Transcript File

Report
Tourist visitors to New Zealand
Introduction
• Main ideas
• Reasons for choosing the particular variables
Introduction to the topic
Tourism has been one of New Zealand’s major
forms of income over the past decades. Through
this research, I would like to investigate the
situation of New Zealand’s tourism asset over
the past years and in the near future. This could
be done by looking into the number of overseas
visitors to New Zealand, in which it is
categorized by purposes such as business,
holiday, friends and relatives, and education.
If you say this, you must come back to
it in your report.
Tourism has been one of New Zealand’s major
forms of income over the past decades. Through
this research, I would like to investigate the
situation of New Zealand’s tourism asset over
the past years and in the near future. This could
be done by looking into the number of overseas
visitors to New Zealand, in which it is
categorized by purposes such as business,
holiday, friends and relatives, and education.
Choice of variables
Reading through articles on the Ministry of Business
websites I have come across statements like, “The
most significant aspects of the drop in spending are
a decrease in UK visitors’ spend, and in the total
amount that holiday visitors are spending.” (as cited
in IVS commentary, 2012) From this I realized that
the population of overseas visitors, who came here
for vacations, is a major parameter that influences
New Zealand tourism and economy. Thus I will
investigate holiday as one of my variables.
Relates to
purpose
Choice of variables
Also other research has pointed out that Australian forms
a large proportion of visitors out of Researched
the population of
reason
overseas visitors. “The Australian visitor
market is the
largest source of revenue for the tourism sector. It will
remain the dominant market for the foreseeable future,”
and it has stated that “The mix of visitors will remain
heavily dominated by those on holiday and visiting
friends and relatives.” (as cited in New Zealand’s tourism
sector outlook-Forecasts for 2012-2018) Hence I think
visitors for friends and relatives could be another
indication that shows the long trend growth of NZ
tourism industry.
Choice of variables
Also other research has pointed out that Australian forms
a large proportion of visitors out of the population of
overseas visitors. “The Australian visitor market is the
largest source of revenue for the tourism sector. It will
remain the dominant market for the foreseeable future,”
and it has stated that “The mix of visitors will remain
heavily dominated by those on holiday and visiting
friends and relatives.” (as cited in New Zealand’s tourism
sector outlook-Forecasts for 2012-2018) Hence I think
visitors for friends and relatives could be another
indication that shows the long trend growth of NZ
tourism industry.
Referrence
He has now clearly established that he will
investigate ‘vacation’ and ‘friends and relatives’
with reasons based on research.
Background Research
The data I am investigating comes from Statistics New
Zealand, which extracted the data from New Zealand
Customs Service. The data are overseas visitors only and
“The number of visitors in New Zealand is estimated from
a sample of records, using day of arrival and intended
length of stay. It is calculated for each day within the
selected period and averaged,” where the sample ratio
remains to be “1 in 16.” Hence there could be sampling
variation acting on the data. However, because of the
relatively high sampling ratio and the randomization of
sampling method, we could be confident that this data is
reliable.
Data source
The data I am investigating comes from Statistics New
Zealand, which extracted the data from New Zealand
Customs Service. The data are overseas visitors only and
“The number of visitors in New Zealand is estimated from
a sample of records, using day of arrival and intended
length of stay. It is calculated for each day within the
selected period and averaged,” where the sample ratio
remains to be “1 in 16.” Hence there could be sampling
variation acting on the data. However, because of the
relatively high sampling ratio and the randomization of
sampling method, we could be confident that this data is
reliable.
Comment on sampling used
The data I am investigating comes from Statistics New
Zealand, which extracted the data from New Zealand
Customs Service. The data are overseas visitors only and
“The number of visitors in New Zealand is estimated from
a sample of records, using day of arrival and intended
length of stay. It is calculated for each day within the
selected period and averaged,” where the sample ratio
remains to be “1 in 16.” Hence there could be sampling
variation acting on the data. However, because of the
relatively high sampling ratio and the randomization of
sampling method, we could be confident that this data is
reliable.
Statement of reliability of the data
The data I am investigating comes from Statistics New
Zealand, which extracted the data from New Zealand
Customs Service. The data are overseas visitors only and
“The number of visitors in New Zealand is estimated from
a sample of records, using day of arrival and intended
length of stay. It is calculated for each day within the
selected period and averaged,” where the sample ratio
remains to be “1 in 16.” Hence there could be sampling
variation acting on the data. However, because of the
relatively high sampling ratio and the randomization of
sampling method, we could be confident that this data is
reliable.
Description of the dataset and dates
This series gives us the monthly average number
of visitors in New Zealand by purpose. This
category consists of business, education,
holidays, friends and relatives (visiting) and
conventional/conference. The series we are
dealing with goes from January 2000 to October
2012, a period of just below 13 years.
Influences
This data has captured a period of economic downturn, as
cited in the Ministry of Business “The drop (in total visitor
numbers in 2012) also reflects global economic conditions.”
(IVS Commentary, 2012) Unexpected events like Christchurch
February and June earthquake also influenced the number of
visitors to New Zealand, in which “February 2011 earthquake
in Christchurch contributed to a decrease in visitor numbers in
March 2011,” (International Travel and Migration: March
2012, Statistics New Zealand). On the other hand we also have
man-made events that boosted the growth of visitors to New
Zealand, e.g. the Rugby World Cup 2011 that made “2011 a
relatively good year for international tourism.”(IVS
Commentary, 2012)
Trend
•
•
•
•
•
•
Graph
Comment from left to right
There may be more than one trend
Trend may be non-linear
Look for levelling off
Special features that might disrupt the trend
1.01A
The set of data shows the annual passenger numbers and total distance of all journeys on
Wellington’s bus network.
Comment on features of interest.
There are two long-term trends in the passenger data:
(i) Numbers rose to a
peak in 1944
(ii) After 1944 they
have steadily
decreased
Sigma Mathematics Workbook
© Pearson Education New Zealand
2007
Reason:
Reason:
Increase in
population
Change to car
ownership
1.01A
The set of data shows the annual passenger numbers and total distance of all journeys on
Wellington’s bus network.
Comment on features of interest.
There are two peaks/troughs not typical of the general trends:
(i) A fall-off in use in
the 1930s
(ii) An increase in use
in the early 1940s
Sigma Mathematics Workbook
© Pearson Education New Zealand
2007
Reason:
Reason:
The Depression
Motor vehicle use
discouraged (during
World War II)
1.01A
The set of data shows the annual passenger numbers and total distance of all journeys on
Wellington’s bus network.
Comment on features of interest.
The graph showing the mileage driven per year is remarkably steady.
This indicates that
the bus service
provided similar
routes and/or
timetables
throughout the
period.
There does not seem to be any significant trend to either increase
or decrease in mileage driven.
Sigma Mathematics Workbook
© Pearson Education New Zealand
2007
1.01B
Comment on the following graph which shows the consumer price index for New
Zealand for the period 1980 to 2000.
New Zealand
experienced high
inflation in the
1970s and 1980s.
In 1987 the graph shows an upwards
spike when GST was first introduced,
having a one-off effect on all prices.
In 1983, the Prime
Minister of the day,
Robert Muldoon,
ordered a wage-price
freeze in a futile attempt
to control market forces.
This produced a temporary
downwards spike in the inflation
rate.
Sigma Mathematics Workbook
© Pearson Education New Zealand
2007
There is a second spike in 1989 caused
by raising the GST rate from 10% to
12.5%.
Graph
Add
labels
Overview
The graph shows that the trend for the number
of holiday visitors was increasing from about
35000 in the beginning of 2000 up to about
59000 visitors in the beginning of 2007. This
means there is a rise of approximately 300
holiday travellers every month.
Overview
The graph shows that the trend for the number
of holiday visitors was increasing from about
35000 in the beginning of 2000 up to about
59000 visitors in the beginning of 2007. This
means there is a rise of approximately 300
holiday travellers every month.
Add numbers
The graph shows that the trend for the number
of holiday visitors was increasing from about
35000 in the beginning of 2000 up to about
59000 visitors in the beginning of 2007. This
means there is a rise of approximately 300
holiday travellers every month.
Add gradient
The graph shows that the trend for the number
of holiday visitors was increasing from about
35000 in the beginning of 2000 up to about
59000 visitors in the beginning of 2007. This
means there is a rise of approximately 300
holiday travellers every month.
Special features
•
•
•
•
Statement
Justification
Research
Opinion
Statement
During this period, we noticed a sharp increase
in the year 2000, this could be caused by
multiple international events happening around
that time, “Visitors to several international
events - America’s Cup, APEC summit, World
Netball Championship, Under-17 Soccer World
Cup - contributed to this large increase” (as
cited in External Migration January 2000)
Justification
During this period, we noticed a sharp increase
in the year 2000, this could be caused by
multiple international events happening around
that time, “Visitors to several international
events - America’s Cup, APEC summit, World
Netball Championship, Under-17 Soccer World
Cup - contributed to this large increase” (as
cited in External Migration January 2000)
Research
During this period, we noticed a sharp increase
in the year 2000, this could be caused by
multiple international events happening around
that time, “Visitors to several international
events - America’s Cup, APEC summit, World
Netball Championship, Under-17 Soccer World
Cup - contributed to this large increase” (as
cited in External Migration January 2000)
Reference
During this period, we noticed a sharp increase
in the year 2000, this could be caused by
multiple international events happening around
that time, “Visitors to several international
events - America’s Cup, APEC summit, World
Netball Championship, Under-17 Soccer World
Cup - contributed to this large increase” (as
cited in External Migration January 2000)
Statement
The prominent increase in the end of 2003 could be
partly contributed to the success of “The Lord of
the Rings” trilogy which is completed in December
2003. This is reflected by the research “The
International Visitor Survey from 2004 found that
six percent of visitors to New Zealand (around
120,000 - 150,000 people) cite The Lord of the
Rings as being one of the main reasons for visiting
New Zealand.” (as cited in Marketing destination
New Zealand through the Hobbit trilogy, 2012)
Justification and research
The prominent increase in the end of 2003 could be
partly contributed to the success of “The Lord of
the Rings” trilogy which is completed in December
2003. This is reflected by the research “The
International Visitor Survey from 2004 found that
six percent of visitors to New Zealand (around
120,000 - 150,000 people) cite The Lord of the
Rings as being one of the main reasons for visiting
New Zealand.” (as cited in Marketing destination
New Zealand through the Hobbit trilogy, 2012)
Reference
The prominent increase in the end of 2003 could be
partly contributed to the success of “The Lord of
the Rings” trilogy which is completed in December
2003. This is reflected by the research “The
International Visitor Survey from 2004 found that
six percent of visitors to New Zealand (around
120,000 - 150,000 people) cite The Lord of the
Rings as being one of the main reasons for visiting
New Zealand.” (as cited in Marketing destination
New Zealand through the Hobbit trilogy, 2012)
Statement
However, from the start of 2007 to the end of 2011, the trend remains
to be relatively stable with a very slight decrease over time. This
change in trend could be explained by the global economical recession
starting from roughly 2008, “The global economy slowed sharply in
2008 and 2009, which led to a deep recession in the US and dampened
economic growth in Europe and Asia,” and “Directly, it will affect visitor
numbers and spending from Europe. Indirectly, it could dent global
growth and visitor number and spending from other parts of the
world.” (as cited in Forecast commentary, 2012) This statement is
justified by the decrease in trend from about 58000 to 55000 holiday
visitors, starting from the mid 2008 to the beginning of 2009. The
change is understandable as people will first cut their budget in
recreational activities like holiday travel.
Justification
However, from the start of 2007 to the end of 2011, the trend remains
to be relatively stable with a very slight decrease over time. This
change in trend could be explained by the global economical recession
starting from roughly 2008, “The global economy slowed sharply in
2008 and 2009, which led to a deep recession in the US and dampened
economic growth in Europe and Asia,” and “Directly, it will affect visitor
numbers and spending from Europe. Indirectly, it could dent global
growth and visitor number and spending from other parts of the
world.” (as cited in Forecast commentary, 2012) This statement is
justified by the decrease in trend from about 58000 to 55000 holiday
visitors, starting from the mid 2008 to the beginning of 2009. The
change is understandable as people will first cut their budget in
recreational activities like holiday travel.
Research and reference
However, from the start of 2007 to the end of 2011, the trend remains
to be relatively stable with a very slight decrease over time. This
change in trend could be explained by the global economical recession
starting from roughly 2008, “The global economy slowed sharply in
2008 and 2009, which led to a deep recession in the US and dampened
economic growth in Europe and Asia,” and “Directly, it will affect visitor
numbers and spending from Europe. Indirectly, it could dent global
growth and visitor number and spending from other parts of the
world.” (as cited in Forecast commentary, 2012) This statement is
justified by the decrease in trend from about 58000 to 55000 holiday
visitors, starting from the mid 2008 to the beginning of 2009. The
change is understandable as people will first cut their budget in
recreational activities like holiday travel.
Opinion or own input
However, from the start of 2007 to the end of 2011, the trend remains
to be relatively stable with a very slight decrease over time. This
change in trend could be explained by the global economical recession
starting from roughly 2008, “The global economy slowed sharply in
2008 and 2009, which led to a deep recession in the US and dampened
economic growth in Europe and Asia,” and “Directly, it will affect visitor
numbers and spending from Europe. Indirectly, it could dent global
growth and visitor number and spending from other parts of the
world.” (as cited in Forecast commentary, 2012)
This statement is justified by the decrease in trend from about 58000
to 55000 holiday visitors, starting from the mid 2008 to the beginning
of 2009. The change is understandable as people will first cut their
budget in recreational activities like holiday travel.
Statement
At the beginning of 2012, especially in February, there was a
sudden decrease in holiday visitors to New Zealand. This could
be due to a number of reasons, such as the moving holiday
effect of Chinese New Year, “There were fewer arrivals from
Hong Kong and China because the popular Chinese New Year
travel period fell in January in 2012 compared with February
in 2011.” (as cited in International Travel and Migration:
February 2012) In addition, the drop in trend could be
partially contributed to the decrease in Japanese traveller due
to unexpected tsunami and earthquake in 2011, “Visits from
Japan were further affected after that country experienced its
own devastating earthquake and tsunami in March 2011.” (as
quoted in International Travel and Migration: February 2012)
Justification
At the beginning of 2012, especially in February, there was a
sudden decrease in holiday visitors to New Zealand. This could
be due to a number of reasons, such as the moving holiday
effect of Chinese New Year, “There were fewer arrivals from
Hong Kong and China because the popular Chinese New Year
travel period fell in January in 2012 compared with February
in 2011.” (as cited in International Travel and Migration:
February 2012) In addition, the drop in trend could be
partially contributed to the decrease in Japanese traveller due
to unexpected tsunami and earthquake in 2011, “Visits from
Japan were further affected after that country experienced its
own devastating earthquake and tsunami in March 2011.” (as
quoted in International Travel and Migration: February 2012)
Research and reference
At the beginning of 2012, especially in February, there was a
sudden decrease in holiday visitors to New Zealand. This could
be due to a number of reasons, such as the moving holiday
effect of Chinese New Year, “There were fewer arrivals from
Hong Kong and China because the popular Chinese New Year
travel period fell in January in 2012 compared with February
in 2011.” (as cited in International Travel and Migration:
February 2012) In addition, the drop in trend could be
partially contributed to the decrease in Japanese traveller due
to unexpected tsunami and earthquake in 2011, “Visits from
Japan were further affected after that country experienced its
own devastating earthquake and tsunami in March 2011.” (as
quoted in International Travel and Migration: February 2012)
Second reason
At the beginning of 2012, especially in February, there was a
sudden decrease in holiday visitors to New Zealand. This could
be due to a number of reasons, such as the moving holiday
effect of Chinese New Year, “There were fewer arrivals from
Hong Kong and China because the popular Chinese New Year
travel period fell in January in 2012 compared with February
in 2011.” (as cited in International Travel and Migration:
February 2012) In addition, the drop in trend could be
partially contributed to the decrease in Japanese traveller due
to unexpected tsunami and earthquake in 2011, “Visits from
Japan were further affected after that country experienced its
own devastating earthquake and tsunami in March 2011.” (as
quoted in International Travel and Migration: February 2012)
Seasonality
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•
•
•
•
•
•
Introductory sentence
Graph
Pattern
Highs and lows
Absolute high or low
Other features
Consistency
Hardware shop sales
350
300
Sales per day ($000)
250
200
150
100
50
0
Mon Tues Wed Thur Fri
1
Sat Sun Mon Tues Wed Thur Fri
Sat Sun Mon Tues Wed Thur Fri
2
3
Day and week
Sat Sun Mon Tues Wed Thur Fri
4
Sat Sun
Sales per day ($000)
Hardware shop sales
350
300
250
Identify how long the
pattern is.
200
150
100
50
0
Mon Wed Fri Sun Tues Thur Sat Mon Wed Fri Sun Tues Thur Sat
1
2
3
Day and week
4
What is the period of
time it takes for the
pattern to repeat?
The season is a weekly (7 days) pattern.
Sales per day ($000)
Hardware shop sales
350
Describe the highs and
the lows in each
pattern….
300
250
200
150
100
50
0
Mon Wed Fri Sun Tues Thur Sat Mon Wed Fri Sun Tues Thur Sat
1
2
3
4
Day and week
Highest sales always seem to occur on a Friday, where
sales of between $290 000 and $250 000 have occurred.
The weekly high values have decreased slightly over the
four week period.
Lowest sales of $100 000 or less have occurred on
Saturdays and Sundays. These low values have not
changed over the four week period.
Sales ($000)
350
300
250
200
150
100
50
0
Hardware shop sales
Describe the absolute
high and / or low over the
entire time period.
TuesThur Sat MonWed Fri Sun TuesThur Sat MonWed Fri
1
2
Day and week
3
4
Over these 4 weeks the highest value of sales in one day
was about $290 000, on the Friday of Week 1. The lowest
value of sales was about $75 000 on Sunday, Week 3.
Sales ($000)
350
300
250
200
150
100
50
0
Hardware shop sales
TuesThur Sat MonWed Fri Sun TuesThur Sat MonWed Fri
1
2
Day and week
3
Describe what happens
in between the high and
low points..
4
Each week sales generally increase slowly from Monday
through to Thursday. There is a large jump in sales on
Fridays and a steep decline to Saturday’s sales figures.
Sales per day ($000)
Hardware shop sales
350
300
250
200
150
100
50
0
Describe how consistent is
the seasonal pattern from
one week to the next…
Mon Wed Fri Sun Tues Thur Sat Mon Wed Fri Sun Tues Thur Sat
1
2
3
4
Day and week
The seasonal pattern is very consistent from week
to week
Always, always put
Dates
Values
Context (units)
in your writing
Introduction
There is very clear seasonality in this series.
Graph
Time series graphs
DESCRIBING THE SEASON
Pattern
The season is a monthly (12 month) pattern.
Highs - statement
From the Estimated seasonal effect, it shows
that holiday visitors are considerably higher in
January and February with the peak at 30,000
travellers above the trend. This has important
implication to New Zealand economy and
tourism dependent industries, as that is the
time where they can maximize their profits.
Hence we can see that tourism industry in New
Zealand is a heavily seasonally dependent
market.
Always give the value
From the Estimated seasonal effect, it shows
that holiday visitors are considerably higher in
January and February with the peak at 30,000
travellers above the trend. This has important
implication to New Zealand economy and
tourism dependent industries, as that is the
time where they can maximize their profits.
Hence we can see that tourism industry in New
Zealand is a heavily seasonally dependent
market.
Relates to the investigation
From the Estimated seasonal effect, it shows
that holiday visitors are considerably higher in
January and February with the peak at 30,000
travellers above the trend. This has important
implication to New Zealand economy and
tourism dependent industries, as that is the
time where they can maximize their profits.
Hence we can see that tourism industry in New
Zealand is a heavily seasonally dependent
market.
Justification and research
Holiday visitors in December are about 20,000 above the trend line,
which is not as high as expected, even though that’s the beginning for
Christmas holiday. This is because most overseas visitors would start
their holiday in early January, which is immediately after Christmas,
and it is in that time, the visitors are allowed to travel. Moreover, we
notice that the peak is normally in February: this possibly is due to the
fact that New Zealand is sometimes visited after going to Australia in
January. An increasing population of Chinese holiday visitors to New
Zealand also supports the February peak, as their holiday of Chinese
New Year usually starts between early and mid February. This is
justified by, “Tourism is set to recover from its current slowdown due
to the continuing strength of Australia and a growing Chinese market.”
(as cited in Forecast commentary, 2012)
Lows
The number of visitors troughed in June (about 25000 people
below the trend line) but raised slightly in July. The trough in
June can be caused by the decreasing temperature as New
Zealand goes to winter and the increasing amount of rainfall
which makes holiday to be less favourable. July, however,
seems to favour more visitor numbers than June; one would
expect this because July is when the summer holiday of the
Northern Hemisphere starts. Hence we would see an increase
in holiday visitors from UK and China. This explanation is
supported by Statistics New Zealand, “A holiday was the main
travel reason for 1.156 million visitors to New Zealand in the
July 2009 year,” (as cited in International Travel and Migration:
July 2009)
Justification
The number of visitors troughed in June (about 25000 people
below the trend line) but raised slightly in July. The trough in
June can be caused by the decreasing temperature as New
Zealand goes to winter and the increasing amount of rainfall
which makes holiday to be less favourable. July, however,
seems to favour more visitor numbers than June; one would
expect this because July is when the summer holiday of the
Northern Hemisphere starts. Hence we would see an increase
in holiday visitors from UK and China. This explanation is
supported by Statistics New Zealand, “A holiday was the main
travel reason for 1.156 million visitors to New Zealand in the
July 2009 year,” (as cited in International Travel and Migration:
July 2009)
Feature
The number of visitors troughed in June (about 25000 people
below the trend line) but raised slightly in July. The trough in
June can be caused by the decreasing temperature as New
Zealand goes to winter and the increasing amount of rainfall
which makes holiday to be less favourable. July, however,
seems to favour more visitor numbers than June; one would
expect this because July is when the summer holiday of the
Northern Hemisphere starts. Hence we would see an increase
in holiday visitors from UK and China. This explanation is
supported by Statistics New Zealand, “A holiday was the main
travel reason for 1.156 million visitors to New Zealand in the
July 2009 year,” (as cited in International Travel and Migration:
July 2009)
Feature
Looking at the Seasonal Plot for Holiday, one
could see that seasonality has very less variation
and the number for each month did not increase
significantly over the years. In particular, there is
an outlier in the seasonality for September in
2011, which reaches to about 50,000 instead of
the usual 30,000 visitors. This change is caused
by positive influence brought by the Rugby
World Cup of 2011.
Feature
Looking at the Seasonal Plot for Holiday, one
could see that seasonality has very less variation
and the number for each month did not increase
significantly over the years. In particular, there is
an outlier in the seasonality for September in
2011, which reaches to about 50,000 instead of
the usual 30,000 visitors. This change is caused
by positive influence brought by the Rugby
World Cup of 2011.
Variation and Residuals
•
•
•
•
10% test
Unusual events
Relative contributions
Main source of variation
Decomposition
Compare to 10%
After a visual inspection of the graph, the
residual is relatively small with most of the
variations being below 10% of the overall range
(±4000).
Decomposition
Unusual events
However, at the beginning of 2011, there is a
large residual of about 7500. This unusual
residual was probably caused by the flooding
occurred in Queensland and Victoria in January
2011, where more Australian moved to New
Zealand to avoid the disaster, “Within Australia,
there were more visitors from Queensland (up
2,100) and Victoria (up 1,800),” (as cited in
International Travel and Migration: January
Don’t
2011)
forget the
research
Unusual features
The unusual residual that happened in the
second half of 2011 is mostly likely a result of
Rugby World Cup in Auckland, which reaches a
residual of around 7600.
Relative contribution of components
Often do not
add up to 100%
Decomposition
Raw data
Trend
Decomposition
Raw data
Seasonal
Main source of variation
The main source of variation comes from the
seasonal component that contributes around
76% of the overall variation. About 20% can be
accounted for by the residual, where the trend
accounts for the remaining variation in the
series. The total trend rises about 400 every
year.
Prediction Interval
• Graph
• Table of prediction intervals (rounded)
• Fit of the model (white space)
Graph
Table of prediction intervals
Fit of the model
Confidence in the model
After a visual inspection of the plot I am
confident that the model provides a good fit as
differences (white spaces) between the fitted
data and the raw data are very small. I have
taken out the prediction from November 2013
onwards, because as time passes by the
prediction interval becomes large and more
unreliable.
Prediction Interval
I predict that the average number of holiday
visitors to NZ in August 2013 will be between
17400 and 44600. Hence, in the near future, my
model predicts that there will be a decreasing
trend in 2013.
Second variable
Repeat the process with the second variable
Comparison
Combined
Limitations
The data that I am analyzing does not have the
latest information in 2013. Hence the prediction
I made is based on older data, which will
become inaccurate as the forecast pass 2013.
Furthermore, the data captures a period of
economical downturn at the near end, hence
predictions are generally negative and it will be
inaccurate if New Zealand economy becomes
better in the future.
Conclusion
Relate this to the aim of the
investigation
The aim of the report is to investigate the
situation of New Zealand’s tourism in the past
decade and in the near future. In this way, we
can reflect upon its contribution to New Zealand
economy and the country’s economy itself.
Main features of trend
Looking through the data from past years, the trends of
the data for three of my series all show an increasing
trend before around 2007 to 2008; however as the
economic recession impacts and dampens NZ’s economy,
the trends all show a down turn or a leveling off effect. In
contrast to the holiday visitors, the number of friend and
relative visitors was more resilient and was impacted one
year later than the holiday series. Thus, it reflects familybased activities are harder to be given up by people than
recreational activities at times of economical hardship.
There seems to be a decreasing trend after 2012 and my
forecasts through insight reflect this.
Main features of seasonality
New Zealand’s tourism is a highly seasonal
business, where the peak of the year all happens
around Christmas. The implication is vital for
tourism dependent industry so that they can
achieve maximum profit at that time. However, we
also notice that the trough repetitively occur in
June with a slight rise in July. Thus the length of the
holiday is also a key for New Zealand’s tourism,
since during the trough months there are no major
holidays.
Unusual features
Disruption (residuals) in the seasonality could
also be affected by natural disasters such as the
flooding in Queensland and Victoria of Australia,
which boosted the number of Australian family
visitors to New Zealand in early 2010 and early
2011. Man-made events also created the
unusually high number of visitors in September
2011, that is, the 2011 Rugby World Cup held in
Auckland.
References