New Economy and the Effects of Industrial Structures on International Equity Market Correlations

7/28/2019 New Economy and the Effects of Industrial Structures on International Equity Market Correlations

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ECONOMICS AND RESEARCH DEPARTMENTERD WORKING PAPER SERIES NO. 31

Cyn-Young Park and Jaejoon Woo

December 2002

Asian Development Bank

New Economy and the Effectof Industrial Structures

on International Equity MarkeCorrelations


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ERD Working Paper No. 31

NEW ECONOMY AND THE EFFECTS OF INDUSTRIALSTRUCTURESON INTERNATIONALEQUITYMARKETCORRELATIONS

Cyn-Young Park and Jaejoon Woo

December 2002

Cyn-Young P ar k is an Economist at t he Mekong Depar tment of the Asian D evelopment B an k. J aejoon Woois an Economist at the Organization for Economic Co-operation and Development (OECD). All errors arethe authors an d the usua l disclaimer a pplies to the Asian D evelopment B an k and OECD . An earlier versionof th is paper was wri t ten while Cyn-young Park was an economist at OECD.


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ERD Working Paper No. 31N EW E CONOMY AND THE E FFECTS OF INDUSTRIAL S TRUCTURES ON INTERNATIONAL E QUITY M ARKET C ORRELATIONS

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Asian D evelopment B an kP.O. Box 7890980 ManilaPhi l ippines

2002 by Asian Development BankDecember 2002ISSN 1655-5252

The views expressed in this paperare those of the author(s) and do notnecessarily reflect the views or policiesof the Asian Development B ank.


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Foreword

The E RD Working P a per S eries is a forum for ongoing a nd r ecently completedresearch a nd policy stu dies underta ken in the Asian D evelopment B a nk or on its beha lf.The Series is a quick-disseminat ing, informal publica tion mean t to stimula te discussiona nd elicit feedback. P a pers published under t his Series could subsequently be revisedfor publication a s a rticles in professiona l journa ls or cha pters in books.


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Contents

Abst ra ct vii

I. I N T R O D U C T I O N 1

I I . D ATA D ES C RIP TION AND CORRE LATION ANALYS E S 3

I II . E CONOME TRI C ME TH OD S AND E MP I RI CAL RE S ULTS 10

A. E st ima ting Indust ry a nd Count ry Fa ct ors by B eta s 10

B . Indust ry-specific Tra nsmission of S hocks 14

IV. C ONC LU S ION 16

References 17


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Abstract

This pa per investiga tes t he effects of the ongoing cha nges in indust ria l structu resarising from technology evolution and financial liberalization on the correlations ofinternational equity markets. Results point to the greater influence of industry structureson the internat ional co-movements of equity returns, largely driven by economicintegra tion an d recent t echnology spillovers. First, t he correla tion ana lyses find t ha tthe cross-countr y correla tions ha ve not only significa ntly increa sed, but the increasesa lso seem to be more pronounced in the sectors tha t r elate t o the new economy. S econd,based on a forma l multifactor pricing model, the estima ted risk exposure of the na tionalindustr y index to the world industry a nd local ma rket indices illustra tes the growingimporta nce of th e world indust ry fa ctors in the equity pricing rela tive to the nat iona lma rket. Third, emergence of indust ry-specific tr a nsmission in th e telecom, media, a ndtelecom sectors is indicat ed. The vector a utoregression a na lyses, wh ere a U S shock ofthe industry-specific component is found to transmit more widely and effectively thanth a t of the country -specific component w ithin th e TMT sectors, su pport th e hypothesisthat the new economy has become a new channel of financial transmission, at leastam ong the G7 mar kets .


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I. INTRODUCTION

In recent decades, the financial deregulation of domestic capital markets, the removal of legala nd nonlegal barr iers to capita l flows, a nd improved access to information ha ve substant iallyra ised f inan cia l integrat ion a cross capital ma rkets in ma jor industr ia l ized countr ies . One

impor ta n t implica t ion o f f ina nc ia l in tegra t ion i s tha t n a t iona l s tock ma rke t re tu rns w i l l beincreasingly influenced by global rather than domestic factors, since in a financially integratedmarket similar assets should display the same risk-adjusted returns. Indeed, stock market co-movements a cross borders ha ve been w ell documented by nu merous empirical st udies.

The existing studies on the issue of integration can be broadly classified into two categories.The first stra nd of the litera ture tr ies to directly estima te interna tional risk fa ctors priced in the

domestic asset returns, using international capital asset pricing models (ICAPM). Clearly, withincreasing integra tion, interna tiona l factors ar e expected to play a grea ter role in the pricing ofnational markets. The studies often report mixed results, providing no clear evidence of integrationor segmenta tion. Some stud ies find evidence of time-va rying integra tion (see, for example, Solnik[1974]; S tu lz [1981]; Fer son a nd H a rvey [1991]; a nd B eka ert a nd H a rvey [1995, 1997]).

The second stra nd of the litera ture suggests t ha t t he degree of rea l economic integrat ionis importa nt in explaining equity ma rket co-movements. The line of a rgument is tha t t ighter tr a delinkages and greater capital mobility will lead to higher correlations of future dividend growthacross countries and thus higher correlations of equity prices (for example, see Fama and French1989 a nd B ra cker et a l. 1999). A relat ed research interest a lso focuses on t he increa sing interna tionalspillovers a nd m a rket conta gion since the October 1987 stock ma rket cra sh (see Bennet t a nd K eleher1988, Roll 1988, and Dwyer and Hafer 1988). These studies so far indicate that stock marketcorrelat ions are s ignif ica nt a nd tend to increase over t ime, but tha t t hey vary substant ial ly indegree depending on the geogra phica l proximity a nd indust ria l composition similar ity betw eencountries.

Nat urally, na tiona l ma rkets wit h different industr ia l s tructures ar e exposed to differentrisks. 1 For exam ple, a country with a high concentra t ion of the ma nufacturing industry is m oreexposed to the risks concerning th e world man ufacturing indust ry, th a n a nother where the ba nkingindustry is more domina nt. I n t his context, the effects of different industr y mixes wit hin na tionalma rkets on interna tional equity ma rket correlat ions ha ve long dra wn a ttent ion from researchersa nd m a rket pra cti t ioners . Heston a nd R ouw enhorst (1994) noted t ha t imperfectly correlat ed

indust ries might lea d count ries wit h different indust ry composition to be imperfectly correlatedand that the benefits of international diversification could stem from industrial diversification.

1 Roll (1992) finds t ha t a technical aspect of index construction a nd t he industria l structures of a country explaindifferent beha viors of stock price indices a cross countr ies.


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In their ea rlier paper in w hich they empirica lly estima ted t he industry - a nd countr y-specific effectsin equity returns, however, they found tha t industria l structure explained very litt le of the cross-country correlation of equity returns for the sample period 1978-1992. But, factors that are specificto industr ia l sectors ma y ha ve become relat ively more importa nt in t he pricing of equity risk overthe past decade a long w ith increasing ma rket integration. In effect , using the sa me method asin Heston and Rouwenhorst (1994), Tsatsaronis (2001) shows that the sectoral effects have becomes t r o n g er f o r t h e e u r o a r e a i n m o r e r e ce n t y e a r s . Ts a t s a r on i s a rg u e s t h a t s y n c h r on i z e dma croeconomic conditions help shift gears from a cross count ries to a cross indust ries in t erms ofportfolio diversifica tion w ithin E urope from a pan -Eu ropean perspective.

However, there a re no studies tha t a ddress the issue of integrat ion a t t he industry levelor the compa rison of the degree of integra tion a cross indust ries. A number of factors ma y ha vecontr ibuted to grea ter influence of indust ryw ide integra tion in interna tional correla tions, yet indifferent degrees a cross indust ries. First, under t he premise of the n ew economy, shocks ma inlydriven by the information and communication technology sector are likely to have more global

impacts by reducing tr a ding costs via online netw orks a nd informat ion sha ring. 2 Second, potentia llygreater earnings prospects in certain industry sectors, thanks to a positive productivity shockspecific to those sectors, may have encouraged portfolio managers to seek geographical diversificationof the sa me or related industries to minimize national va riat ions in returns wit hin the part icularsectors. Third, to the extent tha t t he interna tional equity -ma rket comovements a re related to tra delinkage, one ca n expect low er cross-count ry correlations in n ontra ded indust ries relat ive to tra dedindustries. 3 Litt le has been, however, explored in the ar ea of indust ria l structures for interna tionalcorrelations, leaving many questions unanswered as to effects of such changes on the co-movementsa nd tra nsmission of international equity mar kets .

The purpose of this paper is to examine the role of industrial structures on the internationalco-movements a nd t ra nsmission of equity returns for t he G 7 countries. First, t his study will a na lyzethe interna tional correlations within industry groups to eva luate t he degree of market int egrationo v e r t ime . T h e in d u s t r i a l s t r u c tu r e s o f i n t e rn a t io n a l c o r r e l a t i o n s s h a l l p ro v id e a b e t t e rundersta nding of mar ket integrat ion, by identifying th e ma in drivers in th e co-movements of equityreturn s. Second, given the increasing correlat ions, th e question of part icula r int erest will be theinfluence of intern a tiona l risk factors w ith r espect to globa l indust ry developments on th e pricingof a na tional industr y index. Following the tra dition of ICAPM, th e risk sensitivity of each na tionalindustry group to the world industry a nd na tional ma rket factors will be estima ted over time andthe compar a tive beha viors of these industry fa ctors w ill be investiga ted. La stly, the rise and fa llof the so-called new economy sectors in the United States and its spillovers to other markets

2 Obstfeld an d Rogoff (2000) expla in th at home bias in equit y portfolios is ma inly due to tr ad e costs. With t hetra de costs r educed, one can expect to see great er portfolio diversificat ion across borders.

3 Obstfeld and Rogoff (1996, ch.5) show that under certain assumptions i t is an equilibrium for all the claimsto domestic nontra ded industries to be held only by domestic residents, wh ich implies tha t int erna tional portfoliodiversification even in completely integrated world markets would be associated with high correlations in tradedindustries, but not necessarily in nontraded industries.


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created anew an interest in how industry-specific shocks disseminate across national borders. 4

In this light, t he possibility of industry -specific tra nsmission w ill be explored in a formal vectorautoregression (VAR) system in the telecom, media, and technology (TMT) sector.

This pa per differs from previous st udies in th e follow ing a spects. F irst , by focusing on th ecorrelat ions of return s on nat iona l industry indices rat her tha n th ose on mar ket indices, this paperw ill uncover the rea l dyna mics of interna tiona l co-movements a cross different indust ries. Second,the estimation of market systemic risks will shed light on the relative importance of the worldindustry factor in equity pricing. Not only should the estimated international vis--vis nationalmarket factors point to the evidence of market integration among the G7 markets, but the varyingeffects of the world industr y fa ctors a cross different industr y groups will provide insights for therole of the new economy in the co-movements of international equity markets. Third, a VARframework will allow a more accurate picture of the dynamic transmission of the new economya nd its effects on the interna tiona l equity m a rket co-movements. B y decomposing a shock fromtw o different sources (indust ry-specific versus countr y-specific), th e chan nel of the new economy

tra nsmission w ill be closely a na lyzed. The empirical result w ill have implica tions for a new cha nnelof globa l ma rket t ra nsmission a nd conta gion, if t he indust ry-specific shock is found to becomeincreasingly import a nt relat ive to the country -specific shocks.

The sections of this pa per ar e organized a s follows. S ection II considers t he correla tionsof interna tional equity m ar kets with in each industry component of the G7 ma rkets over tw o timeperiods, 1973-1987 an d 1988-2001. Section I II employs tw o econometric met hods t o investiga tethe compara t ive behav ior o f the p r ic ing fac to rs tha t d r ive marke t co-movements and thetransmission mechanism of a shock to the new economy. First, the time-varying betas will beestima ted using a multifa ctor pricing model. Second, th e tra nsmission to other ma rkets of a shockto the US market will be analyzed in a VAR framework. Conclusions follow in Section IV.

II. DATA DESCRIPTION AND CORRELATION ANALYSES

The data set analysed in this paper consists of monthly s tock price indices of the G7countriesCa na da (CN), Fra nce (FR), Germa ny (B D), It a ly (IT), J apa n (J P ), U nited Kingdom (U K),a nd U nited St a tes (U S)for th e period J a nua ry 1973 to Ma y 2001, which a re all obta ined fromThompson Financial Datastream. We follow the FTSE industry classification and examine tenindustry groups for t he G 7 countries a nd t he w orld: Resources, B a sic industries, Genera l industries,Cy clical consum er goods, Noncyclical consumer goods, Cy clical services, Noncyclica l services,U tilities, Fina ncials, a nd I nformat ion technology. Additiona lly, w e a lso consider t he TMT sector

a nd loca l broad ma rket indices. For th e exercise of th is paper, monthly excess returns ha ve been

4 A recent paper by Amat o and Tsatsa ronis (2001) asks w hether a NASD AQ effect exists in emerging m ar ketsafter accounting for the common global and sectoral components in the shock returns. The empirical resultsof the paper find tha t t he correlation between returns on the NASDAQ a nd hea dline equity indices in emergingmarket economies is generally weak after accounting for industry composition effects.

Section IIData Description and Correlation Analyses


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obtained by subt ra cting one-month r isk free interest ra tes proxied by local money ma rket ra tes(a nd eurocurrency rat es when t hey a re not a vaila ble) from month ly gross returns. Monthly grossreturns are calculated as the first-log differences of the closing prices between the end-of-monthtrading days. In order to control for exchange rate fluctuations, the returns have been taken inlocal currencies (and for t he four Eur opean count ries, the retu rns a re in euro). 5

Ta ble 1 present s t he cross-count ry correla tion coefficients of equity return s for t he G 7count ries in each of the ten indu stry groups, broa der ma rket, a nd TMT sector for the tw o timeperiods (1973-1987 a nd 1988-2001). 6 The coefficients ha ve increas ed for most of the pa irs of count riesover two periods. In the broad market and the TMT sector, every pair of the G7 countries exceptone case (between J a pan an d th e US ) ha s seen a n increa se in the correlat ions. Although thecorrela tions with J a pan t end to rema in relatively low , they also noticeably increased over time.Yet i t i s a l so t rue tha t the indus t ryw ide cor re la t ions vary ac ross d i fferen t indus t ry g roups :correla tions in th e nontra ded goods sectors (such a s U tilities) tend t o be low wh ereas t hose forthe traded goods (such as Basic industries and General industrials) are relatively higher. A closer

look a t t he increases ra ther th a n th e levels themselves a lso revea ls tha t t he sectors with great estincreases in the indust ryw ide correla tions seem t o be relat ed to the new economy. Indeed, otherindustry groups that are barely related to the new economy, such as Resources, Cyclical andNoncyclical consumer goods, and Utilities, do not register spectacular growth in the correlations.

Moreover, despite the stea dy upw a rd t ime trend, th e patt erns of correlat ion dyn a mics seemto differ am ong three regiona l groups of G 7 economies. The first group consists of Ca na da , U K,and U S; the second , F rance, Germany, and I ta ly ; whi le the las t i s J apan . Ca nada and t he UKma inta in the top two highest correlat ions w ith t he US ma rket in both periods, while correlat ionsof the UK ma rket w ith t he rest of Europe increa sed substa ntia lly in t he second period (for exam ple,w ith G erma ny fr om 0.43 to 0.60, and w ith F ra nce from 0.51 to 0.64). The Eu ropea n st ock ma rketsha ve become highly correlat ed, as the broad ma rket correlat ions of the French and I ta lian ma rketswith the German market increased from 0.42 to 0.79 and from 0.28 to 0.63 respectively. The on-going economic integra tion a mong the E uropea n U nion (EU ) member count ries as w ell as th eirgeographic and cultural proximity must have contributed to the increased correlation betweenthe E uropean countries. The similar t endency across all industry groups in th e EU a rea suggeststhat national market factors such as monetary and f iscal policies , and legal and inst i tut ionalstructures may ha ve greatly a ssimilat ed at a regiona l level.

5 A number of studies have documented the impact of foreign exchanges in various contexts. Although somestudies find t ha t foreign excha nge risk a ffects t he cross-count ry correlat ions of asset retur ns (Roll 1992, B ra ckeret a l. 1999), their result s ar e mostly inconclusive a s to the direction of either correlat ion or int egra tion of equit ymarkets. Given the data availabili ty of the exchange rates and further complication, this paper considers onlyra w r eturns in local currency. However, our ma in results remain mostly unchan ged if we do the same exerciseswi th the local a sset in the U S dol lar te rm for th e per iod where the exchange ra t es are a vai lable .

6 The breakdow n a t t he end of 1987 (wh ich coincides with the w ell-known October cra sh) is based on the C how test r esults for each series. For most of the series, the breakdow n of 1987 seemed to be significant . Anotherstructural breakdown was spotted around 1995, and the exercises of this paper have been in fact taken forth e tw o subperiods (1988-1994 an d 1995-2001) a s w ell. The result s from t he la tt er tw o periods are n ot reporteddue to space l imita tions. However, they a re lar gely consistent wit h t he reported t rend betw een 1973-1987 and1988-2001.


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Table 1. Correlation Matrix of Monthly Returns for G7 Countries (1973-2001:5)

G erm a ny C a na da Fra nce I t a ly J a pa n U n it ed U n it edK in gdom S t a t es

ResourcesG e r m a n y 0.2566* 0.2903* 0.2677* 0.1940 0.2316* 0.1773C a na da 0.3254 0.4541* 0.2281* 0.2012 0.5328* 0.6360*Fr a nce 0.2176 0.4004* 0.4234* 0.1546 0.5970* 0.5575*I t a ly 0.1504 0.2348 0.0645 0.2789* 0.3526* 0.2417*J a pa n 0.3116 0.0642 0.0906 0.4304 0.2536* 0.2804*U K 0.3517 0.5420* 0.4938* 0.2041 0.0707 0.6710*U S 0.4066 0.5968* 0.5263* -0.0423 0.1082 0.6370*

Ba s ic Indus t r i esG e r m a n y 0.4710* 0.7199* 0.4452* 0.1989 0.5503* 0.6070*C a na da 0.2516* 0.5129* 0.3375* 0.2260* 0.5364* 0.7095*Fr a nce 0.3493* 0.4298* 0.4884* 0.2456* 0.6230* 0.5836*I t a ly 0.2791* 0.3103* 0.3769*

0.2628* 0.4041* 0.2584*J a pa n 0.3224* 0.2431* 0.2402* 0.1748 0.2862* 0.2002U K 0.4741* 0.5088* 0.4441* 0.3545* 0.3382* 0.6334*U S 0.3823* 0.7705* 0.4485* 0.2455* 0.3193* 0.5478*

Gene ra l Indus t r i a l sG e r m a n y 0.4821* 0.6930* 0.5623* 0.3691* 0.4899* 0.5189*C a na da 0.2678* 0.4748* 0.3422* 0.3315* 0.4748* 0.6673*Fr a nce 0.4064* 0.3736* 0.5031* 0.4040* 0.5222* 0.5536*I t a ly 0.2467* 0.2480* 0.3414* 0.4084* 0.3760* 0.2763*J a pa n 0.4064* 0.3012* 0.1976* 0.1919 0.3268* 0.3554*U K 0.3325* 0.4263* 0.3511* 0.3193* 0.3631* 0.5174*U S 0.3177* 0.6457* 0.3212* 0.2157* 0.3552* 0.4787*

Cycl ical Consumer GoodsG e r m a n y 0.1746 0.6679* 0.5818* 0.3979* 0.3827* 0.5797*

C a na da 0.1142 0.2615* 0.1828 0.1863 0.3570* 0.3103*Fr a nce 0.2627* 0.2314* 0.5102* 0.3172* 0.4362* 0.5769*I t a ly 0.1302 0.2607* 0.3884* 0.3596* 0.3815* 0.3406*J a pa n 0.3148* 0.1210 0.3289* 0.1882 0.2323* 0.2790*U K 0.3750* 0.1955 0.4487* 0.2770* 0.3393* 0.4743*U S 0.2912* 0.3120* 0.5132* 0.2087* 0.3924* 0.4226*

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Table 1 (continued)

Noncyclical consumer goodsG e r m a n y 0.3518* 0.5843* 0.3966* 0.2393* 0.5292* 0.4420*C a na da 0.3346* 0.3723* 0.2039* 0.2361* 0.4252* 0.5447*Fr a nce 0.3651* 0.4776* 0.3632* 0.2561* 0.5335* 0.4567*I t a ly 0.3541 0.3077 0.4639 0.1539 0.2345* 0.1267J a pa n 0.2949* 0.2300* 0.3474* 0.3124 0.2244* 0.2304*U K 0.4016* 0.4473* 0.4432* 0.1707 0.4030* 0.6171*U S 0.3793* 0.4841* 0.4039* 0.2427 0.3320* 0.4571*

Cycl ical S ervicesG e r m a n y 0.3155* 0.5529* 0.4672* 0.2571* 0.4497* 0.3864*C a na da 0.3156* 0.4020* 0.4154* 0.2712* 0.4680* 0.4911*Fr a nce 0.3840* 0.5200* 0.5745* 0.3525* 0.5353* 0.4444*I t a ly 0.1556 0.1861 0.2226* 0.2443* 0.3859* 0.2384*J a pa n 0.2651* 0.1985* 0.2815* 0.1812 0.3174* 0.2164*U K 0.3714* 0.4771* 0.4259* 0.3014* 0.2703* 0.5204*U S 0.3722* 0.6398* 0.4393* 0.2172* 0.3163* 0.4853*

Noncyclical ServicesG e r m a n y 0.4467* 0.5525* 0.4716* 0.2795* 0.5640* 0.3936*C a na da 0.1570 0.3005* 0.4233* 0.2887* 0.4198* 0.4163*Fr a nce 0.2401* 0.3398* 0.4021* 0.3313* 0.5343* 0.3953*I t a ly 0.2076* 0.1652 0.2343* 0.3007* 0.4130* 0.2454*J a pa n 0.1338 0.1161 0.0878 0.1903 0.3058* 0.3304*U K 0.2923* 0.2503* 0.2696* 0.2053* 0.0934 0.5219*U S 0.2159* 0.1686 0.3390* 0.1552 0.0771 0.2481*

Uti l i t iesG e r m a n y 0.2084* 0.2357* 0.1069 0.2279* 0.1276C a na da 0.1632 0.0073 0.2267* 0.2756* 0.4219*I t a ly 0.1535 0.0798 0.1412 0.1905 0.1164J a pa n 0.1717 0.1104 0.0993 0.1910 0.2867*U K 0.1221 0.4309 0.3918 -0.2452 0.2418*U S 0.2545* 0 .5457* 0.0941 0.1233 0.0845

Financ ia l sG e r m a n y 0.5109* 0.6478* 0.5427* 0.2432* 0.5307* 0.4158*C a na da 0.3208* 0.4350* 0.3473* 0.3191* 0.5058* 0.6897*Fr a nce 0.4121* 0.3062* 0.5542* 0.2509* 0.5616* 0.3649*I t a ly 0.2310* 0.2336* 0.2584* 0.2474* 0.4604* 0.2329*J a pa n 0.1505 0.1599 0.2103* 0.2728* 0.3155* 0.3494*U K 0.3546* 0.3857* 0.2638* 0.3508* 0.2504* 0.5858*U S 0.3537* 0.6013* 0.3583* 0.2505* 0.2532* 0.4444*

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Table 1 (continued)

Information TechnologyGermany 0.3524* 0.4224* 0.1061 0.3463* 0.3888* 0.3850*Canada 0.6430* 0.2825* 0.4638* 0.5491* 0.6591*France 0.0648 0.2876* 0.4748* 0.5646* 0.4828*Italy 0.3515 0.5383* 0.2160* 0.1700 0.1717Japan 0.1675 0.1670 0.3147 0.4803* 0.4562*UK 0.0053 0.0968 0.4657 0.3080* 0.5330*US 0.4682* 0.2803* 0.3627 0.2779* 0.1732

Broad MarketGermany 0.5761* (2.52) 0.7922* (4.51) 0.6277* (3.65) 0.3765* (0.26) 0.6014* (1.92) 0.5634* (1.49)Canada 0.3364* 0.5637* (0.54) 0.4605* (1.67) 0.3890* (0.72) 0.6098* (0.56) 0.7671* (0.10)France 0.4156* 0.5136* 0.6120* (1.96) 0.3977* (0.39) 0.6353* (1.41) 0.5642* (0.66)Italy 0.2808* 0.2936* 0.4303* 0.3819* (0.75) 0.4792* (1.19) 0.3612* (1.06)Japan 0.3493* 0.3171* 0.3541* 0.3050* 0.3868* (0.13) 0.3809* (-0.15)UK 0.4279* 0.5636* 0.5142* 0.3608* 0.3693* 0.6803* (1.12)US 0.4236* 0.7519* 0.5088* 0.2458* 0.3864* 0.5930*

Of which TMT sectorsGermany 0.5015* (3.22) 0.6897* (4.64) 0.5284* (3.30) 0.3736* (0.49) 0.6564* (2.91) 0.5737* (2.07)Canada 0.1761 0.6209* (4.33) 0.5047* (3.50) 0.4568* (2.24) 0.6151* (3.74) 0.7177* (2.19)France 0.2785* 0.2133* 0.5988* (3.74) 0.4433* (2.58) 0.6657* (3.99) 0.5442* (1.77)Italy 0.1996* 0.1524 0.2448* 0.4391* (2.24) 0.4722* (2.53) 0.4058* (1.74)Japan 0.3319* 0.2327* 0.1756 0.2141* 0.4100* (1.55) 0.4411* (1.51)UK 0.3965* 0.2617* 0.3140* 0.2230* 0.2487* 0.6515* (1.95)US 0.3766* 0.5332* 0.3876* 0.2284* 0.2903* 0.4804*

Note: The bold figures in the upper triangle report correlations in the latter period (1988-2001). For the correlations of theBroad market and the TMT sector returns, Z-statistics (in parenthesis) test the hypothesis that the correlations haveremained the same over time.

* Indicates level of significance at the 1 percent level.

Although the correlation coefficients tend to increase and many of them are statistically

significant, it is not to imply that the increase is statistically significant. To test the hypothesisthat the correlation has changed over time for each bivariate relation, a test statistic has beendevised. We first normalize the excess returns by dividing them by their standard deviations foreach separate time period. The OLS estimate from a regression of one standardized series on anotherturns out to be equal to the bivariate correlation coefficient between the two series. 7 The test fora structural change in the correlation would then correspond to the test for the structural changein two OLS estimates between two time periods. Using these OLS estimates, we construct thefollowing test statistics for the structural change in the correlation across different time periods:

Z = 212121/ ]}b [ raV ] b [ raV )/{ bb( + .

This Z-statistics is known to be approximately distributed as the standard normal (seeGreene 1993, 167). Table 1 reports the estimates of the statistics in the parentheses for broadmarkets and the TMT sectors. The test results indicate that the increase in correlation among

7 This is so-called z-score transformation. )Y , X ( CorrY

' X

) X

' X

( b =

=

Y X X X

1



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the Continental European countr ies (France, Germany, and I taly) is s tat is t ical ly s ignif icant .Considering the already high correlations, it is not surprising to see that those among Canada,U K, a nd U S do not seem to ha ve cha nged significa ntly. Noticeable cha nges were observed in theTMT sector w here most of the increases h a ve been st a tistically s ignificant .

Cr oss-count ry correla tions of equity ma rkets reflect t he combined effects of tw o distinctivefactors: na tional ma rket conditions a nd industr ial str uctures. As earlier studies pointed out, tw ocount r ies w i th su ff icien t ly d i fferen t indus t r ia l mixes w i l l likely ha ve low er equi ty ma rke tcorrelat ions, rega rdless of capita l ma rket int egrat ion (see Gr inold, Rudd, a nd S tefek 1989; Roll1992; a nd Hest on a nd Rouwenhorst 1994). Although the correlations ha ve generally increasedfor most indust ry groups as shown in Ta ble 1, th e extent t o which they ha ve increa sed seems tovary across different industry groups. Table 2 summarizes the variat ion and changes in theindustry w ide correla tions of Ta ble 1. It reports the simple averages a nd media ns of the bilatera lcross-count ry correla tions an d th e correla tions of the local indust ry w ith t he world industr y indexfor monthly returns. For two different time periods, the simple averages and medians are calculated

from the bivariate correlation coefficients: (A) for each pair of the G7 countries and (B) betweeneach nat iona l industry an d the w orld industry group.

At first glan ce, both correlat ions ha ve increased over time, but t he correlat ions betw eenthe na tional a nd w orld indust ry index ha ve been higher in both periods. It is interesting to notethe compar a tively different va ria tion in t he correlat ion evolutions of t hese correlat ion coefficients.The cross-count ry correla tions (A) ha ve increased in a lmost every indu str y w ith a nota ble exceptionof Noncyclical consumer goods that stayed the same, whereas the global industry correlationsha ve increased relat ively less a nd st a yed ra ther consta nt (a lbeit a t a relatively higher level). Allelse being equa l, the grea ter increa ses in the cross-count ry correlat ions (A) can be la rgely a tt ributedto assimilat ed nat iona l mar ket conditions given tha t indust ry fa ctors a re contr olled by constra iningwithin specif ic industry groups. By and large, the country-specif ic variat ions seem to havediminished at least a mong the G 7 economies, w hich supports the a rgument for t he ongoing economicintegration.

Another int eresting finding is a striking d istinction betw een t he so-called new economya nd t he old economy in t he pat terns of correla tion evolutions. Sectors th a t h a ve been larg ely affectedby t he recent technology sh ocks a nd t he new economy a re th e ones w hose correla tions ha ve increasedsubsta ntia lly more tha n oth er tr a ditional ones. Informa tion technology (from 0.27 to 0.40 in (A)and from 0.48 to 0.60 in (B)) and more generally the TMT sectors (from 0.28 to 0.54 in (A) andfrom 0.50 to 0.69 in (B )) have r egistered rema rka ble growt h in cross-count ry correla tions of retur ns.Fina ncials h a s a lso substa nt ia lly increa sed (from 0.31 to 0.43 in (A) a nd from 0.49 to 0.57 in (B ))perha ps due to deregulat ion a nd liberalizat ion in t his sector since the late 1980s. In the mea ntime,

th e old economy (Cyclica l a nd Noncyclica l consum er goods) and ty pica l domestic indu str ies suchas Utilities remain relatively constant and low in correlations.


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Table 2. Average and Median of Correlation Coefficients of Monthly Returns (median in italics)

(A) Between National Industry Indices (B) With the World Industry Index

1973-1987 1988-2001 1973-1987 1988-2001

Resources 0.29 0.35 0.53 0.570.31 0.28 0.60 0.62

Basic Industries 0.37 0.44 0.58 0.560.35 0.47 0.61 0.55

General Industrials 0.34 0.46 0.56 0.600.33 0.46 0.61 0.59

Cyclical Consumer Goods 0.29 0.38 0.51 0.520.29 0.36 0.48 0.53

Noncyclical Consumer Goods 0.36 0.36 0.55 0.540.37 0.36 0.51 0.52

Cyclical Services 0.33 0.40 0.55 0.550.32 0.40 0.57 0.53

Noncyclical Services 0.20 0.40 0.35 0.590.21 0.40 0.32 0.58

Utilities 0.17 0.20 0.35 0.410.12 0.21 0.40 0.38

Financials 0.31 0.43 0.49 0.570.27 0.44 0.46 0.60

Information Technology 0.27 0.40 0.48 0.600.28 0.42 0.45 0.61

Broad Market 0.42 0.53 0.61 0.640.39 0.56 0.63 0.66

Of which TMT sectors 0.28 0.54 0.50 0.690.25 0.53 0.50 0.70

Notes:1 For Resources, Cyclical and Noncyclical consumer goods, and Utilities and Information Technology, some countries have

a smaller number of observations in the first period (1973-1987). For Resources, Germany starts only from 1985 and Italyfrom 1986; for Cyclical consumer goods, Canada starts from 1977:3; for Noncyclical consumer goods, Italy starts from 1986;for Utility, UK starts from 1987 (France excluded, see below); for Information technology, Germany starts from 1988:12.Given that countries with shorter time series tend to have comparatively less internationally integrated financial marketsand move rather independently of global trends, the correlation coefficients for these industries may be upwardly biasedfor the first period. Thus, the correlation analyses were done for the two subperiods (1988-2001 and 1995-2001) as well,since all the countries in the sample have the full time series at least from 1988 on. The time trend for the two subperiodsmatches with the result from the reported sample periods.

2 For Utilities, France is not included, as its series is only available from August 2000.



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Man y st udies have confirmed tha t st ock ma rket correlat ions cha nge over time. 8 The resultsin this section also evidence tha t t he increase in interna tional equity m a rket correlat ions ha s beensignifican t, suggesting the growing int egration of world fina ncia l ma rkets. Importa ntly, however,the degrees differ a mong the G 7 countries. Not only do some count ries such a s th e US ma nifesthigher integrat ion w ith the rest of the world than others like Ita ly and J a pan, but t he integra tiona lso seems to be rat her conta ined within t he regional boundary . In genera l, the correlat ions w ithintraded sectors are also higher and have increased more than those in nontraded sectors, whichis consistent with the predicted effects of market integration. 9

Consistent w ith the observation tha t substa ntial integrat ion ha s ta ken place industrywidethrough global supply chains and cross-listed stocks particularly of TMT sectors and Financials,the r ise in correla tions ha s been also significant ly higher in t hose indust ries. The correlat ion a na lysesin each industry group hence suggest the increasingly important impacts of the industry-specificdr ivers on the cor re la t ion dynamics . On ba lance , the upward t rend in the cor re la t ions ofinterna tional equit y ma rkets seems to ha ve benefited from the great er influence of the new economy

sectors driven by technology advances and of globalization, as well as the lesser variation of countryfactors at least among the G7 economies.

III. ECONOMETRIC METHODS AND EMPIRICAL RESULTS

A. Estimating Industry and Country Factors by Betas

The results of correlat ion a na lyses support a compelling cas e wh ere indust ry-specific riskfa ctors ma y ha ve become relat ively more importa nt in equity pricing, as global ma croeconomicconditions co-move. The purpose of this section is to assess the comparative role of world industryfactors in th e pricing of na tional industr y indices. B y estima ting mult iple risk factors for th e worldindustr y a nd th e nat iona l mar ket over time, the empirica l results w ill shed light on the drivingfa ctors for th e recent equit y ma rket co-movements a nd possible tra nsmission a cross borders.

According t o the C a pita l Asset P ricing Model (CAP M), th e pricing of a ssets r elies only onthe syst emic risk rela tive to the ma rket, wh ich is often measured by the beta s. While the tra ditiona lCAP M is focused on t he single source of risk, a sset pricing th eory ca n be extended to incorpora temultiple risk factors, by running a regression of the asset return at time t on various factors at t ime t . (Ross 1976, Roll a nd Ross 1980). The beta s th a t a re estima ted in t his ma nner a re referredto a s fa ctor loa dings, risk sensitivities, or risk exposures.

8 See Erb et al. (1994) for the stochastic property of correlation measures in relation to business cycles and asurvey of various studies on time-varying equity correlations.

9 Obstfeld and Rogoff (1996) explain that portfolio diversification in a completely integrated world market willlead to higher correlations in traded goods sectors, but not necessarily in the nontraded goods sector.


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G iven t he focus of this pa per on industry vs. countr y fa ctors, w e have formulated a multipleregression to estimate the betas of the national industries with respect to the local market andworld industry index, which is consistent with the previous CAPM literature. 10

r ic = + 1r iw + 2r mc + ic , (1)where r ic , r iw , and r mc a re excess returns on the na tional indust ry index, world indust ry index,a nd d omestic ma rket index, respectively.

Instead of using the world market index, we employed the world industry index, underthe a ssumption t ha t t he risk exposure of a na tiona l industry t o the world industry should involvethat of the nat ional industry to the world market as well . As i t has been noted in the earl ierliterat ure, the return s on the na tional index are often positively correlat ed with those on th e worldindust ry index. In order t o avoid the multicollinea rity problem betw een tw o indices, ( r iw a nd r mc ),one can isolate the component, which is independent of each either, by projecting one on the other.Tha t is:

r mc = 0 + 1r iw + mcThe estima ted mc is the domestic market component, w hich is not relat ed to the w orld

industr y index. In a tw o-step regression procedure, one can use t he orthogona lized component,i.e., th e residuals from th e simple regressions of r mc on r iw in order to estima te th e risk sensitivityonly to the national market component in the following equation.

r ic = 0 + 1r iw + 2 mc + ic (2)

One ca n show t ha t t he risk sensitivity only to the na tional ma rket component, estima tedby 2 in equa tion (2) is equa l to 2 in (1).

.an d , ) ( , where r r

) r r ( r

icic

icmciw

iciw mciw

icmciw ic

====

+++=

+++=

+++=

221211020

21

10210

210 r r

Similar ly, the risk sensitivity only to the world industr y component is equa l to 1 in (1).Hence 1 a nd 2 in (1) in effect represent th e add itional syst emic risk relat ive only t o the na tionalmarket and world industry component, respectively.

Ta ble 3 summarizes the beta s for t he world industry an d na t iona l market by industry.G iven the time-va rying property of th e beta s, 11 the betas of all the industries are estimated fortwo separate periods (1973-1987 and 1988-2001) as well as an additional subperiod (1995-2001)

10 J orion and Schwa rtz (1986) formulat ed a mult ip le regression to es t imate t he betas to the na t ional and worldma rket index in an effort t o tes t market in t egrat ion versus segmenta t ion .

11 Ferson and Ha rvey (1991) examine a model in wh ich multiple factors are priced with t ime-vary ing para meters,while Ferson an d H arvey (1993) extend t he dyna mic factor model to a n in t ernat ional set t ing . Ha rvey (1994)explores a s imilar formulat ion in emerging capi tal m arkets .

Section IIIEconometric Methods and Empirical Results


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for a compa rison. All the indust ry g roups except for t he indust ries of cyclica l consumer goods a ndcyclical consumer services have recorded greater values of industry betas in the period 1988-2001.The increa se in t he indu str y bet a s is more pronounced in th e lat est 1995-2001 period, compa redto th e period 1973-1987. Most indust ries, on t he other ha nd, ha ve seen a decrea se in the na tiona lma rket beta s, w ith only th e exception of the informat ion t echnology indust ry. The estima ted 1a nd 2, however, mea sure the risk exposure to the a dditional informat ion from the world industr yand national markets respectively, for which a global technology shock that accompanies thestructural changes in the local economy shall not be explained in terms of the industry factor.In other words, any technology shock that has idiosyncrat ical ly changed the nat ional marketcondition is more likely to be ca ptured in t he local ma rket beta , tha n in t he w orld industr y. Thishypothesis is also consistent with the premise of the new economy that the real impact of theinformation and communication technology may lie on the market infrastructure, exerting aninfluence over the entire economy.

Ta ble 3. Industry and Domestic Market Betas by Industry Group

1973-1987 1988-2001 1995-2001

B et a S t d . E r rors B et a S t d . E r rors B et a S t d . E r rors

Indus t ry Be tasResources 0.41 0.04 0.59 0.03 0.74 0.04B a sic indust r ies 0.17 0.02 0.26 0.02 0.55 0.04G enera l indust r ia ls 0.09 0.02 0.10 0.02 0.12 0.04C yclica l consumer goods 0.30 0.05 0.21 0.04 0.28 0.06Noncyclica l consumer goods 0.24 0.02 0.40 0.02 0.55 0.04C yclica l services 0.16 0.02 0.06 0.02 0.13 0.04Noncyclica l services 0.17 0.03 0.34 0.03 0.53 0.05U t ilit ies* 0.42 0.02 0.45 0.02 0.63 0.04F ina ncia ls 0.08 0.03 0.21 0.03 0.39 0.04I n forma t ion t echnology 0.29 0.02 0.44 0.02 0.47 0.04

TMT sect ors 0.17 0.03 0.39 0.02 0.50 0.03Domest ic Market Betas

Resources 0.62 0.04 0.45 0.03 0.27 0.04B a sic indust r ies 0.90 0.02 0.81 0.02 0.54 0.04G enera l indust r ia ls 0.95 0.02 1.00 0.02 0.95 0.04C yclica l consumer goods 0.87 0.05 0.87 0.04 0.78 0.06Noncyclica l consumer goods 0.71 0.02 0.57 0.02 0.40 0.03C yclica l services 0.87 0.02 0.91 0.02 0.79 0.04Noncyclica l services 0.74 0.03 0.81 0.03 0.68 0.05U t ilit ies* 0.52 0.02 0.38 0.02 0.21 0.03F ina ncia ls 0.91 0.03 0.89 0.05 0.75 0.08

I n forma t ion t echnology 0.65 0.02 0.82 0.02 0.93 0.04TMT sect ors 0.82 0.02 0.91 0.03 0.87 0.05

Note: The industry beta s and country beta s are calculated a s simple averages of the beta s of each individual G7 nationalindustry index with respect to the world industry a nd na tional mar ket indices, respectively, over the G 7 countries foreach industry group. Accordingly the standard errors are calculated as the square root of the sum of the estimatedvariances, divided by the number of countries.

* For Utilities, France is not included, as its series is only available from August 2000.


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The different values of industry betas along with different degrees of cross-country,industr yw ide correla tions ha ve interesting implica tions. The relat ively low indust ry beta s (a ndthe high na tional ma rket betas) among the industries wh ose returns a re highly correlat ed acrossborders may suggest that there is increasing synchronization in world business cycles. For example,Cyclical consumer goods and services are more likely to be affected by the national market factor(less by the w orld indust ry), and y et ha ve been increa singly correlat ed a cross borders, which issupportive for the hypothesis of synchronizing domestic business cycles. In the opposite case ofUtilities, it is puzzling that the industry with low cross-country correlation has relatively highindustry and low nat ional market beta . However, the highly regulated nature of the Uti l i t iesindustry in many countries often prevents the prices from closely reflecting the domestic marketcondition, while the energy price may be largely vulnerable to a world industry shock.

Table 4 reports the average risk factors with respect to the world industry and nationalma rket for ea ch country. For a ll the count ries in th e sample except J a pan , the betas a re higherto the world industry and lower to the local market. The result is consistent with the previous

literat ure on t he growing integra tion of the w orld financia l mar kets a t least among the G 7 countries.I t is a lso not surpris ing tha t the U S ma rket has by far t he highest global industry beta a nd thelowest domestic market beta in all periods. For the US, the industry beta increased from 0.52to 0.86 while the domestic market beta decreased from 0.59 to 0.21 from the first period (1973-1987) t o th e la st peri od (1995-2001).

Table 4. Industry and Domestic Market Betas by Country

1973-1987 1988-2001 1995-2001

B et a S t d . E r rors B et a S t d . E r rors B et a S t d . E r rors

Indus t ry Be tasC a na da 0.17 0.03 0.30 0.03 0.42 0.04F ra nce 0.11 0.04 0.26 0.03 0.40 0.05G erma ny 0.10 0.03 0.20 0.02 0.36 0.04I t a ly 0.06 0.03 0.12 0.03 0.23 0.05J a pa n 0.38 0.03 0.41 0.03 0.29 0.04U K 0.13 0.03 0.31 0.02 0.47 0.04U S 0.52 0.02 0.49 0.02 0.86 0.03

Domest ic Market BetasC a na da 0.80 0.03 0.66 0.03 0.54 0.04F ra nce 0.89 0.04 0.87 0.04 0.78 0.05G erma ny 0.84 0.02 0.75 0.02 0.67 0.04I t a ly 0.91 0.02 0.93 0.02 0.84 0.03J a pa n 0.64 0.03 0.75 0.02 0.74 0.03U K 0.89 0.02 0.80 0.03 0.62 0.06U S 0.59 0.02 0.53 0.02 0.21 0.03

Note: The industry beta s and country beta s are calculated a s simple averages of the beta s of each individual G7 nationalindustry index with respect to the w orld industry and nat ional ma rket indices over the ten industry groups for eachcountry . Accordingly the stan dar d errors are calculated a s the squa re root of the sum of the estimat ed varia nces, dividedby the number of industries.



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on other m a rkets. King a nd Wa dhw a ni (1990) a nd L in et a l. (1994) a rgue th a t investors extra ctonly the relevant informa tion from observed price cha nges in th e foreign ma rkets w hen pricingthe d omestic a ssets. As supply cha ins of the n ew economy sectors globalize and recent informa tiona nd communication technology a dva nces pass t hrough interna tional netw orks, the innovat ion ofthese sectors ma y ha ve more globa l repercussions thr ough signa l extra ction of indust ry-specificinformation.

In this context, a shock to a US industry has ripple effects on the rest of the world, viatw o distinct but relat ed chann els. First, th e industry -specific component of the new informa tionw ill ha ve an impact on the sam e indust ry w orldwide. To the extent tha t a shock cha nges futureearnings prospects of the particular industry in question globally, other national markets willincorpora te th e new informa tion in their pricing of the sa me industry . Second, t he ma rket componentof th e innova tion will tra nsmit t o other ma rkets. Since the shock is likely t o cha nge the relat edprofits a nd t hus economic conditions of the domestic market a s w ell, th e informa tion is releva ntfor a ll the trad ing and investment pa rtn ers of the US . For example, when In tel intr oduces a n ew

processor, t he informa tion w ould not only a ffect t he globa l informa tion technology sector directly,but a lso increase US earnings a nd t hus demand for French wine indirect ly.

As is shown in t he previous section, th e return s on a n a tional indus tr y can be decomposedinto t hree different components:

mciwic r r r 21 ++= ,

where is the idiosyncratic national industry component, b

1r iw the world industry, and mcr 2

the nat ional market .We sepa ra tely investiga te impacts of a shock from the w orld indust ry component a nd from

the national market component by constructing the VAR systems as follows: (A) the world industry

component of the US industry returns ( )iwr 1 with the rest of the nat iona l industry returns onCa nada , UK, Fra nce, Germany, I t a ly, and J apa n; and (B ) the nat iona l market component of the

US indus t ry re turns ( )m c r 2 with the rest of nat ional industry returns (Canada, UK, France,G ermany, I ta ly, and J apa n). A shock of one sta nda rd deviat ion is introduced in t he US ma rketa nd its dyna mic effects a re tra ced t hroughout the syst em for t he next yea r. The confidence bandsa re a lso presented using a symptotic distributions. The effects of a shock origina ting from eitherthe US industry or the US market component of G7 countries are quite significant. Most of theshocks ta per off after one month or a t the most t wo, wh ich is consistent w ith t he efficient ma rkethypothesis.

The evidence shows th a t innovat ions in the TMT sector h a ve become more influentia lrecent ly. It should be a lso noted tha t t he impulse responses to indust ry sh ock ha ve been st rongertha n to mar ket shock. The finding tha t t he impact of indust ry shock is great er tha n tha t of ma rketimplies that a shock to the TMT sector has quite a strong industry-specific influence on G7



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economies, aside from indirect effects on t he U S ma rket. Since an innovation from the U S indust rywould a ffect the loca l ma rket performa nce in t he other G 7 ma rkets, th e impulse response functionsof each national industry would also reflect the general reaction to the market component of ashock as well. Thus, only the additional effects of the industry shock over the national marketshock ma y be considered a s t he indust ry-specific tra nsmission, w hich seems t o be quite significa ntin t he TMT sector. In fa ct, t his is ra th er TMT-sector specia l, since the simila r impulse responsefunctions in other industry groups did not differ w idely between the industr y shock a nd t he ma rketshock.

IV. CONCLUSION

The key focus of this paper w a s to ana lyze whether a nd to wh a t extent ongoing cha ngesin industria l structures along with a dva nces in informa tion technology a nd fina ncia l libera lizationhave an impact on the correlations and co-movements of international equity markets.

In an effort to investigate financial integration at the industry level, the paper first examinedthe cross-count ry correlat ions for t he G 7 countries in different indust ry groups. The results indica tedtha t t he cross-count ry correla tions ha ve not only significa ntly increas ed, but th e increas es alsoseem t o be more pronounced in th e sectors rela ted t o the new economy. D iminishing va ria tionof national market conditions particularly for the neighboring countries and the global impactof the new economy have surfaced as the most relevant factors in increasing international co-movements. Secondly, a formal multifactor pricing model was employed to estimate the riskexposure of the na tional industry index to the world indust ry a nd na tional ma rket factors. In supportof the correlat ion a na lyses (w hich imply both less differentia l na tional economic conditions a ndmore influentia l global industr y effects), th e estimated beta s clear ly suggest th at the w orld industryfactors have become increasingly important in the pricing of national industry indices. The thirdfinding of this paper is the emergence of industry-specific transmission in the TMT sector. TheVAR syst em of the G 7 equity return s a llow s a compar ison betw een responses of the G 7 marketsto a shock of the domestic market and to the global industry component of the TMT sector. Theresults support that the industry-specific transmission channel has become more important inthe TMT sector in recent years.


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Dw yer, G. , a nd R. H a fer, 1988. Are National Stock Markets Linked? Feder al Reser ve B an k of St. L oui s Revi ew 70:3-14.

Erb, C . B ., C. R. Ha rvey, and T. E. Viskan ta , 1994. Forecasting Interna tional Equity C orrelations. Fin a n ci a l An a ly st s Jou r n a l (Novermber-December):32-45.

Fa ma , E., a nd K. F rench, 1989. B usiness Conditions and E xpected Return s on St ocks an d B onds. J our na l o f Finan cia l E conomics 25:23-50.

Ferson, W., and C. Harvey, 1991. The Variation of Economic Risk Premiums. J our nal of Poli t ical Economy 99:385-415.

, 1993. The Risk and P redicta bility of Int ernat iona l Equity Return s. Review of Fi nan cial Stud ies 6:522-66.

Granger, C., 1969. Investigating Causal Relations by Econometric Models and Cross-spectralMethods. Econometr ica 37:424-38.

G reene, W., 1993 . Econometr i c An al ysis . 2nd ed. New York: Macmillan Publishing Company.Grinold, R., A. Rudd, and D. Stefek, 1989. G lobal Fa ctors: Fa ct or Fiction? J our na l o f Por t fol i o

M anagement 16:79-88.Ha milton, J . , 1994. T im e Ser ies An al ysis. P rinceton: P rinceton Un iversi ty P ress .Harvey, C., 1994. Predictable Risk and Returns in Emerging Markets. Fuq ua School of B usiness,

Duke U niversi ty, North Ca rolina. U npublished.Heston, S. , and K. Rouwenhorst , 1994. Does Indus t r ia l S t ruc ture Expla in the Benef i t s o f

International Diversification? Jour na l o f Fin ancia l Economics 36:3-27.J orion, P ., and E . Schwa rtz, 1986. Integration vs. Segmentation in the Canadian Stock Market.

Jo u r n a l of F in a n ce 41:603-14.King, M., an d S. Wa dhw a ni, 1990. Tra nsmission of Volat ility between S tock Ma rkets. Review

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MONOGRAPH SERIES(Published in-house; Available through ADB Office of External Relations; Free of charge)

EDRC REPORT SERIES (ER)

ERD POLICY BRIEF SERIES (PBS)(Published in-house; Available through ADB Office of External Relations; Free of charge)

No. 1 Is Growth Good Enough for the Poor? Ernesto M. Pernia, October 2001

No. 2 Indias Economic ReformsWhat Has Been Accomplished?What Remains to Be Done?

Arvind Panagariya, November 2001No. 3 Unequal Benefits of Growth in Viet Nam Indu Bhushan, Erik Bloom, and Nguyen MinhThang, January 2002

No. 4 Is Volatility Built into Todays World Economy? J. Malcolm Dowling and J.P. Verbiest, February 2002

No. 5 What Else Besides Growth Matters to PovertyReduction? Philippines

Arsenio M. Balisacan and Ernesto M. Pernia, February 2002

No. 6 Achieving the Twin Objectives of Efficiency andEquity: Contracting Health Services in Cambodia

Indu Bhushan, Sheryl Keller, and BradSchwartz,March 2002

No. 7 Causes of the 1997 Asian Financial Crisis: What

Can an Early Warning System Model Tell Us? Juzhong Zhuang and Malcolm Dowling, June 2002

No. 8 The Role of Preferential Trading Arrangementsin Asia

Christopher Edmonds and Jean-Pierre Verbiest, July 2002

No. 9 The Doha Round: A Development Perspective Jean-Pierre Verbiest, Jeffrey Liang, and LeaSumulong, July 2002

No. 1 ASEAN and the Asian Development BankSeiji Naya, April 1982

No. 2 Development Issues for the Developing Eastand Southeast Asian Countriesand International CooperationSeiji Naya and Graham Abbott, April 1982

No. 3 Aid, Savings, and Growth in the Asian Region J. Malcolm Dowling and Ulrich Hiemenz,

April 1982No. 4 Development-oriented Foreign Investment

and the Role of ADB Kiyoshi Kojima, April 1982

No. 5 The Multilateral Development Banks

and the International Economys Missing Public Sector John Lewis, June 1982

No. 6 Notes on External Debt of DMCs Evelyn Go, July 1982

No. 7 Grant Element in Bank Loans Dal Hyun Kim, July 1982

No. 8 Shadow Exchange Rates and StandardConversion Factors in Project Evaluation Peter Warr, September 1982

No. 9 Small and Medium-Scale Manufacturing

Establishments in ASEAN Countries:Perspectives and Policy Issues Mathias Bruch and Ulrich Hiemenz,

January 1983No. 10 A Note on the Third Ministerial Meeting of GATT

Jungsoo Lee, January 1983No. 11 Macroeconomic Forecasts for the Republic

of China, Hong Kong, and Republic of Korea J.M. Dowling, January 1983

No. 12 ASEAN: Economic Situation and ProspectsSeiji Naya, March 1983

No. 13 The Future Prospects for the Developing Countries of Asia

Seiji Naya, March 1983No. 14 Energy and Structural Change in the Asia-

Pacific Region, Summary of the ThirteenthPacific Trade and Development ConferenceSeiji Naya, March 1983

No. 15 A Survey of Empirical Studies on Demandfor Electricity with Special Emphasis on PriceElasticity of DemandWisarn Pupphavesa, June 1983

No. 16 Determinants of Paddy Production in Indonesia:1972-1981A Simultaneous Equation Model

ERD TECHNICAL NOTE SERIES (TNS)(Published in-house; Available through ADB Office of External Relations; Free of Charge)

No. 1 Contingency Calculations for EnvironmentalImpacts with Unknown Monetary Values David Dole

February 2002No. 2 Integrating Risk into ADBs Economic Analysis

of Projects Nigel Rayner, Anneli Lagman-Martin,

and Keith WardJune 2002

No. 3 Measuring Willingness to Pay for Electricity Peter Choynowski

July 2002No. 4 Economic Issues in the Design and Analysis of a

Wastewater Treatment Project David Dole

July 2002No. 5 An Analysis and Case Study of the Role of

Environmental Economics at the AsianDevelopment Bank

David Dole and Piya AbeygunawardenaSeptember 2002


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ApproachT.K. Jayaraman, June 1983

No. 17 The Philippine Economy: EconomicForecasts for 1983 and 1984 J.M. Dowling, E. Go, and C.N. Castillo,

June 1983No. 18 Economic Forecast for Indonesia

J.M. Dowling, H.Y. Kim, Y.K. Wang,and C.N. Castillo, June 1983

No. 19 Relative External Debt Situation of AsianDeveloping Countries: An Application

of Ranking Method Jungsoo Lee, June 1983No. 20 New Evidence on Yields, Fertilizer Application,

and Prices in Asian Rice ProductionWilliam James and Teresita Ramirez, July 1983

No. 21 Inflationary Effects of Exchange RateChanges in Nine Asian LDCs Pradumna B. Rana and J. Malcolm Dowling,

Jr., December 1983No. 22 Effects of External Shocks on the Balance

of Payments, Policy Responses, and DebtProblems of Asian Developing CountriesSeiji Naya, December 1983

No. 23 Changing Trade Patterns and Policy Issues:The Prospects for East and Southeast AsianDeveloping CountriesSeiji Naya and Ulrich Hiemenz, February 1984

No. 24 Small-Scale Industries in Asian EconomicDevelopment: Problems and ProspectsSeiji Naya, February 1984

No. 25 A Study on the External Debt Indicators Applying Logit Analysis Jungsoo Lee and Clarita Barretto,

February 1984No. 26 Alternatives to Institutional Credit Programs

in the Agricultural Sector of Low-IncomeCountries Jennifer Sour, March 1984

No. 27 Economic Scene in Asia and Its Special Features Kedar N. Kohli, November 1984

No. 28 The Effect of Terms of Trade Changes on theBalance of Payments and Real NationalIncome of Asian Developing Countries Jungsoo Lee and Lutgarda Labios, January 1985

No. 29 Cause and Effect in the World Sugar Market:Some Empirical Findings 1951-1982Yoshihiro Iwasaki, February 1985

No. 30 Sources of Balance of Payments Problemin the 1970s: The Asian Experience Pradumna Rana, February 1985

No. 31 Indias Manufactured Exports: An Analysisof Supply Sectors Ifzal Ali, February 1985

No. 32 Meeting Basic Human Needs in AsianDeveloping Countries Jungsoo Lee and Emma Banaria, March 1985

No. 33 The Impact of Foreign Capital Inflowon Investment and Economic Growthin Developing Asia Evelyn Go, May 1985

No. 34 The Climate for Energy Development

in the Pacific and Asian Region:Priorities and PerspectivesV.V. Desai, April 1986

No. 35 Impact of Appreciation of the Yen onDeveloping Member Countries of the Bank Jungsoo Lee, Pradumna Rana, and Ifzal Ali,

May 1986No. 36 Smuggling and Domestic Economic Policies

in Developing Countries A.H.M.N. Chowdhury, October 1986

No. 37 Public Investment Criteria: Economic InternalRate of Return and Equalizing Discount Rate

Ifzal Ali, November 1986No. 38 Review of the Theory of Neoclassical Political

Economy: An Application to Trade Policies M.G. Quibria, December 1986

No. 39 Factors Influencing the Choice of Location:Local and Foreign Firms in the Philippines E.M. Pernia and A.N. Herrin, February 1987

No. 40 A Demographic Perspective on Developing Asia and Its Relevance to the Bank E.M. Pernia, May 1987

No. 41 Emerging Issues in Asia and Social Cost

Benefit Analysis I. Ali, September 1988No. 42 Shifting Revealed Comparative Advantage:

Experiences of Asian and Pacific Developing Countries P.B. Rana, November 1988

No. 43 Agricultural Price Policy in Asia:Issues and Areas of Reforms I. Ali, November 1988

No. 44 Service Trade and Asian Developing Economies M.G. Quibria, October 1989

No. 45 A Review of the Economic Analysis of PowerProjects in Asia and Identification of Areasof Improvement I. Ali, November 1989

No. 46 Growth Perspective and Challenges for Asia: Areas for Policy Review and Research

I. Ali, November 1989No. 47 An Approach to Estimating the Poverty Alleviation Impact of an Agricultural Project I. Ali, January 1990

No. 48 Economic Growth Performance of Indonesia,the Philippines, and Thailand:The Human Resource Dimension E.M. Pernia, January 1990

No. 49 Foreign Exchange and Fiscal Impact of a Project: A Methodological Framework for Estimation I. Ali, February 1990

No. 50 Public Investment Criteria: Financialand Economic Internal Rates of Return

I. Ali, April 1990No. 51 Evaluation of Water Supply Projects:

An Economic Framework Arlene M. Tadle, June 1990

No. 52 Interrelationship Between Shadow Prices, ProjectInvestment, and Policy Reforms: An Analytical Framework I. Ali, November 1990

No. 53 Issues in Assessing the Impact of Projectand Sector Adjustment Lending I. Ali, December 1990

No. 54 Some Aspects of Urbanizationand the Environment in Southeast Asia Ernesto M. Pernia, January 1991

No. 55 Financial Sector and EconomicDevelopment: A Survey Jungsoo Lee, September 1991

No. 56 A Framework for Justifying Bank-AssistedEducation Projects in Asia: A Reviewof the Socioeconomic Analysisand Identification of Areas of Improvement

Etienne Van De Walle, February 1992No. 57 Medium-term Growth-StabilizationRelationship in Asian Developing Countriesand Some Policy ConsiderationsYun-Hwan Kim, February 1993

No. 58 Urbanization, Population Distribution,and Economic Development in Asia Ernesto M. Pernia, February 1993

No. 59 The Need for Fiscal Consolidation in Nepal:The Results of a Simulation Filippo di Mauro and Ronald Antonio Butiong,

July 1993


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No. 1 International Reserves:Factors Determining Needs and Adequacy Evelyn Go, May 1981

No. 2 Domestic Savings in Selected Developing Asian Countries Basil Moore, assisted by

A.H.M. Nuruddin Chowdhury, September 1981No. 3 Changes in Consumption, Imports and Exports

of Oil Since 1973: A Preliminary Survey of the Developing Member Countriesof the Asian Development Bank Dal Hyun Kim and Graham Abbott,

September 1981No. 4 By-Passed Areas, Regional Inequalities,

and Development Policies in SelectedSoutheast Asian CountriesWilliam James, October 1981

No. 5 Asian Agriculture and Economic DevelopmentWilliam James, March 1982

No. 6 Inflation in Developing Member Countries: An Analysis of Recent Trends A.H.M. Nuruddin Chowdhury and

J. Malcolm Dowling, March 1982No. 7 Industrial Growth and Employment in

Developing Asian Countries: Issues andPerspectives for the Coming DecadeUlrich Hiemenz, March 1982

No. 8 Petrodollar Recycling 1973-1980.Part 1: Regional Adjustments andthe World Economy Burnham Campbell, April 1982

No. 9 Developing Asia: The Importanceof Domestic Policies Economics Office Staff under the direction

of Seiji Naya, May 1982No. 10 Financial Development and Household

Savings: Issues in Domestic ResourceMobilization in Asian Developing CountriesWan-Soon Kim, July 1982

No. 11 Industrial Development: Role of SpecializedFinancial Institutions Kedar N. Kohli, August 1982

No. 12 Petrodollar Recycling 1973-1980.Part II: Debt Problems and an Evaluationof Suggested Remedies Burnham Campbell, September 1982

No. 13 Credit Rationing, Rural Savings, and FinancialPolicy in Developing CountriesWilliam James, September 1982

No. 14 Small and Medium-Scale Manufacturing Establishments in ASEAN Countries:Perspectives and Policy Issues Mathias Bruch and Ulrich Hiemenz, March 1983

No. 15 Income Distribution and EconomicGrowth in Developing Asian Countries

ECONOMIC STAFF PAPERS (ES)

J. Malcolm Dowling and David Soo, March 1983No. 16 Long-Run Debt-Servicing Capacity of

Asian Developing Countries: An Applicationof Critical Interest Rate Approach Jungsoo Lee, June 1983

No. 17 External Shocks, Energy Policy,and Macroeconomic Performance of AsianDeveloping Countries: A Policy AnalysisWilliam James, July 1983

No. 18 The Impact of the Current Exchange RateSystem on Trade and Inflation of SelectedDeveloping Member Countries Pradumna Rana, September 1983

No. 19 Asian Agriculture in Transition: Key Policy IssuesWilliam James, September 1983

No. 20 The Transition to an Industrial Economyin Monsoon Asia Harry T. Oshima, October 1983

No. 21 The Significance of Off-Farm Employmentand Incomes in Post-War East Asian Growth Harry T. Oshima, January 1984

No. 22 Income Distribution and Poverty in Selected Asian Countries John Malcolm Dowling, Jr., November 1984

No. 23 ASEAN Economies and ASEAN EconomicCooperation Narongchai Akrasanee, November 1984

No. 24 Economic Analysis of Power Projects Nitin Desai, January 1985

No. 25 Exports and Economic Growth in the Asian Region Pradumna Rana, February 1985

No. 26 Patterns of External Financing of DMCs E. Go, May 1985

No. 27 Industrial Technology Developmentthe Republic of KoreaS.Y. Lo, July 1985

No. 28 Risk Analysis and Project Selection: A Review of Practical Issues J.K. Johnson, August 1985

No. 29 Rice in Indonesia: Price Policy and Comparative Advantage I. Ali, January 1986

No. 30 Effects of Foreign Capital Inflowson Developing Countries of Asia Jungsoo Lee, Pradumna B. Rana,

and Yoshihiro Iwasaki, April 1986No. 31 Economic Analysis of the Environmental

Impacts of Development Projects John A. Dixon et al., EAPI,

East-West Center, August 1986No. 32 Science and Technology for Development:

Role of the Bank Kedar N. Kohli and Ifzal Ali, November 1986

No. 33 Satellite Remote Sensing in the Asianand Pacific Region

No. 60 A Computable General Equilibrium Modelof NepalTimothy Buehrer and Filippo di Mauro,

October 1993No. 61 The Role of Government in Export Expansion

in the Republic of Korea: A RevisitYun-Hwan Kim, February 1994

No. 62 Rural Reforms, Structural Change,and Agricultural Growth inthe Peoples Republic of China Bo Lin, August 1994

No. 63 Incentives and Regulation for Pollution Abatementwith an Application to Waste Water Treatment

Sudipto Mundle, U. Shankar,and Shekhar Mehta, October 1995

No. 64 Saving Transitions in Southeast Asia Frank Harrigan, February 1996

No. 65 Total Factor Productivity Growth in East Asia: A Critical Survey Jesus Felipe, September 1997

No. 66 Foreign Direct Investment in Pakistan:Policy Issues and Operational Implications

Ashfaque H. Khan and Yun-Hwan Kim, July 1999

No. 67 Fiscal Policy, Income Distribution and Growth Sailesh K. Jha, November 1999


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Mohan Sundara Rajan, December 1986No. 34 Changes in the Export Patterns of Asian and

Pacific Developing Countries: An EmpiricalOverview Pradumna B. Rana, January 1987

No. 35 Agricultural Price Policy in NepalGerald C. Nelson, March 1987

No. 36 Implications of Falling Primary CommodityPrices for Agricultural Strategy in the Philippines Ifzal Ali, September 1987

No. 37 Determining Irrigation Charges: A Framework

Prabhakar B. Ghate, October 1987 No. 38 The Role of Fertilizer Subsidies in AgriculturalProduction: A Review of Select Issues M.G. Quibria, October 1987

No. 39 Domestic Adjustment to External Shocksin Developing Asia Jungsoo Lee, October 1987

No. 40 Improving Domestic Resource Mobilizationthrough Financial Development: Indonesia Philip Erquiaga, November 1987

No. 41 Recent Trends and Issues on Foreign DirectInvestment in Asian and Pacific Developing Countries P.B. Rana, March 1988

No. 42 Manufactured Exports from the Philippines: A Sector Profile and an Agenda for Reform I. Ali, September 1988

No. 43 A Framework for Evaluating the EconomicBenefits of Power Projects I. Ali, August 1989

No. 44 Promotion of Manufactured Exports in Pakistan Jungsoo Lee and Yoshihiro Iwasaki,

September 1989No. 45 Education and Labor Markets in Indonesia:

A Sector Survey Ernesto M. Pernia and David N. Wilson,

September 1989No. 46 Industrial Technology Capabilities

and Policies in Selected ADCs Hiroshi Kakazu, June 1990

No. 47 Designing Strategies and Policiesfor Managing Structural Change in Asia Ifzal Ali, June 1990

No. 48 The Completion of the Single European Commu-

nity Market in 1992: A Tentative Assessment of its Impact on Asian Developing Countries J.P. Verbiest and Min Tang, June 1991

No. 49 Economic Analysis of Investment in PowerSystems Ifzal Ali, June 1991

No. 50 External Finance and the Role of MultilateralFinancial Institutions in South Asia:Changing Patterns, Prospects, and Challenges Jungsoo Lee, November 1991

No. 51 The Gender and Poverty Nexus: Issues and

Policies M.G. Quibria, November 1993No. 52 The Role of the State in Economic Development:

Theory, the East Asian Experience,and the Malaysian Case Jason Brown, December 1993

No. 53 The Economic Benefits of Potable Water SupplyProjects to Households in Developing Countries Dale Whittington and Venkateswarlu Swarna,

January 1994No. 54 Growth Triangles: Conceptual Issues

and Operational Problems Min Tang and Myo Thant, February 1994

No. 55 The Emerging Global Trading Environmentand Developing Asia Arvind Panagariya, M.G. Quibria,

and Narhari Rao, July 1996

No. 56 Aspects of Urban Water and Sanitation inthe Context of Rapid Urbanization inDeveloping Asia

Ernesto M. Pernia and Stella LF. Alabastro,September 1997

No. 57 Challenges for Asias Trade and Environment Douglas H. Brooks, January 1998

No. 58 Economic Analysis of Health Sector Projects- A Review of Issues, Methods, and Approaches Ramesh Adhikari, Paul Gertler, and

Anneli Lagman, March 1999No. 59 The Asian Crisis: An Alternate View

Rajiv Kumar and Bibek Debroy, July 1999No. 60 Social Consequences of the Financial Crisis in

Asia James C. Knowles, Ernesto M. Pernia, and

Mary Racelis, November 1999

No. 1 Poverty in the Peoples Republic of China:Recent Developments and Scopefor Bank Assistance K.H. Moinuddin, November 1992

No. 2 The Eastern Islands of Indonesia: An Overviewof Development Needs and Potential Brien K. Parkinson, January 1993

No. 3 Rural Institutional Finance in Bangladeshand Nepal: Review and Agenda for Reforms A.H.M.N. Chowdhury and Marcelia C. Garcia,

November 1993No. 4 Fiscal Deficits and Current Account Imbalances

of the South Pacific Countries: A Case Study of VanuatuT.K. Jayaraman, December 1993

No. 5 Reforms in the Transitional Economies of Asia Pradumna B. Rana, December 1993

No. 6 Environmental Challenges in the Peoples Republicof China and Scope for Bank Assistance Elisabetta Capannelli and Omkar L. Shrestha,

December 1993

No. 7 Sustainable Development Environmentand Poverty Nexus K.F. Jalal, December 1993

No. 8 Intermediate Services and EconomicDevelopment: The Malaysian ExampleSutanu Behuria and Rahul Khullar, May 1994

No. 9 Interest Rate Deregulation: A Brief Surveyof the Policy Issues and the Asian ExperienceCarlos J. Glower, July 1994

No. 10 Some Aspects of Land Administrationin Indonesia: Implications for Bank OperationsSutanu Behuria, July 1994

No. 11 Demographic and Socioeconomic Determinantsof Contraceptive Use among Urban Women inthe Melanesian Countries in the South Pacific:

A Case Study of Port Vila Town in VanuatuT.K. Jayaraman, February 1995

No. 12 Managing Development throughInstitution Building Hilton L. Root, October 1995

No. 13 Growth, Structural Change, and Optimal

OCCASIONAL PAPERS (OP)


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No. 1 Estimates of the Total External Debt of the Developing Member Countries of ADB:1981-1983 I.P. David, September 1984

No. 2 Multivariate Statistical and GraphicalClassification Techniques Appliedto the Problem of Grouping Countries I.P. David and D.S. Maligalig, March 1985

No. 3 Gross National Product (GNP) MeasurementIssues in South Pacific Developing MemberCountries of ADBS.G. Tiwari, September 1985

No. 4 Estimates of Comparable Savings in SelectedDMCs Hananto Sigit, December 1985

No. 5 Keeping Sample Survey Designand Analysis Simple I.P. David, December 1985

No. 6 External Debt Situation in AsianDeveloping Countries I.P. David and Jungsoo Lee, March 1986

No. 7 Study of GNP Measurement Issues in theSouth Pacific Developing Member Countries.Part I: Existing National Accountsof SPDMCsAnalysis of Methodologyand Application of SNA Concepts P. Hodgkinson, October 1986

No. 8 Study of GNP Measurement Issues in the SouthPacific Developing Member Countries.Part II: Factors Affecting IntercountryComparability of Per Capita GNP P. Hodgkinson, October 1986

No. 9 Survey of the External Debt Situationin Asian Developing Countries, 1985 Jungsoo Lee and I.P. David, April 1987

No. 10 A Survey of the External Debt Situationin Asian Developing Countries, 1986 Jungsoo Lee and I.P. David, April 1988

No. 11 Changing Pattern of Financial Flows to Asianand Pacific Developing Countries Jungsoo Lee and I.P. David, March 1989

No. 12 The State of Agricultural Statistics inSoutheast Asia I.P. David, March 1989

No. 13 A Survey of the External Debt Situationin Asian and Pacific Developing Countries:1987-1988 Jungsoo Lee and I.P. David, July 1989

No. 14 A Survey of the External Debt Situation in Asian and Pacific Developing Countries: 1988-1989 Jungsoo Lee, May 1990

No. 15 A Survey of the External Debt Situationin Asian and Pacific Developing Countries: 1989-1992 Min Tang, June 1991

No. 16 Recent Trends and Prospects of External DebtSituation and Financial Flows to Asianand Pacific Developing Countries Min Tang and Aludia Pardo, June 1992

No. 17 Purchasing Power Parity in Asian Developing Countries: A Co-Integration Test

Min Tang and Ronald Q. Butiong, April 1994No. 18 Capital Flows to Asian and Pacific Developing

Countries: Recent Trends and Future Prospects Min Tang and James Villafuerte, October 1995

STATISTICAL REPORT SERIES (SR)

Poverty InterventionsShiladitya Chatterjee, November 1995

No. 14 Private Investment and MacroeconomicEnvironment in the South Pacific IslandCountries: A Cross-Country AnalysisT.K. Jayaraman, October 1996

No. 15 The Rural-Urban Transition in Viet Nam:Some Selected Issues

Sudipto Mundle and Brian Van Arkadie,October 1997

No. 16 A New Approach to Setting the Future

Transport Agenda Roger Allport, Geoff Key, and Charles Melhuish June 1998

No. 17 Adjustment and Distribution:The Indian Experience

Sudipto Mundle and V.B. Tulasidhar, June 1998

No. 18 Tax Reforms in Viet Nam: A Selective Analysis Sudipto Mundle, December 1998

No. 19 Surges and Volatility of Private Capital Flows to Asian Developing Countries: Implicationsfor Multilateral Development Banks Pradumna B. Rana, December 1998

No. 20 The Millennium Round and the Asian Economies: An Introduction Dilip K. Das, October 1999

No. 21 Occupational Segregation and the GenderEarnings Gap

Joseph E. Zveglich, Jr. and Yana van der Meulen Rodgers, December 1999No. 22 Information Technology: Next Locomotive of

Growth? Dilip K. Das, June 2000


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2. Improving Domestic Resource Mobilization ThroughFinancial Development: Bangladesh July 1986

3. Improving Domestic Resource Mobilization ThroughFinancial Development: Sri Lanka April 1987

4. Improving Domestic Resource Mobilization Through

Financial Development: India December 1987 5. Financing Public Sector Development Expenditurein Selected Countries: Overview January 1988

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11. Financing Public Sector Development Expenditurein Selected Countries: Pakistan June 1988

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13. Financing Public Sector Development Expenditurein Selected Countries: Thailand June 198814. Towards Regional Cooperation in South Asia:

ADB/EWC Symposium on Regional Cooperationin South Asia February 1988

15. Evaluating Rice Market Intervention Policies:Some Asian Examples April 1988

16. Improving Domestic Resource Mobilization ThroughFinancial Development: Nepal November 1988

17. Foreign Trade Barriers and Export Growth

September 198818. The Role of Small and Medium-Scale Industries in the

Industrial Development of the Philippines April 1989

19. The Role of Small and Medium-Scale Manufacturing Industries in Industrial Development: The Experienceof Selected Asian Countries

January 199020. National Accounts of Vanuatu, 1983-1987 January 1990

21. National Accounts of Western Samoa, 1984-1986 February 1990

22. Human Resource Policy and EconomicDevelopment: Selected Country Studies

July 199023. Export Finance: Some Asian Examples

September 199024. National Accounts of the Cook Islands, 1982-1986

September 199025. Framework for the Economic and Financial Appraisal

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and Socioeconomic Justification of Education Projects January 1994

27. Guidelines for the Economic Analysis of Projects February 1997 28. Investing in Asia

1997 29. Guidelines for the Economic Analysis

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30. Guidelines for the Economic Analysisof Water Supply Projects1999

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11. Current Issues in Economic Development: An Asian Perspective Edited by M.G. Quibria and J. Malcolm Dowling, 1996$50.00 (hardbound)

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