1 Introduction

Migration depends partly on the attractiveness of a region as a place to live. Not only highly skilled persons but also pensioners who want to spend their retirement age at the countryside, at the shores or other attractive places account for a large percentage of European migration flows. These flows are nearly independent of the economic situation of regions. Therefore the Migration Submodel includes an exogenous quality of life indicator. This indicator is a composite indicator derived from a multi-criteria analysis.

The indicator compares three categories, Climate, Landscape and Tourist Facilities, which are composed of three subindicators each.

The climate category considers the fact that retirement migration prefer regions with rather warm and rainless climate. The beauty and variety of the landscape plays also a prominent role. Last but not least the number and the degree of development of leisure and tourist facilities is also an import point for many people in their decisions regarding migration targets.


2 Subindicators

The following nine subindicators have been integrated (with the categories given in brackets):

-	Temperature (climate). The temperature subindicator gives the long- time average temperatures in July taken from Westermann (1997) expressed in degrees centigrade.
-	Sunshine (climate). The daily global radiation on the ground is used as a proxy for sunshine, because information on the number of sunshine hours for the entire European continent is not available. The radiation data are given as the average over all months of the years 1966-1975 in kWh/m2 and are taken from Palz and Greif (1995).
-	Rainfall (climate). The rainfall subindicator is measured as the long- time average yearly amount of rain in millilitres and is based on Westermann (1997).
-	Slope gradient (landscape). The average slope gradients are used as the first proxy for the surface variety. They are derived from a European three-dimensional surface elevation model produced at IRPUD (1998) and are measured in percentage slope.
-	Elevation differences (landscape). The elevation differences are used as the second proxy for the surface variety and are also taken from the European three-dimensional surface elevation model (IRPUD 1998). They are calculated as the difference between the maximum and minimum elevation within one region and are measured in meters. - Open space (landscape). The open space subindicator gives the percentage of open space of the area of a region. Open space includes all forest areas as well as the utilised agricultural areas and arable land. The data are taken from Eurostat (1998).
-	Tourist area (tourist facilities). The tourist area subindicator represents the degree of development of regions with (soft) tourist facilities such as footpaths, resting places, hotels, other recreation facilities, mountain railways, tourist information services etc. This is a qualitative indicator adopted from Ritter (1966) differentiating between (a) areas which are totally influenced and formed by tourism, (b) areas which are locally influenced and formed by tourism, (c) areas with tourism but which are only sparsely formed by tourist facilities, (d) areas which are not influenced and not formed by tourism and finally (e) agglomerations (no tourist regions).
-	Attractive towns (tourist facilities). The attractive towns subindicator counts the numbers of historical and winter sports towns as well as the number of health- and seaside resorts and relates it to the size of the region. The cities are taken from Westermann (1983).
-	Development of shores (tourist facilities). The development of shores subindicator represents the degree of the development of tourist facilities in coastal regions. Again, this is an qualitative indicator adopted from Ritter (1966) which differentiates between regions with (a) totally developed shores, (b) well developed shores, (c) sparsely developed shores, (d) no developed shores or (e) no shores at all.

Comparing the subindicators of the tourist facilities category, the

-	The tourist area subindicator considers the development of facilities of the countryside.
-	The attractive towns subindicator considers the development of facilities of the cities and agglomerations.
-	The development of shores subindicator considers the development of facilities of the seaside.

All the subindicators described are either directly derived from various sources (e.g. rainfall, temperature) or are generated by using individual generation functions (tourist areas, development of shores). However, in any case mapping functions are used to transform the observed values into utilities which are used within the multi-criteria analysis. The mapping functions used are displayed in Figure 1 in a summarised form. The X-axes give the values, while the left Y-axes show the frequencies of the values and the right X-axes show the utilities of the mapping functions.

Figure 1. Mapping functions of the nine subindicators.

3 Weighting

Figure 2 shows the hierarchy of the subindicators and the weights of the indicators in brackets. The weights are based on expert ratings. The three categories (climate, landscape, tourist facilities) are equally weighted with 33.3 percent each. Within the climate category, the subindicators temperature and rainfall have both a weight of 30 whereas sunshine has a weight of 40. Within the landscape category, the slope gradient and the elevation differences subindicators have weights of 20 and 30, respectively, i.e. taking both together as the 'relief energy', they have the same weight as the open space subindicator (50). Considering the tourist facilities category, the main subindicator is the development of shores with a weight of 50, whereas the attractive towns and tourist area subindicator have both a weight of 25. The assumption behind is, that seaside regions are more attractive than hinterland regions. Moreover, historical towns are to some extent an attraction factor but they are unlikely to be the only criterion in a migration target choice.

Figure 2. Hierarchy of the quality of life indicator.

4 Results

Figure 3 shows the overall results of the multi-criteria analysis, i.e. the quality of life indicator. Some of the Mediterranean regions of France, Italy and Spain obtain the highest values. The south of Italy is slightly decreasing in comparison to the northern parts, mainly because the climate is too extreme (temperatures are too high, almost no rainfall) and because of the Naples agglomeration area. The Spanish dry hinterlands obtain values between 45 and 60 points, i.e. lower values in comparison to the coastal regions. Some regions in Germany (Oberbayern, Arnsberg, Braunschweig) obtain also relatively high values mainly because of their surface variety and open space, while other German regions obtain values between 45 and 60 points with the exception of the three city- states Berlin, Hamburg and Bremen. Similarly, most of the Benelux regions obtain only values between 30 and 45 points (flat relief, low share of open space). In Austria, Tirol and Salzburg show also values between 30 and 45 points, because of the high amount of rain. The north of Scandinavia, Scotland and Ireland obtain the smallest values, because of their climatic conditions.


5 Development over Time

It is assumed that the quality of life indicator is an exogenous, static-in- time indicator, which is not predicted endogenously by the SASI Model. There are several reasons for doing so:

-	The climate can be considered to stay constant over the forecast period, although there might be changes in the climate. These changes, however, take place slowly over long time periods, so that the three climate subindicators can be assumed to be constant.
-	Similarly to the climate category, changes in the relief energy evolve in time periods far beyond people's imagination. Again, both relief energy subindicators can be assumed to stay constant. The share of open space might significantly change within the modelling period, but taking all subindicators of this multi-criteria analysis together, open space has a relatively low weight, so that again the assumption to remain constant seems to be justifiable.
-	The three tourist facilities subindicators are qualitative indicators measuring the degree of development of the regions. It can be assumed that changes in the degree of development of one particular region is a matter of many years, and moreover, if development takes place these development will take place in regions which are already highly developed, these three subindicators can also be assumed to remain constant over the modelling period.

Figure 3. Spatial distribution of the quality of life indicator.

References

Eurostat (1997): Regions. Statistical Yearbook. Luxembourg: Office for Official Publications of the European Communities.

Eurostat (1998): Regio Database. Luxembourg: Office for Official Publications of the European Communities.

Institut für Raumplanung, Universität Dortmund (1998): Pan-European Surface Model. Dortmund: IRPUD

Pan, W., Greif, J. (1995): European Solar Radiation Atlas. Solar Radiation on Horizontal and Inclined Surfaces. 3rd Revised Edition sponsored by DGXII of the Commission of the European Communities. Berlin, Heidelberg, New York: Springer.

Ritter, W. (1966): Fremdenverkehr in Europa. Eine wirtschafts- und sozialgeographische Untersuchung über Reisen und Urlaubsaufenthalte der Bewohner Europas. Europäische Aspekte. Eine Schriftenreihe zur europäischen Integration herausgegeben mit Förderung des Europarats. Reihe A: Kultur, No. 8. Leiden: A. W. Sijthoff.

Westermann (1983): Diercke Weltatlas. Braunschweig: Westermann, 998-999.

Westermann (1997): Diercke Weltatlas. Braunschweig. Westermann, 116-117.



© 1999 Carsten Schürmann, IRPUD

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