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Abstract

This study examines the resilient economics of the beauty industry in the UK. The beauty and personal care sector has grown more than three times in the last three decades. The academic studies show that there is a significant economic value of beauty in various situations. Given the economic value of beauty, the beauty and personal care sector has been growing very strongly in many countries, including the UK. The current research collects data on the UK beauty and personal care market and conducts a detailed empirical analysis. The results indicate that the growth of the personal care sector is larger than the growth in overall GDP in the UK. The beauty sector is also more volatile. In addition, the GDP growth and consumer confidence index are found to be the leading determinants for the sector. Other variables like population growth and the unemployment rate do not have statistically significant effects. In addition, the Brexit vote in 2016 produced very negative, but short-lived, effects on the sector.
Portia Antonia Alexis
London School of Economics and Political Science
The Strong Economics of The Beauty Industry
While the beauty industry gets a rising share of consumer expenditures and economic output,
research on this sector has been relatively recent and limited. The majority of statistical
institutions and relevant studies categorize the beauty industry under the general umbrella of
consumer goods, and mostly under miscellaneous consumer goods. However, it can be
argued that the beauty sector displays its own unique characteristics, and it is necessary to
focus on the sector to understand its dynamics (Oxford Economics, 2019).
In this context, the first chapter of the dissertation argues that the beauty sector can be
examined in terms of various dimensions. When the literature and relevant reports are
examined, it is found that two approaches dominate. The first approach focuses on economics
or the value of beauty. In other words, the relevant studies examine how being beautiful is
valued economically, especially in the labour markets. It is generally found that there can be a
positive premium of beauty in wages and promotions (Hamermesh, 2011). In addition, some
other studies find that there can be discrimination against beauty in terms of perceived
truthfulness, trust, and deservingness (Sheppard and Johnson, 2019). This stand of the
literature tries to understand and display how beauty is valued, and why positive premiums
are paid. The second approach in the literature focuses more on the economic dynamics of the
beauty sector (Harari, 2016; Oxford Economics, 2019). These studies are mostly composed
of business reports and try to understand the various economic characteristics of the sector,
like its growth, consumer perceptions, consumer loyalty, competition, and branding. This
study falls within the second category of research on the beauty sector. The literature on the
economic characteristics and dynamics of the personal care sector is very limited in the case
of the UK. This research fills the relevant research gap in the literature.
Then, the second chapter provides a literature review of the topic. In this part, the first sub-
section reviews the academic studies. While they are not directly related to the research, they
still provide important insight into the dynamics of the beauty sector. Overall, the academic
literature on the value of beauty finds that there are various economic, political, and social
biases in favour of more attractive people. Given this finding, it is natural that people would
spend significant time and resources on their beauty and looks. So, these academic studies
become important to understand the underlying forces in the beauty sector. In addition, they
imply that people would be investing more in beauty products and services as the market
economy gains more weight in their daily lives. Then, the second part of the literature review
finds that the studies and business reports on the beauty industry in the UK provide valuable
information on the characteristics of the sector and the recent trends. This information is
helpful to understand the sector dynamics and make projections on the future of the sector.
However, both the academic literature and business reports do not provide long-term analysis
of the sector, and they do not examine the main factors affecting the beauty and personal care
expenditures. The current research aims to contribute to the literature by filling these research
gaps in the case of the UK. Towards this aim, detailed macroeconomic data are collected for
the UK, and this data is examined using quantitative methods in the fourth chapter, while the
third chapter shortly describes the research methodology and data.
The fourth chapter forms the core of the dissertation. It presents the results of the data
analysis in two parts of descriptive statistics and regression analysis. The descriptive
statistics of the relevant macroeconomic variables provide important insights into the
dynamics and determinants of the personal care sector in the UK. Namely, the results indicate
that the personal care sector displayed a stronger growth compared to the overall GDP in the
economy. However, it had higher volatility than GDP. In addition, GDP growth and consumer
confidence seem to be the most relevant factors that are positively associated with the growth
in the personal care sector. These results are in line with the expectations that as the incomes
of households rise, they would increase the purchase of beauty and personal care products
and services. Similarly, if consumers have a high trust and confidence in the economy, this
confidence also supports their purchases of personal care goods. The next empirical sub-
section tries to see whether these relationships hold within a multivariate factor analysis with
the inclusion of other control variables.
The results of the regression also confirm the previous findings. Namely, GDP growth is a
positive and statistically significant determinant of growth in the personal care sector. The
population growth has a negative regression coefficient, as in the negative correlation in
Table 2. However, the regression coefficient is not statistically significant. So, this result
implies that that negative correlation of growth in the personal care sector and the population
growth is not a robust puzzle to be concerned with. Unemployment has a negative effect,
which is an expected result. However, the coefficient is not again statistically significant.
Lastly, consumer confidence has a positive and statistically significant coefficient. The Brexit
dummy is negative and statistically significant, implying that the Brexit vote created very
adverse effects on personal care expenditures. Overall, these results produce robust findings
on the positive effects of income and consumer confidence on the beauty and personal care
sector in the UK.
Overall, the dissertation produces important findings on the UK beauty industry. The results
indicate that the growth of the personal care sector is larger than the growth in overall GDP in
the UK. The beauty sector is also more volatile. In addition, the GDP growth and consumer
confidence index are found to be the leading determinants for the sector. Other variables like
population growth and the unemployment rate do not have statistically significant effects. In
addition, the Brexit vote in 2016 produced very negative, but short-lived, effects on the
sector. The paper can be extended by using quarterly data to get more robust results. In
addition, more control variables can be added and the prices in the beauty industry can be
examined in a similar fashion. Such additional robustness analysis can be done in future
research.
Abstract
This study examines the resilient economics of the beauty industry in the UK. The beauty and
personal care sector has grown more than three times in the last three decades. The academic
studies show that there is a significant economic value of beauty in various situations. Given
the economic value of beauty, the beauty and personal care sector has been growing very
strongly in many countries, including the UK. The current research collects data on the UK
beauty and personal care market and conducts a detailed empirical analysis. The results
indicate that the growth of the personal care sector is larger than the growth in overall GDP in
the UK. The beauty sector is also more volatile. In addition, the GDP growth and consumer
confidence index are found to be the leading determinants for the sector. Other variables like
population growth and the unemployment rate do not have statistically significant effects. In
addition, the Brexit vote in 2016 produced very negative, but short-lived, effects on the
sector.
THE RESILIENT ECONOMICS OF THE BEAUTY INDUSTRY
1. Introduction
While the beauty industry gets a rising share of consumer expenditures and economic output,
research on this sector has been relatively recent and limited. The majority of statistical
institutions and relevant studies categorize the beauty industry under the general umbrella of
consumer goods, and mostly under miscellaneous consumer goods. However, it can be
argued that the beauty sector displays its own unique characteristics, and it is necessary to
focus on the sector to understand its dynamics (Oxford Economics, 2019). To quantify the
size of the beauty industry, one can estimate the direct and indirect effects of this industry on
the broad economy. The detailed report by Oxford Economics (2019) estimates the direct size
of the beauty industry’s own activities to be at £14.2 billion in 2018. Then, there is the
indirect size of the sector in terms of £5.9 billion from the industry’s procurement activities
and £8.4 billion from the workers and supply chain connections. So, the total size of the
sector in the UK within the UK is estimated to be £28.4 billion or 1.3% of GDP in 2018. If
one follows an approach from the consumer side, the total value of the sector is estimated at
£27.2 billion for the UK in 2018. This is close to 3% of consumption expenditures. So, both
approaches give similar sizes.
Another approach to follow the dynamics of the beauty industry would be to focus on the
personal care sector. The size of this sector was £30.9 billion in 2018 (ONS, 2020). This
value is close to the above-detailed estimations of Oxford Economics (2019). The personal
care sector includes many products and services like skincare, haircare, personal hygiene,
make-up, fragrance and deodorants, and oral hygiene. This study focuses on the personal care
sector as a proxy for the beauty industry as there is long-run data for this sector in the UK
starting from 1988. Therefore, conducting statistical analysis becomes feasible.
This sector can be examined in terms of various dimensions. When the literature and relevant
reports are examined, it is found that two approaches dominate. The first approach focuses on
economics or the value of beauty. In other words, the relevant studies examine how being
beautiful is valued economically, especially in the labour markets. It is generally found that
there can be a positive premium of beauty in wages and promotions (Fletcher, 2009;
Hamermesh, 2011). In addition, some other studies find that there can be discrimination
against beauty in terms of perceived truthfulness, trust, and deservingness (Sheppard and
Johnson, 2019). This stand of the literature tries to understand and display how beauty is
valued, and why positive premiums are paid. The second approach in the literature focuses
more on the economic dynamics of the beauty sector (Harari, 2016; Oxford Economics,
2019). These studies are mostly composed of business reports and try to understand the
various economic characteristics of the sector, like its growth, consumer perceptions,
consumer loyalty, competition, and branding.
This study falls within the second category of research on the beauty sector. The literature on
the economic characteristics and dynamics of the personal care sector is very limited in the
case of the UK. This research fills the relevant research gap. Specifically, it aims to display
the resilient economics of the personal care sector in the UK. Towards this aim, there are
three objectives: i) to display the price dynamics of the sector in relation to the overall
consumer price index (CPI), ii) to document the output dynamics of the sector in relation to
consumer expenditures and GDP; and iii) to investigate the determinants of personal care
sales dynamics like GDP, unemployment rate, and consumer confidence. In the last point, the
possible effects of the Brexit process on the personal care sector are also examined. The
structure of the dissertation is as follows. The next chapter provides a literature review of the
topic. The chapter both provides details of the business reports and academic papers. Then,
the following chapter displays the research methodology and the secondary data used in the
analysis. The fourth chapter gives the data analysis and the findings, while the last chapter
concludes the study.
2. Literature Review
This chapter gives a detailed review of the relevant studies on the beauty industry. There are
many academic papers that examine the economic value of beauty and why a beauty
premium emerges in the labour markets (Rosenblat, 2008; Andreoni and Petrie, 2008;
Doorley and Sierminska, 2015; Cryder et al., 2017; Bonilla et al., 2019). While the focus of
the current research is not the value of beauty, it is still helpful to review this literature to
understand the dynamics of consumer expenditures on beauty products and services. In
addition to the academic studies, this chapter also reviews the business reports on the beauty
industry. These reports examine the composition of the sector and provide some forecasts. As
the current research focuses on the economic dynamics of the UK personal care sector, the
information obtained from these reports is also very valuable.
2.1. Value of Beauty
In one of the first studies regarding the value of beauty in labour markets, Hamermesh and
Biddle (1994) find that physically attractive employees earned significantly higher wages
than other employees. This difference persisted even after controlling many other wage-
related factors like education and experience. This difference is called the beauty premium,
and it was estimated to be around 10-15%. As an interesting finding, the beauty premium is
also economically large and similar in size to the gender or race premium in the US.
Regarding the possible mechanisms on why beauty earns a premium, studies like Biddle and
Hammermesh (1998) and Pfann et al. (2010) argue that in the jobs where there are extensive
customer and co-worker relations and interaction, beauty can support productivity. There
might also be some self-fulfilling dynamics creating the beauty premium. For example, due
to stereotyping, teachers can expect better-looking pupils to outperform, or employers can
expect better-looking employees to be more productive. Then, teachers and employers can
invest more time and resources on their pupils and employees, respectively. In this way, a
beauty premium can emerge due to the initial perceptions of teachers and employers (Hatfield
and Sprecher, 1986; Feingold, 1992; Eagly et al., 2001). In addition, physical attributes can
be important in acquitting non-cognitive skills like confidence and social networks
(Heckman, 2000). Similar premiums on adult income are found for teenage height, which
seems to support the acquisition of non-cognitive skills (Persico et al., 2004). In this context,
Mobius and Rosenblat (2006) conduct an experimental study to examine the mechanism
where beauty premium arises. The authors identify three channels as “(a) physically attractive
workers are more confident and higher confidence increases wages; (b) for a given level of
confidence, physically attractive workers are (wrongly) considered more able by employers;
(c) controlling for worker confidence, physically attractive workers have oral skills (such as
communication and social skills) that raise their wages when they interact with employers”
(p.222). Overall, these studies show that beauty is valued economically through different
mechanisms. Some of these mechanisms are based on productivity, and others are based on
perceptions, whether right or wrong.
There are more recent studies that examine whether beauty premium disappears under
different conditions and whether beauty premium emerges in non-economic situations. For
example, Kanazawa and Still (2018) shows that once the physiological traits like Big Five
personality factors are added into the analysis, the beauty premium decreases significantly. In
addition, the beauty premium is not linear as there can be differences in the earnings of very
unattractive or average unattractive groups of people. As a study in non-economic context,
King and Leigh (2009) examine whether beauty has any role in political decisions and voting
behaviour in Australia. As voting is compulsory in this country, there would be small
selection biases, thereby increasing the robustness of findings. The results indicate beautiful
candidates get higher voter shares, even after controlling for party effects, age, the exclusion
of well-known candidates, using Australian versus non-Australian beauty raters, and omitting
non-Anglo-Saxon candidates. Similar findings are obtained by Berggren et al. (2010) in the
case of Finland. These authors show that “An increase in our measure of beauty by one
standard deviation is associated with an increase of 20% in the number of votes for the
average non-incumbent parliamentary candidate. The relationship is unaffected by including
education and occupation as control variables and withstands several other robustness
checks” (p.8). As another interesting study, Price (2008) finds that blonde females raise more
funds than brunette females for charities after controlling other factors. Similarly, in the
micro-finance lending business, more attractive, lighter-skinned, and less obese borrowers
have higher chances of obtaining funds (Jenq et al., 2015). In an interdisciplinary study,
Maestripieri et al. (2017) aim to explain financial and prosocial biases towards attractive
people. These authors argue that evolutionary mechanisms are also important to understand
the beauty biases and conclude that “multiple lines of evidence suggest that mating motives
play a more important role in driving financial and prosocial biases toward attractive adults
than previously recognized” (p.1).
Overall, the academic literature on the value of beauty finds that there are various economic,
political, and social biases in favour of more attractive people. Given this finding, it is natural
that people would spend significant time and resources on their beauty and looks. So, these
academic studies become important to understand the underlying forces in the beauty sector.
In addition, they imply that people would be investing more in beauty products and services
as the market economy gains more weight in their daily lives.
2.2. Economic Characteristics of the Beauty Sector
When the long-term trends in consumer spending in the UK are examined, it is found that
spending on beauty and personal has been among the most rising categories. Harari (2016)
estimates that between 1985 and 2015, the volume of spending on beauty and personal care
increased three times. This finding implies that as household income increases, the demand
for beauty products and services increase at a faster pace. In other words, the income
elasticity of demand in the beauty and personal care sector is larger than unity. Regarding the
purchasing behaviour of UK consumers, a report by Deloitte (2019) finds that 76% of
consumers buy beauty and personal care products in-store, whereas only 24% use online
channels. This finding is in large contrast to the case in many sectors like sports equipment,
household appliances, electrical equipment, events, holidays, and digital services that more
than 50% of consumers use digital channels in their purchases. Still, Mintel (2019) estimates
that the online beauty market in the UK reached around £1.5 billion in 2019, growing more
than 10% on annual terms. The report expects that this beauty segment will continue to
display strong growth in the coming years.
The changing composition of the population also makes some important effects on the beauty
sector. For example, a report by Grand View Research (2018) notes that as the millennial
group ages, the younger generation places growing importance on personal care products and
services. One such effect comes from the rise of social media platforms and activities. Young
people are more active on social media, and they care greatly about their appearance on social
media. As they are on social media more frequently than they go out, this trend affects their
beauty product and service purchase behaviours. Specifically, Grand View Research (2018)
notes that “The young generation tends to spend a high amount on the skincare, colour
cosmetics, and other personal care products for ensuring their appearance matching with their
social media presence”. In this context, social media and e-commerce provide new
opportunities for the beauty and personal care brands. Rajput (2016) argues that another
important trend in the beauty sector is the rise of cosmetics products. The author estimates the
global cosmetics market to reach $430 billion by 2022. Changing lifestyles is an important
factor in the strong rise of the cosmetics sector. People started using cosmetics products more
extensively to support their styles and personality as it is used to improve inherent beauty,
personal attractiveness, and physical features.
There are also reports that examine the size and composition of the beauty market in the UK.
For example, Whitehouse (2018) estimates that the UK is the sixth-largest market globally in
terms of beauty and personal care market size. In terms of the per-capita spending on beauty
and personal care, the relevant figure is $155 in the UK for 2017, making it the fifth-highest

level globally. Beauty products and personal care products have each a share of 20% in the
market, followed by 30% share of Spa, Salon, and in-store treatment services, and another
30% share of hairdressing and barbershop services. This report also mentions an interesting
finding on the effects of Brexit for the beauty sector. Specifically, Whitehouse (2018) states
that “Following the Brexit vote, sales of beauty and personal care products continued to rise.
CEW suggests this offers further evidence of ‘The Lipstick Effect’ during periods of
economic downturn, consumers tend to purchase more ‘little luxuries’, such as lipstick,
treatments and cosmetics”. This point is in line with the view that beauty products are like
luxury goods with an elasticity of income higher than unity.
Oxford Economics (2019) conducts one of the most detailed analyses on the UK beauty and
personal care sector. The report categorises the sector into three groups of personal care and
maintenance (including dental care, hair, personal care and hygiene, skin and body care, sun
care, hair removal, and nail care), personal enhancement (cosmetics, nail colour, accessories
and applications, hair enhancements, and personal fragrance and perfumes), and services
(holistic treatments, beauty treatments, and hair services). In terms of consumer spending, the
first category has a market size of £10.4 billion, followed by £8.8 billion in the second
category and £8 billion in the third category. Figure 1 shows the detailed distribution of these
expenditures. It is seen that hair services are the largest spending category by far, followed by
cosmetics and personal care and hygiene. The same ordering is followed when the categories
are ranked in terms of direct employment.
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3. Methodology and Data
3.1. Research Methodology

This research follows a positivist research philosophy and deductive research approach
(Saunders et al., 2016; Bell et al., 2019). In contrast to other alternatives like the interpretivist
research philosophy, positivism assumes that there are some theories and facts that the
research process can be based on. In other words, the researchers can choose the existing
theories and evidence as their starting point and then examine their own data within this
context. In the case o the current research, the quantitative analysis is based on the consumer
theories from economics that explain how demand for certain products would be determined
(Varian, 2014; Baumol and Blinder, 2015). This theoretical approach provides a conceptual
framework to connect the prices and sales of personal care items to the general prices and
output in the economy. This theory is also useful to search for the determinants of the beauty
industry like income, unemployment rate, population, and consumer confidence. Therefore,
the positivist research philosophy is the feasible and appropriate choice for the current
research. Similarly, the deductive inference also follows a top-down approach and starts with
some given research hypotheses. Then, it tests the relevance of these hypotheses with the new
data. In the case of the current research, there are some given hypotheses like the income
elasticity of beauty products being larger than one. So, the deductive inference becomes the
appropriate research approach in the current study. In terms of specific research strategies,
this study focuses on the quantitative analysis of the macroeconomic data on the beauty and
personal care sector. The relevant quantitative methods include summary statistics, cross-
correlation coefficients, and regression techniques.
3.2. Data
The main variables that are used in the secondary data analysis are the price and output levels
of the personal care sector in the UK, along with the overall price and GDP levels. In
addition, other variables like population, unemployment rate, and consumer confidence index
are used as control variables in the quantitative analysis. The data are collected from public
resources like the ONS (2020) and Investing (2020). The sample covers the years of 1988-
2019 in the case of prices and the years of 1985-2019 in the case of output levels, as the ONS
provides price information for the personal care sector starting in 1988 and sales information
starting in 1985. The data is used at an annual frequency so that the sample size becomes 31
or 34 observations. Figure 1 provides the comparison of price levels for personal care
expenditures and the overall consumer expenditures (i.e., CPI). To make the comparison
easier, both indices have a starting value of 100 in 1988. It is seen from the graph that in the

1990s the price index for the personal care products and services was above the general price
index in the 1990s; however, it stabilized in the early 2000s, and both indices started to move
together in the 2000s. Then, both indices diverged again in the 2010s, with CPI continuing to
increase, whereas the price index for personal care following a stable course. Figure 2 shows
the inflation rates for both indices in the same period. It is seen that the growth rate of the
price index for personal care products and services display higher volatility. In addition, the
inflation rate for personal products stayed consistently below the general inflation level in the
last two decades.
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Figures 4 and 5 present a similar analysis with the output levels in the personal care sectoral
and overall GDP in the UK. This time the sample starts in 1985 due to the availability by the
ONS. To make comparison easier, both series were equalized to 100 in 1985. It is seen that
between 1985 and 1995, both personal care and GDP levels displayed very similar dynamics.
However, starting in 1995, personal care witnessed stronger growth than the overall GDP. In
the process, the discrepancy between personal care and GDP levels declined during economic

downturns like the global financial crisis. But, the divergence continued in the long-run.
Compared to the initial values of 100 in 1985, the GDP level reached 517 in 2018, whereas
the personal care industry reached 712. This finding is consistent with the above discussions
that the personal care sector has an income elasticity of demand higher than unity.
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Figure 5 confirms these findings. It is seen that the output growth level for the personal care
sector has been mostly above the GDP growth level since 1995. However, growth rates of the
personal care sector are very volatile, and during crisis years, they are much lower than the
GDP growth. For example, in the Brexit vote year of 2016, the growth rate for nominal GDP
was around 4%, whereas the growth rate for the personal care sector was 0.3%. Overall, the
personal sector grows faster than the overall GDP, but it is more volatile and sensitive to
economic downturns.
4. Data Analysis and Findings

This chapter presents the data analysis of the macroeconomic variables on the personal care
sector and the relevant findings. The results are presented in two parts. The first part gives the
descriptive statistics of the data, and then, the second part presents the time-series OLS
regression results.
4.1. Descriptive Statistics
As the collected variables are not in the same units, the first step of the analysis is to convert
them to comparable statistics. For example, the unemployment rate is a percentage variable,
while GDP level is an index variable. Therefore, all the index variables (such as output and
price indices for personal care and GDP) are converted to annual growth rates. Similarly, the
population variable is used in terms of its yearly growth. Then, other variables of the
unemployment rate and consumer confidence index are used in their original forms. All
analyses are conducted using the professional econometrics program of STATA 15.1. Table 1
shows the summary statistics of the variables used in the analysis.
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It is seen from Table 1 that the average annual growth of the personal care sector in the UK
for the period of 1986-2019 was 6.22%. Compared to the average GDP growth rate of 5.09%
in this period, the growth of the personal care sector can be considered as being quite strong.
At this point, it should be noted that these numbers are based on nominal output levels. In
addition to the stronger growth of the personal care sector, it also displays much higher
volatility. Namely, the standard deviation of personal care growth is 4.24%, whereas the

standard deviation of the GDP growth is 2.66%. So, the personal care sector follows a much
more volatile pattern. This finding also confirms the results of Figures 4 and 5. When the
price changes are compared, a different picture emerges. Table 1 shows that the average
annual inflation for personal care goods and services was 2.21% in the 1989-2019 period. In
the same period, the average annual CPI inflation was higher, with a value of 2.64%.
However, the volatility of inflation for personal care goods was still higher than the volatility
in consumer inflation. Table 1 also shows the summary statistics of control variables. It is
seen that the average population growth was 0.49% in this period, while the average
unemployment rate was 6.88%.
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After presenting the summary statistics of the relevant macroeconomic variables, the next set
of results involve the pairwise cross-correlations of these variables. The relevant results are
presented in Table 2. It is seen that personal care growth has the highest positive correlation
with GDP growth, followed by the consumer confidence index. So, the income of consumers
and their confidence in the economy stand out as the most important factors for the personal
care sector. The pairwise cross-correlation coefficients of personal care growth with its own
inflation, CPI inflation and unemployment rate are relatively small, indicating that they do
not have a close association with the personal care sector. However, interestingly the personal
care sector growth has a strong negative correlation with population growth. This point seems
puzzling as higher population would be associated with higher demand.

Overall, Table 2 shows that income and consumer confidence are very important factors for
the personal care sector. To see these relationships in a close manner using graphs, Figures 6
and 7 present two scatter plots. The first scatter plot in Figure 6 is between the growth of the
personal care sector and the GDP growth. It is seen that there is a quite strong and positive
relationship between income and personal care sales/expenditures. Similarly, Figure 2 shows
the scatter plot between personal care growth and the consumer confidence index. Again, the
graph shows a very strong and positive associated between these two variables.
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8#
Overall, the descriptive statistics of the relevant macroeconomic variables provide important
insights into the dynamics and determinants of the personal care sector in the UK. Namely,
the results indicate that the personal care sector displayed a stronger growth compared to the
overall GDP in the economy. However, it had higher volatility than GDP. In addition, GDP
growth and consumer confidence seem to be the most relevant factors that are positively
associated with the growth in the personal care sector. These results are in line with the
expectations that as the incomes of households rise, they would increase the purchase of
beauty and personal care products and services. Similarly, if consumers have a high trust and

confidence in the economy, this confidence also supports their purchases of personal care
goods. The next empirical sub-section tries to see whether these relationships hold within a
multivariate factor analysis with the inclusion of other control variables.
4.2. Regression Analysis
This sub-section presents the results of the regression analysis. The pairwise cross-
correlations provide some insightful findings. However, as they only consider the bi-variate
relationship and do not control for the possible effects of other variables, they do not provide
very robust findings. Therefore, providing a multivariate analysis would produce more robust
results. Given the form of available data, conducting a time series regression estimation
becomes feasible. The OLS method is used in the estimation of the regression equation, and
the robust standard errors are utilized to control for heterogeneity. In addition, to control for
the possible role of Brexit vote in 2016, a dummy variable for this event is added to the
regression equation. Table 3 presents the results of the relevant OLS regression.
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_cons 9.383773 4.285014 2.19 0.037 .6063199 18.16123
dummy_Brexit -4.912587 1.621665 -3.03 0.005 -8.234418 -1.590756
consumer_confidence .1431204 .0536141 2.67 0.013 .0332969 .2529439
unemployment -.1396505 .3503975 -0.40 0.693 -.8574071 .5781062
pop_growth -5.47253 4.134533 -1.32 0.196 -13.94174 2.996677
gdp_growth .3861987 .2042074 1.89 0.069 -.0321012 .8044987
personal_care_gro~h Coef. Std. Err. t P>|t| [95% Conf. Interval]
Robust
Root MSE = 3.2485
R-squared = 0.5030
Prob > F = .
F(4, 28) = .
Linear regression Number of obs = 34
The results of the regression also confirm the previous findings. Namely, GDP growth is a
positive and statistically significant determinant of growth in the personal care sector. The
population growth has a negative regression coefficient, as in the negative correlation in
Table 2. However, the regression coefficient is not statistically significant. So, this result
implies that that negative correlation of growth in the personal care sector and the population
growth is not a robust puzzle to be concerned with. Unemployment has a negative effect,

which is an expected result. However, the coefficient is not again statistically significant.
Lastly, consumer confidence has a positive and statistically significant coefficient. The Brexit
dummy is negative and statistically significant, implying that the Brexit vote created very
adverse effects on personal care expenditures. Overall, these results produce robust findings
on the positive effects of income and consumer confidence on the beauty and personal care
sector in the UK.
5. Results
This study examines the resilient economics of the beauty industry in the UK. The beauty and
personal care sector has grown more than three times in the last three decades. The academic
studies show that there is a significant economic value of beauty in various situations. For
example, it is widely displayed that physically attractive people earn a premium in the labour
markets. Similar positive biases in favour of beauty can arise in the social and political
settings as well, like the political elections and business decisions. Given the economic value
of beauty, the beauty and personal care sector has been growing very strongly in many
countries, including the UK. There are some new trends like the rise of social media that
support the growth of the beauty industry. In addition, the relevant literature suggests that
expenditures on beauty and personal care products and services are like luxury goods, and the
household income is a leading determinant. The current research collects data on the UK
beauty and personal care market and conducts a detailed empirical analysis. The results
indicate that the growth of the personal care sector is larger than the growth in overall GDP in
the UK. The beauty sector is also more volatile. In addition, the GDP growth and consumer
confidence index are found to be the leading determinants for the sector. Other variables like
population growth and the unemployment rate do not have statistically significant effects. In
addition, the Brexit vote in 2016 produced very negative, but short-lived, effects on the
sector. Overall, the results imply that as long as consumer income continues to grow, and
consumers have confidence in the economy, the beauty industry will display strong growth in
the future.

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
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