agreements. Figure 19 summarizes how FDI can impact on productivity. Appendix 1: Methodology Economic value today

65 February 2014 Frontier Economics 59 Figure 19. Impact of FDI on productivity Review of evidence Evidence on the specific impact of FDI on productivity is limited. We have found the following studies: a) DIW (2009) studies the relationship between outward FDI and economic growth. They find that FDI enables firms to enter new markets, import intermediate goods from foreign affiliates at lower costs and access foreign technology. As a result the domestic economy benefits from outward FDI due to increased competitiveness of the investing companies and associated productivity spill-over to local firms. The analysis shows that for every 1 per cent increase in outward FDI stock, local GDP increases by 0.19 per cent. b) Korea Institute for International Economic Policy (2008) studies the relationship of inward FDI and productivity using Ireland as a case study. They find that FDI advances new foreign technology or import of new intermediary goods and enhances growth by accumulation of human capital by means of labour training or absorption of technology and new management techniques. Their analysis shows that for a 1 per cent increase in inward FDI stock, local GDP increases by 0.24 per cent. We have investigated the potential to use a different elasticity for the US. For example, Borensztein, Gregorio and Lee (1998) analyse FDI flows from industrial to developing countries. They find that FDI contributes to economic growth only if a minimum level of human capital is met in the receiving country. Appendix 1: Methodology Economic value today

66 60 Frontier Economics February 2014 This is likely to hold for most connected countries. Similarly, Alfaro, Chanda, Kalemli-Ozcan and Sayek (2006) find that holding FDI constant, financially welldeveloped economies experience higher growth rates. They identify human capital as one of the key factors that influences this effect. However, none of the literature that we reviewed indicated that the FDI between the US and Canada would be expected to have a different impact on Ontario than FDI with other countries. Selection of assumption values Based on the quantitative analysis we reviewed, we make the following assumptions: a 1 per cent increase in inward FDI increases productivity by 0.24 per cent; and a 1 per cent increase in outward FDI increases productivity by 0.19 per cent. Appendix 1: Methodology Economic value today

67 February 2014 Frontier Economics 61 Appendix 2: Methodology Economic value in 2030 This appendix provides the detailed methodology for estimating economic value in The methodology is largely based on the assumptions described in Appendix 1 but some additional assumptions are required to project the results to More detail on how the competitive scenarios are developed is provided in Appendix 3. Overview of methodology Figure 20 provides an overview of the methodology for the 2030 results. The key step for the baseline scenario is to project passenger numbers for 2030 for Toronto and the 11 competitor airports. Figure 20. Overview of methodology for future economic value Appendix 2: Methodology Economic value in 2030

68 62 Frontier Economics February 2014 Key relationship 1: Macroeconomic trends impact on passenger numbers Passenger numbers in the 2030 baseline scenario are based on the following assumptions: a) GDP growth b) Income elasticities c) Ticket price growth d) Price elasticities We have obtained projections of GDP growth from HSBC Bank (2012). We have used the HSBC source as it provides projections for a large number of countries up until There are few alternative sources that provide projections for so many counties over such a long time period. To ensure the robustness of the HSBC projections we have cross-checked them against a range of international sources including the IMF. Appendix 4 provides a sensitivity test on the assumption about US and Ontario growth. Table 12 provides a summary of the GDP growth assumptions for a selection of countries. Table 12The table shows that growth in the BRIC economies (Brazil, Russia, India and China) is expected to be substantially higher than growth in the developed economies such as Germany and the UK. Appendix 2: Methodology Economic value in 2030

69 February 2014 Frontier Economics 63 Table 12. Summary of GDP growth assumptions Country Average annual growth to 2030 Canada and Ontario US Brazil China Russian Federation India Australia Germany Japan United Kingdom 2.2 per cent 1.3 per cent 3.1 per cent 6.0 per cent 4.1 per cent 5.6 per cent 2.3 per cent 1.4 per cent 0.7 per cent 1.7 per cent The income elasticity describes the increase in demand for travel for every 1 per cent increase in GDP. We have reviewed a number of sources (such as IATA (2007) and UK Department for Transport (2013)) that suggest that the income elasticity is likely to be between 1 and 2. We also found evidence to suggest that the income elasticity is higher in countries with a lower GDP per capita. As a result, we have differentiated income elasticities for countries with different levels of GDP per capita and have used a range between 1.3 for developed countries (including Canada) and 2.2 for developing countries. We have researched likely movements in the ticket price based on changes in cost inputs. IATA (2012) suggests that the oil price is one of the main drivers of changes in ticket prices as it accounts for as much as 34 per cent of total input costs. Oil price projections by the World Bank (shown in Figure 21) show a slight decline in the oil price. This would suggest a potential reduction in ticket prices. Appendix 2: Methodology Economic value in 2030

70 64 Frontier Economics February 2014 Figure 21. World Bank Oil Price Forecast Source: World Bank, (2013), Commodity Price forecast We have assumed no change in ticket prices as the oil price decline may be offset by increases in other input costs. The assumptions on GDP growth, income elasticity and ticket price growth result in demand projections shown in Table 13. Toronto Pearson has a slightly higher average annual growth rate in passengers than the competitor airports. This is because Toronto Pearson has a higher proportion of international passengers. As GDP growth is expected to be relatively low in the US and Ontario compared to the BRIC countries, international passenger demand is expected to grow quicker than local demand. Figure 22 shows each hub airport s share of combined passenger volumes for Toronto Pearson and the 11 hub airports in 2011 and Toronto Pearson s share increases from 5.7% in 2011 to 6.6% in Table Passenger volumes at Toronto Pearson and 11 competitor hubs Airport 2011 Passengers (million) 2030 Passengers (million) Growth Compound Average Annual Growth Toronto per cent 3.1 per cent Atlanta per cent 2.1 per cent Appendix 2: Methodology Economic value in 2030

71 February 2014 Frontier Economics 65 Chicago per cent 2.0 per cent Los Angeles per cent 2.1 per cent Dallas per cent 2.0 per cent Denver per cent 1.8 per cent JFK per cent 2.3 per cent Houston per cent 2.4 per cent Charlotte per cent 2.0 per cent Miami per cent 3.1 per cent Newark per cent 2.1 per cent Detroit per cent 1.9 per cent Appendix 2: Methodology Economic value in 2030

72 66 Frontier Economics February 2014 Figure 22. Share of total passenger volumes at Toronto Pearson and 11 hubs in the US 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% Source: Frontier analysis

73 February 2014 Frontier Economics 67 Appendix 3: Methodology Competitive scenarios in 2030 Our analysis considers the value facilitated by Toronto Pearson today and in In the 2030 scenario, we assume a business as usual scenario in which Toronto Pearson grows in line with economic growth and standard income elasticities. This implies that Toronto Pearson neither gains nor loses share in the market for connecting passengers. To illustrate the opportunity for Toronto Pearson s growth, we have estimated the market size of connecting passengers. We can then link different scenarios for hub competition to the economic value calculations. This allows us to determine the additional economic value facilitated by Toronto Pearson if Toronto Pearson were to attract a greater share of connecting passengers from other North American hubs. The economics of hub networks are such that connecting passengers are crucial for a hub to operate successfully. This is because in the absence of connecting passengers, an airport is solely reliant on OD demand and this is limited to the local catchment. By pooling connecting passengers from all over the world, a hub airport can increase its demand for particular flights and therefore fly more regularly. In fact, without connecting passengers some routes might not be viable at all. Therefore by adding extra connecting passengers, Toronto Pearson is able to: a) make new direct connections; and/or b) increase the frequency of flights on existing routes. Local business passengers get a direct benefit if increased numbers of connecting passengers allow Toronto Pearson to support direct connections to new destinations. With lower numbers of connecting passengers some destinations could not be served meaning that local business passengers would have to fly indirect to reach those destinations and because this is inconvenient and timeconsuming they might respond by flying less frequently or not flying at all. If having more connecting passengers Toronto Pearson is able to increase the frequency of flights on existing routes, then this also benefits business passengers. This is because Toronto Pearson can offer more flights per week or per day. This might create flights that are more convenient to some business passengers who might not have flown otherwise. Appendix 3: Methodology Competitive scenarios in 2030

74 68 Frontier Economics February 2014 Airports considered In our competitive scenarios, we consider passenger volumes at Toronto Pearson and 11 hubs in the US. 2 We have used these hubs because, according to Airports Council International, they all handled either the same number of passengers as Toronto Pearson in 2011 or more. We therefore consider them to represent the largest opportunities to Toronto Pearson with respect to competition for connecting passengers. Figure 23 presents an illustration of the airports considered in the analysis. Figure 23. Hub airports considered in our 'competitive scenarios' ACI 2011 Los Angeles Toronto Detroit Denver Chicago JFK and Newark Charlotte Atlanta Dallas Houston Miami Airport Total Passengers (million) Atlanta 92.4 Chicago 66.6 Los Angeles 61.8 Dallas 57.8 Denver 52.7 JFK 47.9 Houston 40.2 Charlotte 39.0 Miami 38.3 Newark 33.6 Toronto 33.4 Detroit 32.4 Source: Frontier analysis Expected passenger volumes in 2030 As discussed in section 2.5 we have forecast passenger volumes for Toronto Pearson in In order to consider the competitive scenarios, we have also forecast passenger volumes at the 11 US hubs, by following the same approach. Figure 24 summarizes the expected growth in passenger volumes. 2 These hubs are Atlanta, Chicago, Los Angeles, Dallas, Denver, JFK, Houston, Charlotte, Miami, Newark and Detroit Appendix 3: Methodology Competitive scenarios in 2030

75 Toronto Atlanta Chicago Los Angeles Dallas Denver JFK Houston Charlotte Miami Newark Detroit Passengers (millions) February 2014 Frontier Economics 69 Figure 24. Growth in passenger volumes Source: Frontier analysis Our analysis suggests that Toronto Pearson has the potential to experience the highest level of growth out of all the hubs in our analysis. We expect Toronto Pearson to grow to 60 million passengers by 2030 which represents a 78 per cent increase in size over the period This implies an average annual growth rate of 3.1 per cent. Meanwhile, the US hubs are expected to grow by about 50 per cent on average over the same period. This implies a lower average annual growth rate of around 2.2 per cent. The main driver behind this result is that, according to HSBC (2012) growth forecasts: a) Canadian GDP is set to grow by 2.2 per cent a year on average between ; while b) US GDP is expected to increase by only 1.3 per cent a year on average over the same period. Our analysis suggests that there will be around 840 million passengers in total at the US hubs in And around 370 million of them, or about 44 per cent, will be connecting passengers. The first important consideration is that of these 370 million connecting passengers, 220 million - or 60 per cent - are actually domestic connections making a journey which can be described as a US to US, via the US journey. This means that they start their journey in the US, connect via one of the US Appendix 3: Methodology Competitive scenarios in 2030

76 70 Frontier Economics February 2014 hubs, and fly on their final destination also in the US. However, Toronto Pearson is not able to compete for these passengers as this type of traffic cannot be served from Canada under existing air service agreements. This rules out a large number of potential passengers for Toronto Pearson. But the remaining connecting passengers are not all likely to consider Toronto Pearson a viable hub because: a) For some routes Toronto might be poorly placed geographically. This might mean that connecting via Toronto instead of a US hub adds more travel time, and is therefore unattractive to connecting passengers; and b) For some connecting passengers, Toronto Pearson might not offer both legs of the journey that are required in order to make the connection. To arrive at an appropriate market size we have considered both these factors in some detail. Travel distance and market definition The relevance of travel distance for the market definition is best explained by using an example. Our baseline results suggest that in 2030, around 15,000 passengers will travel from the United Kingdom to Los Angeles via JFK in New York and 22,000 passengers will make the same journey but connect via Toronto Pearson instead. In terms of travel distance, there is little difference between the two hub airports, in fact the journey via Toronto is about 3 per cent shorter than the journey via New York. For a passenger, JFK and Toronto Pearson are likely to be substitutable as the travel time is likely to be similar. It is much harder to attract connecting passengers if the use of Toronto Pearson increases their travel times substantially. For example, Toronto Pearson is connected to Seattle and China. Therefore, in principle, Toronto could connect passengers wishing to travel between the two destinations. But in 2011 no passengers travelled from Seattle to China via Toronto even though around 4,000 passengers chose to travel between Seattle and China via LAX in Los Angeles. This can partly be attributed to the difference in travel time. The distance via Toronto is around 8,600 miles compared to only 7,200 miles via Los Angeles, so the connection at Toronto adds an extra 20 per cent of travel distance. The two examples suggest that travel distance is an important factor in determining whether hubs actually compete with each other for connecting passengers. However, we also need to recognize that travel distance also depends on the particular route. This means that two hubs might compete with each other in one market, but not in another. Appendix 3: Methodology Competitive scenarios in 2030

77 February 2014 Frontier Economics 71 Staying with the example of passengers originating in Seattle while Toronto may not be able to compete with LAX for passengers wishing to fly to China, it is likely to be able to attract passengers wishing to fly to Europe. In 2011, Toronto Pearson and LAX both acted as a hub for passengers wishing to travel between Seattle and the UK, France, Germany and Italy. Depending on the precise European destination, routing via Toronto reduces journey distance by 3 per cent to 4 per cent compared to LAX. To account for differences in travel distance we introduced a distance test into our market definition. First, we calculated the total travel distance of connecting every destination in the world to every other destination in the world via Toronto. And we calculated the same figures for the other 11 hubs in our analysis. Taking each possible connection in turn, we estimated whether Toronto Pearson is in the market by considering whether it can pass our distance test. This is described in the box below. Distance test Toronto Pearson is in the market on a particular route if it can satisfy one of the following tests: 1. The travel distance via Toronto Pearson is less than the travel distance of any rival hub that is active in the market; or 2. If the travel distance via Toronto Pearson is longer than all the rival hubs that are active in the market, then it must be within 10 per cent of the shortest travel distance. If Toronto Pearson does not satisfy either of these tests, then it is not in the market By applying a market definition as described above, we identified a total pool of 131m contestable connecting passengers for which Toronto Pearson could compete for in By capturing connecting passengers from rival hubs Toronto Pearson might be able to create new connections In 2011, 50,000 passengers flew from destinations all over the world to Bolivia via one of the hubs in our analysis. However, none of them flew via Toronto because there is no direct connection to Bolivia. But of these 50,000 passengers, around 93 per cent of them started their journey in a destination where Toronto Pearson does have a direct connection. Therefore, in practice Toronto would have been able to offer half the journey but not complete the full connection. Appendix 3: Methodology Competitive scenarios in 2030

78 72 Frontier Economics February 2014 In our analysis we also make the distinction between pairs of destinations that Toronto can currently connect, and those that it cannot. With this in mind, our analysis recognizes that Toronto Pearson competes for connecting passengers in one of two markets: 1. On connecting routes where Toronto can offer both legs of the journey; and 2. On connecting routes where Toronto cannot offer both legs of the journey. This is an important distinction because it allows us to consider whether Toronto Pearson can make a viable new connection by supplementing the underlying OD demand with connecting passengers from rival hubs. Table 14Table shows that by 2030 the majority of contestable connecting passengers travel on routes where Toronto Pearson could offer both legs of the connection. Table 14. Connecting passengers at rival hubs in the US (m) Connecting passengers per cent of total Market per cent Market per cent Total (1+2) per cent Source: Frontier analysis This implies that by 2030, there will be more contestable connecting passengers moving through the rival hubs in the US than all the passengers at Toronto Pearson itself. So, capturing even a fraction of these connecting passengers could result in a large increase in passenger volumes at Toronto Pearson. Linking competitive scenarios to economic value Our analysis allows us to consider the 131 million contestable connecting passengers in more detail. We can split the figure by region and consider the total figure on a region-by-region basis. Figure 25 reports how the 82 million passengers in Market 1 are split between the different geographic regions. We see that of the 82 million contestable passengers in Market 1, 24 million of them or around 30 per cent - both start and finish their journey in North America. 3 3 This figure controls for the fact that Toronto Pearson cannot connect US-to-US domestic transfers. Therefore this figure is made up of passengers either starting their journey in Canada and flying to the US, or vice versa starting their journey in the US and flying to Canada. Appendix 3: Methodology Competitive scenarios in 2030

79 February 2014 Frontier Economics 73 The second most popular region-to-region route is North America to Asia. In 2011, 13 million passengers flew between North America and Asia via one of the rival North America hubs. And again it is important to note that these are passengers whose origin and destination are both served by Toronto Pearson, and that Toronto passes the test for market definition. Appendix 3: Methodology Competitive scenarios in 2030

80 74 Frontier Economics February 2014 Figure 25. The distribution of 'contestable' passengers Source: Frontier analysis Interpretation: The row heading represents the direction of travel. The column heading represents the origin. For example, 55,192 passengers flew from Central America & Caribbean to Asia via one of the North American hubs, and 52,346 passengers flew from Asia to Central America & Caribbean via one of the North American hubs. Note: The entries in this matrix are not symmetric. For example while 52,346 passengers fly to Central America & Caribbean from Asia via one of the North American hubs, 55,192 passengers fly in the opposite direction. This is because in reality, while inbound and outbound passengers are roughly equal on average there is some variation as observed in the 2011 data. Appendix 3: Methodology Competitive scenarios in 2030

81 February 2014 Frontier Economics 75 Figure 26 illustrates the size of the total connecting markets. Our analysis allows for the consideration of any fraction or combination of these passengers. Adding connecting passengers is likely to have a positive impact on the number of Origin-Destination 4 (or O/D) passengers, as connecting passengers add to the network effect at the airport. Having more connecting passengers on a given route increases the total number of passengers flying on that route, which means that airlines can offer greater frequencies. As a result, the increased frequency of flights means that there is greater flexibility in flying on that particular route this is because there are now more flights per day or per week. Some potential O/D passengers might have been unwilling to fly before because the flights available at the time were not at convenient times of the day or days of the week. But the greater availability means that some O/D passengers are now willing to fly. And this results in an increase in O/D demand. This effect is shown in Figure 26 below. Figure 26. Network effect on a given route Increase in connecting passengers Increase in total passengers Increase in flights Increase in OD passengers More attractive to marginal OD passengers Greater flexibility in flying Source: Frontier illustration 4 Origin-Destination (O/D) passengers are all passengers that are not connecting via Toronto Pearson, i.e. passengers for whom Toronto Pearson is either their origin or final destination. Appendix 3: Methodology Competitive scenarios in 2030

82 76 Frontier Economics February 2014 Figure 27. An example of capturing contestable connecting passengers Source: Frontier analysis Note: This is a symmetric matrix. This means that the input that appears in the cell for from Asia to North America will also appear in the cell for from North America to Asia. The underlying assumption is that every connecting passenger that Toronto Pearson captures from a rival hub will also make the same return journey in the opposite direction and therefore needs to be counted twice. In the model, this means that the model user can input a figure in the green cells and the same figure will also appear in the opposite / return cell. In this particular example, we have selected 5 per cent of all connecting passengers travelling to and from North America to every other region in the world. Appendix 3: Methodology Competitive scenarios in 2030