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TOURISM REVENUE IN MAJOR TOURISM CLUSTER IN THAILAND: DETERMINANTS AND RESPONSES OF MACROECONOMIC VARIABLES

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 03, March 2019, pp. 1046-1055, Article ID: IJCIET_10_03_102
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=03
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication
Scopus Indexed
TOURISM REVENUE IN MAJOR TOURISM
CLUSTER IN THAILAND: DETERMINANTS
AND RESPONSES OF MACROECONOMIC
VARIABLES
Bundit Chaivichayachat
Department of Economics, Faculty of Economics, Kasetsart University
Bangkok, Thailand
ABSTRACT
In order to promote tourism sector to be a major sector to enhance the economic
growth in Thailand, MOTS set up the tourism clusters which included the province that
located in the same area, the same activity and the same culture. This paper aims to
find the determinants of the visitor’s behaviors and to simulate the response of tourism
revenue, sectoral final demand and sector output in Andaman and Lanna tourism
clusters. The results can be used for policy recommendation to promote tourism in
cluster level. The difference in tourism characters were found. The behavior of tourists
in each tourism cluster are difference. They response to the economic factors with their
own specific character. For sectoral analysis, tourism revenue concentrates on limited
sectors. (1) The specific policy of promoting tourism in each cluster should be
proposed. Moreover, the qualitative policy should be applied. (2) As the tourism
revenue concentrated in limited sectors, the other policy which is target on the
promoting of the others sectors to treat the equality economic expansion together with
the enhancing of sectoral linkage. and (3) In fact, tourism section contributes a slice
share in total output. Then, the promotion on tourism sector alone cannot generate a
significant economic expansion. For sustain economic expansion and development, the
alternative policy should be considered.
Key words: Thai Tourism, Bridge Matrix, Tourism Policy
Cite this Article: Bundit Chaivichayachat, Tourism Revenue in Major Tourism Cluster
in Thailand: Determinants and Responses of Macroeconomic Variables., International
Journal of Civil Engineering and Technology, 10(03), 2019, pp. 1046–1055
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Bundit Chaivichayachat
1. INTRODUCTION
To promote tourism sector to be a major sector to enhance the economic growth in Thailand,
MOTS set up the tourism clusters which included the province that located in the same area,
the same activity and the same culture. There are 8 tourism clusters, named Lanna Culture,
Royal Coast, Active Beach, Andaman, South I-san, Cultural in Central, Khong River and Chao
Phraya River. Among these clusters, Andaman cluster and Lanna cluster are the important
tourism cluster both in term of tourist number and in term of tourism revenues. (Table 1.1 and
Table 1.2) For the behaviors of visitors, Bundit (2018) found that the behavior of visitor in 8
clusters are differences. They responses to the differences set of macroeconomic variables.
Then, the specific policy for each cluster are required. This paper aims to find the determinants
of the visitor’s behaviors and to simulate the response of tourism revenue, sectoral final demand
and sector output in Andaman and Lanna tourism clusters by applied tourism input-output
table. The results can be used for policy recommendation for Andaman and Lanna clusters to
promote tourism in cluster level.
Table 1.1: Visitors in 8 Tourism Clusters
Lanna Culture
Royal Coast
Active Beach
Andaman
South I-san
Cultural in Central
Khong River
Chao Phraya River
Total
Source: Department of Tourism
2010
8,121,709
8,079,227
16,738,835
10,317,185
9,571,493
10,017,504
322,056
4,547,157
69,295,905
2011
9,361,322
9,628,135
18,023,131
14,669,508
10,947,661
8,565,999
5,079,895
4,539,051
77,923,424
2012
11,392,272
11,026,840
19,757,639
17,701,748
11,759,420
10,129,714
5,676,396
5,527,483
89,592,933
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2013
12,019,986
11,696,881
20,711,369
20,255,102
12,944,660
10,461,621
6,601,508
6,082,771
97,205,626
2014
13,836,485
12,374,205
20,437,168
22,957,420
13,328,234
11,105,677
6,816,155
6,371,675
103,399,508
2015
14,848,013
12,940,899
22,126,467
25,699,039
14,518,237
12,070,063
7,820,709
6,783,196
112,669,515
person
2016
15,399,272
13,416,960
27,104,201
26,531,958
15,296,606
12,436,919
8,129,055
7,098,513
121,182,897
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Tourism Revenue in Major Tourism Cluster in Thailand: Determinants and Responses of
Macroeconomic Variables
Table 1.2: Tourism Revenues in 8 Tourism Clusters
Lanna Culture
Royal Coast
Active Beach
Andaman
South I-san
Cultural in Central
Khong River
Chao Phraya River
Total
Source: Department of Tourism
2010
68,962
28,938
167,402
274,036
16,277
17,100
6,892
9,675
565,516
2011
88,994
52,471
166,511
274,588
19,397
14,350
10,725
10,306
607,472
2012
103,210
57,491
227,653
532,753
21,541
22,043
12,458
14,267
963,368
2013
83,771
50,127
151,826
353,464
23,428
18,104
10,408
14,473
676,636
2014
98,837
53,626
151,113
375,031
24,367
19,615
10,971
15,416
716,824
2015
110,674
57,935
186,141
443,267
27,499
21,737
12,898
17,215
840,748
Million Baht
2016
151,146
76,290
393,342
856,550
31,270
29,398
15,205
20,080
1,535,553
2. MODEL AND METHODOLOGY
Demand theory was referred to explain the behavior of visitor in Lanna culture and Andaman
cluster. The tourism revenues function can be set up referred to Kara et al. (2005), Alvarez
(2007), Allen and Yop (2009), Onder et al. (2009), Monebi and Rahim (2010), Song and Wei
(2010), HanafionHarun and Jamaluddin (2011), Ibranim (2011), Skuflic and Stokovic (2011),
Betonio (2013), Altindag (2013), Bentum-Ennin (2014), Deluna and Jeon (2014), Laframboise
et al. (2014) and Moorthy (2014). The tourism revenue for foreign visitors and Thai visitors in
Lanna Culture and Andaman can be defined as following:
RF1 = f (YM, PW, EX, PT, RT, TB, CR, HG,
HS, PS, YO, PO, Q1, Q2, Q4)
(1)
RT1 = f (YT, UT, PT, RT, TB, CR, HG,
HS, PS, PW, EX, YO, PO, Q1, Q2, Q4)
(2)
RF2 = f (YM, PW, EX, PT, RT, TB, CR, HG,
HS, PS, YO, PO, Q1, Q2, Q4)
(3)
RT2 = f (YT, UT, PT, RT, TB, CR, HG,
HS, PS, PW, EX, YO, PO, Q1, Q2, Q4)
(4)
where RF1 and RT1 are foreign and Thai visitor tourism revenue in Lanna Culture, RF2
and RT2 are foreign and Thai visitor tourism revenue in Andaman, YM is per capita income
of foreign tourists (US dollar), PW is world’s consumer price index, EX is nominal exchange
rate (Bath: US dollar), PT is consumer price index in Thailand, RT is market share of retail
trade to GDP (percent), TB is government budget to promote tourism sector (million baht), CR
is crime rate (time), HG is number of hotels and guest houses, HS is number of hospital, PS is
dummy variable represents economic and political instability (= 1 when instability), YO is per
capita income in Thai’s neighbor, PO is consumer price index in Thai’s neighbor, and Q1, Q2
and Q4 are dummy variable for quarter.
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For the sectoral analysis, the regional tourism input-output table for Lanna Culture and
Andaman will be organized for the calculation of bridge matrix, which used for disaggregating
the aggregate tourism revenue and calculate the final demand generated by tourism sector. The
revenues which were induced by foreign visitors will be set in special export column and the
revenues received from Thai’s visitor will be set in consumption column. Then, the matrix can
be constructed as following:
BF'  bf1 bf 2
bf 26 
(5)
BT'  bt1 bt 2
bt 26 
(6)
26
where BF is bridge matrix of foreign tourism revenue, bfi  Efi /  Efi , Efi is foreign
i1
26
visitor’s expenditure on sector i, BT is bridge matrix of Thai tourism revenue, bt i  Et i /  Et i
i1
and Eti is Thai visitor’s expenditure on sector i.
After defining the bridge matrix, the inverse Leontief’s matrix will be arranged to
calculate the output as following
XT  (I  A) 1(BF  RF)  (I  A) 1(BT  RT )
(7)
where XT is vector of output level initiate by tourism revenue, A is technology matrix,
RF is foreign tourism revenue, RT is Thai tourism revenue, (BF  RF) is sectoral final demand
caused by foreign tourism revenue and (BT  RT ) is sectoral final demand caused by Thai
tourism revenue. The methodology process can be summarized in Figure 2.1.
Figure 2.1: Research Methodologies
The quarterly data during 2010-2016 collecting from ministry of tourism and sports
(MOTS), bank of Thailand (BOT) and IMF, will used to estimate the tourism revenue
functions. For sectoral analysis, regional tourism input-output table including 26 sectors for
2015 will be prepared to calculate bridge matrix, sectoral final demand and sectoral output.
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Tourism Revenue in Major Tourism Cluster in Thailand: Determinants and Responses of
Macroeconomic Variables
3. RESULTS
3.1. Estimation
The least squared (LS) technique was applied to estimate the revenue function. The estimations
were developed by General-to-Specific approach to search for the determinants which are
statistical significant. The estimated equations can be summarized in Table 3.1. The results
indicate that all groups of visitors are significantly determined by exchange rate and size of
retail trade sector. For the others economic variables, the estimated equations suggest that the
difference group of foreign tourists will response to the macroeconomic factors in difference
patterns. In Lanna culture, both foreign and Thai visitors are determined by consumer price
index and the number of hotel and guest house. In contrast, these two factors cannot determine
the tourism income in Andaman. Tourism budget for promoting tourism determines only for
Thai visitors both in Lanna and Andaman. Crime rate shows the negative relationship with
foreign tourism revenue in both clusters. Not only have the economic variables, the results also
indicated the seasonal effect on the tourism revenue in all group of tourism in Lanna culture
and Andaman. The behavior of tourism revenue from Thai visitors both in Lanna culture and
Andaman are difference among quarter. For the income by foreign visitor, a positive significant
increase is found in fourth quarter. The results confirm that tourism revenue are responses to
the macroeconomic variables and seasonal in the difference ways.
Table 3.1: Estimated Equation of Tourism Revenue in Lanna and Andaman Cluster
Constant
RF1
17232.24
RT1
549124.20
RF2
RT2
620722.40 4770982.00
t-stat.
4.65
4.66
2.23
4.86
EX
459.15
3208.14
11805.09
34269.42
2.49
4.47
t-stat.
5.21
2.44
PT
-391.92
-2118.90
t-stat.
-2.67
-2.09
YM
30.71
t-stat.
2.90
RT
9679.10
106836.30
211817.90
741782.10
t-stat.
3.86
6.03
2.67
5.10
CR
-0.05
t-stat.
-4.28
HG
0.90
28.59
t-stat.
3.45
4.10
PS
-580.99
-4201.14
-12352.71
t-stat.
2.39
-3.06
-1.98
UT
-0.75
-2.64
261.85
4.53
-17.51
t-stat.
-1.78
TB
17.01
t-stat.
4.59
HS
91.86
191.33
t-stat.
4.31
3.32
YO
-125.20
t-stat.
Q1
147.42
5.40
5.74
-1184.40
-4.44
1189.97
807.69
-5.43
47993.81
t-stat.
4.20
6.33
Q2
-715.20
19845.51
t-stat.
-2.85
Q4
1488.41
8613.32
51137.92
t-stat.
5.50
5.91
7.79
4.58
R-squared
F-statistic
0.937
29.767
0.918
19.073
0.938
30.431
0.795
11.110
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Bundit Chaivichayachat
3.2. Structure of visitor’s Expenditure, Bridge Matrices and Sectoral Final
Demand
Table 3.2 shows the structure of visitor’s expenditure from Tourism Satellite Account (TSA)
2015. Higher than 85 percent of the visitor’s expenditure spends on tourism characteristics
products especially in food and beverage serving services, and accommodation services. The
structures of visitor’s expenditure were employed to set up the bridge matrix for foreign visitors
(BF) and Thai visitors (BT) following equation (5) and (6). The coefficients in two bridge
matrices collected in Table 3.3. By equation (7), the contribution of tourism revenue on sectoral
final demand and sectoral output in Andaman and Lanna cluster in 2014 and 2015 explore in
Table 3.4 and Table 3.5.
3.3. Simulation
This section used to explore the impact of macroeconomic factors on tourism and output in
2015. There are 3 scenarios which imposed including the expansion of retail trade sector, the
instability in economic and political condition, and the increasing in government budget to
promote tourism. For the first scenario, 5 percent increasing in market share of retail trade to
GDP is assumed. The results on sectoral output in Lanna Culture and Andaman show in Table
3.6. The increasing market share of retail trade to GDP generates the increasing in output for
17,295.35 million baht and 1,570.40 million baht by Thai and foreign tourists in Lanna culture.
For Andaman, the output caused by Thai and foreign tourists will increase for 16,734.71
million baht and 33,179.76 million baht in response to the expansion of retail trade. The total
output for Lanna culture and Andaman increase for 18,865.75 million baht and 49,914.47
million baht respectively. The results for the second scenario present in Table 3.7. The negative
condition for the case the political and economic instability is assumed. Then, the output
induced by Thai and foreign tourists in Lanna and Foreign tourists will decline. The output
caused by tourism in Lanna culture and Andaman decreased for 10,307.78 million baht and
8,759.78 million baht. For the third scenario, 10 percent increasing in government budget to
promote tourism policy is applied. In response to this case, output caused by Thai tourists in
Lanna culture and Andaman will add up for 9,481.55 million baht and 79,489.38 million baht.
(Table 3.8)
4. CONCLUSION
The difference in tourism characters were found. The behavior of tourists in each tourism
cluster are difference. They response to the economic factors with their own specific character.
Not only the difference between clusters, the results also emphasis on the difference between
foreign and Thai tourists. For sectoral analysis, tourism revenue concentrates on limited
sectors. (1) The specific policy of promoting tourism in each cluster should be proposed.
Moreover, the qualitative policy should be applied. (2) As the tourism revenue concentrated in
limited sectors, the other policy which is target on the promoting of the other sectors to treat
the equality economic expansion together with the enhancing of sectoral linkage. and (3) In
fact, tourism section contributes a slice share in total output. Then, the promotion on tourism
sector alone cannot generate a significant economic expansion. For sustain economic
expansion and development, the alternative policy should be considered.
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Tourism Revenue in Major Tourism Cluster in Thailand: Determinants and Responses of
Macroeconomic Variables
Table 3.2: Visitor’s Expenditure
Foreign Visitors
2014
2015
Lanna Cluster
A. Consumption products
A.1 Tourism characteristic products
1. Accommodation services for visitors
2. Food and beverage serving services
3. Railway passenger transport services
4. Road passenger transport services
5. Water passenger transport services
6. Air passenger transport services
7. Transport equipment rental services
8. Travel agencies and other reservation services
9. Cultural services
10. Sports and recreational services
11. Country-specific tourism characteristic goods
12. Country-specific tourism characteristic services
A.2 Other consumption products
Total
Andaman Cluster
3,946.00 4,549.00 7,309.15 8,121.83
4,468.81 5,110.21 11,065.79 12,321.11
215.37
228.36
354.75
398.98
347.99
386.84 1,327.52 1,410.96
11.81
11.86
593.95
778.68
422.87
542.37
994.35 1,153.07 3,293.03 3,656.10
1,694.33 1,918.03 2,740.07 3,011.27
1,511.58 1,702.00 3,211.01 3,561.01
1,570.36 1,781.96 3,257.31 3,621.27
1,303.34 1,498.05 2,670.79 2,988.82
2,370.14 2,602.83 5,876.59 6,527.07
19,028.02 21,720.89 41,528.88 46,160.79
Foreign Visitors
2014
2015
A. Consumption products
A.1 Tourism characteristic products
1. Accommodation services for visitors
38,412.45
2. Food and beverage serving services
41,695.21
3. Railway passenger transport services
1.10
4. Road passenger transport services
1,789.38
5. Water passenger transport services
3,696.89
6. Air passenger transport services
3,563.27
7. Transport equipment rental services
8. Travel agencies and other reservation services
17,963.75
9. Cultural services
4,971.72
10. Sports and recreational services
17,218.26
11. Country-specific tourism characteristic goods
10,205.52
12. Country-specific tourism characteristic services 6,625.77
A.2 Other consumption products
19,526.66
Total
165,669.99
Source: Ministry of Tourism and Sports
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Million Baht
Thai Visitors
2014
2015
1052
Million Baht
Thai Visitors
2014
2015
46,816.57 9,033.20 9,806.70
50,650.06 12,013.69 13,172.24
1.18
10.31
1.16
2,758.76 1,255.11 1,547.39
6,246.35
103.30
89.74
4,894.15
886.84
850.65
21,873.44 3,847.53 4,280.21
6,060.79 1,696.24 1,858.11
20,626.79 4,756.77 5,141.12
12,316.12 3,022.60 3,309.42
8,052.79 2,319.29 2,673.55
21,582.92 7,088.23 8,024.66
201,879.91 46,033.11 50,754.94
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Bundit Chaivichayachat
Table 3.3: Bridge Matrices
Lanna Culture
Andaman
2014
Sector
001
002
003
004
005
006
007
008
009
010
011
012
013
014
015
016
017
018
019
020
021
022
023
024
025
026
2015
2014
Domestic Foreign Domestic Foreign
Tourism Tourism Tourism Tourism
Revenue Revenue Revenue Revenue
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.1760
0.2665
0.0085
0.0320
0.0000
0.0102
0.0000
0.0793
0.0660
0.0773
0.0784
0.0643
0.1415
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2074
0.2349
0.0113
0.0183
0.0006
0.0312
0.0000
0.0523
0.0890
0.0794
0.0825
0.0685
0.1246
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.1759
0.2669
0.0086
0.0306
0.0000
0.0117
0.0000
0.0792
0.0652
0.0771
0.0784
0.0647
0.1414
0.0000
0.0000
Sector
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2094
0.2353
0.0105
0.0178
0.0005
0.0358
0.0000
0.0531
0.0883
0.0784
0.0820
0.0690
0.1198
0.0000
0.0000
001
002
003
004
005
006
007
008
009
010
011
012
013
014
015
016
017
018
019
020
021
022
023
024
025
026
2015
Domestic Foreign Domestic Foreign
Tourism Tourism Tourism Tourism
Revenue Revenue Revenue Revenue
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.1962
0.2610
0.0002
0.0273
0.0022
0.0193
0.0000
0.0836
0.0368
0.1033
0.0657
0.0504
0.1540
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2319
0.2517
0.0000
0.0108
0.0223
0.0215
0.0000
0.1084
0.0300
0.1039
0.0616
0.0400
0.1179
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.1932
0.2595
0.0000
0.0305
0.0018
0.0168
0.0000
0.0843
0.0366
0.1013
0.0652
0.0527
0.1581
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.2319
0.2509
0.0000
0.0137
0.0309
0.0242
0.0000
0.1083
0.0300
0.1022
0.0610
0.0399
0.1069
0.0000
0.0000
Table 3.4: Sectoral Final Demand Induced by Tourism Revenues
Lanna Culture
Sector
Billion Baht
Thai Tourism
Revenue
Foreign Tourism
Revenue
Others
Total
Adaman
Sector
Billion Baht
Thai Tourism
Revenue
Foreign Tourism
Revenue
Others
Total
001
0.00
0.00
169,813.31
169,813.31
001
0.00
0.00
107,771.12
107,771.12
002
003
004
0.00
0.00
0.00
0.00
0.00
0.00
299.44
57,612.18
24,979.58
299.44
57,612.18
24,979.58
002
003
004
0.00
0.00
0.00
0.00
0.00
0.00
1,696.14
15,355.75
9,167.59
1,696.14
15,355.75
9,167.59
005
006
0.00
0.00
0.00
0.00
13,518.19
1,607.75
13,518.19
1,607.75
005
006
0.00
0.00
0.00
0.00
7,318.33
1,614.50
7,318.33
1,614.50
007
008
009
0.00
0.00
0.00
0.00
0.00
0.00
28,867.79
18,420.57
29,823.35
28,867.79
18,420.57
29,823.35
007
008
009
0.00
0.00
0.00
0.00
0.00
0.00
10,146.28
3,933.87
8,580.32
10,146.28
3,933.87
8,580.32
010
0.00
0.00
65,523.94
65,523.94
010
0.00
0.00
31,474.28
31,474.28
011
012
013
0.00
7.72
11.69
0.00
4.25
4.79
0.00
66,289.49
35,358.18
0.00
66,301.45
35,374.67
011
012
013
0.00
9.42
12.59
0.00
42.61
46.17
0.00
96,586.48
79,238.90
0.00
96,638.52
79,297.67
014
0.38
0.22
760.84
761.44
014
0.01
0.00
374.62
374.63
015
016
017
1.37
0.00
0.48
0.37
0.01
0.69
12,955.71
376.46
5,246.79
12,957.45
376.48
5,247.96
015
016
017
1.40
0.10
0.87
2.27
4.97
4.23
8,526.10
9,978.10
3,582.77
8,529.77
9,983.16
3,587.87
018
0.00
0.00
165.18
165.18
018
0.00
0.00
190.69
190.69
019
020
3.47
2.88
1.07
1.81
4,441.65
21,460.59
4,446.20
21,465.27
019
020
4.06
1.78
19.92
5.52
23,208.74
8,448.00
23,232.72
8,455.29
021
022
3.39
3.44
1.61
1.68
4,965.37
6,054.32
4,970.37
6,059.43
021
022
4.95
3.17
18.92
11.26
8,213.43
26,617.09
8,237.30
26,631.51
023
024
2.83
6.20
1.40
2.49
0.00
5,833.77
4.23
5,842.46
023
024
2.50
7.56
7.34
20.55
0.00
14,296.98
9.84
14,325.09
025
026
0.00
0.00
0.00
0.00
135,613.98
8,805.97
135,613.98
8,805.97
025
026
0.00
0.00
0.00
0.00
55,186.34
113.87
55,186.34
113.87
Total
43.84
20.37
718,794.41
718,858.63
Total
48.39
183.77
531,620.30
531,852.47
Lanna Culture
Sector
percent
Thai Tourism
Foreign Tourism
Others
Total
Revenue
Revenue
http://www.iaeme.com/IJCIET/index.asp
Adaman
Sector
1053
percent
Thai Tourism
Revenue
Foreign Tourism
Revenue
Others
Total
[email protected]
001
0.00
0.00
100.00
100.00
001
0.00
0.00
100.00
100.00
002
003
0.00
0.00
0.00
0.00
100.00
100.00
100.00
100.00
002
003
0.00
0.00
0.00
0.00
100.00
100.00
100.00
100.00
Tourism Revenue in Major Tourism Cluster in Thailand: Determinants and Responses of
Macroeconomic Variables
Table 3.5 Sectoral Output induced by Tourism Revenues
Lanna Culture
Sector
Thai Tourism Foreign Tourism
Revenue
Revenue
Billion Baht
Adaman
Others
Total
Sector
Billion Baht
Thai Tourism Foreign Tourism
Revenue
Revenue
Others
Total
001
5.56
2.43
261,237.16
261,245.15
001
6.42
24.46
178,968.35
178,999.22
002
003
004
005
006
3.28
7.15
0.39
15.44
67,896.44
117,031.94
67,901.28
117,042.19
23.48
22.51
48,010.61
291,154.39
48,011.20
291,176.87
81,296.48
63,347.52
30,963.48
129,072.58
81,326.33
63,375.95
30,970.74
129,120.47
5,160.97
5,161.09
002
003
004
005
006
6.37
5.92
1.46
10.28
0.08
1.57
3.10
0.20
7.04
0.04
0.08
0.26
2,929.22
2,929.56
007
008
009
010
7.85
0.54
5.81
0.13
3.82
0.26
2.83
0.06
313,503.87
313,515.54
10.79
41.64
189,417.20
189,469.63
37,996.79
99,252.35
66,549.09
37,997.60
99,260.98
66,549.28
007
008
009
010
0.65
5.27
0.43
2.57
19.60
1.88
12,569.18
55,567.50
35,545.99
12,572.40
55,592.38
35,548.30
011
012
013
014
0.00
7.77
12.26
0.00
67,342.26
37,534.53
0.00
67,354.30
37,551.82
0.00
43.66
47.62
0.00
99,228.85
81,415.27
0.00
99,282.18
81,475.89
853.50
854.10
011
012
013
014
0.00
9.68
13.00
0.38
0.00
4.27
5.04
0.22
0.01
0.03
441.01
441.05
015
016
017
018
1.42
0.00
0.65
0.00
0.39
0.01
0.85
0.00
13,370.57
13,372.39
377.30
6,871.39
377.31
6,872.89
9,842.62
10,043.36
9,847.02
10,048.49
5,402.90
5,409.93
245.13
1.56
0.11
1.22
0.00
2.84
5.03
5.81
245.12
015
016
017
018
0.02
226.11
226.13
019
020
021
022
3.90
4.22
3.39
3.56
1.24
2.53
1.61
1.73
5,300.94
35,121.55
5,306.07
35,128.29
22.44
9.80
18.95
11.37
26,131.65
17,243.33
5,078.89
6,456.95
4.58
2.99
4.96
3.19
26,104.63
17,230.54
5,073.89
6,451.66
019
020
021
022
8,291.30
26,903.76
8,315.21
26,918.32
023
024
025
2.83
6.21
1.38
0.00
6,034.08
146,770.29
4.23
6,042.78
146,772.39
7.34
20.82
4.75
0.00
14,953.27
65,659.63
9.84
14,981.71
65,665.65
0.29
10,132.60
10,133.03
023
024
025
026
2.50
7.62
1.27
026
1.40
2.49
0.72
0.13
0.50
1.99
5,385.70
5,388.20
Total
94.48
44.00
1,649,273.26
1,649,411.74
Total
100.86
382.27
1,150,806.45
1,151,289.58
Lanna Culture
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