Lingnan University Digital Commons @ Lingnan University

Centre for Asian Pacific Studies 亞洲太平洋研究 CAPS Working Paper Series 中心

3-2004

Exchange rate regimes and the twin economies of Hong Kong and Singapore

Yue MA

Y. Y. KUEH

Raymond, C. W. NG

Follow this and additional works at: https://commons.ln.edu.hk/capswp

Part of the Political Science Commons, and the Public Affairs, Public Policy and Public Administration Commons

Recommended Citation Ma, Y., Kueh, Y. Y., & Ng, R. C. W. (2004). Exchange rate regimes and the twin economies of Hong Kong and Singapore (CAPS Working Paper Series No.148). Retrieved from Lingnan University website: http://commons.ln.edu.hk/capswp/58

This Paper Series is brought to you for free and open access by the Centre for Asian Pacific Studies 亞洲太平洋研 究中心 at Digital Commons @ Lingnan University. It has been accepted for inclusion in CAPS Working Paper Series by an authorized administrator of Digital Commons @ Lingnan University. Working Paper Series

Cεn佐 e for Asian Pacific Studies

No. 148 (Mar 04) CAPS

Exchange Rate Regimes and the Twin Economies

. of Hong Kong and Singapore

一 Y些 Ma ， Y.Y. Kueh and Raymond C.W. Ng

Lingnan U nivεrSlty 48 Hong I(ong Exchange Rate Regimes and the Twin Economies

of Hong Kong and Singapore

Yue Ma, Y.Y. Kueh and Raymond C.W. Ng

扎1arch 2004 。 Yue Ma, Y.Y. Kueh and Raymond C.W. Ng

Centre for Asian Pacific Studies Institute ofHumanities and Social Sciences -叮 Unn) LTHTAFEN叫‘拍ahnhhEgVH叮 .u7OE--m句 YZ9u JI uoeaer凹 惜別叫“叫EA 卜 川、 口位叫州到 6 4670 LXmPAhoo-V 。2引凡切臼

叮士 pm叫叫a ，叫 恤叫 J 1凶 n DAnb

CAPS and CPPS Working Papers are circulated to invite discussion and critical comment. Opinions expressed in them are the author's and should not be taken as representing the opmlOns of the Centres or Lingnan University. These papers may be freely circulated but they are not to be quoted without the written perrnission of the author. Please address comments and suggestions to the author. Exchange Rate Regimes and the Twin Economies of Hong Kong and Singapore*

+-uaoY mE也∞Mm anuaαnMDh只YMmkmuevdenht 中 vu - - . 叫]汀 WMU ， 11 叫 也

v7JVYDTLσb 此 叫 inplC NEh r.riomCH073ommhm ghw QU1J n-U--noonoob ok 叫 叫到 侃到φt mwd

U. 可 叫 可叫 A H 心 啥 m

+ Corresponding author

DrYueMa, Economics Department, Lingnan University, Hong Kong Tel : +(852) 2616 7202 Fax: +(852) 2891 7940 Email : [email protected] homepage: www.Ln.edu.hk/econlstaffj.yuema

March 2004

* We are grateful to the useful suggestions and comments from seminar participants of Lingnan Universi 句， Hong Kong, and University of Macau. The authors thank Mr W H Tang for research assistance. The research was supported by a grant from Lingnan Universityο'-l' o. RES-007/200) , Hong Kong. However, we are responsible for any remammg errors.

嶺南夫 三三亡\

!JtJ

LlNGNAN UNiVERb!!YLjBRART Exchange Rate Regimes and the Twin Economies of Hong Kong and Singapore

Abstract

Based on a small, open-economy IS-LM prototype model, this paper examines the sources of macroeconomic instabilities in Hong Kong and Singapore operating under two similar cu訂ency board arrangements (CBAs). The empirical findings suggest that in general both extemal and intemal factors contribute to the macroeconomic volatilities observed in the two economies. Interestingly, whilst in Hong Kong interest rate is the single most important factor accounting for the variation in real GDP, price level and money supply, in most cases in Singapore the volatilities of these three macro variables cannot be attributed to a significant single factor. Interest rate in both Hong Kong and Singapore moves in tandem with that ofthe US in the long run. In the short run, the US interest rate has both direct and indirect impacts on the two economies. Due to the high openness, international prices also affect domestic demands and prices in Hong Kong and Singapore. In addition, macroeconomic volatilities in Hong Kong and Singapore are also attributable to the shocks in their domestic demand, though the relative magnitude of impact differs. Finally, there is evidence of a trade-off between exchange rate and interest rate targeting for the stabili 句 of money supply in Singapore. Our findings provide a useful framework for future research on the financial and monetary transmission mechanisms in the twin economies of Hong Kong and Singapore

JEL codes: F41 - Open Economy Macroeconomics, E52 - Monetary Po1icy (Targets, Instruments, and Effects), F31 - Foreign Exchange, 053 - Asia

Keywords: open-economy IS-LM, VAR, Hong Kong, Singapore 1. Introduction

The financial crisis in East Asia and more recently in Latin America have inspired renewed interest in examining the relative merits of the pegged versus f1 0ating exchange rate regimes, and the search for a new exchange rate system in the emerging economies. Most effort has been devoted to assessing the relative perforrnance of the pegged and f1 0ating systems especially in terms of facilitating economic growth and containing macro-instabilities

This paper attempts to identify and compare the sources of macroeconomic volatilities in Hong Kong and Singapore. Both cities, dubbed ‘twin economies', share similar economic features. Both are small, open metropolitan economies lacking natural resources. They are among the four Asian newly industrialised economies (NIEs) that have successfully adopted an export-oriented strategy for their economic development and industrialisation. They have both developed as key regional financial centres and have accumulated substantial official foreign reserves (Ch凹， 1997). Most importantly, in the context of the present study, Hong Kong and Singapore have adopted the cuπency board arrangements (CBA) 的 the fundamental framework for their monetary and exchange rate systems. However, the CBAs as adopted in two economies differ markedly by design

Hong Kong's CBA is essentially a pegged exchange rate regime with an explicit official parity of 7.8 Hong Kong dollar per US dollar. Among others, its major weakness is that Hong Kong has to import the US monetary policy and its domestic interest rate must follow the US interest rate cJ osely. Otherwise, the resultant interest rate differentials would trigger arbitrage capital f1 0ws and fuel exchange rate

2 volatilities in the foreign exchange market. As a result, the Hong Kong Monetary

Authority (HKMA) has lost the autonomy to (and hence cannot) utilize the monetary policy to fine-tune the domestic economy (Tsang, 1999; Kueh and Ng, 2002)

By contrast, Singapore's CBA is a managed f1 0ating exchange rate regime with a target rate being linked to an imp1icit basket of currencies. Without the constraint from exchange rate targeting, the Monetary Authority of Singapore (MAS) can exercise discretionary control over the domestic demand (when needed) compared to the HKMA. ln other words, the MAS can basically command all the conventional monetary tools to fulfil its demand management objectives. These include, for instance, open market operations, discount window, reserve requirements and foreign exchange market interventions (Chan and Ngiam, 1998)

Inf1ation is one of the key indicators of macroeconomic volatilities. Conventional wisdom suggests that inf1 ation dynamics of a small open economy should in large part be determined by a combination of external and domestically generated factors

Whereas the former refers mainly to the impacts ofvariations in foreign exchange rate and international price, the latter focuses on the role of overheating domestic demand in fuellíng inf1 atíonary pressure. Both Singapore and Hong Kong are small, and extr巴mely open economies. Expectedly, their domestic economies are particularly vulnerable to adverse external economic shocks, and hence seríous macroeconomic volatilities

Hong Kong's adoptíon of an exchange rate peg should warrant a low, steady inf1 atíon rate. Arnong other things, a relatively stable foreign exchange rate and prudent

3 monetary and fiscal disciplines as imposed by such a system should to an extent help to contain inflationary pressure. The observed macroeconomic volatilities, however, point to the opposite. In fact, Singapore seems to have performed better tban Hong

Kong in terms of maintaining macro-stability. Most remarkably, inf1 ation rates and nominal interest rates bave both been lower in Singapore than in Hong Kong (cf.

Figures 1 and 3). In addition, Singapore has consistently achieved faster economic growth than Hong Kong (cf. Figure 2)

Given that Hong Kong's foreign exchange rate had somewhat appreciated during the period of the peg (in large part following tbe prolonged strengthening of the US dollar), it seems apparent that Hong Kong's macroeconomic instability was to a large

extent driven by "domestically generated" factors . Specifically, the domestic interest rate has not been able to adjust to choke off the overheating demand and inf1 ationary

pressure. To make it worse, Hong Kong had to follow the US monet訂Y policy and

hence its interest rate. When the local economic cycle is not consistent with that of the

US , Hong Kong's local interest rate might not respond according to its own need. The

artificially low (or even negative real) interest rate would further exacerbate macro­

volatilities. ln this regard, real interest rate has been more effective in containing

inflation in Singapore than in Hong Kong (Yip, 1996). An examination of Singapore' s

monetary policy and its contribution to maintaining macroeconomic stability would

indeed provide usefullessons to Hong Kong

Against this background, the primary pu中 ose of this paper is to identify the factors

and compare their relative strengths in driving the macroeconomic instabiliti 巳 s m

Hong Kong and Singapore. Special attention will be given to exploring whether the

4 choice of exchange rate targeting (instead of monetary targeting) based on the CBA would have given rise to certain monetary mismanagement that somewhat boosted such macroeconomic volatiIities

We intend to answer this question by estimating two open-economy IS-LM models for Hong Kong and Singapore via a structural vector auto-regressive (V AR) process

(GaIi, 1992; Bemanke and Blinder, 1992; Bemanke and Mihov, 1998). The econometric techniques of impulse response and variance decomposition analyses wilI be appIied to the V AR model to identify the major sources of the macroeconomic instability and inf1 ationary pressure in the two economies

The remainder of the paper is organised as follows . Section 2 brief1 y discusses the conditions required for maintaining macroeconomic stability under a CBA-linked exchange rate regime. Section 3 presents an open-economy IS-LM model and explains the estimation techniques. Section 4 reports the empirical results of the two structural V AR models for Hong Kong and Singapore, and briefly discusses the findings. Finally, Section 5 concludes

2. Exchange rate regime and macroeconomic stability

Since October 1983 , Hong Kong has adopted a linked exchange rate regime with a cu汀ency board arrangement (CBA). The authority needs to fully support the issuing of the domestic cu汀ency by holding an equivalent amount of US dollar reserves

Whilst the rate ofHK$7.8 per US dollar has been fixed for the issuing and redemption of the Hong Kong cu口 ency ， the foreign exchange rate is nevertheless freely

5 determined in the foreign exchange market. Tbe exchange rate parity has been maintained through the self-adjusting interest rate arbitrage mechanism and, at times when needed, discretionary govemment interventions in the foreign excbange market

(Tsang, 1999). The primary and only monetary policy objective is to maintain the parity of the Hong Kong dollar against the US dollar. Nonetheless, the Hong Kong dollar is free to f1 0at against otber foreign currencies following the movements of the

US dollar. The effective excbange rate index is not necessarily constant over time (see

Figure 4).

Theoretical 旬， the macroeconomic stability of an economy operating under a CBA­ pegged exchange rate regime should be restored, automatically, througb domestic

price adjustment. Suppose an economy experiences a boom driven by, for instance, an

improvement in its extemal balance, domestic prices will adjust upward, with the

exchange rate and interest rate being fixed. This should in tum weaken the economy's

price competitiveness, thus discouraging exports and boosting imports. The

deteriorating trade balance will offset the initial expansion of the economy, reducing

the overbeating demand pressure.

It is worth-noting that, as both the exchange rate and interest rate are not allowed to

adjust under an exchange rate peg, price adjustments required for restoring

macroeconomic stabili句 are bound to be more volatile and prolonged than would

otherwise be expected under a f1 0ating exchange rate regime (where both interest rate

and exchange rate could adjust freely to help curb excessive price movements). ln this

regard, tbe pegged exchange rate regime does not necessarily guarantee economic

stability. What is worse, inf1ationary pressure can be expectation-augmented,

6 generating its self-fulfilling momentum. In addition, in f1 ation may be further amplified if there exists domestic market distortion that severely limits price f1 exibility and adjustment

By contrast, Singapore bas adopted a managed f1 0ating exchange rate regime with an implicit index target since June 1973. It allows the Monetary Authority of Singapore

(MAS) to exercise monetary targeting to manage the domestic demand, unlike the case of exchange rate targeting in Hong Kong. The MAS bas all the conventional monetary tools to maintain the extemal and intemal balances of the economy, including open market operations, discount window, reserve requirements and foreign exchange market interventions, etc. (Chan and Ngiam, 1998)

Tbere has been a rapid growth in the literature related to the CBAs in the two economies. The more recent study about Hong Kong focuses on the technical viability of the cu 訂ency board (Tsang, 1999) and its history (Jao, 1998). Siregar and Walker

(2000) shed light on the impact of monetary shocks on the real exchange rate of Hong

Kong only. Chan and Ngiam (1 998) examined the Singapore experience of averting the cu口ency crises. Toh (1999) investigated the causality between the Singapore dollar exchange rate and domestic prices

Research based on institutional approach abound (s白， for example, Ho, 1995). Kueh

(2001) explored the impacts of extemal factors on Hong Kong's trade and industrial sector instability. Ng and Chen (1 998) and MAS (2001) concentrated on the institutional reforrns undertaken to enhance the monetary management mechanisms in

Hong Kong and in Singapore, respectively. Most of these publications are of a

7 descriptive nature, using conventional statistical tabulations to detect and analyse the trends of macroeconomic aggregates

Several macro-econometric models have been developed for the Hong Kong and

Singapore economies, e.g. the Hong Kong model of the LINK project coordinated by

Lawrence KJein (see Chou and Lin, 1994). Whilst Chou and Lin (1 994) focused on the extemal 甘ade of the Hong Kong economy, Sung and Wong (2000) have built models with explicit consideration of the China factor. Choy (1 999) examined the business cycle f1uctuations in Singapore without the monetary sector. Robinson and Wang

(2000) constructed a macro-econometric model for the Singapore economy based on the sectoral approach

This paper intends to fill a research gap by assessing the relative importance of extemal versus intemal factors on driving the macroeconomic volatilities in Hong

Kong and Singapore

3. 心fodel specification and data

Following the work of Gali (1 992), Bemanke and Blinder (1 992), and Bemanke and

Mihov (1998), we adopt an open-economy IS-LM model with a short-run Phillips curve to identify the structural shocks and to capture their impacts on the Hong Kong and Singapore economies respectively. Particular旬， we modify the IS-LM framework to incorporate the restrictions of cuηency board arrangements (CBA) on the

functioning of the macro-economy. We then estimate the model by employing a

structural vector auto-regressive (SV AR) process. The econometric techniques of

8 impulse response and variance decomposition analyses will be applied to the VAR model to capture the major sources of macroeconomic vo latilities in Hong Kong and

Singapore, both in the short run and long run

3. 1. An open-economy IS-LM model

We proceed to specify a theoretical IS-LM framework that should fit in the small , open nature of the Hong Kong and Singapore economies. The model will then be estl 訂lated using the data of two economies respectively. The following outlines a simplified version of the open-economy IS-LM model

s yt =-α1( é1 + Pt - pimt) -α2[R t - E必Pt+ I)] + u/ (1 ) md mdt = pt+α3 叭， α4 rt +α5 RUSl +α6~ é1 + Ut (2)

口1\ =口1dt (3)

Rt = RUSt ﹒ Et (~et+ l) + UtR (4)

Rus RusUSl, = UtU, 。)

Pt=α7 plmt (6)

ptm plmt =-α g e t + Ut (7)

et =IIte (8) where

αparameters

et log of nominal effective exchange rate index

Et(~e叫) = expected change of et+1

Et(企 Pt + l) = expected change ofpt+1

9 RIdt log of nominal demand for money

口1st log ofnominal money supply

pt log of consumer price index

plmt log of import prices

Rt nominal domestic interest rate

Rust US nominal interest rate

UtJ structural shocks

yt log of real aggregate demand

f log of potential output

Eq. (1) represents an open-economy IS equation. Real aggregate demand (y) is essentially determined by the real exchange rate (et . Pt - pimt), the real interest rate

IS [Rt - Et(flpt+ t}], and a structural demand shock (Ut ). Eq. (2) 的 the demand for money function. Money market equilibrium and hence the LM curve is given by Equations

(3) and (2) together. Demand for money (mdt) is determined positively by real aggregate demand (y) and negatively by nominal domestic interest ra臼 (R t ). US interest rate (Rust) in Eq. (2) is to capture the cuπency substitution effect. Variation in the US interest rate alters the opportunity cost of holding the US dollar and therefore affects the demand for the Hong Kong dollar or Singapore dollar. Similarly, the expected exchange rate appreciation [Eμet+l)] is to capture the impact of the portfolio adjustment on the demand for money as caused by exchange rate variations

Eq. (4) represents the uncovered interest parity (UIP) condition, which captures the intrinsic interest rate arbitrage mechanism of an exchange rate peg. The UIP requires the domestic Ínterest rate (Rt) to follow the US interest rate (Rust) closely, subject to a

R stochastic shock (Ut ). Equations (5) and (8) impose that the US interest rate and the

--EAnu exchange rate of Hong Kong (or Singapore) are deterrnined exogenous 旬， and are subject to extemal shocks only. Eq. (6) is a modified short-run Phillips curve. ln a small, open economy such as that of Hong Kong or Singapore, aggregate price level

(P) is influenced by both import prices (p imt) and excess domestic demand (yt - 1)

Finally, as given by Eq. (7), import prices (p imt) 的 deterrnined by the foreign exchange rate and a structural shock

3.2. Econometric techniques

Assuming adaptive expectations, the theoretical model can be estimated by a structural VAR process with a 7x1 vector Xt = (Rus, R, e, pim, y, p, m)t'. ln addition, there are 7 independent structural shocks driving the economy with tbe ordering Ut =

RUS e pim d (ut , U 戶， Ut , Ut , u?, ut , ut )'. One of the advantages of estimating the model by a

V AR process is that the dynamic adjustment of tbe macro-economy can be fully

captured with minimum theoretical restrictions (Rogers, 1999)

Having identified the structural sbocks from the extended IS-LM model, we proceed

to investigate the major sources of macro-instabilities in Hong Kong and Singapore,

respectively. As argued previously, the exchange rate regimes adopted in Hong Kong

and Singapore have exposed the economies to extemal monetary shocks. Specifically,

we examine whether the monetary shocks, such as interest rate and money supply

shocks, would have stronger or more persistent impacts on domestic inf1 ation and

output than the shocks in import prices or foreign exchange rate. This can be

achieved by applying the impulse response and variance decomposition analyses. The

impulse response function helps identify the direction and persistence of a shock,

11 whereas variance decomposition analysis assesses the relative irnportance of the shocks at various time horizons by measuring the proportion of the forecast-error variance of the respective variables explained by each of the shocks

3.3. Data sources

The structural V AR (SV AR) model is estimated by using quarterly data for the period

1982Q4-1999Q4 in the case of Hong Kong, and over the period 1980Q4-1999Q4 for

Singapore. In both cases, y is defined as the log of real GDP in constant 1990 prices m is measured as the log ofmoney supply M2. The price variabJe p is obtained as the log of consumer price index [Index A for Hong Kong (1 990=100), and all item index for Singapore (Nov 97-0ct 98=100), respectively]. We use seasonally adjusted series of y, m and p. e is measured as the Jog of trade-weighted effective exchange rate

(1 990= 100 for Hong Kong and 1995= 100 for Singapore, respectiveJy). pim is obtained as the Jog of price de f1 ator for the imported goods and services weighted by their relative shares

For Hong Kong, nominal interest rate (R) is measured as nominal 3-month Hong

Kong interbank offered rate (HIBOR) whereas for Singapore, interest rate is obtained as 3-month Singapore interbank offered rate (SIBOR). Rus is defined as the US interbank interest rate of 3-month certificate of deposit (CD). A lI variables except R and Rus are expressed in Jogarithms

The data of Hong Kong are co lJected from various issues of the Monthly Digest of

Statistics published by the Hong Kong Census and Statistics Department. The

Singaporean data are collected from the DataStream International, except the effective

12 exchange rate index, which is obtained from the Intemational Financial Statistics (IFS)

CD-ROM published by the IMF. Rus is obtained from the website of the Federal

Reserve Bank of the US

4. Empirical techniques and results

We first brief1 y discuss the econometric techniques applied in this study and the interpretations of the structural shocks. We then present the empirical findings and discuss their policy implications

4.1. Identification 01 shocks in the JS-LM model

Suppose the extended IS-LM model to be estimated for the Hong Kong and Singapore economies can be written as the following structural V AR model

D(L)Xt = Ut (9) where Xt = (Rus t，孔， et, pimt, yt, Pt, mt)', which is defined in Equations (1) - (8), Ut =

Rus d (Ut , UλuλlItpim ， u代 uλut )" Ut - N(O, 17) , h is a 7x7 identity matrix, D(L) =

;:;qi=O Di L\ D(L) 的中 th order matrix of polynomials with the lag operator L. Do is the structural parameter matrix that captures the contemporaneous relationships of Xt. As most macroeconomlC tlme senes are nonstatlOnary, lt IS necessary to re-parametense

Eq. (9) into the first-differenced form I

f'咀 nU、‘'， EE.A ，、 . A0 6Xt = I Aj 6Xt-i + AqXt_q + Ut 、

I If none of the variables in Xt cointegrates, then Aq = 0 and we left with a standard structural V AR in the first-difference of Xt (Rogers, 1999). If some of the variables are cointegrated, then Aq ;t:. 0

13 where 6Xl = Xt - X t 寸 ， Ao = Do, Aj = - ì:1j=o Dj, (i=1 , 2, .. ...， ω

The reduced-fonn of Eq. (1 0) that can be estimated by the Johansenls (1 991) cointegration procedure is given as follows

r l l 、 '. ‘ - ‘ 6Xt = I r j6Xt•j+ r qX叭 V l 、 J where

r j = Ao-1Aj , (i=l, 2 ， ω ， (1 2)

and Vl - N(O , 0) is the reduced-fonn residual tenn and is assumed to be a linear transfonnation of the structural shocks

1 Vl = Ao- Ul (13)

If we could identify Ao from the estimated Eq. (1 1), we can then recover all structural parameters Aj (i = 1, 2, ..... , q) and the structural shocks Ut by Equations (1 2) and (1 3) respectlve旬， given the fact that r j (i = 1, 2, .... . ωare estimated from Eq. (11)

We use the following relationship to identify Ao:

AoOAo' = h (14)

There are 7 x 7 = 49 parameters in Ao but since n is a symmetric matrix, there are only 7 x (7 +1)/2 = 28 equations in Eq. (1 4), Therefore, we need to propose 49 - 28 =

21 restrictions on Ao to identify the whole matrix A。

To achieve this identification pu 中 O 品， we impose zeros for all the values in the upper

triangular of Ao

14 。 11 。 。 Ao = I a 們21 aι22 (1 5)

a 71 an a77 whi.ch states that Ao is a lower triangular matrix, so is AO-l (see Chiang 1984, for example)

The econometric implications of Eq. (1 5) become clear if we rewrite Eq. (11) 的 fo l1 ows

.6 Xt = I r i.6 Xt-i + r qXt-q+ Ao-l Ut (16)

A low triangular Ao-l implies that Eq. (1 6) is a recursive system in the sense that the

k structural shock Ut (k = 1, 2, .....7) enters the system (16) recursively, where Ut = (叫，

2 7 Rus r口 P Ut , .... . Ut )' = (Ut , Uλu已 ut ， U?, Ut , Ut叮叮\ In other words, equation k is only

1 k subject to the shocks of Ut , U?, .. ..., Ut\ but it is immune from the shocks of Ut + 1,

L + 呵 守 K ， J U 心 U

The economic implications ofEq. (15) can be given intuitively as follows

(a) Rus is exogenous to both Hong Kong and Singapore economies, and deþends only on the factors outside of the two economic systems (such as inf1 ation and economic growth in the US). Domestic interest rate R in Hong Kong or Singapore responds only to the US interest rate Rus, rather than their own domestic economic situations

Essentially, this serves to model a key feature of Hong Kong's currency board arrangement (CBA), and should to a certain extent also ref1 ect the policy objectives of

15 the MAS. The choice of an exchange rate as the interrnediate target of mon 巴 tary policy implies that the MAS must give up its control over the domestic interest rate

(or money supply) targeting (see, MAS, 2001 , p.2). It also implies that the effective exchange rates of Hong Kong and Singapore are subject to the Rus shocks and the interest rate shocks from other countries due to the movements of the US dollar against other foreign currencies

These assumptions on Rus, R and e justify the zero-restrictions in the first three rows of Ao in Eq. (1月

(b) Import price pim depends on the foreign exchange rate in Eq. (7) and dom 巴stlc price p is modelled by a modified Phillips-curve in Eq. (6). The structures of

th th Equations (6) and (7) impose zeros for the 4 and 5 rows of Ao in Eq. (1 5)

(c) Finally, Equations (1) and (2) imply zeros in the last two rows of Ao in Eq. (15)

4.2. Estimation results

For Hong Kong, we use quarterly ~ata 1982Q4-1999Q4 to estímate the reduced-forrn

V AR of Xt = (Rust, Rt, et, pimt, yt, Pt, mt)' as defined by Equations (1 )-(8). As for

Singapore, the V AR is estimated for the period 1980Q4-1999Q4. Augmented Dickey­

Fuller (ADF) tests are first performed to examine whether the time series used in the present study for each economy are stationary. The results indicate that all time series

are integrated ofthe first order [i.e. I(1)] (see Table 1)

16 We move on to apply tbe Jobansen (1991) cointegration procedure to tbe 7-variable

VAR system to identify the number of cointegration vectors in Eq. (11) for the two economies, respectively

The estimation results for Hong Kong are reported in Table 2(a). There are 4 cointegrating vectors identified among the 7 variables. The first cointegrating vector is interpreted as tbe ope仆 economy IS curve [Eq. (1)刀] . The second ∞c 0 1l1臼巴 t g叫 111 vector 昀1 s a mo∞ney demand fì.臼111比叫C叫tio∞n with cu π ency subs仗叫titu此1t io∞n [Eq. (ρ2)丸]. The cu π ency substitution bebaviour is characterized by the significance of tbe US interest rate variable in the money demand function. The third cointegrating vector is identified as tbe uncovered interest parity condition [Eq. (4月， and finally the fourtb vector can be identified as the import price function [Eq. (7)]

Table 2(b) reports the estimation results for Singapore. 甘lere are 3 cointegratiing

vectors among tbe 7 variables. The first cointegrating vector is interpreted as the

opei1 -economy IS curve, and the second cointegrating vector is identified as the

lmpo口 price equation. Fina]J y, the tbird cointegrating vector represents a money

demand function with cuηency substitution. Again, the cu汀 ency substitution

behaviour is captured by tbe significance of the US interest rate

Having estimated the cointegration relationships and the reduced-form systems [Eq

(11)] for Hong Kong and Singapore, we apply tbe identification restrictions of Eq. (15)

to recover the structural parameters and shocks in Eq. (10). Tbis enabJes us to

17 conduct the impulse response and variance decomposition analyses for the respective structural V AR models.

Figures 6-8 show the impulse responses ofreal GDP, CPI and nominal money supply variables of the two economies to one-standard-deviation of various structural shocks, respectively. Importantly, a11 structural sbocks are found to have generated persistent impacts on the two economies, although the size of the effects varies sharp!y. In addition, the magnitude of impact increases over time and is statistically significant accordi月 to the one-standard-error criterion introduced by Shapiro and Watson

(1 988). To an extent, our modified IS-LM model seems to fit the data of Hong Kong and Singapore reasonably we11, and manages to capture those external and intemal factors contributing to the macro-instabilities observed in the two economies

Most importantly, although both Hong Kong and Singapore have adopted the CBA, there are marked differences in the way the two economies respond to structural shocks. This is hardly surprising given the fact that the two economies have very different versions of CBAs. Hong Kong has adopted the exchange rate targeting whilst Singapore has opted for the monetary targeting. Specifically, the shocks in money supply are found to have generated the largest positive impacts on the GDP, price, and money demand in Hong Kong [cf. Figures 6(a), 7(a) and 8(a)] whereas the biggest positive impacts on these three macro variables in Singapore are given by the

sbock in domestic demand. In addition, wbilst the shock in domestic interest rate is

found to have generated the largest negative impacts on the same three variables in

18 Hong Kong, the foremost negative impacts on these varíables ín Singapore are attributable to the effective exchange rate shock

To examíne the relatíve ímportance of these shocks, we conduct the variance decomposition analysis on the two V AR models. Table 3 and Figures 9-11 repo口 the variance decomposition of the forecast-errors for real GDP, C肘， nominal money supply (m) and domestic interest rate (R), both ín the short-run and long-run, for the

two economies respectively.

As shown in Table 3, in the short-run the shock in the US interest rate has generated

stronger impacts on the real GDP of both economíes than the shock in domestic

ínterest rate. In addition, the US interest rate shock has larger impact on the money

supply than the shocks in the effective exchange rate and the CPI for both economíes

ln the long run, the US interest rate (Rus) is driving the domestic interest rates (R) of

the two economies, although Rus has relatively small effects on R in the short run

Again, there are marked differences in their respective shares of forecast-error

variance explained by the structural shocks in the two economies. As shown in

Figures 9(a)-11 (a), the domestic interest rate (R) shock accounts for the largest

proportion of variation in the real GDP, CPI and money supply of Hong Kong over

the long run (i.e. over 40 quarters, or 10 ye訂 s ， horizon) [cf. Table 3(a)). In contrast,

as revealed in Figures 9(b )-11 (b), there is no single dominant shock to the Singapore

economy. On the other hand, whilst the shock in effective exchange rate accounts for

most variation in money supply over the long run, the demand and import price

shocks explain most forecast-error variance of real GDP and CPI in the long run

19 Equally interesting, the results for the variance decomposition of real GDP show that demand instability in the short run (i.e. one quarter after the shock) is dominated by the demand shock itself, accounting for 85% and 95% of the total forecast-error variance in Hong Kong and Singapore respectively. In the long run, however, the interest rate shock replaces the demand shock to become the key source of output variation (71 %) in Hong Kong whereas the effecti ve exchange rate shock has become the dominant source of demand volatility (32%) in Singapore

The empirical findings seem to suggest that Hong Kong's domestic interest rate has been the main, direct source of volatility in the economy's ou中 ut growth, inflation and money supply, whilst the US interest rate has been the indirect source (through its impact on the domestic interest rate). On the con甘ary ， there has not been a single shock responsible for the macro-instability in Singapore. This finding helps to confirm that, even under the CBAs, the choice of targeting (between exchange rate and money supply) does matter on macroeconomic performance. The macro也 tability in Singapore, relative to that in Hong Kong, should to an extent reflect the effective demand management in Singapore on macro-performance. This is in turn attributable to the effective management of the Singapore do l1 ar exchange rate by the MAS (Chan and Ngiam, 1998; MAS, 2001), although it does create a trade-offbetween exchange rate and interest rate targeting for the stability ofmoney supply in Singapore

As mentioned previously, the adoption of the exchange rate peg has rendered the

Hong Kong economy subservient to the US monetary policy. Therefore, Hong Kong had to import the US interest rate that might not be appropriate to its own economic conditions. This seemed to be the case in the late 1980s and early 1990s during which

20 Hong Kong had high inf1 ation coupled with strong GDP growth after the 1989 trough

(cf. Figures 1 & 2). As interest rates in Hong Kong had to be kept in line with those in the US to keep the dollar peg intact, the already overheating demand was further boosted by an artificiaIly low interest rate (or negative real interest rate), rather than being contained by a high interest rate as is no口nally required. This led to persistent overheating demand and inf1 ationary pressure. There was virtually no effective monetary policy at all during this period

5. Conclusion

Based on a small, open-economy IS-LM framework, tbis paper examines the sources of macro-instabilities and their impacts on Hong Kong and Singapore under different versions of the cuπency board arrangements. As expected, both extemal and intemal factors combine to drive the macro-volatilities observed in the two economies

Though, the fmdings suggest that whilst the Hong Kong interest rate has been the key source of variation in the economy's real GDP, price and money supply, there has not been a single, dominant factor contributing to the instability of the same three macro­ variables in Singapore

However, the US interest rate is a common force driving the interest rates of Hong

Kong and Singapore in the long run. In the short run, the US interest rate has both direct and indirect impacts on the two economies. Due to their openness, the intemational price also affects domestic demand and prices of both economies. We also found that macroeconomic volatilities in Hong Kong and Singapore are

21 attributable to the domestic demand shock, although the relative importance is different in the two economies.

Hong Kong has been outperfonned by Singapore in achieving macro 也 tability ， and more importantly, domestic interest rate is found to have played a dominant role in driving the macro-volatilities in Hong Kong. This seems to confinn that the adoption of exchange rate peg has rendered the economy particularly vulnerable to external economic shocks, and unable to adopt an active monetary policy to fine-tune the effective demand. Worse, this could lead to importing the "wrong" monetary policy that somewhat “mismanages" the domestic demand

Finally, we found evidence suggesting that there seems to be a trade-off between exchange rate and interest rate targeting for the stability of money supply in

Singapore, although the management of the Singapore dollar exchange rate by the

MAS has been quite effective. Our findings provide a framework for future research on the financial and monetary transmission mechanisms in the twin economies of

Hong Kong and Singapore. For instance, the current linear V AR model could be extended to a nonlinear V AR model, or to a nonlinear structural model to explore the fleasibility of a quasi-target zone arrangement for the CBAs in Hong Kong and

Singapore

22 bl-a一-elU L-a E-i-U l i--?一主a.-h H h-w-bRemyPM-Me A-mm OL---叫一一z---Mn泄一比p hd JA---mke 川 h 釗Hb:11r nu--rLng Kc-CV m OB-KEFDtw r-M-mb--ln 門 a-n--*Lu-e-7TE--)e、- u---n: JL他一 e---E 的一 一 一，-1--lv-e 一一一一一一出--一 一 一)一 一一一一 -vM 一缸一一司一閃一一 --P3.一一一 一一一白日一心的叫叫-CSTI '、 - -EI--eo可 -Lh-31β1997-eM沁 hmp-0253064-ro叫叫一 4 、 J

﹒ I 1 刮 九一b h-34ll--'s-4644625-hd甘心一K 囚一一斤 一 一 一一一 一.---3933640-ne一 s1 7774123-e.n*******-us*******-HHa******-hm 圳 ..... 、 ， vu 叭

- ， 仆仆仆 V 叭 「 •• /KVH叭，口，

、 ， AA ---hu.m VH 日 「 ， Vuη-eη 1 一 -e-1.' -p) -m 一臼-5 -ch -m -hm-a -hi t *2本，. 18%u ﹒ OWH SItl 明白nu 的ca個 < 活侃 ， Tσb ， J ， ιG 過 - . n K U - 恥 巳 h 、 t l w L m n 叫 、 尸 ，'

i

Table l(b). Augmented Dicky-Fuller tests for the Singap9re variables Ho: 1(1) Ho: 1(2) Conclusion Variable name level 1st difference Rus -1.52 -4.56*** 1(1) R -1. 97 -5.30*** 1(1 ) e -1. 55 -3 .23*** 1(1 ) plm -1. 57 -4.27*** 1(1 ) y -0.31 -3.25*** 1(1) P -1.71 -3.57** 1(1) Ms -0.30 -3 .71 *** 1(1 ) Note: see Table l(a)

23 Table 2(a). Johansen cointegration tests for the Hong Kong variables Sample: 1982Q4 to 1999Q4, 69 observations Variables: Rus, R, e, pim, y, p, Ms (with 21ags) Likelihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Critical number of Value Value comtegratmg vectors 0.676425 21 1. 1277 109.99 119.80 None ** 0.509324 133.2733 82.49 90 .45 At most 1 ** 0.428040 84.14735 59.46 66.52 At most 2 ** 0.266249 45.59806 39.89 45 .58 At most 3 ** 0.236358 24 .23664 24.31 29.75 At most 4 0.076796 5.630403 12.53 16 .3 1 At most 5 0.001694 0.116956 3.84 6.51 At most 6 NB. L.R. test indicates 4 cointegrating vectors at the 1% significance level.

Un-normalized Cointegrating Coefficients Rus R e plm y- P Ms 0.019736 0.013067 1.307892 -2.360004 6.581025 1.643693 -2.557951 -0.085234 0.092551 -0.569450 0.602642 -2.022876 -1. 042576 1.048743 -0.068236 0.019216 0.578339 -1.913066 4.512603 -1. 320334 -0.626520 -0.000706 -0.026131 0.619108 0.001927 -5.953487 -2.373745 2.696745 Notes: 1)料 denotes rejection of the hypothesis at the 1% significance level 2) Test 品 sumption: No deterministic trend in the data 3) Variable definitions are given in equations (1) to (8) in the main text

Table 2(b). Johansen cointegration tests for the Singapore variables

Sample: 1980Q4ω1999Q4 ， 77 observations Variables: Rus, R, e, pim, y, p, Ms (with 2 lags) Like1ihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Critical number of Value Value comtegratmg vectors 0.634054 226.0620 134.70 143.09 None ** 0.445125 148.6563 116.14 11 1.01 At most 1 ** 0.435752 103.3023 106.07 .84.45 At most 2 ** 0.235492 59.23 816 63.12 60 .1 6 At most 3 0.200547 38.56195 39.91 41.07 At most 4 0.138142 21.32719 29.96 24.60 At most 5 0.120421 9.880024 11 .24 12.97 At most 6 NB. L.R. test indicates 3 cointegrating vectors at the 1% significance level

Un-normalized Cointegrating Coefficients: Rus R e plm y P 恥18 -0.056951 0.024658 1.460731 0.278603 3.1 39026 -10.83700 -0.64 14 -0.002934 0.071307 -1.291608 -0 .199633 0.680715 1. 321341 -0.248 3 -0.004007 0.063282 1.319057 -0.847400 -1 .339300 -1. 563160 0.8909' Note: see Table 2(a)

24 Table 3(a). Variance decomposition of real GDP, CPI and money supply of HK (in %) i) Variance Decomposition of y (log ODP)

Quarter Rus R plm y p Ms 5.059443 0.406330 2.112472 12.52434 79.89741 0.000000 0.000000 2 2.896267 4.381277 1.642363 24.15171 55.37009 0.001311 11.55698 3 2.138001 11.71339 2.4 33171 24.93141 40.94755 0.077047 17.75943 4 1.570838 27.24447 5.874587 20.52409 3 1. 13780 0.198813 13 .44940

0.685769 53 .29487 3.439162 15.99620 18 .44653 0.313196 7.824274

20 1. 011005 70.44089 2.094005 15 .49451 7.854869 0.3 32082 2.772636

40 1.751756 70.84373 1.526698 17.91363 5.985367 0.690238 1.28 8578 ii) Variance Decomposition ofp (log CPI)

Quarter Rus R e plm y p Ms 1.253277 2.850728 3.865566 20.49419 5.085460 66 .45078 0.000000 2 1.408756 3.916780 8.320667 36.34818 4.134423 45 .80257 0.06861 8 3 0.829990 4.115491 9.900667 33 .86692 8.116466 43.13263 0.037832 4 0.661402 3.164353 8.960117 36.55116 9.660913 40.97782 0.024229

0.342892 1.3 64994 5.974029 42.72232 16.69954 32.87859 0.017633

20 0.169731 25 .4 3485 3.962096 38.30213 15 .06361 17.06193 0.005662

40 0.611890 44.51179 3.203713 3 1. 94914 9.981310 9.740859 0.001294 iii) Variance Decomposition of Ms (log of nominal money supply)

Quarter Rus R e plm y p Ms 5.795056 40.71260 1. 866964 0.244712 5.147364 0.834029 45.39927 2 2.744166 35 .68402 0.902024 1.051595 14.14765 2.026589 43 .44395 3 2.050901 36.88395 1. 717256 1.984689 16.95284 3.234168 37.17620 4 1. 591936 43.71975 2.496439 3.713226 16 .51386 2.519769 29.44502

0.784071 56.50726 2.812822 11. 80720 13 .45434 0.811589 13 .82271

20 0.923285 65 .92649 2.276776 17.70526 8.878178 1.008586 3.281423

40 1.366908 67 .62357 1.978558 19.60881 6.750474 1.589805 1.081871 Note: The definition ofthe variables are given in Eq. (1) to (8) in the main text

25 Table 3(b). Variance Decomposition of real GDP, CPI and money supply of Singapore i) Variance Decomposition ofy (log GDP) Quarter Rus R e plm y p M 4.721943 0.017979 0.003503 0.168531 95.08804 0.000000 0.00000 2 6.633751 2.032656 0.1 97747 5.103046 85.92158 0.026185 0.08503 3 9.761693 3.381785 1.1 85699 8.758574 74.34036 0.207024 2.36486 4 11.1 7919 4.284018 1.637403 1l.27361 66 .63836 0.3 84241 4.60317

16.53799 3.678787 1. 733225 16.94731 5l.80963 0.3 00370 8.99268

20 25.38566 4.015148 14.64972 7.514028 4 1. 77288 0.075411 6.5 8714

40 20.57558 15 .66438 32.42846 2.176234 27.88063 0.052325 1.22238

ii) 句 V缸iance Decomposition of p (log CPI)

Quarter Rus R e plm y p M 1.721030 3.348284 0.3 14014 2.4 80782 0.375360 9 1. 76053 0.00000 2 1.1 83841 1.1 36484 0.135017 12.23834 0.828757 84 .3 0093 0.17663 5.505421 0.901246 0.091913 18.63028 2.024873 7l.06366 1. 78260 4 9.167775 1.273166 0.058836 24.27188 4.793907 56.24948 4.18495

14.05165 l.889376 0.522745 42.07133 10.92814 22 .3 6151 8.17524

20 19.26816 1. 871228 0.480310 45.12549 12.05982 8.165622 13.0293

40 25.69174 9.699075 4.552002 29.14115 16 .49729 4.869656 9.54908

iii) Variance Decomposition ofMs (log ofnominal money supply) Quarter Rus R e plm y p M 1.903806 5.237583 1. 580094 5.760247 5.967115 0.234006 79.3171 2--- 2.181538 2.985975 1. 635173 4.221531 7.385803 0.120446 81 .4695 3 4.084132 4.711463 1.070009 4.633132 6.4 87062 1.3 66464 77.6477 4 5.122572 7.814282 0.772087 4.096498 7.845 119 2.361200 7 l.9882

9.401236 2l.62632 4.958054 1.544676 16.79620 2.70 1886 42.97 16

20 12 .40409 33 .28446 24.68419 2.839856 17 .28337 1.224593 8.27943

40 10.78073 33.51900 34.04253 6.037153 13.94210 0.507304 1.1 7118 Note: see Table 3(a)

26 Fig. 1 Annual infiation rates (%) Fig. 2 GDP growth rates (%) 15 20

15 10 ~

10

' :ν、 ,-,. 、 一，、一 ，一已 • 、 1、、 -,-,' 、 、、 也﹒ ‘1 、

-5

-10 1)-10 1"""'1""" " " '1"'1"'1"""' "" "'1"' '"1"' "'1" " "' ,"', , , , w ~ M ~ M % ~ ~ % M 80 82 84 86 88 90 日 294969 8

| - Hong Kong--- Si呵apm| | - HongKong 一- Singapore|

Fig. 3(a) Interbank i n 旭 restrates (%) Fig. 3(b) US interest rate (%) 20

16

12

nu 日， 司 i -2 '4]' 。 A 日「 90 n 們 n" 。。 aon oo 的一閃­ 9 nu u羽 h u ‘ 0 崎 d u苟 三 一卅一 - - 一 - -- 1 些e 1 2月 e 」 一 - - -

Fig. 4 Nominal effective exchnage rates index (Iog) Fig.5 Real inlerest rates (%)

5.0 15

4.9 10 戶， \ 4.8 464.7 」 v h?J -5

恥 ， 4.4 -1 位三 8 0 " "'8 '2 " " '8址 '''86 ''1 的'的『位 l 的，必 98 B 2 一卅一 -s­ | 一一 Hong Kong 一- S,ngapore I

27 Fig . 6(a) Response of y (Iog Hong Kong GDP) Fig. 6(b) Response of y (Iog 8ingapore GDP) to One 8 .0 . Innovalions 10 One S.D. Innovalions

0.04 i 0.0&t

。。 m0~三ζ亡三三二三一一 。 OO~)~__二三一一一一一一一 五三三三c;::::r三了一一一-

目、

、 、 、 h k k

k 、 、 -0.0

-0 .0 -0.0 115 20 25 3040 r一-Rus 一 --e 一-- y 一- Msl |一--- . R 一-- i mo 一

Fig. 7(a) Response of p (Iog Hong Kong CPI) Fig. 7(b) Response of y (Iog Singapore CPI) 10 One S.D. Innovations 10 One S.D. Innovalions

。。 0.01

。。 。 01 戶，三一一一一-一一 ，正--~一一一 0.00 ~ i 、 ---~一-

、、 、、 、 、、

-0.0 0 日 1 115 20 25 3040 115 20 25 3040 I==~us 一 -e 一-- y 一叫 I==~us 一一。 一-- y 一-叫 一-- . R 一 --1m。一--0 -a . -. R 一 --Imo -一

Fig. 8(a) Response of Ms (Iog Hong Kong Fig. 8(b) Response of Ms (Iog Singapore Money supply) 10 One 8.0. Innovalions Money supply) 10 One S.D . Innovations 。 1 。 1

。 1

-0.1

、 、、 、、 -0.20 -0 .1 10 15 20 25 30 35 40

|三 RUS 二二 L p 二三:一可 | :1US 三二 LD 二三 f -MSI

28 Fig.9(a) Variance Decomposition of y Fig. 9(b) Variance Decomposition of y (Iog Hong Kong GDP) (Iog Slngapore GDP)

100 100

‘ 、、‘ Bnunul 80 吋

1 、、

、 n 141 60 ~\ b \

40 ~ \/ 40

20 1/ /;、 -三之L 一-一一- - 一-一-一，一 1 1 、 ~--- !'， ' 」~\一一一-一一一一一 20 區三三三三三三-- o~"7;- ， ---，--=-于一 l 一" 510 15 20 25 3040 510 15 20 25 3040 I ~~us 一 --e 一-- y 一- . Ms I I~~us 一 -e 一-- y 一-叫 一-_. R 一--， mp 一一 -p ---_. R 一，一 imp 一一-

Fig. 10(a) Variance Decomposition of p Fig. 10(b) Variance Decomposition of p (Iog Hong Kong CPI) (Iog Singapore CPI) 80 100

60 i 40 ~ \- ----­ 八一 l 、/\\ 戶亡--一---- 40 ~ 20 1'三\〈/' 、-- /" ， ;-- 、 之之~-

，一一-←一- 刁戶、、- , ι 一-一一一一一一一一-一一-一 510 15 20 25 3040 I~~us 一 -e 一 - - y 一-叫 ---_. R 一--， mp -一 -p

Fig.11 (a) Variance Decomposition of Ms Fig . 11 (b) Variance Decomposition of Ms (Iog Hong Kong Money supply) (Iog Singapore Money supply)

80 80 \ 60 \ 川、\ 叫 \

、 三三 一一一一τ戶一.::-..;~一 一三三 ­ 20 1 ，、\ -一-一-一一-一-一一一 叫 :ý:~>-/ /-- V\:>-<""三~ | '/\ 、一 ← …卜、 / \--- →一一一一一一一一一 。何寺 '1 1'"~ 10 15 20 25 30 35 40 否? 古 3b i74 日

|-- Rus ---e 一 -y 一，叫

29 References

Bernanke, Ben S, and A S Blinder (1 992) The Federal Funds Rate and the Channels

ofMonetary Transmission, American Economic Review, 82(4), 901-21

Bernanke, Ben S, and 1 Mihov (1998) Measuring Monetary Policy, Quarterly Journal

ofEconom悶， 113(3), 869-902.

Chan, K S and K J Ngiam (1 998) Currencies and the Modified Currency Board

System in Singapore, Pacific Economic Review, 3(3), 243-263

Ch凹， Edward K Y (1997) The Asian Model of Economic Development: Policy

lmplications for the 21st Century, in Asia's Challenges in the Coming Century,

Tokyo: Institute ofDeveloping Economics, 45-53

Chiang, A C (1984) Fundamental Methods of Mathematical Economics, 3rd ed, New

York: McGraw-Hill

Chou, W L and T B Lin (1 994) Hong Kong Model, in S Ichimura and Y Matsumoto

(eds), Econometric Models of Asian-Pacific Countries, Tokyo: Springer­

Verlag

Choy, Keen Meng (1 999) Sources of Macroeconomic Fluctuations in SingaJXlre

Evidence from a Structural VAR Model, Singapore Economic Review, 44(1),

74-98

Gali, J (1 992) How Well Does the IS-LM Model Fít Postwar US Data?, Quarterly

JournaloJEconomics, 107, 709-738

Ho, Lok Sang (1995) Inf1atíon: New Rísks for the Hong Kong Economy, ín S Y L

Cheung and S M H Sze (eds) Hong Kong Report, Hong Kong: The Chínese

Uníversíty Press, 183-222

Jao, Y C (1998) The Working ofthe Currency Board: the Experíence ofHong Kong,

1935-97, Pacific Economic Review, 3(3), 219-242

30 Johansen, Soren (1991) Estimation and Hypothesis-Testing of Cointegration Vectors

in Gaussian Vector Autoregressive Models, Econometrica, 59(6), 1551-1580

Kueh, Y Y (2001) The Greater China Growth Triangle in the Asian Financial Cr甘心 ， m

Shahid Jusuf, Simon Even 闕， and Weiping Wu (eds) Facets 01 Globalization

International and Local Dimensions 01 Development, Washington, DC: World

Bank, 57-77

Kueh, Y Y and Raymond C W Ng (2002) The Interplay ofthe ‘China Factor' and US

Dollar Peg in the Hong Kong Economy, China Quarterly, 170, 105-130

MAS (2001) Singapore's Exchange Rate Policy, February 2001 , Monetary Authority of

Singapore (MAS), posted on website

h句 : //www.mas.gov.s g!resource/download/ exchangePolicy . pdf

Ng, Raymond C W, and Edward K Y Chen (1 998) 甘1e Role ofMonetarγManagement

under a Linked Exchange Rate Regime: The Case ofHong Kong, in C. H

Kwan, Donna Vandenbrink, and Chia Siow Yue (eds.), Coping with Capital

Flows in East As悶， Singapore: Institute of Southeast Asian Studi 白， 136-170

Robinson, Edward and Tok Yoke Wang (2000) Overview ofthe Monetary Model of

Singapore (MMS) and Key Simulation Results, paper presented at the

Conference on Macroeconometric Modelling and Public Poli 句， 2 Feb 2000,

Monetary Authority of Singapore, posted on website

http://www.mas.gov.sg/resource/download/edward.ppt

Rogers, J H (1999) Monetary Shocks and Real Exchange Rates, Journal 01

International Economics, 49(2), 269-288

Shapiro, M and M Watson (1988) Sources of Business Cyc1 e Fluctuations, NBER

Macroeconomics Annual, 3, 111-48.

31 Siregar, R Y, and W C Wa1ker (2000) Monetary Shocks and the Fundamental

Detenninants of the Rea1 Exchange Rate under the Hong Kong Currency

Board, Asian Economic Journal, 14, 1-21

Toh, Mun Heng (1999) Exchange Rates and Domestic Prices in Singapore: An

Empirica1 Study, Singapore Economic Review, 44( 1), 99-115

Tsang, Shu-ki (1 999) A Study of the Linked Exchange Rate System and Policy Options

for Hong Kong, Hong Kong Policy Research Institute

Yip, P S L (1996) Exchange Rate Management in Singapore, in C Y Lim (ed.)

Economic Policy Management in Singapore, 237-252, Singapore: Addison­

Wes1ey

32 Centre for Asian Pacific Studies

Centre FeUows

Deoartment of Economics Deoartment ofPolitics and Sociologv

Dr. CHEUNG, Kui-yin (張鉅賢) Dr. BAEHR, Peter

Dr. FAN, Chengze Simon (范承澤) Professor BRIDGES, Brian

Professor HO, Lok-sang (何灣生 ) Dr. CHAN, Che-po (陳宮博)

Dr. L肘， Ping (林平) Dr. HARRlS. PauI

Dr. MA, Yue (馬躍) Dr. LEE, Keng-mun WilIiam ( 李經文 )

Dr. RAN, Jimmy (冉齊鳴 ) Professor LEUNG, Kit-fun Beatrice ( 梁潔芬 )

Dr. VOON, Thomas (溫演練) Dr. 旭N ， Yue (任越)

Dr. WEI, Xiangdong (魏向東) Dr. WONG, Yiu-chung (王耀宗)

Historv Programme

Dr. LAU, Chi-pang (劉智鵬)

Honorary Fellows

Dr. CHEUNG, Hoi-cheung ( 張海祥)

Dr. LU, Fei-yun (陸排云)

Dr. NG, Chi-wing Raymond ( 吳志榮 ) Centre for Public Policy Studies

Centre Fellows

Department of Economics

Dr. FAN, Cheng-ze Simon (范承澤)

Dr. LEI, Kai-cheong (李繼祥)

Dr. L肘， Ping (林平)

Dr. MA, Yue (馬躍)

Dr. VOON, Jan-piaw Thomas (溫演鑼)

Dr. WEI, Xiangdong (魏向東)

Department of Polítics and Sociology

Dr. HARRIS, Paul

Dr. LEE, Keng-mun William (李經文 )

Dr. S 凹， Oi-ling (蕭愛鈴) Working Paper Series

盟主 主盟k Author

98 (1月 0) CAPS Structural Transfonnation and Economic Growth in Dr. Hiroyuki lmai Hong Kong: Another Look at Young's “ A Tale ofTwo Cities"

99 (2/00) CAPS Corporatism and Civil Society in the People's Republic Dr. \月long Yiu-chung and of China: Empirical Evidence and Theoretical Dr. Chan Che-po lrnplications

100 (3/00) CAPS Globalization and Sino-American Economic Relations Professor C. Fred Bergsten

101 (4/00) CPPS Government Expenditures and Equilibrium Real Professor Ronald J. Balvers and Exchange Rates Dr. J effrey H. Bergstrand

102 (5/00) CPPS A Case Study ofEconomic Ecology: The Hong Kong Professor Lok-sang Ho Economy's Plunge into a Deep Recession in 1998

103 (6/00) CPPS Incentives and Corruption in Chinese Economic Refonn Dr. Chengze Simon Fan and Professor Herschel 1. Grossman

104 (7/00) CPPS Safety Climate and Employee Health Arnong B1 ue Dr. Oi-ling Siu, Dr. Ian Donald, Col1 ar W orkers in Hong Kong and China: Age and Professor David R. Phillips and Gender Differences Mr. Billy Kwok-hung She

105 (8/00) CPPS Tbe Political Economy ofHong Kong SAR's Fiscal Professor Lok-sang Ho Policy

106 (9/00) CPPS A Two-wave Trend Study of Organizational Climate Dr. Oi-ling Siu and Psychological Distress among General and Psychiatric Nurses in Hong Kong

107 (1 /01) CPPS Realistic Exchange Rates: A Post-Asian Financial Professor Lok-sang Ho Crisis Perspective

108 (2 /01) CPPS Health Care Financing and Delivery in Hong Kong Professor Lok-sang Ho What Should Be Done

109 (3 /01) CPPS The World Currency Unit: Can it Work? Professor Lok-sang Ho

110 (4/01) CPPS S 甘ategic Spin-Offs Dr. Ping Lin

111 (5 /01) CPPS Downstream R&D, Raising Rivals' Costs, and Input Dr. Samiran Banerjee and Price Contract Dr. Ping Lin

112 (6/01) CPPS Ecology and Foreign Policy: Theoretical Lessons from Dr. John Barkdull and the Literature Dr. Paul G. Harris

1 日 (7 /01) CPPS Evolving Nonns ofNorth-South Assistance: Will They Dr. Paul G. Harris and be Applied to HIV / AIDS? Dr. Patricia Siplon No. 主盟k Author

114 (8 /01) CPPS "One Country, Two Systems" in Practice: An Analysis Dr. Wong Yiu-chung of Six Cases

115 (9/01) CAPS 中國自由貿易區的構想一 WTO 框架下中國大陸與 遲福林教授 港、澳、台經貿關係展望

116 (1 0/01) CAPS Economic Refonns and Growth Prospects in India Professor Lawrence R. Klein and Dr. Thangavel Palanivel

117 (1 /02) CAPS 加入 WTO 對台灣製造業的衝擊 . 微觀分析 陳信宏博士 、 史惠慈博士

118 (2/02) CAPS 中國大陸加入世質組織對大陸經濟發展之影響 田君美博士

119 (3 /02) CAPS 入世後瓊台農業項下自由質易展望 李昌邦教授

120 (4/02) CAPS 兩岸入世賀後智慧財產權爭議解決之探討 王琇慧女士

121 (5 /02) CAPS 台灣入世銀行服務業在法規和政策上之調適 王應傑先生

122 (6/02) CAPS 加入 WTO 對台灣與大陸證券業之衝擊與因應 吳桂燕博士

123 (7/02) CAPS 兩岸工業部門國際分工程度之比較分析 吳中峻博士

124 (8/02) CAPS 兩岸入會後的金融新情勢 薛琦教授

125 (9/02) CAPS 世貿組織與貿易相關投資措施協定與跨國投資之 王泰銓教授、楊士慧女士 規定問題

126 (10/02) CAPS 中國大陸加入 WTO 後政府職能之變遷調適與挑戰 陳德昇博士

127 (11102) CPPS Competition Policy under Laissez-faireism: Market Professor Edward K. Y Power and Its Treatment in Hong Kong Chen and Dr. Ping Lin

128 (12/02) CPPS R&D in China and the lmplications for lndustrial Dr. Ping Lin Restructuring

129 (13/02) CPPS Education Refonn: An Economic Perspective Professor Lok Sang Ho

130 (14/02) CAPS Do China and Hong Kong Constitute An Optimum Dr. Yue Ma and Professor Currency Area? Shu-ki Tsang

131 (15/02) CAPS Dirty Coal: Voluntary International Environmental Paul G. Harris and Chihiro Agreements and Sustainable Development in the Udagawa People's Republic of China

132 (1 6/02) CAPS Spil1 0ver Effects of FDI on lnnovation in China: An Cheung Kui-yin and Ping Analysis ofProvincial Data Lin

133 (1 7/02) CAPS Competition Policy in East Asia: The Cases of Japan, Ping Lin People's Republic ofChina, and Hong Kong No. I盟i主 Author

134 (1103) CPPS On the Equivalence of the Noncooperative and Yue Ma Cooperative Solutions in a Two-Person Game

135 (2/03) CPPS Education Refonn in HK: The Ideal versus the Reality about Lok Sang Ho Competition

136 (3 /03) CAPS US-Japan Relations: Convergence and Divergence Brian Bridges in the Post-September 11th World

137 (4/03) CAPS The Role ofNon-judicial Mechanisms in Protecting Individual Ren Yue Rights: The China and Hong Kong Experiences

138 (5 /03) CAPS Institutional Disarticulation: The Changing Educational Anita Y.K. Poon and Govemance in Post-Handover Hong Kong W ong Yiu-cbung

139 (6/03) CPPS Tbe Effect ofTrade on Wage Inequality: The Hong Kong Case Lok Sang Ho, Xiangdong Wei 2 Gary Wai-chung Wong 140 (7/03) CPPS Structural Cbange and the Narrowing Gender Gap in Wages: C. Simon Fan and Theory and Evidence from Hong Kong Hon-Kwong Lui

141 (8 /03) CPPS Managers' Occupational Stress in China: The Role of Chang-qin Lu , Oi-Iing Siu and Self-efflcacy L. Cooper

142 (9/03) CAPS Societal Stability and Political Refonn: Chinese Politics in the Wong Yiu-chung 1990s

143 (10/03) CPPS The Nexus between Housing and the Macro Economy: Hong Lok Sang Ho and Kong as a Case Study Gary Wai-chung Wong

144 (1 1103) CAPS Yesterday's Lei Feng and Today's Young People's Liberation Che-po Chan Army Soldiers

145 (12/03) CPPS A New (and Old) Macroeconomic Policy Framework Lok Sang Ho

146 (Jan 04) CAPS The Economic Challenges for the New Cbinese Leadership Yue Ma (馬躍) and Wang Ping (王平) 147 (Feb 04) CAPS China's Domestic and lntemational Policies on Global Warming: Paul G. Harris and Explanations and Assessm 巴 nt Yu Hongyuan

148 (Mar 04) CAPS Exchange Rate Regimes and the Twin Economies of Hong Kong Yue Ma, Y.Y. Kueh and Raymo and Singapore .C.W. Ng

149 (Mar 04) CPPS Macroeconomic Instability in Hong Kong: Intemal and Extemal Yue Ma, Y.Y. Kueh and Raymo Factors C.W. Ng

A full Iist of working papers titles is also available at the centre homepages ht伊 //www.ln.edu . hklcaps and ht伊 //www . l n. edu . hk/cpps Lingnan University Library All books on loan are subject to recall after 2 weeks

Date Due 到期單 - HU 州 uuuuuu州州喇喇州州凹山叫叫山川S WH 叫刷刷刷刷刷mMMM關叫刷刷叫刷Y 附山川川M l 川川川川川 MHHMHqu州州州州州 叫叫山山川 MMMMMnU圳圳圳圳圳淵明喇喇叭也川叫神神州

UHHHH4EE 叫 HQUMMau Onu quA CH Qu7 A 吋 ， 『

香港屯門

嶺蘭大學

亞洲|太平洋研究中心 Centre for Asian Pacific Studies Lingnan University Tuen Mun, Hong l

Tel: (852) 2616 7427 Fax: (852) 2465 5786