A Comparative Analysis of the Economic Performance of Greek and British Small Islands

Harvey Armstrong, Dimitris Ballas and Adreene Staines

University of Sheffield

Paper presented at the 36th Regional Science Association International (British and Irish Section)

conference, Jersey, Channel Islands, 16-18 August 2006.

Draft: Please Do Not Quote

Correspondence: Department of Geography, The University of Sheffield, Winter Street,

Sheffield S10 2TN, UK. Tel: +44 114 222 7906. Fax: +44 114 279 7912. E-mail:

h.armstrong@sheffield.ac.uk, d.ballas@sheffield.ac.uk, a.staines@sheffield.ac.uk.

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Abstract

There has been a growing interest in recent years in the nature of the economic challenges

facing island economies, and in the determinants of differences between islands in their relative

economic performance. In an EU context, this has led to special status being granted within the

EU for particular types of island economies (e.g. the Outermost Regions, six of the seven being

islands, and for wider groups of islands for the 2007-2013 Cohesion policy programmes).

Research on island economies within the EU is severely hampered by poorly harmonised

statistics within the main Eurostat data sets. This paper concentrates on two EU member states

(Greece and Britain) which have large numbers of island economies, many of which are in

highly peripheral locations with respect to the main EU markets and frequently simultaneously

having other ‘geographical handicaps’ (e.g. mountainous, comprising archipelagos etc).

National as well as EU level data are analysed to produce typologies of islands in the two

member states. These typologies are utilised to identify similarities and differences between

British and Greek small islands and to speculate on possible causes of economic performance

variations within and between the islands of these two countries.

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A Comparative Analysis of the Economic Performance of Greek and British Small Islands

1. Introduction

This paper presents preliminary results of an analysis of the relative economic performance of

two different sets of EU island economies. The first comprises some 60 offshore British small

islands, whilst the second comprises 63 offshore Greek islands. The two countries were

selected partly because there are some close similarities (particularly in respect of remoteness

from EU markets), partly because the two countries contain within them large numbers of

islands, and partly because there are some important and interesting differences with respect to

geographical characteristics of the islands which might affect economic performance.

The paper draws mainly upon 2001 data from the British and Greek population censuses,

supplemented with data from EU sources. Separate cluster analyses are conducted on the Greek

and British islands data sets.

The paper begins (section 2) with a review of the existing literature on the economic

performance of island economies, focusing in particular on the role which geographical

characteristics might play. Section 3 examines the data sets used and the method of analysis

adopted (a Ward’s method cluster analysis). The results of the cluster analysis are set out in

section 4, and similarities and differences between the Greek and British clusters discussed.

The conclusion (section 5) summarises the results and speculates on future research.

2. The Economic Performance of Islands: Is Insularity an Advantage or Disadvantage?

2.1 Islands as a special focus for policymaking

Islands, and in particular small islands, have long been thought to face a particularly distinctive

set of challenges likely to hinder their economic performance. As shall be shown, the

perception that islands are at some sort of inherent disadvantage when compared to non-island

(mainland) economies is deep-seated, so intuitive in nature as to be almost a ‘gut reaction’ for

many people, and extremely persistent in nature. At the present time, this perception is vividly

manifested in the European Commission’s view of insularity as a geographical ‘handicap’, one

of several such handicaps requiring remedial policy action:

“Regions with specific and permanent geographical features which constrain their

development, such as the most remote regions, islands, mountain regions and sparsely

populated areas in the far north of Europe, have special problems……. All of these regions, in

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whichever part of the EU they are located, have common problems of accessibility and of

remoteness from major markets which tend to add to both travel and transportation costs and

constrain their economic development” European Commission, 2004, p.30 and p.33.

The EU is not alone in taking the view that insularity is a ‘handicap’ requiring special policy

treatment. The UN officially recognises a category of small island developing states (SIDS) as

being member states with distinctive economic development problems, and the British

Commonwealth too has recognised its small island states as being distinctively vulnerable

economic entities. In addition, many individual countries, both in the EU and elsewhere around

the world have developed favourable policies and governance structures for many of their

offshore islands (e.g. Corsica in France, the Faröe Islands of Denmark and the Åland Islands of

Finland).

If one examines the academic and policy literature on island economies, it rapidly becomes

apparent that it is the combination of two geographical characteristics, small size and insularity,

which is seen by most as being the root cause of the perceived ‘handicap’. Moreover, most

authors seem to regard the ‘islandness’ part of this double handicap as being fundamentally the

result of transport problems, while the ‘smallness’ handicap is usually seen as being the result

of the island companies being unable to reach critical minimum production scale levels.

This rather traditional view of insularity being a handicap for economic performance has been

revealed by research in recent decades to be a considerable over-simplification of the economic

challenges faced by small island economies. The reality is more complex. Moreover, there is

now considerable evidence that many small islands have been able to produce economic

growth performances and standards of living for their citizens which can be at least as good,

and often better than their larger, mainland counterparts. In the remainder of this section, three

very different literatures which have addressed the economic performance of small island

economies are reviewed.

2.2 The evidence from global small states research

There is a large and growing literature on the economic performance of global small states

which has thrown considerable light on the nature of the challenges faced by small island

economies. A high proportion of the smallest countries in the world are island (or archipelagic)

economies. If one adds to the sovereign states with UN membership those entities which are

not fully politically sovereign but which have a very high degree of both political and

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economic autonomy1, one finds that of 127 small states and highly autonomous entities with

populations under 5 million persons, no fewer than 74 of these are islands or archipelagos

(Armstrong and Read, 2005). As shall be shown, most of the small states research literature is

highly relevant for islands all around the world, irrespective of whether they are sovereign

states or not.

With so many small island states in the world, it is not surprising that they have attracted

particular research attention. The small states literature has identified a whole series of

different types of economic challenges facing island economies. The principal ones are as

follows:

(a) Small population size, coupled with greater difficulty in gaining access to wider regional

and global markets because they are islands, means that the domestic market may be too

small for local businesses to attain minimum efficient scale (MES – Bhaduri et al, 1982;

Kuznets, 1960). This has two rather differing implications for economic performance.

Firstly, the local businesses will find it difficult or impossible to compete in wider regional

and global markets to win exports, and secondly, to the extent that the businesses seek to

serve the local market, local prices will be higher, raising the cost of living for island

residents. The MES argument was traditionally couched in manufacturing industry terms

since it is in manufacturing that scale economies are most pronounced. The argument is

also, however, valid for some service sector industries (e.g. banking and finance) and,

perhaps more importantly, for the major utilities sectors (e.g. water, electricity,

telecommunications). Below-MES production levels in the key utilities has a double-

barreled effect; it raises the on-costs for other businesses (hence reducing further their

competitiveness in external markets) and it raises the direct costs of utilities to local

households, increasing island cost of living.

(b) Closely related to the MES argument is the implications a small domestic market has on the

competitive environment within-island. Not only may the firms which exist be too small to

be efficient, but the small market is also likely to mean that developing a critical mass of

competing firms becomes impossible. This can have different ramifications. The most

obvious and direct effect is that there will be many sectors in which local monopoly or very

limited local oligopoly situations exist, raising prices and costs right across the island

economy (Armstrong et al, 1993). Less direct, but perhaps of greater long run importance,

the strict limits on the numbers of local businesses in a given sector means that the

1 These comprise the remaining colonial entities such as the UK’s overseas territories, the French Territoires

d’Outre Mer (TOMs), the USA associated territores, and other similar entities for the Netherlands, Australia and

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potential for vibrant industrial clusters to emerge is severely curtailed. There is now a large

body of evidence of the importance of industrial clusters for the economic development of

regional economies, and new economic geography (NEG) theories, of course, place

enormous emphasis on the ability of clusters to exploit external economies and

agglomeration benefits. In recent years it has become apparent that it is possible for some

islands to be able to develop successful industrial clusters. This can be done by developing

cross-border networks with other islands or mainland regions (as Singapore has done with

adjacent parts of Malaysia and Indonesia). In other cases it has been achieved by

overcoming the barriers of distance by exploiting family and cultural ties (as between

Mauritius and India in the textile industry). In practice, however, most islands have not

been able to develop industrial clusters in this way and have therefore failed to exploit the

advantages of industrial clusters within the modern global economy.

(c) Some of the most severe challenges faced by small island economies are the result of factor

supply (or ‘resource base’) limitations. These frequently apply to the full set of factors of

production (i.e. land, labour, capital and natural resources). Small population not only

limits the size of the local market for goods and services, but also places strict limits on the

local labour supply. This can, of course be supplemented by in-migration and many islands

do indeed seek to attract both seasonal and permanent migrants, but in practice there are

limits (geographical, political and social) on how far this can be taken. A small local labour

force has a series of implications for economic performance. It places constraints on the

agricultural sector. Moreover, creating a manufacturing base in a labour-intensive manner

(as is common in many developing countries) cannot be achieved in small island

economies (Bhaduri et al, 1985). In addition, as has already been noted, a small population

size means that the entrepreneurship base will also be small, with only small numbers of

firms being created. Islands typically respond to the labour force constraint by

concentrating their limited resources on highly specialised niche market exports. In some

cases the islands can end up being highly dependent on a single industry for their exports

(e.g. banana production, oil or fish exports for islands lucky enough to have a natural

resource endowment, or only one or two manufacturing or service sectors, as with the

many offshore finance based island economies, or those wholly dependent on tourism). The

resulting lack of diversification is thought to have two rather different effects on island

economies. Firstly, over-specialisation combined with an extremely small share of external

export markets makes many island economies classic price-takers in export markets. This

inability to significantly influence external market conditions makes them very vulnerable

New Zealand, together with semi-sovereign entities such as the Faröe Islands, Åland Islands etc.

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to sudden changes in trading conditions. Sudden trade shocks are particularly serious

because with a high proportion of factor resources are tied up in the main export sector

there is little in the way of a non-export sector to absorb changes induced by sudden

switches in external trading conditions. Secondly, the high degree of specialisation has

longer-term implications as there is unlikely to be cohorts of small firms in other sectors

waiting to come on-stream as traditional staple sectors go into long-term decline. In an

economy such as the Isle of Man in the 1980s and 1990s, faced with a steady decline in its

traditional summer holiday tourist market as UK travellers moved elsewhere, finding

alternative sectors into which resources could shift was no easy task.

(d) The small states literature has also begun to throw more light on the challenges posed by

higher transport costs for island economies. Of all of the ‘handicaps’ faced by small islands,

it is transport costs which are the most obvious problem. At its simplest, the transport cost

issue for islands is about transhipment costs. Islands, simply because they are islands, face

two additional sets of transhipment costs (loading and unloading) which mainland regions

do not. Transhipment costs affect both freight and passenger transport, involve more than

just the costs of physical movement (e.g. they also include paperwork and bureaucracy

costs), and are known to be high relative to the line-haul element of total transport costs. It

is, however, important not to be too simplistic about the nature of transhipment costs. To

begin with, new vehicle and port technologies (especially roll on-roll off ferries and

containerisation) have greatly reduced transhipment costs over time, just as larger maritime,

air and road transport vehicles (able to exploit vehicle economies of scale) and the growth

of route densities and trip frequencies as trade has expanded have cut other elements in the

transport cost package. It is clear therefore that the transport costs ‘handicap’ facing small

islands has been falling over time, allowing many islands to become more intergrated with

the regional and global economy. In addition, the steady build up of investment in ports,

airports, roads and other elements of transport infrastructures, particularly in the EU where

large amounts of Structural Funds, TENs and other public policy investment spending have

occurred, has also helped to reduce the burden of transport costs for islands. Nevertherless,

it is clear that islands continue to face a burden of additional transport costs, even though

these may be falling over time. Being an island economy brings with it an array of other

transport-related problems which are only now becoming fully understood. These include:

• Freight insurance costs and damage-in-transit costs are higher for islands relying on

maritime and air transport links and with transhipment activities being a necessary part

of the equation. In addition, islands are more likely to face greater uncertainty of

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services given the risks of bad weather and mechanical disruption. The latter is

diminishing in effect as transport technology improves over time, but these factors

remain a sufficient threat to cause additional business costs (especially in the form of

higher inventory holdings).

• The volumes of import and export freight and passenger flows frequently mean that

neither vehicle nor port economies of scale (which are very significant in all three

transport sectors – sea, road and air) can be fully exploited.

• The small scale of import and export flows usually mean that origin and destination

ports are extremely few in number (sometimes involving only a single sea route). This

raises the costs of transport and business costs on the island in two ways. Firstly, local

monopolies are very frequent within the freight and passenger transport sectors, with

implications for higher costs and price levels. Secondly, island exporters and importers

have few route choice options, often leading to longer and less direct shipment routings,

with additional cost implications.

• A rarely recognised but important problem faced by many islands is the asymmetric

nature of freight flows. Island consumers naturally demand a full array of consumer

products. These are typically higher bulk and lower value than the export freight flows

(since island exporters seek to overcome the geographical barriers by concentrating on

high value, low bulk products, or else on services such as financial services with

negligible freight flows). This means that import volumes tend to be much higher than

export volumes. With many vehicles returning empty or at less than 100% loads,

transport costs are effectively doubled for many islands.

(e) Finally, there is a substantial literature on the vulnerability of small island states. One

element of the greater unpredictability of conditions facing small islands has already been

touched upon, namely the fact that islands are usually price-takers in external markets,

making them vulnerable to sudden shifts in terms of trade and other external economic

factors. They are also highly specialised exporters, frequently dependent not only on the

export earnings from a single or small number of products, but also disproportionately

dependent on a single overseas market (often the former colonial power in the case of

sovereign island small states – Bertram, 2003). Economic vulnerability is, however, only

one of a series of vulnerabilities which can affect the economic performance of islands

(Atkins et al, 2000; Briguglio and Galea, 2003). Islands face environmental vulnerabilities

(e.g. hurricane damage, crop pests, earthquakes), including the severe impacts in some

cases of volcanic eruptions. Many small island states are also politically vulnerable, for two

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reasons. Firstly, they are often highly dependent on a single large country (usually an

adjacent large state or the former colonial power) for political influence in international

negotiations. Secondly, their small size means that they have little influence in wider

international debates and decisions, often being wholly unrepresented in bilateral and

multinational negotiations and with very limited consular presence in many parts of the

world. The various different elements which make up the overall picture of vulnerability

combine to make island states more likely to have volatile incomes and consumption levels

over time, interspersed with massive and sudden shifts at rarer intervals.

The list of challenges set out above facing small island states is a long one. Closer scrutiny of

the different ‘handicaps’ shows that virtually all of them apply not only to sovereign small

states that happen to be islands but also to sub-national islands which are not sovereign states.

Although there has been much less research on non-sovereign islands than there has been on

small sovereign island states, it is clear that virtually all of the same arguments apply. The

implications of the small states literature for the analysis conducted in this paper are two-fold.

Firstly, the Greek and British small islands analysed in this paper almost certainly face the full

set of economic challenges set out above. Secondly, the impact of each challenge in turn will

differ from island to island, and hence the challenges set out above may well be important

determinants of the relative economic performance of the different islands. For example, those

islands with good port and airport infrastructures will face smaller transport costs and less

disruption to services than those without. Similarly, bigger islands are more likely to be able to

exploit transport economies of scale than smaller islands, and so on.

There is a further part of the small states literature which has important implications for the

Greek and British islands studied in this paper. The small states literature has devoted

considerable time in recent years to the analysis of the policy responses to the economic

challenges faced by islands. The reason for the focus on policy responses is because there is

now considerable evidence that the economies of small island states do not do uniformly badly

as the long list of ‘handicaps’ would suggest. On the contrary, many small island states have

performed spectacularly well (e.g. Singapore, Bermuda). Moreover, systematic studies of large

data sets comprising large and small states have revealed that neither population size nor

‘islandness’ seem to be systematically related to poor economic performance (Armstrong et al,

1998; Armstrong and Read 2000, 2003a, 2003b; Bertarm and Karagediki, 2004). In other

words, since islands do seem to face some distinctive problems, many of them must have found

policy responses which have allowed them to overcome their ‘handicaps’. The main

advantages they seem to have been able to exploit have been as follows:

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(a) Although it is conventional economic policy logic that industrial diversification is a good

policy stance, it is clear that many small island states have been able to make a virtue out of

a necessity by having a clear niche market strategy. Focusing on high earning niche

markets such as cruise tourism or offshore financial services may be a risky strategy and

poses vulnerability threats, but it is nevertheless still possible to have a high standard of

living whilst the good times last. The keys to success for many of the better-performing

small island states seem to be to (a) focusing government policy support on the key export

earning sector whilst the going is good (e.g. transport infrastructure and hotel/leisure

investment for tourism; business regulation manipulation for offshore finance and other

services), combined with (b) rapid and flexible policy responses when it becomes necessary

to abandon one niche market and move to another (e.g. the response of the Channel Islands

to the loss of UK early vegetable and flower markets following EU entry by the UK).

(b) Many islands have made a virtue out of necessity in another way too. Since small islands

are inherently price-takers in external markets, and have very little influence on global

trading conditions and regimes, they have by necessity had to adopt highly open trading

policies. Trade restrictions are only very rarely imposed since virtually all of the locally

consumed goods must be imported and since exports are the life blood of all islands.

Indeed, many small island states do not even have their own currency (adopting the

currency of a larger nearby state or the US dollar or Euro, or else have rigidly locked

exchange rates with a larger country currency such as the dollar). Since small island states

have by necessity always been highly open, trading economies, it can be argued that they

were fortunate in avoiding the pitfalls of protectionism, a policy stance which bedevilled

many newly decolonised developing countries from the 1960s onwards (Chai, 1998). Most

small island states were therefore in the fortuitous position of already having highly open

trade policies in place when globalisation began to take off in the 1980s and 1990s and

were therefore able to benefit quickly from the new market opportunities opening up.

(c) Small island states, like other non-island small states, have also undoubtedly been able to

exploit a whole series of policy options based upon what has come to be known as the

‘importance of being unimportant’ (Armstrong and Read, 2002). This is most vividly seen

in the manner in which many small island states have been able to develop highly

successful offshore financial centres (Cobb, 2001; Hampton and Abbott, 1999). These

invariably rest upon the establishment of flexible banking and financial regulations which

are tolerated by the large states of the world and by entities such as the EU and OECD

simply because the scale of financial activities in the offshore centres is too small to trigger

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retaliatory action. The ‘importance of being unimportant’ policy loophole is not confined to

financial services. Many small island states also adopt flexible business start-up and

bankruptcy regulations, environmental regulations and maritime industry regulations,

allowing yet more niche sector activities to be established.

(d) Somewhat more controversial than the ‘importance of being unimportant’ argument is the

view that small island states may have better social capital (Putnam et al, 1993) than large

states. The argument here is that small island states have more homogeneous communities

and are small enough to allow policy decisions to be quickly implemented and in an

atmosphere of greater transparency and trust, important building blocks for good social

capital. This argument may well be a good one for some small island states. However,

‘smallness’ may not always be a virtue for social capital accumulation since it is also

evident that nepotism and clientalism are rife in some island states. Indeed, it is often

possible for small cliques of business leaders to come to dominate an island’s political life,

to the detriment of open trading and a welcoming business environment.

(e) Many small island states have retained close economic and political ties with their former

colonial powers, despite their own sovereign independence (Bertram, 2003). These

continuing close ties often have resulted in substantial bilateral aid flows (usually financial

aid but also often aid-in-kind through the provision of teachers, civil servants etc). The

former colonial powers will also often use their influence in multilateral negotiations to

obtain preferential trade access to trade blocs such as the EU or in WTO agreements.They

also often use their influence to generate additional aid from large multilateral

organisations such as the World Bank and the UN.

(f) ‘Islandness’ is not always an inherent disadvantage in itself. For example, being an island

is often in itself a major attraction for tourists, even if the climate is poor.

An interesting issue which has not yet been fully analysed within the small island states

literature is why some small islands have done spectacularly well whilst others have done

extremely badly. Small island states are to be found at both extremes of the spectrum of

economic performance in the global economy. What research has been done suggest that once

again it seems to be the policy response which may be the explanation. The literature suggests

that it is possible for many developing small island states to retain an economic dependency

culture once they have obtained political independence from colonial powers. The evidence

suggests that there is quite a large group of small island states that appear to have developed a

stable, but low level of economic performance based upon income from migrant remittances

(usually from migrants to the former colonial power), aid (in the form of financial flows and

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investment in public infrastructure, again often mainly from the former colonial power) and

bureaucracy (hence ‘MIRAB’ economies – Bertram and Watters, 1985). It is recognised that

there may be several different variants of the MIRAB model, but it is an accurate summary of

one particular type of policy response by some small island states. In contrast to the MIRAB

economies are those small island states which have deliberately made major policy efforts to

break free of dependency situations. In a recent paper, Bertram (2006) argues that there may be

two distinctive types of successful small island states. The first are so-called PROFIT

economies (with success based on successful labour and residential management – ‘people’,

natural resources management, overseas engagement, financial services and transportation

management – Baldacchino, 2006). The second are the so-called SITE economies (small island

tourism economies, which are much more specialised but also successful). Whatever the

realities of the situation, the key finding of this part of the literature is a clear one – it is the

policy response which matters and good policies can lead to success, despite the handicaps

facing small island states.

The ‘policy response’ part of the small states literature is less directly applicable to Greek and

UK islands than is the ‘handicaps’ part. Sovereign island states have a much greater degree of

control over the policy levers than do Greek and British small islands whose local government

policy powers are both limited and virtually identical to those of their mainland counterparts. It

is true that sovereign small island states normally have very little in the way of macroeconomic

policy powers (with limited fiscal policy power and usually no monetary policy powers). Trade

policies too are usually non-existent since as noted earlier small states must by necessity adopt

free trade policies (Read, 2002). In these respects they are almost identical to the Greek and

British islands which are the subject matter of this paper. By contrast, however, sovereign

small states have considerable microeconomic management policy powers. Unlike the Greek

and British islands, they can manage residence and seasonal/temporary migration flows in

order to sustain economic activity and keep local unemployment rates low. They also have

major powers over personal and business tax regimes, often used to attract high income

residents and investors from overseas. Moreover, as has already been noted, they can

manipulate their ‘importance of being unimportant’ to set in place highly attractive financial,

business, maritime and environmental regulations designed to foster strong niche market

sectors. The Greek and British islands which are the subject matter of this paper have none of

these powers. Indeed, their respective national legislation frameworks, combined with strict EU

Single Market prohibitions on barriers to labour and capital mobility and the free movement of

goods and services explicitly rule out most of the microeconomic policies enjoyed by

sovereign small states.

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We may therefore conclude that whilst the Greek and British islands which are the subject of

this paper face virtually all of the economic challenges posed by ‘islandness’ as their sovereign

island state counterparts, they lack many of the distinctive policy powers enjoyed by sovereign

small island states. One might therefore speculate that the Greek and UK small islands face a

harder struggle to succeed than their nearby sovereign counterparts (e.g. Cyprus and Malta in

the case of Greece and the Isle of Man and Channel Islands in the case of Britain). Indeed,

probably the sole advantage which the sub-national islands enjoy over their sovereign

counterparts is that they have more direct access to aid from their national finance ministries

(as well as EU structural funds and agriculture policy subsidies). There is no doubt that many

Greek and British islands do benefit from intra-national fiscal transfers and direct aid (often for

transport infrastructure), but this is probably a poor substitute to the kind of microeconomic

policy weapons available to sovereign small island states.

2.3 The evidence from international growth model research

A second literature which has thrown light on the effects of geographical ‘handicaps’

(including insularity) on economic performance has been attempts to model differences in

economic growth rates between different countries of the world. There has been a great

flowering of studies of this kind since the early 1990s, in recent years much of it being driven

by a desire to understand why some global regions have performed more poorly than others

(especially sub-Saharan Africa). The development of large international data sets has also

meant that the study of international growth differences has been used as a laboratory to test

different types of economic growth theories.

International growth models do, however, only occasionally include ‘islandness’ as one of the

(usually many) explanatory variables tested. This is principally because an unfortunate feature

of the large data sets used is that they are highly truncated. They are truncated two key respects,

both of which render their findings of only very limited use for those interested in the

economic performance of small island economies. Firstly, data limitations mean that many of

the very smallest sovereign states are excluded. Although most small sovereign states have in

recent years greatly improved their statistical data bases, especially for the national income

accounting data so vital for growth model research, the smallest states lack the long time series

for key variables which exist for large states. Secondly, because so many of the world’s

smallest states are islands (or archipelagos), the main data sets are also inherently highly

truncated in that they exclude many island economies.

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Despite the highly flawed nature of the data sets used for international growth analysis, at least

as far as those interested in island economies are concerned, the international growth model

research literature has thrown some interesting light on the nature of the issues of concern in

this paper:

• Those few studies which do incorporate size and/or insularity explanatory variables (size

usually being measured as population size and insularity normally a simple dummy

variable) have tended to find that these variables are statistically insignificant (Milner and

Westaway, 1993; Armstrong and Read, 2003b). It therefore does not seem to be the case

that small size or insularity have systematic effects on national economic growth rates,

despite the many challenges such states face (see above). In this respect the growth

literature supports the evidence set out earlier from the small states research literature, and

presumably for the same reasons. Again, however, it must be stressed that since the main

data sets exclude many of the very smallest island states it is possible that significant

relationships might exist had the data sets used been more comprehensive and had not

excluded the tail of very smallest island states.

• Whilst size and insularity do not figure prominently in the growth model research literature,

there are a number of other ‘geographical handicap’ variables which have proved to be

statistically significantly related to variations in economic growth rates. In fact, quite a

wide array of different ‘geographical’ variables have been tested. These include

accessibility/remoteness from global markets, whether a country is landlocked or not,

climate (tropical climate/disease), how mountainous a country is, and size. Unfortunately,

those geographical variables which have been shown to be statistically significant in

growth models (especially tropical climate, remoteness and landlocked status) are also

highly correlated with a number of institutional variables (e.g. size of government,

corruption, civil strife etc). This has led to the still-unresolved issue of whether it is

‘geography’ or ‘institutions’ (or both) which are the principal determinants of international

differences in economic growth (Sachs, 2003; Ahlfeld et al, 2005; Sachs and Warner,

1997).

It remains impossible at present to be sure from the international economic growth research of

just how important ‘geographical handicap’ variables in general and ‘islandness’ in particular

are in determining international economic growth rates. However, what can be said at the

present time is that (a) what international growth evidence exists does tend to support, despite

its flaws, the evidence from small states research that small size and islandness does not

necessarily result in weaker growth, and (b) if geographical variables are important in

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determining economic growth differences, then of those which have been found to be most

significant to date (i.e. tropical climate, landlocked status, remoteness), it is only ‘remoteness’

which is relevant for the Greek and British islands which are the focus of this paper (since

neither tropical climate nor landlocked status apply in our data sets). As shall be shown later,

we have attempted to incorporate accessibility measures into the analysis undertaken.

2.4 The European Commission’s view of island ‘handicaps’

The quotation from the European Commission with which this section began clearly identified

insularity as being a characteristic which it sees as acting as a constraint on economic

development, and the nature of the constraint is closely linked to transportation (in particular

via difficulties in accessing the wider EU market). This view represents a highly traditional one

of island economies. As such, it is rather an old fashioned one because as we have seen in

sections 2.2 and 2.3 (above), recent international research has revealed a much more complex

picture of many different ways in which ‘islandness’ affects economic performance, by no

means all of which are negative.

The quotation does not, however, do complete justice to the Commission’s view of the nature

of the ‘handicap’ associated with insularity. The Commission has had long experience in

developing policies (particularly Structural Funds, agriculture and transportation policies) for

islands, simply because the EU has so many islands2. A major study undertaken recently on

behalf of the Commission found, using a narrow definition of what constitutes an ‘island’3, that

there were no fewer than 286 island territories within the EU15 (Planistat Europe, Bradley

Dunbar Associates, 2003a). The Commission is therefore well aware, by virtue of its long

experience in developing policies for many island territories over many years, of the complex

nature of the challenges facing island economies. Moreover, from an EU perspective, the

evidence would suggest that insularity is indeed a clear ‘handicap’, or at least a much clearer

‘handicap’ than is the case among small states or across the global economy. For example,

some 93% of EU islanders live within regions with a GDP per capita below that of the EU

average (Eurisles Website, 2006)4. In addition, since the Commission has a clear objective of

2 The vast majority of EU islands are located within Western Europe – EU15. Apart from Estonia and, of course, Malta and Cyprus, there are very few offshore islands associated with the New Member States (NMS10 or NMS12). 3 Defined as (a) having an area of at least one sq. km. or 10 ha., (b) being at least 1 km. from the continent, (c) having a permanent resident population of at least 50 people, (d) having no permanent link (e.g. bridge or tunnel) with the continent, and (e) not housing an EU national capital. 4 This statistic is, arguably, a misleading one for two reasons. Firstly, the Eurostat data on which it is based frequently groups offshore islands in with adjacent (littoral) areas of the continent and it is impossible to identify separate GDP per capita values for the individual islands. Secondly, and perhaps much more importantly, islands

15

creating a much more highly integrated EU economy, insularity inevitably places barriers to

integration and is therefore a characteristic ‘problem’.

The Planisat Europe report contains within it quite a clear exposition of how the complex

nature of the islandness ‘handicap’ is currently viewed within the EU policy making process.

Figure 1 sets out the conceptual framework model which was used as a basis for the research

conducted for the Planistat report. The model has a number of key features:

• ‘Island status’, as can be seen in Figure 1, is one of a number of exogenous factors over

which the local economy has no control. Interestingly, these exogenous factors are all

geographical characteristics, the others being ‘outlying status/remoteness’ (from the EU

market), small size and ‘natural conditions’ (e.g. being mountainous, climate). The model

does not explicitly state that the different exogenous factors have exactly the same effects

on the within-island system (‘endogenous factors in Figure 1), but clearly implies that

insularity is one of a group of characteristics with similar impacts.

• A clear implication of the model, and one which has carried through into subsequent

Cohesion policy debates and regulations, is that any one island may experience an

accumulation of more than one geographical ‘handicap’ (e.g. by being both an island and

mountainous); the greater the accumulation the stronger the policy intervention justified. In

fact, this is simply a restatement of a principle which has long existed in EU policymaking.

Good examples of this have been the Outermost Regions of the EU5 and the sparsely

populated regions of northern Europe. The ORs are regions which combine extreme

remoteness from the continental EU with small size and (for six of the seven entities)

insularity. They have been accorded special policy measures within the EU for many years

(see below). The sparsely populated regions of northern Europe combine the ‘handicaps’ of

small (population) size with geographical remoteness and a harsh (for agriculture) climate.

The accession of Sweden and Finland in 1995 brought a large swathe of sparsely populated

regions into the EU for the first time and led to these regions being accorded their own

are highly concentrated within only a few member states (e.g. only five member states account for over 75% of all islands, and 95% of the population in the islands is concentrated on the big Mediterranean islands of Corica, Sicilia, Sardegna, Baleares and Crete – Planistat Europe, Bradley Dunbar, 2003a). Hence the low average GDP per capita may be largely a reflection of the within-EU regional location of the big island populations (i.e. the Mediterranean region) rather than inherent islandness ‘handicaps’. In a recent paper, Armstrong and Read (2005) analyse data for the 35 EU15 islands for which useable Eurostat data exist and find that when islands’ GDP per capita values are compared with contiguous EU regions (rather than the overall EU15 GDP per capita), there is no evidence that islands are systematically disadvantaged. On the contrary, as with the global small island states, it is found that islands are to be found among both the most prosperous and least prosperous categories or regions within the EU. 5 These comprise the French Départements d’Outre Mer of Gualeoupe, Reunion, Martinique and French Guyana, together with the Açores, Madeira and Islas Canarias of Portugal and Spain. Of these, only one (French Guyana) is not an island.

16

special status (a new ‘Objective 6’ of the Priority Objectives of the Structural Funds in the

1994-99 Structural Funds programming period).

• Figure 1 shows clearly that the complexity of the relationships between insularity and the

inner workings of island systems is well understood. In particular, the transportation

element (shown as the ‘Access to markets, transport problems’ box in Figure 1) is clearly

identified as being only one effect of insularity, and moreover is seen to be only one factor

among many within a highly interrelated within-island system. Hence “from these

(exogenous, geographical) constraints, a whole series of effects, with powerful interactions,

affect the territory studied” (Planistat Europe, Bradley Dunbar, 2003a, p.8).

• Figure 1 shows that insularity can have powerful effects across many different dimensions

of the life of an island community. Some of these are economic, such as the ‘Limited

production possibilities’ box in Figure 1, picking up a major theme of the small states

research literature; and the ‘Limited human resources’ and ‘Limited natural resources’

boxes, which also pick up key themes from the small states literature. Others, however, are

more concerned with standards of living (the ‘Access to public services’ box), the

environment (the ‘Environmental problems’ box) or demography, with many islands

having an ageing populations as younger residents move off-island to find better job

opportunities (the ‘Demography’ box in Figure 1).

• The Planistat Europe report drew upon the conceptual framework to undertake a principal

components analysis of an array of variables designed to quantify the eight endogenous

boxes set out in Figure 1. No attempt was made to analyse the causal relationships between

the various variables. Nevertheless, the results obtained are interesting in that the first

(most important) component (50% of the variance) was dominated by remoteness/isolation

variables (of which six were incorporated in the study)6, followed by geomorphological

conditions (e.g. climate, altitude etc, and including a measure of the size of the archipelago

of which the island is a part – 38% of variance) and then size (only 8% of variance). These

results are interesting in that they tend to support the results of much of the small states and

international growth model research which frequently place remoteness as the most

important of the geographical variables (particularly since ‘landlocked’ status is usually

interpreted as also picking up relevant accessibility issues such as the difficulties such

countries have in accessing major global maritime routes).

6 These were distance to be travelled to meet 15 times the population of the territory, distances island/continent and island/capital of the mother country, number of means of transport, differences between GDP and that of the surrounding population, tonnes of freight per capita and number of passengers transported per capita).

17

The EU view of the effect of insularity can therefore be seen to be a suitably subtle one,

recognising the complexity of the relationships involved. However, it is clear from the

language used (e.g. island status as a ‘handicap’, ‘limited’ production possibilities etc) that

insularity is not seen as having many advantages. In this respect, the EU view is now

somewhat at variance with the emerging consensus within the small states literature and with

the evidence which has been produced by international economic growth models. In these other

two literatures insularity is seen as having advantages as well as disadvantages and other

geographical characteristics as seen as being stronger handicaps (e.g. landlocked status being

more significant as a handicap than either smallness or insularity).

The Commission’s view of insularity as a ‘handicap’ has carried over into major policy

decisions for the 2007-13 Cohesion policy programmes in two main ways. Firstly, the

Outermost Regions of the EU have been granted an extension of the special legal status they

already enjoyed within the EU treaties (and which they were first granted in the Treaty of

Amsterdam in 1997). This special status allows them to enjoy special policy treatment by way

of many different national subsidies and policy concessions and through a series of EU treaty

derogations (e.g. on ceilings for state aids under Article 87(3)(a) and (c) of the Treaty of Rome

and on certain types of taxation). These confer major advantages in respect of agricultural,

transport, fisheries and certain types of industrial policies (e.g. freeport zones in Madeira and

the Canarias). Over the years, the various concessions and derogations have developed into a

formidable collection of policy instruments and subsidies (European Commission, 2004). A

significant on-going debate is whether the assistance being given should be focused most

strongly on strengthening integration with the EU or with with other countries much closer to

the ORs (an important issue for the ORs in the Caribbean, South America and Indian Ocean).

This debate remains largely unresolved, with assistance in the 2007-13 period continuing to be

allowed for both of these types of policies.

In addition, the Outermost Regions will continue to benefit from special treatment within EU

Structural Funds and agriculture policy programmes in the 2007-13 period. The ORs have been

given the privilege of Objective 1 status in successive Structural Funds programming periods

since 1989 irrespective of whether they meet the GDP per capital eligibility criterion, and have

also been able to access special Structural Funds Community Initiatives (Pseidon, Poseima,

Poseican and Interreg). They have also long enjoyed special agricultiure policy subsidies for

crops such as bananas, tobacco etc and a range of additional fisheries policy subsidies. This

special status for the ORs is to continue into the 2007-2013 programming period.

18

Secondly, the Commission has recognised ‘islandness’ as one of a number of geographical

handicaps deserving of special policy treatment in regions of the EU within the EU heartland

on the continent of Europe. In addition to insularity, the 2007-13 Cohesion policy programmes

will take special account of other geographical handicaps, namely mountainous terrain

(Nordregio, 2004), very low population density regions, geographically remote regions, and

isolated rural areas. Of these, only the sparsely populated regions had enjoyed special

Structural Funds benefits (following the accession of Sweden and Finland in 1995). In the

2007-2013 Cohesion policy programmes these geographical handicaps will be systematically

incorporated into the new Objective 2 programmes (European Commission, 2004).

3. Building Typologies for Island Economies: A Cluster Analysis

3.1 The Greek and GB case studies

As has been shown in section 2, island economies face particular social and economic

challenges, but also may well have a number of important advantages too. In this section an

attempt is made to identify differences within and between Greek and British islands in their

relative economic performance and to speculate on possible reasons for the differences

identified. The results presented are preliminary in nature and represent the first part of an

ongoing project. In this paper the results are presented of a classification, drawing upon a

cluster analysis, of the economies of a number of islands which are part of Greece and Great

Britain.

Islands from the member states of Greece and Great Britain have been selected for the

following reasons:

• They are two of those five EU member states which contain within them the vast majority

of EU islands. The results should therefore be of interest not only in themselves, but also

because they cover a large number of EU islands and in numbers which allow sufficient

degrees of freedom for statistical analysis to be conducted for the islands of each country

independently.

• Since the research is concerned with geographical characteristics (of which insularity is

one), the Greek and GB offshore islands have a number of extremely interesting

similarities and differences which make them good case studies for comparative research.

They are at opposite geographical extremes of the EU, with most of the islands being very

remote from the main EU markets (the Scottish islands, which dominate the GB data set

face onto the Atlantic Ocean, and the Greek islands being mostly in the Aegean face onto a

19

non-EU country, Turkey, which at the time of the study data sets, 2001, had borders with

Greek islands which were largely closed in nature). Moreover, many of the islands in the

data set are also mountainous, parts of bigger archipelagos, have small populations, have

widely differing climates, and have varying degrees of accessibility to their main national

markets (all are rather remote from the main EU markets). In other words, there is wide

variability in the other main geographical variables identified by the literature and by the

European Commission as being important.

• Both Greece and Britain conducted comprehensive population censuses in 2001, and their

census questionnaires contain many similar questions, a feature which facilitates

comparisons7. Data from the population censuses form the bulk of the data sets utilised.

• Concentrating on the analysis of islands data from national statistical sources allows many

more islands from the two countries to be incorporated than would have been the case had a

full set of EU15 or EU25 countries been selected. Eurostat data is highly deficient for the

analysis of island economies (see Armstrong and Read, 2005; Planistat Europe, Bradley

Dunbar, 2003 for discussions of the limitations of Eurostat data for islands research).

In the context of the research described in this paper, the island economies of Britain and

Greece have been classified on the basis of an array of geographical, economic and

demographic variables. The resulting classification has then been used to address the following

questions:

• Do certain British and Greek islands share similar economic performance?

• Are there distinctive features of certain groups of Greek and British islands?

• Can British and Greek islands be grouped according to their size and remoteness?

As noted earlier, cluster analysis is used to build a typology for the two sets of island

economies.

3.2 The data sets

Islandness

An initial decision which all researchers interested in studying island economies must make is

how to define an ‘island’. This is more complex than it appears at first sight, even if one

concentrates solely on inhabited islands only. As has already been noted, the 2003 Planistat

7 We have not, however, sought to combine the two sets of islands into a single data base for analysis because there remain significant variations in the manner in which data are available from the two censuses).

20

study for the European Commission identified 286 EU15 islands using the following definition

based on five objective criteria. An island must:

• have an area of at least one square kilometre or 100 hectares;

• be at least one kilometre from the continent;

• have a permanent resident population of at least 50 people;

• have no permanent link with the continent;

• not house an EU capital (Planistat Europe, Bradley Dunbar Associates, 2003).

This definition goes beyond the sole common point shared by islands, that they are surrounded

by water. It imposes a lower limit as regards size, requires a minimum human presence and

eliminates islands too near the coast or connected by a fixed link to the continent. In our

opinion, this definition is too strict and is not wholly logical. There is clear logic in excluding

uninhabited islands (on the grounds of zero interest as far as economic performance is

concerned). There is logic in also excluding very small population islands (on the grounds of

extreme data problems which can be avoided by their exclusion with the majority of island

populations and GDP still being retained within the data sets). There is also clear logic in

excluding islands which house an EU capital, since capital cities have major economic

functions which the vast majority of islands cannot aspire to (i.e. they are extremely unusual

‘outliers’ in any data set). Excluding islands containing capitals has the further advantage that

this excludes the giant ‘outlier’ case of Great Britain itself. On the other hand, we can see little

logic in imposing a minimum of 1 km. distance from the continent, since the nature of

transport costs is such that any separation, however short, will trigger the important

transhipment elements. On the other hand, there is logic in excluding islands with fixed (bridge

or tunnel) links to the continent. This logic is, however, not as clear as it may appear at first

sight. Firstly, many of the fixed links (especially the all important bridge links rather than the

rarer tunnel links) are subject to tolls. They therefore remain a barrier to integration. Moreover,

most bridges are subject to regular closure as a result of weather conditions, and in this respect

more closely resemble maritime routes than they do ordinary road links.

In this study we have therefore used a definition of an ‘island’ which draws upon only three of

the five Planistat criteria – land area of at least 1 sq. km, population of at least 50 and no EU

capital. Hence the database includes islands that are connected to the mainland as well as

inshore coastal islands. Based on these three criteria, some 60 British offshore islands and 63

Greek islands were incorporated into the data bases. Tables 1 and 2 provide lists of the selected

islands, together with the NUTS 3 regions of which they are a part.

21

Data sources

After compiling databases of islands, the next step was to obtain data for the various indicator

variables for the islands that would allow us to perform a cluster analysis. Research on global

small island states usually faces severe data problems because of limited availability of

indicators. This situation is also evident in the pan-EU context, since the lowest geographical

level at which appropriate data are available is usually at NUTS 3 level. Many islands are

smaller than the requirements for NUTS 3 classification and often islands are aggregated

together (into archipelagos) to create an appropriate NUTS 3 unit. Alternatively, and more

common as well as more serious in its effects, is the tendency for many NUTS3 regions to

aggregate offshore islands with a littoral area of the continent, making separate identification of

the island’s statistics impossible. As noted earlier, this was one of the reasons why we have

chosen not to work with pan-EU data sets.

Even when one works with rich data sets such as the population censuses, there are many

problems encountered in constructing comparable and accurate data for small islands. Despite

these potential limitations in data collection, it was possible to obtain data on a series of key

variables from the national population censuses of Britain (i.e. England & Wales and Scottish

censuses) and Greece as well as other secondary sources (including some Eurostat data). The

key data sources used in this paper are the 2001 population censuses for England & Wales and

Scotland, and the 2001 population census for Greece. Other indicators on accessibility and

peripherality are obtained from Copus (1999).

Data on the British Islands

The censuses of population have been and still remain the most authoritative social accounting

of people, housing, social conditions and (some) economic variables in Britain and remain

unique sources of data for the social sciences (Rees, Martin and Williamson, 2002). The

censuses record demographic and socio-economic information at a single point in time and are

normally carried out every ten years. The most recent census in Britain was on 29 April, 2001.

Data output is available at six different spatial levels from the 2001 census – government office

regions, unitary authorities, counties, districts, wards and output areas. Output areas were

designed specifically for statistical purposes on the basis of 2001 Census data and are built

from postcode units. They are the lowest geographical level at which data may be retrieved

from the UK census (Rees, Martin and Williamson, 2002).

22

Most of the islands in the British data set are Scottish islands (54 of the 60). Data on these

Scottish islands were obtained from the General Register Office for Scotland. Data on the

Welsh island of Anglesey as well as the English offshore islands were obtained from the

England & Wales census. There were in fact 96 inhabited individual islands in Scotland in

2001. However, only 54 island groups are represented in the British data set. Even using

census data, with all its richness, there remain problems in that the very smallest output units

can still comprise groups of islands rather than individual islands. In the case of the Scottish

islands there were a number of islands which did not meet the size criteria for an output area.

In order to prevent the disclosure of information pertaining to individuals, output areas cannot

contain less than 20 households. Islands not meeting this size criterion have been aggregated

with other islands and mainland to create an ‘island group’. An island group may contain an

individual island or a main island and other islands, which are so small that they have been

merged in order to form an output area (Fleming, 2003). In this paper, the description ‘island’

indicates an individual island or island.

Of the 54 Scottish islands, 19 are island groups comprising more than one island8. Tresco in

England is the only other island group in the complete data set of British islands.

Two of the British islands (Isle of Anglesey and Isle of Wight) have a Eurostat NUTS 3 region

classification. The remaining 58 islands form part of a NUTS 3 region.

The full list of GB islands used is given in Table 1.

Data on Greek Islands

As it was the case with the British census, the Greek national census is collected every ten

years and provides information on people, housing, social conditions and the economy in

Greece. The last census was collected on Sunday 18 March 2001 and was the principal data

source used for the Greek islands. Data may be retrieved from the national census of Greece at

four spatial levels – regions, prefectures, municipalities and communities. Greece has 13

administrative regions, four of which (Ionian Islands, Crete, North Aegean and South Aegean)

are comprised entirely of islands. Of 55 prefectures, 10 are individual islands or island groups.

At the upper spatial levels, many larger islands are grouped with smaller adjacent islands to

form a prefecture or municipality. Hence, data on the very smallest islands in the Greek data

set is attainable only at the municipality or community spatial levels. In such cases, island

8 The Scottish island groups include Arran, Benbecula, Bute, Colonsay, Housay, Lewis and Harris, Luing, Mainland of Orkney, Mainland of Shetland, Mull, North Uist, Raasay, Rousay, Skye, Stronsay, Tiree, Tresco, West Burra and Westray.

23

groups are disaggregated at the next lower level. For example, the island Chios is a prefecture

in the North Aegean region, whilst the islands Psara and Inousses are municipalities within the

prefecture of Chios. Consequently, for the purposes of our analysis the data for Chios are

disaggregated to the municipality level to obtain individual data for the islands of Psara and

Inousses.

All of the Greek islands, with the exception of Crete, have either a NUTS 3 region

classification or form part of a NUTS 3 region. Crete alone is classified as a NUTS 2 region.

Copus’ (1999) peripherality indices are at the NUTS 3 regional level. Hence, the appropriate

index for Crete was obtained by averaging the indices for its three NUTS 3 regions (Lasithi,

Rethymno and Chania). A list of the Greek islands is presented in Table 2

Variables

The performance of cluster analysis on the British and Greek islands, using geographical and

economic variables, was dependent upon the availability of statistical data. As mentioned in the

previous section, the 2001 population censuses of England, Scotland and Wales as well as the

2001 Greek national census were the main sources for data on selected indicator variables.

Although, comprehensive in their coverage of demographic, social and economic factors,

certain relevant statistics, such gross domestic product levels and institutional indicators such

as turnout for local elections were not available from the national censuses. In spite of these

data constraints, several geographical and economic variables were obtained and included in

the cluster analysis. Precise definitions of these variables are provided in the Appendix.

Geographical Characteristics of the Islands

As discussed in the theoretical overview, islands are typically regarded as vulnerable because

their special geographical features which may handicap their development. Insularity and

mountainousness are two of the more common geographical characteristics identified with

islands. These geographical characteristics, among others, pose special problems for islands as

it relates to accessibility to and remoteness from major markets. The extent of the handicap

posed differs among islands. Six geographical variables were included in the cluster analysis to

account for the special characteristics of these island economies:

24

• Land area

• Population

• Population density

• Distance to the main capital

• Distance to Brussels

• Copus (1999) peripherality indices for the NUTS 3 region of which the island are apart.

• Presence of an airfield

Geographical variables also provide information on the natural resource capacity of islands (e.g.

land area) and their ability to facilitate the emergence of certain sectors, particularly an

agricultural sector. Population related variables are also good indicators of the size of the

domestic market and the labour force. These six geographical indicators allow us to include

data on remoteness, accessibility to major markets and domestic markets capacity in our cluster

analysis of British and Greek islands.

Economic Characteristics of the Islands

Several economic variables were included as measurements of economic performance in the

selected British and Greek islands. Of particular importance, were the economic activity of

these islands in terms of population activity rates, employment and unemployment rates.

Islands with lower unemployment rates are regarded as more successful than their counterparts

with higher levels of unemployment. Additionally, indicators of sectoral specialisation, in the

islands, provide information on the proportion of the population engaged in agriculture,

manufacturing and services. All economic variables used in the cluster analysis were obtained

from the 2001 population census data for England, Scotland and Wales and Greece. The

economic variables include:

• Activity rates

• Measures of employment

• Unemployment rates

• Sectoral breakdown

• Occupany levels

25

Although the selected indicator variables provide relevant and important measures of the

geographical and economic characteristics of these islands, they are far from comprehensive.

Mountainousness is an important geographical characteristic of islands, which influence their

development, however data limitations precluded the inclusion of an appropriate mountainous

indicator in the cluster analysis. Further, more comprehensive indicators on economic activity

such gross domestic product levels were unavailable at the island level. This was mainly

because the selected British and Greek islands are not sovereign economies.

3.3 Cluster analysis

Cluster analysis is a convenient method for summarising and retrieving information from a

large set of data (Everitt, 1993). It is a classification technique widely used in both the natural

and social sciences. The key function of this multivariate method is to group cases of data, by

their characteristics, into clusters such that the objects in a cluster are relatively more

homogenous (Bacher, 1996; Backhaus et al., 1996).

In performing cluster analysis, three principal choices must initially be made. These are the

choice between case or variable clustering, the choice of cluster method and the choice of

proximity coefficient as the basis of the cluster method (Everitt, 1993). Since the objective of

this study is to build typologies of Greek and British island economies, case-by-case cluster

analysis is the appropriate one to use rather than variable-by-variable analysis to distinguish

different groups of islands. The cases are the islands and the variables are the economic and

geographic characteristics that are used to group these islands into homogenous clusters.

There are two broad categories of clustering techniques - hierarchical methods and

optimisation methods. Optimisation techniques, such as k-means, use a one-step clustering

algorithm based on an optimisation function. Each case is assigned to its final cluster in a

manner which ensures maximum final distances between clusters and minimum distances

between cases within each cluster. In the k-means algorithm the number of final clusters must

be specified in advance, a major limitation of the technique.

Hierarchical cluster analysis is by far the most popular approach and is invariably the default

method in the main software packages (e.g. SPSS, used here). The classification algorithm

consists of a series of groupings which run from (a) a single cluster containing all the cases to n

clusters each containing a single case, or (b) n clusters each containing a single case to a single

cluster containing all of the cases (the more popular agglomerative methods - Everitt, 1993).

There are quite a large number of hierarchical cluster procedures. It is the widely used Ward’s

26

method which has been adopted in this analysis. Ward’s method has the advantage of generally

giving a clear definition of clusters compared with other methods since ‘it will generally find

tight minimum variance spherical clusters’ (Wishart, 1987, p.91). Ward’s algorithm joins

cases into clusters such that at each step in the process every possible pair of cluster is

considered, and the pair whose combination involves the smallest ‘information loss’ is

combined (Everitt, 1993). Information loss is defined in terms of an error sum of squares

criterion. The Ward statistic is expressed by the following equation:

( )2

1 1 1

ÂÂÂ=

=

=

=

=

=

-=gk

k

mj

j

ni

i

jkijk

k

xxW

where jkx is the mean value of variable j in the cluster k , ijkx is the value of an observation i

assigned to cluster k , kn is the number of observation in cluster k, m is the number of

variables, and g is the number of clusters. Using Ward’s agglomerative method, every island

begins as an individual cluster in the algorithm. They are then joined together into groups in a

step-by-step manner. Agglomeration continues until only a single cluster remains. The step-by-

step process is usually represented as a dendogram (see Figures 2 and 3). There is no hard and

fast rule on how many clusters one selects for examination since in principle the researcher can

work with either one cluster, n clusters, or any number in between. In practice, researchers seek

to identify the number of clusters to examine by locating a point to cut though the dendogram

where a large numbers of cases are suddenly brought together by the algorithm (shown on the

dendogram by a long vertical line above a cluster – see Figures 2 and 3 for the selections made

in this study).

There are many different proximity coefficients and identifying the similarity or dissimilarity

coefficient to be used to distinguish between the groups is an important step in performing

cluster analysis. In this study, as is always the case with Ward’s method, squared Euclidean

distance is the dissimilarity coefficient utilised. The Euclidean distance between two objects is

expressed in terms of the following equation:

( )Â=

-=p

k

ijijij xxd1

2

27

The Euclidean distance between cases i and j is obtained by taking their scores on a

variable, k , and calculating the distance. The smaller the Euclidean distance between two cases

the more similar the cases are.

The results of the cluster analysis using Ward’s method as the grouping algorithm and squared

Euclidean distance as the dissimilarity coefficient are set out as the dendograms in Figure 2 and

3. The following section discusses the results of applying the Ward’s method on Greek and

UK islands data.

4. Typologies of UK and Greek Islands: Results of the Cluster Analysis

Two separate cluster analyses were conducted. The first was conducted on a data set

comprising 18 variables and 60 island cases for the British small islands. The second was

conducted on a data set comprising the same 18 variables, but this time for 63 Greek island

cases. The 18 variables are listed in the Appendix. As can be seen, they are sub-divided into

two groups. The first comprise geographical characteristics, focusing in particular on measures

of size (land area, population, population density) together with alternative measures of

accessibility (accessibility to the nation’s capital city – London and Athens, accessibility to the

EU centre - Brussels, whether or not the island has an airport, and an index of accessibility to

the whole EU). The second group comprises various measures of economic structure and

performance (economically active population, male and female activity rates, working age

population, employment rate, unemployment rates, self-employment, proportions of

employment in agriculture, manufacturing and services and average rates of property

occupation during the year).

The results of each of the two cluster analyses will be presented in turn, before differences and

similarities between the two sets of results are explored. In each case a Ward’s method/squared

Euclidean distance cluster analysis was conducted.

28

The British Offshore Islands

Examination of the dendogram for the cluster analysis of the 60 British offshore islands (see

Figure 2) suggests that a four-cluster solution is the optimum one (in the sense of maximising

within-cluster homogeneity and between-cluster differences). The four clusters identified are

shown as separately numbered on Figure 2.

In order to understand how the cluster algorithm has produced the four clusters, and in order to

clearly identify their different characteristics, the mean values for each of the 18 variables are

calculated for each cluster in turn. These are set out in the first four columns of Table 3. The

final column of Table 3 presents the overall mean value for each of the 18 variables, this time

calculated across all 60 islands taken as a whole. Cluster mean values which are greater than

the overall mean are picked out in Table 3 in bold numbers, with a shaded cell background.

Table 8 presents the same set of results for the optimum six clusters identified by a cluster

analysis of the 63 Greek islands, and can be interpreted in the same manner as Table 3. It is by

scrutinising the values in Tables 3 and 8 that it is possible to build island typologies.

The mean values set out in Table 3 can be used to facilitate the labelling of the clusters. For

instance, Cluster 1 of the British islands we have labelled as ‘Larger but lagging, dependent on

tourism’. As can be seen from the cluster 1 column of mean values, this cluster of 23 islands

exhibits generally rather poor economic performance with lower than average male activity

rates (although female activity rates are relatively high), higher than average unemployment

rates, lower than average employment rates, small working populations and low occupancy

rates. These islands are generally larger ones on average (in land area terms), but with

relatively low population densities. They exhibit roughly average accessibility values with

respect to both London and the EU (note how close the cluster 1 mean values are to the overall

mean values in the final column). They are not therefore by any means the most remote of the

islands, a finding reinforced by the fact that a disproportionate number also have their own

airport. Finally, as can be seen from Table 3, these islands are disproportionately dependent

upon the service sector, which in island economy terms almost invariably means tourism.

Agriculture and manufacturing are much less well represented. The presence of tourism also

probably accounts for the higher than average female activity rates, the sole economic

performance indicator in which the islands of cluster 1 do well, although even here the cluster

value (44.30%) is only slightly higher than the overall average (43.93%).

29

Table 3: Mean values, by variable for the four British island clusters

Variables

Cluster 1:

Larger but

lagging,

tourism

dependent

Cluster 2:

Small,

remote and

agriculture

dependent

Cluster 3:

Remote,

but

diversified

and

successful

Cluster 4:

Accessible,

successful and

diversified

Overall

mean

values

1. Geographical

characteristics

Land area 325.85 45.20 150.73 130.97 186.75

Population 2529.26 260.37 3083.58 23704.33 5211.35

Population density 18.35 9.68 24.66 205.09 45.31

Access to London 747.52 829.81 932.54 446.47 761.31

Access to EU 984.72 1013.64 1077.95 728.31 972.62

Perindex-ECU 85.86 90.78 95.33 74.23 87.32

Airfield 0.35 0.44 0.33 0.22 0.35

2. Economic

performance

Active population 45.54 52.64 52.04 59.21 50.78

Active male 55.70 58.12 57.33 51.67 56.07

Active female 44.30 41.87 42.67 48.33 43.93

Working age pop. 60.91 65.56 64.25 68.11 63.90

Employed 91.83 92.94 97.42 96.22 93.90

Unemployed 8.09 7.00 2.42 3.22 5.93

Self employed 27.04 43.62 22.50 28.33 30.75

Agriculture 13.82 29.69 11.83 6.17 16.51

Manufacturing 7.69 5.44 13.75 8.67 8.45

Service 56.13 43.94 61.00 66.67 55.43

Occupancy 75.39 74.62 90.00 72.67 77.70

N 23 16 12 9 60

Table 4 provides a list of the 23 islands that comprise cluster 1. As can be seen, the islands are

all Scottish offshore islands, containing within them some of the larger (in terms of land area),

but low population density west coast offshore islands (e.g. Arran, Bute, Jura, Mull, Skye,

Harris and Lewis). These are popular tourist destination islands, but lack diversified sectoral

structures. This group of Scottish islands forms the least economically successfully performing

cluster of islands within the whole British data set. They have some agriculture and fishing, but

30

their mainstay is tourism from which they make a modest living. As shall be shown later, the

nearest Greek equivalent islands to cluster 1 make a much better living from tourism than do

the cluster 1 British islands. This is almost certainly a reflection of two factors: (a) the Greek

islands command much larger absolute flows than the Scottish west coast islands (not as a

result of greater remoteness, but almost certainly because of climate), and (b) many of the

Greek islands can benefit from more types of tourism flows as a result of the much greater

closeness of Athens to the Greek islands, whilst the Scottish islands are very distant from

London and the other big British cities (enabling the Greek islands to access more day trip,

overnight and weekend tourism than the Scottish islands).

Table 4: Larger but lagging, dependent on tourism.

Cluster 1: Larger but lagging, dependent on tourism

North Uist Seil

South Uist Arran

Unst Bute

Barra Jura

Benbecula Islay

Fetlar Mull

Great Bernera Luing

Vatersay Raasay

Scalpay Tiree

Eriskay Great Cumbrae

Skye Lismore

Lewis and Harris

Table 5 lists the 16 British islands that comprise cluster 2, which can be labelled as ‘Small,

remote and agriculture dependent’. Returning to the mean values in Table 3, it can be seen that

in the islands belonging to this cluster the agricultural sector accounts, on average, for no less

than 29.69% of all economic activity (compared with the overall average for all islands of

16.51%, itself a high value by British regional standards). In addition, the average land area of

these islands is a mere 45.20 square kilometres, despite which they still have below-average

31

size populations and population densities. The islands in this cluster exhibit all the

characteristics of traditional agricultural economies – high male activity rates and levels of

self-employment, but low female activity rates and a generally weak economic performance in

terms of high unemployment and low employment rates. Property occupation rates are also low.

Finally, as Table 3 again shows, these small, agricultural islands are relatively remote, both

from London and also the wider EU, despite many of them nowadays having small airfields.

Taken together, clusters 1 and 2 comprise no fewer than 39 of the 60 British offshore islands.

As shall be shown later, the Greek islands exhibit far smaller groups of poorly economically

performing islands than is the case in Britain. In this respect the two sets of islands are very

different from one another.

Table 5: Small, remote and agriculture dependent.

Cluster 2: Small, remote and agriculture dependent

Stronsay Flotta

Westray Berneray

North Ronaldsay Rousay

Papa Westray Shapinsay

Eday Housay

Gigha

Sanday

Coll

Eigg

Hoy

South Ronaldsay

Turning to the list of 16 islands in cluster 2, once again we see that the cluster comprises

wholly Scottish islands, this time being extremely small and remote ones, many actually

offshore from other (larger) Scottish islands. This time, unlike cluster 1, they include small

islands from Orkney (e.g. Papa Westray, Hoy) as well as the west coast Scottish islands (e.g.

Eigg, Coll).

Turning now to cluster 3, Table 3 shows that this comprises 12 islands. We have characterised

this as ‘remote, but diversified and successful’. They are relatively successful since they are

32

characterised by relatively high employment rates (97.42%), working age population (64.25%),

high male activity rates (57.33%), high self-employment (22.50%), and low unemployment (a

mere 2.42%). These islands have diversified economies, with disproportionate shares of both

manufacturing (13.75%) and services (61.00%), and a still-robust agriculture sector too

(11.83%). These are, however, relatively remote islands, both from London and the wider EU,

with low rates of airfield provision.

The combination of remoteness with both diversification and a relatively successful economy

is an unusual one. Table 6, which lists all the islands that belong to this cluster, gives us the

reason for this unusual cluster.

Table 6: Cluster 3: Remote, diversified and successful

Cluster 3: Remote, but diversified and successful

Mainland of Orkney

Mainland of Shetland

Whalsay

Fair Isle

Bressay

East Burra

Muckle Roe

Grimsay (North)

Yell

West Burra

Burray

Trondra

This cluster is dominated by Orkney (main island) and Shetland (main island). These are

islands with extremely distinctive landscapes and culture which have been successful in

attracting tourism, are big enough to have generated some manufacturing and, most

importantly of all, in the case of Shetland have been able to enjoy high levels of income from

oil companies exploiting rich offshore oil reserves. Shetland in particular has used the oil rents

33

to diversify its economy. This is the sole case for the islands of both countries where (apart

from fish stocks) there is a significant natural resource endowment.

Finally, Table 3 identifies one further significant cluster, cluster 4. We have characterised it as

‘accessible, successful and diversified’. It is interesting that this cluster contains only nine

islands. It shows once again that the British offshore islands are mostly less successful

economic entities, with the two successful clusters (i.e. clusters 3 and 4) containing relatively

few of the 60 islands of the full data set.

Table 7: Accessible, diversified and successful islands of England and Wales

Cluster 4: Large, accessible, diversified and successful

Colonsay

Iona

St. Agnes

St. Martins

Tresco

St. Mary's

Anglesey

Isle of Wight

Isle of Walney

The average population of these islands is 23,704.33, which is nearly five times the overall

average for all UK islands. However, scrutiny of Table 7 which lists the nine islands in cluster

4 shows that the mean value in this case is dominated by Anglesey (in Wales) and the Isle of

Wight (in England). The remaining seven are much smaller islands, as is reflected in the land

area value of only 130.97 sq. km. More important is the fact that these are generally successful

and diversified economies. In particular, economic activity rates are relatively high (59.21%

when the average for all GB islands is only 50.78%), high employment rates, high female

activity rates and low unemployment rates (3.22%). The manufacturing and service sectors are

disproportionately large (8.67% and 66.67% respectively), and there remains a substantial

agricultural sector (6.17%). Finally, these are the least remote of all the British islands, both in

terms of access to London and to the wider EU. The cause of the low remoteness mean values

is apparent when one scrutinises Table 7 – this cluster is dominated by the main islands of

England (Isle of Wight and the Scilly Isles) and Anglesey (north Wales), all of which are more

34

accessible than their Scottish counterparts. There are only two Scottish members of this

contingent of islands.

In summary:

• The 60 British offshore isles have been divided by the cluster analysis into four groups, two

of which are relatively economically unsuccessful (clusters 1 and 2) and two of which are

relatively successful (clusters 3 and 4).

• The numbers of islands which fall within the relatively unsuccessful clusters are more

numerous than those in the successful clusters (39 of the 60 islands are in clusters 1 and 2).

• It is the more diversified economies which are the successful islands. Those which are

highly specialised on either just tourism (cluster 1) or agriculture & fishing (cluster 2) tend

in a British context to be less successful.

• There does seem to be a systematic adverse effect of remoteness – accessibility matters. Of

the two less successful clusters, cluster 2 are remote islands, whilst cluster 1 is made up of

islands which are close to the mean value for remoteness, which is very high for the British

islands given the predominance of Scottish islands in the set (very distant from both the UK

national capital, London and also the rest of the EU). The most successful cluster (cluster 4)

is made up almost wholly of the most accessible islands in England and Wales. The sole

exception to the rule that ‘accessibility matters’ is cluster 3. As we have seen, however, this

is dominated by Shetland (and to a lesser extent Orkney), where access to income flows

from oil resource rents have had an important effect. A good natural resource endowment

(and ability to access some of the oil rents even though the local governments are relatively

weak in the UK9). Cluster 3 is therefore the ‘exception that proves the rule’ as far as

remoteness is concerned.

There does not seem to be any systematic relationship between island size (either land area or

population) and economically successful performance.

9 Shetland is a classic example of how a local government can negotiate favourable deals with oil companies seeking to build terminals within a region, even where the natural resource is not a locally owned resource.

35

The Greek islands

Applying the same cluster analysis methodology to the 63 case Greek islands data set resulted

in the identification of six distinct clusters (see Figure 3). Table 8 sets out the cluster mean

values for the same 18 variables that were used to build the Greek island typologies.

Table 8: Mean values, by variable for the six Greek island clusters

Variables

Cluster 1:

Small,

remote from

EU and

agriculture

dependent

Cluster 2:

Small,

remote from

Athens and

the EU ad

agriculture

dependent

Cluster 3:

Accessible,

successful

and

diversified

Cluster 4:

Ionian

islands,

large,

dependent

on agric.

And

tourism

Cluster 5:

Inshore,

diversified,

but mixed

economic

performanc

e

Cluster 6:

Crete

Overall

mean values

1. Geographical

characteristics

Land area 80.90 69.42 419.86 276.69 443.98 8336.00 372.58

Population 1293.87 2507.71 23227.07 26585.87 28250.70 601131.

00

23797.57

Population density 17.33 38.50 64.27 96.37 114.60 72.00 59.56

Access to Athens 169.43 296.41 210.69 332.54 80.75 316.97 216.45

Access to EU 2223.22 2347.82 2251.13 1809.06 2063.98 2381.73 2182.21

Perindex-ECU 95.09 98.75 97.05 92.93 89.30 97.84 95.22

Airfield 0.13 0.21 0.80 0.37 0.10 1.00 0.35

2. Economic

performance

Active population 38.33 36.21 39.07 37.75 37.20 44.00 37.87

Active male 70.47 73.71 66.53 67.50 71.30 62.00 69.87

Active female 29.53 26.29 33.47 32.50 28.70 38.00 30.13

Working age 62.47 66.79 67.13 65.25 68.10 67.00 65.86

Employed 94.20 83.14 90.27 86.87 88.00 89.00 88.81

Unemployed 5.80 16.86 9.73 13.12 12.00 11.00 11.19

Self employed 28.53 19.43 15.33 22.12 15.70 23.00 20.43

Agriculture 25.40 16.57 8.93 17.12 8.40 22.00 15.71

Manufacturing 3.73 3.86 5.33 4.12 6.60 6.00 4.68

Service 39.27 47.21 56.47 49.25 53.40 51.00 48.82

Occupancy 35.93 46.00 49.60 56.25 45.90 65.00 46.05

N 15 14 15 8 10 1 63

36

Once again, as in Table 3, values with greater than average mean scores for a given variable

are picked out in bold type and with a shaded cell background.

The first distinctive feature of Table 8 is cluster 6. This contains a single island case, Crete. In

some ways this is reassuring. Crete is by far the biggest island both in terms of land area (land

area 8,336 squared kilometres, when the overall average for all Greek islands is 372.58 squared

kilometres) and population (over 600,000 compared to an average of only 24,000 persons) of

all of the islands within both the Greek and British data sets, as the land area and population

values for the cluster 6 column in Table 8 show. Crete is a big, not very accessible island (to

either Athens or the EU), but with excellent airport connections for tourists from mainland

Greece and northern Europe. As a result, it is relatively successful, with one of the highest

employment rates, a large service sector and very frequent fast ferry-boat connections to the

Athens port of Pireaus. It can hardly be described as inaccessible or isolated. It is truly an

outlier case in statistical terms and it is identified as such by the cluster analysis. It is, moreover,

both a relatively remote island, but also a diversified and relatively successful one. There does

therefore, in this case, seem to be a size effect. Extremely large islands, such as Crete, may be

able to overcome the disadvantages of remoteness.

However, we must be careful not to jump too quickly to this conclusion – we have a sample of

only one such large island in our data sets, and Crete has outstanding natural environment and

climate advantages which have made it a major tourist destination for northern EU citizens.

This may be a resource effect at work here and not a size effect. Our analysis is incapable of

resolving this issue.

Leaving Crete to one side, and hence concentrating on the other five clusters, cluster 1 is a

large group comprising 15 islands. We have labelled this described as a ‘Small, remote from

EU and agriculture dependent’ cluster. The closest equivalent to this cluster in Britain is cluster

2 (made up largely of Scottish small islands). In the cluster 1 Greek islands, agriculture

accounts for 25.40% of all economic activity (the average value for all Greek islands is

15.71%). As with their Scottish equivalents, the cluster 1 Greek islands also show the

characteristic features of agricultural economies – high male activity rates but low female

activity rates, high rates of self employment and a high overall activity rate. The only

difference between cluster 1 in Greece and its equivalent in Britain (cluster 2) is that the Greek

islands have a relatively low unemployment rate whereas this was higher than average in the

British cluster 2. Occupancy rates are again, however, low. These are not very economically

successful islands. Moreover, as with their British counterparts, these are generally remoter

islands and lack good airport facilities. However, as Table 8 shows, this group are remoter than

37

other Greek islands from the EU, but not from the national capital, Athens. This shows that it

is possible for agriculture dependent islands to continue to exist relatively close to Athens, if

they are small enough and (presumably) if they lack good marine ferry and air links to Athens.

Table 9 lists all the islands that make up the Greek cluster 1.

Table 9: Small, remote from EU and agriculture dependent Greek islands

Cluster 1: Small, remote from EU and agriculure dependent

Serifos

Sifnos

Antiparos

Kea

Kythnos

Agios Efstratios

Folegandros

Schinoussa

Amorgos

Kimolos

Sikinos

Kythera

Skyros

Anafi

Irakleia

About two thirds of these islands are located in the administrative prefecture of Cyclades,

located south east of mainland Greece. It is noteworthy that this is a relatively prosperous

island region of Greece with very frequent ferry-boat services. Nevertheless, the Cluster 1

comprises most of the smallest inhabited islands of the Cyclades region, For instance,

Antiparos is a very small island (1037 enumerated inhabitants in the 2001 census and land area

34.83 squared kilometres) located very near the much larger island of Paros. Antiparos does

not have frequent direct ferry services to Pireaus and the other large islands of the region, but is

38

indirectly connected to them via Paros (which is a very well developed island and, according to

our analysis, it belongs to Cluster 3 discussed below). Likewise, Kimolos is similar island (769

inhabitants and a land area of 35.71 squared kilometres) located near the larger island of Milos.

It is noteworthy that most of the islands in Cluster 1 belong to the so called unprofitable

shipping line which is known in Greece as the “losing line” (in Greek “ μμ ” which

literally means the “unproductive line” or the “infertile line”). Boats serving the islands on this

line are typically subsidised by the Greek state. As noted above, most of the islands of this

cluster belong to the Cyclades archipelago. The rest of the islands belong to administrative

prefectures elsewhere in the Aegean Sea. For instance, Agios Efstratios (371 inhabitants, 43.23

squared kilometres) is a very small island which is located in the North Aegean and belongs to

the prefecture of Lesvos (and is very near the large and relatively prosperous island of Lesvos

which belongs to Cluster 3 discussed below). Also, Skyros belongs to the Sporades archipelago

(also comprising the more prosperous and accessible islands of Skiathos, Skopelos and

Alonissos, that belong to Cluster 5 discussed below).

Returning to Table 8, it can be seen that Cluster 2 is also a large group, comprising 14 islands.

These too, like cluster 1 have a disproportionately large agriculture sector (16.57%) and are

again on average small islands (the average cluster mean for land area is 69.42 sq. km. against

the overall average of 372.58 sq. km.). These islands are even more similar than cluster 1 to

their British equivalents (cluster 2 in Britain). In this case they have relatively high

unemployment rates (on average 16.86% when the overall average for all Greek islands is

11.19%), and they have many of the characteristic features of rural economies (i.e. high male,

but low female activity rates), although self-employment rates and workforce sizes are slightly

below the overall Greek islands average. As with the British cluster 2 islands, these are not

successful economies. They are, moreover, as with their British counterparts relatively remote,

this time both from Athens and the wider EU (the distance from Athens is on average 296.51

km against an overall Greek island average of 216.45 km.). This cluster has therefore been

labelled as ‘Small, remote from both Athens and EU and agriculture dependent’. Table 10 lists

all the islands that belong to Cluster 2. It is noteworthy that half of these islands are located in

the Dodecanese region, located in the southeast Aegean Sea and off the South West coast of

Turkey. All but one (the island of Ios, which belongs to the Cyclades archipelago) of the rest of

the islands in this cluster are located in the East and north-East Aegean. It can be argued that

the islands this Cluster of islands is very similar to the equivalent of the Scottish North Atlantic

cluster (Cluster 2 of the British islands) as the islands in both clusters are very similar in terms

of size, accessibility and economic development. The Scottish North Atlantic islands face onto

the Atlantic Ocean, whereas the Greek Cluster 2 islands are far from the Greek mainland and

39

face onto Turkey, which is a non-EU country and has very limited trade and other links with

the Greek islands. It is noteworthy that when compared to Cluster 1 of Greek islands discussed

above, Cluster 2 islands are similar in terms of size and dependence on the agricultural sector,

but they are much more remote than their Cluster 1 counter-parts. It is also worth noting that as

it was the case with islands such as Antiparos in Cluster 1, there are some very small islands in

Cluster 2 which are very near larger islands that are relatively more prosperous. For instance,

Psara (located in the northern Aegean) is a very small island (422 inhabitants, 39.77 squared

kilometres) which is located very near the much larger and more prosperous island of Chios

(belonging to Cluster 3 discussed below). Similarly, most of the Dodecanese islands in this

cluster are located near the much larger and prosperous islands of Rhodes and Kos.

Table 10: Small, remote from both Athens and the EU, and agriculture-dependent Greek

islands

Cluster 2: Small, remote from both Athens and EU, and agriculture dependent

Kalymnos

Symi

Patmos

Inousses

Nisyros

Ios

Tilos

Psara

Thirasia

Karpathos

Kasos

Astipalaia

Leipsoi

Agathonisi

40

Taking the Greek clusters 1 and 2 together (as agriculture dependent, relatively remote and

small), and comparing them with their (single cluster) British counterparts (cluster 2), it can be

seen that they share many common features. The principal differences are solely:

• Not all of this type of island in Greece is highly remote (at least in terms of how the crow

flies). Cluster 1 islands are remote from the EU, but not from Athens. This highlights a key

difference between the Greek islands and those of Britain. The principal metropolitan

centre of the nation (and source of most national tourists, second home owners and the like)

is much closer to the main sets of islands in Greece than it is in Britain. The Athens

‘economic shadow’ therefore is likely to fall over many more of the Greek islands than

does London (and the other big British cities) does for the British offshore islands, most of

which are far away in northern Scotland. Despite this difference, it is clear that relatively

unsuccessful agriculture-based small island economies can continue to exist even close to

Athens. Whether this is the result of poor local marine and air links is an issue which is

beyond the scope for this paper and must await further research.

• Britain has rather more of this type of traditional rural small island economy (39 of 60

islands in the set – well over half) than is the case in Greece (29 of the 63 islands in the set

– under half).

Turning to the Greek cluster 3, Table 8 shows this is another large group, made up of 15

islands. We have labelled this as ‘Accessible, successful and diversified’ and it is a cluster with

a close British counterpart (cluster 4 on Table 3). Like the British cluster 4, the Greek cluster 3

is a relatively successful set of islands (low unemployment, high activity rates – especially for

females, a high employment rate, high residential occupancy rates, and a high workforce rate).

The cluster is also diversified, with both manufacturing and services (especially tourism one

suspects) over-represented. The British equivalent cluster was made up of English and Welsh

islands which were highly accessible to both London and the wider EU. The situation for

Greece’s cluster 3 is slightly different – the islands are relatively accessible to Athens, but

remoter than average from the EU. However, scrutiny of Table 8 shows that cluster 3 islands

have good airport provision (the best of all the Greek island clusters) and one suspects that

excellent airport access to northern Europe is actually greatly reducing the remoteness from the

EU that islands in this cluster exhibit.

Table 11, which lists the islands in cluster 3 shows that many of the islands in this cluster are

located in the East Aegean Sea and away from the Greek mainland. For instance, Rhodes and

Kos are located 428.70km and 323.92km away from Athens respectively, but they both have

airports (as well as frequent ferry-boat connections to the port of Pireaus, which however is not

41

captured by this data set) and are more connected to the Greek mainland compared to the

islands in cluster 2.

Finally, as with the British counterpart cluster (cluster 4), the Greek cluster 3 is not dominated

by just large islands; there are small islands in this group too.

Table 11: Accessible, successful and diversified Greek islands

Cluster 3: Accessible, successful and diversified

Kos

Rhodes

Milos

Andros

Tinos

Paros

Mykonos

Leros

Syros

Thira

Chios

Samos

Naxos

Lesvos

Donoussa

The remaining two Greek island clusters (excluding Crete – cluster 6) have no directly

comparable British counterparts. Taking cluster 4 in Greece first, Table 8 shows that this is a

small cluster comprising only eight islands. This is a very interesting cluster in terms of its

characteristics. It is the most accessible of all Greek island groups to the main northern EU

markets, and it has better than average airport infrastructures. On the other hand, it is relatively

remote from Athens. Economic performance is a mixed one. The service sector is well

developed, with presumably strong tourism sectors, but there is also still a disproportionately

42

large dependence on agriculture – manufacturing is poorly developed. These are more like dual

economy islands than diversified ones. The result is a mixed economic performance picture –

good rates of self employment and high female activity rates (as is characteristic of tourist

economies), but also relatively high unemployment, low employment rates and low male

activity rates. These are far from being uniformly successful island economies. Finally, cluster

4 is made up of relatively large (average population of 26,586 persons) population islands.

Table 12 solves the mystery of this unusual Greek island cluster. It is dominated by the Ionian

Sea islands located off the western seaboard of Greece. These are islands with good

agricultural conditions, closer to the rest of the EU than all other Greek islands (an advantage

enhanced by good airport infrastructure, and hence strong tourism flows), and they are usually

large islands. It is their distance from Athens which is their main disadvantage, hence the

unusual combination of agriculture and tourism, and hence the mixed picture of economic

performance. We have labelled these ‘Ionian islands, large, dependent on both tourism and

agriculture’. There is no equivalent British island cluster counterpart.

Table 12: Ionian islands, large, dependent on tourism and agriculture.

Cluster 4: Ionian islands, large, dependent on both tourism and agriculture

Othoni

Paxi

Ithaki

Lefkada

Kefalonia

Zakynthos

Kerkyras

Erikoussa

Finally, for Greece there is cluster 5. This too has no direct British counterpart. As Table 8

shows, cluster 5 comprises 10 islands which, as table 13 shows, are all located in the Aegean

Sea. We have labelled this cluster ‘Inshore, diversified, mixed economic performance’. As

Table 8 shows, most of these islands are very accessible. Indeed, they are by far the most

accessible of all of the Greek islands to Athens (and indeed, the Greek mainland in general

(and hence the national market) since this group includes both Evia and the Sporades group of

43

islands comprising Skopelos, Alonissos and Skiathos). They also have better than average

accessibility to the rest of the EU. For instance, Aegina is located only 39 km away from

Athens, a distance which can be covered in about 30 minutes on a high speed boat.

Apart from Skiathos, these islands are not major tourist destinations for visitors from northern

Europe and beyond. On the other hand, these are islands which are popular locations for

second homes for residents of Athens and the other mainland Greek cities. Moreover, they are

accessible enough to attract weekend and overnight visitors, and in some cases (e.g. Salamis,

Aegina) day trippers too from Athens.

Table 13: Inshore, diversified, mixed economic performance islands islands

Cluster 5: Inshore, diversified, mixed economic performance

Agistri

Skopelos

Alonissos

Aegina

Spetses

Hydra

Poros

Skiathos

Evia

Salamina

Cluster 5 is an extremely interesting cluster in that it reveals that accessibility need not always

be the benefit that the research literature implies. In the case of the cluster 5 islands, one can

perhaps argue that they are too close for comfort to Athens and the other mainland big cities.

Large levels of second home ownership in a community can severely damage social cohesion

and economic performance. The influx of visitors at a weekend or at even more infrequent

intervals leaves the communities with very little in the way of income streams for long periods

during the week and across many months of the year. Moreover, whilst weekend visitors do

pump money into the local economy by way of hotel rentals and the like, day trippers spend

relatively little money locally, and can often bring a lot of the food, drink and other goods they

need with them.

44

In other words, the very proximity to Athens and the other mainland Greek cities may be

having a profound and unusual effect on the types of tourism and visitors. There is no British

counterpart to this cluster since virtually all of the British islands are so far from London and

the other large English cities that this sort of impact is extremely small. The result of the types

of visitors to the inshore Greek islands is to generate a decidedly mixed economic performance.

On the one hand, male activity rates and workforce rates are quite high, but there are none of

the other benefits enjoyed by other Greek tourist island – female activity rates are low, self-

employment is low since it is hard to sustain small businesses with so much second home

ownership, overall employment rates are low and unemployment rates are high. This would

appear to be one situation where good accessibility is operating to the detriment of the islands’

economic performance.

5. Conclusion

This paper has drawn upon cluster analysis to examine the relationship between various

measures of economic performance, and a number of geographical characteristics (particularly

size, population density and various measures of accessibility to national and EU markets). The

paper compares two very different sets of island economies – 60 offshore British islands and

63 Greek islands. The data principally refer to the year 2001, when population censuses were

conducted in both countries.

The main findings of the paper are as follows:

• The analysis has revealed that clear and distinctive clusters of islands can be identified

(across the 18 variables used within the cluster analyses) within both Greece and Britain.

Moreover, it has been possible to interpret a coherent picture of the reasons for these very

different clusters. Moreover, the different clusters show quite wide variations in the levels

of economic performance.

• Land area and population size does not seem to be systematically related to economic

performance. In this respect, the findings of the paper are in accord with previous research.

The sole possible exception to this finding is the island of Crete, which is just so large (and

successful), compared to the other islands in the data set, that the cluster analysis separated

it out as a separate cluster in its own right.

• Whilst the British and Greek islands do share a number of common characteristics (the

reason why we selected the two countries for the analysis in the first case), there turned out

also to be some important differences. Hence the two sets of islands are relatively remote

45

from the main EU markets. Moreover, the north western Scottish island seem to share with

Greece’s eastern Aegean (Dodecanese) islands a particularly severe degree of remoteness

from both national and EU markets and being at the very edge of the EU (with the North

Atlantic lying beyond the Scottish islands and Turkey – whose border was largely closed to

the Greek islands in 2001 – lying beyond the Dodecanese islands). A final similarity is that

many of the islands in both countries have developed large tourism-related service sectors.

On the other hand, there turned out to be important differences. Greek islands have a major

climate advantage for summer tourists who are willing to travel long differences to enjoy

this resource. The offshore British islands lack this climatic advantage and must rely on

different types of visitors. There is also a major difference in the accessibility

characteristics of the two sets of islands. The British islands are virtually all both remote

from the EU and also their national capital city, whereas although Greek islands are also

remote from the wider EU, many of them are extremely close to both Attiki and other

Greek mainland population centres. Finally, the Shetland Isles of Britain are the sole group

of islands with a significant natural resource endowment – oil. This too turned out to be an

important feature influencing the results obtained.

• Given the similarities and differences between the two sets of islands, it is perhaps not

surprising that in some cases the clusters identified are almost identical in their

characteristics whilst others are not:

Clusters 1 and 2 from the Greek analysis are very similar indeed to cluster 2 from the

British analysis. These tend to be small, relatively remote islands which have retained a

higher than average dependency on agriculture and which, as a result, perform

relatively poorly. They are mainly north western Atlantic islands in Britain and

Dodecanese islands in Greece. Interestingly however, in Greece there is also a set of

these small islands which are remote from the EU but quite close to Athens (cluster 1)

and yet do not seem to have (yet) experienced any major benefits (or costs) from their

proximity to Athens.

Cluster 4 from the British analysis and cluster 3 from the Greek analysis comprise

islands which have benefited from their good accessibility characteristics to develop

successful and diversified economies. In the British case these are mainly English and

Welsh offshore islands rather than Scottish.

Here the similarities end, and there is one British cluster and three Greek clusters which

have no equivalents in the other country. In Britain, cluster 4 is made up of remote, but

diversified and successful islands, This cluster is dominated by the Shetland Islands

46

with their access to (parts of) the offshore oil resource. In Greece, the analysis picks out

three unusual clusters: (a) Crete – an outlier case which perhaps ought to have been left

out of the analysis, (b) cluster 4, the Ionian Sea islands which are large, relatively

agricultural productive and more accessible than other Greek islands to northern EU

tourist markets, as a result of which they are relatively successful, and (c) a very

interesting cluster of 10 Greek islands (cluster 5) which are inshore islands very

accessible to Athens. This is the one case where accessibility seems to have worked to

the disadvantage of the island economies since this group of small inshore islands have

economies distorted by the presence of many holiday homes, day trip and weekend

tourists, which would appear to be less lucrative types of tourist markets than found

elsewhere among the Greek islands.

This paper remains very much work in progress. It is apparent from the results obtained that

the various accessibility measures we have used remain inadequate. In particular, we will seek

in future research to refine the maritime and air transport accessibility measures so that they

more adequately reflect the reality on the ground. For example, our ‘Airfield’ measure is a

simply ‘dummy’ variable which cannot differentiate size of airport or destinations served (or

number of airports – for instance Crete has two international airports). The economic

performance measures too need to be extended, and data on GDP, incomes, migration and

human capital endowments would be very helpful. Finally, the research would benefit from the

inclusion of detailed resource (especially fish, oil) and climate variables, since these appear to

have been important in separating out some of the clusters. A variable which measures how

mountainous each island is would also be worth incorporating given the importance of

mountain regions in European Commission thinking on geographical ‘handicaps’.

47

Appendix: Description of Variables Used in the Cluster Analysis

As has been noted in the text of the paper, the variables used in the cluster analysis can be

classified into two broad types – geographical characteristics and economic performance

characteristics. The full list of the 18 variables used, and their precise definitions are set out in

the table below.

Variables Definition

Geographic Characteristics British Census Greek Census

Land area Total surface area in square kilometres

Total surface area in square kilometres

Population Total number of permanent residents

Total number of permanent residents

Population density Residents per square kilometre

Residents per square kilometre

Access to national capital city Great circle distance in kilometres to London

Great circle distance in kilometres to Athens

Access to European Union Great circle distance in kilometres to Brussels

Great circle distance in kilometres to Brussels

Peripherality Index-ECU Copus (1999) peripherality index for the 1998 NUTS 3 region of which the island is a part using GDP as the mass variable in current prices (Euros)

Copus (1999) peripherality index for the NUTS 3 region of which the island is a part using GDP as the mass variable in current prices (Euros)

Airfield Presence or absence of an airfield

Presence or absence of an airfield

Economic Characteristics Active population Total economically active

population (age 16 -74) as a percentage of total population

Total financially active population (age 10 and above) as a percentage of total population

Active male Total economically active male (age 16 -74) as percentage of total active population

Total financially active male (age 10 and above) as percentage of total active population

Active female Total economically active female (age 16 -74) as percentage of total active population

Total financially active female (age 10 and above) as percentage of total active population

Working age Population aged 15-64 as percentage of total population

Population aged 15-64 as percentage of total population

48

Variables Definition

Economic Characteristics British Census Greek Census

Employed All people aged 16-74 in employment as a percentage of total active population

All people aged 10 and above in employment as a percentage of total active population

Self employed All people aged 16-74 self- employed as a percentage of total employed

All people aged 10 and above self- employed as a percentage of total employed

Unemployed All people aged 16-74 unemployed as a percentage of (total employed and total unemployed)

All people aged 10 and above unemployed as a percentage of (total employed and total unemployed)

Agriculture All people aged 16 – 74 in employment working in agriculture, hunting, forestry and fishing as a percentage of total active population

All people aged 10 and above employed in agriculture, animal breeding, forestry and fishing as a percentage of total active population

Manufacturing All people aged 16 – 74 in employment working in manufacturing as a percentage of total active population

All people aged 10 and above employed in manufacturing as a percentage of total active population

Services All people aged 16 - 74 in employment working in services (retail and distribution, hotel and restaurants, transport, storage and communication, financial intermediation and real estate, public administration and defence, education and health and social work) as a percentage of total active population

All people aged 10 and above employed in services (retail and distribution, hotel and restaurants, transport, storage and communication, financial intermediation and real estate, public administration and defence, education and health and social work) as a percentage of total active population

Occupancy Total occupied dwellings as a percentage of total dwellings

Total occupied dwellings as a percentage of total dwellings

49

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Table 1: List of British Islands

Island NUTS 3 Region

Anglesey Isle of Anglesey

Arran Lochaber, Skye and Localsh and Argyll and the Islands

Barra Eilean Siar/Western Isles

Benbecula Eilean Siar/Western Isles

Berneray Eilean Siar/Western Isles

Bressay Shetland Islands

Burray Orkney Islands

Bute Lochaber, Skye and Localsh and Argyll and the Islands

Coll Lochaber, Skye and Localsh and Argyll and the Islands

Colonsay Lochaber, Skye and Localsh and Argyll and the Islands

East Burra Shetland Islands

Eday Orkney Islands

Eigg Lochaber, Skye and Localsh and Argyll and the Islands

Eriskay Eilean Siar/Western Isles

Fair Isle Shetland Islands

Fetlar Shetland Islands

Flotta Orkney Islands

Gigha Lochaber, Skye and Localsh and Argyll and the Islands

Great Bernera Eilean Siar/Western Isles

Great Cumbrae Lochaber, Skye and Localsh and Argyll and the Islands

Grimsay Eilean Siar/Western Isles

Housay Shetland Islands

Hoy Orkney Islands

Iona Lochaber, Skye and Localsh and Argyll and the Islands

Islay Lochaber, Skye and Localsh and Argyll and the Islands

Isle of Walney West Cumbria

Isle of Wight Isle of Wight

Jura Lochaber, Skye and Localsh and Argyll and the Islands

Lewis and Harris Eilean Siar/Western Isles

Lismore Lochaber, Skye and Localsh and Argyll and the Islands

53

Luing Lochaber, Skye and Localsh and Argyll and the Islands

Mainland of Orkney Orkney Islands

Mainland of Shetland Shetland Islands

Muckle Roe Shetland Islands

Mull Lochaber, Skye and Localsh and Argyll and the Islands

North Ronaldsay Orkney Islands

North Uist Eilean Siar/Western Isles

Papa Westray Orkney Islands

Raasay Lochaber, Skye and Localsh and Argyll and the Islands

Rousay Orkney Islands

Sanday Orkney Islands

Scalpay Eilean Siar/Western Isles

Seil Lochaber, Skye and Localsh and Argyll and the Islands

Shapinsay Orkney Islands

Skye Lochaber, Skye and Localsh and Argyll and the Islands

South Ronaldsay Orkney Islands

South Uist Eilean Siar/Western Isles

Stronsay Orkney Islands

St. Agnes Cornwall and Isles of Scilly

St. Martin's Cornwall and Isles of Scilly

St. Mary's Cornwall and Isles of Scilly

Tiree Lochaber, Skye and Localsh and Argyll and the Islands

Tresco Cornwall and Isles of Scilly

Trondra Shetland Islands

Unst Shetland Islands

Vatersay Eilean Siar/Western Isles

West Burra Shetland Islands

Westray Orkney Islands

Whalsay Shetland Islands

Yell Shetland Islands

54

Table 2: List of Greek Islands

Island NUTS 3 Region

Aigina Attiki

Agathonisi Dodekanisos

Agios Efstratios Lesvos

Agistri Attiki

Alonissos Magnisia

Amorgos Kyklades

Anafi Kyklades

Andros Kyklades

Antiparos Kyklades

Astipalaia Dodekanisos

Chios Chios

Crete Crete

Donoussa Kyklades

Erikoussa Kerkyra

Evia Evvoia

Folegandros Kyklades

Ydras Attiki

Inousses Chios

Ios Kyklades

Irakleia Kyklades

Ithaki Kefallinia

Kalymnos Dodekanisos

Karpathos Dodekanisos

Kasos Dodekanisos

Keas Kyklades

Kefalonia Kefallinia

Kerkyras Kerkyra

Kimolos Kyklades

Kos Dodekanisos

Kythira Attiki

55

Kythnos Kyklades

Lefkada Lefkada

Leipsoi Dodekanisos

Leros Dodekanisos

Lesvos Lesvos

Milos Kyklades

Mykonos Kyklades

Naxos Kyklades

Nisyros Dodekanisos

Othoni Kerkyra

Paros Kyklades

Patmos Dodekanisos

Paxi Kerkyra

Poros Attiki

Psara Chios

Rhodes Dodekanisos

Salimina Attiki

Samos Samos

Schinoussa Kyklades

Serifos Kyklades

Sifnos Kyklades

Sikinos Kyklades

Skiathos Magnisia

Skopelos Magnisia

Skyros Evvoia

Spetses Attiki

Symi Dodekanisos

Syros Kyklades

Thira Kyklades

Thirasia Kyklades

Tilos Dodekanisos

Tinos Kyklades

Zakynthos Zakynthos

56

Figure 1: Planistat Europe Conceptual Framework

Source: Planistat Europe, Bradley Dunbar Associates (2003a), p.9.

Figure 2: Cluster Analysis of UK Islands Using Ward’s Method

Case-by-Case Analysis

0 5 10 15 20 25

+----------+---------+----------+----------+---------+-

North Uist (2) 37 �� South Uist 47 ���� Unst 55 �� ����� Barra 3 �� � � Benbecula (3) 4 ���� ��� Fetlar 16 �� � � Great Bernera 19 ���� � ��� Vatersay 56 �� ����� � � Scalpay (Harris) 42 ���� � � Eriskay 14 ���������� � Arran (3) 2 �� ��� Bute (2) 8 �� � � Seil 43 �������� � � Islay 25 �� � � � Mull (4) 35 �� � � � Jura 28 �� ����� ��������� Luing (4) 31 �� � � � Raasay (2) 39 �� � � � Tiree (2) 52 ���� � � � Great Cumbrae 20 �� ����� � � Lismore 30 ���� � � Lewis and Harris 29 �������������� � Skye (6) 45 �� ��������� Stronsay (3) 51 �� � � Westray (2) 58 ���� � � North Ronaldsay 36 �� � � � Papa Westray 38 �� � � � Eday 12 �� ����� � � Gigha 18 ���� � � � Sanday (Orkney) 41 ���� � � � Coll 9 ������ ��������������� �

Eigg (6) 13 �� � � � Hoy 23 �� � � ������� South Ronaldsay 46 �� ��� � Flotta 17 �� � � Berneray (North U 5 ���� � � Rousay (3) 40 �� ��� � Shapinsay 44 �� � � Housay (2) 22 ���� � Mainland of Orkne 32 �� � Mainland of Shetl 33 ������ � Fair Isle 15 �� � � Whalsay 59 �� � � Bressay 6 �� ������������������������� East Burra 11 ���� � Muckle Roe 34 �� � � Grimsay (North) 21 �� ��� Yell 60 �� � West Burra (2) 57 ���� Burray 7 �� � Trondra 54 ���� St. Agnes 48 ���� St. Martin's 49 �� ��� Tresco (2) 53 ���� ��� Colonsay (2) 10 ������ ��������������������������� St. Mary's 50 ���� � � Iona 24 �������� � Anglesey (Welsh) 1 ������������ Isle of Wight 27 ���� � Isle of Walney 26 ���������������������������������

Figure 3: Cluster Analysis of Greek Islands Using Ward’s Method

Case-by-Case Analysis

0 5 10 15 20 25

+---------+---------+---------+---------+---------+

Serifos 50 �� Sifnos 51 �� Antiparos 9 �� Keas 25 �� Kythnos 31 ������ Agios Efstrat 3 �� � Folegandros 16 �� ��� Schinoussa 49 ���� � � Amorgos 6 �� ��� ��� Kimolos 28 ���� � � Sikinos 52 �� � ��������������������������������� Kythera 30 �������� � � Skyros 55 �� � � Anafi 7 ���������� � Irakleia 20 �� � Kalymnos 22 �� Symi 57 ���� � Patmos 42 �� ��� � Inousses 18 ���� ����������� � Nisyros 39 �� � � � Ios 19 ������ � � Tilos 61 ���� ��������������������������� Psara 45 ������ � Thirasia 60 �� ������� � Karpathos 23 ���� � � � Kasos 24 �� ��� ����� Astipalaia 10 ���� � Leipsoi 33 �� � Agathonisi 2 ������������ Kos 29 ������������ Rhodes 46 �� � Andros 8 ���� � Tinos 62 �� � � Milos 36 �� ��� � Paros 41 ���� � ��������������� Mykonos 37 �� � � � � Syros 58 ���� ������� � Leros 34 ������ � � Thira 59 �� � � � Chios 11 �� � � � Samos 48 �� � � � Naxos 38 ������ � � Lesvos 35 �� � � Donoussa 13 ������������ � Othoni 40 ���� ����������� Paxi 43 �� ��� � � Ithaki 21 �� � � � � Lefkada 32 ���� ����� � � Kefalonia 26 �� � � � � Zakynthos 63 �� � ������������� � � Kerkyras 27 ������ � � � � Erikoussa 14 ���������� � � � Agistri/Agkistrio 4 �� � � � Skopelos 54 ������ � � � Alonissos 5 �� � ����� � Aegina 1 �� � � � Spetses 56 �� � � � Hydra/Ydras 17 ���� ��������� � � Poros 44 �� ��� � � � Skiathos 53 ���� � ��������� � Salamina 47 ������ � � Evia 15 �������������� � Crete/Kriti 12 ������������������������������������

1