FORECASTING PRODUCTIVITY AND GROWTH WITH INTERNATIONAL FUTURES (IFs) PART 2: DRIVING THE DRIVERS AND INDICES

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1 FREDERICK S. PARDEE CENTER FOR INTERNATIONAL FUTURES EXPLORE UNDERSTAND SHAPE WORKING PAPER b FORECASTING PRODUCTIVITY AND GROWTH WITH INTERNATIONAL FUTURES (IFs) PART 2: DRIVING THE DRIVERS AND INDICES Autho: Bay B. Hughes May 25 Note: If cited o quoted, please indicate woking pape status. PARDEE.DU.EDU

2 Foecasting Poductivity and Gowth in Intenational Futues (IFs) Pat 2: Diving the Dives and Indices Table of Contents 1. The Objectives and Context Social Capital: Govenance Quality Existing Measues/Indices Fowad Linkages: Does Govenance Affect Gowth? Backwad Linkages (Dives): How Foecast Govenance Effectiveness? Specifics of Implementation in IFs: Backwad Linkages Comments on Othe Aspects of Social Capital Physical Capital: Moden (o Infomation-Age) Infastuctue Existing Infastuctue Indices: Is Thee a Quick and Easy Appoach? Backgound: Conceptual, Data and Measuement Issues Infastuctue in IFs Positioning fo Technological Dynamism: Knowledge Ceation Review of Existing Indices on Technological Capability Conceptualizing Knowledge Ceation and Adaptation/Diffusion fo IFs Exploing Knowledge Ceation: R&D Exploing Knowledge Ceation: Tetiay Education Implementation of Knowledge Ceation Index in IFs Globalization The Pesonal Contact Dimension The Economic Integation Dimension Globalization in Intenational Futues The Use of Globalization in Foecasting Poductivity Refeences ii

3 Abstact The foecasting of economic gowth is cental to the foecasting of global futues. It is impossible to exploe the futue of human development, changes in the intenational system, the quality of the envionment, o much of anything else without looking to pattens of economic gowth. In the foecasting of economic gowth, undestanding the likely development of capital and labo stocks is impotant. But undestanding poductivity gains is the eal key. We know that thee ae many dives of poductivity in contempoay knowledge-based societies. This manuscipt is one of two that togethe map an appoach to epesenting that gowth in Intenational Futues (IFs). The fist of the two (Pat 1) eviews the liteatue aound some of the key potential dives of poductivity gowth, daws lessons fom that liteatue, and descibes the fomulation developed within IFs to foecast poductivity and gowth. It also discusses the use and contol of that fomulation via the use inteface of IFs. The second manuscipt (Pat 2) focuses on the dives of poductivity and, in tun, on thei epesentation. In essence it exploes what dives the dives. That second manuscipt diects special attention to a numbe of indices that have been developed in othe liteatue that have poven elevant in the effot to epesent poductivity change within IFs. This epot is Pat 2. It gives special attention to indices and vaiables aound govenance, the knowledge society, infastuctue, and globalization, but its geneal pupose is to exploe the foecasting of economic gowth. It is a companion piece to the moe geneal epot on the modeling of multifacto poductivity. iii

4 1. The Objectives and Context 1 Intenational Futues (IFs) is a lage-scale integated global modeling system. The boad pupose of the Intenational Futues (IFs) modeling system is to seve as a thinking tool fo the analysis of nea though long-tem county-specific, egional, and global futues acoss multiple, inteacting issue aeas. The issue aeas include demogaphics, economics, education, enegy, agicultue, the envionment, and socio-political systems. Yet economic gowth dives much of what changes in the othe systems, including the ability to satisfy human needs, loads upon the envionment, and the position of states in the global system. The economic model of IFs is geneal equilibium, epesenting supply, demand, and exchange in six sectos (agicultue, enegy, othe pimay goods, manufactues, sevices, and ICT). Although the demand side of the model is impotant, in the long-tem the supply-side and, in paticula, the poduction function is citical. The two papes in this set focus on that key aspect of IFs and document ongoing effots to impove its epesentation and to inceasingly endogenize changes in multifacto poductivity. 2 The companion pape to this one, Pat 1 of the set, documents the fomulation of the poduction function in IFs and the dives of it. 1 Thanks to Anwa Hossain fo assistance in finding many of the indices, data, and pieces of liteatue that suppoted this poject and in contibuting his thoughts and advice to the wok. 2 The Stategic Assessments Goup (SAG) has used the IFs system fo a vaiety of analyses including an examination of the changing powe positions of majo counties. It suppoted this poject to enhance IFs by moe fully epesenting the dives of change in the economic size and stength of counties. In addition, Fedeick S. Padee is poviding sustaining suppot fo the Intenational Futues (IFs) poject, and that suppot has helped integate the extensions desied by SAG into a moe compehensive famewok of evision in the poduction function of IFs. 1

5 Moe specifically, Pat 1 of this pai of papes pesented and descibed a typology of potential dives of gowth: Human Capital Education and Taining (quantity and quality) Health Social Capital and Govenance Tust/Community Stength Govenance Quality Govenance Policies/Oientation (especially openness/libealization) Physical Capital Infastuctue (taditional and moden) Robustness of Systems (e.g. enegy divesity) Natual Capital (foests, land quality, etc.) Knowledge Base Ceation Adaptation/Diffusion This pape will not discuss all of these dives. Some of them ae embedded deeply in vaious models and submodels of IFs. Fo instance, fomal education is epesented within IFs in a sepaate submodel of pimay, seconday, and tetiay education. 3 Similaly, the epesentations of enegy and natual/envionmental systems ae found in othe submodels. This pape will focus on those in bold above. Moe specifically, this pape, Pat 2 of the set, has the objective of eviewing the incopoation within IFs of seveal new indices that epesent contempoay dives of poductivity. They can be thought of as components of economic stength in and of themselves and can help captue a static pictue of the elative pefomance of counties. They can, howeve, also be clealy seen as contibutos to the dynamics of systemic change because they ae among the most citical components of economic poductivity. The fou indices identified fo special examination wee govenance quality, moden infastuctue, positioning fo technological dynamism (which can also be seen as ceating and adapting knowledge), and globalization level. 4 In addition, this poject equied futhe development of the education submodel of IFs, with special attention to the tetiay secto and the quality of human capital. 5 3 Mohammod T. Ifan has developed this submodel as pat of his Ph.D. dissetation wok and is documenting it sepaately. A basic intoduction to it can be found in the Help system of IFs and in Hughes with Hossain and Ifan (24). 4 Thanks to Paul Heman of the Stategic Assessments Goup fo leadeship in building this list. 5 Mohammod T. Ifan has developed the education model of Ifs as pat of his PhD dissetation wok at the Gaduate School of Intenational Studies (GSIS), Univesity of Denve. 2

6 The intent of the poject has been to integate these fou citical aeas within IFs as fully as possible. 6 That has meant giving attention both to thei dives (backwad linkages) and to the vaiables they will affect (fowad linkages). In exploing and implementing such indices, two key questions o citeia consistently shape the wok: 1. Can an index be useful in helping to foecast key model vaiables? In paticula, can an index help foecast economic gowth potential? Although each of the indices ae of inteest in and of themselves, the deepe eason fo attention to them is because they ae commonly seen as contibuting to the economic and moe geneal vitality and success of societies. Thus in fomulation of the indices fo the model, we want to be attentive to the stength of such fowad linkage. In addition to economic impact, anothe fowad linkage of inteest is to political stability and/o violence. 2. Can the index itself be foecast within the model? That is, ae the dives of the index (backwad linkages) in place within the model o can they be added? Regadless of the stength of fowad linkages (the inheent utility of a vaiable o index), its utility will be educed significantly if the model does not have the capability of foecasting the index itself. Nonetheless, an index can be useful without backwad linkages, o if such linkages ae not fully developed, because exogenous assumptions about the futue of the index can be intoduced and the impact of those assumptions can be exploed. 6 Thanks to José Robeto Solozano fo his key ole in implementing the new poduction function within IFs and fo moe geneal contibutions to the IFs poject. 3

7 2. Social Capital: Govenance Quality It is clea fom the eview of poductivity and gowth liteatue that govenance quality does affect poductivity and must be included in the poduction function. The pupose of this chapte is to discuss appoaches to conceptualizing and measuing the concept and to pesent an appoach to incopoating the concept into IFs. 2.1 Existing Measues/Indices Some of the best-known measues of govenance ae those associated with the Wold Bank Govenance and Anti-Couption Resouce Cente 7 and with the wok of Daniel Kaufmann and a vaiety of collaboatos (see Kaufmann, Kaay and Zoido-Lobatón 1999; Kaufmann, Kaay, and Mastuzzi, 23; Kaufmann 24a and 24b). 8 The poject pesented data on six indices clusteed oughly aound thee aspects of govenance: (1) the pocess by which govenments ae selected, monitoed and eplaced, (2) the capacity of the govenment to effectively fomulate and implement sound policies, and (3) the espect of citizens and the state fo the institutions that goven economic and social inteactions among them (Kaufmann, Kaay and Mastuzzi 23: 2). On the fist aspect of govenance, they pesented measues of Voice and Accountability and of Political Stability and the Absence of Violence. On the second aspect, thei measues wee Govenment Effectiveness and Regulatoy Quality. 9 On the thid aspect, they povided Rule of Law (including, impotantly, the enfoceability of contacts) and Contol of Couption. The division of govenance measues by this poject into the thee categoies is quite useful, especially with espect to consideing which of them might be given special attention within Intenational Futues. The fist dimension is aleady tapped to some consideable degee within IFs by the measues of democacy and autocacy fom the Polity poject and the measue of feedom fom Feedom House, as well as the measues of state failue fom the State Failue Poject. The thid dimension is tapped to some 7 See 8 See many downloadable papes at Anothe useful poject elated to govenance at the Wold Bank is the database of political institutions, which contains a wealth of political infomation on 177 counties ove the peiod (Beck, Clake, Goff, Keefe, and Walsh (21). It is available at 9 This dimension is also addessed by the Wold Bank s poject on Doing Business, which tacks the time and financial costs involved in setting up businesses. 4

8 degee aleady by including within IFs the couption peception index of Tanspaency Intenational (TI). 1 Specifically, the couption peception index (see Lambsdoff 23) daws on many othe souces and measues including the Wold Bank, all of which focus on the peception of couption (measuement of actual couption is, of couse, nealy impossible). TI ceates an aggegate measue fom the othe souces. Given this ovelap with the boade measues within IFs, it made sense in this enhancement of IFs to focus on adding infomation about the capacity of govenment, as captued by the Bank s Govenment Effectiveness and/o Regulatoy Quality measues (as well as on binging the thee dimensions of govenance into fowad linkages to poductivity). Ae thee souces othe than the Wold Bank, Feedom House and TI to look to fo indices o input concening the capacity of govenment? The Intenational County Risk Guide (ICRG) coves 14 counties and data fo many of them go back to 1984, with updates monthly. Because it has been so widely used in studies of the impact of govenance on gowth, it is a candidate fo use in IFs also. The disadvantage, howeve, is that the sevice is commecial; downloading a single month of values (the composite index only) cost $45 in ealy 25. Fo the puposes of the IFs poject, thee is much to be said fo looking pimaily to the Wold Bank measues, not least of which is thei logical clusteing in thee govenance aeas. The Wold Economic Foum publishes an annual Global Competitiveness Repot. 11 Thei gowth competitiveness index 12 has thee components: a technology index (weighted ½), a public institutions index (weighted ¼) and a macoeconomic envionment index (weighted 1/4). The public institutions index is essentially anothe measue of govenance and is built on two subindices: contacts and law; couption. We have added ecent values of the index (both ank and scoe values) to the IFs database, but the measues ae not as useful as those of the Wold Bank. Consideation of the measues of govenance that ae available and of the ones that ae aleady in IFs suggests that special attention should be given to the Wold Bank s Govenance Effectiveness and Regulatoy Quality measues and possibly to the Bank s Rule of Law measue and/o the CGI s Contacts and Law measue. One impotant way 1 See 11 See petitiveness+repot/global+competitiveness+repot html fo access to seveal ecent ones. 12 Jeffey D. Sachs, now of Columbia Univesity, and John W. McAthu of the Eath Institute oiginally developed the global competitiveness index fo the epot. 5

9 of identifying the dimensions that might be useful to add to IFs involves looking at the elationships among these measues. The table below shows such coelations fo the six Wold Bank measues, the Tanspaency Intenational Couption Peception measue, and the Wold Economic Foum/Global Competitiveness Public Institutions index. Inteestingly, the fist two measues of the Wold Bank clealy do seem to tap a diffeent dimension that do the othe fou. The R-squaed calculations seldom exceed.6. Inteesting, howeve, the two measues themselves do not coelate highly, suggesting the value within IFs of sepaating type of govenment (e.g. level of democacy) fom political and social stability (e.g. the state failue measues). In contast the last fou measues of the Wold Bank all coelate at levels of.75 o bette suggesting that the two dimensions ae quite closely linked. Moeove, the high coelation of Effectiveness with Regulatoy Quality (.869) and of the Rule of Law with Couption (.92) to suggest that the fou measues ae appopiately gouped on thei two sub-dimensions. Note that the Tanspaency Intenational and Wold Bank measues of couption ae nealy identical with an R- squaed of.935. Moeove the Wold Economic Foum s measue coelates most highly with the two couption indicatos, suggesting that it is also basically a peception of couption measue. Voice & Acc Stability Reg Qual Rule of Law Effectiveness Couption Voice & Acc Stability.568 Effectiveness Reg Quality Rule of Law Couption TI Couption WEF Pub Inst Table 1. Adjusted R-squaed coelations acoss measues of govenance. Computed in IFs using most ecent data fo all counties available. What conclusions about epesentation within IFs can we daw fom the above table? It einfoces the pedisposition to add the capacity of govenment measue athe than those focusing on govenance types/inputs, stability, o couption and ule of law. Thus as we move fowad into investigation of fowad linkages, we want to pay special attention to the Wold Bank s Govenance Effectiveness and Regulatoy Quality measues. TI Couption 6

10 2.2 Fowad Linkages: Does Govenance Affect Gowth? As indicated befoe, we want to focus especially on linkages of govenance quality to economic poductivity and gowth. Thee is a huge liteatue on this topic, and a sepaate pape in the IFs poject, a companion to this pape, has eviewed some of the liteatue linking govenance to economic gowth. The pupose of this section is to undetake a vey quick independent analysis of that linkage using some of the data aleady in the IFs database, and theeby also to set the stage fo discussing the implementation of the elationship in IFs. In looking at linkages between govenance quality and economic pefomance, it is citical to undestand that the elationship is close, and that it is pobably long-tem and bi-diectional (see Kaufmann and Kaay 23). The figue below shows an R-squaed of.74 between GDP pe capita and GDP pe capita at puchasing powe paity. A simila elationship chaacteizes all othe measues of govenance quality. Govenance Effectiveness (Most Recent) y =.7464Ln(x) R 2 =.7435 GDP pe Capita at Puchasing Pow e Paity (Most Recent) Figue 1. Govenance Effectiveness as a Function of GDP pe Capita. Clealy, bette govened counties ae, on the whole, iche and/o iche counties ae bette govened. Of moe inteest in foecasting, howeve, is whethe an impovement of govenance is likely to lead to a ise in economic gowth ates, all else being equal. The figue below suggests that pehaps it does, but that the elationship, if any, is vey weak. Some good news about the above elationship is that it holds up also if we contol fo GDP pe capita; in fact, the impact of effectiveness ises somewhat if we do so. 7

11 2 GDP Gowth Rate (Most Recent) y =.3782x R 2 = Govenance Effectiveness (Most Recent) Figue 2. GDP Gowth as a Function of Govenance Effectiveness. Gowth ates ae highly volatile, howeve, so it makes sense to look at a longe time peiod, such as the peiod. Additionally, it is possible to focus on pe capita gowth, so as to contol fo the diffeential gowth ates of population with its own contibutions to gowth doing so will also contol fo the fact that less developed counties tend to have highe GDP gowth (but not necessaily highe pe capita gowth) and that they tend to have less effective govenments, theeby educing the elationship inappopiately. The figue below does that. It suggests that GDP pe capita in counties with the least effective govenments shunk by about 17% duing the decade of the 199s while in the counties with most effective govenment it gew by about 37%. The diffeence of 54% is equivalent to an annual gowth diffeential of 4.4%, quite an astounding potential impact of effectiveness. If GDP pe capita at PPP is added as a second independent vaiable (so as to contol fo the effect of absolute economic level, the adjusted R-squaed in the elationship below ises to just above.2. Ratio of GDP pe Capita (PPP) in 2 and 199 y =.1366x R 2 = Govenance Effectiveness (Most Recent) Figue 3. Decade-long GDP pe Capita Gowth as a Function of Govenance Effectiveness. 8

12 The impact is, howeve, only potential. It is still unclea which diection the diffeence goes. Concen that it might go the othe diection is inceased by the fact that the above figue uses govenance effectiveness data that is mostly fom 22, afte the decade of gowth. Yet govenance effectiveness does not tend to change vey apidly accoding to the Wold Bank Data. The figue below shows that phenomenon ove the athe shot time of its data set, namely 1996 though 22. Although govenance effectiveness ises vey slightly in the Euopean Union of the 15 and falls vey slightly in South Ameica, it is mostly unchanged. Figue 4. A Look at Govenance Effectiveness Ove Time in Majo Regions That elatively stable chaacte of govenance ove time might even give us a little moe confidence that the diection of impact could be fom effectiveness to gowth. The figue below adds to such confidence by shifting the data fo govenance effectiveness fom mostly 22 to mostly 1996 in the elationship with decade-long gowth. The elationship stays petty much the same as that in Figue 3, but the slope of the cuve actually ises slightly. 9

13 3 Ratio of GDP pe Capita (PPP) in 2 and 199 y =.1628x R 2 = Govenance Effectiveness (Ealiest) Figue 5. Decade-long GDP pe Capita Gowth as a Function of Govenance Effectiveness (Ealiest Data). Lest we become too confident, the figue below looks at govenance effectiveness nea 1996 and gowth fom 1996 to 2. The slope would be expected to be lowe and theefoe the coelation to be less stong, but it is obviously not a stong elationship at all. Still, that should not be too discouaging, because shote-tem gowth ates ae highly vaiable and dependent on many shote-tem effects. Ratio of GDP pe Capita (PPP) in 2 and y =.282x R 2 = Govenance Effectiveness (Ealiest Data) Figue 6. Half decade-long GDP pe Capita Gowth as a Function of Govenance Effectiveness (Ealiest Data). 1

14 Although it difficult, if not impossible, to pove that highe levels of govenance effectiveness esult in faste gowth, the evidence is stong. Kaufmann and Kaay (23) undetake a moe extensive and sophisticated analysis and conclude that the elationship unning fom income levels to govenance is pehaps even negative, while the elationship fom govenance to income is stongly positive. In this discussion we have not looked at othe measues of govenance. Thee have been two easons fo that. Fist, as indicated befoe, it is the govenance capability dimension that would most clealy augment fomulations in IFs existing pio to this poject. Second, in the analysis undepinning the above figues othe measues wee, in fact, also examined, but govenance effectiveness almost invaiably geneated the highest coelations with gowth. Fo instance, in looking at the elationship in Figue 3 between effectiveness and decade-long gowth ate, it was noted that when a contol fo GDP pe capita was added the elationship climbed just above an R-squaed of.2. The compaable numbes fo egulatoy quality and ule of law wee.17, fo voice and accountability was.12, fo couption was.9, and fo political stability was.8. As we move fowad with this discussion we will theefoe continue to give special attention to govenance effectiveness. 2.3 Backwad Linkages (Dives): How Foecast Govenance Effectiveness? Although Kaufmann and Kaay (23) ague that changes in income levels do not positively affect govenance quality and that the elationship uns in the othe diection, it is petty obvious fom Figue 1 that levels of GDP pe capita ae stongly associated with bette govenance. We would expect ove the longe tem, that as counties ise in income, they will ise in govenance quality. What else might dive changes? How might we fomulate foecasts of govenance effectiveness? One possibility is education level. We would expect and/o hope that highe levels of education would esult in impoved govenance. The figue below shows a stong coelation. Govenance Effectiveness (Most Recent) y =.2947x R 2 =.6546 Aveage Education Yeas of Population Ove 25 Figue 7. Govenance Effectiveness as a Function of Yeas of Education. 11

15 The above elationship clealy inteacts with gowth levels of GDP pe capita. When GDP pe capita is added as an independent vaiable (logged) the adjusted R-squaed gows to.78. That is, unfotunately, not much above the.74 of GDP pe capita alone (see again Figue 1), but both vaiables emain significant and the beta of education emains clealy positive. Anothe facto that is often agued to be negatively associated with quality of govenance (especially couption) is dependence on aw mateials expots, which offe a honey-pot fo potentially coupt officials. Paul Collie has often agued this in his analysis (see Collie, Elliot, Hege, Hoeffle, Reynal-Queol, Sambanis 23). His wok focuses also on the elationship between aw-mateial dependence and domestic conflict, which helps explain the detimental impact of such dependence on gowth. The figue below elates govenance effectiveness to enegy expots elative to GDP and finds a elationship in the expected diection, but not a vey stong one. If the couption peceptions index is substituted fo govenance effectiveness the R-squaed actually dops slightly. Futhe, if eliance on agicultual and othe aw mateials expots as a potion of total mechandise expots ae substituted fo enegy expot atios, the function is lagely unchanged. And if eithe education yeas o GDP pe capita (o both) ae added to enegy expot dependence, the total adjusted R-squaed is educed elative to those vaiables alone. It might be that a moe sophisticated, compehensive measue of aw mateial dependence (we should look to Collie s analysis fo this) might allow its use as a pedicto of govenance quality, but it does not appea useful with enegy alone. Govenance Effectiveness (Most Recent) y = x R 2 = Ene gy Expots (BBOE)/GDP (Billion Dollas ) Figue 8. Govenance Effectiveness as a Function of Enegy Expot Dependence. Some obseves might expect a cultual explanation fo govenance quality. The map below could einfoce that image, pehaps dawing special attention to a numbe of Islamic societies. Yet moe study of the map suggests that economic development pobably emains a much bette pedicto. 12

16 Figue 8. Political Map of the Wold Bank s Govenance Couption Measue. In fact, if a dummy vaiable fo Islamic cultual dominance is coelated with eithe the Wold Bank s couption o govenance effectiveness measues, the R-squaed is below.3. If the Islamic-cultue dummy vaiable is added to GDP pe capita (logged) and coelated with govenance effectiveness, the adjusted R-squaed ises to.76, somewhat above that of GDP pe capita alone. Both vaiables emain significant. If education yeas ae added, the R-squaed ises futhe to.78 and the significance level fo cultue is slightly highe than that fo education. But the total vaiance explained by GDP pe capita, education, and Islamic cultue is no bette than that with GDP pe capita and education alone. Pasimony, if not concens about cultual bias, would ague fo emaining with GDP pe capita and education as dives of govenmental effectiveness. 13

17 2.4 Specifics of Implementation in IFs: Backwad Linkages Duing the couse of this poject, both backwad and fowad linkages fo govenance wee added to IFs. A sepaate document ( Foecasting Poductivity and Gowth ) elaboates the entie fomulation of poductivity within IFs and the inteested eade should tun to that fo infomation on fowad linkages. Hee we focus only on the epesentation of the dives of govenance quality. As indicated above, it was decided that the Wold Bank s focus on thee dimensions of govenance would be useful fo IFs. Those thee again ae (1) the pocess by which govenments ae selected, monitoed and eplaced, (2) the capacity of the govenment to effectively fomulate and implement sound policies, and (3) the espect of citizens and the state fo the institutions that goven economic and social inteactions among them (Kaufmann, Kaay and Mastuzzi 23: 2). With espect to the fist dimension, IFs aleady includes two diffeent measues of democatization, one linked to the Feedom House s appoach and summing the two measues of Feedom House into a single measue (FREEDOM) and one linked to the Polity Poject s appoach (DEMOCPOLITY). Discussions of the fomulations fo FREEDOM and DEMOCPOLITY can be found in the Help system of the model. With espect to the second dimension, it was decided to add a vaiable to IFs on govenment effectiveness (GOVEFFECT) and empiically to gound that in the Wold Bank data seies of the same name. With espect to the thid dimension, we have seen that the Tanspaency Intenational index of couption peceptions coelates highly with the Rule of Law and Contol of Couption measues with which Kaufmann and colleagues elaboate that dimension. Because it is so well known and egulaly measued, it was decided to add a vaiable based on it called GOVCORRUPT to IFs. Within IFs thee ae thee geneal ways in which vaiables can be epesented (backwad linkages) so that they can be shown in foecasts. These ovelap somewhat and ae not pue types: 1. As functions of deep dive vaiables in the model. In paticula, lage numbes of vaiables of inteest, including govenance quality measues, coelate vey highly with GDP pe capita, especially at puchasing powe paity. Such deep dives ae useful, but they ae not fully satisfactoy. Specifically, they isk ceating a kind of ciculaity in fomulation, wheein GDP pe capita dives a vaiable and that vaiable is of inteest to us because it affects GDP gowth. If the level of the vaiable is of inteest to us in and of itself (as quality of govenance and many othe such vaiables, such as democacy level, ae), that poblem is less significant. Also, if the fomulation involves two o moe deep dives, and yeas 14

18 of education is anothe vaiable often found to be of elevance, the poblem is educed. 2. As functions of policy leves. Fo instance, the model epesents the diection of govenment spending towads education, health, the militay, and R&D. The use can manipulate the balance. Such linkage to policy leves allows us to ceate a base foecast in which histoical o typical pattens of allocation pevail, but also to intevene with altenative scenaios. This is not likely elevant with espect to govenance quality (but could be with both infastuctue and knowledge development/tansfe). 3. As functions of exogenous specification/manipulation. IFs often allows a vaiable to be diectly alteed by a multiplie o additive paamete. This fom of epesentation tells us nothing, of couse, about possible o pobable levels of the vaiable, but does allow us to look at the impact of exogenous changes in level on othe vaiables (fowad linkages). Implementations in IFs often involve a combination of these thee elements. With espect to govenance quality, the balance is heavily weighted towads the fist and thid. We began by adding the govenance effectiveness (GOVEFFECT) vaiable name to IFs. We also added data fo all six indices of the Wold Bank s Govenance Mattes III poject to the IFs database (fo the yeas 1996, 1998, 2, and 22). We then used the data on govenance effectiveness to initialize values of GOVEFFECT on a county-bycounty basis fo all of those counties coveed by the Bank. We used a coss-sectionally estimated function against GDP pe capita (PPP) to fill the limited numbe of holes in this initialization pocess. Fo futue yeas, we developed a fomulation that has thee components. The fist is a tem that computes govenance effectiveness as an analytic function of GDP pe capita (PPP) and education yeas of the population (EDYRSAG25), as discussed above. This is, fo the most pat, a deep dive fomulation. The addition of education yeas does, howeve, allow some policy/scenaio manipulation by the uses who can vay the attention given to education. GOVEFFECT = ( ANALFUNC ( GDPPCP, EDYRSAG25 ) + ConvegTe m) * goveffectm The above fomulation has two othe impotant elements aound that base. The fist is a convegence tem (ConvegTem) that ove a vey long peiod of time bings the specification of govenance effectiveness towads the coss-sectionally estimated value. This is a common appoach within IFs, ecognizing that diffeences between initial conditions and typical levels of vaiables fo counties at given development levels often eode. The second additional tem above is an exogenous multiplie (goveffectm), allowing scenaio manipulation fo the pupose of fowad analysis. The fomulation below fo govenment couption is completely analogous. GOVCORRUPT = ( ANALFUNC ( GDPPCP ) + ConvegTe m) * govcoupt m 15

19 2.5 Comments on Othe Aspects of Social Capital Taxonomies of social capital contibutions to poductivity (see the companion piece to this document) often contain elements that move beyond govenance quality, including at least two additional elements. The fist is tust/community stength. Although IFs does epesent the two dimensions of the Wold Value Suvey, neithe of these is a tuly good poxy fo that measue. Given the difficulty of developing dives, we will not add it. The suvey esults of the Wold Value Suvey s question on tust ae in the database The second is govenance policies/oientation (especially openness/libealization). IFs aleady contains a geneal measue of govenance policies/oientation in the fom of a vaiable of economic feedom (ECONFREE). Thee ae two pimay souces of data/indices on economic feedom. One is the poject of The Heitage Foundation and the Wall Steet Jounal, which is poduced in an annual epot called Index of Economic Feedom (Miles, Feulne, O Gady 24). The othe epot and index is Economic Feedom of the Wold (Gwatney and Lawson 24). The IFs poject has included the latte in its dataset and updated the data values fo this poject. The ECONFREE vaiable in the model is calculated in much the same way that the GOVEFFECT vaiable was constucted. 16

20 3. Physical Capital: Moden (o Infomation-Age) Infastuctue Talk of digital divides and public attention to availability of moden o ICT infastuctue became intense in the 199s and counties aound the wold feaed being left behind in the ace to be at the leading edge. Many oganizations and political leades have embaced the goal of ceating moden infomation-age economies and societies, and explicitly ecognized the infastuctue foundation of that goal. Fo instance, the Global Infomation Infastuctue Commission (GIIC; see has been pomoting it at the Wold Summit on the Infomationa Society (WSIS) and elsewhee. They state thei mission as: The GIIC is a confedeation of chief executive offices of fims that develop and deploy, opeate, ely upon, and finance infomation and communications technology infastuctue facilities. Togethe as GIIC commissiones, these executives ae dedicated to speeding the spead of infomation infastuctue thoughout the wold. The GIIC was established duing a 1995 meeting in Bussels at which the political heads of the wold's leading national economies fomally and fo the fist time acknowledged the tansfoming foces of compute and telecommunications technologies and the emegence of an "infomation society." In doing so, the heads of state challenged business leades to unite in the pomotion of public policies and infomation technology applications likely to spu needed investment in communications infastuctue facilities. Thus was bon the GIIC. Commissiones of the GIIC come fom fims based in developed nations, as well as in developing and emeging maket nations. Not supisingly, ICT infastuctue was a majo topic of convesation at the Wold Summit on the Infomation Society (WSIS) in Geneva duing 23, with the follow-on in Tunis scheduled fo Novembe, 25. Fom the statement of pinciples in Geneva comes this 21. Connectivity is a cental enabling agent in building the Infomation Society. Univesal, ubiquitous, equitable and affodable access to ICT infastuctue and sevices, constitutes one of the challenges of the Infomation Society and should be an objective of all stakeholdes involved in building it. Connectivity also involves access to enegy and postal sevices, which should be assued in confomity with the domestic legislation of each county. 13 The plan of action says that 9. Infastuctue is cental in achieving the goal of digital inclusion, enabling univesal, sustainable, ubiquitous and affodable access to ICTs by all, taking into 13 See 17

21 account elevant solutions aleady in place in developing counties and counties with economies in tansition, to povide sustainable connectivity and access to emote and maginalized aeas at national and egional levels Existing Infastuctue Indices: Is Thee a Quick and Easy Appoach? It would be ideal if thee wee an existing index of infastuctue quality that could be initialized, diven, and used within IFs. Such an index was not found in the couse of this poject. Fo instance, the poject consideed the Infastuctue Quality measue of the Wold Economic Foum s Global Competitiveness Repot (Pote, Schwab, Sala-i- Matin, and Lopez-Claos 24: 512), and we included some of its measues in the IFs database. The figue below plots values on that index against GDP pe capita at PPP. Wold Econonic Foum Infastuctue Quality Scoe y =.1163x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) The Infastuctue Quality measue, 15 like many of the othe indices in the competitiveness epot, come fom the Executive Opinion Suvey (EOS) of the Wold Economic Foum fo moe than 1 counties. The same souce contains data on aiload infastuctue development, pot infastuctue quality, ai tanspot infastuctue quality, quality of electicity supply, telephone/fax infastuctue quality, postal efficiency, 14 See 15 Kaufmann (24a: 5) shows esults on the quality of infastuctue fom Executive Opinion Suveys. These suveys come fom the Global Competitiveness Repot of the Wold Economic Foum, see pinion+suvey+of+the+global+competitiveness+repot.html The data ae available in the CD of esults fom the suveys 23 fo 3 Swiss Fancs, see and+contact+infomation.html and s+cd-roms.html 18

22 quality of public schools, and quality of healthcae. In addition thee ae data fom othe, objective souces on paved oads (as pecent of total in 1999) and othe elated indicatos. The espondents that helped the WEF fomulate thei 7-point subjective scales ae business executives in these counties (p. xi) and the numbe of espondents pe county is not obvious. Unfotunately, the outlies do not give one geat confidence in the measue and make one wonde whethe a few espondents with egime connections o gudges can geatly shift esults. The two counties well below the line between $2-3 thousand dollas ae Italy and Ieland; thei infastuctue may not be geat, but the extent of deviation fom the coss-sectional patten seems exteme. The county at about 5 on the index but with vey low GDP pe capita is Noth Koea the suvey claims of exceptional infastuctue seem dubious, as do those of Jodan and Namibia, also shown well above the coss-sectional elationship. In contast, Malaysia almost cetainly deseves its position well above the line. Even if IFs wee to initialize an infastuctue index with such data, it is not clea how it could foecast change in the index. We theefoe need to conside an appoach based moe in had data and in building up an index fom undestandable components. 3.2 Backgound: Conceptual, Data and Measuement Issues Befoe tuning pimaily to moden o infomation-society infastuctue, it is impotant to note that, in tems of a boad taxonomy of foces that dive dynamism and gowth, taditional infastuctue is potentially as impotant as moden o infomation-age infastuctue. The woking papes of the task foces fo the Millennium Poject (stiving to develop a stategy fo pusuit of the Millennium Development Goals) made this point quite clealy. It is often electicity, oads, ailoads, and pots that hold back development, not ICT systems. Fo a moe integated pespective it is useful to efe back to the Wold Development Repot 1994: Infastuctue fo Development (Wold Bank 1994). 16 They (1994: 2) defined infastuctue sevices as Public utilities powe, telecommunications, piped wate supply, sanitation and seweage, solid waste collection and disposal, and piped gas. Public woks oads and majo dam and canal woks fo iigation and dainage. Othe tanspot systems uban and inteuban ailways, uban tanspot, pots and wateways, and aipots. Data ae skimpy and difficult to nomalize by county size/chaacteistics on many elements of the Wold Bank infastuctue definition, including sanitation and seweage, waste collection, and tanspot. In contast, data on electicity and telephone lines ae 16 Thee is also a Wold Bank poject on taditional infastuctue called the Living Standads Measuement Study. Fo infomation on suveys fom 15 counties see 19

23 quite widely available, as ae data on telecommunications and compute usage. We have added significant amounts of such data to IFs. Unfotunately, we have been less successful in discoveing data on the spead of bandwidth, an impotant element of the ICT infastuctue. It is inteesting to note that telecommunications is the key element in the Wold Bank listing of infastuctue types that would by many be consideed moden o infomationage infastuctue. Wok by Fay and Yepes (23: 2) at the Wold Bank (1994:4) suggests that the cost-based shae of that component of infastuctue stocks inceases with development level, but is still only about 7% of total infastuctue by value at high income levels. In contast, electic powe systems incease thei shae of the total shaply with development, eaching about 4% at the high income levels (just unde oads which account fo 45% of stocks by value). The impotance of powe systems to moden infastuctue suggests that it be consideed fo inclusion in an index of moden infastuctue, o at least be epesented as a foundation. One could even ague that, given the enthusiastic adoption of most ICT technology by individual, business, and govenment uses (thee ae vey long delays, fo instance, in getting telephones installed in most developing counties), the povision of basic electicity is the key infastuctue bottleneck of the knowledge society. Telephone access might be the next level of bottleneck (opening up use of PCs), followed possibly by access to highe bandwidth, but the expenditue equiements in these aeas appea not to be so elatively geat. It is useful to exploe the notion of an infastuctue ladde pio to specifying a fomulation fo foecasting of infastuctue in IFs. The gaph below shows the quite close elationship between GDP pe capita and electicity consumption. Kilowatt-hous pe Capita Annual Consumption y = x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) Counties well above the line include Canada, Noway (at ove 24, kilowatt-hous of annual consumption), Iceland (nealy 25,), and Finland at (15,). Although climate is a logical explanation, it is inteesting that these electically-connected societies tend also to ank high on many technology indices. Logically, electicity lays a necessay but not sufficient foundation fo electonic netwoking moe geneally, although both may esult in pat fom geneal communitaian impulses in a society, ceating a spuious 2

24 elationship. Counties in hot climates, such as the Aabian Gulf emiates and Singapoe, also tend to have unusually high electicity consumption ates; the latte shaes high ICT technology with the Scandinavians, but the fome do not. This suggests that, indeed, extensive electification may be a necessay, but not sufficient foundation fo ICT. Moving one step up the potential moden-infastuctue ladde, the gaph below shows the sum of telephone land lines and cell subscibes as a function of GDP pe capita. Inteestingly, although thee is a hint of satuation effect at uppe levels, the linea fit is quite a bit bette than the logaithmic (which yields an adjusted R-squaed of only.78). 25 Telephone Lines and Cell Subscibes pe Hunded y = x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) Adding electicity consumption pe capita to the fomulation educes adjusted R-squaed to.85 (o to.86 if electicity consumption is added logaithmically). Electicity consumption by itself has an R-squaed of only.55 with telephone usage (enteed logaithmically, that becomes.64). This begins to suggest that the hypothesis of a foundation fo telephones in electicity use is questionable both electicity and telephone usage ae best explained by GDP pe capita alone. Moving up the posited ladde to pesonal computes, the gaph below shows computes pe thousand as a function of GDP pe capita, once again with a vey high adjusted R- squaed. 21

25 8 Pesonal Computes pe y = x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) Again thee is little hint of satuation in the above cuve. Thee is also a slight hint of an s-cuve with a ise aound 2, and using a powe cuve with slight upwad ise does aise the R-squaed to.88; but that added complexity adds little eal powe to the fomulation. Adding telephone lines plus cell subscibes pe thousand as a dive of pesonal compute usage ates aises adjusted R-squaed only to.87. And looking at pesonal compute usage as a function of telephone lines alone (without cells) yields.82. See the gaph below, which again has a hint of upwad s-shaped behavio with a maked ise (o a theshold phenomenon) aound 4 lines pe 1 citizens. Still again, howeve, GDP pe capita does about as well alone as any moe complex fomulation. 7 Pesonal Computes pe y = x R 2 = Telephone lines pe 1 Moving up ou apidly disintegating ladde to intenet use, the gaph below shows intenet usage as function of GDP pe capita alone, with a stong R-squaed yet again. 22

26 8 Intenet Use Pecent in y = x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) If pesonal compute usage pe thousand is added, the R-squaed climbs above.86 and both independent vaiables ae significant. O if telephone lines ae added instead, the R- squaed climbs to.84. This is the fist eal confimation that thee may be some kind of infastuctue ladde-like phenomenon and it cetainly makes sense that intenet usage would equie telephones and computes. Moving up the ladde once again to intenet hosts, the gaph below with GDP pe capita suggests fo the fist time a vey clea theshold phenomenon (at pehaps $7, pe capita at PPP). It appeas that the cuve should ise even moe steeply than the function that was fit below. Intenet Hosts pe y =.114x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) Again in this instance, the availability of pesonal computes is actually a slightly stonge pedicto of intenet hosts than is GDP pe capita, giving some weak suppot to the ladde theoy. Yet the R-squaed in the figue below is little bette than that fo GDP pe capita. 23

27 Intenet Hosts pe Thousand y =.32x R 2 = Pesonal Computes pe Thousand ISDN subscibes ae a somewhat weak measue of the spead of bandwidth, but the best that we found. The cuve below again suggests that GDP pe capita emains a vey stong basis fo foecasts. The R-squaed ises only to.74 if we use pesonal compute usage instead of GDP pe capita (and it falls to.67 if we substitute intenet usage ates). ISDN Subscibes pe y =.32x R 2 = GDP pe Capita in 2 at Puchasing Pow e (Thousand Dollas) Some oveall conclusions ae possible fom the above analysis, and they have clea implications fo model enhancement: Thee ae close coelations acoss moden infastuctue elements. It may be easonable to use single a indicato of moden infastuctue, initialized by efeence to data on telephone lines and cell phones, pesonal computes, and/o intenet usage (electicity consumption may be a peequisite, but local climate appeas to be a big facto fo that usage, so coelations with it ae not that geat). Thee ae high coelations of GDP pe capita with all elements of moden infastuctue; we can use GDP pe capita as a key dive of moden infastuctue. 24

28 Thee may not much point in tying to epesent sepaate elements with a ladde of development steps doing so seems to add elatively little beyond use of GDP pe capita alone. We can only see significant coelations, suggesting possible step-by-step development between (1) telephone lines and pesonal computes and (2) pesonal computes and intenet hosts. Because the lowe elements of the ladde would, in any case, be diven by GDP pe capita, attempting to substitute lowe ungs as dives fo highe ones would be moe atificial than eal. Given the vaiation in the elationships of all types of infastuctue with GDP pe capita, thee clealy is oom fo the impact of policy decisions; we can epesent such intevention by adding exogenous multiplies. Possibly we should use a fomulation o some mechanism to epesent satuation in moden infastuctue it has to happen in almost all of these aeas, even though it is only eally becoming clea in telephones. Yet satuation in moden infastuctue could be quite a distance away, because new levels of technological capability keep appeaing, such as boadband usage and intenet host numbes. In fact, thee could well be additional layes of infastuctue to add that ae not even foeseen yet. Theefoe pehaps it is bette to build satuation into measues focused on discete technologies (like intenet useage ate), but not into an oveall index of moden infastuctue. 3.3 Infastuctue in IFs Thee ae pehaps two basic appoaches fo IFs to epesent infastuctue, with an emphasis on moden infastuctue. The fist was taken some time ago in the context of the TERRA poject and involves focusing only on the gowth of electonic netwoking. The IFs poject developed a measue of the numbe of netwoked pesons (NUMNWP) that was based on data collected fom the ITU seies on intenet use as a pecent of population. This vaiable is diven by a fomulation that elies on a gowth ate calculated fom the same souce and that builds in a dampening of that gowth ate as the potion of a population netwoked begins to each an exogenously specified satuation limit. That appoach was useful as a fist cut, but it is especially weak fo developing counties whee othe infastuctue, such as electicity netwok coveage, may emain inadequate. The second and pobably pefeable appoach is to build indices of infastuctue that explicitly ecognize the two lagest components of infastuctue stocks, namely electicity and oads, and then explicitly to add telecom fo moden infastuctue, and finally to add netwoking (intenet use is close to the WSIS concept noted ealie). It may even pove possible to go back late and add wate and sanitation and ail, the majo missing components in the Fay and Yepes (23) infastuctue stock accounting system. In elaboating the second appoach, it would be ideal to be able to link physical epesentations (e.g. oad density pe peson and telecom lines pe peson) with monetay epesentations. The latte would give us the basis fo connecting govenment and pivate spending on infastuctue with values of stocks and to intoduce financial tade- 25

29 offs in the model between spending on infastuctue and othe spending (such as on education o the militay). Unfotunately, we have been able to find extemely limited data on govenment infastuctue spending. 17 Thus as a fist step on this second appoach, we have intoduced the physical epesentations only. We have ceated five infastuctue vaiables fo IFs. The fist fou ae specific to majo categoies: oads (INFRAROAD) in thousands of kilometes of oad pe million hectaes of land, electicity (INFRAELEC) in kilowatt-hous pe yea pe capita, telcommunications (INFRATELE) in main and cell lines pe capita, and electonic netwoking (INFRANET) in pecentage of population with intenet connections. In each of the fist thee cases the default dive is GDP pe capita at PPP. In the fouth case the dive is the existing foecast in IFs of the numbe of netwoked people (NUMNWP), the fifth and pe-existing vaiable. As indicated above, that is diven by a gowth ate ove ecent yeas and a satuation fomulation as the potion of the population netwoked appoaches a specified limit (numnwplim). These fou indices say a geat deal about infastuctue levels, both acoss counties and acoss time. POP ANALFUNC( GDPPCP, ) LANDAREA INFRAROAD = * INFRAROAD t= 1 ANALFUNC t 1 POP ( GDPPCP = ), t= ) 1 INFRATELE * INFRATELE t= 1 t LANDAREA * infatelem 1 ANALFUNC( GDPPCP ) = = ANALFUNC( GDPPCP ) t= 1 INFRAELEC * INFRAELEC t * infaelecm 1 ANALFUNC( GDPPCP ) = = NUMNWP INFRANET = *1 * infanetm POP t= 1 * infaoadm The fifth vaiable (INFRAIMOD) is an aggegate measue of the thee moden infastuctue foms: electicity, telecommunications, and netwoking. It cuently is a simple aveage of the thee, each of which is contolled in the computation of the aveage by the expected level given the basic undelying fomulation. Thus if the elative level of infastuctue development in the telecommunications categoy fo a county is 3% above the coss-sectional elationship between GDP pe capita and telecommunications infastuctue levels and emains at 3% above the elationship as GDP pe capita ises, the contibution of telecommunications to the infastuctue index emains essentially constant. 17 We have ed Fay and Yepes with a equest fo help. 26

30 INFRAIMOD whee TeleRatio = ElecRatio = ANALFUNC( GDPPCP ANALFUNC( GDPPCP INFRANET NetRatio = PedictionNet TeleRatio + ElecRatio + NetRatio = *1 3 INFRATELE INFRAELEC ) ) The ationale fo such a fomulation of the oveall index is that it indicates infastuctue stength elative to that expected at diffeent levels of development, not absolute levels that would vay geatly acoss levels of development. The index is scaled the fist yea fom to 1 fo easy compaison acoss counties and time. Such an index would theoetically be eady fo inclusion as a dive in the poductivity epesentation of IFs. It was decided, howeve, that although the index has intinsic inteest, it makes sense to add the individual measues of infastuctue, athe than the aggegate one, to the poductivity fomulation; it seems unnecessay to thow away infomation fom the individual ones. Until thee ae linkages to the infastuctue indices fom govenment and/o pivate expenditues on infastuctue (and govenment will be the fist to be developed) the only eal way to move the moden infastuctue index levels and thus to move poductivity is to change the values of multiplies on some subset of the fou basic infastuctue indicato values (infaoadm, infaelecm, infatelem, and infanetm). The next step fo development aound infastuctue is thus quite obvious: Link govenment spending to infastuctue development, theeby also adding automatic tade-offs acoss attention to infastuctue and othe govenment spending and tansfes The Fay and Yepes (23) wok make povide a foundation fo that epesentation of infastuctue in govenment spending. Biceño-Gamendia, Estache, and Shafif (24) cite them as pegging wold s infastuctue stock, excluding housing, at $15 tillion, 6% in high-income counties, 28% middle-income, and 13% low income; electicity and oad about 8% of total. Biceño-Gamendia, Estache, and Shafif (24) also cite calculations indicating that govt o public utilities financed 7% of total spending in 199s, ODA financed 5-1%. In total, pivate secto financed 2-25% (pp 16-17). Cuently, in developing counties, the public secto is spending oughly between aound 2% (in high middle income counties) to aound 4% (in low income counties) of GDP on infastuctue. (p. 17) 27

31 4. Positioning fo Technological Dynamism: Knowledge Ceation Positioning of a society fo technological dynamism needs definitional claification. On its suface, foundations of technological dynamism could easily be intepeted to encompass stength of educational institutions, stong technological infastuctue, an open society, substantial spending on infastuctue, and even high govenance quality. This section will eview some existing indices that ae, in fact, athe boad and encompassing. Fo the puposes of the IFs poject, and especially fo the pupose of fowad linkages, howeve, it makes moe sense to maintain shape conceptual diffeentiation. Thus sepaately tacking yeas of education, types of technological infastuctue, and dimensions of govenance makes sense fo IFs (they have been addessed elsewhee in this and othe poject epots). In addition to such elements, the most specific components of positioning fo dynamism that appea most in need of incemental epesentation in this pape ae pobably knowledge ceation and knowledge adaptation/diffusion. Thus afte the eview of existing boade indices we will tun to consideation of epesentation of those components in moe detail. 4.1 Review of Existing Indices on Technological Capability Thee ae at least thee existing indices of technological capability/sophistication to conside when detemining how best to epesent knowledge ceation and adaptation within IFs: the Netwoked Readiness Index of the Wold Economic Foum, the Technology Achievement Index of the United Nations Development Pogam, and the Digital Access Index of the Intenational Telecommunication Union. 19 The Wold Economic Foum publishes a well-known annual Global Competitiveness Repot. 2 Thei gowth competitiveness index (CGI) has thee components (23: 21-21): a technology index (weighted ½), a public institutions index (weighted ¼) and a macoeconomic envionment index (weighted ¼). The technology index is built on thee sub-indices: innovation, technology tansfe and ICT (which could be consideed an infastuctue component). Inteestingly, the weighting of innovation and tansfe is diffeent acoss counties, highe fo what ae called the coe innovatos what in intenational political economy might be called the system technology leades. The 19 Thee is also an Infomation Society Index pepaed by the IDC Continuous Intelligence Sevice. Thei web site says the index tacks 52 counties using 15 vaiables: IT spending as a pecent of GDP, softwae spending, IT sevices spending, PC penetation, Intenet uses, home Intenet uses, mobile Intenet uses, ecommece spending, boadband households, wieless subscibes, handset shipments, seconday education levels, tetiay education levels, civil libeties, and govenment couption. They appaently have compiled the index fo 24 and foecast all vaiables fo The sevice is popietay so data and foecasts ae not eadily available. 2 See petitiveness+repot/global+competitiveness+repot html fo access to seveal ecent ones. 28

32 public institutions index is built on two sub-indices: contacts and law and couption. The macoeconomic envionment index is built on thee sub-indices: macoeconomic stability, county cedit ating, and govenment expenditue. Thus the index is an effot to captue a substantial ange of the vaiables that dive economic competitiveness and poductivity, anging well beyond technological competiveness. Fo instance, the govenance measues discussed in an ealie section of this pape ae included. It is the technological index that would paticulaly inteest us hee. The Wold Economic Foum also poduces, howeve, a less-well known annual Global Infomation Technology Repot. 21 That epot includes a Netwoked Readiness Index (NRI) that goes back at least to the Kikman, Osoio, and Sachs (22) vesion fo the epot and has been pepaed in ecent yeas in collaboation with the Wold Bank and INSEAD. 22 In the index had thee component indices, on envionment (including maket envionment, political and egulatoy envionment and infastuctue envionment), eadiness (individual, business, and govenment), and usage (individual, business, and govenment). The envionmental component cuts acoss the govenance and infastuctue domains of this poject, but the eadiness and usage components moe closely focus on the ICT envionment and its usage. As with the GCI, this index appeas to daw on a substantial numbe of suvey esponses, as well as some objective indicatos. 23 The IFs poject has incopoated the index fo 23 in its database unde the vaiable name ICTNetwokReadinessIndex. The United Nations Development Pogam (21) intoduced the Technology Achievement Index (TAI) in its Human Development Repot 21. The index has fou components: ceation of technology (patents, fees fom aboad); diffusion of ecent innovations (intenet hosts pe capita and technology expots); diffusion of old innovations (telephones and electicity consumption pe capita); and human skills (mean yeas of schooling, tetiay enollment in science, mathematics and engineeing). The data appendices of the HDR 21 show computation of the measue fo only 72 counties, pesumably because of unavailability in the undelying input measues (one eason that the Wold Economic Foum s measues, dependent on suvey data ceated by the oganization, has moe extensive coveage). 21 See, fo example, Wold Economic Foum, Global Infomation Technology Repot, and+contact+infomation.html and CD Rom infomation at s+cd-roms.html 22 See a moe ecent desciption by Dutta and Jain (24) fo the epot; the same co-authos also descibed the vesion. 23 One unique featue of the GCI is its vey heavy use of data fom suveys fo many components; the downside of that is that the basic data fo epesenting components such as innovation o technology tansfe in the model is coespondingly limited. 29

33 Inteestingly, the 23 and 24 volumes of the Human Development Repot do not show the index again, but athe povides a table with a vaiety of vaiables tapping technology ceation and diffusion. The vaiables show oughly coespond to the index components named above, but thee ae significant diffeences. Fo instance, R&D spending and scientists engaged in it ae added, while technology expots and electicity consumption ae dopped. It appeas pehaps that, as the UNDP has tuned heavily to a focus on the Millennium Development Goals, it has educed its attention to technology and its suppot of the TAI. This is unfotunate because, except fo the components in its measue that seem to tap infastuctue (like intenet hosts and uses), the measues in its table seem faily shaply to focus on knowledge ceation and adaptation. The IFs poject has incopoated the index fo 21 (pehaps the only yea it was eve compiled) in its database unde the vaiable name ICTTechnologyAchievementIndex. The Intenational Telecommunications Union (ITU) has ceated a Digital Access Index (DAI). The ITU collapses 8 indicatos into five components fo the index: infastuctue, affodability, knowledge, quality, and usage. 24 The IFs poject has incopoated the index fo 22 in its database unde the vaiable name ICTDigitalAccessIndex. Some geneal obsevations about these indices might be useful. Fist, thei content tends to cut acoss a wide ange of gowth/dynamism factos, not just technological positioning. Thee is tapping of some combination of human capital, infastuctue, govenance, and knowledge/technology level components, the mixtue of which vaies acoss the indices. Second, most of the measues ae oiented towads desciption of the cuent situation, not foecasting. Pehaps the Netwoked Readiness Index of the Wold Economic Foum is the most clealy futue-oiented, and the authos note that thee appea to be impotant theshold effects with espect to the benefits of netwoking and ICT developments (Dutta and Jain 23: 16). Thid, in pat because of the conflation of vaious elements, but also because of the lage numbe of factos involved in most of these indices, it is not easy to see a path towads epesentation of them in the model. That is the topic of the next section. The thee indices discussed above ae athe diffeent in thei components, but the table below shows that they ae nonetheless highly coelated. Digital Access Technology Achievement Netwok Readiness Technology Achievement.9 Adjusted R-squaed Coelations among Thee Moden Technological Indices 24 See the ITU Digital Access Index at 3

34 4.2 Conceptualizing Knowledge Ceation and Adaptation/Diffusion fo IFs None of the technology-oiented measues discussed above is eally a measue focused on the ability of a society to ceate knowledge o to adapt it fom elsewhee. They all tap multiple dimensions that this analysis and the IFs model ae attempting to tack with moe cae sepaately. Moeove, each boade index is subject to a vaiety of additional limitations fo the puposes of IFs, especially the availability of undelying data seies ove a significant peiod of time. It is impotant to emembe that we have aleady coveed govenance and infastuctue dimensions in pevious chaptes and that we intend to tun to globalization in the next chapte. What is of inteest in this chapte and the next is knowledge ceation and adaptation/diffusion. That naowe focus is, to some consideable degee, the same as that of the 1998/99 Wold Development Repot: Knowledge fo Development, unde the team leadeship of Cal Dahlman (Wold Bank 1999). Based on that issue of the WDR and fom the above discussion of indicatos, especially the UNDP s Technology Achievement Index, it appeas useful to conside the following components and dives of knowledge ceation and diffusion, ecognizing that all components in the ceation categoy can be vey helpful also with espect to adaptation: Knowledge ceation. Reseach and Development expenditues; patents ganted to esidents; numbes of scientists and enginees (o size of tetiay education moe geneally); eceipts of oyalties and license fees. Knowledge adaptation/diffusion. Manufactued impots as a potion of total impots o the GDP; inflows of foeign diect investment (FDI) as a potion of total investment o the GDP; payments of oyalties and license fees. Looking at this list it becomes clea that we should defe consideation of knowledge adaptation/diffusion to the next chapte and the discussion of globalization. The A. T. Keaney/Foeign Policy globalization index (GI), to be discussed in that chapte, is heavily linked to vaiables such as tade and FDI. In fact, within that index is a subdimension called economic integation that we have eplicated in IFs as an appoach to captuing those key dives of knowledge adaptation/diffusion. This chapte esticts focus to knowledge ceation. Can the IFs model easonably foecast the elements identified above as impotant to knowledge ceation? IFs includes a calculation of eseach and development expenditues, aleady diven by deep dives, open to policy manipulation of govenment spending, and accessible via an exogenous multiplie. It also includes the numbe of individuals (o the pecent of population) that have tetiay education. It does not include any vaiables on patents, scientists o enginees as sepaate fom othe tetiay degee holdes, o eceipts of oyalties o license fees (although the database has seies on each). Fo the puposes of long-tem foecasting, R&D expenditues and tetiay gaduates vey pobably ae the best dive vaiables fo knowledge ceation in any case, and the est of this chapte will exploe 31

35 them, concluding with the specification of a knowledge society index fo IFs that is based upon them. 4.3 Exploing Knowledge Ceation: R&D The discussion of R&D in this pape is a supplement to that of the companion pape (Pat 1), which exploes the poductivity liteatue fo insights about the impact of R&D spending on economic gowth and descibes the implementation of a poductivity fomulation in IFs that dives multifacto poductivity with a vaiety of vaiables including R&D spending. This section supplements the discussion of the companion pape by exploing the elationships between GDP pe capita and R&D on the one hand (backwad linkages fo R&D) and between R&D and economic gowth on the othe hand (fowad linkages fo R&D) using the database of IFs itself. The data on R&D spending in IFs come ovewhelmingly fom two souces, the Wold Bank s Wold Development Indicatos (WDI) and the Oganization fo Economic Coopeation and Development (OECD). The advantage of WDI data is extensive county coveage, but the cost is a lack of disaggegation of R&D types. The OECD offes such disaggegation, including public and pivate expenditues, but povides vey limited county coveage. The two gaphs below use the county-extensive WDI data to exploe the elationship between GDP pe capita at puchasing powe and the potion of Goss National Income (GNI) spent on R&D by public and pivate sectos. 4 R&D as Pecent of GNI (2) y =.681x R 2 = GDP pe Capita in Thousand Dollas at PPP (2) 32

36 R&D as Pecent of GNI (2) y =.5766Ln(x) R 2 = GDP pe Capita in Thousand Dollas at PPP (2) In the above two gaphs, the linea elationship looks stonge and that is the one used within IFs to epesent the backwad linkage of R&D to GDP pe capita. Among the outlies nea the top of the gaphs ae Isael at $19,7 and 3.7% spending on R&D and Sweden at $24,3 and 3.76%. A sample outlie at the bottom of the gaph is Cypus at $19,5 and.25%. But it will be impotant fo both backwad and fowad linkages to distinguish pivate and public R&D. The thee gaphs below use OECD data fo a much moe limited set of counties to show the elationships between R&D of fims and govenments sepaately with GDP pe capita. R&D of Fims as Pecent of GDP (1999) y =.875x R 2 = GDP pe Capita in Thousand Dollas at PPP (2) 33

37 R&D of Fims as Pecent of GDP (1999) y = 1.523Ln(x) R 2 = GDP pe Capita in Thousand Dollas at PPP (2) R&D of Govenment as Pecent of GNP y =.35x R 2 = GDP pe Capita in Thousand Dollas at PPP (2) Seveal conclusions can be dawn fom the above gaphs. Fist, pivate R&D is nealy an ode of magnitude lage than public R&D. Second, the slope of pivate R&D is quite a bit highe, suggesting that within OECD counties with lowe incomes ae elatively moe eliant on govenment spending than those with the highest incomes. Diving R&D foecasts within IFs is athe complicated as a esult of the diffeent pattens and the impotance of the pivate and public distinction. In lage pat because of the two data souces and thei distinctive coveage, it was decided to epesent sepaately within IFs total R&D spending as a potion of GDP (RANDDEXP) and govenment spending on R&D (GDS, RandD). Tuning to fowad linkages, the next two gaphs show the elationship between total R&D (public and pivate) and GDP gowth between 199 and 2 and then between public R&D only and the same gowth. Unfotunately it was not possible to use R&D spending at the beginning of the peiod (199) as desied to captue possible causal diection with lags, because thee wee not enough data points. 34

38 3 GDP in 2 ove GDP in y = -.65x R 2 = Public and Pivate R&D as Pecent of GDP (Most Recent) Supisingly, the gaph above suggests an invese, not a positive impact of R&D spending levels on gowth. The one below, focusing on govenment R&D spending, shows a vey slightly positive one. But both gaphs have coelations that ae too low to be significant. In geneal, these esults contadict the findings of the poductivity liteatue epoted in the companion pape to this one. Because the studies in that liteatue go so much moe deeply into the elationship, howeve, the IFs fomulation fo the impact of R&D on poductivity comes fom it. The two gaphs ae slightly disconceting, but only slightly fo thee easons: (1) the time sequences wong in them, (2) GDP gowth is quite diffeent fom poductivity gowth, (3) the data set used hee is extemely limited. The main pupose of showing the two gaphs is to indicate the complications of exploing the elationship and theeby to einfoce the utility of using moe specialized liteatue in ceating the poductivity fomulations of IFs. 3 GDP in 2 Ove GDP in y =.312x R 2 = Public R&D as Pecent of GDP (Most Recent) 35

39 4.4 Exploing Knowledge Ceation: Tetiay Education In paallel to the last section, this one exploes the linkages between GDP pe capita and levels of tetiay education and between tetiay education and economic gowth. The fome is quite unnecessay with espect to model specification, because IFs includes a full fomal education model acoss pimay, seconday and tetiay levels (developed by Mohammod T. Ifan as pat of his Ph.D. dissetation wok). Nonetheless, it is useful to see the elationships. The two gaphs below show the quite stong elationships between GDP pe capita and the numbe of those ove 15 yeas of age with tetiay education (the IFs database also includes infomation on those ove 25). Pecentage of Population Ove 15 with Tetiay Education y =.3133x R 2 = GDP pe Capita in Thousand Dollas at PPP (2) 3 Pecentage of Population Ove 15 with Tetiay Education y = 2.582Ln(x) R 2 = GDP pe Capita in Thousand Dollas at PPP (2) In the above gaphs, the outlie at the 24.9% level of tetiay education is the United States; the outlie at $1,15 and.9% is Mauitius. 36

40 The two gaphs below show the elationship of GPD pe capita with goss tetiay enolment athe than levels within the adult population. Goss Enollment in Tetiay Education (21) y = x R 2 = GDP pe Capita in Thousand Dollas at PPP (2) 1 Goss Enollment in Tetiay Education (21) y = Ln(x) R 2 = GDP pe Capita in Thousand Dollas at PPP (2) In the above gaphs the outlie in lowe ight-hand cone is Luxemboug; the outlie at $25,1 and ove 8% goss tetiay enollment is Finland. In the fomal education model of IFs, the tetiay intake ate is available. The figue below shows the elationship of GDP pe capita with tetiay intake levels in the IFs model itself. Unfotunately, the lage numbe of points on the logaithmic cuve do not indicate a supisingly stong elationship; instead they ae illustative of the lage amount of missing data fo tetiay education (it also is lagely available fo OECD counties); the points on the line ae estimated fom the function computed with the smalle set of data that is available. 37

41 EDTERINT[],Total Tetiay Education Intake Rate (Pecent of Age Goup) as Function of GDP pe Capita 7 Finland Hungay Is ael J apan 6 South Koea Denmak New Zealand Hong Kong Unitd Kingdm Aus talia Cy pus Ieland Aus Canada Qata Sweden Singapoe tia USA Slov enia Taiwan Ic eland Noway 5 Kuwait Bahamas, The UAE Potugal Spain Belgium Fanc e Lux emboug Bahain Bunei Nethelands Babados Geec e Malta Thailand Bots wana Belaus Chile Mauitius Pueto Oman Ric o 4 Switz eland Coatia Cos Tinidad Poland Es South tonia ta Saudi Afic a Ric a Aabia Italy Gemany Peu Rus s Beliz e Algeia Bulgaia Columbia Genada Liby Latv Lithuania ia Uuguay Philippines Ian St. Romania Luc a Agentina Gabon Kaz Panama Venez Tuk ak Baz hs uela ey il tan Slovak Rep 3 Cz ec h Republic Egypt Fiji Albania El Lebanon St. Mac Salvado Dominic Vinc edonia ent anrep and the Genadines China J odan Namibia Malay s ia Amenia Cape JGuy Mic amaic ones ana Iaq Vede a ia, Fed. Sts. Pales Samoa Si Suiname Tonga Tuk menis tan Uk Lanka aine Sy Mex ic o Az Ec Mooc ebaijan uado Maldiv ia Swaz tine c oes iland 2 Boliv Honduas Geogia Zimbabwe Ky gy Guatemala Paaguay z India Equatoial Guinea Banglades Nic Moldov Uz Vanuatu bek is aagua a Tunis tan ia h Cuba Solomon Ghana Pak Yugos Vietnam Papua is tan lav NG Isia lands Bhutan Democatic Afghanis tan Cambodia Comoos Cote Cameoon Gambia Mongolia Les Indones otho ia Haiti My Laos Djibouti anma Iv oie Republic of Timo-Leste Nepal Senegal 1 Cental Angola Sao Sudan Togo Uganda Mauitania Tome Guinea AfR and Pinc ipe Benin Keny Bos nia a Libeia Eitea Chad Buk ina Fas o Congo Buundi Ethiopia GuineaBis Nigeia Moz Madagas Mali Rwanda Noth Tajik is Koea tan Zambia Yemen Zaieambique cs a Malawi Nige SieaLeo Somalia Tanz ania GDPPCP[] Yea = 2 In spite of the elatively small numbe of eal data points in the figue above, thee is some useful infomation thee. The outlies ae, fo the most pat, not supising in the figue. We would expect intake ates to be exceptionally high in Isael, Finland, and South Koea. And we would expect somewhat lowe ones in Italy and Gemany. A significant supise is that intakes have isen so shaply in many counties that lage numbes ae now well above the US ate. The implication of this is that the US will steadily lose the shap advantage that was shown in an ealie figue with espect to stocks of those within the adult population with tetiay education ates. Tuning to fowad linkages between tetiay education and economic gowth, the impot of the figue below is again geatly limited by the small numbe of counties epesented in it. As with R&D, howeve, we once again see an invese elationship athe than the expected positive one. 3 GDP in 2 Ove GDP in y = -.36x R 2 = Tetiay Intake Rate (OECD A+B), Most Recent 38

42 Tuning in the figue below to population with tetiay education instead of intake ates, and moving to education data in 199 and theefoe in advance of the peiod of gowth examined, the figue below again supises somewhat with an invese elationship between tetiay education and gowth. 4 GDP in 2 ove GDP in y = -.151x R 2 = Potion of Population Above 15 w ith Tetiay Education (199) The unexpectedly invese elationship in the figues above is not statistically significant. Does the level of GDP pe capita influence the elationship? Could it be that iche counties with highe education levels could have gown less apidly in the 199s than pooe counties? If we add GDP pe capita at PPP to the analysis, we find in the table below that the negative elationship between tetiay education and economic gowth in the 199s actually intensifies and has a high t-value. This esult is especially supising since the 199s wee supposed to have been a decade influenced by an emegent knowledge society. 39

43 We would at least expect that highe potions of tetiay gaduates would esult in highe ates of patents pe capita. Supisingly, the figue below shows again a small negative elationship. (Iceland was emoved because it had nealy 1, applications pe million people that may eflect the big push in Iceland on enegy and biotechnologies, but it might also be a data eo). Patent Applications pe Million people (1997) y = x R 2 = Tetiay Gaduates as Potion of Population Above 15 (2) Oveall, the above analysis does not give us a geat deal of confidence in any elationship between tetiay education levels and economic gowth ates. In contast to the analysis 4

44 of R&D, thee is not a poductivity liteatue to fall back on that povides us contay infomation and a basis fo including tetiay education in the IFs poduction function in spite of ou own analysis. Thus we will not include it (see the companion pape, Pat 1, fo a discussion of the linkages between knowledge vaiables and poductivity). 4.5 Implementation of Knowledge Ceation Index in IFs In spite of the decision not to include tetiay education among the dives of poductivity, it is useful to have a measue of knowledge ceation tied to R&D spending and tetiay education. Theefoe a vaiable called knowledge society (KNOWSOC) was ceated based on R&D spending as a potion of GDP and on the tetiay gaduation age as a pecentage of population. The two components ae weighted equally. KNOWSOC = RANDEXP + EDTERGRATE 2,Total The figue below shows how the knowledge society index may povide some useful insights. That figue looks at the index as a function of GDP pe capita (at PPP). KNOWSOC[] Knowledge Society Index Displayed Acoss GDP pe Capita (PPP) Levels Many Points ae on the Logaithmic Line Because of Missing Data Is ael Koea South J apan Finland Ic eland Sweden Lux emboug Fanc e Belgium 6 Unitd Singapoe Kingdm Taiwan Denmak Qata Switz eland Hungay Gemany 5 SlovNew eniazealand Aus talia Bahamas UAE Canada Ieland Bunei Bahain Cy pus Hong Kong 4 Babados Malta Geec e Spain Aus tia Noway Belaus Rus Coss ta iapueto Oman Ric a Ric o Nethelands Bulgaia Poland Es South tonia Saudi AficCz aaabia Kuwait ec h Republic 3 Thailand Coatia Algeia Lithuania Bots wana Slovak Rep China Philippines Genada Liby Agentina Italy Gabon Beliz Dominic Ian Latva Peu Panama Romania St. Luc Tinidad ia Potugal Uk aine Venez e Albania Colombia Chile anrep Fiji Kaz Tukuela ak hs ey tan 2 JLebanon odan St. Mac Vinc edonia ent and the Genadines Amenia Baz il India Az Cape JGuy Egy Mic ebaijan amaic Maldiv El Salvado pt ones ana Vede a ia, Malay Mex Fed. ics Sts oia. Cuba Moldov Boliv Geogia Ec Pales Samoa Mooc Si Suiname Tonga Tuk Swaz Tunis menis iland tan Sy Guatemala uado ia Lankaa tine c o Honduas Les Ky Afghanis Iaq Equa gy otho Paaguay z Mauitius Guinea Namibia Uganda Sebia Uz Zimbabwe 1 Vanuatu bek Ghana Pak Nic Papua aagua Montenego tan Uuguay Togois tanng Cote Cameoon Gambia Djibouti Angola Banglades Iv oie h Bhutan Benin Bos Buk Cental Comoos Haiti My Mauitania Mongolia Solomon Is lands Nepal anma Indones ia Sao Sudan Timo Vietnam Senegal Cambodia Laos Guinea Tome nia ina Fas AfRand Pinc ipe o Congo, Buundi Malawi Ethiopia GuineaBis Nigeia Eitea Moz Madagas Mali Chad Libeia Rwanda Koea Keny Tajik is ambique anoth tan SieaLeo Somalia Tanz Zambia Yemen ania Republic Democatic cs a of Republic of GDPPCP[] Yea = 2 Thee ae some potential supises in the figue above. Finland, Isael, Iceland, Japan, and South Koea, all sit comfotably above the cuve. A fai numbe of Euopean counties, howeve, including Italy, Potugal, Spain, Austia, and Noway ae positioned below it. So, too, is Ieland (the Celtic Tige ). Although it is impossible to see in the clutteed gaphic above, the position of the fou BRICS (Bazil, Russia, India and China) is also significant. On public R&D alone, all fou ae well above values expected at thei levels of GDP pe capita, indicating a stong govenmental effot to move fowad on the USA 41

45 knowledge society dimension. But when total R&D and tetiaty gaduation ates ae added to the pictue and into the index above, with the patial exception of China none paticulaly stands out fom the cowd. This chapte has focused on knowledge ceation and the knowledge society index of IFs. The next tuns to knowledge diffusion/adaptation, a key element of globalization. 42

46 5. Globalization This chapte shifts focus to globalization. When the topic tuns to possible indices of globalization only one leaps out: the A.T. Keaney/Foeign Policy Globalization Index (GI). Foeign Policy eleased the fifth annual esults in thei May/June 25 issue. 25 Thee is no tuly competitive index of globalization. See aticles by Kudle (24) and Lockwood (24) fo some evaluations of the GI. Although the index has changed a little ove time, its stuctue has emained elatively stable. It consists of fou sub-indices: (1) political engagement (intenational oganization membeships, UN peacekeeping, teaties atified, and govenment tansfes o aid); (2) technological connectivity (intenet uses, intenet hosts, secue seves); (3) pesonal contact (tavel and touism, intenational telephone taffic, emittances and pesonal tansfes); and (4) economic integation (tade and foeign diect investment; in past yeas this also included potfolio flows and income payments). This chapte will exploe two issues aound the Globalization Index (GI). The fist is the degee to which IFs can eplicate the GI o something appoximating it. This poject has added a vaiable called GLOBALIZ to the model fo that pupose. Many components of the index exist within IFs. On the political engagement dimension, IFs epesents official developmental assistance o foeign aid. It makes no attempt to captue elements such as intenational oganization (IO) membeships o teaty atification, because these vaiables ae highly subject to political decisions. On the technological connectivity dimension, the INFRANET index descibed in Chapte 3 of this epot taps intenet uses; intenet hosts and seves ae closely elated and, in long tem foecasting, would add elatively little. Theefoe this chapte will focus on the pesonal contact dimension (descibing a new measue in IFs called PERSCON ) and the economic integation dimension (descibing a new measue called ECONINTEG). The GLOBALIZ index of IFs bings these fou dimensions togethe in paallel to the GI. The second issue is what to do with the index. Beyond its intinsic inteest, ae thee any fowad linkages of impotance? The last chapte discussed the most obvious one, namely the linkage of globalization to knowledge diffusion acoss the global system. The last section of this chapte will etun to this issue. 5.1 The Pesonal Contact Dimension Chapte 3 descibed the addition to IFs of a measue on telephone infastuctue (INFRATELE), a key foundational element fo both domestic and intenational telephone contact. Although the GI uses actual minutes of intenational communication, that is a bette shot-tem desciptive measue than a foecasting measue. IFs uses INFRATELE as the backbone of such taffic volume fo its PERSCON measue. 25 The timing of annual elease has become somewhat late ove time. The two pevious yeas wee eleased in Jan/Feb 23 and Mach/Apil

47 With espect to emittances and pesonal tansfes, the GI measue builds on a data seies called Compensation to Employees 26 Although this is useful, IFs looks to the boade Wold Bank data seies on woke emittances. In the GI seies, which is keyed heavily to copoate payments, the value fo Mexico in 2 was about $1 billion and that fo the United States was about $3 billion. In the seies on woke emittances seies the values wee close to $4 and $18 billion. IFs uses the boade seies because these numbes ae integated into the model s cuent account calculations and ae impotant to it; they ae also impotant to globalization and would pehaps be used in the GI measue if they wee poduced fast enough to meet the annual publication cycle. As a geneal ule, the IFs fomulation ties to look to the undelying and lage-scale elements of the globalization pocess, not just to the latest desciptive seies. The figue below shows woke emittances as a potion of GDP. What stikes one immediately is that many of the counties most globalized by such flows ae not even among the 62 counties on which the GI focuses (those 62 include the lagest and ichest counties of the wold) and ae cetainly not among the stas of the GI anking. Fo instance, Eitea, Lebanon, Lesotho, and Albania appea highly globalized in the figue. It could be agued that emittance eceipts might indicate the extent of a diaspoa o even vulneability to globalization pocesses, but not so much globalization in the positive sense of using the pocess that A. T. Keaney/Foeign Policy nomally taps. Yet flows of Mexican immigants into and out of the U.S. and thei emittances home have been a vey poweful foce fo globalization of both counties. In adding this measue to PERSCON, the values wee capped at two times the global aveage to limit the weighting of exteme cases. 26 See fo data behind the 25 index. 44

48 It would also be possible to focus in constucting a measue of pesonal contact on migation ates as a potion of population. The figue below shows those ates at the tun of the centuy. In some cases, especially fo inwad flows, they clealy do epesent an attactiveness to othe counties that could be consideed pat of globalization. Yet fo many of the developing counties, highe values clealy can indicate living in a bad neighbohood and eceiving efugee flows (note Bosnia and Buundi) o can indicate a epatiation of ealie outwad flows (e.g. Afghanistan, Eitea, and Timo-Leste). Again the figue suggests the complexity of extending many measues beyond the ichest counties. Although Singapoe, Hong Kong and Isael always ank highly on the GI index, Afghanistan and Timo-Leste do not. The PERSCON measue of IFs does not include these migation ates the pupose of this discussion has been to show the complications involved in choosing vaiables fo it. 45

49 5.2 The Economic Integation Dimension Tuning to economic integation, the measue of ECONINTEG in IFs focuses, as does the GI measue, on tade and foeign diect investment. Moe specifically, the GI measue appaently uses expots as the indicato of tade and inflows as the measue of FDI (looking at the data shown on the A.T. Keaney web site). Obviously, it is impotant to look at these elative to GDP, not in absolute tems. Thee is significant eason to believe that the both tade and FDI ae closely tied to knowledge diffusion and thus to poductivity, an issue that to which a late section etuns. Exploing Knowledge Diffusion: Tade The figue below shows how tade has gown as a potion of GDP since the 196s. This gowth and that of financial flows can easily be consideed the backbone of the globalization pocess. 46

50 Is thee any kind of obvious elationship between economic development level and tade? The figue below suggests that thee is not. That figue excludes pimay sectos to focus on those aspects of tade that might be most likely to cay knowledge with them (manufactues, sevices, and ICT tade). Some high ates of tade appea associated with entepôt economies (e.g. Hong Kong and Luxemboug). Some appea associated with what might be called dependent economies, e.g. Eitea, Belize, and Afghanistan. Othes ae entie economies, e.g. UAE and Bahain. Those economies who might be most benefiting fom technology tansfes embedded in tade, like Malaysia, Ieland and Belgium, ae somewhat swamped by counties manifesting these othe categoies of tade connection. One could ague that this weighs against the inclusion of tade in the globalization measue. At the same time, howeve, it is clea that counties like Aghanistan, Belize, and the UAE ae, in fact, heavily globalized in many espects just not, pehaps, as the GI measue is nomally intepeted. 47

51 MS [ ]+MS [ ]+MS[ ] / GDP [ ], Manufact ues+sevices+i CTech/ Equatoial Guinea Impots as Ratio to GDP Excluding Pimay Sectos Hong Kong Lux emboug Pueto Ric o 1. Afghanis tan Malay s ia Les Guy otho Swaz anailand Ieland.8 Es tonia Malta Eitea Belgium Angola Beliz e Bahain Cambodia Mongolia Moldov Samoa a Belaus Slovak Rep UAE.6 Chad Bos nia Cape FijiVede Babados Hungay GuineaBis s Cz ec h Republic Vietnam Maldiv es Aus tia Bulgaia Congo Gambia GhanaMac St. Thailand edonia Luc Coatia Mauitius Bahamas Slov, The enia Nethelands Laos Genada Honduas J Albania amaic J odan alatv Lithuania.4 Vanuatu Pales Tuk St. tine Vinc Philippines menis Namibia ent Bots Cos tan iaand the Genadines wana ta Ric a Bunei Denmak Canada Cy pus Iaq Is ael Taiwan Malawi Zambia Nigeia Mali Tajik Sao Mauitania Nicis Tome UkPaaguay Djibouti Az ebaijan El Salvado Kaz and ak Pinc hs tan ipe Togo Kuwait Finland GemanyIc eland Ethiopia Moz Noth Si ambique Koea Tonga aine Tunis ia Yugos lav Lanka ia Tinidad Potugal Chile Aus talia Democatic Ec uado Lebanon Liby a Oman Geec e Qata Senegal Cote Cameoon GuineaAlgeia Gabon Dominic Romania South Republic anrep New Koea Sweden Singapoe Switz eland Somalia Suiname Zealand Nepal Haiti Solomon Papua of Timo-Leste Benin Bhutan Boliv Ky Indones Mooc gy Iv Guatemala China ia oie zng Is Ian c lands o Mex Poland South ic o Afic a Uganda Uz bek is tan Spain.2 Libeia Keny amic ones ia, Fed. Sts Agentina. FancItaly e Noway Panama Tuk ey Unitd Kingdm Tanz Madagas Rwanda Buk Banglades Amenia Sy ia ina Fas Columbia o Buundi Comoos Geogia c a Rus s ia Saudi Aabia USA Nige Yemen Zaie Pak Zimbabwe ania Egy pt h J apan SieaLeo Cental India is tan Uuguay Peu Venez uela AfR Baz il Sudan Cuba. My anma GDPPCP[] Yea = 2 Manufactues vey much dominate above the gaph. Looking only at ICT impots (below) changes the pespective and highlights somewhat moe the counties in the developed wold that tend to ank highly on the GI. But the data quality is low in this secto and thee is still a stong entepôt -economy effect. Impots of ICT as Ratio to GDP Ieland.25 MS[]/GDP[],ICTech/.2 Equatoial Guinea.15 Hong Kong Hungay Lux emboug Guy ana.1 Les Afghanis otho tan Es tonia Nethelands Swaz iland MalayPueto s ia Ric o Sao Tome and Pinc ipe Eitea Angola Belaus Malta GuineaBis Mongolia Moldov Samoa sa Slovak Bahain Rep South Koea Tajik Beliz Babados e Belgium Cambodia Gambia Chad Mauitania iscape Vede Cz ec h Republic Bos Djibouti JMaldiv odan Fiji es nia JAlbania amaic Bulgaia Congo GhanaSt. Bahamas, The Honduas Mac Vinc Genada St. Thailand aedonia Aus tia Amenia Az ebaijan Latv Lithuania Luc Coatia ent and Mauitius the Genadines Laos Cos Mex ic Ric o Slov enia Togo Nic aagua Tonga UAE.5 Vietnam Vanuatu Uk Kaz Namibia Algeia Bunei a Cy pus Finland Denmak Malawi Nigeia ak hs tan Aus talia Canada Democatic Bhutan Geogia KyPales Philippines Sweden El Salvado Is ael Libeia Gabon Republic Bots wana of Timo-Leste Ethiopia Moz Mali Noth Papua Haiti Iaq ambique gy Lebanon z Mooc Mic Koea Paaguay ones NG tine Singapoe SieaLeo Somalia Senegal Solomon Si Suiname Tuk aine Tunis Lanka menisia Is Kuwait Benin Comoos Cote Cameoon Chile Boliv EcIvuado Agentina Buundi Buk Banglades ina China oie Dominic c Romania Liby lands o ia, Tinidad tan Zambia Yugos lav a Fed. Sts. Taiwan Yemen Unitd Kingdm anrep Oman New Zealand Gemany Keny Nepal Guinea Uz Indones a bek is tan Guatemala Ian ia Fanc e Ic eland Nige Panama Poland Potugal Qata South Afic a Switz eland Tanz Madagas Rwanda Uganda Sy ia Zaie Fas o Cental Cuba Pak Zimbabwe ania Egyc pt a AfR Columbia Tuk Rus eys ia h Geec e Italy Noway India is tan Saudi Aabia Spain Sudan Peu Uuguay USA Venez Baz uela il J apan. My anma GDPPCP[] Yea = 2 48

52 Exploing Knowledge Diffusion: FDI Tuning to FDI, the figue below, like that fo tade, shows the apid gowth of this foundation of globalization since the 196s and especially since the 198s. It also shows a suge and collapse in the 199s and theeafte, indicating a stong cyclical element aound FDI flows to which we will etun. Among the impotant questions fo the epesentation of FDI in IFs and within the economic integation measue ae whethe to use flows o stocks of FDI and how to dive the foecast of FDI. The est of this section will focus on these issues. Thee ae two pimay souces of data on FDI fo the IFs poject, the Wold Bank s Wold Development Indicatos (WDI) and UNCTAD s Wold Investment Repot (WIR). The two figues below show the flow data fom each as a function of GDP pe capita at PPP. The fist figue below looks at the patten of flows in 2 and the second looks at 22. Wheeas thee appeaed in 2 to be an upwad sloping cuve linking GDP pe capita and FDI flows, that disappeaed in 22. The eason is most likely that the downtun in FDI flows afte 2 was pimaily fo meges and acquisitions (not geen field investments) and M&As tend to be located dispopotionately in moe developed counties. 49