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Zentrum für Europäische Integrationsforschung Center for European Integration Studies Rheinische Friedrich-Wilhelms-Universität Bonn Charles Goodhart, Boris Hofmann FCIs and Economic Activity: Some International Evidence B 14 2003

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Zentrum für Europäische IntegrationsforschungCenter for European Integration StudiesRheinische Friedrich-Wilhelms-Universität Bonn

Charles Goodhart, Boris Hofmann

FCIs and Economic Activity:Some International Evidence

B 142003

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FCIs and Economic Activity :

Some International Evidence*

Charles Goodharta and Boris Hofmannb aFinancial Markets Group, London School of Economics

bZentrum für Europäische Integrationsforschung, University of Bonn

ABSTRACT

A Monetary Conditions Index (MCI), a weighted average of the short-term real interest rate and the real exchange rate, is a commonly used indicator of aggregate demand conditions. In-sample evidence for the US, the euro area, Japan and the UK suggests that a Financial Conditions Index (FCI), also comprising property prices and share prices, would be a better indicator for economic activity than the standard MCI. Out-of sample the FCI also performs better than the MCI, but its overall performance is mixed. An FCI would have predicted the recent economic downturn in Japan and the UK, but not in the US and the euro area.

* We thank Ben Bernanke, Andrew Filardo, Jürgen von Hagen, Frank Smets, Bernd Hayo and participants at the the Stanford University/San Francisco Fed Conference on ‘Asset Prices, Exchange Rates, and Monetary Policy’, 2-3 March 2001 and seminars at the ZEI for helpful comments and suggestions. Correspondence: Boris Hofmann, Zentrum für Europäische Integrationsforschung, Walter-Flex-Strasse 3, 53113 Bonn, Germany, [email protected]

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1. Introduction A Monetary Conditions Index (MCI), a weighted average of the short-term interest rate and

the exchange rate, has commonly been used as a composite measure of the stance of

monetary policy. The MCI concept was pioneered by the Bank of Canada in the 1980s

(Freedman, 1995, Duguay, 1994), based on empirical findings that inflationary pressures are

determined by excess aggregate demand and that monetary policy mainly affects aggregate

demand via its leverage over short-term interest rates and the real exchange rate. In the

underlying class of models on which the MCI concept is based, the short-term real interest

rate and the real exchange rate are the main determinants of aggregate demand. The interest

rate determines internal demand conditions via its effect on the cost of borrowing and the

returns to saving, while the exchange rate determines external demand via the relative price

of tradable goods1.

Recent developments in theoretical and empirical research on the monetary transmission

process suggest that property and equity prices may also play an important role in the

transmission of monetary policy via wealth and balance sheet effects. Monetary policy can

affect property and equity prices via arbitrage effects and the expected value of future

dividends. Changes in asset prices affect economic activity via wealth and balance sheet

effects. A change in property and equity prices may affect consumers’ perceived lifetime

wealth, inducing them to change their consumption plans2. Another, more indirect wealth

effect of property and equity price movements operates via households’ and firms’ balance-

sheets. Households and firms may be borrowing constrained due to asymmetric information

in the credit market, which gives rise to adverse selection and moral hazard problems3. As a

1 Formal treatments of the theoretical underpinnings of the MCI concept can be found in Ball (1998), Gerlach and Smets (2000), and Svensson (2000). 2 See Modigliani (1971). 3 Basic references of this literature are Bernanke and Gertler (1989) and Kiyotaki and Moore (1997). For a survey see Bernanke et al. (1998).

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result, households and firms can only borrow when they offer collateral, so that their

borrowing capacity is a function of their net worth, which in turn depends on asset

valuations4.

Thus, there are good reasons to consider other potential determinants of aggregate demand

variables besides the real interest rate and the real exchange rate. This implies that an

extended MCI, a Financial Conditions Index (FCI), comprising a wider set of asset prices

and yields, may be a more useful indicator of aggregate demand conditions than the standard

MCI5. However, while there is a large empirical literature on MCIs, there are only very few

studies trying to estimate an FCI empirically6. In the following we construct MCIs and FCIs

for the four largest economic areas of the world, the US, the euro area, Japan and the UK,

using quarterly data over the period 1982-1997. The indices are derived based on coefficient

estimates from reduced form aggregate demand equations. The results suggest that that the

real interest rate and real property prices are important determinants of aggregate demand

conditions, while the exchange rate and share prices are generally not found to have a

significant effect on output. In-sample, FCIs appear to have been better indicators for the

development of economic activity than the standard MCIs. Out-of sample the FCI also

performs better than the MCI, but its overall performance is mixed. An FCI would have

predicted the recent downturn in economic activity in Japan and the UK, but not in the US

and the euro area.

The plan of the paper is as follows. In section 2 we discuss potential strategies and problems

associated with the construction of an FCI. In section 3 we estimate reduced form aggregate

demand equations. Based on these estimates we derive in Section 4 MCIs and FCIs and

evaluate their performance as indicators of economic activity. Section 5 concludes.

4 On the empirical relationship between bank lending and asset prices see Borio et al. (1994), IMF (2000), BIS (2001) and Hofmann (2001). 5 Smets (1997) generalizes the theoretical analysis of Gerlach and Smets (2000) and develops a theoretical foundation of an FCI. 6 The exception are Mayes and Virén (2001) who estimate an FCI comprising a real short-term interest rate, the real exchange rate and the change in real house and share prices for the euro area.

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2. Constructing Monetary and Financial Conditions Indices: Conceptual Issues

FCIs can be estimated based on:

- simulations in large scale macro-econometric models

- VAR impulse responses

- reduced form aggregate demand equations.

Large-scale macro-econometric models are developed by central banks, international

organisations and economic research centers to analyse the effects of economic policy

measures and all kinds of shocks. Mayes and Virén (2000) use the National Institute Global

Economic Model (NIGEM) to simulate interest rate and exchange rate shocks in order to

derive MCIs for euro area countries7. However, neither the NIGEM nor any other multi-

country macroeconometric model incorporates housing prices, so that large scale

macroeconometric models are not an option for the derivation of FCIs.

Vector Autoregressive Models (VARs) are commonly used to analyse the dynamic effects of

monetary policy shocks8. FCI weights could also be derived based on the impulse responses

of output to asset price shocks in an identified VAR. The major short-coming of such a VAR

based approach is that the practical meaning of the identified asset price shocks would not be

clear9. FCI weights derived based on VAR analysis apply to asset price and interest rate

shocks and cannot be generalised to systematic asset price and interest rate movements. Also,

the VAR impulse responses will depend on the identifying restrictions imposed on the

system, for which we do not have clear theoretical priors.

7 For an alternative set of MCI estimates for the euro area based on the Nederlandsche Bank’s EUROMON model see Peeters (1998). 8 See Sims (1980) as the basic reference and Bagliano and Favero (1997) for a more recent review of the issues. 9 The same criticism has been brought forward against the analysis of monetary policy shocks in a VAR (Rudebusch, 1998)

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The most commonly used approach to derive MCI weights is to estimate reduced form

aggregate demand equations. This approach can also be easily applied to derive FCI weights

(Mayes and Virén, 2001). However, when estimating FCI weights using reduced form

demand equations, there are several caveats which we want to address beforehand10. First, if

a reduced form model is not stable over sub-samples and if the MCI/FCI weights have wide

confidence bands, then the estimated MCIs and FCIs become unreliable. Thus, when

estimating an FCI, the assessment of statistical significance should receive sufficient

attention.

The reliability of an MCI or FCI is also impeded if the weights are model dependent. There

are various possible specifications for reduced form aggregate demand equations. In his

classical MCI paper, Duguay (1994) derives MCI weights for Canada based on an output

growth equation. For the euro area, Mayes and Viren (2000) estimate MCIs for euro area

countries by regressing the output gap on the level of the real interest rate and the level of the

real exchange rate, while Dornbusch et al. (1998) take real GDP growth as the dependent

variable. Batini and Turnbull (2000) estimate an output gap regression equation to derive

MCI weights for the UK. Ericsson et al. (1998) derive MCI weights for Canada, New

Zealand, Norway, Sweden and the US based on output growth regressions.

Reduced form regressions are exposed to the Lucas critique with particular force. Changes in

policy regime and economic structure may give rise to instability in the estimated

relationships. As a result, significant in sample evidence may be a poor guide for out of

sample prediction. Since FCIs are supposed to be indicators of future demand conditions, this

argument is of particular relevance in the following analysis. Any in sample based derivation

of MCIs and FCIs should therefore be complemented with an assessment of their out of

sample forecasting performance.

Simple backward-looking IS Curves regressions may also not be able to disentangle the

demand effects of interest rates and asset prices from their endogenous forward looking

10 For a discussion of the caveats associated with estimating and interpreting an MCI see Eika et al. (1996), Ericsson et al. (1998) and Gerlach and Smets (2000).

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component. For equity and property prices, the bias that may arise from this simultaneity will

be upwards. According to standard asset pricing theory, asset prices are equal to the

discounted sum of future returns. If future returns are positively correlated with future output,

anticipation of higher future output would lead to a rise in asset prices. Thus, a positive

correlation between output and lagged share and property prices may arise because of either

demand effects or because of forward-looking expectations in asset markets. As a result,

estimated demand effects of asset prices may be upwards biased.

For interest rates and exchange rates, on the other hand, the bias will be rather downwards. If

monetary policy is forward looking, then the endogenous component of monetary policy will

be positively correlated with future output. As a result, the estimated negative demand effect

of interest rate changes may be biased downwards. A depreciation of the effective real

exchange rate will stimulate external demand and thus have a positive effect on aggregate

demand. It may, however, also reflect expectations about a weaker economy in the future,

associated with lower returns on domestic assets relative to foreign assets. As a result, the

demand effect of exchange rate movements may also be biased downwards.

3. Asset Prices and Economic Activity

In the following we estimate MCIs and FCIs for the four major economic areas of the world,

the US, the euro area, Japan and the UK. Given the short-comings of the other two

alternative approaches and following the empirical literature on MCIs we will base our

analysis on reduced form aggregate demand equations, bearing in mind that there is also a

large range of problems associated with this approach, as we discussed in the previous

section. The estimating equations are of the form:

MCI Model:

(1) ( ) ( ) ( ) ,3211 ttttt rexLrirLyLy εβββ +++=+

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FCI Model:

(2) ( ) ( ) ( ) ( ) ( ) ( ) tttttttt rspLrhpLirLrexLrirLyLy ηββββββ +∆+∆++++=+ 6543211 .

In order to assess the robustness of our results with respect to the chosen measure of

economic activity (y), we estimate the models both for the output gap, measured as the

percent gap between real GDP and potential real GDP, where potential real GDP is

calculated using a standard Hodrick-Prescott-Filter with a smoothing parameter of 1600, and

for the quarterly change in real GDP as the dependent variable. rir is the short-term ex-post

real interest rate, calculated is the differences between the short-term nominal interest rate

and the quarterly CPI inflation rate. rex is the effective real exchange rate defined as units of

home currency per unit of foreign currency, so that a higher real effective exchange rate is a

real depreciation. rhp∆ and rsp∆ are respectively the change in real residential property

prices and real share prices. Real house price and share price indices were calculated by

deflating the nominal house and share price indices with the CPI.

Data on real GDP, consumer prices, interest rates and share prices were taken from the IMF

International Financial Statistics for the US, Japan and the UK. Aggregate euro area data

were provided by the ECB. Real effective exchange rates were taken from the OECD Main

Economic Indicators. Residential property price data for the US, the euro area, Japan and the

UK originate respectively from the US Office of Federal Housing Enterprise Oversight

(OFHEO), the ECB, the Japan Real Estate Institute and the UK Department of the

Environment.

Empirical measures of the long-term real interest rate appeared to be highly correlated with

the short-term real interest rate, introducing a severe multicollinearity problem in the

estimation and often giving rise to implausible coefficient estimates11. For this reason we do

11 This finding may be due to measurement problems. Aggregate demand depends on the ex-ante real long-term interest rate, defined as the difference between the long-term nominal interest rate and long-term inflation expectations. There is no direct measure of the ex-ante real long-term interest rate available across countries, so

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not consider the long-term real interest rate as a separate determinant of aggregate demand.

Given the high correlation between the two real interest rate measures, the short-term real

interest rate will capture the demand effects of both the short-term and long-term real interest

rate.

The equations were estimated by OLS over the sample period 1982:1-1998:412. The final

specification was chosen by a general-to-specific modelling strategy, retaining all lags of a

variable between the first and last lag significant at the 10% level, searching over up to five

lags. If no lag was significant at least at the 10% level, the lag with the highest t-statistic was

retained.

Tables 1 and 2 report the estimation results for the MCI model. Lags reports the lags retained

for each variable. If more than one lag was retained we report the sum of the coefficients of

the retained lags. Standard errors are in parentheses, elasticities which are significant at least

at the 10% level are in bold. The results suggest that the MCI model yields very poor

estimates of the demand effects of the real exchange rate. Neither the output gap nor the

output growth regressions yield a single significant exchange rate elasticity. The real interest

rate elasticities are significant in the US, the euro area and Japan, but insignificant in the

UK13.

that for empirical studies an ex-post long-term real interest rate, defined as the difference between the long-term nominal interest rate and the current level or a moving average of the inflation rate, is usually used. Batini and Turnbull (2001) find a significantly negative effect of the real yield of an indexed linked long-term bond on the output gap in the UK. Indexed linked long-term bonds are indeed likely to be a better proxy for the ex-ante long-term real interest rate than ex-post measures, but have been issued only in the UK for a period sufficiently long for time series regression analysis. 12 The sample period was chosen in order to avoid that the large increase in short-term real interest rates in the early 1980s dominates the estimation results. 13 Nelson (2001, 2002) also finds an insignificant real interest rate elasticity for the UK and refers to this finding as the IS Puzzle.

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Table 1: OLS estimates of MCI model; Dependent variable: output gap

Country (Lags)

rir rex

2R DW

USA (1-2,3,1)

-0.085 (0.041)

-0.015 (0.009)

0.88 2.32

Japan (1,1,1)

-0.158 (0.037)

0.003 (0.003)

0.79 2.25

EU (1,2,2)

-0.098 (0.044)

0.001 (0.008)

0.73 1.96

UK (1-2,4,3)

-0.021 (0.026)

0.015 (0.009)

0.88 1.95

Note: rir is the ex-post short-term real rate of interest and rex is the effective real exchange rate. ‘Lags’ indicates the lags retained of each variable. The table shows the coefficient sum of the retained lags with standard errors in parentheses. Significant elasticities are in bold.

Table 2: OLS estimates of MCI model; Dependent variable: output growth

rir rex

2R DW

USA (1-5,3,1)

-0.317 (0.182)

-0.093 (0.041)

0.42 2.11

Japan (1-3,1,1)

-0.42 (0.175)

0.011 (0.013)

0.53 2.15

EU (1-4,2,1)

-0.503 (0.194)

0.009 (0.035)

0.23 1.85

UK (1-3,4,1)

-0.028 (0.113)

0.058 (0.045)

0.3 1.96

Note: rir is the ex-post short-term real rate of interest and rex is the effective real exchange rate. ‘Lags’ indicates the lags retained of each variable. The table shows the coefficient sum of the retained lags with standard errors in parentheses. Significant elasticities are in bold.

Tables 3 and 4 report the estimation results for the FCI model. The demand effects of the real

interest rate and of the change in real property prices appear to be well identified. In each case

we find a significantly negative effect of the real interest rate and a significantly positive

effect of the change in real property prices on the output gap and on output growth. The

demand effect of the real exchange rate is still poorly identified. Only for the euro area do we

find an exchange rate elasticity which is significant at the 1% level. In all other case the

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exchange rate elasticity is not significantly different from zero. The change in real equity

prices appears to be unrelated to the output gap, but is found to have a significantly positive

effect on output growth in Japan and the UK. Table 3: OLS estimates of FCI model; Dependent variable: output gap

rir rex

rhp∆ rsp∆ 2R DW

USA (1-2,3,1,1,3)

-0.079 (0.039)

-0.01 (0.009)

0.047 (0.019)

0.005 (0.003)

0.90 2.22

Japan (1,1,1,1,4-5)

-0.185 (0.036)

0.002 (0.003)

0.041 (0.017)

-0.0002 (0.003)

0.83 2.39

Euro Area (1,2,2,3,1)

-0.091 (0.039)

0.031 (0.009)

0.054 (0.012)

-0.002 (0.002)

0.80 1.92

UK (1-2,4,3,2,4)

-0.042 (0.025)

0.012 (0.009)

0.02 (0.006)

0.002 (0.002)

0.91 2.1

Note: rir is the ex-post short-term real rate of interest, rex is the effective real exchange rate, rhp∆ is the change in real property prices and rsp∆ is the change in real share prices.’Lags’

indicates the lags retained of each variable. The table shows the coefficient sum of the retained lags with standard errors in parentheses. Significant elasticities are in bold. Table 4: OLS estimates of FCI model; Dependent variable: output growth

rir rex

rhp∆ rsp∆ 2R DW

USA (1-4,3,1-4,1,3)

-0.346 (0.174)

-0.062 (0.041)

0.29 (0.094)

0.019 (0.012)

0.53 2.07

Japan (1,1,1,3-5)

-0.575 (0.147)

0.011 (0.011)

0.245 (0.07)

0.03 (0.014)

0.66 (2.34)

Euro Area (1-4,2,1,3,2)

-0.538 (0.179)

0.10 (0.05)

0.21 (0.068)

0.013 (0.009)

0.39 1.72

UK (1-2,4,2,2,2-5)

-0.21 (0.111)

0.053 (0.042)

0.098 (0.027)

0.074 (0.025)

0.45 1.94

Note: rir is the ex-post short-term real rate of interest, rex is the effective real exchange rate, rhp∆ is the change in real property prices and rsp∆ is the change in real share prices.’Lags’

indicates the lags retained of each variable. The table shows the coefficient sum of the retained lags with standard errors in parentheses. Significant elasticities are in bold.

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In Table 5 we summarise the estimation results by reporting for each explanatory variable the

number of significant elasticities obtained from each of the estimated equations. The numbers

show that we obtain many more significant elasticities from the FCI equations than from the

MCI equations, suggesting that the FCI model does a much better job in explaining the

development of economic activity.

Table 5: The performance of the empirical models

MCI model FCI model

rir rex rir rex rhp∆ rsp∆

gap gdp∆ gap gdp∆ gap gdp∆ gap gdp∆ gap gdp∆ gap gdp∆

3 3 0 0 4 4 1 1 4 4 0 2

Note: The table displays the number of significant elasticities obtained for each explanatory variable.

4. MCIs, FCIs and the recent downturn in economic activity

Based on the estimated elasticities in the IS equation we can now derive weights for the MCIs

and FCIs. MCIs and FCIs are calculated as ( )iiti i qqw −∑ , where itq is the realisation of

variable i in period t, iq is the realisation of the FCI in a base period and iw is the relative

weight given to variable i in the FCI. We calculate the weight of variable i by dividing the

sum of the absolute value of the estimated coefficient of variable i by the sum of the absolute

value of the estimated coefficients of all variables included in the FCI.

The resulting MCI and FCI weights are displayed in Tables 6 and 7 respectively. Standard

errors of the weights are in parentheses. Except for the UK, the MCI weights are broadly

similar across the two empirical models, suggesting that the choice of the measure of

economic activity does not have a strong effect on the derived weights. The exchange rate

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does not appear to play an important role in the MCIs. The weight of the exchange rate is

insignificant in the euro area, Japan and the UK. In the US the weight is significant but results

from an implausible negative exchange rate elasticity (see Table 1).

Table 6: MCI Weights

Output Gap Model GDP Growth Model rir rex rir rex

USA 0.85 (0.05)

0.15 (0.05)

0.77 (0.06)

0.23 (0.06)

Japan 0.98 (0.02)

0.02 (0.02)

0.97 (0.03)

0.03 (0.03)

Euro Area 0.99 (0.08)

0.01 (0.08)

0.98 (0.07)

0.02 (0.07)

UK 0.58 (0.35)

0.42 (0.35)

0.32 (0.92)

0.68 (0.92)

Note: rir is the ex-post short-term real rate of interest, rex is the effective real exchange rate. MCI weights are calculated by dividing the sum of the absolute value of the estimated coefficient of a variable by the sum of the absolute value of the estimated coefficients of all variables included in the MCI. Standard errors are in parentheses.

Table 7: FCI Weights

Output Gap Model GDP Growth Model rir rex rhp∆ rsp∆ rir rex rhp∆ rsp∆ USA 0.56

(0.13) 0.07

(0.05) 0.33

(0.16) 0.04

(0.02) 0.48

(0.12) 0.09

(0.04) 0.40

(0.15) 0.03

(0.02) Japan 0.81

(0.06) 0.01

(0.01) 0.18

(0.06) 0.00

(0.01) 0.67

(0.06) 0.01

(0.01) 0.29

(0.06) 0.03

(0.02) Euro Area 0.51

(0.13) 0.17

(0.06) 0.31

(0.08) 0.01

(0.01) 0.63

(0.11) 0.12

(0.05) 0.24

(0.06) 0.01

(0.01) UK 0.56

(0.16) 0.15

(0.12) 0.26 (0.1)

0.03 (0.03)

0.48 (0.14)

0.12 (0.1)

0.23 (0.07)

0.17 (0.06)

Note: rir is the ex-post short-term real rate of interest, rex is the effective real exchange rate gap, rhp∆ is the change in real property prices and rsp∆ is the change in real share prices. FCI weights are calculated by dividing the sum of the absolute value of the estimated coefficient of a variable by the sum of the absolute value of the estimated coefficients of all variables included in the FCI. Standard errors are in parentheses.

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The FCI weights derived based on the output gap regressions and those derived based on the

output growth regression are also broadly similar, suggesting that model dependence is not a

major issue. The real interest rate gets in each case the largest weight, followed by real

property prices. The exchange rate appears to get a sizeable weight only in the euro area and

in the UK. For cross country comparisons, the weights are very similar for the US, the euro

area and the UK, while in Japan the weight of the real interest rate is larger than in the other

countries.

In Figure 1 and 2 we plot four-quarter moving averages of the MCIs (dotted line), the FCIs

(broken line) and respectively the output gap and the output growth rate (solid line). The base

period for the MCIs and the FCIs is the first quarter 1998, the first out-of-sample period. The

graphs suggest that over the in-sample period, 1982-1997, the FCI was a better leading

indicator of economic activity than the MCI. In particular, the FCIs gave much stronger

signals of weak demand prior to the economic downturn in the early 1990s than the MCIs.

A more interesting question is, of course, how the MCIs and FCIs performed out-of sample,

in particular in predicting the recent economic downturn. Figure 1 and 2 reveal that the

performance is mixed. The MCI failed to predict the slowdown in economic activity in all

four cases, while the FCI predicted the downturn in Japan and the UK, but not in the US and

the euro area. In the US, the MCI and the FCI stayed flat during the recent downturn or, in the

case of the output growth model, even signalled an economic expansion rather than a

weakening. This result is due to the high weight of house prices in the US FCI and the

surprising strength of house prices during the recent downturn. The euro area FCI, as well as

the MCI, signalled weaker economic activity only after the sharp drop in output growth in

early 2000. In Japan, the FCI signalled an economic weakening for output growth, but not for

the output gap. The Japanese MCIs stayed rather flat over this period. In the UK, the FCI

signalled weak demand both for the output gap and for output growth around two quarters

before economic activity started to slow down, while the MCIs rather signalled a slight

improvement of demand conditions in 2001.

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Figure 1: MCIs, FCIs, and Economic Activity: Output Gap

USA Euro Area

-4

-2

0

2

4

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Gap MCI FCI

-4

-3

-2

-1

0

1

2

3

4

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Gap MCI FCI

Japan UK

-4

-3

-2

-1

0

1

2

3

4

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Gap MCI FCI

-4

-2

0

2

4

-15

-10

-5

0

5

10

15

82 84 86 88 90 92 94 96 98 00

Output Gap MCI FCI

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Figure 2: MCIs, FCIs, and Economic Activity: Output Growth

USA Euro Area

-4

-2

0

2

4

6

8

10

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Growth MCI FCI

-4

-2

0

2

4

6

8

10

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Growth MCI FCI

Japan UK

-4

-2

0

2

4

6

8

10

-6

-4

-2

0

2

4

6

82 84 86 88 90 92 94 96 98 00

Output Growth MCI FCI

-4

-2

0

2

4

6

8

10

-15

-10

-5

0

5

10

15

82 84 86 88 90 92 94 96 98 00

Output Growth MCI FCI

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5. Conclusions

A Monetary Conditions Index (MCI), a weighted average of the short-term real interest rate

and the real exchange rate, is a commonly used indicator of the stance of monetary policy. In

the underlying class of models on which the MCI concept is based, the short-term real

interest rate and the real exchange rate are the main determinants of aggregate demand.

However, recent developments in theoretical and empirical research on the monetary

transmission process suggest that property and equity prices may also play an important role

in the transmission of monetary policy via wealth and balance sheet effects. This implies that

an extended MCI, a Financial Conditions Index (FCI), also comprising property and share

prices, may be a more useful composite indicator of monetary conditions than the standard

MCI.

In this paper we construct MCIs and FCIs for the four largest economic areas of the world,

the US, the euro area, Japan and the UK, using quarterly data over the period 1982-1997. The

indices are derived based on coefficient estimates from reduced form aggregate demand

equations. The results suggest that that the real interest rate and real property prices are

important determinants of aggregate demand conditions, while the exchange rate and share

prices are generally not found to have a significant effect on output. In-sample, FCIs appear

to have been better indicators for the development of economic activity than the standard

MCIs. Out-of sample the FCI also performs better than the MCI, but its overall performance

is mixed. An FCI would have predicted the recent downturn in economic activity in Japan

and the UK, but not in the US and the euro area.

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17

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Policy ChallengesIulia Traistaru, Jürgen von Hagen

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for Transition EconomiesJürgen von Hagen, Jizhong Zhou

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tan, Michael L. WyzanB28-01 Political Economy of the Nice Treaty: Rebalancing the EU

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Membership: The Convergence of Their Monetary Policy WithThat of the Europaen Central Bank

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B18-01 Monetary Policy in Unknown Territory. The European CentralBank in the Early Years

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Jan Fidrmuc

B08-01 The Functioning of Economic Policy Coordination Jürgen von Hagen, SusanneMundschenk

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2000B20-00 Breakin-up a Nation, From the Inside Etienne FarvaqueB19-00 Income Dynamics and Stability in the Transition Process, ge-

neral Reflections applied to the Czech RepublicJens Hölscher

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B17-00 Rückführung der Landwirtschaftspolitik in die Verantwortungder Mitgliedsstaaten? - Rechts- und Verfassungsfragen des Ge-meinschaftsrechts

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B16-00 The European Central Bank: Independence and Accountability Christa Randzio-Plath, TomassoPadoa-Schioppa

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B14-00 Sources of Real Exchange Rate Fluctuations in Transition Eco-nomies: The Case of Poland and Hungary

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B13-00 Back to the Future: The Growth Prospects of Transition Eco-nomies Reconsidered

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B12-00 Rechtsetzung und Rechtsangleichung als Folge der Einheitli-chen Europäischen Währung

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B11-00 A Dynamic Approach to Inflation Targeting in Transition Eco-nomies

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B10-00 The Importance of Domestic Political Institutions: Why andHow Belgium Qualified for EMU

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B09-00 Rational Institutions Yield Hysteresis Rafael Di Tella, Robert Mac-Culloch

B08-00 The Effectiveness of Self-Protection Policies for SafeguardingEmerging Market Economies from Crises

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B06-00 The Demand for Money in Austria Bernd HayoB05-00 Liberalization, Democracy and Economic Performance during

TransitionJan Fidrmuc

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B03-00 Integration, Disintegration and Trade in Europe: Evolution ofTrade Relations during the 1990’s

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B02-00 Inflation Bias and Productivity Shocks in Transition Economies:The Case of the Czech Republic

Josef C. Barda, Arthur E. King, AliM. Kutan

B01-00 Monetary Union and Fiscal Federalism Kenneth Kletzer, Jürgen von Ha-gen

1999B26-99 Skills, Labour Costs, and Vertically Differentiated Industries: A

General Equilibrium AnalysisStefan Lutz, Alessandro Turrini

B25-99 Micro and Macro Determinants of Public Support for MarketReforms in Eastern Europe

Bernd Hayo

B24-99 What Makes a Revolution? Robert MacCullochB23-99 Informal Family Insurance and the Design of the Welfare State Rafael Di Tella, Robert Mac-

CullochB22-99 Partisan Social Happiness Rafael Di Tella, Robert Mac-

CullochB21-99 The End of Moderate Inflation in Three Transition Economies? Josef C. Brada, Ali M. KutanB20-99 Subnational Government Bailouts in Germany Helmut SeitzB19-99 The Evolution of Monetary Policy in Transition Economies Ali M. Kutan, Josef C. BradaB18-99 Why are Eastern Europe’s Banks not failing when everybody

else’s are?Christian E. Weller, Bernard Mor-zuch

B17-99 Stability of Monetary Unions: Lessons from the Break-Up ofCzechoslovakia

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B16-99 Multinational Banks and Development Finance Christian E.Weller and Mark J.Scher

B15-99 Financial Crises after Financial Liberalization: Exceptional Cir-cumstances or Structural Weakness?

Christian E. Weller

B14-99 Industry Effects of Monetary Policy in Germany Bernd Hayo and Birgit UhlenbrockB13-99 Fiancial Fragility or What Went Right and What Could Go

Wrong in Central European Banking?Christian E. Weller and Jürgen vonHagen

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Mehmet Caner and Lutz Kilian

B11-99 Financial Supervision and Policy Coordination in the EMU Deutsch-Französisches Wirt-schaftspolitisches Forum

B10-99 Financial Liberalization, Multinational Banks and Credit Sup-ply: The Case of Poland

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B09-99 Monetary Policy, Parameter Uncertainty and Optimal Learning Volker WielandB08-99 The Connection between more Multinational Banks and less

Real Credit in Transition EconomiesChristian Weller

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B07-99 Comovement and Catch-up in Productivity across Sectors: Evi-dence from the OECD

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B06-99 Productivity Convergence and Economic Growth: A FrontierProduction Function Approach

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B05-99 Tumbling Giant: Germany‘s Experience with the MaastrichtFiscal Criteria

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B04-99 The Finance-Investment Link in a Transition Economy: Evi-dence for Poland from Panel Data

Christian Weller

B03-99 The Macroeconomics of Happiness Rafael Di Tella, Robert Mac-Culloch and Andrew J. Oswald

B02-99 The Consequences of Labour Market Flexibility: Panel EvidenceBased on Survey Data

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1998B16-98 Labour Market + Tax Policy in the EMU Deutsch-Französisches Wirt-

schaftspolitisches ForumB15-98 Can Taxing Foreign Competition Harm the Domestic Industry? Stefan LutzB14-98 Free Trade and Arms Races: Some Thoughts Regarding EU-

Russian TradeRafael Reuveny and John Maxwell

B13-98 Fiscal Policy and Intranational Risk-Sharing Jürgen von HagenB12-98 Price Stability and Monetary Policy Effectiveness when Nomi-

nal Interest Rates are Bounded at ZeroAthanasios Orphanides and VolkerWieland

B11A-98 Die Bewertung der "dauerhaft tragbaren öffentlichen Finanz-lage"der EU Mitgliedstaaten beim Übergang zur dritten Stufeder EWWU

Rolf Strauch

B11-98 Exchange Rate Regimes in the Transition Economies: Case Stu-dy of the Czech Republic: 1990-1997

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B10-98 Der Wettbewerb der Rechts- und politischen Systeme in derEuropäischen Union

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B09-98 U.S. Monetary Policy and Monetary Policy and the ESCB Robert L. HetzelB08-98 Money-Output Granger Causality Revisited: An Empirical Ana-

lysis of EU Countries (überarbeitete Version zum Herunterla-den)

Bernd Hayo

B07-98 Designing Voluntary Environmental Agreements in Europe: So-me Lessons from the U.S. EPA’s 33/50 Program

John W. Maxwell

B06-98 Monetary Union, Asymmetric Productivity Shocks and FiscalInsurance: an Analytical Discussion of Welfare Issues

Kenneth Kletzer

B05-98 Estimating a European Demand for Money (überarbeitete Ver-sion zum Herunterladen)

Bernd Hayo

B04-98 The EMU’s Exchange Rate Policy Deutsch-Französisches Wirt-schaftspolitisches Forum

B03-98 Central Bank Policy in a More Perfect Financial System Jürgen von Hagen / Ingo FenderB02-98 Trade with Low-Wage Countries and Wage Inequality Jaleel AhmadB01-98 Budgeting Institutions for Aggregate Fiscal Discipline Jürgen von Hagen

1997B04-97 Macroeconomic Stabilization with a Common Currency: Does

European Monetary Unification Create a Need for Fiscal Ins-urance or Federalism?

Kenneth Kletzer

B-03-97 Liberalising European Markets for Energy and Telecommunica-tions: Some Lessons from the US Electric Utility Industry

Tom Lyon / John Mayo

B02-97 Employment and EMU Deutsch-Französisches Wirt-schaftspolitisches Forum

B01-97 A Stability Pact for Europe (a Forum organized by ZEI)

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ISSN 1436 - 6053

Zentrum für Europäische IntegrationsforschungCenter for European Integration Studies

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