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CESifo Area Conference on Global Economy 10 – 11 December 2004 CESifo Conference Centre, Munich Globalization Distance Metrics for the World Economy Ray Riezman, John Whalley and Shunming Zhang CESifo Poschingerstr. 5, 81679 Munich, Germany Phone: +49 (89) 9224-1410 - Fax: +49 (89) 9224-1409 E-mail: [email protected] Internet: http://www.cesifo.de Globalization Distance Metrics For The World Economy ∗ Raymond Riezman Department of Economics, University of Iowa Center for Economic Studies - Institute for Economic Research (CES-ifo, Munich) John Whalley Department of Economics, The University of Western Ontario National Bureau of Economic Research, Inc. (NBER) Center for Economic Studies - Institute for Economic Research (CES-ifo, Munich) The Centre for International Governance Innovation (CIGI, Waterloo) Shunming Zhang School of Business, Nanjing University Department of Economics, The University of Western Ontario December 2, 2004 Abstract An earlier paper of ours discusses metrics of globalization between fully integrated and trade restricted equilibria for individual price taking economies. These reflect the distance from full global integration due to trade barriers, barriers to factor flows, barriers to international financial intermediation, slowed technological diffusion and other economy specific features yielding less than full integration into the global economy. Here we discuss distance measures from integrated free trade for the whole of the global economy. Important differences arise relative to single economy metrics since globalization measures for the world can be small if small economies are integrating into large economies, rather than all economies treated as separating integrating into a larger world. Importantly globalization distance measures for individual economies are also shown to depend on both domestic and foreign barriers to goods and factor flows. ∗ This is a draft of a paper to be presented at a CES - ifo conference to be held in Munich, Germany, December 10 - 11, 2004. The second author acknowledges financial support from SSHRC (Ottawa). 1 1 Introduction An earlier joint paper of ours (Riezman, Whalley and Zhang (2004)) discussed how close particular economies are to an equilibrium characterized by full integration into the global economy (such as free trade in goods, full factor mobility, or both) where each economy was treated as a small open price taking economy and we assumed such equilibria are unique. The motivation we offered was that there was an emerging popular literature in the Economist, Foreign Policy and other media outlets reporting indices of globalization by country, but little or no research literature on appropriate metrics. We suggested that what was at issue was an explicit comparison between equilibria using distance metrics 1 , and we also highlighted the main focus of prior general equilibrium literature as being on comparative statics and issues of existence, uniqueness, and stability (see Arrow and Hahn (1971), and Mas-Colell (1985)) not measures of distance between equilibria. We formalized alternative metrics of globalization as distance measures between equilibria, and explored the behaviour of these metrics in the single price taking economy case using data to yield simple forms of integration restricted equilibria for some sample economies. We used data for ten OECD countries (Australia, Canada, Germany, Italy, Japan, Korea, Mexico, Norway, UK, US) and made calculations of globalization metrics for each using these measures. These were chosen as a sample of countries varying by size, level of income per capita, trade pattern, and size of trade barriers. Our conclusion was that globalization distance metrics can behave in different ways and numerical measures of the degree of globalization for individual economies can therefore be hard to interpret. No unambiguously preferred metric seemed to offer itself despite the growing importance attached to distance metrics in globalization debate. In this paper our focus is instead globalization measures on the whole of the global economy rather than on single economy measures, and we ask how far the world is from complete globalization or integration (or integration). We first show how measures similar to those for individual economies can be constructed using a model a the global economy taken as a single entity. Some yield a single index measure, others measures for individual economies. To 1 Measures of distance between equilibria are also critical in a number of other current subareas of economics. In the calibration area, for instance, inexact calibration (see Dawkins, Srinivasan, and Whalley (2001)) involves choosing parameter values for equilibrium structures so as to produce model generated equilibria as close as possible to observed data (pre-adjusted for compatibility with model equilibrium conditions), and closely related metrics of distance between equilibria are also needed here. 2 implement certain of the measures we propose we require some form of global social welfare function, which we also discuss in the text. We then discuss how this approach to globalization metrics affects perceptions of the extent of globalization, compared to our earlier approach. For large economies, with endogenous global prices as trade and other barriers removed or modified, little change in domestic prices need occur. In effect, small economies will now integrate into larger economies and globalization distances for large economies may be small even if their own barriers are large. Hence globalization metrics constructed for individual economies can be misleading if their relationship with the wider global economy is not also considered. Any computed variance in separately constructed measures across individual economies conveys little about the closeness of the world to full integration. Also, barriers in foreign markets influence the globalization metric for a given economy, as well as (and in some cases more so than) barriers employed at home. Our conclusion is that this new round of analysis of globalization metrics casts further doubts over the interpretation of measures of globalization that percolate the public domain beyond those raised by our earlier paper. 3 2 Globalization Distance Measures in A Global Economy In this section we present some analytics for distances measure which can be used to assess how close to or far away an equilibrium for the world economy is from that which would characterize full integration by all economies into the global economy (globalization). We assume that we are to compare a global trade (or factor flow) restricted equilibrium to a full integration equilibrium and only one of these equilibria will be observed (typically a global equilibrium in the presence of trade and factor flow restrictions). We first calibrate a model of global trade to data in the presence of such restrictions, and then use the parametrization generated for this model to compute an unobservable free trade global equilibrium. Globalization measures involve some form of pairwise equilibrium comparison. We make the strong assumption that both free trade and restricted equilibria are unique 2 . These measures are closely related to those for individual economies presented in Riezman, Whalley and Zhang (2004). We begin with simple measures of distance between free trade and trade restricted global equilibria calculated by summing the squares of differences across equilibria in endogenous variables (prices, quantities). As Riezman, Whalley and Zhang (2004) note there are several difficulties which arise with such measures. One is that if price variables are involved they are not invariant to alternative price normalizations. Another is that the rationale for including all variables in such measures (such as both prices and quantities) is not clear, while neither is it clear that some variables should be excluded. If only a subset of variables are included in such distance measures one has to rationalize which they are and why they should be so used. Such metrics could also involve exogenous variables such as endowments, although for simplicity these are not used here. A second type of distance measure we use involves computing excess demands in the global economy at non-equilibrium prices. For these measures we take the prices from one equilibrium and use them in the model of the global economy generating the other equilibrium and calculate the size of the implied global excess demands. Thus, if we calibrate our global model using data generated in the presence of tariffs, we can introduce the free trade equilibrium prices into the associated model parameterzation and compute global excess demands (i.e. the sum of country imports and exports). We take the absolute value of the excess demands generated in this way relative to total global demands as the distance measure between the two equilibria. 2 But see the discussion of the likelihood of multiplicity of equilibria in models similar to those we use in Kehoe (1991) and Whalley and Zhang (2004) 4 These are model dependent measures in that the numerical value of the distance measure will vary as the underlying model parametrization used to calibrate to the equilibrium data in the presence of country tariffs changes (say, as elasticities of substitution and share parameters in CES functions change). These are also problems with these types of measure and these are similar to those identified by Riezman, Whalley and Zhang (2004) in the small open economy case. One is that such measures are only operational in the sense of producing a single value where there are point-topoint mappings (a pure exchange economy), not correspondences (economies with production). Another is that one can have pairs of equilibria for this class of measures which yield sharp differences in distance measures (close, far) in prices and quantities. Finally, we use a third class of global distance measures constructed in model parameter space. These are measures motivated by the Debreu (1951) coefficient of resource utilization, which determine the maximum proportional uniform shrinkage in the endowments of the global economy which is possible subject to the constraint that global utility (in the form of a global social welfare function) is preserved as distortions are removed, and provides a measure of the degree of inefficiency of the global economy. Using this type of globalization metric implies that, in a two good, two factor model of the world economy, one computes the maximal proportional shrinkage for each of the two factor endowments which preserves global utility as trade barriers are removed. As Riezman, Whalley and Zhang note for the single economy case, there is seemingly no satisfactory way of choosing between these alternative measures since there is no single measure which dominates all others. Each will yield a numerical measure of distance, and these metrics will behave differently across alternative pairwise equilibrium comparisons. One measure may indicate a large distance between equilibria and another small. The interpretation of such measures thus becomes an issue. What can one conclude, for instance, if endowments change by, say, 10% in a Debreu type measure in comparsions across equilibria while an excess demand calculation implies say a 50% measure for the same tariff barrier. Our purpose is thus to raise the issue of which distance measures to use in globalization debate and why, rather than definitively resolve the issue of which measure to use in all circumstances. To show more concretely how measures of distance can be constructed between globalized and non-globalized equilibria, we take the simple case of a global economy with N countries, 2 produced goods and 2 factors of production in each. For this economy, there will be various 5 features which limit integration of national economies into the global economy, such as tariffs, domestic taxes, quotas and other policy interventions. We assume these are present in the observed trade restricted (tariff) equilibrium, but absent in the hypothetical globally integrated equilibrium. For country n, we assume two input CES production functions for the two goods which are given by Qnj = φnj σnj −1 σnj f =L,K δnjf Tnjf σnj σnj −1 , j = 1, 2 (1) where Qnj denotes output of the j-th industry, φnj is the scale or units parameter, δnjf is the distribution parameter ( f =L,K δnjf = 1), Tnjf is the labor and capital factor input (f = L, K), and σnj is the elasticity of factor substitution. The factor demand functions derived from cost minimization for these production functions (1) are: Tnjf = Qnj φnj σnj −σnj 1−σnj 1−σnj Dnf Dnf δnjf , δnjf δnjf j = 1, 2 f = L, K (2) f =L,K where Dnf is the price of factor f (per-unit factor costs for the industry). World prices for goods are P0j and are exogenous to the model, and the tariff rate on imports of goods j is rnj . rnj > 0 if good j is imported (Xnj > Qnj ), and rnj = 0 if good j is exported (Xnj ≤ Qnj ). The domestic price of good j is Pnj = (1 + rnj )P0j . On the demand side of the economy we consider a representative consumer with a CES utility function given by Un = j=1,2 1 σn σn −1 σn αnj Xnj σn σn −1 (3) where Xnj is the quantity of good j demanded by the consumer, αnj is the share parameter ( j=1,2 αnj = 1), and σn is the substitution elasticity in the consumer’s CES utility function. Consumer income has three parts, endowment income f =L,K Dnf Wf , tariff revenue Rn = j=1,2 rnj P0j Znj and an exogenous foreign resource transfer Bn = j=1,2 P0j Znj reflecting the financing of any trade imbalance 3 . In = Dnf Wnf + Rn + Bn (4) f =L,K 3 We incorporate the trade imbalance in this way since typically actual economy data used in model calibration will not be consistent with zero trade balance. 6 where Wf is the consumer’s endowment of labor and capital, Znj = Xnj − Qnj is the import and export of good j (excess demands for goods). The consumer’s budget constraint in country n is Pnj Xj = In (5) j=1,2 where Pnj is the consumer price for good j. Demand functions from utility maximizing behaviour are Xnj = σn Pnj αnj In 1−σn , j =1,2 αnj Pnj j = 1, 2 (6) The equilibrium conditions in this model are that world market demand equals world market supply for goods and also for factors in each country, and profits are zero in each industry. These equilibrium conditions are that [1] Demands equal supply for goods in the world Xnj = n=1,··· ,N Qnj , j = 1, 2 (7) n=1,··· ,N [2] Demands equal supply for factors in each country Tnjf = Wnf , f = L, K, n = 1, · · · , N (8) j=1,2 [3] Zero profit conditions hold in both industries in each country Dnf Tnjf = Pnj Qnj , j = 1, 2, n = 1, · · · , N (9) f =L,K In this global economy model, an equilibrium is characterized by factor prices DnL and DnK , and world prices P01 and P02 , such that equations (7) - (9) hold. From equations (2) and (9) we have Dnf 1−σnj δnjf = [φnj Pnj ]1−σnj , δnjf j = 1, 2 (10) f =L,K Defining excess demand of goods as Znj = Xnj − Qnj , j = 1, 2 (11) and excess demands for factors as Ynf = Tnjf − Wnf , j 7 f = L, K (12) the equilibrium conditions can be rewritten as [1] excess demands for goods in the world are zero, i.e. n=1,··· ,N Znj = 0, j = 1, 2; [2] excess demands for factors in each country are zero, i.e. Ynf = 0, f = L, K, n = 1, · · · , N ; and [3] zero profit conditions hold in both industries (i.e. Equation (9)). At such an equilibrium we can also show that the trade imbalance constraint is satisfied in each country. Using the full employment condition (8) and zero profit conditions (9), we have In = Pnj Qnj + Rn + Bn (13) j=1,2 from equation (4). Rewriting the budget constraint (5) as Pnj Xnj = j=1,2 that is, Pnj Qnj + Rn + Bn (14) j=1,2 (1 + rnj )P0j Znj = j=1,2 Pnj Znj = j=1,2 rnj P0j Znj + Bn (15) j=1,2 from the excess demand of goods equation (11), and P0j Znj = Bn (16) j=1,2 which is the trade imbalance. Where distance metrics of globalization for the world economy require a global social welfare function (as for the Debreu type measures), we assume a set of share parameters for each countries as follows Q0n1 + Q0n2 0 0 . n=1,··· ,N (Qn1 + Qn2 ) λn = (17) Global utility is thus, for simplicity, assumed to be additive across the N countries using the share parameters, i.e. U = n=1,··· ,N λn Un . Into this economy, we can introduce a wide range of trade distorting instruments in each country beyond tariffs, such as domestic taxes and quotas. All of these policy interventions will limit the degree of integration of national economies into the wider global economy. Assuming for now that equilibria in this global economy are unique, this economy has two equilibria for cases with and without country trade policy interventions. We label these restricted and unrestricted economies as E (1) and E (2) . Typically we will have an observed equilibrium E (1) in the presence of trade barriers and a model parametrization will be calibrated to this equilibrium data so as to be consistent with it. The other equilibrium E (2) will be computed as a counterfactual equilibrium. 8 We can construct various distance measures between equilibria for different barriers applying to imported goods in each country, including barrier elimination. These equilibria are charac(1) (1) (1) (1) (1) (1) (2) (2) (2) (2) (2) (2) terized by the variables (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) and (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) for n = 1, · · · , N , j = 1, 2 and f = L, K. Riezman, Whalley and Zhang (2004) define simple normalized Euclidean distance measures between restricted and unrestricted small open economy equilibria for each country in prices and quantities as MDn = MP n = MQn = MT n = f =L,K (1) (2) 2 Dnf − Dnf 1 (m) m=1,2 f =L,K Dnf 4 (1) (2) 2 P − P j=1,2 nj nj 1 (m) m=1,2 j=1,2 Pnj 4 (1) (2) 2 Q − Q j=1,2 nj nj 1 (m) m=1,2 j=1,2 Qnj 4 (1) (2) 2 − T T j=1,2 f =L,K njf njf (18) (19) (20) (21) 1 (m) T 8 m=1,2 j=1,2 f =L,K njf (1) (2) 2 j=1,2 Xnj − Xnj (22) MXn = 2 1 (m) X 4 m=1,2 j=1 nj We compute global normalized Euclidean distance measures between restricted and unrestricted global equilibria in prices and quantities as (1) (2) 2 − P P j=1,2 0j 0j MP 0 = 1 (m) P 4 m=1,2 j=1,2 0j 2 (1) (2) j=1,2 n=1,··· ,N Qnj − Qnj MQ = 2 1 (m) m=1,2 n=1,··· ,N Qnj j=1 4 2 (1) (2) X − X j=1,2 n=1,··· ,N nj nj MX = 2 1 (m) m=1,2 n=1,··· ,N Xnj j=1 4 9 (23) (24) (25) We also construct global excess demand measures between the two economies: E (1) and (1) (1) (1) (1) (1) (1) (2) (2) (2) (2) (2) (2) E (2) and their equilibria: (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) and (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) for n = 1, · · · , N , j = 1, 2 and f = L, K, are the associated variable values. We assume E (1) in the presence of barriers is observed, and we then introduce the prices from E (1) into the model parametrization supporting E (1) and compute excess demands. This procedure does not yield an equilibrium solution to the model, but does suggest locally how large excess demands for goods (trade) would be were trade barriers to be eliminated in all countries. We construct excess demand measures in either factor space in each country, or in goods (2) space across all countries. In the factor space case, we introduce the production values Qnj (1 ) into model supporting Economy E (1) , and evaluating excess demand functions for factors Ynf (1 ) (2) given by equation (12). Given Qnj , we solve for Tnjf from Equation (2), for j = 1, 2 and f = L, K, (1 ) Tnjf = (2) Qnj φnj −σnj (1) Dnf δnjf δnjf σnj 1−σnj 1−σ (2) nj Qnj (1) = (1) Tnjf δnjf Qnj (1) B nf f =L,K (1 ) and generate the excess demands for factors Ynf = (1 ) j=1,2 Tnjf (26) − Wnf (f = L, K) as in equation (12). This yields a factor excess demand measure between E (1) and E (2) for country n as (1) RF n = (1) f =L,K (1 ) Dnf |Ynf | (1) (1 ) f =L,K Dnf Tnjf j=1,2 (27) In this evaluation of factor excess demands full employment conditions do not hold, and so consumer’s income is given by In(1 ) = f =L,K (1 ) (1 ) (1) Dnf Wnf + j=1,2 (1) (1 ) rnj P0j Znj + Bn (28) (2) where Znj = Xnj − Qnj . (1 ) Solving for consumption Xnj from Equation (6), for j = 1, 2, (1) (1) (1 ) (2) αnj D W + r P [X − Q ] + B 0j n nf f =L,K nf j=1,2 nj nj nj (1 ) Xnj = (1) σn (1) 1−σn [Pnj ] j αnj [Pnj ] (29) we also generate a global excess demand distance measure between E (1) and E (2) using goods (1 ) excess demands Znj from Equation (11). This yields a goods excess demand measure of distance for country n as (1) RGn = (1) (1 ) j=1,2 Pnj |Znj | (1) (1 ) j=1,2 Pnj Xnj 10 (30) Global excess demand globalization measures in goods space between economies are (2) calculated by introducing the world prices P0j into model supporting Economy E (1) , to get (1 ) the domestic good prices Pnj , (1 ) (1) (2) Pnj = (1 + rnj )P0j (31) (1 ) (1 ) we then solve for factor prices Dnf from equation (10), compute production Qnj and factor (1 ) (1 ) use Tnjf from equations (2) and (8), and obtain consumer income In (1 ) (1 ) and consumption Xnj in equations (31) and (32), then goods excess demands Znj from Equation (11). This yields a goods excess demand measure of distance between E (1) and E (2) as (1) RG j=1,2 = j=1,2 (1) (1 ) (1) (1 ) n=1,··· ,N Pnj |Znj | n=1,··· ,N Pnj Xnj . We can finally construct Debreu type shrinkage measures of distance between the two (1) (1) (1) (1) (1) (1) global equilibria: E (1) and E (2) and their characteritics: (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) and (2) (2) (2) (2) (2) (2) (P0j , Dnf , Pnj , Qnj , Tnjf , Xnj ) for n = 1, · · · , N , j = 1, 2 and f = L, K. To do this we use (2) P0j in the model specification supporting Economy E (1) , and compute a global equilibrium for the case where tariffs are eliminated in all countries and there is a supporting endowment of (1 ) (1) (1) factors Wnf = [1 + RDn ]Wnf which yields unchanged utility for the representative consumer (1) n. RDn yields the Debreu type shrinkage measure of distance for country n between the two equilibria E (1) and E (2) . For the global economy, there is a scalar supporting endowment of (1 ) (1) (1) (1) factors Wnf = [1 + RD ]Wnf (for all n = 1, · · · , N ) which yields unchanged global utility. RD yields the Debreu type shrinkage measure of distance between the two equilibria E (1) and E (2) . 11 3 Applying Globalization Distance Metrics to the Global Economy To investigate how the globalization distance measures set out above behave in practice, and what numerical measures of globalization distance are implied for the world economy, we have used the simple 2 good, 2 factor global trade model set out above to construct globalization distance measures between the actual world economy and hypothetical fully integrated world with no barriers between countries involving a sample of OECD economies and a residual rest of world (ROW). We treat Australia, Canada, Germany, Italy, Japan, Korea, Mexico, Norway, UK, US as separate OECD economies which differ in size, their trade patterns, their levels of development, and their degree of openness and add in a residual rest of the world yielding a 10 region model. We use the OECD STAN database for 2000 which provides consistent data on consumption, production, and trade for all OECD economics. Into this we also introduce measures of average tariff rates on imports taken from OECD sources. We find this OECD data simpler to use and in some ways more applicable to our needs than the GTAP data base currently widely used by trade equilibrium modellers. We construct an initial base case global data set reflecting an equilibrium for each of these economies in the presence of domestic trade restrictions, which for simplicity we limit to tariffs. The equilibrium data for each economy is set out in Table 1. We have generated this by taking information from the STAN database in value terms in domestic currency from which we assemble consumption, production, factor by sector, and net trade for each country for the year 2000. 12 13 73,354 55,593 33,058 K3 - M 94,772 62,681 104,127 20,227 198,899 82,908 112,580 11,880 310,640 15,870 423,220 27,750 Germany 49,096 M 122,450 M 197,570 48,865 -1,329 -34,043 303,129 76,083 -120,091 48,333 182,608 62,088 -37,996 26,554 98,397 27,220 122,207 8,314 220,604 35,534 Italy 92,936 17,376 -19,178 9,604 52,608 5,390 59,506 2,382 112,114 7,772 Japan 0.673166 0.105931 M 0.000000 0.000000 0.000000 0.208675 0.923392 105,882 68,392 -57,401 42,072 103,613 23,205 59,670 0.000000 0.158008 0.009275 3,115 163,283 0.000000 0.368725 0.000884 0.348223 0.000000 0.105719 1,159,129 141,163 145,532 -131,025 702,358 221,083 311,239 51,105 1,013,597 272,188 Mexico 0.032875 0.000000 0.113496 220,763 52,604 78,985 -305,955 44,118 333,498 97,660 25,061 141,778 358,559 Norway 0.041334 0.000000 1.515850 190,470 33,784 36,799 -0,325 43,188 27,946 110,483 6,163 153,671 34,109 UK 0.033641 0.109535 1.000000 1,841,611 356,465 321,348 89,103 538,482 178,172 981,781 89,190 1,520,263 267,362 US 0.000000 0.000000 1.000000 1,285,722 61,297 -34,893 -155,999 530,964 157,434 789,650 59,861 1,320.615 217,295 ROW 2 for the underlying data used to generate tariff averages reputed here. 4 See Table 3 In this table, M and NM denote Total Manufacturing and Non Manufacturing (Agriculture, Hunting, Forestry and Fishing; Mining and Quarrying); L and K denote Labour and Capital. JPY 109 , KRW 109 , MXP 106 , NWK 106 , GBP 106 , USD 106 , and USD 106 . 2 These value units in domestic currency are AUD 106 , CAD 106 , EUR 106 , EUR 106 , 0.000000 0.208675 0.923392 1 Sources: OECD STAN database plus Table 2. 0.000000 NM Initial Tariff Rate on Imports4 0.581567 Korea 26,320 Exchange Rate (How Many USDs Are Equal to 1 Unit Local Currency) 32,172 NM Value of Consumption -23,421 NM Value of Net Trade (Imports - Exports) 45,088 40,296 10,505 K - NM 3 L -M 3 L3 - NM Value of Factor Use M 3 NM3 Value of Output Canada and a Residual ROW1 (Country Data in Domestic Currency2 ) Value Data Reflecting Assumed 2000 Benchmark Equilibria for a Sample of OECD Economies Australia Table 1 We use a two sector classification for each economy, and we first ignore all service related and non-tradable transactions such as utilities, government activity, retailing, wholesaling, distribution, banking, and financial services. We consider two aggregate traded goods sectors which we take to reflect manufacturing and non-manufacturing activity. From the STAN data, “total manufacturing” is taken as manufacturing and “agriculture, fishing, forestry, and mining / quarrying” are taken as non-manufacturing. The 2 × 2 case requires as many factors as goods in the model, and so this is a relatively easy case to implement. Subsequent applications of this approaching can easily (but more tediously) be applied to multisector multifactor models and the change of level aggregation in data will clearly affect the numenical value of globalization distance measures. STAN data give value added according to this sectoral classification, and also provide data on compensation of employees by sectors. The return to capital by sector in each country is constructed by residual as the difference between the two. We make the strong assumption that the output of each sector is given only by the value added originating in the sector, and we ignore all intermediate transactions. This yields data on output and factor use by sector in value terms for each country for our benchmark year. This data is in value terms, and to produce equilibrium data on both prices and quantities we need to adopt a units convention for the measurement of both goods and factors. We follow the convention attributed to Harberger (1962) and discussed in Shoven and Whalley (1992) of assuming unitary prices for factors, and unitary world prices for goods in the trade distorted equilibrium. This yields domestic prices for imports as one plus the tariff rate. We use the trade data in STANs on a net trade basis and net out imports and exports (again in value terms) by good (for our 2 good classification) for each country. This yields consumption as production plus net trade. This substantially reduces trade volumes as they appear in each country model relative to published trade data. Most of the OECD economies we consider are net exporters of manufactured goods. Trade balance does not hold for this net trade data by country since some countries have trade surpluses and other (notably the US) have trade deficits. One procedure is to modify the data to force trade balance; another is to use a model which incorporates a fixed trade imbalance (which is non-zero). We choose the latter procedure. For the US, this yields the feature that both goods are imported, and financed by foreign resource transfers supporting the observed trade imbalance. We use tariff rate data from OECD sources as our trade barrier representation in the re- 14 stricted equilibrium. This data (also used by Riezman, Whalley and Zhang (2004)) is presented in Table 2 which also reports the tariff data we have used to produce on for our barrier estimates. This data is from OECD Sources on bound tariff rates by Harmonized Nomenclature section headings, and gives the fraction of line items in specified tariff lines falling in numerical ranges of tariff rates. There is a considerable literature on constructing tariff averages, which for simplicity we ignore. We use statutory rather than effective tariff rates, and we have aggregated this data using simple means for in sample ranges. We do not employ trade weighted average, nor use applied rather than bound tariff rates. The benchmark equilibrium in Table 1 is taken as observed for our representation of the global economy. We calibrate our global model to this data which we assume for now to be generated in the presence of tariffs as the only trade barrier which creates distance from full integration. We then apply the procedures set out in the previous section and construct globalization metrics for the world economy. The procedures set out in Section 2 are relatively simple to implement, but there are a number of issues of detail which arise. One is that in a model in which factors are fully mobile within each economy production frontiers in each economy will be close to linear for conventional fractional forms such as Cobb Douglas and CES unless share and substitution parameters differ sharply across sectors. This means that even for small barrier changes specialization will occur and so globalization distance measures may only be able to be computed for this model for modest barrier reductions rather than barrier eliminations. In reality there are many barriers which limit integration into the global economy including other trade measures (quotas, dumping and countervailing daties), national standards, differential regulation of financial institutions, transportation regulation, agricultural policies, and many others. Each of these would need an explicit model representation which world sharply differ from a representation by an advalorem equivalent tariff if they were to be sensibly incorporated into such analyses. Extensions of this approach can be used to analyze now these barriers also affect globalization measures. We have not done so since our purpose is to illustrate a general approach to constructing globalization metrics rather than provide definitive estimates. 15 16 16.2 1.6 0.0 44.0 4.2 1.4 18.7 19.6 28.1 17.7 2.5 11.6 1.7 0 − 5% 5 − 10% 10 − 15% 15 − 20% 20 − 50% > 50% Duty Free 0 − 5% 5 − 10% 10 − 15% 15 − 20% 20 − 50% > 50% 0.0 0.2 7.1 8.7 39.5 16.4 28.6 0.9 6.3 26.6 0.0 0.3 23.9 42.1 Canada 0.0 0.2 0.4 7.0 27.3 43.0 22.2 17.0 11.2 12.2 7.7 9.3 16.1 26.5 Germany 10.5931 M 5.7168 8.1469 4.1334 20.8675 9.6 10.3 22.0 1.2 6.7 19.1 31.0 0.0 0.2 0.4 7.0 27.3 43.0 22.2 4.1334 20.8675 2.3100 15.8008 0.0 0.4 0.2 2.7 14.5 28.4 53.8 Manufacturing 17.0 11.2 12.2 7.7 9.3 16.1 26.5 11.8107 36.8725 0.2 10.5 8.2 36.8 23.8 7.1 13.5 38.6 8.1 7.2 19.1 16.6 8.4 2.2 Korea 0.0 99.2 0.3 0.0 0.2 0.0 0.2 84.8 0.3 0.0 8.4 3.0 3.3 0.1 Mexico 34.8223 65.1276 2 Sources: Tariffs and Trade: OECD query and reporting system, OECD 2000. 1 Note: Calculations are report 6 - digit HS section headings. 10.7450 NM Japan Non Manufacturing Italy Calculated Country Average Tariff Rates (Percentage) 32.6 Australia Duty Free Ranges Binding Tariff by Country Used to Calculate Country Tariff Rates in Table 11 2 3.2875 12.8729 0.2 0.0 0.0 10.6 13.7 31.4 44.1 4.2 0.3 14.3 56.4 0.4 0.9 23.4 Norway 4.1334 20.8675 0.0 0.2 0.4 7.0 27.3 43.0 22.2 17.0 11.2 12.2 7.7 9.3 16.1 26.5 UK US 3.3641 10.9535 0.0 0.8 1.3 5.6 15.6 39.6 37.2 0.4 4.7 48.1 0.1 2.0 16.7 27.9 OECD Data on Tariff Intervals by HS Section (Post-Uruguay Round Bound Rates) (% of Tariff Nomenclature Section Headings in Specified Rate Ranges by Country) Table 2 Table 3 presents the calibrated model parameter values for our global model, along with model data on endowments and tariff rates. The calibration procedures we use are set out in Dawkins, Srinivasan and Whalley (2001). To implement calibration we rely on a simple literature search to generate substitution elasticities by sector by country, and we use values roughly consistent with those reported in Piggott and Whalley (1985) and Hammermesh (1993) of 2.0 in non manufacturing and 0.5 in manufacturing. We use each country model to compute a new global equilibrium with reduced country tariffs. We are able to then construct sum of squares distance measures between these equilibria, as set out in previous section. We are also able to use the model parameterizations supporting each equilibrium to construct excess demand distance measures, and Debreu type shrinkage measures of distance of economies from full integration (globalization). 17 18 1.804019 M 1.998893 1.858949 0.524728 0.674450 0.475272 L-M K - NM K-M 0.488235 0.637729 0.511765 0.362271 0.796049 M 78,146 K 157,453 124,354 0.801712 0.198288 124,460 326,510 0.791659 0.208341 0.375783 0.463866 0.624217 0.536134 1.883737 1.646108 Germany 125,617 130,521 0.737189 0.262811 0.472938 0.644054 0.527062 0.355946 1.994158 1.527880 Italy 10.5931 M 0.0000 0.0000 0.0000 20.8675 0.0000 20.8675 -35,372.0 -80,102.6 -16,026.5 -10,884.5 0.0000 -26,662.9 0.0000 36.8725 1.25 -23,081.5 34.8223 0.0000 923,441 362,344 0.898458 0.101542 0.600354 0.675316 0.399646 0.324684 1.425990 1.781035 Mexico -229,483.9 3.2875 0.0000 377,616 122,721 0.808824 0.191176 0.401958 0.784851 0.598042 0.215149 1.864649 1.509935 Norway 35,013.3 4.1334 0.0000 71,134 116,646 0.850640 0.149360 0.384699 0.680453 0.615301 0.319547 1.823638 1.769515 UK 352,576.6 3.3641 10.9535 716,654 1070,971 0.835407 0.164593 0.425482 0.585645 0.574518 0.414355 1.892864 1.751178 US -190,891.4 0.0000 0.0000 688,398 849,511 0.954495 0.045505 0.450550 0.618571 0.549450 0.381429 1.980627 1.893515 ROW from abroad. 2 Footnote from Table 1. 1 Model tariff rates on exports are set equal to zero, the US imports both goods, with the trade imbalance financed by a resource transfer 20,972.4 Foreign Resource Transfers in Domestic Currency2 0.0000 NM Initial Tariff Rate on Imports1 (Percentage) Substitution Elasticities in Consumption (All Countries) 2.0 M 126,818 62,785 0.588701 0.411299 0.568545 0.731858 0.431455 0.268142 1.963106 1.202613 Korea 2.0 15.8008 57,998 61,888 0.837555 0.162445 0.484604 0.600681 0.515396 0.399319 1.998105 1.659805 Japan NM Substitution Elasticities in Production (All Countries) 50,801 L Initial Endowment 0.203951 NM Share Parameters in Preferences 0.325550 L - NM Share Parameters in Production 1.782958 NM Scale Parameters in Production Canada Calibrated and Other Model Parameter by Country Reproducing the Equilibrium Data in Table 1 Australia Table 3 4 Some Calculations of Global Distance Measures We have made calculations of globalization distance measures for the world economy for the year 2000 using ten OECD countries (Australia, Canada, Germany, Italy, Japan, Korea, Mexico, Norway, the UK, and the US) and a residual rest of the world. To make these calculations we first calibrate our global model as described above and then proceed to compute a barrier change equilibrium as our counterfactual in each case. We then compare initial and barrier change equilibria and construct the globalization measures for the world economy set out in Section 2. As we note above, due to the near linearity of the production frontier in the 2 × 2 case (see Johnson (1966), and Abrego and Whalley (2001)) specialization occurs as the equilibrium outcome on most countries in the tariff elimination case, The US, The UK, and Australia are the exceptions. We therefore compute globalization metrics for a common percentage reduction in tariffs in all countries. We use 1.000%, 2.000%, 3.000%, 3.600%, 3.690%, and 3.698% common reduction in tariff rates in all countries with 3.69803045848% as the maximal common reduction computationally possible. Table 4 presents the results. Just as in Riezman, Whalley and Zhang (2004) there are many globalization measures (and equilibrium metrics in general) available for the global economy and their numerical behavior differs. Euclidean distance measures which differing one from another are approximately linear in the depth of tariff cut. Excess demand measures, however, are smaller in some case for larger tariff costs. Which measure to use, and how to interpret such measures when calculated, especially when reported in popular press, is not clear. Not only do they vary in size, but they also vary in their precentage changes across tariff reductions of different depth. Measures will also vary further with the degree of disaggregation in models, the structural form of models, and the treatment of factor flows and barriers. Hence, making sense of the numbers which currently circulate in popular media as measures of globalization in popular media thus seems to be a hazardous occupation, if one is to say how far equilibria are apart. This also presumes that equilibrium rather than disequilibrium adequately characterizes the state which the global economy finds itself in. 19 Table 4 Globalization Metrics for the World Economy for Common 1.000%, 2.000%, 3.000%, 3.600%, 3.690%, and 3.698% Reductions in Tariff Rates in Each Country 1.000% 2.000% 3.000% 3.600% 3.690% 3.698% Euclidean Distance Measures MP0 0.000602 0.001219 0.001863 0.002235 0.002293 0.002298 MQ 0.007433 0.014704 0.021913 0.026035 0.026663 0.026718 MX 0.001043 0.002048 0.003026 0.003582 0.003666 0.003673 0.217444 0.215840 0.215598 0.215576 0.000820 0.000988 0.001013 0.001015 Excess Demand Measures 1 RG 0.222684 0.220066 2 RG 0.238726 0.251927 Debreu Shrinkage Measures RS1 0.000269 0.000543 RS2 -0.000271 -0.000548 20 Table 5 compares country measures of globalization distance for both 1.000%, 2.000%, 3.000%, and 3.600% common tariff reductions generated by the global model set out in earlier sections to separate country calculations of the type reported by Riezman, Whalley and Zhang (2004) for the small open economy case. These measures differ sharply, highlighting the pitfalls in making separate country calculations of globalization distance rather than using global measures. Table 5 also reveals competing influences on results. Because there is a common % reduction in tariffs, countries with higher initial tariff (Mexico, for instance) have larger globalization metrics. But also in globally based measures metrics are smaller for larger economies (the US, for instance) as smaller economies integrate into their markets and there is smaller domestic price change as barriers are lowered. 21 22 Canada 0.001979 0.001981 Models 0.000000 0.000000 0.003988 0.003995 Models 0.000000 0.000000 0.006072 0.006088 Models 0.000000 0.000000 0.007331 0.007354 Models 0.000000 0.000000 Global Models RF1 0.003572 2 RF 0.003578 Individual Economy RF1 0.002198 2 RF 0.002200 Global Models RF1 0.007154 RF2 0.007180 Individual Economy RF1 0.004391 2 RF 0.004401 Global Models RF1 0.010826 2 RF 0.010867 Individual Economy RF1 0.006580 RF2 0.006602 Global Models RF1 0.012951 2 RF 0.013034 Individual Economy RF1 0.007891 2 RF 0.007922 Italy Japan Korea Mexico Norway 0.005149 0.005137 0.008417 0.008452 0.006023 0.006011 0.003370 0.003366 0.009464 0.009374 0.007339 0.007291 0.016998 0.017287 0.020927 0.021460 0.000221 0.000221 0.000637 0.000637 0.010340 0.010291 0.006700 0.006680 0.012088 0.012037 0.006707 0.006692 0.019181 0.018816 0.014808 0.014591 0.033514 0.034614 0.041104 0.042820 0.000441 0.000442 0.001281 0.001282 0.015572 0.015460 0.025079 0.025378 0.018195 0.018078 0.009957 0.009922 0.029163 0.028327 0.022332 0.021839 0.049211 0.051678 0.060125 0.063830 0.000662 0.000662 0.001941 0.001943 0.011946 0.011937 0.018732 0.018570 0.019377 0.019556 0.030037 0.030462 0.021880 0.021710 0.011901 0.011852 0.035285 0.034067 0.026922 0.026208 0.058456 0.061955 0.071339 0.076584 0.000795 0.000795 0.002338 0.002341 Common 3.600% Reduction in Tariff Rate for all Countries 0.009995 0.009948 0.016224 0.016350 Common 3.000% Reduction in Tariff Rate for all Countries 0.016776 0.016910 0.010883 0.010939 Common 2.000% Reduction in Tariff Rate for all Countries 0.003355 0.003350 0.005500 0.005515 Common 1.000% Reduction in Tariff Rate for all Countries Germany 0.002040 0.002042 0.005217 0.005229 0.001700 0.001702 0.004332 0.004340 0.001134 0.001134 0.002862 0.002865 0.000567 0.000567 0.001424 0.001426 UK (Common 1.000% and 2.000% Reductions in Tariff Rate for all Countries) 0.006980 0.006972 0.000451 0.000451 0.005813 0.005807 0.000410 0.000410 0.003871 0.003869 0.000329 0.000329 0.001933 0.001933 0.000180 0.000180 US ROW 0.000000 0.000000 0.006483 0.006497 0.000000 0.000000 0.005369 0.005378 0.000000 0.000000 0.003524 0.003528 0.000000 0.000000 0.001747 0.001748 Comparing Globally Constructed and Individual Economy Based Measures of Globalization Australia Metrics Table 5 Table 6 presents sensitivity analyses of computation of globalization metrics in Table 4. Here we vary substitution elasticity in production between 0.75 and 4.00. The maximum percentage reduction in tariff that are computationally feasible falls and so results across the case are not directly comparable. Euclidean distance measures do not change as these are data not model based. Excess demand measures seem relatively in sensitive, while Debreu shrinkage measures vary more. 23 Table 6 Sensitivity Analyses of Global Metrics of Globalization (Change Substitution Elasticities and Reproduce Table 4) σnj = 0.750 for n = 1, · · · , N and j = 1, 2 1.000% 2.000% 3.000% 4.000% 5.000% 6.000% Euclidean Distance Measures M P0 0.000601 0.001207 0.001815 0.002428 0.003044 0.003664 MQ 0.002813 0.005616 0.008413 0.011201 0.013982 0.026756 MX 0.000403 0.000802 0.001197 0.001588 0.001975 0.002358 Excess Demand Measures 1 RG 0.224370 0.223330 0.222283 0.221311 0.220344 0.219371 2 RG 0.230539 0.235650 0.240762 0.245866 0.250961 0.256049 Debreu Shrinkage Measures 1 RS 0.000109 0.000214 0.000321 0.000427 0.000533 0.000638 2 RS -0.000107 -0.000215 -0.000322 -0.000430 -0.000537 -0.000645 σnj = 1.500 for n = 1, · · · , N and j = 1, 2 1.000% 2.000% 3.000% 4.000% 4.900% 4.910% Euclidean Distance Measures M P0 0.000601 0.001212 0.001833 0.002464 0.003043 0.003048 MQ 0.005596 0.011110 0.016548 0.021913 0.026689 0.026735 MX 0.000787 0.001553 0.002299 0.003026 0.003666 0.003672 0.217435 0.215630 0.215610 0.000826 0.001015 0.001017 Excess Demand Measures 1 RG 0.223363 0.221344 0.219407 2 RG 0.235456 0.245445 0.255375 Debreu Shrinkage Measures 1 RS 0.000204 0.000410 0.000617 2 RS -0.000205 -0.000413 -0.000623 24 Table 6 Sensitivity Analyses of Global Metrics of Globalization (Change Substitution Elasticities and Reproduce Table 4) —- CONTINUED σnj = 2.000 for n = 1, · · · , N and j = 1, 2 1.000% 2.000% 3.000% 3.600% 3.690% 3.698% Euclidean Distance Measures MP0 0.000602 0.001219 0.001863 0.002235 0.002293 0.002298 MQ 0.007433 0.014704 0.021913 0.026035 0.026663 0.026718 MX 0.001043 0.002048 0.003026 0.003582 0.003666 0.003673 0.217444 0.215840 0.215598 0.215576 0.000820 0.000988 0.001013 0.001015 Excess Demand Measures 1 RG 0.222684 0.220066 2 RG 0.238726 0.251927 Debreu Shrinkage Measures 1 RS 0.000269 0.000543 2 RS -0.000271 -0.000548 σnj = 3.000 for n = 1, · · · , N and j = 1, 2 1.000% 2.000% 2.400% 2.470% 2.474% Euclidean Distance Measures MP0 0.000605 0.001234 0.001491 0.001536 0.001539 MQ 0.011067 0.021745 0.025920 0.026645 0.026687 MX 0.001549 0.003011 0.003575 0.003672 0.003678 0.215849 0.215566 0.215550 0.000982 0.001011 0.001013 1.850% 1.858% 1.8589% Excess Demand Measures 1 RG 0.221361 0.217454 2 RG 0.245237 0.227728 Debreu Shrinkage Measures 1 RS 0.000401 0.000814 2 RS -0.000404 -0.000740 σnj = 4.000 for n = 1, · · · , N and j = 1, 2 1.000% 1.800% Euclidean Distance Measures MP0 0.000609 0.001119 0.001151 0.001156 0.001156 MQ 0.014648 0.025863 0.026552 0.026662 0.026649 MX 0.002045 0.003574 0.003666 0.003681 0.003682 0.215584 0.215541 0.215536 0.001007 0.001011 0.001012 Excess Demand Measures 1 RG 0.220080 2 RG 0.251711 0.215854 Debreu Shrinkage Measures 1 RS 0.000535 2 RS -0.000540 0.000979 25 5 Concluding Remarks In this paper we discuss metrics of globalization for the world economy constructed as distance measures between barrier restricted and globally integrated trade equilibriua. This contrasts with an earlier paper of ours reporting globalization metrics for single economies treated as price takes in world markets. We emphasize that literature on equilibrium metrics in general is limited, and so our paper is also a contribution to part of a wider discussion of metrics of distance across equilibria in other circumstances. We report measures generated using a global model involving 10 OECD countries and residual rest of world using 2000 data applied to simple 2 × 2 country models. These suggest both substantial differences in measures for the global economy and differences across countries in country measures for the same barrier reduction. As such our results may seem on the whole negative, but they again illustrate the pitfalls involved with measures currently reported in populist magazines such as the Economist and Foreign Policy. 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