Impact of Beijing Olympic-related Investments on Regional Economic Growth of China: Interregional Input Output Approach*

Transcription

1 Asian Economic Journal 2007, Vol. 21 No. 3, Impact of Beijing Olympic-related Investments on Regional Economic Growth of China: Interregional Input Output Approach* Yaxiong Zhang and Kun Zhao Received 27 July 2006; Accepted 30 April 2007 Using the interregional input output model, the present paper analyzes the impact of Olympic-related investments on the economic development of Beijing and its surrounding areas, as well as the rest of China. The interregional input output model provides a satisfactory simulation and analysis of Olympic-related investments that are implemented in Beijing and other areas and their spillover effects on other regions. We estimate that from 2002 to 2007, Olympic-related investments will add 2.02, 0.23 and 0.09 percent annually to gross regional products of Beijing, its surrounding areas and the rest of China, respectively. Keywords: Olympic-related investments, interregional input output model, regional economic growth of China, linkage analysis. JEL classification codes: C67, R11, R15 doi: /j x I. Introduction On 13 July 2001, Beijing won the bid to host the 2008 Olympic Games: the preparation for the Games thereafter set off. To stage such a sporting pageant as the Olympic Games is a sign of an ever-stronger and developed China. Beijing s hosting of the Games with themes of Green Olympics, High-tech Olympics, People s Olympics should greatly improve the international image of Beijing and China as a whole. Apart from its significance as a grand societal gathering, hosting the Olympic Games will greatly promote investment and consumption. The Olympics catalyses stupendous economic growth, and boosts the construction of infrastructure. The Beijing Olympic Games will accelerate Beijing s development towards an international metropolis and add impetus to the economic development in the region around the capital and even that of the whole country. Since the Los Angeles Olympics of 1984, a number of cost-benefit analyses have been conducted regarding the economic impact of hosting the Games. To quantify the various impacts of hosting such an event, it is necessary to build a model of the economy in question (Table 1). From the previous studies regarding economic impacts induced by past Olympic Games, it is evident that hosting * Zhang (corresponding author) and Zhao: Department of Economic Forecasting, State Information Center, No. 58 Sanlihe Road, Beijing, , China. zhangyx@mx.cei.gov.cn

2 Table 1 Summer Olympics Reference Total economic impact Economic impact studies of past games Impact as % of GRP Tourists New Jobs Period Modeling approach Sydney 2000 Andersen (1999) A$6.5bn (1996 prices) 2.78 NA (Australia) CGE Atlanta 1996 Humphreys and US$5.1bn (1994 prices) m (Georgia) I-O Plummer (1995) Barcelona 1992 Brunet (1995) US$0.03bn m (Spain) None Seoul 1988 Kim et al. (1989) WON1846bn 1.40 NA (South Korea) None Los Angeles 1984 Economics Research Associates (1984) US$2.3bn (1984 prices) m (South California) 1984 I-O Notes: Gross regional products (GRP) in Olympic year, except for Seoul where comparison is with national GDP. CGE, computable general equilibrium; I-O, input output. Source: PricewaterhouseCoopers (2004). ASIAN ECONOMIC JOURNAL 262

3 BEIJING OLYMPICS AND REGIONAL GROWTH 263 the Olympic Games will have a series of impacts on the economy, culture, environment and society (Arthur Anderson, 1999; Humphreys and Plummer, 1995; Brunet, 1995; Kim et al., 1989). After Beijing s successful bid for the 2008 Olympic Games, many domestic scholars and institutions have carried out research regarding the potential impact of the Olympic Games on Beijing and China s economy and society, and reached some important conclusions. Gu et al. (2003) divide the impact of Olympic-related investments on the economy of Beijing into three phases: pre-games, the year of the Games and post-games. Using the investment multiplier, the consumption function and the input output (I-O) model, they predicted that from 2003 to 2009, the direct Olympic investments will add another 5 percent to Beijing s gross regional product (GRP) growth, and result in a 7 percent increase in fiscal revenues and a 0.87 percent increase in the employment rate. Based on the Tenth Five Year Plan, the available information regarding newly-added Olympic investments and the increased consumption caused by Keynes s multiplier effect, Wei and Yan (2003, 2005) carried out empirical research using the I-O model. Their conclusion is that Olympic-related investments will add 0.8 percent in annual GRP growth for Beijing from 2005 to Li and Duan (2005) developed a bi-regional (Beijing and the rest of China) computable general equilibrium model and conducted a quantitative study of the impact of the Olympic Games on China s economy. Their finding is that from the year 2003 to 2007, the Olympic Games will help to increase Beijing and the rest of China s GRP growth by an extra annual rate of 2.3 and 0.07 percent, respectively. Using the economic impact model and based on statistics from various government departments, Lin (2004) shows that preparing for and hosting the 2008 Olympic Games will result in a direct economic impact of bn yuan and an indirect impact of bn yuan. Nevertheless, as China s economy is a complicated and open system comprising large groups of consumers, producers, sectors and markets, the economic effects of the Olympics will reach Beijing s neighboring regions and beyond. The Beijing Olympics will also affect the global economy to some degree. Therefore, it is necessary to investigate the different impacts of the Olympic Games on Beijing and other regions at the disaggregated industrial sector level. Because much of the Olympic-related investment and major Olympic events take place in Beijing, the impact of the Olympic Games on Beijing will be direct and distinctive. In contrast, the other regions in China will indirectly benefit from the event as a result of the rising demands from Olympic investments. The impacts on different industries will be different from that in Beijing. To begin with, interregional economic impacts induced by the Olympic Games should be considered. The first impact of the Games is the conductive effect on the surrounding area of the host city. Some Olympic venues will be constructed or renovated in the surrounding areas of Beijing. The hosting of these events will influence local economic development, providing opportunities for related industries in these areas, especially in Tianjin, Hebei and Shandong. The activities created by the Olympic investments boost the need for more raw

4 ASIAN ECONOMIC JOURNAL 264 materials and machinery, and increase demands on related sectors; therefore further boosting the development of other regions. Second, the business opportunities that the Olympic Games provide are open to a wider range of operations in China, and are equally available to different regions of China (e.g. public biddings for franchise, construction of venues and infrastructures and leasing or providing of equipment). Finally, the conductive effects of the Olympic Games will spread to the rest of world, and influence relevant industries of other countries. However, considering the total value of the world s economy, Beijing s constitutes only a small fraction and, therefore, the 2008 Beijing Olympics will not have a big influence on the global economy. The successful hosting of the Olympic Games requires concerted efforts by various sectors. Most industries will be directly or indirectly involved in the Olympic Games. First, the construction industry and the building-material industries are considered to be the industries most directly affected by the Olympics. The construction of large-scale projects have brought opportunities to the construction industry, and related industries, such as building-material, machinery, metal products, decoration, and other related industries. Meanwhile, the Beijing Olympic Games, with High-tech Olympics as one of its themes will present a rare opportunity for the high-tech industries. Related technologies and products will be upgraded timely. As for the service industries, various sectors related to the tourism industry (e.g. catering, accommodation, transportation and entertainment), information systems (e.g. e-commerce, telecommunication network and personalized information services) and the environment will make headways during the time of the Games. As an effective tool for impact analysis at interregional and inter-industrial levels, in the present study the interregional I-O (IRIO) model is adopted to estimate the impacts of Olympic-related investments on the regional economic growth of China. The model classifies China into three regions (Beijing, its Surrounding Area and the Rest of China) and its industries into 17 sectors. The methodology of the model will be discussed in Section II. The compilation and updating procedure used in the present study for China s IRIO model will be explained in Section III. Findings of the empirical study regarding the impacts of Olympic-related investments on regional economic growth of China will be presented in Section IV and Section V contains closing remarks. II. Methodology II.1 Interregional input output model The IRIO model is an effective tool for analysis of interdependencies among regions and industries. It was originally developed by Isard (1951). For this reason, the IRIO model is also called the Isard model. After Isard s theoretical work, some IRIO projects, such as a series of Japanese survey-based interregional models (METI, undated) and Dutch three-region interregional models were implemented (Oosterhaver, 1981).

5 BEIJING OLYMPICS AND REGIONAL GROWTH 265 The IRIO model requires a large amount of primary data, which can only be compiled where the spatial and sectional origin and destination of the interindustry flows are perfectly and directly known. However, the data on shipments of goods between sectors and between regions are not readily available for most countries, so it is difficult to compile an IRIO model of a relatively large scale in terms of sectors and regions. This has generated a great deal of work in the development of mathematical approaches to estimate interregional commodity flows: one of the very ambitious attempts in this direction is the multiregional input output (MRIO) model originated (independently) by Chenery (1953) and Moses (1955). It is sometimes referred to as the Chenery Moses Model. In the present study, it was impossible for us to construct the IRIO model of China on a full-survey basis, so we implemented the MRIO model and conducted a special survey on the interregional commodity flows to modify the mathematical estimation. Using the MRIO model, the technical structure of production in each region and interregional trade structures are compiled in different ways. Less data, which is usually more easily available, is needed to implement an MRIO model than is needed for the direct construction of an IRIO table. In addition, the separation of the regional technical structure and the trade structure allows us to update the table more easily. II.2 Model structure To estimate the impacts of Beijing Olympic-related investments on regional economic growth in China using the MRIO model, we classified China into three regions: Beijing (BJ), the Surrounding Area (SA) 1 and the Rest of China (RC). RS The structure of the model is shown in Table 2. x ij denotes the intermediate RS transaction of sector i in region R to sector j in region S. f i, E, M, V and X are the final demand, export, import, value added and total output (input) of each region. The model also can be represented in matrix form as follows: ^ ^ ^ ^ ^ ^ ^ ^ ^ E M X E M = X 3 3 E M X 1 A 0 0 X 2 0 A 0 X A X 1 2 3, ^ ^ ^ + ^ ^ ^ ^ ^ ^ F 2 F 3 F (1) where A R denotes the intraregional direct input coefficient matrix of region R, F R denotes the final demand of region R (including intraregional and interregional), and ^ RS is the trade coefficient matrix from region R to region S, which is a diagonal matrix of coefficients. 1. Including Tianjin, Hebei and Shandong.

6 ASIAN ECONOMIC JOURNAL 266 Table 2 Layout of the multiregional input output model for China Intermediate input Intermediate demand Final demand Export Import Total output BJ SA RC BJ SA RC BJ [ ] [ ] [ ] [ f ] E 1 M 1 X 1 i [ f i ] 13 [ f i ] x ij x ij x ij SA [ x E 2 M 2 X 2 ij ] [ x ij ] [ x ij ] [ f i ] [ f ] 23 i [ f i ] 31 RC [ ] [ ] [ ] [ f ] E 3 M 3 X 3 i [ f i ] [ f i ] x ij x ij x ij Value added V 1 V 2 V 3 Total input X 1 X 2 X 3 The elements of trade coefficient matrix, denoted by c i RS, show the proportion of all good i used in region S that comes from region R. Trade coefficients are derived from the transaction from R to S divided by the total inflow of S, defined as c i RS = t i RS n ( n = 12, ), t R i RS (2) RS where t i shows the amount of good i moved from region R to region S. This treatment implies that each sector in the region purchases the commodities and services within one sector from the other region at the same ratio. III. Data Estimation To estimate the impacts of Beijing Olympic-related investment on regional economic growth in China using the MRIO model, the 17-sector input output table, which was published in the China Statistical Yearbook (National Bureau of Statistics, 2003), is used at national level and the 40-sector input output table (2000) is used for Beijing, Hebei, Tianjin and Shandong province. Using these tables and other data estimations for the MRIO model, a three-region MRIO model of China for 2000 was compiled, and was then updated to III.1 Sector classification Table 3 shows how the National Bureau of Statistics national 40-sector classification of the National Bureau of Statistics is converted to the 17-sector classification used in the present study. 2. The first exercise of compiling a 1997 China MRIO model at 8-region and 30-sector level was jointly conducted by the State Information Center and IDE. For details on this compilation method, see Okamoto et al. (2005) and Zhang and Zhao (2004).

7 BEIJING OLYMPICS AND REGIONAL GROWTH 267 Table 3 The converter between 17-sector classification in China multiregional input output model and national 40-sector classification of National Bureau of Statistics, China 17-sector classification 40-sector classification 1. Agriculture 1. Agriculture 2. Mining 2. Coal mining and processing 3. Crude petroleum and natural gas products 4. Metal ore mining 5. Non-ferrous mineral mining 3. Food products 6. Manufacture of food products and tobacco processing 4. Textile and wearing apparel 7. Textile goods 8. Wearing apparel, leather, furs, down and related products 5. Wooden products 9. Sawmills and furniture 6. Paper and printing 10. Paper and products, printing and record medium reproduction 7. Chemical products 11. Petroleum processing and coking 12. Chemicals 8. Non-metallic mineral products 13. Nonmetal mineral products 9. Metal products 14. Metals smelting and pressing 15. Metal products 10. Machinery 16. Machinery and equipment 11. Transport equipment 17. Transport equipment 12. Electronic products 18. Electric equipment and machinery 19. Electric and telecommunication equipment 13. Other manufacturing products 20. Instruments, meters, cultural and office machinery 21. Maintenance and repair of machine and equipment 22. Other manufacturing products 23. Scrap and waste 14. Electricity, gas and water supply 24. Electricity, steam and hot water production and supply 25. Gas production and supply 26. Water production and supply 15. Construction 27. Construction 16. Trade and transport 28. Transport and warehousing 32. Passenger transport 17. Services 30. Wholesale and retail trade 29. Post and telecommunication 31. Eating and drinking places 33. Finance and insurance 34. Real estate 35. Social services 36. Health services, sports and social welfare 37. Education, culture and arts, radio, film and television 38. Scientific research 39. General technical services 40. Public administration and other sectors

8 ASIAN ECONOMIC JOURNAL 268 III.2 Estimation of interregional commodity flows In China, statistics concerning interregional shipments of commodity by region are limited, so we applied two methods of estimating the interregional commodity flows: the special survey and the estimation model. Special survey To obtain the information on 2000 inter-provincial commodity flows, a special survey (see detail in Appendix) was conducted. We selected 549 state-owned enterprises and group companies that are regarded as important in terms of size and activity, and distributed questionnaires to them regarding their production inputs and distribution for 2000 (Zhang and Zhao, 2006). Because of the limitation of the survey scale and response ratio, there was not enough information for some sectors, like the service sector and certain regions. However, the survey provided us very important information on the commodity shipments over the region. Estimation model The trade coefficients are the most important data for estimating the MRIO model. We adopted the Leontief-Strout Gravity model to calculate those coefficients. It can be defined as: t x d = Q i RS, x i RS i R i s i R R R S where x i is the total supply of good i in region R, d i is total demand of good RS i in region S, and Q i is the spatial friction factor of movement of good i from region R to region S. Leontief and Strout (1963) found various ways of estimating the parameter Q. In the present study, we use the proportional distribution coefficient of interregional commodity flows (Ihara, 1979, 1996) as an approximation to RS calculate Q i. In China, only the railway transport origin destination table is provided in the Yearbook of China Transportation and Communications (China Transportation and Communication Association, 2001). In this case, we estimated the origin destination tables for the corresponding commodities of road and water transport using the data flow of each product from each region and the average distance of shipment for every commodity as the control. 3 After the origin destination tables of the three transport modes were estimated, RS we calculated the Q i using the estimated origin destination tables based on the following formulae: 3. The air and pipeline shipments are neglected, which might not lower the overall accuracy of our estimation very much. As the supplementary, we modified the estimation result using the survey and superior data on some sectors interregional commodity flows, such as the crude oil.

9 BEIJING OLYMPICS AND REGIONAL GROWTH 269 Q i RS = Hi RS Hi RO H H i OO i OS, RS RO where H i is the amount of i commodity flow from region R to region S, H i OS is the total amount of i commodity flow departed from region R, H i is the OO total amount of i commodity flow arriving in region S and H i is the total amount of commodity flow in all regions. III.3 Updating As investments in the Olympic Games have been carried out during 2002 to 2007, the compilation of the MRIO model has been updated. Because of the limitation of available data, we cannot update the model to each year. As with the single-region case, we use China s MRIO model for the analysis by assuming that a base-year A matrix remains valid for subsequent years. This means that the production technology within each of the regions as well as interregional commodity flow (trade) patterns between the regions is unchanged. We update the 2000 MRIO model to 2005 and use this to analyze the economic impacts of Olympic-related investments in the years 2002 to 2004 and 2005 to 2007, respectively. The assumption is that the economic and technological structure from 2002 to 2004 remains the same as that in 2000, and from 2006 to 2007 the same as that in The updated work is mainly focused on the national and provincial tables to year 2005 based on the year 2000 table, while the interregional commodity flows for 2005 were estimated using related transport data for With some related sectors data from China Statistical Yearbooks and nominal annual growth rates for corresponding items, national and provincial total output, final demands and value added for 2000 are updated to 2005, and then the modified RAS method is applied to estimate intermediate transactions for In this way, the national and provincial 2005 input output table was updated, and the same methodology as used in the 2000 model compilation was applied to estimate the MRIO model for IV. Empirical Study IV.1 Interregional inter-industrial interdependency between Beijing and other areas In the context of input output analysis, a (intermediate) sector is linked with other sectors, which supply (intermediate) inputs to it and also with those whose output is used as their inputs (intermediate demands). Therefore, the expansion of a sector induces larger demand for inputs from its input-supplying

10 ASIAN ECONOMIC JOURNAL 270 sectors, and provides greater input supply to the sectors using its output. The former type of linkage is called backward linkage and the latter, forward linkage. The linkage analysis can be applied to the IRIO model. The intraregional and interregional backward and forward linkages can be defined as: b i IBL = and IFL = 1 b ij pq ij pq p q i j where and are the elements of the Leontief inverse matrix and Ghosh inverse matrix, which are denoted as b ij pq d ij pq A and H are the input and distribution coefficient matrix, respectively. The intraregional and interregional backward and forward linkages of 2000 between Beijing and the other two areas are calculated and depicted in Figure 1. The overall backward linkages of Beijing, between Beijing and Surrounding Area and the Rest of China are , and , respectively. Beijing s demand will take up a big share of Surrounding Area and the Rest of China s output. The electronic products (12), machinery (10), transport equipment (11), construction (15) and other manufacturing products sectors possess stronger backward linkage in Beijing, while the electronic products (12), transport equipment (11), textile and wearing apparel (4) and machinery (10) sectors in the Rest of China and chemical products (7), construction (15), p j q d i ij pq B B B D D D 1 B = ( I A) = B B B 1 D = ( I H) = and D D D B B B D D D j d ij pq, Figure 1 Intraregional and interregional backward and forward linkages of Beijing

11 BEIJING OLYMPICS AND REGIONAL GROWTH 271 metal products (9) and wooden products (5) sectors in Surrounding Area have the stronger backward linkage with Beijing. The overall forward linkages of Beijing, between Beijing and Surrounding Area and the Rest of China are , and , respectively. Therefore, a relatively large portion of Beijing s products is provided as greater input supply to the sectors using the output in the Beijing economy. The mining (2), chemical products (7), metal products (9) and other manufacturing products (13) are the sectors in Surrounding Area and the Rest of China that have the stronger forward linkages with Beijing. IV.2 Estimation of Olympic-related investments and classification of Olympic-related investments Estimation of Olympic-related investments The Olympic-related investments are classified into three categories. The first is the investments in Olympic venues and related facilities, which amounts to 23.72bn yuan and can be classified as directly-related investments. 4 The second is the newly-added investments in building infrastructures in Beijing and in other cities, which amount to bn yuan and 8.11bn yuan, respectively. Investments of this category should also be included in the directly-related investments. The third is the investments in infrastructure construction, which were originally included in the development schemes, such as the Tenth Five-Year Plan and are closely related to the Olympic Games, such as investments in environmental protection and transportation projects. These investments in infrastructure construction stand at bn yuan. These investments are treated as indirect investments for the Olympic Games. In this way, we calculated that direct investment for the Olympic Games amounts to bn yuan and indirect investment bn yuan, adding up to a total of bn yuan, as shown in Table 4. Here, we will only analyze the economic impact of the direct investments for the Olympic Games on Beijing and other areas. Classification of Olympic-related investments Of all the Olympic venues to be built or renovated, six are located outside Beijing: Qingdao International Marina, Tianjin Stadium, Qinhuangdao Stadium, Shenyang Wulihe Stadium, Shanghai Stadium and Hong Kong Racetrack. The first three venues mentioned are to be newly built, and the latter three are to be renovated, with a total investment of 1.8bn yuan. Because detailed budgets for these six Olympic venues are not available, and the investment into the venues to be newly built has the lion s share of the total investment outside Beijing, we consider the investment of 1.8bn yuan as the newly-added investment belonging to the Surrounding Area (Tianjin, Hebei and Shandong). Meanwhile, based on the 4. There are some adjustments based on the budget-cut of Olympic-related direct investments, and the data used in the paper is processed based on the adjustments.

12 ASIAN ECONOMIC JOURNAL 272 Table 4 The estimation of Olympic-related direct and indirect investments Items Direct investments Olympic venues and related facilities Newly built Olympics venues Olympic venues to be renovated and expanded Newly built Olympic related facilities Training sites Special facilities for the Paralympics Newly-built infrastructures in Beijing Railway and civil aviation projects Electric power projects Information communication project Newly-built infrastructures in other provinces Indirect investments Environment protection Energy projects Water projects Waste handling Forestation and environment monitoring Transportation projects Track transportation projects City road projects Highway projects Transportation hub projects Others Yuan billion a billion 7.00 billion 2.69 billion billion 0.39 billion 0.38 billion billion billion billion billion 8.11bn b billion billion billion billion 1.44 billion 6.55 billion billion billion billion billion 1.21 billion 2.99 billion Note: a There are some adjustments based on the budget-cut of Olympic-related direct investment. b Estimated. Source: Beijing 2008 Organization Committee, Olympic Action Plan, ratio of investments in the venues and facilities of the Olympic Games to investments in infrastructure construction, we calculated that newly-added investment in infrastructure of the Surrounding Area amounts to 8.11bn yuan. Therefore, the Olympic-related direct investment for the Surrounding Area is 9.91bn yuan. Based on the Olympic Action Plan, with reference to the progress of the projects during 2002 and 2005, we set up a distribution of Olympic-related direct investments from 2002 to 2007 (see data in Table 5). The Olympic-related investments of Beijing and Surrounding Area in each year, from 2002 to 2007, are distributed to each sector based on the structure of fixed capital formation in the model. It is noted as the increase of fixed capital formation (one part of final demand) in each sector from the Olympic-related investments. As a part of aggregate demand, the increment of investments, such as the Olympic-related investments, directly contribute to economic growth. With the growth of national income, consumption is also stimulated. The Olympicrelated investments have a multiplier effect, which can be measured and calculated using an econometric model.

13 BEIJING OLYMPICS AND REGIONAL GROWTH 273 Table 5 Distribution of Olympic-related direct investments from 2002 to 2007 (billion yuan) Total Beijing Surrounding area Based on the current State Information Center of China macroeconometric models of Beijing, Hebei, Tianjin and Shandong Provinces, the investment multipliers were estimated for each region (SIC, 2005). 5 It was found that the investment multipliers were and for Beijing and the Surrounding Area, respectively. Hence, a 1 yuan investment in Beijing will result in an increase of yuan in final consumption and, therefore, yuan in GRP for Beijing; whereas 1 yuan invested in fixed assets in the Surrounding Area will boost final consumption growth by yuan and, therefore, yuan in GRP for the Surrounding Area. We assume that the marginal propensity of consumption is stable, so we can estimate the effects on consumption from Olympic-related investments in these two regions based on the estimated investment multipliers. Then, the stimulated consumption from Olympic-related investments in Beijing and Surrounding Area in each year from 2002 to 2007 is distributed to sectors based on the structure of final consumption in the model. The stimulated consumption from Olympic-related investments in Beijing and Surrounding Area is noted as the increase in final consumption (one part of final demand) in each sector from Olympic-related investments. Summing the change in final consumption and the change in fixed capital formation in each sector of Beijing and Surrounding Area, we get the change of final demand of these two areas induced by Olympic-related investments. Therefore, the impacts of Olympic-related investments on each sector of each area can be estimated using the IRIO approach. IV.3 Impact analysis Impact analysis using the China multiregional input output model 1* F * If the final demand is additionally changed to F* = 2 F, the induced sectional outputs in each of the regions can be calculated as X* = 2 3* F 1* X * X using X* = (I A) 1 3* F*. X 5. The concept of the investment multiplier is from Keynes s theory, which shows the change in national income that would result from a unit change in investment.

14 ASIAN ECONOMIC JOURNAL 274 Table 6 Impacts on Beijing gross regional products of Olympic-related direct investments (2002 to 2007) Average Value (billion yuan) Percentage The matrix form of X* = (I A) 1 F* can be denoted as: X X X 1* 2* 3* ( I A ) A A = A ( I A ) A A A ( I A ) B B B = B B B B B B where B is the Leontief inverse. The new final demands of any one or all the regions have impacts on gross outputs in all regions. Therefore, the impacts are distinguished both sectorally and spatially. Olympic-related direct investment effect on Beijing s annual gross regional product From 2002 to 2007, the Olympic-related investments will contribute 1.77bn, 6.54bn, 14.15bn, 20.12bn and 20.51bn yuan to Beijing s GRP each consecutive year, respectively. These figures are estimated using the MRIO model (Table 6). Based on the economic growth of Beijing from 1996 to 2005 and the Eleventh Five-Year Plan of Beijing, we predict that Beijing s GRP will grow at an annual rate of 11.0 percent in the following years. At the same time, the price index is supposed to rise at an annual rate of 2.5 percent. Under this assumption, Beijing GRP s will additionally increase by 0.41, 1.30, 2.33, 2.95, 2.77 and 2.34 percent as a result of Olympic-related investments. The average annual increase of Beijing GRP is 2.02 percent. The impacts of the investments reach the highest levels in 2005 and 2006, which is consistent with the construction project implementation on Olympic-related infrastructures. At the sector level of the Beijing economy, industries such as services (17), construction (15), electronic products (12), trade and transport (16) and machinery (10) are most affected by the Olympic-related investments. Services (17) and construction (15) account for over 30 and 21 percent of the whole impact, respectively (Table 7). The increased consumption will greatly stimulate the trade and transport sectors and other service sectors, such as hotels, restaurants and other recreation sectors, and construction project implementation of sports venues and Olympic-related infrastructures will contribute greatly to the construction industry. Boosted by the Olympic-related investments, the pattern 1 F F F 1* 2* 3*, 1 F F F 1* 2* 3*

15 BEIJING OLYMPICS AND REGIONAL GROWTH 275 Table 7 Impact on industries of Beijing from Olympic-related direct investments (2002 to 2007) (billion yuan) Total 1. Agriculture Mining Food products Textile and wearing apparel Wooden products Paper and printing Chemical products Non-metallic mineral products Metal products Machinery Transport equipment Electronic products Other manufacturing products Electricity, gas and water supply Construction Trade and transport Services Table 8 Impact on the gross regional products of the surrounding area from Olympic-related direct investments (2002 to 2007) Average Value (billion yuan) Percentage of industrial structure of Beijing, in which the service industry has a bigger share in surrounding areas, followed by secondary and primary industry, will be further strengthened. Olympic-related direct investments annual effect on Surrounding Area From 2002 to 2007, the Olympic-related investments will contribute 0.85bn, 3.14bn, 6.79bn, 10.98bn, 11.71bn and 11.19bn yuan to Surrounding Area GRP each consecutive year, respectively (Table 8). According to the Eleventh Five-Year Plans of Tianjin, Hebei and Shandong and considering the trend of economic growth of these provinces and cities, without the impact of the Olympic Games, we estimate that the GRP of Tianjin, Hebei and Shandong in the Surrounding Area will grow at annual rates of 12.0, 11.0 and 10.0 percent, respectively, in the following 2 years. Assuming that the price index will rise at an annual rate of 2.5 percent in the following years, the Olympic-related investments will add 0.05, 0.14, 0.25, 0.34, 0.32 and 0.27 percent to the GRP of the Surrounding Area annually. The average annual increase is 0.23 percent.

16 ASIAN ECONOMIC JOURNAL 276 Table 9 Impact on industries of the surrounding area from Olympic-related direct investments (2002 to 2007) (billion yuan) Total 1. Agriculture Mining Food products Textile and wearing apparel Wooden products Paper and printing Chemical products Non-metallic mineral products Metal products Machinery Transport equipment Electronic products Other manufacturing products Electricity, gas and water supply Construction Trade and transport Services Services (17), trade and transport (16), mining (2), metal products (9) and chemical products (7) sectors are most affected by the Olympic-related investments in the Surrounding Area. The service (17) sector accounts for over 23 percent of the total impact (Table 9). The pattern of the impact at the sector level is quite different from that in Beijing, although services (17) and trade and transport (16) sectors still hold big shares in the total impact. The impact on the construction industry dramatically decreases as most projects are located in the Beijing area, whereas some other manufacturing industries, such as metal products (9), chemical products (7) and non-metallic mineral product (8) industries expand their productions to fit the demands from Beijing as a result of the Olympic-related direct investments. At the same time, although the industry structure will not change much, the development of the service industry will be faster than secondary industries, and its proportion will rise. Olympic-related direct investments effect on the annual gross regional product for the Rest of China Although the Olympic-related direct investments are mainly carried out in Beijing and the Surrounding Area, the economic links and cooperation between different regions of China are so close that the economic development of the Rest of China will benefit from that of Beijing and the Surrounding Area. Estimation shows that from 2002 to 2007, the Olympic-related direct investments of bn will contribute 1.65bn, 6.11bn, 13.21bn, 20.44bn, 21.79bn and 20.83bn yuan to the annual GRP growth of the Rest of China, as shown in Table 10. We

17 BEIJING OLYMPICS AND REGIONAL GROWTH 277 Table 10 Impact on the gross regional products of the Rest of China from Olympic-related direct investments (2002 to 2007) Average Value (billion yuan) Percentage assume that the GRP of the Rest of China will grow at an annual rate of 10.4 percent and the price index will rise at an annual rate of 2.5 percent in the following years, then Olympic-related investments will add 0.02, 0.06, 0.10, 0.13, 0.14 and 0.13 percent to the GRP of the Rest of China, equivalent to an annual increase of 0.23 percent. Because the scale of the economy of the Rest of China is huge compared with Beijing and its Surrounding Area, the figures of the contribution ratios to GRP are rather small. However, in terms of value, the impact of the Olympic-related direct investments on the Rest of China is near that on Beijing. Comparing the sector level impacts with the other two regions, the impacts on the Rest of China are more diversified. Services (17), Trade and transport (16), chemical products (7), mining (2), electronic products (12), metal products (9), electricity, gas and water supply (14) and agriculture (1) are the sectors most affected by the Olympic-related investments (Table 11). Comparing the impacts of the Olympic-related direct investments to the Surrounding Area with that to the Rest of China, it is evident that distinctive differences exist between the two regions economic links with Beijing. First, the effects on services (17), non-metallic mineral products (8), construction (15), metal products (9) mining (2) and machinery (10) industries on the Surrounding Area are bigger than that on the Rest of China. It is evident that these industries are relatively developed in the Surrounding Area, and they can meet the various demands rising from the Beijing Olympic-related direct investments. It is also clear that these industries in the Surrounding Area fully utilize regional priorities of their own in commanding bigger benefits from the Olympic-related investments. Second, impacts on electricity, gas and water supply (14), chemical products (7) and electronic products (12) for the Rest of China are much higher than that of the Surrounding Area, which is even distinctive when seen from the value term. This shows that these industries in the Rest of China are more competitive than other industries, while the Olympic-investments need comprehensive and strong support from industries of energy production and fundamental industries, such as electricity and chemical sectors, and hi-tech industries, such as the electronic sector. The ratios of annual gross regional product increment to Beijing, the Surrounding Area and the Rest of China The Olympic-related investments of bn yuan will add 14.90bn, 7.45bn and 14.01bn yuan annually to Beijing, the Surrounding Area and the Rest of

18 ASIAN ECONOMIC JOURNAL 278 Table 11 Impact on industries of the Rest of China from Olympic-related direct investments (2002 to 2007) (billion yuan) Total 1. Agriculture Mining Food products Textile and wearing apparel Wooden products Paper and printing Chemical products Non-metallic mineral products Metal products Machinery Transport equipment Electronic products Other manufacturing products Electricity, gas and water supply Construction Trade and transport Services China GRP, respectively, from 2002 to The ratios of annual GRP increment to Beijing, the Surrounding Area and the Rest of China are 0.41, 0.20 and In other words, nearly 60 percent of the impacts of the Olympic-related investments go to regions outside of Beijing. Meanwhile, we can calculate the total added value of GDP by simply summing up the three regions GRP increases, which are 89.38bn, 44.67bn and 84.03bn yuan, respectively. Every 1bn yuan invested directly in the Beijing Olympic Games will help add approximately 0.64bn yuan to the GRP of Beijing, 0.32bn yuan to the Surrounding Area, and 0.60bn yuan to the Rest of China. V. Closing Remarks In the present paper, we have estimated the impacts of Olympic-related investments on regional economic development of China using the IRIO approach. The Olympic Games is not only an important sport and cultural event in Beijing, but its related investments will play an important role in Beijing s economic and social development in the following years. The self-sufficient ratios of most industrial sectors in Beijing are lower than 100 percent, and the interregional backward and forward linkages of a lot of sectors are rather high. The economic development of Beijing, especially induced by the Olympic Games, will surely have great influence on the areas outside of Beijing. The empirical study in the present paper shows that through 2002 to 2007, Olympic-related investments will add 2.02, 0.23 and 0.09 percent to annual GRP in Beijing, Surrounding Area and the Rest of China.

19 BEIJING OLYMPICS AND REGIONAL GROWTH 279 In the present study, we compiled the 2000 China MRIO model and updated it to The investments for the Olympic Games are carried out during 2002 to 2007, but it is difficult to predict the change in technical and final demand structure for each year. Therefore, we have to make a strong assumption that the structure of the economy in years 2002, 2003 and 2004 is the same as that in year 2000, and the structure of the economy in year 2006 and 2007 is the same as that of However, this might enlarge the discrepancy of the result. Appendix 1 Special survey on the input structure and output flows of state-owned enterprises To obtain information on inter-provincial commodity flows, a survey was conducted in 2001 with the support and cooperation of the then State Economic and Trade Commission. We selected 549 state-owned enterprises and business groups that are regarded as important in terms of enterprise size and economic activity in China, and distributed questionnaires to them concerning their figures of input structure and flow of products for As the 549 large-scale enterprises and enterprise groups in the survey cover almost all industries and make up a large share of total national output, the data we obtained represents well the input and output situation of the sectors that they belonged to. 2 Design of the questionnaire In the survey, the enterprises we chose were asked to report the amount, value and source of their input from home (domestic input, classified by provinces) and abroad (import, classified by major economies), and direction of the flow of their products. To obtain more samples and ensure authenticity of the data, the enterprises we surveyed were required to report not only their input and output data, but also their five biggest branches data in terms of output volume. Sector classification To keep in line with common practice, we adopted the China standard industrial classification (GB/T ). In this national standard, the principle for classification and codes for sectors etc. are all specified. As the enterprises we surveyed were from different industries, to obtain statistics on the source of input and direction of flow of output, the sector classification needed to be as detailed and standardized as possible. The 92-sector classification of the national standard fully meets our needs. Details of the questionnaire First, every enterprise that we surveyed was required to provide its name, location, the sector it belongs to, ownership status, name and position of the

20 ASIAN ECONOMIC JOURNAL 280 person who filled in the questionnaire and contact information (address, telephone and fax number, address etc.). Second, some major financial statistical indicators are sought in the questionnaire (e.g. total assets, total liabilities, sales revenue, total profits and employment). Based on these data, we obtain a thorough understanding of the enterprise concerned, and get to know the percentage of output of its branches. Third, the structure of raw material input of these enterprises and enterprise groups was surveyed. There were two tables to be filled: one was input structure and origin; the other was import structure and origin. The former one refers to input of raw materials that were from the domestic market; the latter refers to imported raw products (classified by major economies). The surveyed enterprises (enterprise groups) were required to classify their inputs into sectors according to GB/T , and then to identify the five largest input sectors; the term origin refers to the provinces or municipalities where the input concerned came from. Products imported by the enterprises (enterprise groups) were mainly for inputs, such as raw materials and equipment. The surveyed enterprises (enterprise groups) were again required to report the structure of these imports and their origins, meaning the countries or regions where these imports came from. Finally, the enterprises (enterprise groups) were required to report the output volumes of their five major products and direction of sales (to which province or which country). 3 Result of the Survey Of the 549 sets of questionnaires, 218 sets were returned through post, fax or , accounting for percent of the total. Taking the returned data of branches into account, there were 503 sets of data, among which 381 sets were suitable for further processing, accounting for 75.7 percent of the total. During the survey, we received more than 200 inquiries from these enterprises. We responded to these inquiries with detailed explanations, which helped to enhance the quality of the returned questionnaires. From the perspective of sector classification, of all the 92 sectors in the national standard, 62 sectors were covered in the survey, including agriculture, mining and processing, manufacturing, and the service sectors, accounting for 67.4 percent of the total. However, most enterprises responding to our surveys were from manufacturing industries, and few were from the service industry. 4 Processing of the questionnaires Processing of the 503 sets of returned questionnaires involved the following two stages. First, the returned questionnaires were checked to verify that they were usable. Some of the names of the products filled by the surveyed enterprises were too general to identify which sector they belonged to; in this case, the returned questionnaire was considered as not suitable for use. Second,

21 BEIJING OLYMPICS AND REGIONAL GROWTH 281 for enterprise groups that reported data both as a whole entity and for their major branches, we needed to check if their branches are in the same province/ municipality, and if the sum of their branches was equal to the group as a whole. After the above-mentioned processing, we obtained 381 sets of data that were suitable for use after minor modification. References Arthur Andersen, 1999, Economic impact study of the Sydney 2000 Olympic Games, Centre for Regional Economic Analysis. University of Tasmania, Tasmania. Brunet, F., 1995, An economic analysis of the Barcelona 92 Olympic Games: Resources, financing and impact. In: The Keys to Success: The Social, Sporting, Economic and Communications Impact of Barcelona 92 (eds Miquel M. and Botella M.), pp Servei de Publicacions de la UAB, Barcelona. Chenery, H., 1953, Regional analysis. In: The Structure and Growth of the Italian Economy (eds Chenery H., Clark P. and Pinna, V). U.S. Mutual Security Agency, Rome. China Transportation and Communication Association, 2001, Year Book of China Transportation & Communications for Year Book House of China Transportation and Communications, Beijing. Economics Research Associates, 1984, Community economic impact of the 1984 Olympic Games in Los Angeles and Southern California. Los Angeles Olympic Organizing Committee, Los Angeles, CA. Gu et al., 2003, The impact of Olympic direct investment on Beijing's Economy. In: Study on Beijing Olympic Economy (ed. Liu Q.), pp Beijing Publishing House, Beijing (in Chinese). Humphreys, J. M. and M. K. Plummer, 1995, The economic impact of the state of Georgia of hosting the 1996 Olympic Games. Mimeo. Seig Centre for Economic Growth, Georgia. Ihara, T., 1979, An economic analysis of interregional commodity flows. Environment and Planning, 11, Ihara, T., 1996, Economic Analysis on Region. Chuo-keizai-sya, Tokyo. Isard, W., 1951, Interregional and regional input-output analysis: A model of space economy. Review of Economics and Statistics, 33, pp Kim, J. G., S. W. Rhee, J. C. Yu, J. Hong and K. Koo, 1989, Impact of the Seoul Olympic Games on national development, Korea Development Institute. Leontief, W. and A. Strout Multiregional Input-Output Analysis. In: Structural Interdependence and Economic Development (ed. Barna T.), pp St. Martin s Press, London. Li, S. and Z. Duan, The impact of the Olympic economy to Beijing and the other regions of China. In: Input-Output Theory and Practice in China 2004 (eds Xu X. and Liu Q.), pp China Statistical Press, Beijing. METI (Ministry of Economy, Trade and Industry) (undated), Inter-regional input-ouput table for Japan, Trade and Industry of Japan. METI, Seoul. Moses, L. N., 1955, The stability of interregional trading patterns and input-output analysis. American Economic Review, 45, pp National Bureau of Statistics, 2003, China Statistical Yearbook for China Statistics Press, Beijing. Okamoto, N., Zhang, Y., Hioki, S., Kanazawa, T. and K. Zhao, 2005, A method for constructing an interregional input-output model of China for The Journal of Econometric Study of Northeast Asia, 5, Oosterhaven, J., 1981, Interregional input-output analysis and dutch regional policy problems. Gower, Aldershot, UK. PricewaterhouseCoopers, 2004, European Economic Outlook. PricewaterhouseCoopers. SIC (State Information Center) 2005, Multi-regional input-output model for China Social Sciences Academic Press, Beijing (in Chinese).