12th national convention on statistics (ncs) edsa...
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12th National Convention on Statistics (NCS) EDSA Shangri-La Hotel, Mandaluyong City
October 1-2, 2013
ESTIMATING THE QUARTERLY CONTRIBUTION OF TOURISM TO THE ECONOMY THROUGH THE
PHILIPPINE TOURISM SATELLITE ACCOUNTS (PTSA)
by
Florande S. Polistico and Cynthia S. Regalado
Author’s name Florande S. Polistico Designation Statistical Coordination Officer IV Affiliation National Statistical Coordination Board Address 403 Midland Buendia Bldg., Sen Gil Puyat Ave., Makati City Tel. no. 895-5002 E-mail [email protected]
Author’s name Cynthia S. Regalado Designation Statistical Coordination Office VI Affiliation National Statistical Coordination Board Address 403 Midland Buendia Bldg., Sen Gil Puyat Ave., Makati City Tel. no. 895-5002 E-mail [email protected]
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ESTIMATING THE QUARTERLY CONTRIBUTION OF TOURISM TO THE ECONOMY THROUGH THE PHILIPPINE TOURISM SATELLITE ACCOUNTS (PTSA)1
by
Florande S. Polistico and Cynthia S. Regalado2
ABSTRACT
In recognition of the role of a timely statistics for policy setting in tourism industry, this paper explores the possibility of determining the quarterly contribution of tourism to the economy that is consistent with the System of National Accounts (SNA). In this paper, available tourism related statistics on annual and quarterly will be summarized and evaluated. The Proportional Denton Method, one of the benchmarking methods described in existing international recommendations, was used in the quarterisation or the estimation of high frequency data (quarterly) from low frequency data (annual). The annual estimates of the Philippine Tourism Satellite Accounts (PTSA) on tourism expenditures from 2000 to 2011 will be used as benchmark while quarterly estimates on tourism related sectors derived from the National Accounts of the Philippines (NAP) will be considered as indicator variables. Lastly, this paper will propose recommendations towards institutionalization of quarterly estimation of the contribution of tourism to the economy.
Keywords: Philippine Tourism Satellite Accounts (PTSA), Quarterisation, Proportional Denton Method, National Accounts of the Philippines (NAP)
I. Introduction
1.1 Importance of tourism and tourism statistics
Unarguably tourism is one of the fastest growing industries worldwide and has
enormously contributed to the world’s social and economic development. While number of literature about tourism was richly growing and evolving over the decades, some countries were left behind with the way tourism research has evolved, particularly in other emerging forms of tourism which was not given due importance in the past. In addition, there are a number of concerns whose importance became more evident to further improve tourism statistics and harmonize them with other official statistics. One of the key issues in tourism statistics is the concept and dimensions of quality and quality indicators. Among these dimensions of quality are relevance and timeliness3. The generation of timely and relevant statistics in tourism should include the generation of higher frequency data for tourism policy makers, planners, and other stakeholders.
In the Philippine Development Plan (PDP) for the period 2011 to 2016, tourism is
considered as one of the key areas for economic development. Specifically, the long-term goal for Philippine tourism, as stipulated in the National Tourism Development Plan (NTDP), is to
1 The analyses and views expressed in this paper are those of the authors and do not reflect the views of the National Statistical
Coordination Board (NSCB). The results and analyses presented in this paper are exploratory/preliminary in nature hence not for quotation. 2 Statistical Coordination Officer IV and Division Chief, respectively, of the NSCB. The authors acknowledge the assistance of
Stephanie Rose Moscoso in the preparation of this paper. 3 Other dimensions of quality are credibility, accuracy, methodological soundness, coherence, and accessibility. International
Recommendations on Tourism Statistics (IRTS) paragraph 9.5
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develop an environmentally and socially responsible tourism that delivers larger and more widely distributed income and employment opportunities. In support to this, it is essential to come up with relevant and timely statistics and indicators by which the industry’s economic contribution can be measured and which will be useful in the formulation of policies and programs for the sector. However, the nature of tourism as an industry which cuts across many economic sectors makes it difficult to directly measure its economic contribution, especially in a more frequent basis.
As part of the efforts to address the need of tourism statistics, the Philippine Statistical
System (PSS), through the National Statistical Coordination Board (NSCB), Department of Tourism (DOT), and the National Statistics Office (NSO) which have been working closely together has been making significant achievements in the recent years4. The DOT and NSO are primarily responsible in conducting surveys for tourism. In addition, DOT is doing administrative data collection mechanisms to measure flows of visitors and supply demand of tourism. On the other hand, the efforts of NSCB and DOT include, among others, the compilation of the Philippine Tourism Satellite Accounts (PTSA). The framework of the TSA is used primarily to quantify the contribution of tourism to the economy within the context of the Philippine System of National Accounts (PSNA). Specifically, tourism statistics and tourism satellite accounts provide the means by which we can measure the size, economic contribution, and social impact of tourism.
The next section provides the overview of the PTSA.
1.2 The Philippine Tourism Satellite Accounts (PTSA)
The PTSA, being consistent with the internationally accepted macroeconomic statistical
frameworks, is the main framework to determine the contribution of tourism to the economy. While the nature of tourism industry5 differs from the other sectors, the TSA framework will enable to connect tourism with the aggregate macroeconomic indicators.
The PTSA is composed of tables patterned after the 10 tables recommended by the
United Nation World Tourism Organization (UNWTO) as the centre of the process of reconciliation of the most relevant economic information related to tourism and of international comparisons of the economic contribution of tourism to development and growth. Derived from these tables are the main aggregates which are comparable with other macro-indicators relating to consumption and value added in a country. These aggregates are very useful because they provide summary indicators of the size of tourism. These tables are aggregate tables intended to promote homogeneity among countries. In them, visitors are broken down into two types, and products and industries are presented in aggregated categories. Individual countries should compile these tables by aggregation from more detailed levels, in which, for instance, visitors could be classified according to country of residence, purpose of trip, modes of transport, types of accommodation, etc. in a way that allows analysis and contrast of their patterns and levels of consumption. Tourism products and industries should also be more disaggregated according to their relevance for the economy of reference (TSA: RMF p. 37).
4 The major coordination mechanism in place is through the Interagency Committee of Tourism Statistics (IACTS) co-chaired by
NSCB and DOT. http://www.nscb.gov.ph/aboutus/committees/tourism/default.asp 5 Tourism, as an economic activity, is not highlighted in the Philippine Standard Industrial Classification (PSIC). By nature, it cuts
across many economic activities such as hotel and restaurant services, transportation services, entertainment and recreation services, etc.
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After numerous discussions in the IACTS, one of the major highlights of the PTSA compilation is the approval of the methodology by the NSCB Executive Board through Resolution No. 6 Series of 2009 “Approving the Methodology for Compiling the Philippine Tourism Satellite Accounts”. At present, the PTSA tables were consequently updated to cover the years 2000 to 20116.
However, the available PTSA estimates are only at the annual levels and in nominal
terms. In recognition of the role of a timely statistics for policy setting in tourism industry, this paper explores the possibility of having the tourism satellite accounts of the Philippines in a quarterly basis for major indicators, namely: Tourism direct gross value added (TDGVA), domestic tourism expenditures, and inbound tourism expenditures. In addition, quarterly estimates for these indicators in real terms (at constant 2000 prices) will likewise be estimated to determine the indicator of tourism contribution to the economy on a quarterly basis.
The rest of this paper is structured as follows: Chapter 2 Review of available data and
indicators; Chapter 3 Benchmarking approach to estimate quarterly PTSA; Chapter 4 Results and discussions, and Chapter 5 Future Directions.
II. Review of available data and indicators
Consistent with the present international standards, the NSCB compiled the PTSA on an
annual basis. Indicators derived from the PTSA include inbound, domestic, outbound, and internal tourism expenditures. Also available are Gross Value Added of Tourism Industries (GVATI), Tourism Direct Gross Value Added (TDGVA), and Tourism employment. In particular these indicators were examined vis-à-vis the national accounts indicators to determine the impact of tourism to the economy.
In addition, the NSCB also compiled quarterly the National Accounts of the Philippines
which include the income from hotel and restaurants from the production side which form part of tourism characteristic industries. In the supply side, aggregate for travel export services and travel import services were also compiled quarterly.
The DOT, the lead agency in generating tourism indicators, conducts the different data
gathering activities to collect information on tourism that serve as inputs to the compilation of the PTSA. These indicators include volume of visitor arrivals to the Philippines, distribution of regional travellers, and relevant characteristics, behavior and expenditure of visitors as well as accommodation statistics that serve as inputs to the compilation of the PTSA. Another input to the PTSA, specifically on the estimation of domestic tourism expenditure is the HSDV. It is a rider to the NSO’s Labor Force Survey and is conducted to provide baseline data to measure the volume of domestic tourism, determine the profile and travel characteristics of domestic visitors, identify the travel patterns of the Filipino households, and estimate the extent and economic contribution of domestic tourism in the country.
On the other hand, the Bangko Sentral ng Pilipinas (BSP) compiles monthly the Balance
of Payments specifically on travel exports of services and travel imports of services.
Summary of the available statistics and indicators is presented in Table 1 below.
6 Highlights of the PTSA and other related topics can be accessed athttp://www.nscb.gov.ph/stats/ptsa/default.asp
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Table 1 List of available tourism statistics and indicators
Among the indicators mentioned it is the PTSA that gives more idea on the contribution of tourism to the economy being consistent to the concepts in the system of national accounts. However, since the PTSA is compiled only at the annual level, there is a need to link the yearly estimates to quarterly indicators in order to determine the impact of tourism on a quarterly basis.
The next section will discuss the proposed methodology to derive the PTSA quarterly
estimates, in particular the domestic and inbound tourism expenditures.
Data Frequency Agency
Philippine Tourism Satellite Accounts (PTSA) Annual
Inbound Tourism Expenditure
Domestic Tourism Expenditure
Outbound Tourism Expenditure
Internal Tourism Expenditure
Gross Value Added of Tourism Industries (GVATI)
Tourism Direct Gross Value Added (TDGVA)
Tourism Employment
National Accounts of the Philippines (NAP) Quarterly
Hotel and Restaurants GVA
Transportation GVA
Travel (Exports/Imports of Services)
Balance of Payments (BoP) Monthly
Travel (Export/Import of Services)
Tourism Demand
Visitor Arrivals to the Philippines Monthly
Distribution of Regional Travellers Annual
Average Hotel Occupancy Rate in Metro Manila Monthly
Hotel Length of Stay in Metro Manila Monthly
Tourism Supply
Number of accommodation establishment and
rooms Annual
Number of Available Hotel Rooms for Occupancy
in Metro Manila
Household Survey on Domestic Visitors (HSDV) 2005, 2009,
2010 & 2012
Survey of Tourism Establishments in the Philippines
(STEP)2010
National Statistical
Coordination Board (NSCB)
National Statistical
Coordination Board (NSCB)
Bangko Sentral ng Pilipinas
(BSP
Department of Tourism
(DOT)
Department of Tourism
(DOT)
National Statistics Office
(NSO)/ DOT
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III. Quarterisation of the Annual PTSA to Estimate Quarterly Levels
3.1 Benchmarking approach to estimate quarterly PTSA
The approach used in this paper to derive the quarterly estimates from the annual levels
is called Benchmarking7. It deals with the problem of combining a series of high-frequency data (e.g., quarterly data) with a series of less frequent data (e.g., annual data) for a certain variable into a consistent time series. The purpose of benchmarking is to combine the relative strengths of the low- and high-frequency data. More typically, the annual data provide the most reliable information on the overall level and long-term movements in the series, while the quarterly source data provide the only available explicit information about the short-term movements in the series, so that there is a need to combine the information content of both the annual and quarterly sources.
Table 2 summarizes the quarterly indicators (high frequency data) to split the annual
tourism statistics (low frequency data).
Table 2 Annual TSA aggregates and the quarterly indicators
Annual levels from PTSA Quarterly Indicators Source
Accommodation services Hotel and restaurant services
GVA
Quarterly National
Accounts (QNA) National
Statistical Coordination
Board (NSCB)
Food and beverage Hotel and restaurant services
GVA
Transportation services Transportation services GVA
Travel agencies other reservation services
Services incidental to transport GVA
Entertainment and recreation Recreational, cultural, and Sporting Activities GVA
Shopping Retail trade GVA
Miscellaneous tourism services Combination of the above
indicators
Other industries Combination of the above
indicators
The general objective of benchmarking is to preserve as much as possible the short-
term movements in the source data under the restrictions provided by the annual data and, at the same time, to ensure, for forward series, that the sum of the four quarters of the current year is as close as possible to the unknown future annual data. This is important because the short-term movements in the series are the central interest of the quarterly indicators, about which the indicator provides the only available explicit information.
7 This approach was introduced by the International Monetary Fund (IMF) primarily to estimate the Quarterly National Accounts
(QNA) from the Annual National Accounts (ANA).
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One of the benchmarking methods is the Proportional Denton Method8. This method will address the problem called Step Problem which is caused by the distortion of quarterly pattern from basic distribution technique. Specifically, this step problem was caused by suddenly changing from one benchmark-indicator ratio to another. The basic version of the proportional Denton benchmarking technique keeps the benchmarked series as proportional to the indicator as possible by minimizing (in a least-squares sense) the difference in relative adjustment to neighboring quarters subject to the constraints provided by the annual benchmarks.
Mathematically, the basic version of the proportional Denton technique can be
expressed as:
∑[
]
{ } under the restriction that, for flow series
∑
{ }
That is, the sum of the quarters should be equal to the annual data for each benchmark
year, where
t is time (e.g., t = 4y – 3 is the first quarter of year y, and t = 4y is the fourth quarter of year y);
is the derived QNA estimate for quarter t;
is the level of indicator for quarter t;
is the annual data for year y;
β is the last year for which an annual benchmark is available; and
T is the last quarter for which quarterly source data is available
For a more detailed exposition of the methodology see Quarterly National Accounts Manual – Concepts, Data Source, and Compilation Chapter VI9.
3.2 Estimating quarterly TSA levels at constant prices
In order to eliminate the effect of prices, the derived quarterly estimates will be deflated
using the implicit prices indices (IPIN) of the corresponding quarterly indicators from the national accounts.
8 To facilitate the computation process, a special program called BENCH developed by the IMF is used in this paper
9 Can be accessed at the IMF website at http://www.imf.org/external/pubs/ft/qna/2000/Textbook/ch6.pdf
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IV. Results and discussions
The following are the highlights of the results of the quarterisation exercises at constant
prices described above. More details of the results can be found in Annex Tables 1 to 4.
4.1 Fourth Quarter 201110 During the fourth quarter of 2011, the contribution of tourism to the economy, as
measured by TDGVA was 6.5 percent, the highest during the period Q1 2000 to Q4 2011 (Figure 1). TDGVA grew by 7.2 percent, higher than the 3.8 percent in the overall economic performance. Of the 7.2 percent growth, 6.0 percentage points was contributed by tourism characteristic industries while the remaining 1.2 percentage points from the other industries (Table 3).
Figure 1 Share of Tourism Direct Gross Value Added (TDGVA) to
Gross Domestic Product (GDP) at Constant Prices 2000 - 2011
Based on Table 3, among the tourism characteristic industries, shopping emerged as the top contributor with 2.1 percentage points with the growth of 8.5 percent over the same period in 2010. Accommodation services, which grew by 12.3 percent in Q4 2011, came next with 1.4 percentage points contribution. Other tourism industries and their contributions are: Entertainment and recreation services with 1.1 percentage points, travel agencies and other reservation services with 0.8 percentage point; food and beverage services with 0.3 percentage point; transportations services with 0.2 percentage point; and miscellaneous tourism services with 0.1 percentage point.
10
The last period in which results are available
6.5
5.0
5.2
5.4
5.6
5.8
6.0
6.2
6.4
6.6
6.8
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Shar
e t
o G
DP
(%
)
Period
Share Average
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Table 3 Tourism Direct Gross Value Added (TDGVA) by Sub-industry at Constant Prices
Growth rates and Contribution to growth Fourth Quarter 2011
On the demand side, internal tourism expenditure grew by 22.1 percent in Q4 2011, representing three consecutive quarters of more than 20 percent growth and nine consecutive quarters of double-digit growth. The 11.3 percent share for the combined HFCE and exports was the highest for the period Q1 2000 to Q4 2011 (Annex Table 2).
Domestic tourism, which accounted for 90 percent of the internal tourism expenditure, grew by 22.8 percent in the quarter, a seven consecutive quarters of at least 20 percent growth (Annex Table 3). Meanwhile, inbound tourism expenditure grew by 16.9 percent in Q4 2011, filling the slack of the country’s total export of goods and services which was down by 3.9 percent during the same quarter (Annex Table 4).
4.2 Summary of quarterly estimates from First Quarter 2000 to Fourth Quarter 2011
On the average, the average contribution of tourism to the economy, as measured by
the share of TDGVA to the country’s GDP was 5.8 percent with the average growth of 4.9 percent, higher than the 4.7 percent average growth of the Philippine GDP. In particular, the average growth of the fourth quarter period from 2001 to 2011 surpassed the fourth quarter GDP growth rates by 1.4 percentage points with 6.0 percent as compared to 4.6 percent.
Q4 2010 - Q4 2011
Growth rate
(%)
Contribution
to growth
(percentage
points)
Tourism Characteristics products 9.9 6.0
Accommodation 12.3 1.4
Food and Beverage 5.8 0.3
Transportation 13.8 0.2
Travel agencies and other reservation services 14.9 0.8
Entertainment and Recreation 9.2 1.1
Shopping 8.5 2.1
Miscellaneous 7.1 0.1
Other products 3.1 1.2
TOTAL 7.2 7.2
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Figure 2 Growth of Tourism Direct Gross Value Added (TDGVA) and Gross Domestic Product (GDP) at Constant Prices
2000 - 2011
In terms of contribution to growth, 3.1 percentage points out of the 4.9 percent average growth were contributed by the tourism characteristic industries while the rest [1.8 percentage points] was from other industries. Shopping was the top contributor with 1.2 percentage points followed by entertainment and recreation services [0.8 percentage point]; travel agencies and other reservation services [0.2 percentage point]; food and beverage services [0.3 percentage point]; transportation services [0.05 percentage point]; and miscellaneous tourism services [0.04 percentage point].
Figure 3 Contribution to growth of tourism characteristic industries
by quarter Average from Q1 2001 – Q4 2011
On the demand side, the average growth of internal tourism expenditure from Q1 2001 to Q4 2011 stood at 7.8 percent. On the average, this shared about 8.1 percent to the combined
(2.0)
-
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Gro
wth
(%
)
GDP
TDGVA
TDGVA average
GDP average
-
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Q1 Q2 Q3 Q4 Average
Co
ntr
ibu
tio
n (
in p
erc
en
tage
po
ints
) Accommodation
Food/Beverage
Transport
Reservation Agencies
Entertainment/Recreation
Shopping
Miscellaneous
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HFCE and total exports of goods and services of the country. Among the four quarters of the year, highest average share was noted in the fourth quarter with 8.5 percent. About 80 percent of the internal tourism expenditure is from domestic tourism expenditure while the remaining 20 percent came from the demand of inbound visitors. Domestic tourism expenditures grew quarterly, on the average, by 10.0 percent as against the 4.4 percent average growth of HFCE. This represents an average share of 11.3 percent of the total HFCE for the period covering Q1 2000 to Q4 2011.
V. Way Forward and Recommendations
The activities done in this paper are just exploratory in nature, hence, the empirical
results are subject to major limitations. Major leap forward is therefore necessary to improve the initial quarterly estimates of tourism contribution that is consistent with international standards. As a way forward, first the quarterisation process discussed in this paper should be enhanced, and ultimately the efforts should be moving towards regular and institutionalized quarterly compilation. Specific steps will be described below.
5.1 Enhancing the quarterisation process
The most critical part in the process of quarterly benchmarking is the choice of quarterly data (high frequency data) that will serve as indicators in deriving quarterly estimates from the annual data (low frequency data). Therefore, it is necessary to review the quarterly indicators specifically by considering the seasonality of the quarterly data and validating these movements vis-à-vis the data on the demand of visitors. On the other hand, the choice of price indices used as deflators is crucial in precisely deriving the estimates at constant prices. These price indices should be verified how reflective they are on the actual movements of the prices of goods and services either as consumed by the visitors and/or produced by tourism industries for the visitors. 5.2 Quarterly estimation on a regular basis
The quarterly estimates derived in this paper will serve as benchmark and are proposed to be extrapolated quarterly by utilizing the most appropriate and relevant indicators. Thus, there is a need to enhance the collection of data both from the supply and demand side.
On the supply side, the data collection through establishment surveys should be improved by giving emphasis on tourism industries particularly by adding more samples on these industries. On the demand side, the data from the Visitor Sample Survey (VSS) will be used in a more comprehensive way, specifically on the data on the length of stay of visitors and the average expenditure on different types of goods and services consumed during the period of reference.
In addition, the most important indicator is the data on the volume of visitors during the
period; hence the timely release of this statistics from the Arrival Card is a must. Meanwhile, with domestic tourism expenditure getting the lion’s share of the internal tourism expenditure, it is imperative to boost the data collection of domestic tourism statistics on a more frequent method. Specifically, the timeliness and the quality of the Distribution of Regional Travellers compiled by the DOT from administrative data are vital in ensuring that the quarterly estimation of domestic tourism expenditure will be possible.
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In terms of the timing of release, the compilation of quarterly account on tourism should be consistent with the availability of the data and indicators as well as on the compilation of the quarterly national accounts.
5.3 Revision of quarterly estimates using the annual TSA and/or availability of
Household Survey on Domestic Visitors To ensure that the quarterly estimates will be consistent with TSA concept and
methodology, it is important that it will be revised once the annual PTSA will be available. In connection with this, the availability of the Household Survey of Domestic Visitors will
be important in reflecting the travel characteristics to the annual TSA. Thus, the parameters such as expenditure and length of stay derived from HSDV should be reflected in the annual TSA, and in turn, to the quarterly TSA. Most importantly, the HSDV should be regularly collected and the utilization should be enhanced.
5.4 Institutional arrangements
Like any other undertakings and milestones in tourism statistics in the Philippines, the
quarterly estimation of the contribution of tourism should be done in close coordination of the DOT and the NSCB as the highest policy making body on all statistical matters in the country.
The Interagency Committee on Tourism Statistics (IACTS) will provide guidance and
direction in the course of generating quarterly estimates and will serve as forum in resolving emerging issues and/or concerns in relation to the quarterly estimation. Ultimately, the NSCB Executive Board will be the authority to decide based on the recommendation of the IACTS.
One of the major setbacks in another statistical undertaking is the limited resources
given to statistics. In order to pursue the compilation of another major indicator, it is imperative that the government will invest more in statistics.
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REFERENCES Commission of the European Communities, Organization for Economic Cooperation and
Development, World Tourism Organization (2008): Tourism Satellite Accounts: Recommended Methodological Framework. Luxembourg, Madrid, New York, Paris
Department of Tourism (2011): National Tourism Development Plan (NTDP) 2011 – 2016 International Monetary Fund (IMF) (2001): Quarterly National Accounts Manual – Concepts,
Data Sources, and Compilation. http://www.imf.org/external/pubs/ft/qna/2000/Textbook/index.htm
National Statistical Coordination Board (2012): National Accounts of the Philippines (NAP)
http://www.nscb.gov.ph/sna/default.asp National Economic Development Authority (2011): Philippine Development Plan (PDP) 2011
– 2016 United Nation Statistics Division (UNSD) and United Nation World Tourism Organization
(UNWTO) (2010): International Recommendations on Tourism Statistics (IRTS). Virola, R., F.S.Polistico, R.S.Reyes, and A.S. Oliveros (2012): “Things Statisticians Wanted
To Know About the Tourism Satellite Account But Were Afraid To Ask”, Technical Paper Series 2012-001, National Statistical Coordination Board (NSCB). http://www.nscb.gov.ph/stats/ptsa/Techpaper_PTSA.pdf
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ANNEX TABLES
Annex Table 1 Tourism Direct Gross Value Added (TDGVA) and Gross Domestic Product (GDP)
Current and Constant Prices, Q1 2000 to Q4 2011
Year Quarter TDGVA % growth Total GDP % growth
Share of
TDGVA to
GDP in %
TDGVA % growth Total GDP % growth
Share of
TDGVA
to GDP
in %
2000 1 48,598 819,296 5.9 49,859 842,436 5.9
2 51,196 865,429 5.9 51,649 874,668 5.9
3 52,885 889,238 5.9 52,477 889,137 5.9
4 57,465 1,006,750 5.7 55,299 974,474 5.7
2001 1 53,447 10.0 888,669 8.5 6.0 50,634 1.6 863,259 2.5 5.9
2 55,634 8.7 943,685 9.0 5.9 52,152 1.0 900,956 3.0 5.8
3 57,970 9.6 967,631 8.8 6.0 53,820 2.6 913,039 2.7 5.9
4 61,923 7.8 1,088,817 8.2 5.7 56,932 3.0 1,007,086 3.3 5.7
2002 1 57,017 6.7 958,193 7.8 6.0 53,067 4.8 890,693 3.2 6.0
2 59,823 7.5 1,022,497 8.4 5.9 54,888 5.2 936,709 4.0 5.9
3 62,253 7.4 1,029,339 6.4 6.0 56,924 5.8 937,391 2.7 6.1
4 67,783 9.5 1,188,315 9.1 5.7 60,716 6.6 1,053,874 4.6 5.8
2003 1 61,900 8.6 1,049,455 9.5 5.9 54,454 2.6 933,194 4.8 5.8
2 63,019 5.3 1,094,331 7.0 5.8 54,831 -0.1 981,777 4.8 5.6
3 66,986 7.6 1,115,618 8.4 6.0 57,028 0.2 986,863 5.3 5.8
4 73,832 8.9 1,288,697 8.4 5.7 62,264 2.6 1,106,635 5.0 5.6
2004 1 69,712 12.6 1,169,104 11.4 6.0 57,819 6.2 1,001,203 7.3 5.8
2 71,871 14.0 1,237,189 13.1 5.8 58,843 7.3 1,057,384 7.7 5.6
3 75,010 12.0 1,259,313 12.9 6.0 61,532 7.9 1,044,249 5.8 5.9
4 83,882 13.6 1,454,829 12.9 5.8 67,313 8.1 1,174,106 6.1 5.7
2005 1 77,276 10.8 1,290,345 10.4 6.0 60,894 5.3 1,045,576 4.4 5.8
2 80,056 11.4 1,381,750 11.7 5.8 61,439 4.4 1,111,438 5.1 5.5
3 82,961 10.6 1,392,203 10.6 6.0 63,578 3.3 1,089,848 4.4 5.8
4 92,761 10.6 1,613,451 10.9 5.7 69,966 3.9 1,234,417 5.1 5.7
2006 1 86,802 12.3 1,438,608 11.5 6.0 64,580 6.1 1,101,758 5.4 5.9
2 87,309 9.1 1,529,161 10.7 5.7 62,572 1.8 1,169,901 5.3 5.3
3 89,141 7.4 1,529,279 9.8 5.8 64,358 1.2 1,143,389 4.9 5.6
4 102,586 10.6 1,774,110 10.0 5.8 73,404 4.9 1,301,183 5.4 5.6
2007 1 94,073 8.4 1,573,657 9.4 6.0 67,243 4.1 1,171,255 6.3 5.7
2 96,359 10.4 1,691,200 10.6 5.7 68,277 9.1 1,258,385 7.6 5.4
3 99,853 12.0 1,666,597 9.0 6.0 69,973 8.7 1,215,811 6.3 5.8
4 114,356 11.5 1,961,267 10.5 5.8 79,964 8.9 1,382,837 6.3 5.8
2008 1 104,526 11.1 1,714,032 8.9 6.1 71,922 7.0 1,217,869 4.0 5.9
2 108,406 12.5 1,916,133 13.3 5.7 72,436 6.1 1,313,024 4.3 5.5
3 108,542 8.7 1,925,077 15.5 5.6 73,258 4.7 1,280,042 5.3 5.7
4 121,831 6.5 2,165,660 10.4 5.6 82,321 2.9 1,426,165 3.1 5.8
2009 1 108,138 3.5 1,808,557 5.5 6.0 73,730 2.5 1,229,618 1.0 6.0
2 110,136 1.6 1,968,888 2.8 5.6 73,561 1.6 1,334,449 1.6 5.5
3 111,178 2.4 1,952,870 1.4 5.7 72,793 -0.6 1,286,674 0.5 5.7
4 129,524 6.3 2,295,828 6.0 5.6 83,942 2.0 1,446,499 1.4 5.8
2010 1 120,219 11.2 2,050,544 13.4 5.9 78,178 6.0 1,333,040 8.4 5.9
2 124,707 13.2 2,245,797 14.1 5.6 80,084 8.9 1,453,390 8.9 5.5
3 124,291 11.8 2,177,534 11.5 5.7 78,537 7.9 1,380,231 7.3 5.7
4 154,661 19.4 2,529,605 10.2 6.1 97,268 15.9 1,534,877 6.1 6.3
2011 1 128,025 6.5 2,239,997 9.2 5.7 81,381 4.1 1,393,979 4.6 5.8
2 135,907 9.0 2,424,313 7.9 5.6 84,583 5.6 1,499,915 3.2 5.6
3 137,356 10.5 2,327,680 6.9 5.9 84,209 7.2 1,422,219 3.0 5.9
4 170,893 10.5 2,714,277 7.3 6.3 104,297 7.2 1,592,887 3.8 6.5
Constant PricesCurrent Prices
Page 15 of 17
Annex Table 2 Internal Tourism Expenditures
Current and Constant Prices, Q1 2000 to Q4 2011
Year Quarter
Internal
Tourism
Expenditure
%
growth
HFCE and
Exports
%
growth
Share in
%
Internal
Tourism
Expenditur
e
%
growth
HFCE and
Exports
%
growth
Share in
%
2000 1 74,918 986,232 7.6 76,897 1,053,716 7.3
2 80,643 1,041,642 7.7 81,419 1,080,655 7.5
3 79,515 1,133,161 7.0 78,640 1,112,368 7.1
4 88,230 1,263,628 7.0 85,186 1,177,924 7.2
2001 1 93,061 24.2 1,128,164 14.4 8.2 88,200 14.7 1,091,316 3.6 8.1
2 91,970 14.0 1,113,567 6.9 8.3 86,090 5.7 1,077,172 -0.3 8.0
3 94,656 19.0 1,164,259 2.7 8.1 87,539 11.3 1,099,668 -1.1 8.0
4 96,521 9.4 1,247,362 -1.3 7.7 88,559 4.0 1,132,137 -3.9 7.8
2002 1 89,827 -3.5 1,165,900 3.3 7.7 83,455 -5.4 1,098,818 0.7 7.6
2 91,943 0.0 1,231,121 10.6 7.5 84,364 -2.0 1,142,414 6.1 7.4
3 90,501 -4.4 1,287,772 10.6 7.0 82,491 -5.8 1,176,817 7.0 7.0
4 98,792 2.4 1,380,253 10.7 7.2 88,636 0.1 1,199,406 5.9 7.4
2003 1 93,512 4.1 1,287,669 10.4 7.3 82,525 -1.1 1,154,382 5.1 7.1
2 92,948 1.1 1,322,087 7.4 7.0 80,924 -4.1 1,186,336 3.8 6.8
3 103,323 14.2 1,395,610 8.4 7.4 88,131 6.8 1,225,340 4.1 7.2
4 109,595 10.9 1,521,000 10.2 7.2 92,685 4.6 1,287,499 7.3 7.2
2004 1 111,739 19.5 1,434,667 11.4 7.8 93,093 12.8 1,248,535 8.2 7.5
2 120,741 29.9 1,524,410 15.3 7.9 99,076 22.4 1,300,061 9.6 7.6
3 122,462 18.5 1,588,596 13.8 7.7 100,256 13.8 1,343,067 9.6 7.5
4 142,201 29.8 1,754,346 15.3 8.1 114,287 23.3 1,378,632 7.1 8.3
2005 1 146,010 30.7 1,576,562 9.9 9.3 115,021 23.6 1,292,117 3.5 8.9
2 147,236 21.9 1,668,268 9.4 8.8 112,559 13.6 1,353,037 4.1 8.3
3 155,290 26.8 1,740,010 9.5 8.9 118,650 18.3 1,415,605 5.4 8.4
4 172,624 21.4 1,893,834 8.0 9.1 130,015 13.8 1,453,853 5.5 8.9
2006 1 157,201 7.7 1,751,928 11.1 9.0 116,658 1.4 1,389,725 7.6 8.4
2 166,236 12.9 1,910,945 14.5 8.7 119,039 5.8 1,505,999 11.3 7.9
3 167,004 7.5 1,904,259 9.4 8.8 120,188 1.3 1,506,456 6.4 8.0
4 196,692 13.9 2,031,838 7.3 9.7 140,815 8.3 1,529,281 5.2 9.2
2007 1 193,044 22.8 1,903,376 8.6 10.1 137,846 18.2 1,495,102 7.6 9.2
2 198,719 19.5 1,991,519 4.2 10.0 140,219 17.8 1,575,782 4.6 8.9
3 205,328 22.9 1,994,294 4.7 10.3 143,616 19.5 1,578,847 4.8 9.1
4 205,118 4.3 2,157,120 6.2 9.5 144,140 2.4 1,608,422 5.2 9.0
2008 1 182,046 -5.7 1,957,393 2.8 9.3 125,182 -9.2 1,478,019 -1.1 8.5
2 177,639 -10.6 2,145,365 7.7 8.3 117,973 -15.9 1,633,820 3.7 7.2
3 160,798 -21.7 2,211,285 10.9 7.3 107,204 -25.4 1,626,996 3.0 6.6
4 178,218 -13.1 2,275,493 5.5 7.8 119,378 -17.2 1,580,574 -1.7 7.6
2009 1 163,886 -10.0 1,993,387 1.8 8.2 110,315 -11.9 1,447,616 -2.1 7.6
2 173,259 -2.5 2,135,783 -0.4 8.1 114,553 -2.9 1,588,445 -2.8 7.2
3 179,775 11.8 2,131,697 -3.6 8.4 116,299 8.5 1,578,916 -3.0 7.4
4 209,431 17.5 2,319,574 1.9 9.0 134,630 12.8 1,588,743 0.5 8.5
2010 1 196,215 19.7 2,247,221 12.7 8.7 126,317 14.5 1,588,382 9.7 8.0
2 211,160 21.9 2,366,931 10.8 8.9 134,118 17.1 1,757,899 10.7 7.6
3 221,944 23.5 2,406,281 12.9 9.2 138,533 19.1 1,757,737 11.3 7.9
4 263,272 25.7 2,555,108 10.2 10.3 164,209 22.0 1,727,942 8.8 9.5
2011 1 241,231 22.9 2,429,133 8.1 9.9 151,478 19.9 1,669,886 5.1 9.1
2 265,593 25.8 2,554,044 7.9 10.4 163,050 21.6 1,804,028 2.6 9.0
3 280,890 26.6 2,503,139 4.0 11.2 169,541 22.4 1,730,149 -1.6 9.8
4 332,450 26.3 2,749,283 7.6 12.1 200,571 22.1 1,770,262 2.4 11.3
Current Prices Constant Prices
Page 16 of 17
Annex Table 3 Domestic Tourism Expenditures and Household Final Consumption Expenditures (HFCE)
Current and Constant Prices, Q1 2000 to Q4 2011
Year Quarter
Domestic
Tourism
Expenditure
%
growthHFCE
%
growth
Share in
%
Domestic
Tourism
Expenditure
%
growthHFCE
%
growth
Share in
%
2000 1 52,679 590,285 8.9 54,198 596,572 9.1
2 57,177 635,558 9.0 57,765 650,216 8.9
3 58,036 635,711 9.1 57,569 628,112 9.2
4 67,056 723,722 9.3 64,380 710,376 9.1
2001 1 68,191 29.4 657,351 11.4 10.4 64,568 19.1 620,394 4.0 10.4
2 69,366 21.3 705,450 11.0 9.8 64,841 12.2 674,991 3.8 9.6
3 73,334 26.4 708,187 11.4 10.4 67,764 17.7 654,713 4.2 10.4
4 77,071 14.9 792,471 9.5 9.7 70,502 9.5 740,777 4.3 9.5
2002 1 66,670 -2.2 711,416 8.2 9.4 61,989 -4.0 649,260 4.7 9.5
2 68,064 -1.9 764,903 8.4 8.9 62,414 -3.7 707,495 4.8 8.8
3 68,863 -6.1 766,177 8.2 9.0 62,779 -7.4 689,143 5.3 9.1
4 77,237 0.2 859,949 8.5 9.0 69,095 -2.0 782,442 5.6 8.8
2003 1 71,836 7.7 772,664 8.6 9.3 63,214 2.0 684,183 5.4 9.2
2 74,139 8.9 833,836 9.0 8.9 64,348 3.1 745,670 5.4 8.6
3 81,899 18.9 834,818 9.0 9.8 69,639 10.9 726,129 5.4 9.6
4 88,599 14.7 940,298 9.3 9.4 74,542 7.9 827,758 5.8 9.0
2004 1 85,237 18.7 855,989 10.8 10.0 70,621 11.7 726,539 6.2 9.7
2 93,187 25.7 931,602 11.7 10.0 76,036 18.2 794,140 6.5 9.6
3 97,097 18.6 945,765 13.3 10.3 79,430 14.1 766,488 5.6 10.4
4 115,806 30.7 1,081,533 15.0 10.7 92,854 24.6 874,724 5.7 10.6
2005 1 119,042 39.7 962,997 12.5 12.4 93,670 32.6 759,157 4.5 12.3
2 123,761 32.8 1,048,435 12.5 11.8 94,285 24.0 832,560 4.8 11.3
3 129,896 33.8 1,048,501 10.9 12.4 99,179 24.9 795,184 3.7 12.5
4 145,081 25.3 1,199,199 10.9 12.1 109,014 17.4 914,889 4.6 11.9
2006 1 126,400 6.2 1,067,806 10.9 11.8 93,757 0.1 790,939 4.2 11.9
2 129,656 4.8 1,165,971 11.2 11.1 92,562 -1.8 863,715 3.7 10.7
3 134,055 3.2 1,144,076 9.1 11.7 96,561 -2.6 826,002 3.9 11.7
4 159,871 10.2 1,300,134 8.4 12.3 114,243 4.8 959,219 4.8 11.9
2007 1 158,973 25.8 1,156,024 8.3 13.8 113,405 21.0 831,284 5.1 13.6
2 168,897 30.3 1,256,556 7.8 13.4 118,926 28.5 896,897 3.8 13.3
3 174,725 30.3 1,234,423 7.9 14.2 122,210 26.6 864,485 4.7 14.1
4 177,518 11.0 1,417,460 9.0 12.5 124,720 9.2 1,005,778 4.9 12.4
2008 1 154,259 -3.0 1,281,806 10.9 12.0 106,263 -6.3 871,347 4.8 12.2
2 151,338 -10.4 1,420,659 13.1 10.7 100,759 -15.3 921,752 2.8 10.9
3 138,622 -20.7 1,425,850 15.5 9.7 92,805 -24.1 895,037 3.5 10.4
4 154,859 -12.8 1,611,278 13.7 9.6 103,977 -16.6 1,042,724 3.7 10.0
2009 1 138,598 -10.2 1,383,004 7.9 10.0 93,875 -11.7 887,468 1.9 10.6
2 148,271 -2.0 1,501,521 5.7 9.9 98,325 -2.4 959,004 4.0 10.3
3 155,612 12.3 1,440,826 1.1 10.8 100,843 8.7 900,681 0.6 11.2
4 184,212 19.0 1,668,074 3.5 11.0 118,599 14.1 1,070,755 2.7 11.1
2010 1 169,837 22.5 1,491,734 7.9 11.4 109,693 16.9 923,065 4.0 11.9
2 184,681 24.6 1,599,826 6.5 11.5 117,566 19.6 977,453 1.9 12.0
3 194,309 24.9 1,547,459 7.4 12.6 121,451 20.4 922,575 2.4 13.2
4 234,540 27.3 1,803,014 8.1 13.0 146,398 23.4 1,122,734 4.9 13.0
2011 1 213,861 25.9 1,636,517 9.7 13.1 134,702 22.8 969,538 5.0 13.9
2 235,907 27.7 1,779,604 11.2 13.3 145,122 23.4 1,025,090 4.9 14.2
3 248,537 27.9 1,708,542 10.4 14.5 150,244 23.7 985,430 6.8 15.2
4 297,397 26.8 2,007,918 11.4 14.8 179,750 22.8 1,188,852 5.9 15.1
Current Prices Constant Prices
Page 17 of 17
Annex Table 4 Inbound Tourism Expenditures and Exports of Goods and Services
Current and Constant Prices, Q1 2000 to Q4 2011
Year Quarter
Inbound
Tourism
Expenditure
%
growthExports
%
growth
Share in
%
Inbound
Tourism
Expenditure
%
growthExports
%
growth
Share
in %
2000 1 22,239 395,947 5.6 22,699 457,145 5.0
2 23,466 406,084 5.8 23,655 430,439 5.5
3 21,479 497,450 4.3 21,071 484,257 4.4
4 21,174 539,906 3.9 20,806 467,547 4.5
2001 1 24,871 11.8 470,813 18.9 5.3 23,632 4.1 470,922 3.0 5.0
2 22,604 -3.7 408,117 0.5 5.5 21,250 -10.2 402,181 -6.6 5.3
3 21,322 -0.7 456,072 -8.3 4.7 19,775 -6.1 444,955 -8.1 4.4
4 19,450 -8.1 454,891 -15.7 4.3 18,057 -13.2 391,361 -16.3 4.6
2002 1 23,157 -6.9 454,483 -3.5 5.1 21,466 -9.2 449,557 -4.5 4.8
2 23,879 5.6 466,218 14.2 5.1 21,949 3.3 434,919 8.1 5.0
3 21,638 1.5 521,596 14.4 4.1 19,713 -0.3 487,675 9.6 4.0
4 21,555 10.8 520,304 14.4 4.1 19,541 8.2 416,965 6.5 4.7
2003 1 21,676 -6.4 515,005 13.3 4.2 19,311 -10.0 470,199 4.6 4.1
2 18,809 -21.2 488,251 4.7 3.9 16,576 -24.5 440,666 1.3 3.8
3 21,424 -1.0 560,792 7.5 3.8 18,491 -6.2 499,212 2.4 3.7
4 20,996 -2.6 580,702 11.6 3.6 18,143 -7.2 459,741 10.3 3.9
2004 1 26,502 22.3 578,678 12.4 4.6 22,472 16.4 521,996 11.0 4.3
2 27,554 46.5 592,808 21.4 4.6 23,040 39.0 505,922 14.8 4.6
3 25,365 18.4 642,832 14.6 3.9 20,826 12.6 576,579 15.5 3.6
4 26,396 25.7 672,813 15.9 3.9 21,433 18.1 503,908 9.6 4.3
2005 1 26,968 1.8 613,565 6.0 4.4 21,351 -5.0 532,960 2.1 4.0
2 23,475 -14.8 619,833 4.6 3.8 18,274 -20.7 520,478 2.9 3.5
3 25,395 0.1 691,509 7.6 3.7 19,471 -6.5 620,421 7.6 3.1
4 27,542 4.3 694,635 3.2 4.0 21,001 -2.0 538,964 7.0 3.9
2006 1 30,801 14.2 684,122 11.5 4.5 22,900 7.3 598,785 12.4 3.8
2 36,581 55.8 744,974 20.2 4.9 26,477 44.9 642,284 23.4 4.1
3 32,949 29.7 760,183 9.9 4.3 23,627 21.3 680,453 9.7 3.5
4 36,821 33.7 731,704 5.3 5.0 26,572 26.5 570,062 5.8 4.7
2007 1 34,071 10.6 747,351 9.2 4.6 24,440 6.7 663,818 10.9 3.7
2 29,821 -18.5 734,963 -1.3 4.1 21,293 -19.6 678,885 5.7 3.1
3 30,603 -7.1 759,872 0.0 4.0 21,405 -9.4 714,363 5.0 3.0
4 27,600 -25.0 739,660 1.1 3.7 19,421 -26.9 602,645 5.7 3.2
2008 1 27,786 -18.4 675,587 -9.6 4.1 18,919 -22.6 606,672 -8.6 3.1
2 26,301 -11.8 724,706 -1.4 3.6 17,215 -19.2 712,068 4.9 2.4
3 22,176 -27.5 785,435 3.4 2.8 14,399 -32.7 731,958 2.5 2.0
4 23,359 -15.4 664,215 -10.2 3.5 15,401 -20.7 537,850 -10.8 2.9
2009 1 25,288 -9.0 610,383 -9.7 4.1 16,440 -13.1 560,147 -7.7 2.9
2 24,988 -5.0 634,262 -12.5 3.9 16,227 -5.7 629,440 -11.6 2.6
3 24,162 9.0 690,871 -12.0 3.5 15,456 7.3 678,236 -7.3 2.3
4 25,220 8.0 651,500 -1.9 3.9 16,031 4.1 517,988 -3.7 3.1
2010 1 26,378 4.3 755,487 23.8 3.5 16,624 1.1 665,317 18.8 2.5
2 26,480 6.0 767,105 20.9 3.5 16,552 2.0 780,446 24.0 2.1
3 27,636 14.4 858,822 24.3 3.2 17,082 10.5 835,162 23.1 2.0
4 28,733 13.9 752,094 15.4 3.8 17,811 11.1 605,208 16.8 2.9
2011 1 27,370 3.8 792,616 4.9 3.5 16,775 0.9 700,348 5.3 2.4
2 29,686 12.1 774,440 1.0 3.8 17,928 8.3 778,938 -0.2 2.3
3 32,353 17.1 794,597 -7.5 4.1 19,298 13.0 744,719 -10.8 2.6
4 35,053 22.0 741,365 -1.4 4.7 20,820 16.9 581,411 -3.9 3.6
Current Prices Constant Prices