Regional labour market effects of an improved transportation system COWI A/S

Transcription

1 Regional labour market effects of an improved transportation system COWI A/S

2 Title: Client: Produced by: Regional labour market effects of an improved transportation system Nicole Due, Capital Region of Denmark and Sten Hansen, Region of Scania, Sweden COWI A/S Visionsvej 53, 9000 Aalborg, Denmark Project manager: Experts/team: Poul Sørensen Grethe Helledie, Dan Nissen, Diana Kringelbach, Ina Ringsdal, Søren Staal, Ole Kveiborg Published September

3 Contents 1. INTRODUCTION AND BACKGROUND APPROACH AND DEFINITIONS COMMUTING AND EMPLOYMENT DEVELOPMENT TRENDS MAIN DRIVERS BEHIND COMMUTING... 7 a) Definitions... 7 b) Commuting as a reaction to imbalance... 7 c) Cross-border commuting developments COMMUTING TARGET GROUPS a) Long-distance commuter COMMUTING DURATION a) High educational level means long-term commuting OPPORTUNITIES FOR AND BARRIERS TO COMMUTING a) Personal barriers to commuting b) Formal barriers EXPECTATIONS FOR COMMUTING WITHIN THE CORRIDOR COMMUTING ANALYSIS APPROACH a) Driving catchment area Destinations b) Population basis FINDINGS FROM THE COMMUTING ANALYSIS SUMMARY EDUCATION AND INCOME IN THE GREEN STRING CORRIDOR INDICATIONS OF THE RECRUITMENT BASIS EDUCATIONAL LEVEL ATTACHMENT TO LABOUR MARKET INCOME SUMMARY INTERVIEW STUDY GENERAL EXPECTATIONS INDUSTRIES AND COMPETENCIES a) Civil engineering b) Health c) Industry d) Commuting between Zealand and the Oresund area COMMUTING TYPES a) Commuting or influx of residents? b) Long-distance commuting EXPERIENCE WITH COMMUTING AND LABOUR ACROSS BORDERS a) Barriers and challenges SUMMARY

4 6. CONCLUSIONS AND PERSPECTIVES APPENDIX: TABLES AND FIGURES APPENDIX: INTERVIEW LIST APPENDIX: REFERENCES

5 1. Introduction and background The fixed link across Fehmarnbelt is due to open to traffic in In parallel to the establishment of the Fehmarnbelt link, the railway link across Zealand towards Fehmarnbelt will be upgraded to ensure faster rail services. Minor improvements of the motorway link will also be carried out. On the German side of the belt, the traffic system will also undergo improvements; however, it is not currently clear that all improvements will be in place for the opening of the Fehmarnbelt link. The improved traffic system will improve conditions within the entire traffic corridor between the Oresund area and Hamburg. Even though the Fehmarnbelt fixed link will be the single greatest improvement, travel opportunities within the two countries will also be improved. This analysis examines the potential labour market effects of an improved transportation system within the traffic corridor between the Oresund area and Hamburg. That is, improved commuting possibilities for labour and companies possibilities for recruiting labour within the corridor, or put differently: To what extent will the improved transportation system lead to better recruitment possibilities for companies within the traffic corridor between the Oresund area and Hamburg. 1.1 APPROACH AND DEFINITIONS The analysis is based on the future transportation system between Copenhagen/Malmo and Hamburg, i.e. a fully developed motorway link between Copenhagen and Hamburg and improved rail service between the cities. The transportation system has previously been described in analyses undertaken in the context of the Green String Corridor. The analysis focuses on a number of specific commuting possibilities within the corridor. The background is a wish to analyse the commuting potential between the two metropolitan areas of Copenhagen/Malmo and Hamburg as well as within the corridor, that is, between other cities in the corridor. As a result, the analysis does not uncover the total commuting potential within the corridor, rather the impact of the improvements introduced by the new transportation system. The impact will be demonstrated by means of examples; select cities with a certain concentration of both industry and workforce. 5

6 The analysis is carried out by combining several approaches that altogether shed light on a series of both qualitative and quantitative aspects of commuting, general as well as specific to the corridor between the Copenhagen/Malmo area and Hamburg. The analysis elements will be described in more details below. Desk research on commuting We have reviewed key literature on typical commuting characteristics: Commuting target groups, commuting distances, commuting duration, formal and psychological commuting barriers. Furthermore, the desk research uncovered specific experience with commuting trends in the Oresund area and between Denmark and Germany. Commuting analysis We have analysed the commuting potential within the corridor, based on the improved transportation system. The commuting analysis indicates what additional workforce potentially will become accessible thanks to the new fully developed transportation system. The analysis is based on examples of trips between cities in the corridor, a mapping of the population ages 16 to 65, and data on travel times (road net databases and future rail travel times). Analysis of income and labour market affairs To supplement the desk research and commuting analysis, the income level and educational level in geographical areas within the corridor are mapped. Several analyses indicate a clear link between income level, educational level and commuting: The higher the income and educational level, the greater the trend of commuting. Qualifying interview sessions The analysis was concluded by interviews with companies and industrial promoters in order to qualitatively uncover the commuting potential within the corridor and the parties concrete expectations for the commuting trend in the transportation corridor. The analysis findings are reported in the following chapters of this report. 6

7 2. COMMUTING AND EMPLOYMENT DEVELOPMENT TRENDS This chapter contains the findings of a review of existing analysis of commuting and how commuting impacts the labour market. This chapter focuses especially on the background and general drivers behind commuting, the commuting target groups, and typical opportunities and barriers related to commuting trends. Finally, the review of commuting analyses leads to a number of general assessments regarding the expectations for commuting within the Green String Corridor, primarily based on the new situation after the opening of the Fehmarnbelt fixed link. 2.1 MAIN DRIVERS BEHIND COMMUTING a) DEFINITIONS Statistics Denmark defines a commuter as a person who does not live and work on the same address. The commute is often a daily trip between the person s home and workplace, but may also be a more seldom trip. Consequently, the concept of a commuter does not imply a precise indication of the distance between the commuter s home and workplace. Yet, the concept is used when there is a certain commuting time between home and workplace. In practice, and in order to statistically process commuting, commuting is most often defined as transportation across an administrative border (e.g., a municipal border), thereby distinguishing between the night population and day population of an area, i.e. the number of citizens commuting across the municipal border to jobs outside of their municipality of residence. b) COMMUTING AS A REACTION TO IMBALANCE The need or motivation to commute emerges when an imbalance exists between the place where you live and your possibilities on the labour market. Or put differently; when the difference between the two places creates incentive for you to travel. In case of commuters in the same country, incentive may be created by the difference between urban and rural areas. You want to live in rural surroundings, but they offer limited work possibilities. As regards cross-border commuters and regional commuters, the difference between the district where you live and the district where you work may be what creates the 7

8 incentive. This could be a difference in house prices, tax rules, wage level, employment situation etc. So, differences spur labour force to travel 1. For the same reason, the willingness to commute differs greatly between regions, even though commuting in total has increased globally 2. Today, major cities in particular attract commuters. 105,601 persons commute to Hamburg from other areas in Northern Germany /2008 figures show that 66,500 commute from hinterland areas to Copenhagen and environs, 26 per cent of which come from Scania 4. c) CROSS-BORDER COMMUTING DEVELOPMENTS Commuting in the Oresund region Quite a few commuters choose to work in another country because it is interesting and exciting to work in a different environment, in an unfamiliar place. Studies of commuting in the Oresund region shows, nevertheless, that the cross-border commuter s motivation most often is caused by vital differences between the country of residence and the country of work, in terms of house prices, tax rules, wage level, employment possibilities and so on. In the Oresund region, especially before the financial crisis, Scanian commuters were motivated by, e.g., higher wages and better job opportunities in Denmark (despite apparently being paid less than Danes in similar positions), and in the same period, Danish commuters were motivated to take up residence in Scania, which offers lower house prices, while keeping their jobs in Denmark 5,6. Wages and house prices are two main drivers of commuting. As many as 49 per cent of the Oresund commuters indicate that they commute across Oresund for more personal reasons, including factors such as their spouses jobs and nationality as well as the Danish 24-year rule 7. 1 Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver, kap 5. 2 Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver, kap 5. 3 Fast Femern Bælt Forbindelse, En ny dymaniask udvikling i Nordeuropa. Sammenfatning af Christian Wichman Mattiessen Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver, kap 5. 5 Pendling i Øresundsregionen, Beskæftigelsesregion Hovedstaden og Sjælland, Tendens Øresund, Øresundskomiteen, Analyse af den kollektive trafik i Øresundsregionen, Cross Border Øresund,

9 The Oresund fixed link significantly increased the number of commuters, and the number continued to go up untill the start of the financial crisis. The number of commuters peaked in 2008 at 19,805, falling to 18,414 in Öresundskomiteen estimates that the number went down further in The decrease in commuting is primarily due to a decrease in total employment caused by the financial crisis and declining house prices in Denmark in the same period. Part of the Danes that chose to set up in Sweden have since moved back to the Copenhagen area. When the crisis hit, it reduces the employment opportunities for commuters. Figure 2-1: Commuting across Øresund Number of commuters DK-SE and SE-DK. Source: Tendens Øresund However, overall, international commuting is mainly cross-border commuting which in terms of travel time and distance is quite similar to national commuting 9. Commuting between Denmark and Germany The number of cross-border commuters has gone up considerable in some border regions in the past decade. This also goes for the Danish-German border 10, although the number went down due to the financial crisis. The specific number of commuters crossing Fehmarnbelt today is not known, but in 2001 a total of 12,870 persons commuted to Denmark from Germany and 1,560 to Germany from Denmark. Peaking in 8 Tendens Øresund International persontransport i Øresundsregionen, IBU Øresund, Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver. 9

10 2008 at 19,300 commuters across the Danish-German border, commuting dropped to around 8,400 commuters in 2012, due to the financial crisis 11. The majority crosses the Danish-German land border. It is worth noting that Danish-German commuting has gone down considerably more than Danish-Swedish commuting, cf. above section. Distance and travel time Travel time is a key parameter for commuting. In the Oresund region, a daily 60- minute travel time each way is what commuters can stand when commuting across Oresund. However, regional issues may motivate people to commute across longer distances and a travel time exceeding 60 minutes is, e.g., not unusual for Scanian domestic commuters 12,13. In geographical areas with poor employment opportunities, commuters are more than willing to commute for more than 60 minutes 14. In general, people commute less than 30 minutes to get to work, but if you work in a big city, the actual travel time may in fact be longer, despite a short distance. The share of people commuting between 30 and 60 minutes each way is considerable higher for people working in Hamburg and Berlin, than for the rest of Germany 15. A strong incentive for long commutes is the possibility of matching qualifications and jobs. Companies that require highly specialised labour may need to recruit far away in order to find those best qualified. In the Oresund region, commuters from across Oresund travelling more than 1.5 hours inland are almost exclusively found in so-called special trades. Nonetheless, commuters continue to travel longer people are willing to commute longer than before COMMUTING TARGET GROUPS Several studies show that gender, age, wage and educational level affect the labour force s willingness to commute 17. For instance, women average a shorter commuting 11 Region Sønderjylland-Schleswig. Den samfundsmæssige værdi af grænsependling mellem Danmark og Tyskland Öresundsregionen: tillgänglighet och mobilitet af arbetskraften 13 Analyse af den kollektive trafik i Øresundsregionen 14 Manche pendeln weit - Berufspendler im Bundesländervergleich 15 Manche pendeln weit - Berufspendler im Bundesländervergleich 16 Öresundsregionen: tillgänglighet och mobilitet af arbetskraften 10

11 distance than men, and more men commute across the Oresund 18,19,20, which may reflect the fact that women s mobility in the labour market highly depends on family and children 21. Especially the analyses of commuting in the Oresund region show that commuting behaviour and commuting distance initially depend on the commuter s personal employment situation. The higher the income, the longer the average commutes, and the more often the commute is by private car. It also shows that part-time employees more rarely take on work far away from home 22. Most commuters from Scania to Copenhagen are newly educated young people with a higher education who are yet to become well established on the labour market 23. In general, commuters are well educated and work to a high extent in the private sector, widely distributed over trade groups. The average Oresund commuter is a young, male salaried employee without management duties who resides in Sweden 24,25 In the Oresund region, many commuters are Danes residing in Sweden, but working in Denmark. Those who choose to move to the other side of the bridge are typically young people, ages 25 to 34, who return to their native country when it is time for their kids to start school 26. a) LONG-DISTANCE COMMUTER People with higher educations who either earn a high wage or live in place with poor employment opportunities are willing to commute the longest Pendling i Øresundsregionen 18 Manche pendeln weit - Berufspendler im Bundesländervergleich 19 Tendens Øresund 20 International persontransport i Øresundsregionen 21 Pendling i Øresundsregionen. Job og kompetencer i Øresundsregionen Data from Ørestat. 22 Manche pendeln weit - Berufspendler im Bundesländervergleich 23 Pendling i Øresundsregionen. Job og kompetencer i Øresundsregionen Data from Ørestat. 24 Tendens Øresund 25 Analyse af den kollektive trafik i Øresundsregionen 26 Tendens Øresund 27 Öresundsregionen: tillgänglighet och mobilitet af arbetskraften 11

12 The long-distance commuter is motivated by a large financial or development gain from commuting a long distance rather than a short. The reason may be that the commuter s household is tied to a specific geographical area (natural values, spouse s workplace, children s school), or it may benefit the commuter, for a limited period of time, to work somewhere that increases the commuter s earnings and/or personal development. For the long-distance commuter to achieve a personal gain from a long commute, it is key that the travel time can be utilised efficiently, i.e. either for work or relaxing, so this commuter type avoid means of transportation that prevents working on the go 28. A fast train service in the Green String Corridor will therefore be an ideal mode of travel for the long-distance commuter. A typical long-distance commuter is a highly educated male, ages 25 to 40, who does not commute every day, but once or twice a week. The commuter may therefore have two homes, or the commuter is able to work from a home office by means of modern electronic means of communications 29. The average Oresund commuter travels 1,49 trips per day 30. The average number of weekly trips to the workplace decreases as the commuting distance increases, i.e. the share of weekend commuters increases as distance increases. Transport costs consequently increase under proportionally to the actual cost per trip. This also affects the long-distance commuter s motivation to commute COMMUTING DURATION Studying commuting trends, it is interesting to not only look at how long travel time is generally acceptable to commuters, but also how long they maintain a daily life that involves commuting. The duration of commuting thereby indicates to what extent commuters constitute a stable labour force. a) HIGH EDUCATIONAL LEVEL MEANS LONG-TERM COMMUTING Commuters who have a long-cycle higher education commute for more years than commuters with a different educational background. Also, young commuters mainly 28 International persontransport i Øresundsregionen, IBU Øresund, International persontransport i Øresundsregionen, IBU Øresund, Derfor rejser vi over Øresund. Øresundskonsortiet Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver

13 commute for a few years, whereas commuters over 50 often commute for longer periods. Furthermore, men and persons with a high average wage commute for longer than others do 32 - i.e. fits the profile of the long-distance commuter. The logical reason is that long-distance commuting is often limited to one or two travel days a week and occurs in a way that allows the commuter to actively utilize the travel time. Altogether, this puts lets stress on the daily life than daily commuting 33. A survey carried out in the Oresund region from 2001 to 2007 demonstrates that 46 per cent of Scanian commuters between Scania and the Copenhagen area commuted for up to a year. In comparison, 29 per cent of the Danish commuters between Eastern Denmark and the Copenhagen area commuted for up to a year. Part of the explanation lies in the commuters ages: 41 per cent of Scanian commuters were under 30, whereas only 17 per cent of the commuters from Eastern Denmark were under : Young people are at this age typically not yet established on the labour market, and they may commute for seasonal positions or student jobs. On average, Danes commuting to jobs in the Greater Copenhagen area and Elsinore from elsewhere in Eastern Denmark commute for a longer period of time than do those who cross national borders OPPORTUNITIES FOR AND BARRIERS TO COMMUTING In the Oresund region, the fixed link exerts a huge impact on the labour market. The bridge entailed a growth in Swedish employees in retail and business service on the Danish side of the sound 36. And calculations show that companies in Malmo have increased their recruitment basis by 181 per cent, since 560,000 in the Copenhagen labour force can reach Malmo city centre by car within one hour. In turn, around 400,000 in the Scanian labour force can reach Copenhagen by car within one hour. If you choose public transit, the figures are around 100,000 and 200,000, respectively 37. Overall, the socioeconomic impact of the bridge is assessed to far exceed its con- 32 Pendling i Øresundsregionen, Beskæftigelsesregion Hovedstaden og Sjælland, Pendling i Øresundsregionen, Beskæftigelsesregion Hovedstaden og Sjælland, Pendling i Øresundsregionen 35 Pendling i Øresundsregionen 36 Tendens Øresund 37 Öresundsregionen: tillgänglighet och mobilitet af arbetskraften 13

14 struction costs one of the factors being costs saved as unemployed Swedes found jobs in Denmark, as well as the value created by these workers contribution to the Danish production 38. There are barriers to this development, though. Partly mental/personal barriers among commuters, partly legislative and cultural barriers. a) PERSONAL BARRIERS TO COMMUTING Practical barriers Several studies show that commuters have a barrier towards travelling more than 60 minutes each way. The labour markets remains designed for people coming to their workplace every day. In the Oresund region, very few jobs are available on the other side of the sound for people who only want to travel for 30 minutes, whereas people willing to travel for 60 minutes have access to a very large labour market on either side of the Oresund. Fehmarnbelt presents a very different situation as the areas on either side of the belt are peripheral areas facing demographic challenges and weak economic development. The industrial basis of the areas consists of agriculture and tourism, supplemented by various niche industries. The areas are sparsely populated and local jobs lie especially in the public sector and consumer-oriented service business 39. Today, the share of commuters is very low due to the missing fixed link, and even with a fixed link in place, the share of jobs reachable within an hour by cross-border commuters is low. Cross-border commuting in the Fehmarnbelt region is therefore considered to be attractive mainly to the commuter who is willing to commute for more than 60 minutes (see above section on long-distance commuters). Interruptions of transportation and wait time not least a ferry trip to a neighbouring region that can be seen in the horizon also makes a distance seem subjectively vast 40. The study looks into travel times by both public transit and car, and even though a car can take you further than public transit, public transit is still seen as creating good accessibility to jobs within a one-hour travel Broeffekter og muligheder i Øresundsregionen. Öresundskomiteen Regionale udviklingsperspektiver for Femern Bælt-regionen: Fokus på regioner nær Femern-Bælt, Wichmann Matthiessen, Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver Öresundsregionen: tillgänglighet och mobilitet af arbetskraften 14

15 Other than time, the price of the travel also presents a practical barrier. Low-paid employees are underrepresented among commuters since travel costs make up a relatively high share of their wage. Consequently, many in this group reject jobs that entail high travel costs 42,43. Language and cultural barriers Language barriers have always been a major problem for cross-border commuters. In addition to the concrete barrier of having to use a foreign language at work, bilingual information material and bilingual forms in relation to social security and tax law are still to be prepared in both Denmark and Germany. Much information on the Internet is also only available in the local language of the workplace 44,45. An important part of integrating labour markets is the existence of a sound counselling infrastructure that provides information on rules and regulations and offers advice to commuters and employers. This is the case in the Oresund region and the Danish- German land border in Southern Jutland, but there is room for development 46. Mental barriers to commuting As previously mentioned in this chapter, some commuters find it attractive and exciting to work in a different country with a different culture. However, this is not always the case and the foreign element can constitute a mental barrier. Young Danes and Swedes are not particularly interested in living and studying in German. But young Germans are interested in both studying and even more so living in either Sweden or Denmark. Even though young Scandinavians and Germans to a far extent share values and attitudes, they lack general knowledge about their neighbouring countries. Developing the Fehmarnbelt region presumes that steps be made to reduce the mental distance that seems to exist between the German and Danish regions Analyse af den kollektive trafik i Øresundsregionen Mobilitetsbarrierer på det dansk-tyske arbejdsmarked 45 Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver Regionale udviklingsperspektiver for Femern Bælt-regionen: Fokus på regioner nær Femern-Bælt

16 A great transportation link to a major metropol can contribute to breaking down mental barriers because a metropol within reach creates positive, mental value. You feel a mental connection to the metropol thanks to the potential possibility of using its offers (cultural, educational, employment). This value exists whether you make use of the link or not, and may positively affect the willingness to acknowledge employment opportunities in a foreign metropol 48. Many mental barriers will be broken down over time when inhabitants in the different parts of the region become aware of each other and get to know each other better as well as the opportunities lying on the other side of the link 49. b) FORMAL BARRIERS EU citizens have the right to find a job in any member state, regardless of their place of residence. In reality, there are, though, wealth of barriers to this in practice. There are still a number of legislative and practical barriers to integration of labour markets. Different systems regarding wage accounts, unemployment insurance, rules on notice, general employment terms and conditions, tax legislation and not lest hindrances in terms of qualifications such as recognition of certificates and different educational programmes all these make up a barrier to commuters 50. To create an integrated labour market, an institutional effort is required which also includes harmonizing rules and legislation 51. Despite the abovementioned barriers, it should be mentioned that yet another incentive for living or working in a neighbouring region could be tax advantages or better social benefits, so a field of tension exists between mobility barriers and mobility incentives. In this sense, mobility across borders emerges as a result of these differences/imbalances 52. To some extent, formal barriers will always be a basic condition in the life of the crossborder commuter. Basically, barriers are a contributing factor to limiting the possibility of an integrated labour market. However, in cases where strong incentives for labour 48 Tendens Øresund Mobilitetsbarrierer på det dansk-tyske arbejdsmarked. 51 Regionale udviklingsperspektiver for Femern Bælt Regionen: Fokus på regioner nær Femern Bælt Den faste Femern Bælt-forbindelse: Regionale udviklingsperspektiver

17 market integration exist, it does seem possible to break down barriers by entering into bilateral national agreements and separate regulations in border regions EXPECTATIONS FOR COMMUTING WITHIN THE CORRIDOR In the long term, commuting in the Oresund region is expected to increase due to increasing recruitment difficulties on the Danish labour market 54. A very strong integration in the Copenhagen-Hamburg corridor is expected to increase commuter figures by 40 per cent from Germany to Denmark and by 30 per cent from Denmark to Germany 55. It must be assumed that a very important precondition for this development will be a stable development in the overall economic trends the coming years and that the basic motivations for the commuters to travel will still be present. The future commuting trend is linked to the future settlement and relocation trend, and the development of the real estate market and the employment situation in each country are expected to determine the development 56. Assessments from the Oresund region state that changes in the countries relative wage level lead to different impacts, depending on the difference in house prices at the exact time in question, and vice versa 57. New labour market demands will be a driver A key trend that is considered to impact the development of transportation and mobility in the Oresund region and that is already noticeable on today s labour market is the fact that Danish companies increasingly need to specialise to survive the competition with countries that offer significantly lower production costs. This increased need to specialise entails a growth in the demand for specialised labour, and excellent transportation possibilities increase companies possibility of attracting and recruiting this labour. It is expected that, in the future, different commuting activity will develop due to the increased flexibility offered by employers thanks to technological development in communications. This does not necessarily imply less transportation as people may commute longer distances. For this to work in practice depends on more than mere Analyse af den kollektive trafik i Øresundsregionen Tendens Øresund 57 Prognos för arbetspendling i Öresundsregionen med nya förbindelser Helsingborg - Helsingør 17

18 technological development, though: Even at workplaces where it is technically possible to work from home, the social network at work continues to be of high importance to most, and regular physical presence is culturally necessary. Environment and climate considerations Another trend concerns climate change and increased attention to choosing means of transportation that do not use fossil fuels. Consequently, there will be an increased demand for fast rail links that supplement and possibly replace airplanes on short and medium international distances. This is related to the trend of increased individualisation, which entails that people to a lesser extent use work and social status to identify themselves, and increasingly first choose where to live and then find a job. The study only applies these two parameters in projecting commuting and states that any change in the countries relative wage level will have different impacts, depending on the difference in house prices at the time in question, and vice versa. 18

19 3. COMMUTING ANALYSIS As part of the study of the regional labour market effects of an improved transportation system, the potential for expanding the labour catchment area has been mapped. The study is based on a mapping of travel times for inhabitants ages 16 to 65 in the corridor, related to seven major towns and cities with considerable business life or, alternatively, new planned growth areas for business development. Changes have been compared to a situation without any expansion of regional infrastructure. Travel times include trips by car, train and combinations of the two. The calculation of the potential for increased labour catchment areas presumes that the labour chooses the fastest means of transportation to reach the selected destinations. 3.1 APPROACH a) DRIVING CATCHMENT AREA Based on a calculation road network featuring speed information from the project Visualisering af fremtidige rejsetider via Femern, it was assessed what areas will offer one-hour and a two-hour trips by car to seven select destinations with considerable business life. The calculations were carried out for a road network of today and an expanded road network of Furthermore, driving catchment areas for trips by car were calculated as well as combination trips (car/train). Driving catchment areas for combination trips are calculated by first determining the train travel time between railway stations, adding ten minutes of terminal time (spent going from one means of transportation to another), and then calculating driving catchment areas for the remaining time up to one and two hours of travel time. The starting point for the calculations is: In the basic scenario, travel times between stations are taken from the Danish State Railways (DSB) timetable for 8 May 2013, departure from Copenhagen Central Station at 07:44 (Intercity-Express). 19

20 Tabel 3-1 Example of time table for train trip between Copenhagen Central Station and Lübeck in 2013 Station Intercity- Express (ICE) Copenhagen 07:44 Næstved 08:31 Nykøbing 09:08 Lübeck 11:37 Hamburg 12:16 Train trips after 2022 are based on an estimate of future travel times. The time table example in table 3-2 is prepared by Femern A/S and shows expected times and stops for trains and high-speed trains on the Malmo-Hamburg section. Table 3-2 Time table example of train trip between Copenhagen Central Station and Hamburg after Calculations include a ten-minute terminal/shift time for combination trips due to a shift between car and train. The potential labour for each destination is calculated based on the one-hour and twohour travel times, regardless of means of transportation. This analysis therefore pre- 20

21 sumes that commuters always choose the fastest means of transportation. Whether this is always true in practice is, naturally, up for discussion. This approach also means that some destinations might be just outside the one- or two-hour travel time. This applies among others for travelling between Copenhagen and Lübeck. The specific train travel time is 1:43, but added terminal time at both stations means that the total calculated travel time just exceeds 2 hours. DESTINATIONS The eight destinations were determined in cooperation with the working group and are: Denmark Copenhagen Næstved Maribo Nykøbing Falster. Germany Hamburg Lübeck Kiel Oldenburg in Holstein b) POPULATION BASIS The number of persons in the workforce that can reach the seven destinations within one or two hours, regardless of means of transport, is reported separately for Sweden, Denmark and Germany as the statistical population basis is based on different sources and divided into different geographical zones, see table 3. Table 3-3 List of statistical population basis used to calculate the number of persons in the labour catchment areas Country Year Age range of labour force Geographical division (zones) Source Denmark 2011 Ages metre square grid Germany 2012 Ages Kreise and Gemeinde Sweden 2012 Ages metre square grid Statistics Denmark Regionaldatenbank Deutchland Region of Scania 21

22 The number of persons in the labour catchment areas in Denmark is calculated based on a national square grid using 2011 population figures. As regards labour catchment areas, persons ages 15 to 65 are relevant. The number of persons in this age group is calculated in the square grid based on an average per municipality. In Germany, the labour force is calculated as the number of persons ages 15 to 65. Population data are divided according to the German Kreise in rural areas and according to Gemeinde in urban areas with more than 20,000 inhabitants in Schleswig- Holstein and Mecklenburg-Vorpommern and urban areas with more than 75,000 inhabitants in the remaining German lands. The geographical division is shown in figure 3.1. Figure 3-1 Zone division for German population data When a Kreis or Gemeinde is only partly covered by a driving catchment area, the labour force is calculated per area unit. In Sweden, the number of persons in the labour catchment area is calculated based on a Scanian square grid including people ages 16 to 65. Data are provided by Region of Scania. The statement of the Swedish labour force does not include 15-year-olds. This is due to an error during data extraction. 22

23 This report only includes data from Scania, so the labour force for catchment areas outside of Scania is not included. This is, however assumed to have minor effect on the overall results. 3.2 FINDINGS FROM THE COMMUTING ANALYSIS Findings from the commuting analysis reveal that the new transportation system within the Green String Corridor will have the greatest effect on destinations near the future fixed link across Fehmarnbelt. As for the selected destinations, the largest effects are gained by Maribo and Nykøbing Falster which, within one hour of transportation each way, gain access to additional 73,000 and 26,000 inhabitants of working age, respectively. As for all other destinations, a two-hour travel time each way is required to gain access to a larger labour catchment area after the establishment of the improved transportation system. It is key for several destinations that, at a two-hour trip, you gain access to labour from Lübeck and Kiel and not least Hamburg. Copenhagen marginally expands its labour catchment area in case of a two-hour trip, as two hours of travel time get you to the island of Femern on the German side of the belt, with some 17,000 persons. On a two-hour trip from Maribo, you reach Lübeck, Kiel and Hamburg. In this case, Hamburg is the largest labour catchment area. Maribo hereby accesses a labour catchment area of 2,158,000 persons. On a two-hour trip from Nykøbing Falster, you reach both Lübeck and Kiel and a catchment area of 708,000 persons. It is worth noting that by travelling slightly longer than two hours, Hamburg is also reachable. As to Næstved, a two-hour trip accesses a labour catchment area of 98,000 persons. If we look at destinations on the German side of Fehmarnbelt, changes in the labour catchment area caused by the new transportation system are relatively small in most situations: In absolute numbers, the biggest change happens to Oldenburg in Holstein, which expands its labour catchment area by 22,000 persons at a one-hour trip and by 270,000 persons at a two-hour trip. 23

24 Hamburg slightly expands its labour catchment area by 22,000 persons at a twohour trip, as a labour catchment area in Maribo becomes accessible. Kiel expands its labour catchment area by 57,000 persons. On a two-hour trip from Kiel, almost all of the labour catchment areas on the island of Lolland and on parts of the island of Falster becomes accessible. Among the German destinations, Lübeck achieves the largest expansion of its labour catchment area as a consequence of the new transportation system, since it gains access to an additional 98,000 persons at a two-hour trip. Lübeck is connected to Southern Zealand, so a slightly longer commute could get you to Næstved. The following tables and maps present the results of the calculations for each destination. City indicates the city whose catchment area is calculated. 24

25 City Catchment area Basis After 2022 Change (persons) Change in % Copenhagen 1 hour 1,906,000 1,906,000-0% Copenhagen 2 hours 2,673,000 2,690,000 17,000 1% Figure 3-2: Commuting to Copenhagen. Respectively wihin one or two hours travel time. City Catchment area Basis After 2022 Change (persons) Change (%) Maribo 1 hour 156, ,000 73,000 47% Maribo 2 hours 2,014,000 4,172,000 2,158, % Figure 3-3: Commuting to Maribo. Respectively within one or two hours travel time. 25

26 City Catchment area Basis After 2022 Change (persons) Change (%) Nykøbing Falster 1 hour 209, ,000 26,000 12% Nykøbing Falster 2 hours 2,156,000 2,872, ,000 33% As regards Nykøbing Falster, a combination of train and car will be the fastest trip for some 8,000 persons. In the map, this area is marked in red. Figure 3-4: Commuting to Nykøbing Falster. Respectively within one or two hours travel time. City Catchment area Basis After 2022 Change (persons) Change (%) Næstved 1 hour 1,317,000 1,317,000-0% Næstved 2 hours 2,656,000 2,754,000 98,000 4% Figure 3-5: Commuting to Næstved. Respectively within one or two hours travel time. 26

27 City Catchment area Basis After 2022 Change (persons) Change (%) Hamburg 1 hour 3,159,000 3,159,000-0% Hamburg 2 hours 8,300,000 8,322,000 22,000 0% Figure 3-6: Commuting to Hamburg. Respectively within one or two hours travel time. City Catchment area Basis After 2022 Change (persons) Change (%) Kiel 1 hour 1,843,000 1,843,000-0% Kiel 2 hours 4,845,000 4,902,000 57,000 1% Figure 3-7: Commuting to Kiel. Respectively within one or two hours travel time. 27

28 City Catchment area Basis After 2022 Change (persons) Change (%) Lübeck 1 hour 2,855,000 2,855, % Lübeck 2 hours 6,239,000 6,337,000 98,000 2% Figure 3-8: Commuting to Lübeck. Respectively within one or two hours travel time. City Catchment area Basis After 2022 Change (persons) Change (%) Oldenburg 1 hour 801, ,000 22,000 3% Oldenburg 2 hours 4,230,000 4,500, ,000 6% Figure 3-9: Commuting to Oldenburg, Holstein. Respectively within one or two hours travel time. 28

29 3.3 SUMMARY As the findings in section 3.2 demonstrate, the improved transportation system within the Green String Corridor will entail minor changes in the access to labour within the corridor, especially when it comes to labour within what is considered normal commuting travel time. Naturally, this analysis looks at a number of examples of commuting potentials for certain select cities, so the analysis does not uncover the entire potential; rather, it illustrates the key potentials. The basis for the findings is that the major improvements of the transportation occur with the establishment of the fixed link across Fehmarnbelt, and that other improvements of the transportation system only slightly affect the expansion of labour catchment areas. The primary cause of this small, immediate effect is first and foremost that the population density and thereby the size of the labour force is relatively small in the areas that see the biggest improvements of the transportation system. Consequently, there might be good reason for examining labour market effects of commuting over larger distances, e.g. so-called weekly commuting where major labour catchment areas in the Oresund region and Hamburg are brought into play more. However, it should be noted that for passenger transport between the two metropoles, commuting options already exist via air travel, which may turn out to be competitive, especially as regards travel time and often the price as well. 29

30 4. EDUCATION AND INCOME IN THE GREEN STRING CORRIDOR The analysis in chapter three focused on improvements in travel time within the transportation corridor between the Oresund area and Hamburg and on the increased potential for commuting within the corridor thanks to the new transportation system. The commuting potential was first uncovered by mapping travel times for seven major cities for the total population, ages 16 to 65, within the corridor. The desk research indicated a clear link between educational level, income level and commuting: The higher the educational level and income level, the greater the possibilities of the labour force choosing to commute. This chapter presents the findings of a mapping of variances regarding educational level and income level within the transportation corridor. The purpose of this part of the analysis is to more closely uncover the actual commuting potential within the transportation corridor, i.e. to what extent a link exists between improved travel times and the labour force s presumed willingness to commute. 4.1 INDICATIONS OF THE RECRUITMENT BASIS First and foremost, the educational level and income level provide rough indications of the recruitment basis. In some situations and in some sub-labour markets, longdistance commuting does take place, despite a relatively low educational level. For instance, builders have a tradition of commuting across relatively long distances often in connection with weekly commuting. Especially craftsmen from German and other countries east and south of Denmark have a tradition of commuting to Denmark, and the improved transportation system will give them more incentives to commute to Denmark. 4.2 EDUCATIONAL LEVEL This section describes the educational level in the Green String Corridor. This offers insight into the educational level in different areas, thereby uncovering the commuting potential. To determine the educational level in different areas, data from Statistics Denmark have been used regarding the highest completed education of the population. Figure 4-1 illustrates the share of 15- to 69-year-olds that has completed a medium-cycle higher education or a long-cycle higher education. 30

31 The horizontal line in the figure at 26 per cent illustrates what share of the 15- to 69-year-olds in the Capital Region of Denmark and Region Zealand has completed a medium-cycle higher education, as a minimum. The share in the Capital Region of Denmark (30 per cent) is, though, almost twice as large as that of Region Zealand (18 per cent). Large variations exist between the different municipalities in Region Zealand. In the Municipality of Lolland, only 12 per cent of the 15- to 69-year-olds have completed a medium-cycle or long-cycle higher education, whereas share in Næstved is 18 per cent. Figure 4-1 Share of 15- to 69-year-olds who have completed a medium-cycle or long-cycle higher education by % 30% 27% 30% 25% 20% 15% 18% 12% 16% 18% 16% 17% 17% 18% 10% 5% 0% Source: Statistics Denmark - KRHFU1. Note1: The horizontal line illustrates the average share of persons with a medium-cycle or long-cycle higher education in Region Zealand and the Capital Region of Denmark (26%). Note2: The appendix contains more information on the educational level of this age group. Figure 4-2 illustrates the educational level of persons ages 25 to 64. In this age group, the share of persons on the labour market is significantly higher than for persons ages 15 to 69, as that group numbers many undergoing training. Figure 4-2 shows a tendency of lower educational level, the further away from Copenhagen you are. Especially the Municipality of Lolland demonstrates a significantly lower educational level. 31

32 Figure 4-2 Share of 25- to 64-year-olds who have completed a medium-cycle or long-cycle higher education by 2012 > < 18 Source: Statistics Denmark - KRHFU1. The appendix contains more information on the educational level of the 25- to 64- year-olds. It appears that 415,000 persons in Region Zealand and the Capital Region of Denmark have, as a minimum, completed a medium-cycle higher education. 3,200 of these live in the Municipality of Lolland, 6,000 in the Municipality of Guldborgsund, and 8,900 in the Municipality of Næstved. Table 4-1 compares the educational level in Denmark with the level in Germany. As indicated in the table, a relatively higher percentage in Denmark have a tertiary education (as a minimum, a short-cycle higher education) compared to Germany. It is also evident that the share of persons with a tertiary education is lower in Hamburg than in the Capital Region of Denmark. The share of persons with a tertiary edu- 32

33 cation in Region Zealand is lower than in Hamburg, but higher than in Schleswig- Holstein. Table 4-1 Educational level in select areas in Denmark and Germany. Percentage of the specified target group. The number of students in a tertiary education, stated at the share of the total population of 20- to 24-year-olds in the region The share of 30- to 34-year-olds in the region with a tertiary education The share of 25- to 64-year-olds in the region with a tertiary education Region Zealand Capital Region of Denmark Denmark Schleswig-Holstein Hamburg Germany Source: Eurostat Note: In Denmark, a person who has completed a tertiary education is defined as a person who has, as a minimum, completed a short-cycle higher education. The appendix describes the development over time in educational level for the different areas. Most areas see an increasing educational level over time. However, in Region Zealand, the share of 30- to 34-year-olds with a tertiary education has not gone up as much as in other areas. 4.3 ATTACHMENT TO LABOUR MARKET Another important factor that highly affects commuting is attachment to labour market. The figures in table 4-2 show that especially the youth unemployment rate (ages 15 to 24) is higher in Denmark than in Germany. This goes for both Region Zealand and the Capital Region of Denmark. Comparing the unemployment rate for 20- to 64-year-olds, the difference between Denmark and Germany is smaller. Especially the unemployment rate for this age group in Region Zealand is close to the German level. 33

34 Table 4-2 Unemployment rates in select areas in Denmark and Germany 2012 unemployment rates for 15- to 24-year-olds 2012 unemployment rates for 20- to 64-year-olds Region Zealand Capital Region of Denmark Denmark Schleswig-Holstein Hamburg Germany Source: Eurostat Note: The appendix illustrates unemployment rated in the period from 2010 to Figure 4-3 shows the socioeconomic status of citizens in different areas in The figure shows that 63 per cent are self-supporting in the Municipality of Lolland, whereas the share of self-supporting persons in Region Zealand as a whole is 75 per cent. Figure 4-3 Socioeconomic status of 25- to 64-year-olds, categorised by area of residence in 2012 Source: Statistics Denmark - RASU33. 34