Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
50
Estimating the Monetary Policy Reaction Function
for Taiwan: A VAR Model
Hui S. Chang
University of Tennessee – Knoxville
Abstract This study examines Taiwan’s monetary policy reaction function based on an extended
Taylor rule including the exchange rate, the stock price, and the lagged interest rate. The VAR
model is employed to consider simultaneous relations among the endogenous variables. Two
major monetary policy instruments - the discount rate and the collateral loan rate - are
considered. The results show that within a 95% confidence interval, the discount rate or the
collateral loan rate responds positively to a shock to the inflation gap and the stock price gap but
does not react significantly to a shock to the output gap or the exchange-rate gap. Furthermore,
except for the lagged interest rate, the inflation gap is more influential in explaining the variance
of the interest rates than other endogenous variables, suggesting that the major focus of the
monetary policy in Taiwan is to contain inflation.
Keywords: MPRF, Taylor Rule, output gap, inflation gap, impulse response functions, variance
decompositions
JEL Classifications: E52, F41, O53
Introduction
The Central Bank of China (CBC) in Taiwan monitors the economy through movements
in prices, interest rates, employment, exchange rates, business cycles, and other major indicators
to formulate its monetary policy. CBC’s monetary policy is to pursue long-term price stability
and economic growth and to maintain the dynamic stability of exchange rates. It sets target zones
for M2 and M2+bond funds, engages in open market operations, discount window refinancing,
and selling of the certificates of deposits (CDs) to mitigate temporary liquidity shortage of
financial institutions, and adopts proper measures to counter shocks of any new international
developments. In recent years, CBC has maintained easy monetary policy to stimulate
consumption and investment spending. On December 31, 2004, CBC increased the discount rate,
the rate on loans without collateral, and the rate on loans with collateral by 12.5 base points to
1.75%, 4.0%, and 2.125%, respectively (Central Bank of China, December 31, 2004). CBC
predicted that the short-term rates would remain relatively low for the foreseeable future and that
it would continue to maintain an accommodative or easy monetary policy. CBC set the target
growth of M2 in the range of 3.5% - 7.5% for the year 2005. To strengthen the monetary
transmission mechanism, banks have been encouraged to adopt adjustable-rate mortgages
(ARMs) and lower prime rates since the mid-2001. CBC also reduced the average required
reserve ratio from 6.22% to 5.0%, thus increasing market liquidity considerably. It pursued a
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
51
managed floating exchange rate policy and allowed market forces to determine the exchange rate
to some extent. CBC indicates that it will step in to intervene in the foreign exchange market if
there are excessive volatility, irregular factors, irrational expectations, market disorder, and/or
deviations of the exchange rate from market fundamentals. To avoid a huge loss due to
exchange-rate fluctuations, CBC stresses exchange-rate risk management for exporters and
importers regularly. For instance, to hedge exchange-rate risk, importers may purchase foreign
exchange forwards when placing orders and exporters may sell foreign exchange forwards when
receiving orders.
This paper attempts to estimate the monetary policy reaction function (MPRF) for
Taiwan to determine whether CBC in Taiwan has applied or considered the Taylor rule (1993,
1998, 1999). This paper has several unique aspects. First, following Assane and Malamud
(2000), David Romer (2001), Rogobon and Sack (2003), Hsing (2004), and others, this study
extends the Taylor rule by considering the exchange rate, the stock price, and the lagged interest
rate as additional variables. It is well known that the economy in Taiwan depends heavily on
international trade and that the CBC would like to see a dynamic, stable exchange rate, which
would be conducive to exports and imports. It is interesting to examine whether CBC uses the
interest rates to intervene in the foreign exchange market. It is also worthwhile to test whether
CBC responds to stock market performance in order to stimulate aggregate demand and the
economy through the wealth effect and the balance-sheet channel. Second, in estimating the
MPRF for Taiwan, this paper applies the VAR model in order to avoid simultaneity bias that
may exist in the single-equation estimation. Third, the impulse response function and variance
decomposition for the interest rates are estimated to find possible responses of the discount rate
and the collateral loan rate to a shock to one of the endogenous variables and to determine the
explanatory power of each of the variables on the variance of the interest rate. Fourth, U.S.
federal funds rate is considered as an exogenous variable to determine whether CBC would react
to a shock to U.S. monetary policy.
Literature Survey
There are several recent articles examining the Taylor rule or the monetary policy
reaction function (MPRF) for some industrialized countries. Clarida, Gali and Gertler (1997)
estimated MPRFs for G3 (U.S., Germany, and Japan) and E3 (U.K., France, and Italy). Central
banks in G3 pursued inflation targeting, were forward-looking, and experienced more success in
monetary policy. They showed that interest rates in E3 were greatly higher than what
macroeconomic conditions would suggest and that inflation targeting could be a better policy
option than fixing the exchange rates. In estimating an MPRF for the U.S. based on a forwardlooking model, Clarida, Gali, and Gertler (1998) found that the Volcker and Greenspan
administrations were more responsive to expected inflation changes than the pre-Volcker period
and that the goal of monetary policy during Volcker and Greenspan was to stabilize output and
inflation. Wesche (2003) estimated the MPRFs for five industrialized countries including the
U.S., U.K., Japan, Germany, and France. He showed that central banks assigned different
weights to the inflation gap and the output gap and that the German interest rate influenced
monetary policy in Italy and France after the EMS. Extending the Taylor rule, Hsing (2004)
estimated the monetary policy reaction function for Japan and found that the call rate showed a
positive response to a shock to the output gap, the inflation gap, stock prices, yen depreciation,
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
52
and the lagged call rate. He also revealed that except for the lagged call rate, the inflation gap
and the exchange rate are more important than the other variables in explaining the variance of
the call rate.
Employing a VAR model to examine the relationship between monetary policy and
exchange rates, Assane and Malamud (2000) found that the U.S. dollar appreciated after the
federal funds rate rose and that to respond to a weak dollar, the Fed would raise the federal funds
rate. According to Kalyvitis and Michaelides (2001), the U.S. dollar was instantaneously
overshot due to a monetary shock.
Some scholars maintained that the Fed should not consider stock market performance in
conducting its monetary policy because it may be counterproductive and difficult to find the
correct timing to take actions (Cogley, 1999; Bullard and Schaling, 2002). Rigobon and Sack
(2003) showed that monetary policy reacted to stock market performance significantly to cause
impacts on aggregate expenditures and that the probability of a 0.25 percentage point increase in
the federal funds rate would increase by 50% if there is a 5% increase in the stock price index.
Several interesting articles analyzed monetary policy in Taiwan. Emery (1987) reviewed
Taiwan’s monetary policy in dealing with the two energy crises and huge trade surpluses since
1973. He found that the tight monetary policy of raising the discount rate due to the energy crises
was too small, too late, and not effective in containing inflation. He also suspected that CBC’s
open market operations to reduce money supply due to large trade surpluses and capital inflows
did not succeed.
In studying the monetary reaction function for Taiwan, Shen and Hakes (1995) found that
the CBC reacted differently to four inflation regimes, namely, no inflation, low inflation,
moderate inflation, and high inflation. Specifically, CBC responded to both inflation and output
when there is no inflation, responded to output counter-cyclically and did not respond to inflation
when inflation is low, and reacted increasingly to inflation only when inflation is moderate and
high. Shen and Chen (1996) developed an index for monetary policy to evaluate the linear and
nonlinear reaction functions. CBC in Taiwan responded differently to inflation and output
depending upon economic conditions. It would react strongly when inflation and GDP are
greater than the threshold levels. Ford (1997) identified different targets of CBC, assigned
weights to different targets, and examined tradeoffs. He found containing inflation to be very
important to monetary policy. Based on the probit model with correction for autoregression,
Huang and Shen (2001) reported that CBC in Taiwan pursued a tight monetary policy during
high inflation but not during high economic growth. They also indicated that the simple probit
model without correction for autoregression would not be appropriate.
Applying the regime switching model, Cheng and Huang (1998) found that CBC
followed a non-intervention policy in most cases and maintained a target of monthly money
growth in the range of 0.95% to 2.17%. Furthermore, CBC would adjust the discount rate and
pursued an easy monetary policy when warranted. Based on a sample during 1978-1999, three
different monetary tools and selected targets, Cover, Hueng and Yau (2002) examined whether
the discretionary monetary policy or the optimal-rule policy in Taiwan would perform better.
They found that only 6.25% of the rules performed better than the discretionary policy.
The Theoretical Model
Extending the Taylor Rule for Taiwan, the VAR model can be written as
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
Et = α1Et-1 + … + αmEt-m + δXt + εt
53
(1)
where
E
X
α, δ
ε
IG
YG
EG
SG
DIS
CLR
FFR
= a k-vector of the endogenous variables [IG, YG, EG, SG, DIS or CLR];
= a d-vector of the exogenous variable [FFR];
= parameter matrices;
= white noise error term;
= the inflation gap;
= the output gap;
= the exchange rate gap;
= the stock price gap;
= the discount rate;
= the collateral loan rate; and
= U.S. federal funds rate.
As the Taylor rule indicates, we expect that DIS or CLR would respond positively to a
shock to IG or YG. Whether CBC would use the discount rate or the collateral loan rate to
intervene in the foreign exchange market is unclear. It is possible that CBC may use other
monetary tools such as selling or buying of CBC’s CDs and/or open market operations to
stabilize the exchange rate and pursue a fair market value for the currency. Stock market
performance is included in the VAR model mainly because CBC may use its interest rate policy
to enhance a healthy stock market. The U.S. federal funds rate is included to examine whether
CBC is sensitive to the U.S. federal funds rate, which is a major monetary policy instrument
employed by the Federal Reserve Bank.
Some of these variables may have simultaneous relations. For example, we expect that
DIS or CLR would respond to IG or YG. On the other hand, IG may also respond to YG. After
CBC lowers the interest rate, consumption and investment spending would rise, thus shifting
aggregate demand to the right and causing the equilibrium GDP to rise. A higher GDP would
cause YG to increase. As output rises, inflation may go up as well, causing IG to increase. SG
and YG may also interact to each other. Increased stock prices would stimulate consumption and
investment spending and cause output and the output gap to rise. Because all the endogenous
variables in a VAR model are lagged, there is no simultaneity problem, and OLS estimates are as
good as GLS estimates.
Data and Empirical Results
The collateral loan rate, the discount rate, the exchange rate, and stock prices were taken
from the Central Bank of China in Taiwan. Output and the price index came from the National
Statistics of Taiwan published by the Directorate General of Budget, Accounting, and Statistics.
The federal funds rate was obtained from the Federal Reserve Bank. The inflation rate is the
average of the implicit price deflator in the current and past 3 quarters. The targeted inflation rate
is 2.0% annually. Potential GDP, the target exchange rate, and the target stock-price index were
estimated based on the Hodrick-Prescott (1997) filtering process. After taking lags, the sample
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
54
consists of quarterly data ranging from 1980.Q3 to 2003.Q2 with a total of 92 observations.
Because Taiwan pursued a fixed exchange rate before 1979, earlier data are not included.
According to the ADF test, DIS and CLR have unit roots in levels, IG, YG, EG, and SG
are stationary in levels, and all the variables are stationary in the first difference. According to
the Johansen cointegration analysis, the null hypothesis of a zero cointegrating relationship
versus the alternative hypothesis of one cointegrating relationship was tested. The trace statistic
is estimated to be 117.35 when DIS is considered and 117.64 when CLR is considered. The
critical value is 76.07 at the 1% level. Hence, it is concluded that these variables have a longterm stable relationship.
Based on the several criteria, a lag length of one is selected. Graph 1 presents the
impulse-response function of the discount rate up to 12 quarters with a 95% confidence interval.
The VAR output shows that the value of the adjusted R2 is 0.9805 and the F test statistics is
762.228, which suggests that the regression is significant at the 1% level. As shown in Graph 1,
the discount rate reacts positively to a shock to the inflation gap, the stock price gap, or the
lagged discount rate during some of the quarters, and it does not responds significantly to a
shock to the output gap or the exchange rate gap at the 5% level. Table 1 reports the impulseresponse function of the discount rate in numerical values. Table 2 shows the variance
decomposition of the discount rate. Within the 95% confidence interval, the lagged discount rate,
the inflation gap, and the stock price gap can explain up to 76.50%, 59.16%, and 19.18% the
variation of the discount rate, respectively. Hence, the lagged discount rate is the most influential
variable, followed by the inflation gap and the stock price gap.
Graph 2 shows the impulse-response function of the collateral loan rate with a 95%
confidence interval. Similar results can be found. The VAR output reveals that the value of the
adjusted R2 is 0.9847 and that the F test statistics is 979.553, indicating that the whole regression
is significant at the 1% level. The collateral loan rate responds positively to a shock to the
inflation gap, the stock price gap, and the lagged collateral loan rate in some of the quarters, and
it does not respond significantly to a shock to the output gap and the exchange rate gap at the 5%
level. Table 3 presents the impulse-response function in numerical values. Table 4 reports the
variance decomposition of the collateral loan rate. The lagged collateral loan rate is the most
influential variable as it can explain up to 79.17% of the variation in the collateral loan rate. Up
to 52.80% of the variation in the collateral loan rate can be attributable to a shock to the inflation
gap. The stock price gap can explain up to 17.52% of the variance. Based on either the discount
rate or the collateral loan rate, we can reach similar conclusions that the lagged interest rate is the
most influential variable, followed by the inflation gap and the stock price gap..
This study also considers the reserve money as a policy tool. The results show that the
reserve money responds positively to a shock to the output gap and the stock price gap and does
not react to a shock to the inflation gap and the exchange rate gap, suggesting that more quantity
of money would be provided to accommodate an increase in the output gap or the stock price
gap. To save space, the graph and tables are not presented here and will be available upon
request.
Summary and Conclusions
This study has applied and extended the Taylor rule to examine Taiwan’s monetary
policy reaction function. In addition to the inflation gap and the output gap, this study also
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
55
examines whether monetary policy would respond to a shock to the exchange rate gap or the
stock price gap. Empirical results are summarized below. The discount rate or the collateral loan
rate responds positively to a shock to the inflation gap, the stock price gap, or the lagged interest
rate, but neither reacts significantly to a shock to the output gap or the exchange rate gap. It is
interesting to find that the response of reserve money to a shock to the output gap and the stock
price gap is positive and significant. It suggests that CBC in Taiwan would consider the Taylor
rule and also employ other instruments in conducting its monetary policy.
Because the inflation gap is much more important than the output gap in determining the
variation in the interest rates, CBC regards price stability as a top priority in conducting
monetary policy. It is possible for a country to have other targets such as the stability of
exchange rates and/or financial market performance. It appears that CBC would rely on market
forces to determine a fair value of the exchange rate and would not employ the discount rate or
the collateral loan rate to cause the exchange rate to depreciate or appreciate. CBC in Taiwan
would reduce the interest rate in response to a lower stock price, and vice versa. There may be
areas for further research. Since the Taylor rule deals with the determination of the U.S. federal
funds rate, it may be extended to other monetary policy instruments. Potential output, the
exchange rate target, and the stock price target may be estimated differently. We may treat the
MPRF as part of a general equilibrium in determining output and the interest rate
simultaneously.
References
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Shocks,” Applied Financial Economics, 10(5), 461-470.
Bullard, J. B. and E. Schaling. 2002. “Why the Fed Should Ignore the Stock Market?” Federal
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Cheng, J. C. and C. J. Huang. 1998. “A Monetary Target Model: The Case of Taiwan,” Pacific
Economic Review, 3(1), 71-81.
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Clarida, R., J. Gali, and M. Gertler. 1998. “Monetary Policy Rules and Macroeconomic
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Cover, J. P., C. J. Hueng, and R. Yau. 2002. “Are Policy Rules Better than the Discretionary
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Emery, R. F. 1987. “Monetary Policy in Taiwan, China,” Board of Governors of the Federal
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Huang, R. H. C. and C. H. Shen. 2001. “The Monetary Policy Reaction Function for Taiwan:
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Romer, D. 2001. Advanced Macroeconomics, second edition. New York, NY: McGraw Hill.
Shen, C. H. and H. R. Chen. 1996. “Monetary Policy Index and Policy Reaction Function,”
Academia Economic Papers, 24(4), 559-590.
Shen, C. H. and D. R. Hakes. 1995. “Monetary Policy as a Decision-Making Hierarchy: The
Case of Taiwan,” Journal of Macroeconomics, 17(2), 357-368.
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Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
58
Graph 1. Impulse Response Function of the Discount Rate
Response to Cholesky One S.D. Innovations ± 2 S.E.
Response of DIS to IG
Response of DIS to YG
.5
.5
.4
.4
.3
.3
.2
.2
.1
.1
.0
.0
-.1
-.1
-.2
-.2
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
Response of DIS to EG
4
5
6
7
8
9
10
11
12
10
11
12
Response of DIS to SG
.5
.5
.4
.4
.3
.3
.2
.2
.1
.1
.0
.0
-.1
-.1
-.2
-.2
1
2
3
4
5
6
7
8
9
10
11
12
10
11
12
Response of DIS to DIS
.5
.4
.3
.2
.1
.0
-.1
-.2
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
9
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
59
Table 1. Impulse Response Function of the Discount Rate
Period
1
2
3
4
5
6
7
8
9
10
11
12
IG
0.144796
(0.03255)
0.187399
(0.03556)
0.219868
(0.04284)
0.242297
(0.05082)
0.255424
(0.05841)
0.260302
(0.06516)
0.258149
(0.07082)
0.250235
(0.07530)
0.237812
(0.07858)
0.222053
(0.08069)
0.204023
(0.08170)
0.184655
(0.08171)
YG
0.017931
(0.03072)
0.043938
(0.04581)
0.065722
(0.05005)
0.076703
(0.05146)
0.079150
(0.05162)
0.075795
(0.05077)
0.068807
(0.04921)
0.059794
(0.04719)
0.049912
(0.04490)
0.039973
(0.04245)
0.030524
(0.03993)
0.021911
(0.03736)
EG
-0.009573
(0.03068)
-0.032041
(0.03396)
-0.045855
(0.04192)
-0.053596
(0.05016)
-0.056504
(0.05733)
-0.055642
(0.06290)
-0.051992
(0.06672)
-0.046435
(0.06885)
-0.039719
(0.06945)
-0.032461
(0.06876)
-0.025143
(0.06703)
-0.018129
(0.06447)
SG
0.063216
(0.03032)
0.137189
(0.03767)
0.168505
(0.04991)
0.172876
(0.05974)
0.160753
(0.06665)
0.139359
(0.07088)
0.113654
(0.07287)
0.086960
(0.07313)
0.061423
(0.07211)
0.038337
(0.07022)
0.018395
(0.06775)
0.001866
(0.06489)
DIS
0.287371
(0.02119)
0.233850
(0.02008)
0.182140
(0.02288)
0.133994
(0.02722)
0.090799
(0.03162)
0.053331
(0.03539)
0.021867
(0.03830)
-0.003681
(0.04033)
-0.023651
(0.04155)
-0.038544
(0.04208)
-0.048954
(0.04204)
-0.055513
(0.04154)
Cholesky Ordering: IG YG EG SG DIS. Standard Errors: Analytic.
Table 2. Variance Decomposition of the Discount Rate
Period
1
2
3
4
5
6
7
8
9
10
11
12
S.E.
IG
YG
EG
SG
DIS
1.358593
1.865478
2.214205
2.473536
2.671948
2.825474
2.944670
3.037109
3.108509
3.163313
3.205040
3.236508
19.42049
25.54625
31.09093
36.15741
40.78408
44.94856
48.60964
51.73664
54.32334
56.39066
57.98258
59.15889
0.297830
1.025815
1.956531
2.760530
3.343024
3.713360
3.912508
3.986059
3.975020
3.912923
3.825347
3.730494
0.084885
0.509378
0.958994
1.350592
1.658378
1.879448
2.021373
2.096954
2.121247
2.109447
2.075384
2.030569
3.701748
10.39316
15.24722
17.97459
19.09750
19.17956
18.66235
17.85876
16.97647
16.14292
15.42683
14.85594
76.49504
62.52539
50.74632
41.75687
35.11702
30.27907
26.79413
24.32159
22.60392
21.44404
20.68986
20.22411
Cholesky Ordering: IG YG EG SG DIS.
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
60
Graph 2. Impulse Response Function of the Collateral Loan Rate
Response to Cholesky One S.D. Innovations ± 2 S.E.
Response of CLR to IG
Response of CLR to YG
.4
.4
.3
.3
.2
.2
.1
.1
.0
.0
-.1
-.1
-.2
-.2
-.3
-.3
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
Response of CLR to EG
4
5
6
7
8
9
10
11
12
10
11
12
Response of CLR to SG
.4
.4
.3
.3
.2
.2
.1
.1
.0
.0
-.1
-.1
-.2
-.2
-.3
-.3
1
2
3
4
5
6
7
8
9
10
11
12
10
11
12
Response of CLR to CLR
.4
.3
.2
.1
.0
-.1
-.2
-.3
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
9
Chang, International Journal of Applied Economics, 2(1), March 200, 50-61
61
Table 3. Impulse Response Function of the Collateral Loan Rate
Period
1
2
3
4
5
6
7
8
9
10
11
12
IG
0.135228
(0.03266)
YG
0.021801
(0.03106)
EG
-0.005440
(0.03102)
SG
0.059640
(0.03070)
CLR
0.291476
(0.02149)
0.170388
(0.03566)
0.198171
0.053853
(0.04620)
0.075501
-0.034166
(0.03461)
-0.054028
0.127286
(0.03838)
0.156973
0.246948
(0.02033)
0.202631
(0.04270)
0.218474
(0.05051)
(0.05045)
0.086130
(0.05174)
(0.04272)
-0.066821
(0.05114)
(0.05056)
0.162568
(0.06008)
(0.02220)
0.160366
(0.02552)
0.231676
(0.05797)
0.238422
0.088665
(0.05179)
0.085746
-0.073768
(0.05851)
-0.076005
0.153428
(0.06653)
0.135943
0.121474
(0.02909)
0.086734
(0.06463)
0.239503
(0.07026)
(0.05091)
0.079368
(0.04936)
(0.06432)
-0.074598
(0.06844)
(0.07029)
0.114428
(0.07186)
(0.03230)
0.056513
(0.03487)
0.235780
(0.07477)
0.228121
0.070984
(0.04738)
0.061638
-0.070502
(0.07092)
-0.064545
0.091742
(0.07179)
0.069712
0.030873
(0.03674)
0.009669
(0.07815)
0.217367
(0.08045)
(0.04516)
0.052060
(0.04281)
(0.07194)
-0.057424
(0.07169)
(0.07055)
0.049443
(0.06853)
(0.03794)
-0.007386
(0.03855)
0.204299
(0.08174)
0.189624
0.042754
(0.04040)
0.034047
-0.049702
(0.07041)
-0.041826
0.031540
(0.06600)
0.016264
-0.020663
(0.03866)
-0.030583
(0.08211)
(0.03797)
(0.06832)
(0.06317)
(0.03836)
Cholesky Ordering: IG YG EG SG CLR. Standard Errors: Analytic.
Table 4. Variance Decomposition of the Collateral Loan Rate
Period
1
2
3
4
5
6
7
8
9
10
11
12
S.E.
1.366258
1.866394
2.206496
2.457912
2.650083
2.799262
2.915883
3.007258
3.078794
3.134631
3.178012
3.211512
IG
17.04143
21.74660
26.14590
30.32481
34.29221
38.00728
41.41420
44.46430
47.12704
49.39339
51.27416
52.79591
YG
0.442914
1.551249
2.740432
3.723766
4.442716
4.922143
5.208586
5.349495
5.386785
5.355105
5.281757
5.187276
Cholesky Ordering: IG YG EG SG CLR.
EG
0.027576
0.550088
1.242810
1.937284
2.557886
3.073540
3.475968
3.769813
3.967289
4.084595
4.139264
4.148244
SG
3.314705
9.080620
13.40629
15.99028
17.21367
17.51780
17.25930
16.69723
16.00885
15.30848
14.66394
14.11003
CLR
79.17338
67.07144
56.46457
48.02386
41.49352
36.47924
32.64194
29.71917
27.51003
25.85843
24.64088
23.75855