1. THE STUDY OF
TOURISM DEMANDS FOR
MALAYSIAN VISITING THAILAND
INSTRUCTOR
DR. CHRISTINE LIM, PHD
STUDENTS
ZACK FONG MB74684
KIKI HO MB74669
KIKI NG MB84662
DATE
11T H JULY 2019
FACULTY OF BUSINESS & A DMINISTRATION
DEPA RTMENT OF INTEGRATED RESORT
& TOURISM MA NAGEMENT
IIRMM7 0 3 7 TOURISM & TRAVEL MA NAGEMENT
SPRING 2 0 1 9
4. Malaysia – Stats & Facts
13 States; 3 federal territories
31 million population (2018)
Land size is 300 times bigger than HK;
11000 times of Macau
3 major ethnics
Nominal GDP (2018) USD 346.8b
Nominal GDP Per Capita (2018) USD 11338
https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=266&bul_id=SW5lOVJadmV1ckdQa0
9RVUlHbDFjQT09&menu_id=TE5CRUZCblh4ZTZMODZIbmk2aWRRQT09
5. Malaysia – Stats & Facts
Chart: Malaysia GDP (MYR) (2010-2018)
https://insights-ceicdata-com.libezproxy.umac.mo/Untitled-insight/views
6. Malaysia – Stats & Facts
https://tradingeconomics.com/malaysia/gdp-from-services
https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=266&bul_id=SW5lOVJadmV1ckdQa09RVU
lHbDFjQT09&menu_id=TE5CRUZCblh4ZTZMODZIbmk2aWRRQT09
Chart Left: Malaysia GDP (2017) Composition Breakdown;
Chart Right: Malaysia GDP from Service Sector (MYR million) 2010-2019
7. Malaysian Best Pick of Destination
Chart Left: Most Travelled & Most Favourited Tourism Destination Picked by
Malaysian Students in University of Macau
Chart Right: Top Tourism Destination in APAC by UNWTO 2017
8. Thailand – Stats & Facts
68 million population (2018)
Land size is 600 times bigger than HK;
22000 times of Macau
2 major ethnics (Thai & Chinese)
4 Sub-Thai Ethnics
Nominal GDP (2018) USD 504.9b
Nominal GDP (2018)Per Capita USD 7238
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=TH. Retrieved 2 July 2019.
World Population Prospects: The 2017 Revision". ESA.UN.org (custom data acquired via website). United
Nations Department of Economic and Social Affairs, Population Division. Retrieved 10 September 2017.
9. Thailand – Stats & Facts
Chart Left: Thailand GDP by Sector Composition (2017)
Chart Right: Tourists Arriving Thailand by Nationalities (2017)
http://emerging-markets-research.hktdc.com/business-news/article/Asia/Thailand-Market-
Profile/mp/en/1/1X000000/1X003IMW.htm
Source: IMF, World Bank
http://www.thaiwebsites.com/tourists-nationalities-Thailand.asp
https://theodora.com/wfbcurrent/thailand/thailand_economy.html
10. Comparison
Malaysia (Origin) Attributes Thailand (Destination)
31m Population 68m
330,803 km2 Land Size 513,120 km2
346.8b Nominal GDP 2018 (USD) 504.9b
11338 Nominal GDP Per Capita 2018 (USD) 7238
60% Service
23% Manufacture
10% Agriculture
GDP by Composition (2017)
56% Service
35% Manufacture
9% Agriculture
12. Data Sourcing
Secondary Sourcing through CEIC:
• Tourism Arrivals
• CPI of destination & origin country
• GDP of destination & origin country
• Population
• Inflation Rate
• Demography
• Exchange Rates
13. Defining Variables
Tourism Demand
• Tourists Arrivals (TA)
Income
• Real GDP
Tourism Prices
• Exchange Rate (ER)
• CPI Ratio (CPI)
• Real Exchange Rate (RER)
14. Tourist Arrivals
Extraction of data through CEIC by sourcing Visitor Arrivals from Malaysia and rescaling monthly data to quarterly data.
16. Tourism Prices
• Extracting Exchange Rate (ER) from CEIC
• Extracting & Calculating CPI Ratio
• Calculating Real Exchange Rate by using
formula 𝑅𝐸𝑅 =
𝐶𝑃𝐼(𝑇ℎ𝑎𝑖𝑙𝑎𝑛𝑑)
𝐶𝑃𝐼(𝑀𝑎𝑙𝑎𝑦𝑠𝑖𝑎)
1
𝐸𝑅
20. Trend Analysis 173 thousands of constant visitors and
10 thousands increment visitors per quarter.
ො𝑦𝑡 = 173715.5 + 10010.27𝑡
Monthly Model Quarterly Model
Both models tested significant at 5%
confidence (t > ± 1.96); good fit of models at
R-sq > 78%
21. Regression Analysis – Income Elasticity
Exchange Rate Model CPI Ratio Model Real Exchange Rate Model
All 3 models tested significant
at 5% confidence (t > ± 1.96) .
Only CPIR Model is income-
elastic; the others are inelastic .
22. Regression Analysis – Tourism Prices
Exchange Rate Model CPI Ratio Model Real Exchange Rate Model
All 3 models tested significant
at 5% confidence (t > ± 1.96) .
Only RER Model is reported
positively correlated with TA, the
others are negatively correlated.
23. Regression Analysis – Dummy Variables
Exchange Rate Model CPI Ratio Model Real Exchange Rate Model
All D2003 models tested significant (t > ± 1.96) ;
all D2014 models are insignificant (t < ±1.96)
All models has negative correlation with TA
24. Regression Analysis – Model Fit
Exchange Rate Model CPI Ratio Model Real Exchange Rate Model
All models are good fit ( R-sq > 83%); CPIR Model having highest fit (89%)
25. Regression Analysis – Drawing Conclusion
Exchange Rate Model CPI Ratio Model Real Exchange Rate Model
• Income-elastic
• Tourism Price negatively
correlated
• Event brings significant
impact
• Very Good Fit of Model
26. Discussion &
Conclusion
1. Tourist arrivals dependent by Malaysian school holidays.
2. Festivals in Thailand may not correlated with TA.
3. The CPI Ratio model is selected best explains tourism
model for Malaysian arriving Thailand with a high fit of 89%
R-sq. The findings as follow:
◦ Tourism Demand is income-elastic as illustrated by RealGDP’s
correlation with TA.
◦ Tourism Demand is negatively correlated with Tourism Price, as
indicated by CPI Ratio correlation with TA.
◦ The 2003 SARS event has significant impact on TA.
28. Closing Remark
& Limitation
•Different fundamental knowledge in Travel & Tourism
•Different of experience and skills in data analysis, computing
using E-Views and statistical analysis
•Various of resources to be screened
•Limited understanding at researched location.
29. Reference
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https://www.ceicdata.com/en
CEIC, Foreign Exchange Rate: BOT: Simple Avg: Mid: Malaysia Ringgit, extracted on June 23rd, 2019. Retrieved from
https://www.ceicdata.com/en
CEIC, Foreign Exchange Rate: BOT: Simple Avg: Mid: Malaysia Ringgit, extracted on June 23rd, 2019. Retrieved from
https://www.ceicdata.com/en
CEIC, Forex: Thai Baht to Malaysia Riggit: Mid, extracted on June 23rd, 2019. Retrieved from https://www.ceicdata.com/en
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CEIC, Nominal GDP: USD mn: Thailand, extracted on June 23rd, 2019. Retrieved from https://www.ceicdata.com/en
30. Reference
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32. Reference
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