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Assessing the Impacts of Holiday Home Ownership upon Housing Markets in the Lake District National Park

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Second home ownership is a phenomenon that has evolved vastly since the 1960s in the UK, along with a multitude of associated impacts; economic, social, political, environmental, regional, national, local, the list goes on. In 2011, the UK government added second home counts to the census, perhaps a signal that they were beginning to appreciate the importance of and need for an assessment of this national trend. This study aims to investigate the spatial variation of holiday homes in the UK and how these patterns correlate with patterns of house price change, thus providing a baseline for further study of a particular region where second home ownership is perceived to be a prolific issue, in this case, the Lake District National Park. Census data, local council tax data amongst other sources such as Zoopla, have been used alongside a suite of analytical tools such as statistical analysis and geographical information systems (GIS) to determine the spatial variation of second homes and their impacts upon housing markets. The primary findings of this study at a national level are: a weak, positive correlation between house price increase and holiday home prevalence and a significant impact of National Park boundaries upon the prevalence of holiday homes and the degree of house price change. At a regional level, in the Lake District National Park, the main findings are: a weak, negative correlation between house price increase and second homes and a stronger, positive correlation between house price value and second homes. Suggestions for the patterns of second/holiday homes at each geographical level are discussed such as the amenity value of English nature and accessibility as well as reasons for the contrast between the correlative results of the two different geographical levels. Arguments and issues such as saturation, rent seeking, the difficulty of isolating separate impacts upon a housing market and adventitious urban demand are presented along with the limitations second home studies are faced with.
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ASSESSING THE IMPACTS OF
HOLIDAY HOME OWNERSHIP UPON
HOUSING MARKETS IN THE LAKE
DISTRICT NATIONAL PARK
Jenny Broomby
200781514
University of Leeds
BA Geography 2016
(Source: Lakedistricts.co.uk, n.d. & Keswick Plus, n.d.)
GEOG3600 - Dissertation
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Acknowledgements
I would like to take this opportunity to thank the following people for their support
throughout the past year. Firstly, to Gordon Mitchell my dissertation tutor who has
provided me with invaluable advice and support. To Rachel Homer for all her
patience and support helping me with not only my statistics, but the whole of my
dissertation. To Paula Allen, without whom I would have struggled greatly to do
anything at all, she has provided me with such helpful advice and of course, the bulk
of my data! To Clifford Walker at Copeland District Authority for his help filling in my
data gaps. To the wonderful Parish Councils of Copeland who responded so warmly
and enthusiastically to my cry for help. To Leeds University Union Hiking Club for
providing me, as always, with an outlet for all my pent up dissertation stress. To my
employers, Merrell, for being so understanding and supportive throughout this long,
tough process. To my rock, Freya Crocker whom I have tapped on the shoulder
countless times to ask her for advice, whether it be the margins of the page, MapInfo
or where to put a comma. To my mum for giving up her evenings, even on Mothers
Day, to read through all my work and correct my grammar countless times. To Lydia
Hitchcock for always being there to put a smile on my face and finally, to the rest of
my family and friends who have all been so wonderfully helpful and supportive.
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ABSTRACT
Second home ownership is a phenomenon that has evolved vastly since the 1960s in
the UK, along with a multitude of associated impacts; economic, social, political,
environmental, regional, national, local, the list goes on. In 2011, the UK government
added second home counts to the census, perhaps a signal that they were beginning
to appreciate the importance of and need for an assessment of this national trend.
This study aims to investigate the spatial variation of holiday homes in the UK and
how these patterns correlate with patterns of house price change, thus providing a
baseline for further study of a particular region where second home ownership is
perceived to be a prolific issue, in this case, the Lake District National Park. Census
data, local council tax data amongst other sources such as Zoopla, have been used
alongside a suite of analytical tools such as statistical analysis and geographical
information systems (GIS) to determine the spatial variation of second homes and
their impacts upon housing markets. The primary findings of this study at a national
level are: a weak, positive correlation between house price increase and holiday
home prevalence and a significant impact of National Park boundaries upon the
prevalence of holiday homes and the degree of house price change. At a regional
level, in the Lake District National Park, the main findings are: a weak, negative
correlation between house price increase and second homes and a stronger, positive
correlation between house price value and second homes. Suggestions for the
patterns of second/holiday homes at each geographical level are discussed such as
the amenity value of English nature and accessibility as well as reasons for the
contrast between the correlative results of the two different geographical levels.
Arguments and issues such as saturation, rent seeking, the difficulty of isolating
separate impacts upon a housing market and adventitious urban demand are
presented along with the limitations second home studies are faced with.
Key words: Second homes, holiday homes, National Parks, rural housing markets,
saturation, Lake District, Cumbria, rent-seeking.
Word count: 9,990
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TABLE OF CONTENTS
Abbreviations .......................................................................................................... 7
List of Figures & Tables .......................................................................................... 8
Figures ............................................................................................................... 8
Tables ................................................................................................................ 8
Chapter 1: Introduction ........................................................................................... 9
1.1 Why Second Homes? .................................................................................. 9
1.2 Structure of the Study ................................................................................ 10
1.3 Aims & Objectives ..................................................................................... 10
1.4 Study Area: ............................................................................................... 11
Chapter 2: Literature Review ................................................................................ 14
2.1 A Brief History of Second Homes in the UK ............................................... 14
2.2 Second Homes & Housing Markets ........................................................... 14
2.3 Second Homes In The Lake District National Park .................................... 16
Chapter 3: Methodology ....................................................................................... 19
3.1 Research Approach ....................................................................................... 19
3.2 Data ............................................................................................................... 19
3.2.1 National Level.......................................................................................... 19
3.2.2 Regional Level......................................................................................... 20
3.3 Analysis ......................................................................................................... 21
3.4 Limitations...................................................................................................... 22
3.4.1 Second Homes Data ............................................................................... 22
3.4.2 Data Recording ....................................................................................... 23
3.4.3 House Price Data .................................................................................... 23
Chapter 4: Results Analysis & Discussion .......................................................... 25
4.1 National Level ................................................................................................ 25
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4.1.1 National Second Home Patterns.............................................................. 25
4.1.2 Holiday Homes in England & Wales ........................................................ 27
4.1.3 House Price Change in England & Wales ................................................ 29
4.1.4 The Impact of National Parks .................................................................. 30
4.1.4 Holiday Homes’ Impact Upon House Price Change ................................. 34
4.2 Regional Level: The Lake District ................................................................... 37
4.2.1 Second Home Patterns ........................................................................... 37
4.2.2 House Price Patterns............................................................................... 40
4.2.3 Second Homes & The Lake District Housing Market ............................... 42
Chapter 5: Conclusion .......................................................................................... 48
5.1 Overall Conclusions ....................................................................................... 48
5.2 Study Limitations............................................................................................ 49
5.3 Future Research & Data Collection ................................................................ 50
Bibliography .......................................................................................................... 52
Appendices ............................................................................................................ 60
Appendix A: Dissertation Support Group Forms................................................... 60
Appendix B: DSG Reflective Log ......................................................................... 69
Appendix C: First Interim Report .......................................................................... 70
Appendix D: Second Interim Report ..................................................................... 76
Appendix E: Risk Assessment Form .................................................................... 96
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ABBREVIATIONS
ANOVA Analysis of Variance
FOI Freedom of Information
LAD Local Authority District
LDNP Lake District National Park
LDNPA Lake District National Park Authority
ONS Office for National Statistics
PPMCC Pearson Product Moment Correlation Coefficient
SHO Second Home Ownership
SNP Snowdonia National Park
YDNP Yorkshire Dales National Park
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LIST OF FIGURES & TABLES
FIGURES
FIGURE 1.1 UK NATIONAL PARKS. (SOURCE: NATIONAL PARKS UK (N.D.)(A)) ............................. 11
FIGURE 1.2 LDNP BY PARISH (SOURCE: LDNPA, 2014) ........................................................... 13
FIGURE 4.1.1 SECOND HOMES (2011) (SOURCE: 2011 CENSUS) ............................................... 26
FIGURE 4.1.2 HOLIDAY HOMES IN ENGLAND & WALES (SOURCE: 2011 CENSUS) ......................... 27
FIGURE 4.1.3 HOUSE PRICE CHANGE (%) IN ENGLAND AND WALES (2001-11) (SOURCE: 2011
CENSUS) ...................................................................................................................... 29
FIGURE 4.1.4 MEAN PERCENTAGES OF HOLIDAY HOMES IN LADS WITHIN NATIONAL PARKS (SOURCE:
2011 CENSUS). ............................................................................................................. 31
FIGURE 4.1.5 HOLIDAY HOME % VS NATIONAL PARKS (SOURCE: 2011 CENSUS) ......................... 32
FIGURE 4.1.6 IMPLICIT PRICES FOR KEY ENVIRONMENTAL AMENITIES IN ENGLAND CAPITALISED
VALUES) (SOURCE: GIBSON ET AL., 2014, PP.193) ............................................................ 34
FIGURE 4.1.7 HOUSE PRICE INCREASE VS HOLIDAY HOME PREVALENCE (SOURCE: 2011 CENSUS) . 35
FIGURE 4.1.8 MINITAB STATISTICAL ANALYSIS RESULTS ........................................................... 35
FIGURE 4.2.1 SECOND HOMES BY PARISH (SOURCE: ALLEN, 2015 AND WALKER, 2015) ............... 37
FIGURE 4.2.2 TOPOGRAPHICAL RELIEF MAP OF THE LDNP (SOURCE: LDNPA, 2010) .................. 39
FIGURE 4.2.3 PERCENTAGE HOUSE PRICE INCREASE (2006-16) (SOURCE: ZOOPLA) .................... 40
FIGURE 4.2.4 SCATTERPLOT OF HOUSE PRICE INCREASE VS SECOND HOME PREVALENCE (SOURCE:
LDNPA, COPELAND BOROUGH COUNCIL AND ZOOPLA) ..................................................... 41
FIGURE 4.2.5 MINITAB STATISTICAL ANALYSIS RESULTS ........................................................... 41
FIGURE 4.2.6 AVERAGE HOUSE PRICE VALUE (2016) (SOURCE: ZOOPLA) .................................... 42
FIGURE 4.2.7 MINITAB STATISTICAL ANALY SIS RESULTS ............................................................. 42
TABLES
TABLE 3.1 NATIONAL DATA SOURCES ..................................................................................... 20
TABLE 3.2 REGIONAL DATA SOURCES ..................................................................................... 20
TABLE 4.1.1 TOP 5 LADS IN UK FOR HOLIDAY HOME OWNERSHIP (SOURCE: 2011 CENSUS) ......... 28
TABLE 4.1.2 KRUSKAL-WALLIS TEST, HOLIDAY HOME % VERSUS NATIONAL PARKS ............. ERROR!
BOOKMARK NOT DEFINED.
TABLE 4.1.3 KRUSKAL-WALLIS TEST - HOUSE PRICE CHANGE VERSUS NATIONAL PARKS ............. 33
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CHAPTER 1: INTRODUCTION
1.1 WHY SECOND HOMES?
According to the 2011 census, almost 1.6 billion people owned a second home in
England and Wales. This impressive figure surely confirms the importance and need
for careful study and further understanding of this ever-increasing phenomenon
(Oxley et al., 2008, pp.29) and its impacts. Second home ownership (SHO) raises
numerous ‘complex and wide-ranging issues’ (Downing and Dower, 1974, pp.i),
positive and negative, and since 1968, the second home has become increasingly
accepted ‘as a topic for serious study’ (Rogers, 1977, pp.85). In Britain, rises in ‘the
number of properties used as second homes in recent years has been blamed [...] for
a housing shortage in rural areas’ (Hoggart, 2003, pp.160 cited in Gallent, 2007,
pp.98) and ‘driving up house prices in areas where wage levels are typically low’
(pp.98). In 2008, the Place Survey revealed that affordable housing was the ‘top
issue in need of improvement’ in the Lake District National Park (LDNPA, 2013,
pp.32) whilst the 2011 census revealed that 24% of all dwellings in the Park were
either second homes or holiday lets, with some communities experiencing levels as
high as 51% (LDNPA, 2013). Such significant figures have created tensions in
second home hotspots as ‘demand for second homes has increasingly been directed
towards properties that otherwise could be used by permanent residents’ (Wallace et
al., 2005, pp.42), forcing often less well-off locals to compete with wealthy second
home purchasers for homes (Shucksmith, 1981; Gallent et al., 2002). This study is
both relevant and timely as the British government in 2016 plans to increase the tax
on second homes ‘to ease demand for those squeezed out by house price rises’
(Pitas, 2015). The recent addition of second home counts to the UK census in 2011
(Walker, 2012) further supports the notion that the second home phenomenon is
increasingly respected as a societal issue facing countless regions, towns, villages
and communities across the country. The ‘topic addresses key national and local
policy concerns, notably sustainable communities and housing demand’ (Wallace et
al., 2005, pp.2). It is therefore important that this newly available information is used
effectively and purposefully to be able to fully understand the wide-ranging impacts
second homes have.
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1.2 STRUCTURE OF THE STUDY
Chapter 2 will offer an overview of the existing literature on second homes. Firstly, a
brief history of the second home phenomenon, looking at its origins and trends since
the 1960s, followed by a summary of previous studies which have explored the
impact second homes have had, particularly upon local, rural communities and
housing markets in addition to the national spread and patterns of second homes.
The literature review will also look more closely at specific regional and local case
studies such as National Parks, namely the Lake District National Park (LDNP).
Finally, the chapter will conclude with justifications for this study, introducing the gap
that this research will fill within the existing literature. Chapter 3 will outline the data
used throughout this research, the methods used to analyse and depict the results
and the justification for such an approach, finally followed by limitations of the data
used. Chapter 4 details the findings of this study and discusses the results and
finally, chapter 6 will close with the overall conclusions of this study, its limitations
and suggestions for future research.
1.3 AIMS & OBJECTIVES
AIMS
1. To investigate the spatial variation of second homes at a national level (England
and Wales) and within the LDNP
2. To understand and assess the impact of second homes upon the housing market
at a national level and within the LDNP
OBJECTIVES
Aim 1
Analyse patterns of second home ownership nationally
Analyse patterns of holiday home ownership nationally
Determine and investigate the impact of National Park boundaries upon holiday
home prevalence and patterns
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Analyse and investigate patterns of second (holiday) home ownership in the
LDNP
Aim 2
Determine and investigate the relationship between holiday home ownership and
changing house prices at a national level
Determine and investigate the relationship between second (holiday) home
ownership and changing house prices in the LDNP
Determine and investigate the relationship between holiday home ownership and
average house price value in the LDNP
1.4 STUDY AREA:
This study will initially cover England and Wales, followed by the LDNP, located in
figure 1.1.
Figure 1.1 UK National Parks. (Source: National Parks UK (n.d.)(a))
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The LDNP is composed of 4 local authority districts (LADSs), within which are 69
parishes. It is the largest National Park in England covering 2292 square kilometres
(Lake District National Park Authority, n.d.). According to the 2011 census, 40,800
people live within the boundaries of the LDNP, with a population density per square
kilometre of 18.4 (Lake District National Park Authority, n.d.), compared to England’s
overall population density of 413 per square kilometre (Ons.gov.uk, n.d.). Figure 1.2
shows the boundaries of the 4 LADs. North is Allerdale, West is Copeland, East is
Eden and South and Central and South East are South Lakeland. Figure 1.2 gives a
rough idea of the parish boundaries and their names that will be referred to
throughout the study (please note that some parishes and boundaries differ slightly to
those used in this study, figure 1.2 is included for reference to the specific names and
their locations during the analysis and discussion).
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Figure 1.2 LDNP by parish (Source: LDNPA, 2014)
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CHAPTER 2: LITERATURE
REVIEW
2.1 A BRIEF HISTORY OF SECOND HOMES IN THE UK
The ‘second home boom’ is widely regarded to have begun in the mid-1960s (Bevan
and Rhodes, 2005; Bennett, 1979; Satsangi et al., 2010; Davies and O’Farrell, 1981;
Tewdwr-Jones et al., 2002) when second home buyers began purchasing property,
surplus to the local housing market, a demand that was initially deemed as positive.
Decline in local industries such as mining, quarrying and agriculture had created a
surplus of dwellings in attractive, rural locations such as Wales and the Lake District,
the desire of many second home buyers (Bevan and Rhodes, 2005). However, by
the late 1970s, studies suggest this balance between supply and demand was
reaching a watershed, as demand for empty, unused properties in local, often rural,
housing markets from second home buyers reached saturation point (Bevan and
Rhodes, 2005; Bielckus, 1977). Since then, this phenomenon has continued to
expand. In 2005, Direct Line predicted a 24% rise in second homes by 2015,
increasing by 77,000 from 328,000 to 405,000 (Oxley et al., 2008, pp.29). Today,
however, in comparison to the 1970s and 80s, purchases of second homes involve
‘properties that rival or even surpass that of the main residence’ (Gilbert, 2001,
pp.18).
2.2 SECOND HOMES & HOUSING MARKETS
Today, more often than not, second homes are referred to as a curse as opposed to
a blessing (Coppock, 1977). They ‘disrupt’ local communities, particularly in their
‘distorting effect on house prices’ (Bollom, 1978, Shucksmith 1981 cited in Gallent,
2014, pp.174), most notably in regions and communities where an agricultural and
service based economy ‘delivers low wages for the permanently resident population’
(pp.174). Second homes are perceived as the ‘wreckers of rural communities in
Britain’ (Satsangi et al., 2010, pp.79), held responsible for housing pressures in the
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countryside. Indeed, journalist George Monbiot referred to second home owners as
‘amongst the most selfish people’ in Britain (Monbiot, 2006). In general, however, the
media is split in its coverage of the issue (Satsangi et al., 2010). Local publications
write of the impacts second homes have upon communities (Pyne, 2016) whilst large
national publications speak of issues such as an increase in the tax upon second
homes and the potentially detrimental effect upon the national market and people’s
‘buy-to-let dreams’ (Dunn, 2015). There is a marked contrast between the response
and feelings to second homes at a local and regional level compared with those at
the national level, where it is supposedly ‘not perceived to be an issue’ because
second homes only constitute ‘around 1% of housing stock’ (Oxley et al., 2008 cited
in Barnett, 2014 pp.10). In the Dartington Amenity Research Trust’s study into
second homes, it was concluded that once second homes grow beyond a few
properties that are no longer wanted as first homes, the problems, political,
economic, environmental and social, begin to surface (Downing and Dower, 1972).
The study flagged the impact of second homes upon house prices, reporting that
‘prices of houses in areas favoured for second homes [had] risen more rapidly even
than house prices generally’ (Downing and Downer, 1972, pp. 31). This was leaving
young people who are at a financial disadvantage compared to second home
owners, to be forced to move away from the area (1972). 10 years ago, the Centre
for Housing Policy undertook a systematic literature review of the impact of empty,
second and holiday homes on the sustainability of rural communities, and more
recently, in 2008, the Centre for Comparative Housing Research conducted a similar
literature review, assessing the research literature on the purchase, use and impacts
of second homes. Throughout both reviews there appeared to be a common
scepticism of the evidence available to prove some of the publications’ assertions
that SHO increases house prices. For example, in their 2005 report, Direct Line
stated, “Second homes and holiday homes contribute to rural social exclusion as
local residents are increasingly priced out of the limited housing resource” (Direct
Line, 2005, pp11), but the Centre for Comparative Housing Research concluded that
the evidence to suggest this statement was “wholly inadequate” (Oxley et al., 2008,
pp.25).
Those reports that appeared to prove the impact of second homes on house
prices, however, were extremely localised and thus unable to offer any suggestion of
the impact at a wider, county or even national level. There does not appear to be any
publicly available, recent (past 10-20 years) research that has looked at the
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relationship between holiday/second homes and the rate at which house prices
increase, as opposed to the effect upon raw house prices. Gallent et al. (2002) found
that the issue of second and holiday homes may not be a huge problem at local
authority level, however, the issue does cause for particular concern in some
individual villages and small local communities. However, this research was,
conducted over 10 years ago and the aforementioned increase in second homes
may now be presenting problems at wider geographical levels, such as the regional
level, e.g. the LDNP. With such a significant increase predicted, it is surely necessary
to be prepared for the potential impact it may have on local communities and housing
markets as was suggested in the 1972 study for the Countryside Commission
(Downing and Dower, 1972).
2.3 SECOND HOMES IN THE LAKE DISTRICT NATIONAL
PARK
As a rule, ‘second home ownership in Britain has often grown in high amenity areas’
(Paris, 2011, pp.164). The Lake District, renowned for its dramatic scenery of
mountains, lakes and extensive greenery has been a National Park since 1951 and
since then it receives approximately 16.4 million visitors yearly (Lakedistrict.gov.uk,
2015). This increase in tourism has been accompanied by an increase in second
homes in the National Park, with around 15% of the total 22,930 dwellings now
second homes (Lakedistrict.gov.uk, 2015). A number of studies have investigated the
impact of second homes within the LDNP (Wallace et al., 2005), many of which were
conducted in the late 1970s and the 1980s; even Women’s Institutes and Young
Farmers Clubs began doing ‘small surveys of the number of second homes and
suggested that they should be discouraged’ (Clark, 1982, pp.62). In 1979, at the time
when second homes had begun to manifest themselves as being a potential issue,
Bennett conducted a study into rural housing in the Lake District. She interviewed
key informants to gauge the impact of SHO on the local economy as well as using
census data to analyse the changing demographics of rural communities (Bennett,
1979). Bennett concluded that the demand for holiday homes had curbed the
numbers and demographics of people able to live in the countryside ultimately
resulting in disruptive effects as locals became dissatisfied and frustrated. Mark
Shucksmith’s study ‘No Homes for Locals?’ later, in 1981, found that ‘external
17
demand for property in the Lake District was hugely significant’ (Wallace et al.,2005,
pp.39) and local estate agents estimated that more than half of the properties
purchased were by people outside the National Park (2005). Shucksmith, along with
others such as Bennett, identified the purchase of holiday homes as a source of
external demand; however, he also revealed examples of locals buying properties to
let as holiday homes (Shucksmith, 1981; Bennett, 1979; Gallent et al., 2002). In
1987, Margaret Capstick’s study, ‘Housing Dilemma’s in the Lake District’ also looked
at second homes, studying the impacts of the early stages of the Right-to-Buy policy
in the Park. This scheme is held accountable in many studies for the ease at which
second home purchasers could acquire local dwellings to use as second homes
(Wallace et al., 2005). Alike to Bennett, Capstick looked at the impact second homes
were having upon affordability in the Lake District and the subsequent rural
depopulation (Capstick, 1987). She found that whilst second homes were affecting
rural housing markets, there were many other forces causing a lack of affordable
housing in the region as well as a lack of social amenities being another primary
push factor for rural depopulation (Capstick, 1987). Despite this, her study found that
younger people who moved away did wish to return to their parish of origin later in
life but the high house prices prohibited this (Bennett, 1979; Capstick, 1987).
Capstick compared figures from her own study with those of Bennett’s 1979 study,
which had used figures from 1975. It revealed that ‘53% of parishes had experienced
over a 50% increase in second homes by 1981’ (Wallace et al., 2005, pp.44).
There is extensive literature focused on the impact of second homes upon
local, rural communities elsewhere in Britain and throughout the world (Farstad,
2013; Farstad and Rye, 2013; Pacione, 1979; Barnett, 2014, The Centre for Housing
Policy, 2005). However, no study has yet conducted an initial baseline national level
analysis before looking at a National Park such as the Lake District. The Lake District
National Park Authority (LDNPA) along with the local district councils within the Park
recently assessed these impacts, covering a large scope of outcomes. It very briefly
reviewed the impacts, both positive and negative, of second homes upon areas such
as sustainability, house prices, culture, society and the environment (Lake District
National Park, n.d.). Hence, there is a gap in the literature for a more concentrated
analysis of the Lake District, looking at the effect of second homes upon the housing
market within the boundaries of the Park at the lower parish level.
18
With the predicted increase in second homes (Oxley et al., 2008); the recent
addition of second homes to the census and the new second home tax coming into
place, this dissertation is certainly timely. Furthermore, it is hoped that it will also fill a
gap in the extensive research into the impacts of second homes upon housing
markets at a more localised level within the Lake District as well as at a national level
using the newly available census data.
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CHAPTER 3: METHODOLOGY
3.1 RESEARCH APPROACH
This study has taken a quantitative approach to allow for the analysis of large
datasets, combined with mapping, to provide a visualisation of the relationships and
data patterns. Secondary data were used to analyse the spatial variation of second
homes and house price change and their relationship at a national and regional level.
3.2 DATA
3.2.1 NATIONAL LEVEL
The 2011 second home census data sets used for the national level analysis were
sourced from the ONS website, extracting data for all LADs in England and Wales.
For the purpose of this study, the counts for ‘holiday’ second homes were used for
the statistical analysis, as this count is the most pertinent to the LDNP. The house
price data were extracted from the ONS website at a LAD level for the year 2001 and
2011 and a calculation was conducted in Microsoft Excel to determine the
percentage difference between the two dates, providing an average figure for house
price change in each LAD in England and Wales. The boundary data used in the
maps were downloaded from the UK Data Service website, using the Boundary Data
Selector (Census.edina.ac.uk, 2011). Table 3.1 below outlines the census datasets
that were used along with where they were obtained.
Variable by 2011 LAD
Source
All usual residents elsewhere with a
second address in this area; all second
address types
Census, ONS
All usual residents elsewhere with a
second address in this area; holiday
Census, ONS
Median sale price by dwelling type and
local authority (£), 2001
Census, ONS
20
Median sale price by dwelling type and
local authority (£), 2011
Census, ONS
KS401EW Dwellings; All dwelling types,
2011
Nomis
Table 3.1 National Data Sources
3.2.2 REGIONAL LEVEL
The second homes data for the LDNP were sourced from the LDNPA through a
freedom of information request (FOI). These data have been collated in collaboration
with local authorities within the LDNP using council tax estimates from 2013. The
authority of Copeland was missing from this dataset so to fill this gap council tax
estimates from the year 2016 were used. As with the national level boundaries, the
parish boundaries used in the GIS were downloaded using the UK Data Service
(Census.edina.ac.uk, 2011). Table 3.2 below outlines the specific datasets used in
this study for the regional level analysis and their origin.
Variable by 2011 Parishes
Source
South Lakeland Second Home Counts
(2013 Council Tax Estimates)
LDNPA (Allen, 2015)
Eden Second Home Counts (2013
Council Tax Estimates)
LDNPA (Allen, 2015)
Allerdale Second Home Counts (2013
Council Tax Estimates)
LDNPA (Allen, 2015)
Copeland Second Home Counts (2016
Council Tax Estimates)
Copeland Borough Council (Walker,
2016)
Table 3.2 Regional Data Sources
House price changes and average values were collated using Zoopla. The name of
each parish was entered into the website’s house price and value search function
and the following two figures were recorded on 13 January 2016 for each parish in
the LDNP.
a) Current average value
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b) Percentage value change (past 10 years)
For parishes where a search returned no results, the postcodes and settlements that
fell within those parishes were searched using Google, combined and averaged to
give a result for each of the above variables.
3.3 ANALYSIS
The initial national level analysis was done at the outset to determine whether there
was any relationship between the two variables (holiday home ownership and house
price change) at a wider geographical level and would thus offer a baseline for a
more detailed research into one particular area of the UK, in this case, the LDNP.
Limitations of the data meant that a temporal analysis of the changing patterns and
impacts of holiday home ownership was not possible at either level and thus ruled
out a multivariate analysis, comparing the regional and national level.
MapInfo and Minitab were used to conduct the analyses. Utilising MapInfo
allowed for clear, thematic maps and for the comparison of the data (Burrough,
2001), whilst also offering a visual representation of the findings, particularly the
impact of National Park boundaries at the national level. Minitab was used to perform
more meticulous and thorough statistical analyses of the dataset variables, presented
through equations and graphs, providing a more accurate visualisation of the
bivariate relationships. The combination of GIS and statistics ‘provides a powerful
and complementary suite of tools for spatial analysis’ (Burrough, 2001, pp.361).
The results of the statistical analyses were obtained from descriptive statistics,
correlation and significance. The particular methods used are detailed and justified
below:
a) Regression analysis was used to determine the relationship between SHO
and changing house prices at a national level, revealing the type of
relationship (positive or negative) and the strength of this relationship. At a
regional level, the analysis was conducted to determine the same relationship
as well as the relationship between SHO and raw house prices.
b) The Pearson Product Moment Correlation Coefficient was conducted to
further determine the strength of the linear association between the
22
aforementioned variables and indicate how well the data points fit to the line
of best fit (Laerd Statistics, n.d.). For this test, a p value of less than 0.05
means that the result can be considered statistically significant at the 95%
significance level.
c) A Kruskal-Wallis test was conducted to compare the means of holiday home
ownership in LADs in National Parks to those outside National Parks and
determine whether there are any significant differences between them, thus
signalling any impact of National Park borders upon holiday home prevalence.
d) An Analysis of Variance (ANOVA) test was used to determine the different
holiday home percentage means of each National Park, to allow for a
comparison between them as well as between LADs not within National Park
boundaries.
3.4 LIMITATIONS
3.4.1 SECOND HOMES DATA
NATIONAL LEVEL
Prior to 2011, the census did not record SHO on a per capita basis and any count of
second homes was done through county council tax records or surveys. In 2011, the
census began officially recording the number of second homes at a LAD level,
differentiating between working, holiday and other second homes. Ideally, this study
would have done a temporal analysis into the impact of holiday homes to provide
more insight into the effect of increasing second homes, using temporal figures.
Unfortunately, this was not possible due to the limitations of the data as the previous
counts of second homes would not be comparable due to different data collection
methods.
REGIONAL LEVEL: LAKE DISTRICT
The use of census data for this level was unsuitable, as the lowest geographic level it
is recorded at is the LAD level, which would render the study too broad for a
significant and detailed analysis, as there are only four LADS within the LDNP. The
data provided by the LDNPA provided figures for local parishes within each authority
from 2011-13 with the exception of Copeland. This gap was filled using data provided
by Copeland authority’s 2016 tax estimates. To combat this discrepancy in the
23
consistency of the data, FOI requests were sent to each LAD in the LDNP, however,
those requests were either not met in time or were not able to be met meaning the
data is temporally inconsistent, with all LADs apart from Copeland using tax
estimates from 2013.
The data should be treated with some caution. According to the Taylor
Review (2008), council tax counts for second homes rely on second home owners
seeking a discount on council tax for their second home. However, ‘not all second
home owners will register their property as such, particularly as local authorities now
have the discretion to reduce the discount for Council Tax from 50 to 10 per cent’
(pp.115). Following this change, in places such as Cornwall, the number of registered
homes stopped rising and instead the number of registered holiday lets ‘(which
business rates than would be paid as council tax for a second home)’ (pp.115) began
to rise, however in many cases second homes and holiday lets are the same thing.
The LDNPA report into second homes also regarded this to be an issue in their
figures that also used council tax estimates (Lake District National Park, n.d.).
3.4.2 DATA RECORDING
At both a national and regional level, the data collected significantly impedes any real
assessment of the impact of the holiday home industry as a whole upon local
communities and house prices. This is because some holiday homes are registered
as businesses (as mentioned above) (Lake District National Park, n.d.) and thus are
not counted in the census or in council tax estimates as second homes, despite them
fulfilling much the same role as second homes owned by an individual that is not
classed as a business. An example of this is a company such as Lake Lovers
(Lakelovers.co.uk, 2016) which owns numerous houses and cottages that are now
considered businesses despite once previously being a dwelling before conversion
into a holiday business. The same can be said for guesthouses and B&Bs.
3.4.3 HOUSE PRICE DATA
Zoopla was used to determine the change in house prices over the last 10 years.
Data is not available for house prices on the census at this geographical level and
Zoopla was the next best option. Typing in the name of the parish provided results,
24
however, there is no way of knowing for certain that those results included every
single postcode/area within the boundaries of the parish used in MapInfo, despite
efforts to ensure the whole parish was taken into account using postcode searches
and aggregating then averaging the data.
25
CHAPTER 4: RESULTS
ANALYSIS & DISCUSSION
4.1 NATIONAL LEVEL
4.1.1 NATIONAL SECOND HOME PATTERNS
This section will give an overview of the national patterns of SHO, holiday home
ownership and house price changes, using the statistical tools described above to
analyse the relationship between the latter two variables. Further statistical analysis
will be undertaken to determine the impact of National Parks upon these variables.
This initial study will place the LDNP in a wider context, ultimately providing a
baseline for further detailed analysis.
Figure 4.1.1 shows the spread of second homes throughout England and
Wales, including all definitions and classifications, namely working, holiday and other.
Working homes refer to second homes used for work purposes, for example,
members of parliament’s homes in their local constituency and a second ‘working’
home in Westminster. Holiday homes refer to those homes used as holiday retreats
for families, e.g. a family who lives in London may own a holiday home in Cornwall
that they retreat to at the weekend and during the summer holidays. Other homes
refer to any second home that does not come under the umbrella of working or
holiday. This may include a student’s term time address at university or a child with
parents living at two separate addresses.
The map shows that nationally there are a number of clusters, big and small
that have high percentages of second homes. It appears that in general, rural areas
attract higher levels of SHO and in many cases, those rural areas are within or near
the borders of a National Park. Metropolitan regions such as Manchester, Leeds and
Newcastle show low levels of SHO with the exception of central London. Snowdonia
National Park (SNP) in North Wales has particularly high levels of SHO and indeed
all the authorities that fall within SNP have some of the highest proportions of second
homes nationally. Gwynedd, the main authority within SNP ranks sixth out of 348
authorities in England and Wales.
26
Figure 4.1.1 Second homes (2011) (Source: 2011 Census)
Of the top fifty authorities with high second home prevalence, thireteen (26%) are
within National Park boundaries and of the top twenty-five, nine are within National
Park boundaries (36%). King’s Lynn & West Norfolk and City of London have the
highest levels of SHO, but whilst neither are within the boundaries of a National Park,
King’s Lynn & West Norfolk borders Norfolk, which is within the Norfolk Broads
National Park and ranks third of all authorities with high SHO. The City of London
authority could be speculated to have a high proportion of ‘working’ second homes,
hence, its high percentage.
27
This study will be analysing the impact of holiday homes upon house price changes
because holiday homes are the type of second home most commonly found in the
LDNP (South Lakeland District Council, n.d.) (See fig.4.1.2) and indeed, the debate
surrounding the impact of the tourism and holiday industry upon the area is
particularly topical and relevant today.
4.1.2 HOLIDAY HOMES IN ENGLAND & WALES
Figure 4.1.2 Holiday Homes in England & Wales (Source: 2011 Census)
28
Again, there is a clear relationship between high levels of holiday home prevalence
and the boundaries of a National Park, as well as coastlines. There is a clear band of
low second home levels spreading north from London, up through the central region
of England. Anomalies of this pattern include LADs within the Peak District National
Park most notably and Rutland. In general, areas bordering this central band have
much higher levels of SHO with a few exceptions such as the areas surrounding
Cardiff, Bristol and Newcastle. Of the top ten authorities in England and Wales with
high levels of second homes, (60%) fall within the boundaries of a National Park. Of
the top fifty, twenty-three are within National Park boundaries (46%). 42% of all the
LADs that fall within a National Park are ranked within the top fifty authorities with
high second home percentages. Table 4.1.1 below reveals that of the top five local
authorities with high second home prevalence, only one (King’s Lynn & West Norfolk)
does not fall within borders of a National Park, however, it does border the top LAD
which is within the Norfolk Broads. Of the four authorities that are within the LDNP,
three are in the top fifty authorities with high second home proportions.
Area
Authority Name
Percentage
of ‘holiday’
second
homes (%)
Norfolk Broads
Norfolk
North Norfolk
14.84
N/A
Norfolk
King’s Lynn & West Norfolk
13.52
Snowdonia
Wales
Gwynedd
12.76
Lake District &
Yorkshire Dales
Cumbria
South Lakeland
8.77
Dartmoor
Devon
South Hams
8.65
Table 4.1.1 Top 5 LADs in UK for holiday home ownership (Source: 2011 Census)
29
4.1.3 HOUSE PRICE CHANGE IN ENGLAND & WALES
Figure 4.1.3 House price change (%) in England and Wales (2001-11) (Source: 2011
Census)
The overwhelming pattern in figure 4.1.3 shows the lower levels of house price
increase in central, southern England where there appears to be a buffer of low
house price increase surrounding London. Wales and the north of England appear to
have experienced the highest levels of house price increase, particularly the coastal
30
regions of Wales and the most rural areas of northern England, e.g. Cumbria and
North Yorkshire. Whilst coastal and rural areas in the south of England have
experienced higher levels of house price increase than that of the authorities
surrounding London, their increase looks to be much less in comparison to the north.
In contrast to other relatively rural and coastal regions, southeast England has much
lower levels of house price increase, despite the presence of the Norfolk Broads
National Park. The same can be said of the central-southern coastal regions of
England, which have also experienced lower levels of house price increase despite
the presence of two National Parks. Cornwall looks to have the highest levels of
overall house price increase of all the southern authorities.
4.1.4 THE IMPACT OF NATIONAL PARKS
Raw data and maps appear to show a link between the level of the two variables and
the location of the authority. LADs within a National Park look to experience a high
level of both house price increase and holiday home prevalence, for example,
Gwynedd in SNP, Wales. The graph below (fig.4.1.4) depicts the results of the
ANOVA test, showing the mean percentage of holiday homes in each National Park
in England and Wales, based upon the LAD data. The LDNP has the third highest
mean, Snowdonia the highest and the Peak District the lowest. These results reflect
the deductions that had been made following the analysis of figure 4.1.2, namely that
National Parks do have a significant impact upon holiday home proportions in an
area.
31
Figure 4.1.4 Mean percentages of holiday homes in LADs within National Parks
(Source: 2011 Census).
Kruskal-Wallis Test on Percentage of Holiday Homes
National Park
Boundaries
No.
Median
Ave Rank
Z
In National Park
55
0.9193
255.1
6.48
Not in National
Park
293
0.1409
159.4
-6.48
Overall
348
174.5
H = 41.96 DF = 1 P = 0.000
Table 4.1.2 Kruskal-Wallis Test, Holiday Home % versus National Parks
The Kruskal-Wallis test (table 4.1.2) reveals a large H value of 41.96, which further
proves a statistically significant difference between the percentages of holiday homes
32
in LADs within the borders of a National Park compared to those outside. The
median percentage of holiday homes found in a LAD within a National Park is 0.9193
as opposed to 0.1409 for those outside. The P value of 0.00 confirms that the results
are reliable and significant. The findings are depicted in the box-plot shown below in
figure 4.1.5.
Figure 4.1.5 Holiday Home % vs National Parks (Source: 2011 Census)
Table 4.1.4 depicts the Kruskal-Wallis test on house price change in National Parks.
It reveals that the median house price increase in LADs within National Parks was
approximately 8% higher in the years between 2006 and 2016 than the median
house price increase in the same period in LADs outside a National Park.
These findings are consistent with existing literature such as the 2014 study
into the amenity value of English nature, which revealed that many environmental
variables have a large, significant effect upon house prices (Gibbons et al., 2014), all
of which tend to be found in large volume in a National Park (National Parks UK,
n.d.). Tewdwr-Jones et al. (2002) also found that upland and coastal locations
abundant in natural beauty have consistently predominated for second homes for
years. Gibbons et al. (2014) said,
33
“Gardens, green space and areas of water within the census ward all attract a
considerable positive price premium. There is also a strong positive effect
from freshwater and flood-plain locations, broadleaved woodland, coniferous
woodland and enclosed farmland. Increasing distance to natural amenities
such as rivers, National Parks and National Trust sites is unambiguously
associated with a fall in house prices” (Gibbons et al., 2014, pp.175).
Whilst this study was only conducted in England, it would not seem to be
unreasonable to suggest that these conclusions could plausibly be extended to
Wales, which is home to five Areas of Outstanding Natural Beauty (AONB)
(Visitwales.com, n.d.) and two National Parks (National Parks UK, n.d.). Figure 4.1.5
shows a table included in the Gibbons et al. (2014) study that observed a 17.36%
house price increase when situated in a National Park in England, concurring with
this study’s finding regarding the inflationary impact of National Parks upon house
price change, mentioned above.
Kruskal-Wallis Test on House Price Change
National Park
No.
Median
Ave Rank
Z
In National
Park
55
98.98
202.7
2.26
Not in National
Park
293
90.61
169.2
-2.26
H = 5.12 DF = 1:00 P = 0.024
Table 4.1.4 Kruskal-Wallis Test - House Price Change versus National Parks
34
Figure 4.1.6 Implicit prices for key environmental amenities in England (£ capitalised
values) (Source: Gibson et al., 2014, pp.193)
4.1.4 HOLIDAY HOMES IMPACT UPON HOUSE PRICE CHANGE
When comparing figure 4.1.2 and figure 4.1.6, there are certainly some instances of
similarity, with a number of authorities experiencing high levels of both house price
increase and holiday home prevalence. For example, as previously mentioned, the
coastal and northern areas of Wales have had high levels of both variables,
particularly SNP. Authorities within the YDNP and the LDNP have also experienced
high levels of the two variables focused upon in this study. A regression analysis to
determine the strength and nature of the relationship between these variables was
35
conducted as well as the PPMCC as a test of significance and further analysis of the
correlation.
Figure 4.1.7 House price increase vs holiday home prevalence (Source: 2011
Census)
Figure 4.1.8 MiniTab Statistical Analysis Results
The MiniTab results and graph (fig.4.1.7) confirm a positive correlation between the
two variables. A PPMCC value of 0.196 implies a weak correlation and with a P-
value of 0.000, the results can be considered significant to the 95% significance
level. The Kruskal-Wallis test (table 4.1.3) also proved that the two variables are very
similarly affected by the presence of a National Park. Whilst statistically there is only
Pearson correlation of %HP Increase 2001-11 and Percentage
of holiday homes = 0.196
P-Value = 0.000
Regression equation:
%HP Increase 2001-11 = 92.41 + 2.048 Percentage of holiday
homes
S = 20.2952 R-Sq = 3.9% R-Sq(adj) = 3.6
LADS not in NP
36
a weak positive correlation at national level, by simply comparing the raw data in the
table and by looking at the map, it is clear that there is a relationship between house
price increase and holiday home ownership. This is reflected in previous literature,
that has found ‘in an open ‘second home’ market the number of competitors is
inflated, heightening demand pressure, pushing up prices, and reducing both
affordability and access’ (Suffolk County Council, 2004, pp.30). Of the research
readily available, there does not appear to be a study into the impact of holiday
homes at a national level since the census was released with the new second homes
data in 2011 and few seem to have much faith in the national figures prior to this
(Satsangi et al., 2005). The maps alone are surely proof that second and holiday
home ownership is prolific in many regions of the country, even those outside
National Park boundaries. However, it has been the case for a number of decades
now that many parties do not consider second homes to be an issue at a national
level due to the low overall percentages. Previous governments, such as Thatcher’s
in 1981, Blair’s in 1998 and the post 2005 administration have not ‘been persuaded
that the problem, such as it is, could be tackled effectively through the planning
system’ (DCLG, 2009, pp.35). Today, still, they continue to maintain that ‘distortions
in local housing markets rarely warrant a general response that stretches across an
entire county or region, let alone the country as a whole’ (Satsangi et al., 2005,
pp.82). However, this statistically significant relationship once referred to as being
‘modest’ (Affordable Rural Housing Commission, 2006, pp.62), is now surely cause
for concern, particularly with the predicted increases in second homes (Direct Line,
2005; Satsangi et al., 2005).
Second homes may not be considered to be the ‘primary driver’ behind housing
shortages in some areas, but they are ‘held up as a pressure making a difficult
situation worse, [...] probably a fair assessment of their impact in many local markets’
(Satsangi et al., 2005, pp.82). It is hoped, however, that with this newfound national
level relationship, revealed by the census, perhaps National Government will begin to
take more notice of the local concentrations. Glen Bramley’s foreword in Oxley et
al.’s (2008) literature review of second homes, in agreement with this study’s
findings, ‘gave weight to the view that second home purchasing is an issue of
national significance’ (Satsangi et al., 2005, pp.88-89) and is interpreted by ‘some as
an acknowledgement that second home impact on house prices’ (pp.89).
Additionally, Nick Gallent also argues that there needs to be action taken upon the
37
‘specific pressures’ (Gallent, 2009, pp.276) that are affecting rural housing
affordability in the UK, and SHO is widely regarded to be one of those pressures.
4.2 REGIONAL LEVEL: THE LAKE DISTRICT
4.2.1 SECOND HOME PATTERNS
Figure 4.2.1 Second homes by parish (Source: Allen, 2015 and Walker, 2015)
As depicted in figure 4.2.1, higher levels of second home prevalence appear to be
concentrated in the east of the LDNP with the west of the region experiencing much
lower levels of second home percentages. Of the top twenty parishes with high
second home percentages, four are in Eden, two in Allerdale, two in Copeland and
twelve in South Lakeland. Martindale in Eden (refer to fig.1.2 for parish names) has
the highest proportion of second homes at 37.14% whilst Bewaldeth and Snittlegarth
has no second homes, followed by Blindbothel where second homes make up 1.47%
of its total dwellings. With the exception of the aforementioned Bewaldeth and
Snittlegarth, according to the data used in this study, every parish in the LDNP has,
at least one second home within its boundaries. Areas where a parish is only partially
38
within the boundaries of the National Park tend to have lower levels of second home
prevalence, perhaps further signalling the impact of National Park boundaries.
Overall, Copeland has the lowest overall levels of second homes of all the LADs
within the LDNP, which is confirmed by the national level 2011 census data, whilst
South Lakeland has the highest, followed by Eden then Allerdale. Despite South
Lakeland being home to some parishes with the highest second home percentages
(Skelwith, Cartmel Fell, Dunnerdale with Seathwaite, Blawith and Subberthwaite,
Broughton East, Meathop and Ulpha, all in the top 10 highest), it also has a number
of parishes that have amongst the lowest percentages (Witherslack, Longsleddale,
Underbarrow and Bradleyfield and Over Staveley, all in the far east).
Using Google Maps, it has been found that of the parishes ranked in the top
20 for second home prevalence, 40% are within a half hour drive to the nearest M6
motorway junction and 95% are within an hour’s drive (with no traffic) (Google Maps,
2016). Therefore, it may be reasonable to assume that accessibility and travel time
have an impact on the location of a second home. The western regions of the Park
show very low second home percentages, which could be attributed to the time taken
to travel from the M6 motorway. In addition, figure 4.2.2 shows a map with the
primary, main, secondary and minor roads that run through the National Park. South
Lakeland and Eden appear to have access to a higher number of primary and main
roads in comparison to Allerdale and Copeland where the majority of the roads are
either secondary or minor.
Comparing figure 4.2.1 and the topographical relief map (fig.4.2.2) of the
LDNP, there also appears to be a similarity between the prevalence of mountains
and lakes and the location of second homes. Whilst the 2014 Gibbons et al. study of
the amenity value of English nature was looking primarily at the impact upon house
prices, the positive correlation found in this study between SHO and average house
price value could potentially further support their findings and thus imply English
nature also has an impact upon the numbers of second homes. Increased demand
for nature in close proximity to a dwelling has an inflationary effect upon the housing
market in an area abundant with such natural beauty, and in this case, this demand
is coming from both people looking to purchase a permanent residential home and
people looking for a second (holiday) home.
39
Figure 4.2.2 Topographical relief map of the LDNP (Source: LDNPA, 2010)
40
4.2.2 HOUSE PRICE PATTERNS
Figure 4.2.3 Percentage house price increase (2006-16) (Source: Zoopla)
Figure 4.2.3 reveals four distinct areas and patterns of house price increase. The
northeast of the LDNP has experienced the lowest levels of house price increase
whilst the southeast has experienced the highest (approx. 26%). The west and far
north-west has experienced the next highest increase in house prices whilst the
south-west and central areas have experienced rather low levels of house price
increase. In contrast with the national level analysis, the relationship between house
price increase and second home percentages within the LDNP boundaries are much
less obvious. Unexpectedly, there are very few areas where there is a high figure for
both variables. Of the top twenty parishes to experience high house price increase,
four are in Allerdale, three are in Copeland and thirteen are in South Lakeland. At
first glance, this seems to be similar to the numbers described for second home
percentages in the region, however only two parishes are in the top twenty for both
variables and the Bewaldeth and Snittlegarth parish has experienced one of the
highest house price increases but has a second home percentage of zero. The ten
41
parishes that have experienced the lowest levels of house price change are all in
Eden, yet four of them are also in the top ten parishes with high levels of SHO.
Figure 4.2.4 Scatterplot of house price increase vs second home prevalence
(Source: LDNPA, Copeland Borough Council and Zoopla)
Figure 4.2.5 MiniTab Statistical Analysis Results
A statistical analysis (see fig.4.2.5) reveals that whilst the results are more than 95%
significant, there is, in fact, a weak, negative correlation between the two variables,
the opposite to what had been expected and to the results at a national level. An
analysis of just one local authority within the LDNP, South Lakeland, provided similar
results to those of the Park as a whole, implying that the results are accurate and
representative.
Value Change last 10 yrs (%) = 22.55 - 0.1130 % of 2nd homes
Pearson correlation of Value Change last 10 yrs (%) and % of
2nd homes = -0.293
P-Value = 0.015
42
Figure 4.2.6 Average house price value (2016) (Source: Zoopla)
A comparison of figure 4.2.6 above, showing the spread of average house prices,
and figure 4.2.1 shows many more instances of similar patterns than that of figure
4.2.1 and figure 4.2.3. A MiniTab analysis (see fig.4.2.7) revealed that there was
indeed a much stronger, positive and significant (at the 95% significance level)
correlation between the two variables.
Figure 4.2.7 MiniTab statistical analysis results
4.2.3 SECOND HOMES & THE LAKE DISTRICT HOUSING MARKET
The results for the regional level analysis in the LDNP have produced unexpected
results that ultimately contradict those of the national level analysis. It had been
Pearson correlation of Current Avg Value and % of 2nd homes = 0.306
P-Value = 0.011
43
expected that a very similar relationship would be found between house price
increase and second home percentage as was found at the national level, but in fact,
both the maps and the statistics imply otherwise, almost opposite, with a negative,
albeit weak, correlation. However, these findings are in fact consistent with the
findings of previous studies, for example, in their assessment of second home
research literature, Oxley et al. (2008), found that the studies available fall into two
categories; national but more generalised; and local but highly specific; and the two
can offer contradictory findings’ (pp.25).
SATURATION
The maps show that in a number of cases, second homes are higher in areas where
house price increase has been lower, which is supported by the negative relationship
found through the statistical analysis. In her study, Bennett (1979) found that second
homes were most prevalent in Eden due to its easy accessibility and South Lakeland
as a strong tourist area. The western regions of the National Park such as Copeland
and Allerdale were found to have originally had fewer second homes until the late
1970s, following the rapid increase of second homes since the 1960s (Wallace et al.,
2005). Figure 4.2.1 in this study has found these patterns of second homes in the
LDNP to be largely similar still today, particularly the areas of South Lakeland and
Eden, and it has also been suggested, in agreement with Bennett (1979), that such
patterns could still be accounted for by the ease of access, amongst many other
factors. Despite this, some areas in Allerdale and Copeland are still experiencing
relatively high levels of SHO, such as Irton with Santon and Ulpha in Copeland and
Borrowdale, St Johns, Castlerigg and Wythburn and Above Derwent in Allerdale, all
of which have a second home percentage of over 13%. Bennett (1979) had found
that the popular urban centres of Keswick, Ambleside, Windermere and Bowness-on-
Windermere and their surrounding were beginning to become saturated with high
levels of second homes and holiday lettings. This in turn was leading to a spill over
effect to areas of the Park that had previously been largely unaffected by the
phenomenon (Bennett, 1979; Gallent & Tewdwr-Jones, 2001), such as Allerdale and
Copeland.
This pattern of saturation and spill over would appear to be still taking place.
The ‘popular urban centres’ are still home to a high percentage of second homes,
however a negative relationship between house price increase and SHO would imply
that second home purchasers are deterred by the high average house prices in the
44
popular, eastern areas (see fig.4.2.3). As a result, they are branching out into areas
previously less favoured by second home owners, where house price value is low
and house price increase has been relatively small over the past 10 years, such as
Copeland and Allerdale. In 1972, Jacobs found that ‘when the concentrations of
second homes reached 12% of the local dwelling stock a saturation point was
achieved, and demand for second homes was directed elsewhere” (Wallace et al.,
2005, pp.44). Whilst it is unclear how Jacobs came to his figure, Bennett’s work
supported this idea and found that second homes spread across the LDNP were
closely linked to suitable properties drying up in certain settlements thus spreading
the demand into adjoining areas (Bennett, 1979 cited in Wallace et al., 2005). 34 of
the 69 parishes analysed in this study have a second home percentage of 12% or
more and Ambleside, Windermere, Bowness-on-Windermere are all within the
boundaries of one of those 34, which therefore, to an extent, supports Jacob’s
suggestion of saturation levels. Bennett (1979) found that the ‘cheaper end of the
market’ was going to the second home purchasers (Wallace et al., 2005, pp.51) a
trend this still occurs today, as found by Suffolk County Council who in their 2004
study into second homes in Suffolk, observed that ‘second homes tend to be in the
lower (tax) bands, and thus the same types of properties as those sought by first-time
buyers, or those seeking affordable housing’ (Suffolk County Council, 2004, pp.13).
RENT SEEKING
The contrasting findings of the national and regional level and the relationships
between second home ownership and house price change versus house price value,
could also be attributed to the ‘rent-seeking society’ theory. It is regarded by most
economists as being the equivalent to ‘profit seeking’, whereby ‘the expectation of
excess returns motivates value increasing activities(Tollison, 1982, pp.575). In this
case, second home purchasers may have recognised saturation taking place in the
LDNP and as a result, have purchased areas where spill-over is beginning to occur,
e.g. Copeland and Allerdale. Whilst we know second homes are not the sole force
behind rising house prices in the Lake District, they certainly have a significant
impact on top of the other factors (see below). By purchasing a second home in an
area currently less affected, as the area becomes ever more popular with second
home purchasers, the housing market will begin to react as prices begin to rise to the
same levels being experienced in the eastern regions of the LDNP. Investopedia
45
describes rent seeking as when an ‘individual uses their resources to obtain an
economic gain from others without reciprocating any benefits back to society through
wealth creation(Investopedia, n.d.). Second home purchasers, some perhaps
unwittingly, are choosing areas of low house price increase (Copeland and Allerdale)
but over time will find their property soar in value as has been experienced previously
in areas of South Lakeland and Eden. This increase in value of their property
represents the ‘rent-seekers’ (the second home purchaser)’s ‘economic gain’ whilst
the locals who are out-competed of the increasingly inaccessible and expensive
housing market represent the lack of any reciprocation of wealth creation from the
second home purchaser.
ISOLATING THE IMPACT
The positive correlation between SHO and average house value does not necessarily
mean that second home purchasers are attracted to areas where average house
prices are high, as discussed above. Instead previous second home purchasers
(amongst other factors highlighted below) have been instrumental in the inflation of
the housing market by significantly contributing to the intense demand, whereby
leaving second home hotspots with higher house prices than those areas with lower
demand from second home purchasers. Had this same study been conducted in the
mid-1970s, the results would most likely have been very different and instead, there
would perhaps be a positive correlation between house price increase and second
home prevalence as the SHO phenomenon was in its early stages. Pyne (1973)
stated that to isolate completely the impact of second homes from other actors that
may affect the housing market is a sizeable challenge and one that many have
struggled to do since the 1970s. Barnett (2014) conducted a similar study to this one,
using the PPMCC to reveal a ‘significant moderate-strength positive correlation
between the percentage of second homes in a parish and the median house price in
that parish (r = 0.531 p ≤ 0.05)’ (pp.17). However, the presence of parishes with
‘lower percentages of second homes to have higher house prices demonstrates that
there are many influences on house prices, limiting the strength of this relationship. A
causal relationship between house prices and proportions of second homes cannot
be deduced despite this statistically significant relationship existing’ (pp.17). Brief
analyses of secondary data tend to confirm the majority of residents’ opinions, that
areas of high second home prevalence often also have higher house prices thus
implying that the two variables are potentially connected. However, other studies
46
have found this to be inconclusive due to the aforementioned difficulty to isolate
second home impacts (Leyshon and DiGiovanna 2005; Wallace et al. 2005 cited in
Barnett, 2014).
Instead, ‘evidence available from local studies has tended to focus on the
extent to which external demand, derived from retirement and commuting patterns,
and including second home purchase, has pushed property prices beyond the reach
of local residents (Oxley et al., 2015, pp.26). Shucksmith (1981) found that in the late
1970s, outside demand for dwellings in the LDNP was ‘hugely significant’ (Wallace et
al., 2005, pp.39) and local estate agents estimated that ‘over half of all property
purchases were by people outside the area’ (pp.39). Bennett (1979) traced the
impact of ‘urban demand’ upon the region’s housing market and found that the
intense, demand for the cheaper homes from second home owners and commuters
was raising the price ‘beyond the means of locals’ (Wallace et al., 2005, pp.51).
Bennett’s findings are consistent with Richards and Satsangi’s (2004) study of
affordable housing in Britain’s National Parks, which also found that the people
‘purchasing properties for these purposes [second home owners, commuters,
retirees] tend to be in-migrants to the area, with greater buying power, who can
therefore out bid the local residents, resulting in rises in house prices beyond the
reach of locals (Stockdale et al., 2000 cited in Richards and Satsangi, 2004, pp.252).
The constant growth in demand for properties in the LDNP is driven and
perpetuated by ‘economic inequality between the urban region and the rural area
(Gallent & Tewdwr-Jones, 2000). On top of this demand from ‘in-migrants’ are the
National Park’s ‘restrictive planning policies’ (School of Planning and Housing et al.,
2001 cited in Richards and Satsangi, 2004, pp.252). Gallent (2009) called for the
allocation of ‘more land for housing through the planning system in locations where
second home demand is high’ (Satsangi et al., 2010, pp.90) but the LDNP has, and
in all likelihood always will have, a short supply of housing as a consequence of the
strict planning regulations and laws enforced by the LDNPA, in addition to the
mountainous and lake-heavy topography of the region, thus rendering any further
allocation of land for housing extremely difficult. This subsequent excess in demand
pushes house prices up ‘higher and higher’ (pp.252). As a result, second homes may
not be forcing house prices up as extensively as other forces, but instead, the high
prices resulting from those other actors mentioned above ‘can only be afforded by
more affluent outsiders’ (pp.252).
47
Whilst it is difficult to fully isolate and analyse the impact of second homes
upon the housing market from the likes of external demand, commuters, retirement
homes, etc. what can be concluded is these ‘in-migrants’ are likely to be coming to
and choosing the LDNP for the same reasons; beauty, tranquillity and outdoor
activities, amongst others. Regardless of what these people are buying the properties
for, what the majority of the academic literature discussed in this study can agree
upon is the impact of all these actors upon affordability and thus the ability of local
residents to remain in their home communities.
48
CHAPTER 5: CONCLUSION
5.1 OVERALL CONCLUSIONS
The focus of this study has been the impact of second homes upon house price
change at a national level (UK) and a regional level (LDNP) whilst also looking at the
patterns of holiday home ownership across both levels, looking particularly at the
influence of National Parks upon both variables at a national level. It was found that
at a national level, using the PPMCC, there is a statistically significant, positive
correlation between house price change and holiday home ownership but that this
relationship was not reflected at the regional level within the borders of the LDNP,
which produced a weak, negative correlation. A statistical analysis of SHO and
current average house price value in the LDNP revealed a much stronger
relationship between the two. The Kruskal-Wallis and ANOVA tests revealed the
significant impact of National Park borders upon SHO and house price change where
both were higher in LADs within a Park’s boundaries, thus justifying a study that
would analyse the patterns within those boundaries along with the impact of SHO
upon house price change. Patterns of SHO within the LDNP revealed a concentration
of second homes to the east and centre of the region where the major urban centres
such as Ambleside are located, as well as the higher concentrations of accessible
lakes and mountains. The patterns of second homes and house prices at both
geographical levels reflected previous studies that had found natural beauty has a
significant amenity value in England as well as ease of accessibility.
The correlation found at a national level would appear to be in keeping with
some previous findings, however the positive correlation would appear to be more
significant than previously thought or cared to be thought. SHO is attributed to be a
consequential pressure upon housing markets when working alongside other actors,
particularly in rural regions. The unexpected negative relationship between house
price change and SHO in the LDNP, along with the stronger positive relationship
between SHO and house price value implies a saturation effect is taking place.
Popular SHO destinations in the central, eastern regions have been saturated in
49
terms of housing stock and house price values, pushing second home purchasers
towards areas where house price change has been low over the past 10 years and
previously less popular as second home destinations. Such second home purchasing
patterns could also be attributed to rent-seeking theory, whereby second home
purchasers aim to maximise their own profits. It is also accepted, however, that
second homes are just one factor out of many that are at work in the LDNP, affecting
the rural housing market and its subsequent reduced affordability for locals.
Significant demand from the adventitious population for housing, the restrictive
topography and planning regulations and the subsequent shortage of housing are all
already having a considerable effect in the National Park’s housing market and the
added pressure of huge demand for second homes is resulting in huge house price
increases in many parishes within the LDNP.
The term ‘saturation’ features only a handful of times in the available literature
on second homes and the majority of those articles date back to the 1970s. Jacobs
(1972) and Bennett (1979) are the only academics to refer to the same saturation
that appears to manifesting itself in the LDNP today, as discovered in this study. It is
therefore hoped that the findings of this work are a valuable and original contribution
to the existing literature focused upon this topic.
5.2 STUDY LIMITATIONS
The ‘difficulties with differentiating between a second and holiday home [have been]
readily acknowledged by a number of the studies (Davies and O’Farrell, 1981;
Bielckus, 1977 cited in Wallace et al., 2005, pp.27). At a national level this was less
of an issue thanks to the census data, however at a regional level, the council tax
data used does not distinguish between second home uses such as working, holiday
and other. It was assumed, due to the nature of the region, that the majority of
recorded second homes would be used for holiday purposes, potentially limiting the
overall validity of this study’s conclusions, particularly when comparing the two
geographical levels.
Had reliable, consistent data been available at both levels, a temporal analysis
would have been conducted to provide more insight into the effect of increasing
second home numbers as opposed to comparing a temporal figure (house price
change over 10 years) to a static figure (second homes in 2011). This would have
offered a more accurate and relevant insight into how an increase in second homes
50
leads to an increase in house prices compared to how high levels of second homes
increase house prices.
5.3 FUTURE RESEARCH & DATA COLLECTION
Whilst Oxley et al. (2008) argued that ‘there is an almost total lack of robust evidence
to support the contention that second homes increase property prices’, this cannot be
attributed completely to the lack or quality of the studies available for their
assessment of the research literature on the purchase and use of second homes
proves much the opposite. Instead, it surely highlights the lack of quality data made
available. The recent introduction of second home counts to the national census may
be a step in the right direction, however without accurate and comprehensive data at
geographical levels lower than the local authority level, academics, government and
planners (particularly at a local level) are going to struggle to make any progress in
isolating the impact of second homes upon house prices and thus create any
effective policies or plans to mitigate the negative impacts.
The problem for many communities is not just the purchase of local housing
stock by affluent outsiders for second homes, but also the conversion of that housing
stock into other holiday businesses such as multiple holiday rentals owned by one
company (see Lake Lovers who own over 130 properties in Ambleside alone), bed
and breakfasts and guest houses. These particular types of ‘businesses’, particularly
holiday rentals, are very similar to second homes in terms of the impacts they have
upon the rural housing market, outcompeting local buyers who want to use the
property as a permanent residence as opposed to it being used only seasonally and
being left empty for large parts of the year. In areas such as the Lake District where
businesses like these are just as prolific as second homes, it is important that they,
and other dwellings converted from their intended use as a permanent residence to a
business, are counted at a low geography level to assess their impact and
prevalence. Further research could also include a comparative analysis of national
parks in England, Scotland and Wales to see how the patterns, correlations and
impacts differ. AONBs have also been excluded somewhat from studies as National
Parks have taken precedence, yet many are still endowed with extensive
concentrations of rural regions and green spaces that so many second home
51
purchasers and indeed, many who are looking for a permanent residence, are
attracted to.
Finally, the new stamp-duty tax on second homes and buy-to-let properties is
likely to influence significantly the purchase of second homes. Once this tax has
been implemented in April 2016, it would be interesting to see how it will affect the
national level and local communities to assess whether such a policy can improve
the second home situation at more than one geographical level, a feat that many
remain sceptical of.
52
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60
APPENDICES
APPENDIX A: DISSERTATION SUPPORT GROUP FORMS
Name of Student: Jenny Broomby
Meeting Number: 1 Date: 27/02/2015
Members present: Gordon Mitchell, Jenny Broomby (others no longer in my DSG)
Apologies for absence: n/a
First DSG meeting with Gordon Mitchell, groups have changed since then)
Issues to be raised (complete prior to each meeting):
Would like to look at globalisation in the Lake District, how is it spreading and
what are its impacts
Is this feasible? Is it going to be too broad?
What are the sort of indicators I could look at?
Would prefer to use mapping and quantitative methods, will a focus purely on
this approach be a detriment to my study?
Do marks tend to be given more generously to those who have collated their
own primary data? Is it considered ‘better’ than secondary?
Is it better to decide on a research approach before the question?
Should the availability of census datasets be looked at first before settling on a
question?
Solutions discussed (to be completed during/after the meeting):
There may be some necessary iteration and some research is inspired by
available data but having a clear path from question to data is still critical so need
to think of clear question first.
Work out one solid aim first, and focus upon just one, it needs to be able to be
expressed as a question
Need to go away and have a look at previous dissertations/studies that have
focused upon globalisation, create my own KOF index?
Either secondary or primary data is fine, but consider what is best for your study
Quantitative and mapping also fine but again, can you justify using that approach
for your study?
Questions for mentor (record after peer-group meeting only; bring to next meeting
with mentor):
N/A
61
Name of Student: Jenny Broomby
Meeting Number: 2 Date: 12/03/2015
Members present: Russell Smith, Jenny Broomby, Molly Gunton
Apologies for absence: n/a
DSG Group Meeting
Issues to be raised (complete prior to each meeting):
Would like to look at the Lake District National Park in some capacity,
however having done some initial research, I’m worried about just how much
of a challenge looking at globalisation within the park will be. It will require a
lot of primary research into numerous, well thought out variables
Literature surrounding the topic of globalisation is extensive but struggled to
find anything pertaining to globalisation in a rural area such as a national
park, is it that relevant? Would fill a gap but not enough literature available yet
to refer back to.
Solutions discussed (to be completed during/after the meeting):
Globalisation may not be the best track to go down, but instead another
indicator of ‘changing times’ in the Lake District
I am mostly interested in economic/political changes with a hint of social
change too
Could potentially look at house prices in the Lake District
What is causing them, why, since when and how?
Going to look into literature surrounding this topic and decide what variable I
would focus on. Perhaps worth getting in touch with someone at the National
Park Authority
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
Is the topic of house prices over done? Would a specific analysis of once place
in particular be suitable for such a study considering how many impacts there
are on house price at so many different levels?
62
Name of Student: Jenny Broomby
Meeting Number: 3 Date: 21/04/2015
Members present: Russell Smith, Jenny Broomby, Molly Gunton
Apologies for absence: n/a
DSG Group Meeting
Issues to be raised (complete prior to each meeting):
Dissertation proposal deadline is in 2 days, we will use this meeting to check
over one another’s proposals to double/triple check that we are all along the
same lines
Have we justified our research topic properly and effectively in the rationale?
Are everyone’s aims reasonable and are they approached in a suitable,
justified way in the methodology?
What have people put in their dissertation timetable?
Solutions discussed (to be completed during/after the meeting):
Potentially got one too many aims, will the study be too broad? Going to take
one out in the hope it will make the study more focussed and easier to achieve
coherent results/discussion. Perhaps looking at social and economic factors is
too much.
Could some of the aims actually be objectives? Something to consider.
Dissertation timetable should set some goals for certain tasks/sections to be
finished and started, e.g. lit review, data research, data analysis. Be realistic
and set achievable goals.
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
Do I have too many aims?
63
Name of Student: Jenny Broomby
Meeting Number: 4 Date: 05/05/2015
Members present: Russell Smith, Jenny Broomby, Molly Gunton
Apologies for absence: n/a
DSG Group Meeting
Issues to be raised (complete prior to each meeting):
My methodology has been flagged as needing a lot more work, my data is
vague and I need to search for some better sources, struggling to find any
data other than that of a local authority level which will be too broad to do a
study of the Lake District
Should I take out my aim of looking at the demographic composition of the
Lake District and just focus on house prices being affected by second homes.
How can I link it in if I do intend on using it? Still struggling to decide!
Solutions discussed (to be completed during/after the meeting):
Suggested that perhaps a FOI request to local councils will work, do they
count second homes? Worth a try but will need a backup plan if they cannot
provide you with the data, perhaps do a survey of a particular area? How
feasible will it be?
The demographic composition of the area may come up during the discussion
so may be worth taking it out of the aims and just using it as a part of the
discussion section.
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
Should I consider changing my topic to assessing a variable that is available
from the census at a lower geography level than LADs?
64
Name of Student: Jenny Broomby
Meeting Number: 5 Date: 27/05/2015
Members present: Gordon Mitchell, Jenny Broomby
Apologies for absence: n/a
Meeting with mentor
Issues to be raised (complete prior to each meeting):
Worries regarding data collection have emailed councils but still waiting on a
reply.
Are my aims etc okay to go away and start working on over summer? All
clear?!
Solutions discussed (to be completed during/after the meeting):
Need to think about alternative methods of collecting data for second homes
If you are in the LD all summer then could do a data collection of all the
different towns, the main ones such as Ambleside and Windermere
Prepare a data collection framework to be on the safe side
Perhaps go into the council offices and ask?!
Aims are fine, just make sure they are clearly differentiated from your
objectives for your first report. What are you doing to achieve your aims?
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
N/A
65
Name of Student: Jenny Broomby
Meeting Number: 6 Date: 9/10/15
Members present: Gordon Mitchell, Jenny Broomby
Apologies for absence: n/a
Meeting with mentor
Issues to be raised (complete prior to each meeting):
Struggling to differentiate between my aims and my objectives
What kind of statistics would be most suitable, have had a look at correlative
analysis but there are a number of different ones and not sure which is best
Worried about the possibility of the results not being conclusive/proving
something completely different!
Solutions discussed (to be completed during/after the meeting):
Go and see Rachel Homer regarding stats, she will be best placed to give
advice. Consider doing a multi-level regression model, seeing as you are
comparing two different geographical levels. Would improve methodology
which had previously been flagged up
Aim is the overall question, objectives are how you are going to achieve that
aim. Bullet point them and make sure they link up. Will your objective help
achieve your aim?
Do not need to worry if results arent what you expect, this is the case for many
studies and it will give you plenty to talk about!
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
N/A
66
Name of Student: Jenny Broomby
Meeting Number: 7 Date: 04/12/2015
Members present: Russell Smith, Jenny Broomby
Apologies for absence: Molly Gunton
DSG Group Meeting
Issues to be raised (complete prior to each meeting):
Struggling to find the correct boundaries for my study, I have received the
data from the Lake District National Park Authority but they have given it to
me at a parish level. Where can I find the boundary data? Strikes me as
being quite an old boundary to use.
Cannot find boundary data for National Parks
Solutions discussed (to be completed during/after the meeting):
Neighbourhood Statistics have parish level datasets up until 2011 so should
be able to find them either on there or use OS Open Data
We had a look for the National Park boundaries but to no avail so have
emailed the National Park authority to see if they can give us access to it.
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
N/A
67
Name of Student: Jenny Broomby
Meeting Number: 8 Date: 11/02/2016
Members present: Russell Smith, Jenny Broomby, Molly Gunton
Apologies for absence: n/a
DSG Group Meeting
Issues to be raised (complete prior to each meeting):
Review our second interim reports
Should I use the Kruskal-Wallis test to have a statistical analysis of the
impact of National Parks? Will it really add to my study?
Should the methods be in the past tense or the present?
Solutions discussed (to be completed during/after the meeting):
Definitely worth adding the KW test, means you can actually prove the impact
as opposed to just speculating using the maps. Use the results regardless of if
they prove what you expected, will add to the discussion.
Methods should be in the past tense, results in the present
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
N/A
68
Name of Student: Jenny Broomby
Meeting Number: 9 Date: 17/02/2016
Members present: Gordon Mitchell, Jenny Broomby
Apologies for absence: n/a
Meeting with mentor
Issues to be raised (complete prior to each meeting):
Interim Report 2 feedback
Bit confused regarding the rent-seeking model that you refer to in the
feedback, when I’ve researched it I tend to find it relates mostly to politics,
how can I relate it to what I’m doing?
Struggling to use a log to make first scatterplot look better, seems to come up
with something completely different to original image
Solutions discussed (to be completed during/after the meeting):
Rent-seeking is a misguiding term and what the theory really means is quite
different to its ‘title’ – have a look at profit maximisation and see how you can
link this theoretical framework into your findings.
Scatterplot will suffice without log, just a display issue so not vital
Questions for mentor (record after peer-group meeting only; bring to next
meeting with mentor):
N/A
69
APPENDIX B: DSG REFLECTIVE LOG
Whilst I found the DSG process to be helpful on occasion, I feel that how much
you gain from them is very much dependent on how well everyone is matched in
terms of their study focus. I appreciate that there will be a vast array of study topics,
but even placing people into groups who are intending on using GIS and quantitative
methods heavily throughout their study should be encouraged because it tends to be
the methods that pose a number of difficulties to people, particularly those that are
reliant upon software such as MiniTab and MapInfo. I believe that matching students
based upon the methods they intend on using is more important than matching them
based on their study topic and have found that I have contacted my GIS classmate
from last year to ask questions about GIS methods and quantitative analysis as
opposed to asking those in my DSG group.
I found my one-to-one meetings to be much more helpful and useful than the
peer-group meetings. I have taken more sound advice away from those meetings
than I have from the peer-group meetings. Meetings tend to feel a little awkward
because you don’t want to come across as hogging the conversation, talking about
your own study and you may sometimes refrain from asking a question you need to
know the answer to. In addition to that, I think as students, we feel less confident to
answer someone else’s question for fear of sending them off in the wrong direction
and in reality, they will inevitably end up going to the tutor to ask the question,
regardless of the help you may receive in a group meeting.
I have found that conversing with my group via social media such as our
Facebook group, to be much easier than organising a meeting. It means I am able to
post the question online as soon as I think of it, instead of having to wait until the next
meeting to discuss, by which time I am either likely to have forgotten it or resolved it
via other channels. I would recommend that students do use a Facebook group,
some may perceive it as being lazy, but I regard it as being much more efficient,
especially in terms of time management which is so important throughout the
dissertation process.
70
APPENDIX C: FIRST INTERIM REPORT
GEOG3600
Dissertation
Does holiday home ownership
increase the rate at which house
prices rise in the UK?
Literature review
Early studies suggest the expansion of the second home phenomenon started in the
1960s (Davies and O’Farrell, 1981; Tewdwr-Jones et al., 2002) and since it has
continued to grow. In 2005, Direct Line predicted a 24 per cent rise in second homes
by 2015, increasing by 77,000 from 328,000 to 405,000 (Oxley et al., 2008, pp.29).
10 years ago, the Centre for Housing Policy at the University of York undertook a
systematic literature review of the impact of empty, second and holiday homes on the
sustainability of rural communities, and more recently, in 2008, the Centre for
Comparative Housing Research at De Montfort University conducted a similar
literature review, looking assessing the research literature on the purchase and use
of second homes. Throughout both reviews there appeared to be a common
skepticism of the evidence available to prove some of the publications’ assertions
that second home ownership increases house prices. For example, in their 2005
report, Direct Line stated, “Second homes and holiday homes contribute to rural
social exclusion as local residents are increasingly priced out of the limited
housingresource” (Direct Line, 2005, pp11), but the Centre for Comparative
Housing Research concluded that the evidence to suggest this statement was “wholly
inadequate” (Oxley et al., 2008, pp.25).
Those reports that appeared to prove the impact of second homes upon house
prices, however, were extremely localised and thus were unable to provide any
suggestion of the impact at a wider, county or even national level. There does not
appear to be any publicly available, recent (past 10-20 years) research that has
instead looked at the relationship between holiday/second homes and the rate at
71
which house prices increase, as opposed to the effect upon raw house prices.
Gallent et al. (2002) found that the issue of second and holiday homes may not be a
huge problem at local authority level, however the issue does cause for particular
concern in some individual villages and small local communities. This research was,
however, conducted over 10 years ago and the aforementioned increase in second
homes may well now be presenting problems at wider geographical levels, such as
the regional level, e.g. Cornwall. With such a significant increase predicted, it is
surely necessary to be prepared for the potential impact it may have upon local
communities and housing markets.
The Lake District has been a National Park since 1951 and since then the area
receives approximately 15.5 million visitors from around the world every year. With
this increase in tourism has come an increase in second homes in the National Park,
with around 15% of the total 22,930 dwellings now holiday or second homes
(Lakedistrict.gov.uk, 2015). There is already extensive literature focused around the
impact of second homes upon local, rural communities elsewhere in Britain and
throughout the world (Farstad, 2013; Farstad and Rye, 2013; Pacione, 1979; Barnett,
2014, The Centre for Housing Policy, 2005), however there has not been a study that
has looked at the UK as a whole before analysing national parks and areas of
outstanding natural beauty followed by a specific area such as the Lake District
National Park. The Lake District National Park Authority (LDNPA) along with the local
district councils within the park recently conducted an assessment of these impacts,
covering a large scope of outcomes. It briefly reviewed the impacts, both positive and
negative, of second homes upon areas such as sustainability, house prices, culture,
society and the environment (Lake District National Park Authority, n.d.). Hence there
is a gap in the literature for a more concentrated analysis of the Lake District, looking
at the four district councils within its boundaries, and specific, detailed case studies of
local villages that are particularly impacted such as Coniston where 51% of all
dwellings are second homes (Lake District National Park Authority, n.d.). This
dissertation is therefore not only timely due to the predicted increase in second
homes, but it also fills a gap within the extensive research into the impacts of second
homes upon housing markets.
Aim
The overall aim of this study is to understand and assess the impact of holiday
homes on the housing market in National Parks and Areas of Outstanding Natural
Beauty in the UK and how the borders of such areas increase the severity of the
impact, looking specifically at the Lake District National Park.
72
In order to achieve this aim effectively and successfully, the research question has
been broken down into 3 objectives stated below.
Objectives
1) Determine the relationship between changing holiday home ownership and
changing house prices in rural areas at a national level.
2) Determine the relationship between changing holiday home ownership and
changing house prices in popular holiday areas of the UK such as national parks and
areas of outstanding natural beauty.
3) Determine the relationship between changing holiday home ownership and
changing house prices in the Lake District National Park/Cumbria
Methodology/Tasks
This study aims to fill a gap in the research into second homes and their impact upon
housing markets, but will move away from the conventional approach of simply
looking at the relationship with house prices and instead will focus on the relationship
between holiday homes and the rate at which house prices increase. To do this, a
national analysis will be conducted initially to determine whether it is an issue at this
wide geographical level before looking at smaller, individual areas, specifically
national parks and areas of outstanding natural beauty, both of which are predicted
to have an increased proportion of holiday homes due to their popularity and higher
levels of tourism.
A mix of methods will be utilised, such as spatial mapping using GIS software and
statical analysis. The data used for the spatial mapping and statistical analysis will be
secondary data from the 2011 census along with secondary data collated by the local
district authorities and the county councils for tax purposes.
The Pearson product moment correlation-coefficient will be used to determine
whether or not there is a positive relationship between the rate at which house prices
increase and the number of holiday homes there are in the same area. Furthermore,
the Chi Squared Test will be used to help determine the reliability of the results and
conclusions.
73
National level
Analysis at a regional level followed by local district authority level or county
level
Map house prices at a local district authority level or county level
o Using HPI data from the Land Registry
Map second home ownership at same geographical level
o Using data from the 2011 Census
Pearson Product Moment Correlation Coefficient (PPMC)
o Find r to determine the strength of the relationship between the rate of
house price increase and the number of holiday homes across the UKs
Chi Squared Test to determine the reliability of the results
Compare regions and counties
Identify hotspots by analysing separate counties/local authorities using the
PPMCC
Suggest and research reasons for such hotspots
National Park/Local district authority/county level
(Lake District National Park/South
Lakeland/Cumbria)
Analysis at ward/postal code/LSOA/MSOA level dependent upon data available
Identify and analyse hotspots within the area
Identify and map the borders of the Lake District National Park to determine
whether or not this also impacts house price increase as a result of potential
increased second home ownership in that area
Pearson Product Moment Correlation Coefficient
o Find r to determine the strength of the relationship across the National
Park/County
o Find r within areas of the Lake District/Cumbria (postcodes/local
authorities/towns) to identify which areas are more affected
Chi Squared Test to determine the reliability of the results
Identify hotspots
Suggest and research reasons for such hotspots
Determine the severity of the impact by analysing the strength of the PPMCC
o Compare with other areas within the region
Compare the trends, patterns and hotspots with those at national level
74
Bibliography
Barnett, J. (2014). Host community perceptions of the contributions of second homes.
Annals of Leisure Research, 17(1), pp.10-26.
Bielckus, C., Rogers, A. and Wibberley, G. (1972) Second Homes in England and
Wales. Ashford: Wye College, Countryside Planning Unit, School of Rural Economics
and Related Studies.
Bollom, C. (1978) Attitude and Second Homes in Rural Wales, Social Science
Monographs No.3, Cardiff:.University of Wales, Board of Celtic Studies.
Brooks, F., Rubin, H. and Rubin, I. (1996). Qualitative Interviewing: The Art of
Hearing Data. The Modern Language Journal, 80(4), p.555.
Capstick, M. (1987). Housing dilemmas in the Lake District. [Lancaster]: Centre for
North-West Regional Studies.
Cumbriatourism.org, (2015). Surveys and Data Overview. [online] Available at: http://
www.cumbriatourism.org/research/surveys-data.aspx [Accessed 12 Apr. 2015].
Davies and O’Farrell (1981) An Intra-regional Locational Analysis of Second Home
Ownership. Cardiff: Dept of Town Planning, University of Wales.
Direct Line (2005) Second Homes in the UK (Croydon, Direct Line
Insurance).Downing, P. and Dower, M. (1977) Second Homes in Scotland.
Dartington: Dartington Amenity
Research Trust.
Farstad, M. (2013). Local Residents' Valuation of Second Home Owners' Presence in
a Sparsely Inhabited Area. Scandinavian Journal of Hospitality and Tourism, 13(4),
pp.317-331.
Farstad, M. and Rye, J. (2013). Second home owners, locals and their perspectives
on rural development. Journal of Rural Studies, 30, pp.41-51.
Gallent, N., Mace, A., & Tewdwr-Jones, M. (2002). Second Homes in Rural Areas of
England. London: Countryside Agency.
Hall, C. (2014). Second homes planning, policy and governance. Journal of Policy
Research in Tourism, Leisure and Events, 7(1), pp.1-14.
75
Lakedistrict.gov.uk, (2015). Lake District National Park - Facts and figures. [online]
Available at: http://www.lakedistrict.gov.uk/learning/factsandfigures [Accessed 12
Apr. 2015].
Mottiar, Z. (2006). Holiday Home Owners, a Route to Sustainable Tourism
Development? An Economic Analysis of Tourist Expenditure Data. Journal of
Sustainable Tourism, 14(6), pp.582-599.
Lundmark, L. and Marjavaara, R. (2013). Second Home Ownership: A Blessing for
All?. Scandinavian Journal of Hospitality and Tourism, 13(4), pp.281-298.
Müller, D. and Hoogendoorn, G. (2013). Second Homes: Curse or Blessing? A
Review 36 Years Later. Scandinavian Journal of Hospitality and Tourism, 13(4),
pp.353-369.
Norris, M. and Winston, N. (2010). Second-Home Owners: Escaping, Investing or
Retiring?. Tourism Geographies, 12(4), pp.546-567.
Oxley, M., Brown, T., Lishman, R. and Turkington, R. (2015). Rapid Evidence
Assessment of the Research Literature on the Purchase and Use of Second Homes.
Leicester: Centre for Comparative Housing Research, pp.1-65.
Pacione, M. (1979). Second homes on Arran. Norsk Geografisk Tidsskrift -
Norwegian Journal of Geography, 33(1), pp.33-38.
Paris, C. (2014). Critical commentary: second homes. Annals of Leisure Research,
17(1), pp.4-9.
Pidd, H. (2014). How Lake District holiday homeowners are pushing out local
residents. The Guardian. [online] Available at: http://www.theguardian.com/uk-
news/2014/jul/09/lake-district- homeowners-local-residents [Accessed 21 Apr. 2015].
Shucksmith, M. (1981). No homes for locals?. Farnborough: Gower.
Tewdwr-Jones, M., Gallent, N., and Mace, A. (2002) Second Homes and Holiday
Homes and the Land Use Planning System. Cardiff: Welsh Assembly.
The Centre for Housing Policy, (2005). The Impact of Empty, Second and Holiday
Homes on the Sustainability of Rural Communities: A Systematic Literature Review.
York: ESRC, pp.1-135.
Walters, T. and Carr, N. (2015). Second homes as sites for the consumption of
luxury. Tourism and Hospitality Research, 15(2), pp.130-141.
76
APPENDIX D: SECOND INTERIM REPORT
Dissertation, Interim Report 2
Sections 1-4
Title: Assessing the impacts of second home ownership upon house prices and
demographics of local communities in the Lake District National Park (LDNP).
Aim: To understand and assess impact of second homes upon housing market at
national level and LDNP, and how this impact in turn effects demographics of local
communities.
Objectives
1. Analyse patterns of second home ownership nationally
2. Analyse the patterns of holiday home ownership nationally and the relationship
with National Park boundaries
3. Determine the relationship between holiday home ownership and changing house
prices at a national level
4. Determine the relationship between holiday home ownership and changing house
prices in the LDNP
5. Determine and analyse the relationship between number of retirees and house
price increase in LDNP and holiday home ownership
77
Findings & analysis
Figure 1 Percentage of all second homes (2011) (Census, 2011)
National Level:
Small clusters of areas have high percentages of second homes
Many fall within/around national park boundaries.
Snowdonia National Park (SNP), North Wales
All authorities that fall within SNP have some of highest proportions of second
homes
Gwynedd (main authority within SNP) ranks 6/348 authorities
Top 50 authorities with high second home prevalence:
13 within national park boundaries (26%)
Top 25 authorities, 9 within national parks (36%)
78
Two areas with % of second homes: King’s Lynn & Norfolk and City of London
Neither within national park boundary, however King’s Lynn & West Norfolk
borders Norfolk (within national park) which has the 3rd highest prevalence of
second homes overall.
The city of London popular area for ‘working’ second homes (see Figure 2)
Figure 2 Percentage of ‘working’ second homes in England and Wales (2011)
Aggregated and mapped data based on second home classification: working,
holiday, other
Help determine and confirm why some areas have high levels of second
homes, e.g. London
79
Richmondshire, Yorkshire second highest
Attributed to Catterick Army Garrison (largest in UK)
Over 13,000 personnel, military, civilian and their dependents, living and
working in the area” (Army.mod.uk, n.d.)
Figure 3 Percentage of ‘other’ second homes in England and Wales (2011)
“Majority [77%] of people with a second address recorded that this was for a
purpose other than work or holiday, such as the home address of students.
(Office for National Statistics, 2012).
80
Figure 4 Percentage of ‘holiday’ second homes in England and Wales (2011)
National Park(s)
authority falls within
Area
Authority Name
Percentage of
‘holiday’ second
homes (%)
Norfolk Broads
Norfolk
North Norfolk
14.84
N/A
Norfolk
King’s Lynn & West Norfolk
13.52
Snowdonia
Wales
Gwynedd
12.76
Lake District +
Yorkshire Dales
Cumbria
South Lakeland
8.77
Dartmoor
Devon
South Hams
8.65
Figure 5 Holiday home figures
Top 10 authorities, 6 fall within boundary of NP (60%)
81
Top 50 authorities, 23 fall within boundary of NP (46%)
42% of all authorities within NP ranked in top 50 authorities with high levels of
second home numbers.
Top 5 local authorities, only one does not fall within borders of NP however it
borders with top local authority which is within NP.
Of the 4 authorities that fall LDNP, 3 are in top 50 authorities with high second
home prevalence (rationale for study)
Figure 6 House price increase (%) in England and Wales (2001-11)
Comparison: figure 4 & 6
82
Instances of similarity: some areas experienced high house price increase plus
high holiday home prevalence.
E.g. western and northern coast of Wales = high levels of both variables,
particularly Snowdonia; authorities within Yorkshire Dales National Park (YDNP)
and those within LDNP (rationale for study)
Regression analysis to determine strength and nature of relationship
Pearson Product Moment Correlation Coefficient (PPMCC) to test significance of
results and correlation
Figure 7 Scatterplot of house prince increase vs holiday home prevalence
1614121086420
150
125
100
75
50
Percentage of holiday homes (2011)
House Price Increase 2001-11 (%)
Northumberland
Peak District
Pembrokshire
Snowdonia
South Downs
Yorkshire Dales
Brecon Beacons
Dartmoor
Exmoor
Lake District
Lake District & Yorkshire Dales
New Forest
Norfolk Broads
North Yorkshir e Moors
National Park Name
Scatterplot of 2001-11 house price increase (%) vs holiday homes (%)
83
Positive correlation between two variables confirmed
Figure 8 MiniTab statistical results
For every unit increase of the percentage of holiday homes, the percentage
change in house prices from 2001-11 will increase by 2.048 units, positive
correlation.
PPMC (0.196) implies low, positive correlation
Lake District National Park
Figure 9 Percentage of second homes in LDNP by parish
Pearson correlation of %HP Increase 2001-11 and Percentage
of holiday homes = 0.196
P-Value = 0.000
Regression equation:
%HP Increase 2001-11 = 92.41 + 2.048 Percentage of holiday
homes
S = 20.2952 R-Sq = 3.9% R-Sq(adj) = 3.6
84
Figure 10 Percentage house price increase in LDNP (2006-16)
The relationship between house price increase and second home prevalence
within LDNP boundaries less obvious compared to national level
Small number of areas where there is high second home prevalence and high
house price increase, unexpected.
85
Figure 11 Scatterplot of house prince increase vs second home percentage
Figure 12 MiniTab statistical analysis results
PPMCC figure implies significant result but negative correlation between
variables, opposite of national level and expected result. However, still very weak
negative correlation.
Analysis of just one local authority within LDNP, South Lakeland, proved similar
to results of the park as a whole
Figure 16 compared with figure 9 shows more instances of similar patterns
Stronger relationship between house price value and second homes as opposed
to house price increase
403020100
27.5
25.0
22.5
20.0
17.5
15.0
S 2.889 45
R-Sq 8.6%
R-Sq(adj) 7 .2%
Percentage of second homes
House price increase (%) from 2006-16
Scatterplot of 2006-16 house price increase vs second home %
Value Change last 10 yrs (%) = 22.55 - 0.1130 % of 2nd homes
Value Change last 10 yrs (%) = 22.55 -
0.1130 % of 2nd homes
Pearson correlation of Value Change last
10 yrs (%) and % of 2nd homes = -0.293
P-Value = 0.015
86
Figure 13 Average house price value (2016)
Figure 14 Retired population (%) (2011)
87
Figure 15 Scatterplot of retired pop (%) vs second homes (%)
Incoming retirees often attributed to increase in second homes and house prices
However, very weak correlation between two variables
Links with existing literature & discussion
National Level
Positive, albeit weak, correlation at national level consistent with existing
literature
“In an open ‘second home’ market the number of competitors is inflated,
heightening demand pressure, pushing up prices, and reducing both affordability
and access” (Suffolk County Council, 2004, pp.30)
“Many of these hotspots are desirable locations with second home-owners now
significant minorities” (Gilbert, 2001, pp.18).
Regional level: the Lake District
Had expected to find similar relationship between house price increase and
second home ownership as national level
Statistics and maps implied otherwise, almost opposite
Very weak, negative correlation
302520151050
24
22
20
18
16
14
12
10
S 3.311 07
R-Sq 2.6%
R-Sq(adj) 1 .0%
Percentage of second homes
Percentage of retired population (2011)
Fitted Line Plot
Retired % = 15.04 + 0.07412 % of 2nd homes
88
This too is consistent with previous studies:
“Studies available fall into two categories; national but more generalised; and
local but highly specific; and the two can offer contradictory findings” (Oxley et al.,
2015)
“Ssecond homes tend to be in the lower (tax) bands, and thus the same types of
properties as those sought by first-time buyers, or those seeking affordable
housing” (Suffolk County Council, 2004, p13)”
In line with findings of this study
Second homes higher in areas where house price increase is lower
The evidence available from local studies has tended to focus on the extent to
which external demand, derived from retirement and commuting patterns, and
including second home purchase, has pushed property prices beyond the reach
of local residents” (Oxley et al, 2015, pp.26)
Second homes may not be pushing prices up, the high prices caused by other
factors (strict National Park planning regulations) can only be afforded by more
affluent outsiders
Maps show that second homes are higher in areas where house price increase
has been lower
Pattern of high average house prices (vs increase) similar to second home
prevalence
High levels of inward migration, people not wanting second homes but looking to
move permanently to area (compared to many other NPs, large amount of
employment opportunities, combined with physical attraction of area, many are
drawn to LDNP)
Lots of “wealthy achievers” come to the area
This constant, sustained demand perpetuates high house prices and increases
Low housing stock due to strict planning regulations and local occupancy clauses
as well as the topography of the area (mountainous, lakes, forests)
Locals outcompeted by both second home owners and wealthy outsiders wanting
to move to the area
Increased population of retirees: may be very weak correlation however many
retirees who have second homes often move into them as permanent residence
Does not increase second home prevalence, potentially has opposite effect but
still detrimental to local ownership and communities (arguably)
89
Issues with datasets
National
Second home ownership introduced to census in 2011
Temporal analysis of changing patterns and relationships not possible
Limited to authority level
Lake District
Data collated for LDNP derived from figures provided by LDNPA and council tax
estimates from some local authorities
Census data could not be used at authority level as study would be too broad
(only 4 authorities within LDNP)
Not all authorities have responded to FOI requests fully meaning data is not
consistent across the board, e.g. LDNPA did not have data for Copeland,
therefore the gap was filled with data directly from Copeland’s 2016 tax estimates
whereas data for other LA’s is from 2011-13.
Data similar to Copeland was requested to eliminate this inconsistency however it
was not made available by other LA’s
Does not distinguish between classifications of second homes, e.g. working,
holiday or other
Many residences are used as ‘holiday lets’ but are not counted in census data as
‘second homes’ despite them fulfilling a very similar role to that of second homes
Holiday lets, guest houses and B&Bs counted as businesses rather than second
homes, also not counted in the overall number of dwellings despite previously
being a dwelling before conversion into holiday business.
Links with literature:
“Data sets relating to second homes are extremely variable […] lack of clarity and
consistency in defining ‘second homes’, identifying the incidence of second home
ownership” (Paris, 2011, pp. 162)
“Unless there is a solid evidence base to identify the magnitude of second home
ownership and use it would be impossible to monitor the effects of any changes”
(Paris, 2011, pp.163)
90
“Perhaps the greatest single problem faced by the researcher interested in
second homes concerns the general absence of reliable data” (Rogers, 1977
pp.86).
Sections 5-7
5. Draft dissertation structure
1. Title Page
2. Table of contents
3. Acknowledgements
4. Abstract
5. Abbreviations
6. Table of figures
7. Introduction
8. Literature review
9. Rationale
10. Aims and objectives
11. Methodology
12. Results
13. Analysis
14. Discussion
15. Conclusions
16. Future research
17. Policy suggestions
18. Data collection suggestions
19. Reference list
20. Appendix
6. Outstanding work that has to be done before submission
Abbreviations
Acknowledgements
Abstract
91
Finalise/finish literature review and rationale
Finish Methodology
Conclusions
Policy suggestions
Data collection suggestions
Future research
92
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Oxley, M., Brown, T., Lishman, R. and Turkington, R. (2015). Rapid Evidence
Assessment of the Research Literature on the Purchase and Use of Second Homes.
Leicester: Centre for
Comparative Housing Research, pp.1-65.
Paris, C. (2011). Affluence, mobility, and second home ownership. New York, NY:
Routledge.
Rogers, A.W in Coppock, J. (1977). Second homes. Oxford: Pergamon Press.
Suffolk County Council (2004) Second Homes and Affordable Housing in Suffolk.
Ipswich, Suffolk County Council: Policy Unit
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Paris, C. (2011). Affluence, mobility, and second home ownership. New York, NY:
Routledge.
Paris, C. (2014). Critical commentary: second homes. Annals of Leisure Research,
17(1), pp.4-9.
Pidd, H. (2014). How Lake District holiday homeowners are pushing out local
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96
APPENDIX E: RISK ASSESSMENT FORM
97
98
99
100
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