Discussion Papers In Economics
And Business

The Dynamic Welfare Costs of the 1997 Asian Crisis

Tatsuyoshi Miyakoshi, Masakatsu Okubo and Junji Shimada

Discussion Paper 07-25

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe Dynamic Welfare Costs of the 1997 Asian Crisis

Tatsuyoshi Miyakoshi, Masakatsu Okubo and Junji Shimada

Discussion Paper 07-25

June 2007
この研究は「大学院経済学研究科・経済学部記念事業」
基金より援助を受けた、記して感謝する。
Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe Dynamic Welfare Costs of the 1997 Asian Crisis *byTatsuyoshi Miyakoshi a , Masakatsu Okubob and Junji Shimada cabOsaka School of International Public Policy, Osaka University

Graduate School of Systems and Information Engineering,University of TsukubacSchool of Management, Aoyama Gakuin University

Abstract

This paper has measured the welfare cost, investigated the effects of and the recovery
process of the 1997 Asian crisis, and evaluated the IMF-supported programs. The paper
finds: (i) the ratios of ‘whole cost’ to the consumption level of the hypothetical economy
are large: 30% for Thailand, 50% for Indonesia, 36% for Korea, 18% for Malaysia and 39%
for Hong Kong; (ii) the dynamic process of ‘cost at period t’ quickly converges to 40%
right after the crisis, but the costs for Indonesia and Hong Kong gradually increase towards
100%; (iii) the IMF-supported programs for Thailand, Indonesia and Korea have been
implemented right after the cost hits peaks; (iv) the cost of the IMF-supported program was
not expensive compared with the corresponding welfare cost of crisis.

Keywords: dynamic welfare cost; time-varying model;1997 Asian crisis
JEL Classification Number:C32; C50; E32;E20

Correspondence: Tatsuyoshi Miyakoshi, Osaka School of International Public Policy
Osaka University,1-31, Machikaneyama-machi, Toyonaka,Osaka, 560-0043, Japan.
tel:+81-6-6850-5638; fax:+81-6-6850-5656. E-mail: miyakoshi@osipp.osaka-u.ac.jp* Earlier versions of this paper were presented at Osaka University and Hitotsubashi University in
2003, City University of Hong Kong and Tokyo University in 2004, 2004 Western Regional Science
Association Conference (in Hawaii), 2004 Western Economic Association Conference (inVancouver), 2004 East Asian Economic Association Conference (in Hong Kong). We thankKenneth S. Chan, Makoto Saito, Yum K. Kwan, Yong Wang, Eiji Ogawa, Yoshiro Tsutsui, Yuzo
Honda, Shinsuke Ikeda, Soyoung Kim, and Joshua Aizenman for useful suggestions. The firstauthor’s research was supported by Grant-in-Aid 16530204 from the Ministry of Education, Culture,
Sport, Science, and Technology of Japan.

1. Introduction
Some Asian currencies in the wake of flotation of the Thai baht in 2 July 1997 collapsed,
and the crisis spread to other countries in the Asian region. The currency crisis triggered thefinancial crisis. Thus, the Asian crisis (currency and financial crises) covered most of theEast-Asian countries by the early 1998. The Asian economies have experienced the drastic
reduction of the economic growth. In particular, to Thailand, Indonesia and Korea (called as
supported-countries by the IMF), the international organization (International Monetary
Fund, World Bank, Asian Development Bank) and the G-7 countries provided theassistance together with the program of economic reform. Diagnoses of the seriousness ofcrisis and the appropriate recovery process are important because they enable a government
to evaluate its policy effects (i.e., the IMF-supported program) and implement additional
policy if required.
Few papers for diagnoses exist. Most of them diagnose it by independently using eachmeasure of GDP, the exchange rates and the stock prices as well as previous researches. Ito(1999) and Yoo and Moon (1999) diagnosed no smooth recovery in the real economy andclaimed that the IMF programs that do not address the crux of the matter were ineffective
and costly. Berg (1999) stated that the issues of short-run stabilization receded as early as
1999. However, Cerra and Sweta (2005) found that while growth recovered fairly quickly
after the crisis, there was evidence of permanent losses in the levels of output in all thecountries. Lane et al. (1999) presented a preliminary assessment that the developments
toward recovery had been much more favorable in Thailand and Korea that had been able
to keep to the programs, but Indonesia had been still facing more difficult task in part
because of the severity of the underlying political crisis. Kho and Stulz (2000) found thenegative impact of IMF bailout announcements on the bank stock indices. In contrast, Lau
1and McInish (2003) found the positive impact on the individual bank stock returns and on
the multiple event dates. No research diagnosed the Asian crisis by using the composite
measure reflecting the change of fundamentals (GDP, exchange rates and stock prices). The
people’s welfare can reflect the changes of fundamentals through people’s consumption andthen will become one of composite measure.
A welfare measure was provided by Lucas (1987) and Obstfeld (1994). They
measured compensations that would leave consumers indifferent to a decline in economic
growth and an increase in economic instability. Miyakoshi, Okubo and Shimada (2006)
refer to both types of compensation (for the decline in economic growth and the increase ininstability) as the ‘welfare cost of stagnation’ and the model as the ‘Lucas–Obstfeld model’.
The welfare costs based on utility will equal the costs that people are willing to pay toprevent the stagnation. Then, we can evaluate whether the cost of the policy to prevent
stagnation, which a government would finance from tax revenues, is higher than the welfare
cost of stagnation. The practical use of measuring this cost has been explored by Miyakoshi,
Okubo and Shimada (2006).1 Their paper has proposed an alternative measure of costs to
the Lucas–Obstfeld model, which can evaluate: (i) whether the policy was implemented ina timely fashion, (ii) whether the policy cost was expensive compared with the cost of
stagnation, and (iii) whether the policy implemented was effective or whether an additional
policy is required. Their model is widely applicable by replacing the costs of stagnation
with the costs of crisis.
The purpose of this paper is to measure dynamically the welfare cost, investigate the1

However, Lucas and Obstfeld did not define the cost of stagnation. Rather, their concern
was with the latter compensation (the cost of the economic instability) and they did notprovide any analysis of the cost of stagnation: they only derived the formulation for the costof stagnation. This also applies to work by Dolmars (1998), Krusell and Smith (1999),
Storestetten et al. (2001), Beaudry and Pages (2001), and Pallage and Robe (2003).
2effects of and the recovery process of the 1997 Asian crisis, and evaluate the
IMF-supported programs We deploy Miyakoshi, Okubo and Shimada (2006)’s model toThailand, Indonesia, Korea, Malaysia, and Hong Kong.
The paper finds: (i) the ‘whole cost (ratios) per quarter’ of crisis are evaluated large
for all countries: 30% of the quarterly consumption in the starting period of crisis for
Thailand, 50% for Indonesia, 36% for Korea, 18% for Malaysia and 39% for Hong Kong;(ii) the dynamic process of the ‘cost (ratios) at period t’ in Thailand, Korea and Malaysia
quickly converges to 40% right after the crisis, reflecting the effectiveness of the policy; but
the cost for Indonesia and Hong Kong remain still high at now, suggesting that theadditional policy is required; (iii) the IMF-supported programs for Thailand, Indonesia andKorea have been implemented right after the cost hits peaks in each country, implying thequick program implementation; (iv) the policy cost of the IMF-supported program is not
expensive compared with the corresponding welfare cost, suggesting the agreement of the
program in each country.
This paper is organized as follows. In Section 2, we describe the Lucas-Obstfeld
Model and the alternative model proposed by the Miyakoshi,Okubo and Shimad (2006). In
Section 3, we describe the data set. In Section 4, we diagnose the 1997 Asian crisis. Section
5 concludes the paper.

2. Economic Model
Lucas-Obstfeld Model
Miyakoshi,Okubo and Shimad (2006) provide two models: the Lucas-Obstfeld Model andan alternative model. Detail derivations are given in their paper. First, we describe theformer one. The representative agent lives infinitely and maximizes an expected utility3

function V by choosing real consumption Ct at time t. The agent has preferences specified
by:

⎤
⎡∞
1
V = E ⎢∑ β t
Ct1−γ ⎥ ,1− γ⎦
⎣ t =0(1)

where β∈(0,1) is a constant discount factor and γ>0 is the constant coefficient of relativerisk aversion. Here, consider a pure exchange economy with no production, no storable
goods and no borrowing. Then, the optimal consumption Ct for an agent is subject toexogenous income It in each period and hence is equal to its income: Ct = It for all t.
Assume a class of exogenous income and hence optimal consumption streams Ct
with trend and cycle components, given by:

Ct = λ (1+ µ ) e
t

1
− σ2
2

zt ,

1
i. e., ln Ct = ln λ - σ 2 + t ⋅ ln (1+ µ ) + ln zt : ln zt ~ N (0,σ 2 )2(2)where µ is the growth rate of consumption and ln zt ~ N(0, σ2). In addition, assume that an
agent has rational expectations, which implies that an agent knows those moments, and thenis maximizing an unconditional expectation of utility (1): the subscript of time t is not
attached on V in (1). Owing to the property of the log-normal distribution, E(zt•exp(–σ2/2))= 1, the mean consumption is:E(Ct ) = λ (1+ µ )t ,(3)4

where the mean consumption at t = 0 is λ.
Thus, Lucas and Obstfeld assumed that the stagnation process of exogenous income(consumption) can be expressed by constant moments over time of the distribution of
consumption, λ, µ, and σ2, and that an agent has rational expectations.
Under the above setup, we can calculate the indirect utility given the consumption
process described by (2) and denote it by V(λ, µ, σ2|γ,β).This is derived as follows:

V (λ, µ,σ 2 | γ , β ) =1γ⎧⎫exp⎨(1− γ )(ln λ − σ 2 )⎬ if φ < 1,
(1− γ )(1− φ )
2
⎩
⎭
(4)

φ = exp{ln β + (1− γ ) ln(1+ µ)}.

We define that the period of Asian crisis outburst is the next period to the peak period
for consumption series after the third quarter of 1997 for all Asian countries, considering
the Asian currency crisis on July 2 1997. We partition the whole sample (1990:Q1 to
2004:Q3) into two sub-samples by the outburst of the Asian crisis: the crisis periods
including the crisis outburst and the pre-crisis periods excluding it.
We consider two economies. One is called the crisis economy in which consumption
growth µ C and its variance σC2 are calculated based on the data in the crisis periods. We
denote the resulting indirect utility as V( λ C , µ C , σ C2 | γ , β ) . The other is called the
hypothetical economy (i.e., the economy without crisis), which is based on expectedconsumption under the assumption that the growth rate and variance in the pre-crisis period
are maintained during the crisis periods. The resulting indirect utilityis V( λ H , µ H , σ H2 | γ , β ) . The intuition behind this comparison is shown in Figure 1.
Owing to (3), the λH is mean consumption at the beginning of the crisis period for the5hypothetical economy. However, in actual, the consumption falls gradually during several
periods after the crisis outburst, as denoted by dot line. We replace the dot line by a solidline for analytical convenience. Thus, we compare both economies depicted by the solidlines in the crisis periods. Although γ and β differ between both economies, we assume thatthey remain constant over time at ( γ , β ) .

[INSERT Figure 1]

We define the ‘whole cost’ of crisis as follows.

Definition 1. The ‘whole cost of crisis’ is given by λ*, which satisfies the following
equation:

V (λC + λ*,µC , σ C2 | γ , β ) = V (λH , µ H ,σ H2 | γ , β ) ,(5)where the subscripts C and H denote the crisis and hypothetical economy, respectively.
The key concept relating to the ‘whole cost’ of crisis is the following. The consumption
parameters are different between the crisis (C-ECO) and the hypothetical economies(H-ECO). Consumer preferences, given by ( γ , β ) , transform the difference in
consumption parameters into a difference in utility levels. The ‘whole cost’ of crisis ismeasured by the compensation, uniform across all periods, required to leave consumers’
utility indifferent between two economies. The ‘whole cost’ implies the cost from the
beginning of the crisis to the future.
The calculation of the cost λ* is given by:6λ* = exp{Ψ} − λC ,
Ψ=⎫1 ⎧ 1- φC
2
2
ln
(
)
+
(1
−
γ
)(
ln
λ
−
γ
σ
/2)
⎨
⎬ + γσ C /2 ,HH
1 − γ ⎩ 1- φH
⎭

(6)

where

φC = exp{ln β + (1− γ ) ln(1+ µC )} and φH = exp{ln β + (1− γ ) ln(1+ µ H )}.

An Alternative Model: The Dynamic Welfare Cost
Assume that the crisis economy for consumption can be expressed by the time-varying
intercept and slope as follows:

lnCt = at + bt ⋅ t + ln zt :ln zt ~ N (0,σ 2 )1at ≡ ln λt − σ 2 ; bt ≡ ln(1+ µt )2
⎡a t ⎤ ⎡α0 ⎤ ⎡α1 0 ⎤ ⎡a t−1 ⎤ ⎡ηa,t ⎤⎢ ⎥= ⎢ ⎥+ ⎢⎥ ⎢b ⎥ + ⎢η ⎥ :bβ
0β⎢⎣ t ⎥⎦ ⎣ 0 ⎦ ⎣ 1 ⎦ ⎢⎣ t −1 ⎥⎦ ⎢⎣ b, t ⎥⎦(7)⎛⎛ 0⎞ ⎡qa2 0 ⎤ ⎞⎡ηa,t ⎤⎢ ⎥~ N⎜⎜⎜⎜ ⎟⎟, ⎢ 2 ⎥ ⎟⎟ t=0,1,2,…
⎢⎣ηb,t ⎥⎦⎝⎝ 0⎠ ⎢⎣0 qb ⎥⎦ ⎠We assume that an agent has myopic rational expectations, which implies that an
agent knows the moments of the distribution of only today t’s consumption parameters, σ2,at (λt) and bt (µt ). Moreover, an agent expects (or believes) these moments of today t tocontinue forever for future consumption. Thus, based on today t’s information, an agent
obtains the conditional moments for today t and for future consumption (i.e., for the crisis
economy). The indirect utility function of (4) conditioned on today t’s information includes
the subscript of time t.

7

Vt (λt , µt ,σ 2 | γ , β ) =1γ ⎫⎧exp⎨(1− γ )(lnλt − σ 2 )⎬ if φt < 1,(1−γ )(1−φt ) ⎩2 ⎭(8)

φt = exp{lnβ + (1−γ ) ln(1+ µt )}.

At period t, an agent gets these parameters and computes indirect utility from periodt to the future, based on the coming information at period t. Here, we compare this ‘indirect
utility at period t’ with the ‘indirect utility at period t’ for the hypothetical economy
mentioned in the Lucas-Obstfeld model. The ‘cost at period t’ of crisis is given by λt*,which satisfies the following equation:

Vt (λC,t + λ∗t , µC, t , σ C2 | γ , β ) = Vt (λH ,t , µ H ,σ H2 | γ , β ) ,(9)where the subscripts C and H denote the crisis and hypothetical economy, respectively. The
parameters for the crisis economy are changed period by period, whereas the parameters forthe hypothetical economy are the same and constant over each period, as in the
Lucas-Obstfeld model. The λH,t is the exception, because it is an intercept of consumption
and it changes at period t.
Then, an agent re-computes the ‘cost at period t’ of crisis period by period, based on
the updated information.

8

λ∗t = exp{Ψt } − λC, t ,Ψt =⎫1 ⎧ 1- φC, t
2
2
,
ln
(
)
+
(1
−
γ
)(
ln
λ
−
γ
σ
/2)
⎨
⎬ + γσ C /2
H ,tH
1 − γ ⎩ 1- φH
⎭

(10)

where

φC, t = exp{ln β + (1− γ ) ln(1+ µC, t )} and φH = exp{ln β + (1− γ ) ln(1+ µ H )}Keeping the variance constant in the crisis period but letting the consumption intercept andgrowth fluctuate, the agent recomputes the ‘cost at period t’ of crisis, relative to the
hypothetical economy. The ‘cost at period t’ measures the cost from period to future andhence is different period by period.
Figure 2 is a schematic diagram that describes this idea, which summarizes ouralternative model. An agent knows only the present period (T1)’s intercept λC,T1 and slopeµC,T1 in (7) from information at period T1, expects these parameters λC,T1 and µC,T1 willcontinue forever. On this basis, the agent constructs the crisis economy from period t to the
future. Thus, the crisis economies expected from period T1 to the future and from period T2
to the future will be different each other and the costs at T1 and T2 will be also different
period by period. The ‘cost at period t’ calculated in this way may be literally called adynamic cost of crisis, in contrast to a ‘whole cost’ computed from the beginning of crisisto the future by the Lucas-Obstfeld model. In general, the cost at period t will be higher at
the start and lower at the end of the crisis period.

[INSERT Figure 2]

9By using a ‘cost at period t’, we can evaluate: (i) whether the policy was
implemented immediately in the period when the highest welfare cost arose, (ii) whether
the cost of the implemented policies was expensive compared with the welfare costs ofstagnation, and (iii) whether the cost of stagnation decreased gradually—that is, whether
the policies were effective—or whether additional policies are required, which will be
ascertained by determining the current welfare costs. These specific exercises cannot be
undertaken under the existing frameworks, including under the Lucas–Obstfeld model.
Although an alternative model can compute the cost period by period, how can it
derive the whole cost of crisis that occurred in an era? We may consider the ‘cost at theperiod t’ as the ‘whole cost’ of crisis. However, as an agent has myopic rational
expectations about the crisis economy expressed by time-varying parameters, he or shecannot predict the future economy. Thus, the ‘cost at the starting period’ of the crisis cannot
correctly capture the ‘whole cost’ from the starting period to the future. On the other hand,
it is a very bold and implausible assumption that an agent has rational but not myopic
rational expectations of the crisis economy expressed by time-varying parameters.
Moreover, it is technically difficult to derive the ‘whole cost’ and the ‘cost at period t’ by
applying the Lucas–Obstfeld model to an economy expressed by constant parameters. Thus,
the two cost measures are derived based on the two different conceptions of the crisis
economy. However, we propose a compromise. If we value a long-run viewpoint, it isnatural to assume a stagnation economy with constant growth over time and instability. In
contrast, if we value a short-run viewpoint, the assumption of a crisis economy with
time-varying parameters is more natural. In this sense, when we value the long-run
viewpoint and evaluate the ‘whole cost’ of crisis that has occurred in an era, theLucas–Obstfeld measure may be appropriate.

10

To calculate the costs of crisis in Lucas- Obstfeld model, we proceed as follows.
First, by using data for each sub-sample (the pre-crisis or the crisis period), we estimate theparameters (λ,µ, σ2) for each economy and then use the preference parameters ( γ , β )employed by Pallage and Robe(2003). These parameter estimates are reported in Table 1.
Second, we measure the costs of crisis, which are reported in Table 2. Third, we calculatethese costs for varying values of the parameters ( γ , β ) to do the robustness check.
These results are reported in Table 3.

3. Data and the 1997 Asian Crisis
The data used in this paper are quarterly data mostly from the first quarter 1990 to the third
quarter 2004 (i.e., 1990:Q1 to 2004:Q3), which gives 59 observations but changes
depending on the data availability for each country: Thailand, Indonesia, Korea, Malaysia,
and Hong Kong. To estimate the parameters (λ, µ, σ2) for consumption in the model, we use
total consumption expenditure for households (line 96f, measured in national currency)from the International Financial Statistics (IFS).2 The per capita series is constructed by
dividing consumption expenditure by the number of population (line 99z).3 These data areconverted to real values by using the consumer price index (line 64, for general prices in2000): the money unit is a Baht for Thailand, a Rupiah for Indonesia, a Won for Korea, a
Ringgit for Malaysia and a Hong Kong Dollar for Hong Kong. For the preference2

The consumption series is non-seasonally adjusted. It is seemingly important to delete theseasonal effects, while the sample size is small for all countries and then the seasonal
adjustment reduce the sample size. In addition, for each country, we compare thenon-seasonal adjusted data between both consumption paradigms. Then, the seasonal
adjustment or non-adjustment is not so important.
3
The data for population is on annual base, and then we assign the increase of the annual
data to the quarterly data at a constant growth rate.
11

parameters ( γ , β ) employed by Pallage and Robe(2003), we calibrate the model.
Figure 3 plots consumption in logs for each country, which suggests a drop in the logof consumption (which reduces consumption growth) around 1997:Q3. The crisis outburst
is 1997:Q3 for Thailand, 1998:Q1 for Indonesia, 1997:Q4 for Korea, 1998:Q1 for Malaysia
and 1998:Q1 for Hong Kong. Our objective is to estimate the cost of the Asian crisis during
the crisis period by comparing it with the hypothetical economy. This specification of thecrisis outburst seems appropriate, and consistent with previous research, including Corsetti,
Pesenti and Roubini (1999a,b). Therefore, we do not implement a formal test for structuralchange between two sub-periods.

[INSERT Figure 3]

4. Estimation Results and Discussion for Costs
Lucas-Obstfeld Model
The parameters for consumption in a pre-crisis period and a crisis period are estimatedby applying a Maximum Likelihood methodology to the whole sample:

1
lnCt = ln(λH (1− DUt ) + λC DUt ) - (σH2 (1− DUt ) +σC2 DUt )2+ t ⋅ ln(1+ µH (1− DUt ) + µC DUt ) + lnzt :lnzt ~ N(0,σ (1− DUt ) +σ DUt )
2
H

(11)

2
C

where DUt=1 if t≥TB (that is, TB=crisis outburst period) and 0 otherwise. In Table 1, theparameters in both the pre-crisis and the crisis periods are estimated and denoted as theestimated parameters for the hypothetical economy and the crisis economy. An agent
12perceives that the estimated parameters in both periods are the consumption parameters forboth economies. All parameter estimates for consumption are obviously significant at the
1% level (not shown in Table 1). 4 All the null hypotheses of H1: λH=λ C ;H2: μH =μC ;H3:
σ2H =σ C 2 are rejected except for Malaysia (μ) and Hong Kong (σ2). That is, the differencein consumption growth and variance between both economies is statistically significant at
the 5% level. In Thailand, the estimated quarterly consumption growth rate falls from
1.30% in the hypothetical economy to 1.06%. The variance of the error term in the log of
consumption decreases from 0.0009 to 0.0002. The estimate of initial consumption at
1997:Q3 is 13,202 baht for the hypothetical economy and the one at 1997:Q3 for the crisis
economy is 10,085 baht. The initial consumption of the crisis economy drastically dropped.
These imply the drop of λH and λC in equations (5) and (6). See Figure 3. The instability ofσ2 reduces in the crisis periods except for Korea. This result will be due to the policy effectsof each country.

[INSERT Table 1]

How much is the estimated ‘whole cost’ of crisis according to the model? As
explained in Section 3, to measure these costs, we use the same preference parameters as
Pallage and Robe (2003) does. For both economies, we use 0.98 as a base value for β ofquarterly data, since they use 0.96 as a typical discount factor of annual data for developing
countries. We also use the moderate risk-aversion level at γ=2.5.
As Table 2 shows, by using these parameters in equation (4), for Thailand, we obtain autility level of –1.698E (–05) for the hypothetical economy (H-ECO) and one of –1.861E

4The data for dotted line in Figure 1 are omitted for estimation.
13

(–05) for the crisis economy (C-ECO). This implies that crisis reduces utility. Our costmeasure λ* enables us to convert the reduction in the utility level into a level ofcompensation in national currency. The cost of crisis is 3,948 baht. In general, it is difficult
to identify whether the cost is large or small. However, this amount is 30% of the initiallevel of consumption λH (13,202baht). This ratio 30% is easy to identify the large, whichshows the relative amounts and hence an actual impact. These ratios are large for all
countries: 30% for Thailand, 50% for Indonesia, 36% for Korea, 18% for Malaysia and
39% for Hong Kong.

[INSERT Table 2]

Which country paid the higher costs than other countries? Considering the ratios of thecost /λH, the supported-countries by the IMF (Thailand, Indonesia and Korea) burdened
larger costs: in particular, the ratio for Indonesia is the highest,50%. However, the one of
Malaysia is the lowest, 18% and about one-third of that of Indonesia. These findings are
similar to those of the previous papers in a qualitative sense, while our paper is different inthat we provide the money measures in a quantitative sense and a people’s welfare point ofview by using the welfare costs. Then, the advantage of our model can reveal how muchpeople could pay the costs to prevent the crisis, which should be equal or less than thiswelfare cost, and can compare seriousness in people’s mind of defects among countries. We
will have to investigate the causes for the different costs between Indonesia and Malaysia in
future.
To check the robustness of the results, we calibrate the preference parameters in (1).
We use γ = 2.0, 2.5, 5.0 and β = 0.97, 0.98, 0.99, which encompass the range of parametervalues used in previous research (see, e.g., Pallage and Robe, 2003). Note here that γ>014implies risk aversion. In Table 3, for Thailand, the ratio of costs /λH ranges from 28% to
35% at β =0.99 as γ decreases and from 26% to 28% at γ=5, as the theoretical analysis with
µH>µC are shown in Miyakoshi, Okubo and Shimada (2006).5 Varying the parameters, themaximum is 35% and the minimum is 26%. The minimum ratio is still large than 26%,
compared with the ratio 30% at γ=2.5 and β =0.98 in Table 2. The ratios are robustly larger
for the other countries. In particular, the ratios for the IMF-supported countries (i.e.,
Thailand, Indonesia and Korea) are larger than 35% at base values. In addition, the evenminimum ratio 19% of Indonesia and 25% of Korea is larger than the maximum ratio
18.1% of Malaysia.

[INSERT Table 3]

An Alternative Model : Dynamics of Welfare Costs
The estimation results for α0, α1, β0, β1 and other parameters in model (7) by the
Kalman filter algorithm for the time varying parameter model are obtained. The estimation
results are shown in Table 4. 6 Moreover, the estimated a t and b t over time, actual values
log C t and the estimated a t+ t⋅b t values over time are shown in Figure 4 and Figure 5. Byusing the estimated parameters for Thailand in Table 4, the estimated parameters over time
are a t =1.9342+0.7901 a t-1 and b t=0.0026+0.7434 b t-1 , where all estimated parameters are
significant at the 5% level. However, the dynamics of parameters converge to lim t→∞a t=1.9342/(1-0.7901)=9.21 and lim t→∞b t =0.0026/(1-0.7434)=0.01. Also, the dynamic

5

Also, the theoretical analysis with µH<µC in Miyakoshi, Okubo and Shimada (2006)shows ∂λ∗ / ∂β <0 and ∂λ∗ / ∂γ >0, which is confirmed in the findings for Malaysia.
6
A formal test of qa(b) = 0 involves nonstandard statistics, and hence the associated t-value
are meaningless.
15

process of those parameters are shown in Figure 4, and thus the time-varying parameter
estimates with the growth component and with the intercept component can capture theactual values of consumption, as seen in Figure 5. On period T1 seen in Figure 3, an agent
can know the moments of distribution of the consumption process on period T1, that is, a2
T1(=lnλ T1-σ /2) , b T1(=ln(µT1+1) ) and σ in (6), and expect these parameters to continue

forever (i.e., constant forever), and computes the cost on this basis. But at period T1+1, theagent recomputes a different cost, based on the actual values of a T1+1 , b T1+1 and σ on period
T1+1.

[INSERT Table 4, Figure 4 and Figure 5]

As seen in Figure 4, the estimated growth parameter µCT(=exp(b T)-1) and the intercept
component of consumption λCT (=exp(a T+σ2 /2)) for the crisis economy are respectively
less than those of the hypothetical economy in all periods, which induce the higher cost ofcrisis. On the other hand, the finding that the instability σ2(=0.0153x0.0153 in Table 4) of
the crisis economy for Thailand is smaller than that of the hypothetical economy σ2(=0.0009 at H-ECO in Table 1) induce the lower cost.
We should compute the ‘cost at each period t ‘ by applying equation (10). As seen in
Figure 6, the dynamic cost ratio for Thailand (IMF-supported country as well as Korea andIndonesia), i.e., the cost at period T / (λHT on period T for the hypothetical economy), hit
uncountable-high cost in 1997Q3-1998Q1 (not shown in Figure 6 and due to φA>1) but
immediately decreases to 53% in 1999Q3 and now converges to 50%. For Korea, the cost
hits uncountable-high in 1997Q3 for only one period, but disappears at 1% in 1998Q3 oneyear after. However, after then, the cost increases gradually and stags at 40%. In this sense,16the IMF-supported program to rescue these countries seems to have been effective. The costfor Indonesia did not hit the high level right after the crisis outbursts, while the cost did notshow a sign of decreases and approaches to 100%, suggesting the IMF-supported program
is not effective in this country. For Malaysia which is not a IMF-supported country (rather,refused a supported program), the cost is high right after the crisis outburst but rapidly drop
down at 46% in 1999Q1 and decreasing more. The decrease suggests that its own policy,i.e., the capital control, was effective.7 Finally, the cost of Hong Kong is not high rightafter the crisis outburst, but after then increases gradually and hits 60% in 2004Q3, showing
no confirmed sigh of decreases. Now, in 2004Q3, the cost is still more than 40% for all
countries, which needs more additional policy implementation.

[INSERT Figure 6]

Next, we investigate whether the policy (IMF-supported program) was implemented
immediately at the period that the highest cost arose. The peak cost at more than 500%
continues during 1997Q3-1998Q1 for Thailand and only in 1997Q4 for Korea, i.e., rightafter the crisis outburst. However, the costs for Indonesia increase in gradually creeping,requesting the additional programs. Table 5 shows that the IMF-supported program starts
right after the crisis occurs in all three countries. In this sense, the IMF-supported programfor each country was implemented right after the crisis outburst.
Whether was the cost of the IMF-supported program implemented expensive in

7

Malaysia more strictly controlled the stock markets to prevent the speculative attacks
during the crisis than the pre-crisis period. In fact, in 1998, Malaysia imposed a range of
foreign exchange and capital controls that substantially insulated Malaysian financial
markets from external influences and effectively closed down the offshore ringgit market.
See IMF (1999, pp.180-185) in detail.
17

comparison with the size of the welfare costs? That is, if an SDR 2.9 billion Stand-By
Arrangement for Thailand approved by the IMF (seen in Table 5) could rescue the Thai
economy immediately (i.e., maintain its hypothetical economy), would people agree to pay
this policy cost?. In 1998Q2 of Figure 6, the welfare cost is paid, 37,926 bath (276%) per
quarter forever. If the policy cost of SDR 2.9 billion in Table 6 can maintain the
hypothetical economy, how many quarters should people pay 37,926 bath per quarter tofinance SDR 2.9billion ? That is, (Policy costs /people’s number on 1998Q2) /How many
months?=the welfare cost, and then, (SDR 2.9billion X 56.34 baht /0.05923 billion people)/37,926 baht per quarter =0.07 quarters8. It is very short period compared with forever,meaning the policy cost is cheap and people will agree to pay the policy cost. For Indonesia,
in 1998Q1, the welfare cost is 111,138 rupiah (11%) and the policy cost is SDR 7.3 billion.
(SDR 7.3billion X 11121 rupiah /0.20304 billion people) /111,138 baht per quarter =3.6
quarters. Similarly, for Korea, in 1998Q1, the period for people to pay is, (15.5billion SDR
X 1847.54 won /0.04581 billion people) /1,223,880 won per quarter =0.51 quarters. The
period for people to pay the policy cost is at most 3.6 quarters for three countries. It is avery short period, compared with the ‘forever‘, since the welfare cost is paid ‘forever’. In
this sense, the policy cost of the IMF-supported program seems to be cheap.

5. Concluding Remarks

This paper has measured dynamically the welfare cost, investigated the effects of and therecovery process of the 1997 Asian crisis, and evaluated the IMF-supported programs for
Thailand, Indonesia, Korea, Malaysia, and Hong Kong, by deploying Miyakoshi, Okubo

8

The data for exchange rate per SDR is complied from IFS(line aa.zf).
18

and Shimada (2006)’s model.
The paper finds: (i) the ratios of ‘whole cost’ to the consumption level of the
hypothetical economy are large for all countries: 30% for Thailand, 50% for Indonesia,
36% for Korea, 17.7% for Malaysia and 39% for Hong Kong; (ii) the dynamic process ofthe ‘costs at period t’ in Thailand, Korea and Malaysia converge to around 40% right after
the crisis, reflecting the effectiveness of the policy. However, the costs for Indonesia andHong Kong increase gradually toward 100%, suggesting that the additional policy isrequired; (iii) the IMF-supported programs for Thailand, Indonesia and Korea have been
implemented right after the cost hits peaks in each country, implying the quick
implementation of the program; (iv) the policy cost of the IMF-program is not expensive
compared with the corresponding welfare cost, suggesting that the program in each
IMF-supported country will be agreed.
The findings of the paper support the previous qualitative analysis with the 1997 Asiancrisis. However, the results of this paper are different in that we first provide the money
measures in a quantitative sense, a people’s welfare point of view by using the welfare costs,
and the dynamics inspection.

19

References
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unemployment insurance”, European Economic Review 45:1545–1572.
Berg, A. (1999),” The Asia Crisis - Causes, Policy Responses and Outcomes ”, IMF
Working Paper No. 99/138.
Cerra,V. and Saxena, S.C. (2005), “Did Output Recover from the Asian Crisis?” IMF Staff
Papers 52:1-23
Corsetti,G., Pesenti,P. and Roubini,N.(1999a),”Paper tigers?: A model of the Asian crisis”,
European Economic Review 43:1211–1236.
Corsetti,G., Pesenti,P. and Roubini,N.(1999b),” What caused the Asian currency andfinancial crisis?”, Japan and the World Economy11:305-373.
Dolmars, J.(1998), “Risk preferences and the welfare cost of businesscycles”, Review of Economic Dynamics 1:646–676.
IMF(1999), The Annual Report 1999, International Monetary Fund.
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Lane, T. etc.(1999),”IMF-Supported Programs in Indonesia, Korea, and Thailand: A
Preliminary Assessment”, IMF Occasional Paper No.178.
Lau, S-T. and McInish, T. (2003),”IMF Bailouts, Contagion Effects, and Bank Security
Reurns”, International Review of Financial Analysis 12:3-23.
Lucas, R.E. (1987), Models of Business Cycles, Blackwell, Oxford.
Lucas, R.E. (2003), “Macroeconomic priorities”, American Economic Review :1–14.
Kho, B-C. and Stulz, R. M. (2000),”Banks, the IMF, and the Asian crisis”, Pacific-Basin
Finance Journal 8:135-275.
Miyakoshi,T. ,Okubo,M.and Shimada,J.(2006),” An Alternative Measure to Lucas-Obstfeld
20Model:Dynamic Welfare Cost of Stagnation”, mimeo, March 2006
Obstfeld,M.(1994),”Evaluating risky consumption paths: The role of intertemporal
substitutability”, European Economic Review 38:1471–1486.
Pallage, S. and Robe, M.A. (2003), “On the welfare cost of economic fluctuations indeveloping countries”, International Economic Review 44: 677–698.
Saito, M.(1996), A New Macroeconomics (in Japanese), Yuhikaku, Tokyo.
Storestetten, K., Telmer, C.I. and Yaron, A. (2001), “The welfare cost of business cycles
revisited: Finite lives and cyclical variation in idiosyncratic risk”, European
Economic Review 45:1311–1339.
Yoo, J-H. and Moon, C. W. (1999),”Korean financial crisis during 1997–1998 Causes andChallenges”, Journal of Asian Economics 10:263-277.

21

Table 1. Estimated Parameters for Consumption
CountryλCrisisσ2

μH1:χ2(1) H2:χ2(1)λH=λCμH =μCH3: χ2(1)σ2H =σ2C

Thailand
H-ECO
97Q3
13,2020.0130 0.0009 331.47
6.30
5.56
C-ECO
97Q3
10,0850.0106 0.0002
Indonesia
H-ECO
98Q1
965,6160.0193 0.0052 6.13
406.29
12.42
C-ECO
98Q1
996,3170.0033 0.0002
Korea
H-ECO
97Q4
1,665,633
0.0211 0.0003 512.34
234.44
10.19
C-ECO
97Q4
1,393,492
0.0129 0.0022
Malaysia
H-ECO
98Q1
1,698
0.0103 0.0028 67.39
0.08
4.36
C-ECO
98Q1
1,375
0.0107 0.0010
Hong-Kong
H-ECO
98Q1
31,3530.0069 0.0013 59.28
38.99
0.50
C-ECO
98Q1
27,2290.0009 0.0010
Notes: H-ECO and C-ECO denote the hypothetical and the crisis economy. The value of lambda ismeasured in national currency. The critical value of χ2(1) distribution is 3.84 at 5% level.

Table 2. Welfare Costs of the Crisis (γ=2.5, β=0.98)
Country

Indirect Utility
H-ECO

C-ECO

Welfare Costs
Level λ*Ratio (λ*/λH) %Thailand-1.698E(-05) -1.861E(-05)

3,948

30

Indonesia-1.418E(-08) -2.699E(-08)

487,22950

Korea-8.069E(-09) -1.052E(-08)

594,993

36

Malaysia-3.760E(-04) -3.687E(-04)

301

18

Hong Kong-4.946E(-06) -6.969E(-06)

12,18639

Notes: The cost is measured in national currency. E(-0X) denotes 10-X . See notes of Table 1.

22

Table 3. Welfare Costs of the Crisis based on Various Preference Parameters
Country
β
γ
0.97
0.98
0.99
Thailand
2
29%
31%
35%
2.5
28%
30%
32%
5
26%
27%
28%
Indonesia
2
42%
62%
113%
2.5
36%
50%
83%
5
19%
25%
33%
Korea
2
35%
41%
35%
2.5
32%
36%
32%
5
25%
26%
25%
Malaysia
2
17.9%
17.6%
17.0%
2.5
18.0%
17.7%
17.3%
5
18.1%
18.0%
17.9%
Hong Kong
2
32%
41%
67%
2.5
31%
39%
60%
5
27%
32%
42%
Notes: The shaded number is the one at γ=2.5 and β=0.98 in Table 2. In particular, the number for
Malaysia is denoted to one place of decimals.

Table 4. Estimated Parameters in (6)ThailandIndonesia
Korea
Malasia
HongKong

σ

α0

α1

qa

β0

β1

qb

Est.

0.0153

1.93420.79010.00000.00260.74340.0000t-value[8.89][5.91][22.45][0.42][4.59][21.06][1.13]

Est.

0.01071.86050.86560.00000.00050.73630.0003t-value[1.64][0.64][4.10][0.09][0.53][3.22][0.23]

Est.

0.0160-0.1153

0.99940.00000.03320.73490.0011t-value[3.12][-2.96] [226.07][1.76][3.16][24.67][5.12]

Est.

0.0231

4.99210.31050.01730.00340.64520.0000t-value[2.87][4.18][1.89][2.00][6.35][14.66][0.14]

Est.
t-value0.0239[4.02]

0.8780[4.42]

0.9145[46.55]0.0000[0.67]-0.0006[-0.41]0.4946[3.26]

0.0008[2.98]

23

Table 5. IMF Supported Program Right After the Crisis: Date and Finance
Thailand
1997:August 20 The Board approves an SDR 2.9 billion Stand-By Arrangement for Thailand andreleases a disbursement of SDR 1.2 billion.
October 17 The Board reviews the Stand-By Arrangement under the Emergency Financing
Mechanism procedures.
November 25 Thailand issues a Letter of Intent detailing additional measures.
December 8 The Board completes the first review under the Stand-By Arrangement anddisburses SDR 600 million.
1998:February 24 Thailand issues a Letter of Intent describing further measures.

Indonesia
1997:November 5 The Executive Board approves a Stand-By Arrangement for Indonesia
authorizing drawings of up to SDR 7.3 billion, and disburses SDR 2.2 billion.
1998:January 15 Indonesia issues Memorandum of Economic and Financial Policies on
additional measures.
April 10 Indonesia issues a Supplementary Memorandum of Economic and Financial Policies
on additional measures.
May 4 The Board completes the first review under the Stand-By Arrangement and disburses SDR
734 million.
June 24 Indonesia issues a Second Supplementary Memorandum of Economic and Financial
Policies on additional measures.
July 15 The Board completes the second review of the Stand-By Arrangement, disbursing SDR
734 million, and approves an increase in IMF financing under the Stand-By Arrangement by SDR
1 illion.

Korea
1997:December 4 The Board approves an SDR 15.5 billion Stand-By Arrangement for Korea andreleases a disbursement of SDR 4.1billion.
December 18 The Board concludes the first biweekly review of the Stand-By Arrangement andreleases a further SDR 2.6 billion, activating the IMF’s new Supplemental Reserve Facility.
December 30 The Board approves a request by Korea for a modification of the schedule ofdrawings, bringing forward part of the amounts originally scheduled for February and May 1998,
but without changing overall access to IMF resources, and disburses SDR 1.5 billion.
1998: January 7 Korea issues a Letter of Intent describing additional measures.
January 8 The Board concludes the second biweekly review of the Stand-By Arrangement anddisburses SDR 1.5 billion.
February 7 Korea issues a Letter of Intent on additional measures.
February 17 The Board completes the first quarterly review of the Stand-By Arrangement anddisburses a further SDR 1.5 billion.

Note: This table is made from Annual Report 1998, p.23-32, IMF.

24

Figure 1. Hypothetical and Crisis economies
Log(Ct)H-ECOlog(λ H )
C-ECO

●

●
log(λ C)
PCP

0

CP

Note: PCP (H-ECO) and CP (C-ECO) denote the pre-crisis and the crisis periods (thehypothetical and the crisis economy), respectively. The t=0 denotes the crisis outburst
period. Parts of intercept, -(1/2)σ2H and -(1/2)σ2C , are neglected because they are negligible.

Figure 2. Hypothetical and Crisis economies using the Alternative Model
Log(Ct)H-ECO
Log(λ Ht0)●

Log(λ Ct0) ●
C-ECO

•T1

PCP

0

•T2

CP

t

Note: see a note of Figure 1

25

Figure 3. Per Capita Consumption in Logarithm (in national currencies)

9.6

Th ailan d

14.0

In don e sia

13.8
9.4

13.6
13.4

9.2

13.2
9.0
1990Q1
14.6

1996Q1

13.0
1990Q1

2002Q1

Kore a7.6

1996Q1

2002Q1

Malaysia

7.5

14.4

7.4

14.2

7.3
14.0

7.2

13.8

7.1

13.6
1990Q1

7.0
1990Q1

10.4

1996Q1

2002Q1

Ho n gKo n g

10.3
10.2
10.1
10.0
1990Q1

1996Q1

2002Q1

26

1996Q1

2002Q1

Figure 4.Estimated log(λt) and µt over Time: Hypothetical and Crisis Economies( Estimated log(λt) )T h ailan d
10.0
9.8
9.6
9.4
9.2
9.0
1997Q3In do n e sia
14.4
14.2
14.0
13.8

2000Q3

2003Q3

13.6
1998Q1

Ko re a
15.0
14.0
13.0
12.0
11.0
10.0
1997Q4

2000Q4

2001Q1
M al ays i a

2003Q4

7.8
7.6
7.4
7.2
7.0
1998Q1

2001Q1

H o n gKo n g
10.6
10.5
10.4
10.3
10.2
10.1
1998Q1:Crisis Economy
Hypothetical Economy

2001Q1

2004Q1

27

2004Q1(Estimated µt)
Indonesia

Thailand

0.04

0.03

0.02

0.02

0.00
0.01

-0.02
-0.04
1997Q3 1999Q3 2001Q3 2003Q3

0.00
1998Q1 2000Q1 2002Q1

Korea

Malaysia

0.02

0.20

0.01
0.10

0.00
-0.01

0.00

-0.02

-0.10
1997Q4

1999Q4

2001Q4

2003Q4-0.03
1998Q1 2000Q1 2002Q1 2004Q1

HongKong

0.010
0.005
0.000

⎯⎯⎯ : Crisis Economy------: Hypothetical Economy-0.005
1998Q1

2000Q1

2002Q1

2004Q128

Figure 5. Estimation vs Actual Values of Consumption for the Crisis Economy
ThailandIndonesia
14.0

9.6
9.5

13.9

9.4
13.8

9.3
9.2
1997Q3

2000Q3

13.7
1998Q1

2003Q3

Korea

2001Q1
Malaysia

14.6

7.6
7.5

14.4

7.4
14.2
14.0
1997Q4

7.3

2000Q4

7.2
2003Q4
1998Q1

2001Q1

HongKong
10.3: log( C t ): a t + t⋅bt
a t = log(λt)-σ 2 /2

10.2

bt = log(1+µt)
10.1
1998Q1

2001Q1

2004Q1

29

2004Q1

Figure 6. The Ratio of Costs at Each Period
Thailand
3
2.5
2
1.5
1
0.5
0
1997Q3

2000Q3
Korea

3
2.5
2
1.5
1
0.5
0
1997Q4

2000Q4

Indonesia
3
2.5
2
1.5
1
0.5
0
1998Q1

2003Q3

3
2.5
2
1.5
1
0.5
0
2003Q4
1998Q1

Hong Kong
3
2.5
2
1.5
1
0.5
0
1998Q1

2001Q1

2004Q1

30

2001Q1
Malaysia

2001Q1

2004Q1