28 th Annual IAEE Interational Conference

Transcription

1 28 th Annual IAEE Interational Conference Impacts of Oil Price Changes on Taiwan s Economy - An Input-Output Study Ji Chou Nai-Fong Kuo Su-Ling Peng Jin-Duan Lai 3-6 June 2005, The Grand Hotel, Taipei Globalization of Energy: Markets, Technology, and Sustainability - 1 -

2 Impacts of Oil Price Changes on Taiwan s Economy - An Input-Output Study I INTRODUCTION International oil prices climbed from US$3094 a barrel in 2003 to US$4114 in 2004, or a 33% annual increase The rise in oil prices could be accused of being due to the strong oil demand in China, geopolitically instability in oil producing countries, and/or speculative attacks from hedge funds However, no matter what the reason is, the dramatic changes in oil prices hurt innumerable economies since most of them are mainly oil imported countries The influences of high oil prices may slow the rate of growth and lead to potentially an increase in the inflation especially for an oil importing country In order to evaluate the impacts of high oil prices to the global economy, Global Insight (2004) set several scenarios to analyze what would happen when global oil prices ran too high In the case of oil prices kept above $40/barrel, the global GDP growth rate could drop 03% and 05% in the years 2005 and 2006, respectively Roubini and Setser (2004) investigated the effect of an oil price shock on the US and the global economy from factors such as: the size of the shock, the shock s persistence, the dependency of the economy on oil and energy, and the policy response of monetary and fiscal authorities They concluded that if the oil price shock had a persistent 10% increase in the price of oil, ie an increase from $30 to an average of $35 over the course of 2004, it would reduce the US and G7 economic growth rates by about 03% to 04% Institutions such as Goldman Sachs are more - 1 -

3 pessimistic and revealed that if oil prices increase further to a level closer to $45, then the reduction in the G7 s GDP growth rates may be closer to 1% While Taiwan s economy is far less dependent on oil imports than it was 20 years ago, any changes to oil prices and the global economy still affect the vulnerability of its economy Liang (2004) evaluated that an oil price shock will raise Taiwan s consumer prices up to 024% annually and decrease the economic growth rate about 014% if the price increment was in 10%, and transmitting to a domestic oil price increment of 5% The main affected industries would be electricity and transportation, and their prices would be pushed up 113% and 063%, respectively Hsu (2004) applied the CGE model to simulate the impact of an oil price shock to Taiwan s economy and concluded that the economic growth rate would be slow, the consumer price would increase, the terms of trade would worsen, private investment may be postponed and decrease, basic industries - such as petroleum and coal products, primary metals, chemical and related products, etc - would see adverse effects in output, product prices, and factor demand, and un-skill workers would be affected the most Two scenarios were simulated in CIER s forecast report of July 2004 First, assuming oil prices continuously rise in the future, this would cause wholesale prices, export prices, and import prices to jump 06% against the baseline from the 3 rd quarter to 4 th quarter in 2004 The economic growth rate will decrease by 017% Second, if the oil prices remained at a high level over one year, then the economic growth would be cut by more than 034% Ho (2004) applied a macro-econometrics model to simulate an oil price shock to Taiwan s economy and concluded that: 1 If oil prices rise US$1 against the - 2 -

4 baseline, then the economic growth rate will decrease by 012% and 003 in the first two years, respectively 2 If oil prices increase US$5 against the baseline, then the GDP growth rate will decrease 059% and 014%, respectively, the unemployment rate will rise 006% and 007%, and the consumer price index would rise 056% and 066% 3 If oil prices rise US$10 against the baseline, then the growth rate will decrease 118% and 028%, respectively, the unemployment rate will rise 012% and 014%, and the consumer price index would rise 11% and 132% Lin (2004) applied 45 sectors input-output table price system from Taiwan in 1999 to evaluate the price change in the petroleum refining industry and the consequent effect to the change in price, production, and labor demand to the other industries Two scenarios set the petroleum and coal product prices to add up 10% and 50% The empirical results show that the average domestic prices will rise up 05% and 23%, respectively, the gross domestic output would decrease 151% and 099%, and the number of employed might be reduced by 84,336 persons and 66,246 persons The most damaged industries would be energy-concentrated ones such as mining and quarrying, while the less affected would be in the service sectors The studies reviewed above either use a macro-econometric model or input-output type (including CGE) model to analyze the impact of international oil price changes on the economy The advantage of the macro-econometric model could give us the dynamic change of the variables studied, but its highly-aggregated variable gives us a top-down idea without any details to investigate The input-output model is based on industrial data which can give us a detailed economic structure to investigate Although its static character may limit it only to one time dimension - 3 -

5 analysis, the split of the imports plus domestic content table and the domestic-only table in Taiwan could make up for this disadvantage partially Since the perfect substitution between imports and domestic only happen in the long run, using the imports and domestic table may represent the long-run effect of Leontief s multiplier The imperfect substitution happening in the short run allows us to use the domestic only input-output table to represent the short-run effect Therefore, an input-output analysis might be an appropriate analytical tool to conduct a study of oil price changes on Taiwan Lin s (2004) paper is a recent study in Taiwan using an input-output table to analyze oil price impacts The study, which referred to Miyazawa s (1995) work in setting up the price sub-model to evaluate the price change, is quite successful in the impact on price changes However, the real sector result seems peculiar, particularly as a larger increase in oil prices has a smaller impact on economy A detailed investigation of the impact of increasing price on final demand is needed This paper investigates the impacts of international oil price changes on Taiwan s economy by using an input-output analysis The goals of our study are: 1 establishing a price sub-model and output sub-model in the input-output analysis framework; 2 analyzing impacts on both price and output sectors; 3 using both an import and domestic content table (or A Matrix) and domestic only table (D Matrix) to investigate the short-run and long-run effect; 4 estimating the final demand for household consumption, fixed investment, and imports as well as exports; 5 utilizing consumption and investment bridge matrices to link final demand to an input-output table - 4 -

6 II The Model 1 The Basic Model An input-output model is constructed from observed data for a particular economic area - a nation, a region, a state, etc The economic activity in the area must be divisible into a number of segments or producing sectors Denote the observed monetary value of the flow from sector i to sector j by Z ij Sector j s demand for inputs from other sectors during the year is related to the amount of goods produced by sector j over that same period In addition, in any country there are sales to purchasers who are more external or exogenous to the industrial sectors that constitute the producers in the economy - for example, households, governments, and foreign trade The demands of these units - and hence the magnitudes of their purchases from each of the industrial sectors - are generally determined by considerations that are relatively unrelated to the amount being produced in each of the units The demand for these external units is generally referred to as final demand Thus, if the economy is divided into n sectors, and if we denote by Xi the total output (production) of sector i and by Yi the total final demand for sector i s product, then we may write: X i = Z i1 + Z i2 + + Z ii + + Z in + F i (1) The Z terms on the right-hand side represent the interindustry sales by sector i Thus, the entire right-hand side is the sum of all sector i s interindustry sales and its sales to final demand Equation (1) represents the distribution of sector i s output There is an equation like this reflecting the sales of the output of each of the n sectors 1 = n 1-5 -

7 2 = n 2 (2) n = n1 n2 nn n The ratio of input to output, Z ij / X j, is denoted a ij : ij = ij / j (3) This ratio is termed a technical coefficient The terms input-output coefficient and (direct) input coefficient are also often used In input-output analysis, this technical coefficient is assumed to be unchanging The a ij s are viewed as measuring the fixed relationships between a sector s output and its inputs Once the notion of a set of fixed technical coefficients is accepted, Eqs (2) can be rewritten, replacing each Z ij on the right by a ij X j 1 = a 11 X 1 a 12 X 2 a 1n X n 1 2 = a 21 X 1 a 22 X 2 a 2n X n 2 (4) n = a n1 X 1 a n2 X 2 a nn X n n In matrix terms, we define: - 6 -

8 a a A = a n a a a n a a a 1n 2n nn X X X = 1 X n 2 F F F = 1 2 F n Equations (4) can be rewritten as follows: = A X +, (5) where we let I be the n n identity matrix Notice that the matrix ( I A) has ( a ), ( 1 a )( 1 ) 1 22 a nn 11 on its main diagonal, and since the identity matrix contains zeros everywhere else, ( I A) simply contains a ij terms elsewhere The complete n n system is then just: ( ) = (6) Whether or not there is a unique solution thus depends on whether or not singular ( I A) is Matrix A is known as the matrix of the technical, input-output, or direct input coefficient If A 0 given by I, then ( A) 1 I can be found and the unique solution is = ( ) -1 (7) Here, ( I A) 1 is often referred to as the Leontief inverse Using F for the vector of changes in final demand, X - the vector of the resulting changes in output - is found as: -1 (8) - 7 -

9 If the ratio of employment to output, L ij / X j, denoted as l ij and the ratio of value-added to output, V ij / X j, denoted as v ij are known and given, then the vector of resulting changes in employment and value-added are found as: ^ ^ L L -1 (9) ^ ^ V V -1, (10) ^ ^ where L and V are diagonal matrices 2 The Price Model 21 Physical-based Structural relationships between sectors in an economy perhaps are measured most accurately in physical units At least this eliminates the influence of prices There now follows an equation reflecting purchases of the inputs of each of the n sectors: Here, n X j = P i Q ij + V j j=1,2 n (11) n i= 1 i= 1 P i Q ij shows the intermediate inputs of sector j, and Vj represents the primary inputs (equal to value-added) of sector j With Eq (11) divided by Q j, we can get the physical-based Leontief price model: P j = n i= 1 P i q ij + vj j=1,2 n (12) Here, q ij =Q ij /Q j is the physical-units input coefficient and v j =V j /Q j represents the value-added coefficient (in value terms) 22 Value-based - 8 -

10 Supposing X ij =a ij X j ) represents the value of sector i s output as the intermediate input of sector j, we then have: X ij = P i Q ij = P i (q ij Q j ) (13) The value of sector j s output is: X j = P j Q j (14) According to eq (13) and eq (14), we can get the relationship between a ij and q ij : a ij = X ij / X j = (P i / P j ) q ij (15) Equation (15) means each value-based input coefficient a ij equals its physical-unit input coefficient q ij multiplied by (P i / P j ) Equation (12) is then divided by P j, which is normalized by each sector s price The equation can now be rewritten as: 1= P j = Pj n i=1 n Pi v j q ij + = aij + v j, (16) Pj Pj i= 1 where v j represents sector j s value-added per dollar output Equation (16) can be expressed in matrix form: P * = A P * +V (17) Equation (17) is rewritten as: (I - A )P * =V (17-1) When (I - A ) is a non-singular matrix, eq (17-1) can be rewritten again as: P * = (I - A ) -1 V (18) - 9 -

11 When the primary input (value-added) has been changed, such as increasing the labor cost, we can calculate the change of the price as: P * = (I - A ) -1 V (19) This implies that sector i completely imputes its cost to others However, in fact, each sector s impute ability is not always equal to 1 Equaton (19) can be adjusted as: P * = kˆ (I - A ) -1 V (20) Here, kˆ is a diagonal matrix and the elements on its diagonal are ki, representing the impute ability of sector i 3 The Empirical Model The purpose of this paper is to simulate the impacts of international oil prices The change in oil prices is not actually the factor of value-added Hence, we have to adjust eq (16) According to Miyazawa (1995), we suppose sector n is crude oil, and then eq (16) can expressed as: P j = ΣP i q ij + P n q nj + v j, (21) where P j is the price of sector j, q ij is the physical-units input coefficient, and v j represents the value-added coefficient (in value terms) Along with eq (21), we rewrite eq (18) as: P * = (I - A ) -1 P n q nj +V (22) Term P * represents the normalized price vector, but does not include the crude oil sector, A is the physical-unit input coefficient matrix (not including the crude oil sector), q nj is the ratio of crude oil as sector j s intermediate input to j s output, and P n

12 is the price of crude oil When the price of crude oil changes, the impact of other sectors prices can be measured as follows: P * = (I - A ) -1 q nj P n (23) According to eq (23) and eq (15), we can adjust the input coefficient: a P P + P new new i i i ij = a new ij = aij (24) P j Pj + P j In matrix terms the adjusted input coefficient matrix is denoted as A new, and the Leontief inverse is (I-A new ) -1 When crude oil prices increase, this impacts final demand such as household consumption, capital formation, government expenditures, exports, and imports According to eq (24) and eq (8), we can get the output effects of crude oil price changes as follows: X = I-A new -1 F (25) Since the intermediate input consists of import and domestic products, the A matrix can be divided into import matrix M and domestic product matrix D: A = M + D (26) The A matrix and D matrix represent the long-run effect and short-run effect in our study, respectively

13 III Empirical Analysis Since the electricity industry and transportation sector are regulated in Taiwan, the change of their fares are controlled by the government The reason for CPI prices rising moderately in 2004 was that electricity and public transportation rates remained unchanged in 2004 In addition to considering the long-run versus short-run effect and a 5% versus a 10% increase in domestic oil prices (ie, the price of petroleum refining), we also take into account whether fares of electricity and public transportation reflect the rise in oil prices In sum there are 2x2x2 =8 cases that are simulated In order to catch the impact of oil prices on final demand, we estimate four items of demand for household consumption using the AIDS demand function, ten sectors of demand for fixed investment using the neoclassical investment demand function, and the total export and import demand function We also utilize the bridge matrix to convert the price effect to final demand in the destination and convert the change of final demand in the destination to final demand in origin for consumption and fixed investment We then conduct a multiplier analysis of the impact of final demand change on output1 The impact on the sectoral price is shown in Table 12 The long-run effect as shown in A Matrix is much higher than the short-run effect shown in the D Matrix; a 1 The empirical results of the final demand estimation are available upon request from readers 2 The detailed 51-sector table is shown in A1 Table

14 10% effect is exactly double that of the 5% effect, implying the price sub-model is linear; and the effect on fares not reflecting oil price changes is smaller than fares reflecting oil price changes as expected, but the difference is not much The public utility, transportation, and communications sectors are affected the most In total, there is a 053% increase in total output prices with a 10% increase in petroleum prices and regulated prices, reflecting it in the long run Table 1 Impacts on Sectoral Price - 10 Sectors unit:% A Matrix D Matrix 5% 10% 5% 10% Agricuture Mining Manufacturing Public Utility Construction Commerce Transportation and Communication Financial and Real estate Other Services Public Administration Total Note: 1: Fares are not reflected the hike oil prices in electricity and transportation sectors 2: Fares are reflected the hike oil prices in electricity and transportation sectors Table 2 shows the impacts of output change from the change in final demand caused by the price changes The impact in the long run is much higher than in the short run While the 10% increase in petroleum prices experiences negative results, the 5% increase in prices shows a positive effect, implying that a small change in oil prices may enjoy resource reallocation efficiency Such a kind of efficiency gain is much obvious in the long run than in the short run Among sectors, public utility, manufacturing, and transportation sectors benefit from the change of oil prices, and

15 the other 7 sectors suffer in the long run In the short run the manufacturing sector will suffer if electricity and public utility prices reflect a 10% increase in oil prices Table 2 Impacts on Sectoral Output - 10 Sectors A Matrix D Matrix 5% 10% 5% 10% unit:% Agricuture Mining Manufacturing Public Utility Construction Commerce Transportation and Communication Financial and Real estate Other Services Public Administration Total Note: 1: Fares are not reflected the hike oil prices in electricity and transportation sectors 2: Fares are reflected the hike oil prices in electricity and transportation sectors

16 IV Concluding Remarks Among eight scenarios conducted in this study, when the price of petroleum refining increases 10%, there is no response in electricity and transportation sector prices, and utilizing the domestic transaction table (or D matrix) mimics the case for the year 2004 The result of the simulation shows that total producer prices could go up 017% and cause real total output to drop 019% For the year 2005, the forecast should be based upon an assumption on a fluctuation of international oil prices, and the response of the domestic electricity and transportation sectors This situation is when international oil prices maintain the level for the year 2004, and the domestic electricity and transportation sectors reflect a 10% change in domestic petroleum refining prices that year In this case, total producer prices are expected to rise 027%, and real output will drop 028% in the short run The second possibility is that international oil prices maintain the level of 2004, but the domestic electricity and transportation sectors reflect a 5% change in domestic petroleum refining prices In this case, producer prices are expected to rise 013%, and real output will increase 012% The third possibility is that international oil prices will go to US$50 for West Texas crude oil or US$40 for Dubai crude oil, but the domestic electricity and transportation sectors do not reflect the change in domestic petroleum refining prices In this case, producer prices are expected to rise 008%, and real output will increase 016% The fourth possibility is that international oil prices go to US$50 for West Texas

17 crude oil or US$40 for Dubai crude oil, and the domestic electricity and transportation sectors reflects changes in domestic petroleum refining prices In this case, producer prices are expected to rise 053%, and real output will drop 024% The study also finds that the difference of impacts between responses or not on the domestic electricity and transportation sectors is limited In the case of a rise of 10% in petroleum refining prices, the difference in producer prices is 014% and the difference in output is only 016% when the long-run analysis using A matrix is implemented Although no response on the regulated sectors such as electricity and transportation could stabilize the price fluctuation, it distorts the demand and supply of energy in Taiwan Taiwan is a natural resources scarce economy Cheaper energy prices seem not a suitable policy Reflecting international oil price changes is quite natural It can raise public attention to appreciate the scarcity of natural resources

18 References 1 Deffeyes, Kenneth S, Hubbert s peak, The Impending World Oil Shortage, Princeton University Press, Fatemeh Bazzazan & Peter W J Batey, The Development and Empirical Testing of Extended Input-Output Price Models, Economic Systems Research, Vol 15, No1, Hsu, Shin-Hsun, (2004), The Evaluation of Oil Price Shocks to Taiwan s Macroeconomic, Industrial and Employment, seminar held at the Bureau of Energy, Ministry of Economic Affairs, Sep 2004 (in Chinese) 4 IEA (2004), International Energy Outlook, 5 Liang, Chi-Yuan, (2004), Effect of Oil Price Rising to Taiwan Economy, seminar held at the Bureau of Energy, Ministry of Economic Affairs, Sep 2004 (in Chinese) 6 Lin, SK, (2004), Spillover Effect of Oil Price Change: An Inter-Industry Analysis to Taiwan, Shin Hsin University Thesis, June 2004 (in Chinese) 7 Meckstroth, DK and P Buckley, Implication of Higher Oil Prices for US Industry, Business Economics, 26, pp Miller, Ronald E, and Peter D Blair, Input-output Analysis Foundations and Extensions, Miyazawa, CI, (1995), Introduction to Input-Output Table, version 6, Japan Economic News Publish Co (in Japanese) 10 Roubini, Nouriel and Brad Setser, (2004), The Effect of the Recent Oil Price Shock on the US and Global Economy, August 2004,

19 Global Insight (2004), Oil Price Scenarios: Crisis, Crunch, and Crumble? WEFA Group

20 Table A1 Impacts on Sectoral Price - 51 Sectors unit:% A Matrix D Matrix 5% 10% 5% 10% Agricultural Products Livestock Forest Products Fisheries Minerals Energy Minerals Foods, Beverages, and Tobacco Textile Mill Products Wearing Apparel and Accessories Leather & Leather Products Wood & Wood Products Paper & Paper Products & Printed Matter Petroleum Refining Products Industrial Chemicals Artificial Fibers Plastic Plastic & Rubber Products Misc Chemical Manufactures Coal Products Non-metallic Mineral Products Manufacturing Iron and Steel Products Miscellaneous Metals Metallic Products Machinery Household Electrical, Electronic Products Information Products Communication Equipment Electronic Components & Parts Electrical Machinery & Other Appliances Transport Equipment Other Manufactures Electricity Gas City Water Construction Commodities Trading Restaurant & Hotel Services Railroad Vehicle Transportation Other Land Transportation Water Transportation Air Transportation Services Incidental to Transport & Travel Warehousing Post Services Telecommunication Services Finance & Insurance Services Real Estate Services Business Services Education & Medical Services Other Social, Personal and Related Community Services Public Administration Total Note: 1: Fares are not reflected the hike oil prices in electricity and transportation sectors 2: Fares are reflected the hike oil prices in electricity and transportation sectors

21 Table A2 Impacts on Sectoral Output - 51 Sectors A Matrix D Matrix 5% 10% 5% 10% Agricultural Products Livestock Forest Products Fisheries Minerals Energy Minerals Foods, Beverages, and Tobacco Textile Mill Products Wearing Apparel and Accessories Leather & Leather Products Wood & Wood Products Paper & Paper Products & Printed Matter Petroleum Refining Products Industrial Chemicals Artificial Fibers Plastic Plastic & Rubber Products Misc Chemical Manufactures Coal Products Non-metallic Mineral Products Manufacturing Iron and Steel Products Miscellaneous Metals Metallic Products Machinery Household Electrical, Electronic Products Information Products Communication Equipment Electronic Components & Parts Electrical Machinery & Other Appliances Transport Equipment Other Manufactures Electricity Gas City Water Construction Commodities Trading Restaurant & Hotel Services Railroad Vehicle Transportation Other Land Transportation Water Transportation Air Transportation Services Incidental to Transport & Travel Warehousing Post Services Telecommunication Services Finance & Insurance Services Real Estate Services Business Services Education & Medical Services Other Social, Personal and Related Community Services Public Administration Total Note: 1: Fares are not reflected the hike oil prices in electricity and transportation sectors 2: Fares are reflected the hike oil prices in electricity and transportation sectors unit:%

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