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January 7, 2008
Region:
Happy regions in Germany share many things in common: they all score well not only in terms of life satisfaction, but also with regard to trust in fellow citizens, state of health, unemployment, birth rate and income. This is in line with DB Research’s analysis at country level. The regions of Donau-Iller, Ostwuerttemberg, Osnabrueck and Hamburg-Umland-Sued achieve particularly good scores. There are no urban agglomerations in the uppermost ranks, though. The east German regions bring up the rear in this ranking. Our analysis suggests that well-being can be shaped and fostered on a regional/decentralised basis with a comprehensive policy approach. [more]
Well-being in Germany: Its happy regions have much in common ****** *** * * * * * **** * **** * Author Stefan Bergheim +49 69 910-31727 stefan.bergheim@db.com Assistance Michael Ziegelmeyer Editor Stefan Schneider Technical Assistant Pia Johnson Deutsche Bank Research Frankfurt am Main Germany Internet: www.dbresearch.com E-mail: marketing.dbr@db.com Fax: +49 69 910-31877 Managing Director Norbert Walter January 7, 2008 Happiness research is gaining an ever higher profile in the public domain: international organisations, the president of Germany and – increasingly – schools have lent new impetus to the issue of late. ** ***** * ***** ** * ***** *** **** ***** ** ******* Not only the degree of life satisfaction, but also the degree of trust in fellow citizens, the state of health, unemployment, birth rate and income all score well. This is in line with DB Research’s analysis at the country level. ** * ***** ** ********* **** * * ** *** ******* ** ** !*******"**** *#* **** *** ******** *** These regions top the list in DB Research’s ranking of well-being in Germany. No urban agglomerations make it into the top ranks. ** ** * **** * ***** ***** ** * * ** ** *** ******** A low degree of life satisfaction goes hand in hand with a low degree of trust in fellow citizens, poor health, high unemployment, low birth rate and low income. ***** * *** * ** * ** * * ******$ * * ***** ****** The significant regional differences suggest that political and societal conditions (as well as changes in them) are determined in the regions. Transfers – determined at federal level * alone are obviously not enough. The close correlation between the variables relevant for human well-being suggests taking a comprehensive approach to policy: high birth rates are not very probable if unemployment is high and there is little trust in fellow citizens. Simply providing lots of day-care facilities will not be the solution. % **** *** ** * ***** Its happy regions have much in common 1.1 1.2 1.3 1.4 1.5 1.6 1.7 5.9 6.2 6.5 6.8 7.1 7.4 &** ** ***** *** ** *** * ** Sources: SOEP, BBR, DBR calculations Life satisfaction in 2003 (0=low to 10=high), birth rate in 2001/02/03, 97 mean values in RORs Birthrate Life satisfaction Current Issues 2 January 7, 2008 '** ** ** ***** ** ****** © BBR Bonn 2004 Colour coding by DBR; see legends on pages 8 and 9 ROR border No. of ROR '** ** ** ***** ** ****** © BBR Bonn 2004 Colour coding by DBR; see legends on pages 8 and 9 ROR border No. of ROR Well-being in Germany January 7, 2008 3 OECD and EU advocate broadly based measures of well-being Happy societies have much in common Commonalities also at the regional level Data available on life satisfaction, trust in fellow citizens, health, unemployment rate, birth rate and income *** *** ***** ** ** **** * Analysis of life satisfaction using broadly based measures of well- being is steadily increasing in importance, and is now also a priority of international organisations. At the end of June, participants in the OECD’s Second World Forum adopted the Istanbul Declaration, calling for a broadly based analysis of societal well-being and its evolution over time. 1 And in mid-November the EU hosted a conference in Brussels entitled “Beyond GDP”. 2 This area of research is attracting more attention in Germany, too. For example, Germany’s president Horst Köhler entitled his Berlin Address “The pursuit of happiness changes the world” and a school in Heidelberg has started to offer a “Happiness” course. Deutsche Bank Research has already flagged up this trend in two studies. 3 “The happy variety of capitalism” showed that countries with a high level of human happiness are characterised by an array of commonalities. All happy societies typically have a high degree of trust in fellow citizens, a low amount of corruption, low unemploy- ment, a high level of education, high income, a high employment rate of older people, a small shadow economy, extensive economic freedom, low employment protection and a high birth rate. The countries may have many more characteristics in common, but it is difficult to capture these in statistics. 4 Array of commonalities within a country There are, however, substantial cultural differences between countries, which suggest that a factor outside the model might be responsible for the commonalities observed between the different varieties of capitalism. This raises the question of whether the correlations can also be observed within a country, where cultural differences are presumably less pronounced. Indeed, similar correlations can be found for Germany’s 97 Raumordnungsregionen (RORs), the geographic regions officially defined by the Federal Office for Building and Regional Planning (BBR); however, categorising them in groups is – not surprisingly – not as easy as at the country level. Analysis is also hampered by the fact that an ROR may group together towns and districts that have entirely dissimilar characteristics. Not all of the data available at the country level is also available for Germany’s RORs: factors such as corruption, years of education, employment rate of older people, shadow economy, economic freedom and employment protection cannot be used. So along with life satisfaction this leaves trust in fellow citizens (these first two readings are the result of surveys), the unemployment rate, the birth rate and income. In addition, data is available from a survey on health – which Germans consider the most important aspect of life. 5 1 www.oecd.org/oecdworldforum/Istanbul 2 www.beyond-gdp.eu 3 Bergheim, Stefan (2006). Measures of well-being: There is more to it than GDP. DB Research. Deutsche Bank Research. Current Issues. September 8, 2006. And Bergheim, Stefan (2007). The happy variety of capitalism. Current Issues. April 25, 2007. Frankfurt am Main. 4 Robert Putnam would probably also expect to find a large number of newspaper readers, high membership of football leagues and high voter turnout; see “Bowling Alone”, chapter 21. 5 See Eurobarometer 66 and Bergheim, Stefan (2006). Live long and prosper! DB Research. Current Issues. March 20, 2006. Frankfurt am Main. Current Issues 4 January 7, 2008 Ranking of well-being in Germany Top ranks for Donau-Iller, Ost- wuerttemberg, Osnabrueck and Hamburg-Umland-Sued In and around Ulm West Germany scores higher on well-being All in all, three survey findings and three “hard” numbers may be combined. The data come from the German Socio-Economic Panel Study (SOEP) or the INKAR database of the Federal Office for Building and Regional Planning; they are presented in further detail in the appendix starting on page 10. There is also a weak correlation between life satisfaction and longevity as well as between life satisfaction and the share of foreigners in the population. Religiosity shows a correlation with life satisfaction only in a comparison of east and west Germany, but not among the west German regions. Of course, there are many other aspects that are also important for human well-being. However, there are no readings available for them at the ROR level. The regions of well-being: Donau-Iller, Ostwuerttemberg, Osnabrueck and Hamburg-Umland-Sued The variables relevant for well-being correlate very strongly with one another, as illustrated in figures 1 to 5. Life is likely to be particularly pleasant in the regions which score well on all six aspects. An overview of the RORs can be found in the DB Research ranking detailed in the map on page 2 and in the table on pages 8 and 9. The methods used are explained in the appendix on page 10. The 14 RORs with the best overall ranking are depicted on the map, in the figures 1 through 5 and in the table on pages 8 and 9 in dark blue, with the shading of blue becoming lighter after every group of 14. Topping the list are the two neighbouring regions called Donau-Iller which include the city of Ulm and its environs in the federal states of Baden-Wuerttemberg und Bavaria. They are followed by Ostwuerttemberg in 3 rd place, Osnabrueck and Hamburg-Umland- Sued. In these regions, all six variables are above the average. Of course, no single ROR ranks first in all six categories – each one has its strengths and weaknesses. The inhabitants of the Donau-Iller region of Bavaria consider themselves particularly healthy, while Osnabrueck has a particularly high degree of life satisfaction and the south of Hamburg a particularly high birth rate. Leading by a nose in the overall analysis is Region 74, i.e. Donau- Iller in Baden-Wuerttemberg with its over 500,000 inhabitants in the city of Ulm and the surrounding districts of Biberach and Alb-Donau. The degree of life satisfaction there is not extremely high, but the degree of trust in fellow citizens and the health scores are excellent. The vast majority of people have a job and the birth rate, at 1.5 for 2001 to 2003, was far above the German average. The share of foreigners is above average, and net immigration clearly positive. Visible divide between east and west Germany The map of Germany on page 2 shows a clear divide between the western and eastern parts of the country. The regions marked in dark blue that top the ranking are all located in the western and southern parts of west Germany. Regions such as 50 Osthessen and 73 Hildesheim are halfway down the list. The many east German regions at the low end of this ranking show yet again that there is no such thing as uniform living conditions in Germany even under a broad definition of the term. The relevant determinants of well-being are all very weak in the east. Well-being in Germany January 7, 2008 5 Trust and life satisfaction go hand in hand Happy and healthy people Unhappy unemployed 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 5.96.26.56.87.17.4 &************** ********* ***(** Sources: SOEP, DBR calculations Satisfaction (0=low to 10=high), "One can trust people" (1=totally agree to 4=totally disagree), mean values in RORs Trust Life satisfaction ) 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 5.9 6.2 6.5 6.8 7.1 7.4 1-14 15-28 29-42 43-56 57-70 71-84 85-97 &** ***** ***** ** * *** Sources: SOEP, DBR calculations Satisfation in 2003 (0=low to 10=high), health in 2003 (1=very good to 5=bad); 97 mean values in RORs Health Life satisfaction * 3 7 11 15 19 23 27 5.96.26.56.87.17.4 &************** ********* Sources: SOEP, BBR, DBR calculations Life satisfaction in 2003 (0=low to 10=high), unemployment rate (%) in 2003, 97 mean values in RORs Unemployment Life satisfaction + Current Issues 6 January 7, 2008 Urban agglomerations with high incomes, but weaker along other dimensions Both high and low degrees of trust in east German regions Migration flows to regions of well- being Comprehensive approach needed Medium-density regions score better than urban agglomerations A cluster analysis of all 97 RORs reveals further information about commonalities and differences between the regions of Germany. For example, it is possible to differentiate between regions of medium population density and urban agglomerations. In the medium- density regions (38 Arnsberg and 97 Suedostoberbayern are prototypes for regions in this cluster), all 6 variables show very high scores, but particularly the assessment of personal health. The population density in this cluster, at 210 inhabitants per square kilometre, is lower than the west German average of 264. By contrast, the agglomerations (prototypes being 86 Industrie- region Mittelfranken and 43 Bochum/Hagen) score very well especially on income, whereas other aspects are less positive. In this cluster, the population density averages over 560 inhabitants per square kilometre. The upper echelons of the ranking on page 8 contain regions where population density is only average – the first agglomeration to appear is in 22 nd place (Stuttgart). Among the regions at the lower end of the table it is also possible to differentiate two clusters. In some regions all the variables are relatively weak (prototypes being 32 Magdeburg and 53 Nord- thueringen), while in another group the degree of trust in fellow citizens is above average (prototypes being 29 Havelland and 60 Chemnitz-Erzgebirge). Higher real estate prices do not fully compensate Theoretically, migration from less happy regions to happy regions should push up real estate prices in the happy regions and, by pushing down real income, help to reduce the differences in life satisfaction. However, for the regions in our ranking this is not the case. The regions in the upper echelons post net immigration on average (and those in the lower echelons post net emigration), suggesting that the currently used models of internal migration need to be augmented. 6 But it is possible in many regions with a high ranking of well-being to obtain building land at a relatively low price: from 2001 to 2003 the price of building land in the 10 highest-ranking regions averaged less than EUR 100 per square metre – in the regions ranking 21 st to 30 th , by contrast, it was over EUR 200. 7 The price increase between 1995/96 and 2002/03 also fails to follow the pattern suggested by the analysis of well-being. It appears that differences in income play a dominant role. Decentralised initiatives can make a difference The table on pages 8 and 9 indicates the respective strengths and weaknesses of all 97 RORs. For a region to be able to advance in the table, a comprehensive approach is necessary: a high birth rate is rather unlikely alongside a high unemployment rate. It is also clear that the level of well-being has a regional/ decentralised basis and can be fostered there. The big differences across Germany and also within its constituent states suggest that development does not have to originate at the national or state level. 6 See Bergheim, Stefan (2003). Migration in Germany: redistribution of a shrinking population. Deutsche Bank Research. Current Issues. May 22, 2003. Frankfurt am Main. 7 The price of building land is strongly subject to political influence, which limits the informative value here. House prices are not available at the level of the RORs. Well-being in Germany January 7, 2008 7 More income in happy regions More children in happy regions Rather, local initiatives can make a substantial contribution to well- being – as presumably can the maintenance of social structures that have grown over time. Examples could conceivably include close cooperation between job centres and business or between district administrations and sport clubs. Civic engagement in educational and healthcare issues can also play a part, as for example in the district of Biberach. The possibilities are virtually endless and emphasis should be attached to continuing the many existing initiatives. In any event, transfers alone are not the answer. A host of unanswered questions The broadly based analysis of human happiness is a relatively new field of research in which a host of questions remain unanswered. It is seldom clear whether there is a causal link behind every correlation. And the historical and cultural roots of the differences observed between the regions generally go very deep – changes can presumably only come about over a long period. In many (east German) regions there may already be changes in the works which are not yet reflected in the data. The correlations shown here between “hard” and “soft” variables merit further attention, though. 1.1 1.2 1.3 1.4 1.5 1.6 1.7 5.9 6.2 6.5 6.8 7.1 7.4 &** ******* *** ** **** ** Sources: SOEP, BBR, DBR calculations Life satisfation in 2003 (0=low to 10=high), birth rate in 2001/02/03, 97 mean values in RORs Birth rate Life satisfaction , 1100 1200 1300 1400 1500 1600 1700 1800 5.9 6.2 6.5 6.8 7.1 7.4 1-14 15-28 29-42 43-56 57-70 71-84 85-97 &** ***** ***** ** ***** Sources: SOEP, BBR, DBR calculations Life satisfaction in 2003 (0=low to 10=high), household income in EUR in 2003, 97 mean values in RORs Income Life satisfaction - Current Issues 8 January 7, 2008 .****** ** **** *** ** ******* *** ) (ranks) No. ROR Rank Satisfaction Trust Health Unemploym. Birth rate Income 74 Donau-Iller (Baden-Wuertt.) 1 28 74616 21 94 Donau-Iller (Bavaria) 2 3 34 1 11 9 38 73 Ostwuerttemberg 3 43 8 3 23 15 24 18 Osnabrück 4 2 4 63 29 22 15 14 Hamburg-Umland-Sued 5 11 10 19 27 4 27 38 Arnsberg 6 29 31 8 44 8 20 36 Bielefeld 7 22 9 57 58 10 5 75 Neckar-Alb 8 31 70 2 12 42 12 16 Oldenburg 9 5 17 27 46 5 56 66 Rheinpfalz 10 14 26 5 31 52 35 96 Oberland 11 1 40 66 1 34 13 79 Bodensee-Oberschwaben 12 42 18 17 4 23 26 84 Oberfranken-Ost 13 8 2 10 61 66 42 35 Muenster 14 6 19 64 33 26 22 47 Siegen 15 4 72 35 30 28 7 71 Nordschwarzwald 16 46 57 13 16 25 11 82 Main-Rhoen 17 7 12 33 32 20 64 68 Unterer Neckar 18 34 1 15 38 85 31 97 Suedostoberbayern 19 23 46 9 7 38 37 2 Schleswig-H. Sued-West 20 56 3 23 64 6 69 83 Oberfranken-West 21 39 5 24 45 48 29 72 Stuttgart 22 35 37 65 5 47 3 89 Ingolstadt 23 52 33 30 3 11 46 95 Allgaeu 24 9 93 6 9 24 41 93 Muenchen 25 58 23 73 8 70 1 80 Bayerischer Untermain 26 17 61 18 24 33 30 5 Schleswig-Holstein Sued 27 18 62 43 41 31 10 51 Rhein-Main 28 26 54 21 39 53 18 86 Industrieregion Mittelfranken 29 16 44 37 48 64 8 70 Mittlerer Oberrhein 30 54 13 41 20 72 19 46 Bonn 31 62 25 32 25 51 16 76 Schwarzwald-Baar-Heuberg 32 63 74 67 10 12 9 43 Bochum/Hagen 33 25 27 51 65 41 17 77 Suedlicher Oberrhein 34 19 29 45 14 63 36 44 Koeln 35 15 68 25 62 56 14 42 Duesseldorf 36 37 47 69 53 54 4 85 Oberpfalz-Nord 37 47 36 20 40 30 68 62 Mittelrhein-Westerwald 38 48 39 46 28 27 44 12 Ost-Friesland 39 50 55 12 69 3 86 17 Emsland 40 27 24 94 37 1 74 1 Schleswig-Holstein Nord 41 20 59 40 52 17 70 11 Bremen 42 36 35 47 72 80 2 65 Westpfalz 43 55 28 16 51 45 65 92 Landshut 44 89 15 53 2 32 45 81 Wuerzburg 45 21 22 58 17 84 50 13 Bremerhaven 46 40 75 29 71 7 62 20 Suedheide 47 41 79 77 50 2 43 67 Saar 48 10 56 34 49 78 52 69 Franken 49 60 78 88 19 18 23 3 Schleswig-Holstein Mitte 50 64 50 7 63 58 63 41 Duisburg/Essen 51 44 49 44 67 46 40 52 Starkenburg 52 67 51 59 34 44 32 90 Regensburg 53 69 43 28 18 50 54 78 Hochrhein-Bodensee 54 32 53 78 13 71 34 87 Westmittelfranken 55 49 60 87 21 19 67 6 Hamburg 56 59 14 90 55 90 6 Sources: SOEP, BBR, DBR calculations / Well-being in Germany January 7, 2008 9 .****** ** * ****** ** ******* *** * 0*****1 No. ROR Rank Satisfaction Trust Health Unemploym. Birth rate Income 19 Hannover 57 45 80 26 57 65 28 63 Trier 58 51 20 81 15 60 77 48 Nordhessen 59 12 45 84 56 55 61 21 Lueneburg 60 30 21 89 66 49 55 40 Emscher-Lippe 61 13 77 48 74 39 60 15 Bremen-Umland 62 83 83 76 42 13 39 22 Braunschweig 63 38 69 75 60 40 48 39 Dortmund 64 24 42 85 75 37 58 64 Rheinhessen-Nahe 65 65 82 62 36 57 33 24 Goettingen 66 53 30 54 68 79 57 37 Paderborn 67 82 76 80 47 14 49 88 Augsburg 68 93 66 82 26 29 25 50 Osthessen 69 61 81 92 35 21 59 49 Mittelhessen 70 70 52 68 43 61 53 4 Schleswig-Holstein Ost 71 75 65 14 70 67 66 45 Aachen 72 87 48 70 59 36 51 23 Hildesheim 73 57 92 79 54 35 47 31 Altmark 74 33 11 31 92 69 95 54 Mittelthueringen 75 78 32 11 82 82 82 29 Havelland-Flaeming 76 68 38 61 76 81 73 10 Mecklenburgische Seenplatte 77 66 6 36 97 75 94 91 Donau-Wald 78 76 97 50 22 43 72 60 Chemnitz-Erzgebirge 79 84 41 38 81 68 80 30 Berlin 80 71 16 60 84 95 76 55 Suedthueringen 81 80 71 39 73 91 75 58 Oberes Elbtal/Osterzgebirge 82 85 73 56 78 73 71 7 Westmecklenburg 83 86 87 52 77 62 93 33 Dessau 84 73 85 22 89 94 89 57 Westsachsen 85 77 58 72 85 93 85 59 Oberlausitz-Niederschlesien 86 97 63 49 93 59 90 56 Ostthueringen 87 74 96 42 79 92 79 32 Magdeburg 88 81 84 74 86 86 88 28 Lausitz-Spreewald 89 72 67 83 91 97 92 61 Suedwestsachsen 90 92 88 91 80 76 83 53 Nordthueringen 91 88 90 86 83 74 97 9 Vorpommern 92 79 91 71 96 83 96 27 Oderland-Spree 93 91 95 55 87 96 78 25 Prignitz-Oberhavel 94 96 89 95 88 77 81 34 Halle/S. 95 90 86 96 95 87 87 26 Uckermark-Barnim 96 95 64 97 94 89 84 8 Mittleres Mecklenb./Rostock 97 94 94 93 90 88 91 Sources: SOEP, BBR, DBR calculations 2 Current Issues 10 January 7, 2008 ******** **** *3 1. Data definitions Life satisfaction: Defined by response to last question in a survey conducted by the Socio-Economic Panel (SOEP) of the Berlin- based Deutsches Institut für Wirtschaftsforschung (DIW) in 2003: “How satisfied are you with your life, all things considered?“ on a scale of 0 (completely dissatisfied) to 10 (completely satisfied). The data at the Raumordnungsregion level (ROR: region of Germany as defined by the Federal Office for Building and Regional Planning, BBR) were aggregated by DB Research. Given the sometimes very small size of the random samples, not all of the values for the regions are statistically sound. Trust: Response to the question “What is your opinion on the following (...) statement(s)? ‘On the whole one can trust people’” on a scale of 1 (totally agree) to 4 (totally disagree). Source: SOEP. Health: Response in 2003 to the question “How would you describe your current health?” on a scale of 1 (very good) to 5 (bad). Source: SOEP. Unemployment rate: Unemployed as a percentage of the total labour force in 2003. Source: Indikatoren und Karten zur Raumentwicklung 2005 (INKAR 2005) of the Federal Office for Building and Regional Planning (BBR). Birth rate: Fertility rate as the consolidated birth rate for the years 2001-03. Source: INKAR 2005. Income: Disposable income per household including transfers in 2003. Source: INKAR 2005. The correlations between these data are in some cases very high, as can be seen in Table 8. 2. Calculation of ranking To consolidate the six variables into an overall ranking they were first standardised: the mean value was subtracted from each variable across all 97 RORs and then divided by the standard deviation across the RORs. The results have a mean value of zero and the identical standard deviation of one. Then, for each region, the values for the six variables were added. The ranking in the table on pages 8 and 9 was set according to this sum. 8 8 See “Handbook on constructing composite indicators: methodology and user guide” (OECD Statistics Working Paper 2005-3) on the advantages and disadvantages of different weighting procedures. ****** **** * * * / ******** Trust Health Unemploym. Birth rate Income Satisfaction -0.5 -0.4 -0.6 0.4 0.5 Trust 1 0.3 0.3 -0.2 -0.3 Health 1 0.3 -0.2 -0.2 Unemployment 1 -0.6 -0.7 Birth rate 1 0.3 Income 1 Source: Deutsche Bank Research For trust and health, low values mean strong trust and good health 4 Well-being in Germany January 7, 2008 11 The overall ranking changes little if individual variables out of the six are disregarded. If the unemployment rate is taken out of the data set, the regions change their ranking by only 3.3 places on average. The biggest change comes when the overall state of health is left out. The rank then changes by 5.3 places on average. Of course, individual regions change in some cases to a considerably greater degree. If income is left out, for instance, Munich slips from 25 th place down to 50 th . All in all, the ranking thus seems fairly robust. However, regions directly adjacent to each other in the table should not be compared with one another in their overall ranking. 3. Comparisons over time are not always possible As in the study “The happy variety of capitalism” it would also make sense to analyse the changes at the ROR level over time. However, not all of the data used are also available for the mid-1990s. Moreover, the ongoing convergence between east and west Germany makes comparisons more difficult: in the east German regions the birth rate rose considerably over the past 10 years – from a very low basis – and incomes jumped. In west Germany, developments in the Osnabrueck region over the past 10 years were particularly positive for life satisfaction: in contrast with the nation- wide trend, the unemployment rate fell; income growth was above average; and the birth rate rose. Much like at the country level: changes are possible! Stefan Bergheim (+49 69 910-31727, stefan.bergheim@db.com) ******* * ** Global growth centres All our publications can be accessed, free of charge, on our website www.dbresearch.com You can also register there to receive our publications regularly by e-mail. Ordering address for the print version: Deutsche Bank Research Marketing 60262 Frankfurt am Main Fax: +49 69 910-31877 E-mail: marketing.dbr@db.com © Copyright 2008. Deutsche Bank AG, DB Research, D-60262 Frankfurt am Main, Germany. All rights reserved. When quoting please cite “Deutsche Bank Research”. The above information does not constitute the provision of investment, legal or tax advice. 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