Financial Spillovers in Asian Emerging
Economies
Shin-ichi Fukuda and Mariko Tanaka∗
This paper explores financial spillovers between emerging Asia and advanced
economies using principal component analysis to extract common shocks in
亚洲. We first investigate stock market spillovers across the regions and find
that spillovers from emerging Asia became significant after the global financial
crisis. 然而, our industry-level analysis shows that the increased spillovers
can be attributed to the first principal component (PC) in the manufacturing
sector rather than to the first PC in the financial sector. This implies that the
rise of the Asian manufacturing sector in the global market played a key role
in enhancing the stock market spillovers. We next examine bilateral spillovers
in short-term and long-term rates. In the tapering period, we find significant
spillovers in long-term rates from the first PC in emerging Asia to Europe and
美国. 然而, these spillovers were much smaller than the stock
market spillovers in magnitude.
关键词: bond markets, emerging Asian economies, financial spillover, 库存
市场
JEL codes: E52, F10, F32
我. 介绍
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In the 2000s, emerging economies substantially increased their share in
global gross domestic product (GDP). The International Monetary Fund’s (IMF)
World Economic Outlook (十月 2018) suggested that the share of emerging and
developing economies in world GDP based on purchasing power parity (PPP),
这是 43.2% 在 2000, 将会 62.7% 在 2023 (see figure) (IMF 2018).
In integrated global production networks, emerging economies are increasingly
more connected with the rest of the world. 然而, despite a large increase in
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∗Shin-ichi Fukuda (corresponding author): Faculty of Economics, University of Tokyo, 日本. 电子邮件:
sfukuda@e.u-tokyo.ac.jp; Mariko Tanaka: Faculty of Economics, Musashino University, 东京, 日本. 电子邮件:
matanaka@musashino-u.ac.jp. An earlier version of this paper was presented at Aoyama Gakuin University, 这
Asian Development Review Conference in Bangkok, the 14th annual conference of the Asia-Pacific Economic
Association at the University of Southern California in Los Angeles, and the 30th Conference of the Korea Money
& Finance Association in Busan. We are grateful to Yasuyuki Sawada, Naoyuki Yoshino, Yoshihiko Tsukuda, 标记
Spiegel, Youngjin Yun, and other seminar participants for valuable comments. We would also like to thank the
anonymous referees for helpful suggestions. Fukuda’s research was supported by JSPS KAKENHI Grant Number
17K18557. Tanaka’s research was supported by JSPS KAKENHI Grant Number 18K01708. ADB recognizes “Hong
Kong” as Hong Kong, China and “Korea” as the Republic of Korea. The usual ADB disclaimer applies.
Asian Development Review, 卷. 37, 不. 1, PP. 93–118
https://doi.org/10.1162/adev_a_00142
© 2020 Asian Development Bank and
Asian Development Bank Institute.
在知识共享下发布
归因 3.0 国际的 (抄送 3.0) 执照.
94 Asian Development Review
Share of World Gross Domestic Product
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笔记: The share of world gross domestic product is based on purchasing power parity.
来源: International Monetary Fund. 2018. World Economic Outlook, 十月 2018. 华盛顿, 直流.
their disposable income, many of them have not been able to sell rights over
their output in advance, 那是, to create financial assets, owing to their financial
underdevelopment. 所以, despite the dramatic output growth, there still exists
a view that financial markets in emerging economies have a limited role in the global
financial market.
在本文中, we explore how financial spillovers between emerging East
Asia and advanced economies have evolved in the 2000s. To investigate financial
spillovers between emerging and advanced economies, East Asia has the following
three notable features. 第一的, emerging East Asian economies have undergone rapid
industrialization and maintained exceptionally high growth rates, often called the
“East Asian Miracle.” According to the IMF’s World Economic Outlook (十月
2018), the share of emerging and developing Asia in world GDP, 这是 16.7%
在 2000, 将会 37.8% 在 2023 based on PPP. East Asia now plays a central role
in global production networks (看, 例如, Ito and Vézina 2016, Helble and
Ngiang 2016, Aizenman and Fukuda 2017, and Shepherd 2018). 第二, 尽管
the dramatic output and trade growth, financial markets in emerging East Asia
have developed at a slower pace and from a lower base until recently. 在里面
2000s, some Asian emerging economies started a process of financial “catching
up” toward mature economies. 然而, various indicators suggest that the scope
for financial catching up is still substantial in most of the Asian emerging economies
Financial Spillovers in Asian Emerging Economies 95
(看, 例如, Fukuda 2013, and Ito and Kawai 2016). 第三, since Asian
financial markets are open when European and New York markets are closed, 我们
may identify causality from Asian financial market shocks to Europe and the United
状态 (我们) without serious simultaneous biases. If the financial markets were open
同时, it would be difficult to identify from which financial markets the
shocks originated. But because of substantial time differences across the regions,
the use of daily data in each region may allow us to identify the direction of spillover
effects without serious simultaneous biases.
In the analysis, we use principal component analysis (PCA) 捕捉
common financial shocks in Asia and estimate global vector autoregressive (GVAR)
models to see bilateral spillovers across the regions. In the first part, we investigate
bilateral stock market spillovers across the regions. We find that while spillovers
from Asian stock markets to those in Europe and the US had been small before
the global financial crisis (GFC), stock market spillovers from the first principal
成分 (PC) in emerging Asia became significant in the post-GFC period.
然而, we also find that the increased spillovers were attributable to the first PC
in the manufacturing sector rather than to the first PC in the financial sector. 这
implies that the Asian manufacturing sector’s rise in the global market played a key
role for enhancing stock market spillovers from emerging Asia in the post-GFC
时期.
In the second part, we examine bilateral spillovers in short-term and
long-term rates. With short-term rates, there were no significant spillovers from the
advanced economies to Asia or from Asia to the advanced economies. 相比之下,
with long-term rates, we find large spillovers from the advanced economies to
亚洲. We also find some significant spillovers from Asia to Europe and the US in
long-term rates. 然而, spillovers from emerging Asia were much smaller in the
bond markets than in the stock markets. This supports the view that bond market
linkages from emerging Asia to advanced countries were, 如果有的话, small even after
the GFC.
在文献中, a number of studies have investigated financial spillovers
from advanced economies. The studies found that financial market shocks in
advanced countries had large spillover effects on emerging market economies
(EMEs), although the responses of EMEs were heterogeneous (看, 例如,
Gauvin, McLoughlin, and Reinhardt 2014; 恩格尔 2016; and Aizenman, Chinn, 和
Ito 2017). 尤其, an extensive literature suggested that US unconventional
monetary policy had enormous spillover effects on EMEs after the GFC, 尤其
on those with fragile macro fundamentals (看, 例如, 罗杰斯, Scotti,
and Wright 2014; Neely 2015; Eichengreen and Gupta 2015; Rey 2016; 和
Tillmann 2016). Several regional studies also found that financial shocks in
advanced economies had various spillover effects on emerging Asian economies
(看, 例如, 摩根 2011; Park and Um 2016; Fukuda 2018, 2019).
然而, spillovers originating from emerging markets have received relatively
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96 Asian Development Review
scant attention in most previous studies. Gelos and Surti (2016) and Huidrom, Kose,
and Ohnsorge (2016) are exceptional studies that showed the growing importance of
financial spillovers from emerging economies in the 2000s especially after the GFC.
然而, few studies have investigated spillovers from Asian financial markets
to advanced markets. It is thus important to understand the magnitude of these
spillovers in the 2000s and to what extent they have increased after the GFC.
This paper is a straightforward extension of Fukuda and Tanaka (2017)
in that we explore the degree of financial spillovers from emerging Asia in the
2000s. 然而, it has two critical differences. 第一的, this paper uses PCA to
extract common financial shocks in Asia. The extracted financial shocks allow
us to investigate the size of regional spillovers from Asian common financial
shocks. A number of studies have suggested growing regional integration in
Asian financial markets (看, 例如, 于, Fung, and Tam 2010; Boubakri
and Guillaumin 2015; Komatsubara, Okimoto, and Tatsumi 2017; Mensah and
Premaratne 2017; Didier, Llovet, and Schmukler 2017; and Sugimoto and Matsuki
2018). Given financial integration in Asia, it is important to estimate regional
spillovers excluding spillovers from country-specific shocks. 第二, 这篇论文
investigates bond market spillovers in addition to stock market spillovers. Bond
markets have been less developed than stock markets in Asia.1 Thus, by comparing
spillovers in the two types of financial markets, we may see whether bond market
linkages from emerging Asia to advanced countries were smaller owing to their
financial underdevelopment.
Our empirical results suggest that financial market spillovers from advanced
economies to emerging Asia were much larger than those from emerging Asia
to advanced economies. This is particularly true in bond markets. 然而, 我们
also find significant spillovers from Asian stock markets to advanced economies in
the post-GFC period. The industry-level stock market spillovers indicate that this
happened because of increased manufacturing sector shocks in emerging Asia. 这
impact of fundamental shocks in emerging Asia has been rising in global financial
市场. This has considerably increased stock market spillovers from Asia to
global financial markets even if financial markets remained less developed in Asia.
然而, direct financial linkages from emerging Asia to advanced countries were,
如果有的话, limited even after the GFC. Structural reforms of financial markets are still
an important policy agenda in emerging Asia.
The paper proceeds as follows. After explaining our empirical methodology
in section II, section III provides empirical results on stock market spillovers.
Section IV extends the analysis by using industry-level stock returns. Sections V
and VI investigate spillovers of short-term and long-term rates, 分别. 部分
VII summarizes our results and refers to their implications.
1See AsianBondsOnline. https://asianbondsonline.adb.org/.
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Financial Spillovers in Asian Emerging Economies 97
二. Empirical Methodology
To investigate bilateral spillovers between Asian and advanced financial
市场,
the following sections estimate GVAR models and investigate the
degree of financial market spillovers by using variance decomposition. 除非
the spillovers are one directional and have no further propagation, 一个单一的
equation would not be enough to capture financial spillovers across the regions. 在
globalized economies, a financial shock has a complicated international propagation
机制. It not only has direct and indirect spillover effects on other financial
市场, but the affected financial markets also have further spillover effects on
the financial market where the shocks originated. The feedback loop sometimes
continues for a few days. A GVAR is a useful econometric framework to capture
such multilateral financial spillovers with various feedbacks across regions.
In the analysis, we use PCA to capture total (常见的) financial shocks in
亚洲. PCA is a mathematical procedure that transforms a number of (possibly)
correlated variables into a (较小) number of uncorrelated variables called
“principal components.” By using a linear combination, we calculate the first PC
to account for as much of the variability in the data as possible. We then remove
this variance and seek a second linear combination which explains the maximum
proportion of the remaining variance. In the PCA, we use financial variables from
five emerging Asian economies: 香港, 中国; the People’s Republic of China
(PRC); the Republic of Korea; 新加坡; and Taipei,中国. These economies have
more developed financial markets than the other emerging Asian economies.
Using the first and second PCs in the Asian economies, we estimate the
following GVAR:
Yt = a +
p(西德:2)
j=1
β jYt− j +
p(西德:2)
j=1
γ xt− j + ut
(1)
where Yt is a vector of endogenous variables and xt is an exogenous variable. 这
vector of endogenous variables is composed of six financial variables: a financial
variable in Japan, the first and second PCs in the Asian economies, two European
financial variables (in the United Kingdom [英国] 和欧洲), and a financial
variable in the US. The exogenous variable is the daily log difference of the Chicago
Board Options Exchange Volatility Index (VIX). We use VIX as an exogenous
variable to account for common and systematic global factors. The estimation of
the GVAR model is done recursively, with the number of lags set to 2.2
The order of the Cholesky decomposition is the variable in Japan, the first PC
in Asia, the second PC in Asia, the variable in the UK, the variable in Europe, 和
2Schwarz criterion chose either 1 或者 2 lags in all cases and so did the Akaike information criterion. 我们的
essential results were robust even if we set the number of lags to 1.
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98 Asian Development Review
the variable in the US. We chose the order because Asian financial markets are open
when European and New York markets are closed. Putting aside overlaps of a few
小时, London and Frankfurt markets are open after Asian financial markets close,
and the New York market is open after the European markets close. 因此, the use
of daily data may allow us to identify spillover effects across the regions without
serious simultaneous biases.
Because causality identified by GVAR is “Granger causality,” our identified
spillovers do not necessarily mean “true” causality. This is because financial
variables can move in anticipation of future shocks. 例如, if some event
is expected to happen in the UK when Asian stock markets are open, stock prices
in Asia would respond earlier in anticipation of that shock in the UK. 在这种情况下,
the identified Granger causality is from Asia to the UK, although the true causality
is from the UK to Asia. 然而, noting that most of the country-specific shocks
tend to occur when its local market is open, large European or US-specific events
are less likely to happen when Asian markets are open. In the following analysis,
we thus suppose that our GVARs approximately identify true spillovers from Asian
financial shocks to European and US markets.
In addition to the above limitation, our identified spillovers may not mean
“true” spillovers when important news is announced after stock markets close. 在
这个案例, our order of the Cholesky decomposition may identify some European
shocks as US shocks and some US shocks as Japanese shocks. 然而, 给定
the order of the Cholesky decomposition, it is unlikely that we identify shocks in
Europe and the US as emerging Asian market shocks. In the Appendix, we show
that our results are essentially the same, even if we control for spillover effects of
shocks after the New York market closes.
Unless explained otherwise, we downloaded the data from Datastream. 到
the extent that the data are available, the sample period starts in January 2003 和
ends in April 2018. We split the sample periods into three subsample periods: 3
一月 2003 到 29 六月 2007 (pre-GFC period), 1 七月 2009 到 20 可能 2013
(post-GFC and pretapering period), 和 21 可能 2013 到 27 四月 2018 (tapering
时期). The subsample periods did not include 1 七月 2007 到 30 六月 2009 到
exclude the effects of the GFC. We split the post-GFC period into two to allow
different monetary policy regimes in the US. The break point is the date when
Federal Reserve Chairman Ben Bernanke first mentioned the idea of gradually
reducing or “tapering” the Federal Reserve Board’s monetary expansion.
三、. Empirical Results: Stock Market Spillovers
在这个部分, we explore stock market spillovers between Asian and
advanced financial markets. We take the log difference of daily stock market indexes
and use them as endogenous variables. The stock market indexes in Asia are the
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Financial Spillovers in Asian Emerging Economies 99
桌子 1. Correlation of Principal Components with
Stock Market Returns
(我) Pre-GFC period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
1st PC 2nd PC 3rd PC
−0.059 −0.205
0.030 −0.127
0.090
0.982
−0.109 −0.265
−0.004 −0.052
−0.136
0.928
0.476
0.489
0.109
0.445
0.475
0.315
(二) Post-GFC and pretapering period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
(三、) Tapering period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
1st PC 2nd PC 3rd PC
−0.158 −0.436
0.076
0.166
−0.120 −0.472
−0.150
0.089
−0.360
0.739
0.430
0.466
0.310
0.425
0.441
0.354
0.073
0.897
1st PC 2nd PC 3rd PC
−0.199 −0.413
0.197 −0.038
0.215
0.849
−0.169 −0.379
−0.140
0.073
−0.390
0.796
0.431
0.483
0.300
0.432
0.440
0.331
GFC = global financial crisis, PC = principal component.
来源: 作者的计算.
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Shanghai Stock Exchange Composite Index; Hong Kong Hang Seng Index; 韩国
Composite Stock Price Index; FTSE Straits Times Index; the weighted index of
Taipei,China’s stock exchange; and Stock Exchange of Thailand Index. Those in
日本, 欧洲, 英国, and the US are the Nikkei 225, DAX 30, FTSE 100, 和
Dow Jones Industrials, 分别.
桌子 1 reports the correlation of the first, 第二, and third PCs in Asia with
stock market returns in each Asian economy for the three alternative subsample
periods. It shows that the first PC is positively correlated with stock market returns
in all Asian economies. The correlation with the PRC’s stock market returns is
small for the first subsample period (pre-GFC period). 然而, the correlation lies
almost between 0.3 和 0.5 for other Asian returns. This implies that the first PC is
a weighted average of all Asian stock market returns. 相比之下, the second PC has
a large positive correlation only with the PRC’s stock market returns. The degree of
the correlation is over 0.8 for all subsample periods, which implies that the second
PC reflects mainly PRC-specific returns. 相似地, the third PC has a large positive
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100 Asian Development Review
桌子 2.1 Variance Decomposition of the Principal Components in
Asian Stock Returns (%)
(我) Decomposition of the 1st principal component
1st PC
Shock
57.09
56.17
64.26
Advanced Economies
全部的
日本
英国
德国
我们
41.62
43.02
33.33
24.39
15.33
14.80
6.03
19.49
8.05
3.03
1.55
0.84
8.17
6.65
9.65
Pre-GFC period
Pretapering period
Tapering period
(二) Decomposition of the 2nd principal component
2nd PC
Shock
98.59
97.09
97.95
Advanced Economies
全部的
日本
英国
德国
我们
0.99
2.08
1.46
0.15
0.03
0.77
0.08
1.22
0.17
0.33
0.03
0.01
0.43
0.79
0.50
Pre-GFC period
Pretapering period
Tapering period
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US =
美国.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
correlation only with Thai stock market returns. The degree of the correlation is
超过 0.7, which implies that the third PC reflects mainly Thai-specific returns.
Using the first and the second PCs in Asia, we estimate the GVAR formulated
in the last section for the three alternative subsample periods. Tables 2.1 和 2.2
report the variance decomposition over 10 business days. These show in percentages
how much of the stock price fluctuations were explained by their own and other
stock market shocks over 10 business days. Our main interest is to see spillover
effects between Asian stock markets and those in advanced economies. 因此, 桌子
2.1 reports how much of the first and second PCs in Asia were explained by shocks
in Japan, the two European countries, and the US, while Table 2.2 reports how much
of the stock prices in Japan, the two European countries, and the US were explained
by the first and second PCs in Asia.
桌子 2.1 indicates that the first PC in Asia was largely explained by stock
price shocks in the advanced economies throughout the three subsample periods.
多于 40% of the first PC was explained by shocks in the advanced economies
in the first and second subsample periods (pre-GFC period and post-GFC and
pretapering period) 以及超过 30% in the third subsample period (tapering
时期). This implies that there have been large positive spillovers from stock
markets in advanced economies to Asian stock markets before and after the GFC,
although the spillover effects declined significantly in the tapering period. Among
the advanced economies, shocks in Japan explained most of the first PC in the first
and third subsample periods, while shocks in the UK were the biggest driver in the
second subsample period. Shocks in the US also explained more than 8% 在里面
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Financial Spillovers in Asian Emerging Economies 101
桌子 2.2 Variance Decomposition of Stock Returns in Advanced
Economies (%)
(我) Japan’s stock prices
Pre-GFC period
Pretapering period
Tapering period
(二) UK stock prices
Pre-GFC period
Pretapering period
Tapering period
日本
Shock
82.64
70.99
74.84
英国
Shock
80.45
74.59
71.09
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
15.87
27.87
22.18
1.29
0.25
2.38
0.19
0.89
0.61
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
14.83
9.47
16.00
4.53
14.77
12.00
0.19
1.17
0.92
(三、) Germany’s stock prices
German Other Advanced
Shock
Economies
1st PC 2nd PC
Shock
Shock
Pre-GFC period
Pretapering period
Tapering period
37.19
22.37
35.87
(四号) US stock prices
56.53
64.92
53.03
6.03
11.18
9.79
0.25
1.52
1.32
Pre-GFC period
Pretapering period
Tapering period
我们
Shock
62.42
40.92
65.17
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
34.76
50.14
28.42
2.60
7.46
6.01
0.22
1.47
0.41
GFC = global financial crisis, PC = principal component, UK = United Kingdom,
US = United States.
笔记: The table reports the variance decomposition over 10 business days after a
震惊.
来源: 作者的计算.
first and the third subsample periods. The only exceptions were shocks in Germany
which explained only 1.55% in the second subsample period and 0.84% in the third
subsample period. This may have happened because of the euro debt crisis during
these periods.
然而, 桌子 2.1 suggests that stock price shocks in the advanced
economies explained very little of the second PC in Asia. Except for UK shocks
in the second subsample period, any shock in the advanced economies explained
少于 1% of the second PC. Even UK shocks in the second subsample period
explained only 1.22%. This does not mean that there has been no positive spillover
to the PRC, because the first PC is correlated with the PRC’s returns. 但是这个
implies that there has been no positive spillover from the advanced economies to
PRC-specific returns that were independent of stock prices in the other emerging
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102 Asian Development Review
Asian economies. This may happen partly because of various financial regulations
in the PRC and partly because of independent remarkable economic growth in the
国家.
相比之下, 桌子 2.2 shows that
the first and second PCs in Asia
explained only a small percentage of the stock price fluctuations in the advanced
economies throughout the subsample periods. 尤其, the first and second
PCs’ contribution to stock price fluctuations in Japan in the first and the second
subsample periods were small. This implies that the stock price spillovers are
asymmetric between Asia and the advanced economies. 那是, spillovers from
advanced economies to Asian markets have been much larger than those from Asian
markets to advanced economies.
然而, 桌子 2.2 also indicates that after the GFC, the first PC in Asia
came to explain a significant percentage of stock price fluctuations in the two
European countries and the US. In the second subsample period, the first PC
解释了 14.77% of stock fluctuations in the UK, 11.18% in Germany, 和 7.46%
in the US. In the third subsample period, it explained 12% in the UK, 9.79% 在
德国, 和 6.01% in the US. These percentages were much larger than those in
the first subsample period. This implies that stock market spillovers from emerging
Asia to Europe and the US, which were small before the GFC, became significantly
positive after the GFC. The spillovers from Asia to the advanced economies became
far from negligible even though they were still smaller than those from the advanced
economies to Asia.
IV. Industry-Level Estimation Results
In the previous section, we found that stock market spillovers from the first
PC in emerging Asia to those in Europe and the US became significant in the
post-GFC period. The result indicates that even in the stock markets, 常见的
shocks in emerging Asia came to have substantial impacts on advanced countries
after the GFC. 然而, stock market spillovers could increase because emerging
Asian economies were increasingly more connected with the rest of the world
in integrated global production networks. If this is the case, the spillovers do
not necessarily suggest direct financial linkages from emerging Asia to advanced
countries in the post-GFC period.
在这个部分, we investigate whether the stock market spillovers from
emerging Asia in the post-GFC period originated from the financial sector or the
manufacturing sector. In the analysis, we use daily industry-level stock market
returns in emerging Asia and explore which sector’s shocks had larger impacts
on the stock prices in advanced countries. We use PCA to extract common stock
price shocks of the manufacturing sector and those of the financial sector in the
five emerging Asian economies for the three subsample periods. Except for the use
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Financial Spillovers in Asian Emerging Economies 103
桌子 3. Correlation of Principal Components with Industry-Level Returns
(我) Pre-GFC period
Manufacturing Sector
Financial Sector
1st PC 2nd PC 3rd PC 1st PC 2nd PC 3rd PC
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
0.461
0.485
0.316
0.434
0.441
0.264
0.006 −0.302
−0.151 −0.021
−0.591
0.650
0.160 −0.393
−0.038 −0.081
0.570
0.775
0.435
0.491
0.348
0.379
0.453
0.316
−0.239
0.092
−0.037 −0.203
0.551 −0.620
−0.549
0.126
−0.094 −0.015
0.741
0.572
(二) Post-GFC and pretapering period
Manufacturing Sector
Financial Sector
1st PC 2nd PC 3rd PC 1st PC 2nd PC 3rd PC
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
(三、) Tapering period
0.410
0.448
0.463
0.374
0.425
0.310
−0.337
0.201
0.060 −0.398
0.013 −0.260
0.601
0.060 −0.373
0.484
0.816
−0.462
0.385
0.460
0.454
0.383
0.420
0.334
−0.415
0.439
0.076 −0.396
0.047 −0.373
0.350
0.064 −0.314
0.539
0.770
−0.472
Manufacturing Sector
Financial Sector
1st PC 2nd PC 3rd PC 1st PC 2nd PC 3rd PC
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
0.389
0.464
0.457
0.401
0.410
0.310
−0.248
0.584
−0.127 −0.396
−0.189 −0.301
−0.159
0.502
0.045 −0.372
0.145
0.927
0.314
0.489
0.477
0.392
0.439
0.297
GFC = global financial crisis, PC = principal component.
来源: 作者的计算.
0.679
0.495
−0.143 −0.358
−0.110 −0.344
0.039
−0.070 −0.093
−0.630
0.706
0.325
of PCs in the manufacturing sector and those in the financial sector, the estimated
equations are essentially the same as those in the last two sections.
桌子 3 reports the correlations of the first, 第二, and third PCs with
industry-level stock returns in each Asian market. It shows that both in the
manufacturing and financial sectors, the first PC is positively correlated with
industry-level stock market returns in all Asian economies. The correlations
are relatively small in Thailand. 然而, except for a few cases in Thailand,
the correlations lie between 0.3 和 0.5 for each industry-level return. 这
implies that the first PC is a weighted average of all Asian industry-level stock
market returns. Unlike with aggregated returns, the second and third PCs in the
industry-level returns do not have a dominant positive correlation with stock market
returns in the PRC. 反而, in the manufacturing sector, the second PC has a
large positive correlation with stock market returns only in Thailand. This is also
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104 Asian Development Review
桌子 4.1 Variance Decomposition of the Principal Components: Industry-Level
Returns (%)
(我) Decomposition of the 1st principal component
Manufacturing
sector
Financial sector
Pre-GFC period
Pretapering period
Tapering period
Pre-GFC period
Pretapering period
Tapering period
1st PC
Shock
60.62
57.88
68.25
25.19
12.98
22.92
Advanced Economies
全部的
日本
英国
德国
我们
37.20
41.24
30.48
35.40
41.12
31.16
22.19
13.45
13.75
20.46
14.38
13.73
5.66
19.69
7.64
4.89
18.09
8.35
2.88
1.72
1.18
2.96
1.98
1.01
6.47
6.38
7.91
7.09
6.67
8.07
(二) Decomposition of the 2nd principal component
Manufacturing
sector
Financial sector
Pre-GFC period
Pretapering period
Tapering period
Pre-GFC period
Pretapering period
Tapering period
2nd PC
Shock
97.36
96.98
97.12
90.86
73.55
80.53
Advanced Economies
全部的
日本
英国
德国
我们
0.53
1.76
1.83
2.86
2.41
2.40
0.02
0.82
0.81
1.84
0.83
0.99
0.08
0.41
0.96
0.04
0.67
0.90
0.14
0.15
0.03
0.71
0.42
0.38
0.29
0.37
0.02
0.28
0.49
0.13
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US = United States.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
true even in the financial sector, where the second PC in the second subsample
period and the third PC in the first and third subsample periods have large positive
correlations. This implies that either the second or the third PC reflects mainly Thai
returns when using industry-level stock prices.
As in the previous section, we estimate GVARs for three alternative
subsample periods: 3 一月 2003 到 29 六月 2007 (pre-GFC period), 1 七月
2009 到 20 可能 2013 (post-GFC and pretapering period), 和 21 可能 2013 到
27 四月 2018 (tapering period). Except for the use of the first and second PCs in
the manufacturing and financial sectors for emerging Asia, the set of endogenous
变量, the exogenous variable, and their order are the same as those in the
last section. When estimating GVARs, we ordered the first and second PCs of the
manufacturing sector prior to those of the financial sector in Asia.
Tables 4.1 和 4.2 report the variance decomposition over 10 business days.
For the three subsample periods, 桌子 4.1 reports in percentages how much of the
first and second PCs in Asian manufacturing and financial sectors were explained
by shocks in Japan, the two European countries, and the US, while Table 4.2 报告
how much of the stock returns in Japan, the two European countries, and the US
were explained by the first and second PCs in Asian manufacturing and financial
部门. In both of the tables, we find no significant spillover from advanced
countries to the second PC in Asia throughout the subsample periods.
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Financial Spillovers in Asian Emerging Economies 105
桌子 4.2 Variance Decomposition in Advanced Economies by Industry (%)
(我) Variance decomposition of Japan’s stock prices
Manufacturing Sector
Financial Sector
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
1st PC 2nd PC
Shock
Shock
15.68
27.32
22.27
1.15
0.56
2.18
0.11
0.08
0.70
0.75
0.36
0.17
0.13
0.40
0.04
日本
Shock
82.17
71.28
74.64
Pre-GFC period
Pretapering period
Tapering period
(二) Variance decomposition of UK stock prices
Manufacturing Sector
Financial Sector
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
1st PC 2nd PC
Shock
Shock
14.90
9.83
16.00
2.92
14.77
11.33
0.10
0.44
0.36
1.28
0.58
1.00
0.83
0.68
0.17
英国
Shock
79.97
73.69
71.14
Pre-GFC period
Pretapering period
Tapering period
(三、) Variance decomposition of Germany’s stock prices
Manufacturing Sector
Financial sector
German Other Advanced
Shock
Economies
1st PC
Shock
2nd PC
Shock
1st PC 2nd PC
Shock
Shock
Pre-GFC period
Pretapering period
Tapering period
37.04
22.37
35.61
56.63
64.62
53.09
4.04
10.92
9.41
0.34
0.42
0.41
1.67
1.03
1.12
0.27
0.63
0.35
(四号) Variance decomposition of US stock prices
Manufacturing Sector
Financial Sector
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
1st PC 2nd PC
Shock
Shock
34.89
50.32
29.32
1.52
7.55
5.04
0.01
0.19
0.30
1.04
0.61
0.37
0.26
0.29
0.12
我们
Shock
62.29
41.04
64.85
Pre-GFC period
Pretapering period
Tapering period
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US = United States.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
But as in the previous section, we find large spillovers from advanced
countries to the first PC in Asia throughout the subsample periods. 桌子 4.1 节目
that in both the manufacturing and financial sectors, shocks in advanced economies
explained more than 30% of the first PC in the first and third subsample periods and
多于 40% in the second subsample period. Before and after the GFC, 那里
have been large positive spillovers from stock markets in advanced economies to
Asian stock markets in both sectors. 然而, in the manufacturing sector, 大约
60% of the first PC’s fluctuations were explained by its own shocks. 相比之下, 在
the financial sector, a substantial part of the first PC’s fluctuations was explained
by the first PC’s shocks in the manufacturing sector. This implies that the financial
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106 Asian Development Review
sector in Asia has experienced large positive stock market spillovers not only from
advanced economies but also from the manufacturing sector in Asia.
As in the previous section, we can confirm that the spillovers are asymmetric
between Asia and the advanced economies. 桌子 4.2 shows that the first PCs of
Asian stock prices in the manufacturing and financial sectors contributed only a
small percentage of the stock price fluctuations in advanced economies. 然而,
looking at spillovers from Asia to the advanced economies, we see one noteworthy
feature which we did not observe in the previous section.
Throughout the subsample periods, the first PC of the Asian financial sector
never had significant spillover effects on the advanced countries. Throughout the
subsample periods, it never explained more than 2% of stock price fluctuations in
each advanced country. 相比之下, the first PC in the Asian manufacturing sector
had significant spillover effects on stock prices of the advanced countries after the
GFC. Both in the second and third subsample periods, it explained more than 10%
of UK stock price fluctuations, 关于 10% of German stock price fluctuations, 和
多于 5% of US stock price fluctuations. These features suggest that stock
market spillovers from emerging Asia increased in the post-GFC period mainly
because common manufacturing sector shocks in emerging Asia had significant
impacts on the advanced economies.
The share of emerging Asia in global output and trading network has
progressed steadily in the 2000s. Before the GFC, this increased real linkage did not
intensify financial linkages much. 然而, in the post-GFC period, it came to have
a significant impact on stock market linkages between the two regions. 因此,
stock market spillovers from emerging Asia to the advanced economies increased
significantly even though direct financial linkages were, 如果有的话, small even after the
GFC.
V. Interest Rate Spillovers
In previous sections, we explored spillovers between Asian stock markets and
those in advanced economies. 在以下部分中, we will examine spillovers
of short-term and long-term interest rates across the regions. As in the previous
sections, we calculate the variance decomposition of GVARs and investigate how
much of the fluctuations can be explained by the other interest rate shocks over 10
business days. Variables in the GVARs are composed of six endogenous variables
and one exogenous variable (IE。, daily log difference of VIX). The endogenous
variables include the first and second PCs of the daily difference in interest rates in
five Asian economies (IE。, 香港, 中国; the People’s Republic of China; 这
Republic of Korea; 新加坡; and Taipei,中国) and the daily difference in interest
rates in Japan, 英国, 欧洲, and the US. The estimation of the GVAR model is
done recursively, with the number of lags set to 2, for the three subsample periods.
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Financial Spillovers in Asian Emerging Economies 107
The subsample periods are the same as those in the last section. 然而, 因为
of missing data, the pre-GFC period is from 6 一月 2006 到 29 六月 2007 为了
short-term interest rates. Since Asian financial markets are open when European
and New York markets are closed, the order of the Cholesky decomposition is an
interest rate in Japan, the first PC in Asia, the second PC in Asia, an interest rate in
英国, an interest rate in Europe, and an interest rate in the US.
We first explore spillovers of short-term interest rates. For short-term interest
rates of the five Asian economies, we use overnight rates (IE。, Bank of Korea
base rate; Singapore Overnight Rate Average; Bangkok Interbank Offered Rate;
swap overnight of Taipei,中国; Shanghai Interbank Offered Rate; and Hong Kong
Interbank Offered Rate) and calculate the PCs of their daily changes. 为了
advanced economies, we use daily changes of the uncollateralized overnight call
rate in Japan, the UK bank rate, the European Central Bank main refinancing
operations or deposit rate, and the US federal funds target rate. Data for these
interest rates were downloaded from Datastream. 然而, because of the zero
lower bound, we use the estimated shadow rates for short-term interest rates in
advanced economies. All of the shadow rate estimates are obtained using the Leo
Krippner shadow or lower bound framework with two factors (see Krippner 2015).3
桌子 5 summarizes the correlations of the first, 第二, and third PCs with
daily changes of each Asian short-term rate for the three alternative periods. 不像
with stock returns, we cannot conclude that the first PC is a weighted average of
all Asian economies in the short-term rates. The second and third PCs also have
large correlations only with specific economies. This may have happened not only
because short-term rates were still regulated by the government in emerging Asia
but also because each central bank can control its policy rate without being affected
by external policy rates.
Tables 6.1 和 6.2 report the variance decomposition over 10 business days
for the three subsample periods. 桌子 6.1 reports in percentages how much of the
first and second PCs in Asian short-term rates were explained by short-term rates in
the advanced economies, while Table 6.2 reports how much of the short-term rates
in the advanced economies were explained by the first and second PCs in Asian
short-term rates. In both tables, we find no significant spillovers in either direction
throughout the subsample periods. This indicates that there were no significant
spillovers either from the advanced economies to Asia or from Asia to the advanced
经济体. This was true even after the GFC when central banks in advanced
economies adopted unconventional monetary expansion.
In the case of the European countries and the US, the variance decomposition
shows that some spillovers existed. 然而, in the case of Asian economies,
including Japan, the results show that the Asian economies’ own shocks explained
3The two factors are the K-ANSM(2), a fixed 12.5 basis point lower bound, and yield curve data with
maturities from 0.25 到 30 years with the sample beginning in 1995.
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108 Asian Development Review
桌子 5. Correlation of the Principal Components
with Short-Term Rates
(我) Pre-GFC period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
2nd PC 3rd PC
1st PC
−0.342 −0.367
0.294
0.042 −0.615 −0.103
0.703 −0.156
0.246
0.353
0.114
0.800
0.396 −0.020
−0.481
0.425 −0.451
0.376
(二) Post-GFC and pretapering period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
(三、) Tapering period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
2nd PC 3rd PC
1st PC
−0.312 −0.505
0.283
0.195
0.459
0.258 −0.599
0.239
0.292
0.666
−0.200
−0.517
0.478
0.410
0.283
0.515
0.402
0.310
1st PC
2nd PC 3rd PC
0.242 −0.126 −0.547
0.019
0.672
0.131
0.058 −0.014
0.636
0.696 −0.152
0.178
0.212 −0.702
0.021
0.812
0.062
0.094
GFC = global financial crisis, PC = principal component.
来源: 作者的计算.
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多于 90% of the short-term rate fluctuations. This indicates that the short-term
rates in emerging Asia are not only independent of those in the other regions but
also show no synchronization within the region.
六、. Spillovers of Long-Term Interest Rates
In the previous section, we found that there were no significant spillovers of
short-term interest rates either from the advanced economies to Asia or from Asia
to the advanced economies. The purpose of this section is to explore whether there
were any significant spillovers of long-term interest rates between emerging Asia
and advanced economies. Specifically, using daily differences of 5-year or 10-year
government bond yields, we explore the spillover effects between emerging Asia
and the advanced economies (IE。, 日本, 德国, 英国, and the US). 不像
short-term rates, long-term rates are difficult to control without being affected by
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Financial Spillovers in Asian Emerging Economies 109
桌子 6.1 Variance Decomposition of the Principal Components in
Asian Short-Term Rates (%)
(我) Decomposition of the 1st principal component
1st PC
Shock
97.28
98.41
98.90
Advanced Economies
全部的
日本
UK Euro Area
我们
1.21
1.46
0.56
0.68
1.05
0.35
0.07
0.27
0.06
0.35
0.13
0.12
0.11
0.02
0.04
Pre-GFC period
Pretapering period
Tapering period
(二) Decomposition of the 2nd principal component
2nd PC
Shock
95.74
99.12
98.78
Advanced Economies
全部的
日本
UK Euro Area
我们
2.05
0.37
1.15
1.32
0.06
0.17
0.35
0.13
0.26
0.30
0.16
0.10
0.09
0.02
0.61
Pre-GFC period
Pretapering period
Tapering period
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US =
美国.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
external shocks for each central bank. It is thus likely that long-term interest rates
have different spillovers across the regions. The estimated equations are essentially
the same as those in previous sections, except that we use daily differences of the
long-term interest rates as the endogenous variables. We estimate GVARs for the
three subsample periods.
In the analysis, we use PCA to extract common changes in long-term interest
rates of the five Asian economies. 桌子 7 reports the correlation of the first, 第二,
and third PCs with changes in 5-year or 10-year government bond yields in each
Asian economy. The table shows that in both government bond yields, the first PC
is positively correlated with each Asian long-term interest rate except with Thai
long-term rates. The correlations with Taipei,China’s long-term rates are relatively
small in the first and second subsample periods. But putting aside these outliers,
the other correlations lie between 0.37 和 0.6 in 10-year government bond yields.
They also tend to exceed 0.4 in 5-year government bond yields. This implies that
the first PC is a weighted average of Asian long-term interest rates.
相比之下, the second PC has a large positive correlation only with Thai
long-term interest rates. The degree of the correlation is over 0.8 except for 5-year
government bond yields in the first subsample period, which implies that the second
PC reflects mainly Thai long-term interest rates. It is likely that long-term bond
markets in Thailand were still less developed and were little affected by external
shocks.
Tables 8.1 和 8.2 report the variance decomposition over 10 business days
for the three subsample periods. 桌子 8.1 reports in percentages how much of the
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110 Asian Development Review
桌子 6.2 Variance Decomposition in Advanced Economies’
Short-Term Rates (%)
(我) Japan short-term shadow rates
Pre-GFC period
Pretapering period
Tapering period
日本
Shock
98.38
90.18
94.53
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
0.62
9.61
5.23
0.49
0.17
0.14
0.51
0.04
0.10
(二) UK short-term shadow rates
Pre-GFC period
Pretapering period
Tapering period
英国
Shock
89.65
93.07
91.83
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
7.34
6.86
1.86
1.75
0.06
0.15
1.26
0.01
6.16
(三、) Euro area short-term shadow rates
Pre-GFC period
Pretapering period
Tapering period
Euro
Shock
72.50
70.58
75.92
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
25.48
28.69
17.90
0.13
0.14
0.95
1.90
0.60
5.24
(四号) US short-term shadow rates
Pre-GFC period
Pretapering period
Tapering period
我们
Shock
71.53
71.09
68.42
Other Advanced
Economies
1st PC
Shock
2nd PC
Shock
27.31
28.06
30.10
0.98
0.53
0.27
0.18
0.31
1.21
GFC = global financial crisis, PC = principal component, UK = United Kingdom,
US = United States.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
first and second PCs in Asian long-term rates were explained by shocks in the four
advanced countries, while Table 8.2 reports how much of the long-term rates in the
four advanced countries were explained by the first and second PCs in Asia.
桌子 8.1 indicates that in both 5-year and 10-year yields, there were
significant spillovers from the advanced economies to the first PC in Asia
throughout the subsample periods. The spillovers were smaller than stock market
spillovers. But in the first subsample period, the long-term rates in the four advanced
economies explained more than 40% of the first PC. 尤其, US long-term
rates explained about one-fourth of the first PC in the first subsample period. 在
the second and third subsample periods, the explanatory power of the long-term
rates in the advanced economies declined because the first PC was explained more
by its own shocks. This indicates that intraregional spillovers increased in Asian
bond markets after the GFC. 然而, even in these subsample periods, 先进的
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Financial Spillovers in Asian Emerging Economies 111
桌子 7. Correlation of the Principal Components with Long-Term Rates
(我) Pre-GFC period
10-year bond yields
5-year bond yields
1st PC
2nd PC
3rd PC
1st PC
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
0.375
0.569
0.419
0.129
0.583
−0.054
(二) Post-GFC and pretapering period
0.165
0.007
−0.120
0.101
0.042
0.973
0.089
−0.083
−0.099
0.971
−0.131
−0.122
0.446
0.606
0.158
0.165
0.614
0.066
2nd PC
−0.304
0.027
0.745
0.167
0.018
−0.569
3rd PC
−0.117
−0.137
0.194
0.794
−0.100
0.538
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
(三、) Tapering period
Republic of Korea
香港, 中国
People’s Republic of China
Taipei,中国
新加坡
Thailand
10-year bond yields
5-year bond yields
1st PC
0.439
0.532
0.442
0.265
0.503
0.071
2nd PC
−0.077
−0.065
−0.116
0.546
−0.163
0.807
3rd PC
−0.224
0.267
−0.048
−0.723
0.260
0.535
1st PC
0.476
0.474
0.408
0.299
0.521
0.145
2nd PC
−0.005
−0.149
−0.149
0.304
−0.172
0.913
3rd PC
0.010
−0.121
−0.173
0.887
−0.167
−0.374
10-year bond yields
5-year bond yields
1st PC
0.457
0.488
0.390
0.394
0.493
0.057
2nd PC
−0.121
−0.048
0.013
0.063
−0.015
0.989
3rd PC
1st PC
0.225
−0.214
0.677
−0.665
−0.008
0.051
0.462
0.463
0.398
0.416
0.490
0.006
2nd PC
−0.030
0.077
−0.131
0.059
0.000
0.986
3rd PC
0.207
−0.352
0.746
−0.498
−0.049
0.163
GFC = global financial crisis, PC = principal component.
来源: 作者的计算.
economies’ shocks explained a significant part of the first PC’s fluctuations in
5-year and 10-year yields. After the GFC, spillovers from advanced economies were
slightly larger in 5-year yields than in 10-year yields. This may have happened
because unconventional monetary policy in advanced economies had increased
spillovers to Asia in 5-year yields.
In the case of the second PC, we do not infer significant spillovers from
the advanced economies to Asia in 5-year yields. In 5-year yields, the Asian
economies’ own shocks explained most of the second PC’s fluctuations throughout
the subsample periods. Noting that the PRC’s long-term interest rates have no
correlation with the first PC but have a large correlation with the second PC, 这
implies that the PRC’s 5-year interest rates have been determined independently.
然而, in the case of 10-year yields, shocks in the four advanced economies
explained more than 20% of the second PC in the second and third subsample
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112 Asian Development Review
桌子 8.1 Variance Decomposition of the Principal Components in Asian Long-Term
Rates (%)
(我) Decomposition of the 1st principal component
10-year yields
5-year yields
Pre-GFC period
Pretapering period
Tapering period
Pre-GFC period
Pretapering period
Tapering period
1st PC
Shock
52.31
81.82
77.88
56.23
72.74
68.73
Advanced Economies
全部的
日本
英国
德国
我们
47.37
15.43
19.84
43.53
22.06
24.42
3.30
2.59
2.25
2.94
2.75
2.48
15.04
3.92
5.56
12.27
6.89
9.02
4.33
1.75
0.89
2.00
1.29
0.70
24.69
7.17
11.13
26.32
11.14
12.22
(二) Decomposition of the 2nd principal component
10-year yields
5-year yields
Pre-GFC period
Pretapering period
Tapering period
Pre-GFC period
Pretapering period
Tapering period
2nd PC
Shock
56.23
70.15
60.76
96.58
95.95
97.16
Advanced Economies
全部的
日本
英国
德国
我们
43.53
29.24
37.21
2.42
3.39
2.01
2.94
3.89
3.34
0.47
0.79
0.10
12.27
6.50
9.71
1.11
0.35
0.38
2.00
4.92
1.72
0.36
0.08
0.10
26.32
13.94
22.45
0.49
2.18
1.43
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US = United States.
笔记: The table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
periods. This suggests that
the PRC’s 10-year yields experienced significant
spillovers from the advanced economies after the GFC even though the PRC’s
5-year yields were still controlled by the government.
相比之下, 桌子 8.2 shows that the first and second PCs in Asia explained
only a small percentage of the long-term rate fluctuations in the advanced
economies throughout the subsample periods. 那是, as in the stock markets,
spillover effects from advanced economies to Asia have been much larger than
those from Asia to advanced economies in the long-term bond markets. Among the
advanced economies, long-term rate fluctuations in Japan were explained mainly by
Japan’s own shocks and were explained very little by the other shocks throughout
the subsample periods. This may have happened because unconventional monetary
policy by the Bank of Japan induced extremely low long-term rates throughout
the sample periods. Even the long-term rate fluctuations in the other advanced
economies were mostly explained by their own shocks or by shocks in the other
advanced economies. This is in marked contrast with stock market spillovers in
which the first PC in Asia came to explain a significant percentage of stock return
fluctuations in the two European countries and the US after the GFC.
After the GFC, the first and the second PCs in Asia came to explain about
5% of long-term rate fluctuations in the UK, 德国, and the US. 例如,
in the UK, the two components in Asia explained 5.11% of 10-year yields and
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Financial Spillovers in Asian Emerging Economies 113
桌子 8.2 Variance Decomposition in Advanced Economies’ Long-Term Rates (%)
(我) Variance decomposition of Japan’s long-term rates
10-Year Yields
其他
5-Year Yields
其他
Japan Advanced 1st PC 2nd PC Japan Advanced 1st PC 2nd PC
Shock Economies Shock Shock
Shock Economies Shock Shock
Pre-GFC period
Pretapering period
Tapering period
92.45
82.42
86.71
7.28
17.10
11.96
0.08
0.16
0.96
0.20
0.32
0.36
93.59
83.32
93.40
6.28
16.44
6.33
0.05
0.21
0.25
0.07
0.04
0.03
(二) Variance decomposition of UK long-term rates
10-Year Yields
其他
5-Year Yields
其他
英国
Advanced 1st PC 2nd PC
Shock Economies Shock Shock
英国
Advanced 1st PC 2nd PC
Shock Economies Shock Shock
Pre-GFC period
Pretapering period
Tapering period
91.59
87.75
86.30
6.21
7.14
7.74
2.14
2.62
2.19
0.06
2.49
3.77
91.37
91.62
91.60
5.05
4.87
3.72
3.07
3.32
4.47
0.50
0.19
0.22
(三、) Variance decomposition of Germany’s long-term rates
10-Year Yields
其他
5-Year Yields
其他
German Advanced 1st PC 2nd PC German Advanced 1st PC 2nd PC
Shock Economies Shock Shock
Shock Economies Shock Shock
Pre-GFC period
Pretapering period
Tapering period
37.80
39.92
41.63
59.22
54.38
53.00
2.81
2.28
2.32
0.17
3.42
3.05
59.60
55.88
51.80
37.76
40.88
41.72
2.05
1.49
2.89
0.60
1.75
3.60
(四号) Variance decomposition of US long-term rates
10-Year Yields
其他
5-Year Yields
其他
我们
Advanced 1st PC 2nd PC
Shock Economies Shock Shock
我们
Advanced 1st PC 2nd PC
Shock Economies Shock Shock
Pre-GFC period
Pretapering period
Tapering period
38.42
60.31
61.53
57.30
37.88
34.83
3.81
1.80
3.17
0.47
0.01
0.46
69.81
60.67
64.10
28.14
36.56
30.76
1.84
2.41
5.09
0.22
0.36
0.05
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US = United States.
笔记: Table reports the variance decomposition over 10 business days after a shock.
来源: 作者的计算.
3.51% of 5-year yields in the second subsample period and 5.96% of 10-year yields
和 4.68% of 5-year yields in the third subsample period. This implies that after
the GFC, spillovers from emerging Asia to Europe and the US came to have some
significance even in bond markets. But these spillovers were much smaller than the
stock market spillovers in magnitude. Noting that stock market spillovers from Asia
to Europe and the US increased mainly because manufacturing sector shocks in
Asia had significant impacts on advanced economies, this result also supports the
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114 Asian Development Review
view that direct financial linkages from emerging Asia to advanced countries were,
如果有的话, small even after the GFC.
VII. Concluding Remarks
在本文中, we explored how financial market spillovers between emerging
Asia and advanced economies have changed in the 2000s. Stock market spillovers
from emerging Asia became significant in the post-GFC period. Even in long-term
费率, we found significant spillovers from emerging Asia to Europe and the US
in the tapering period. 然而, bond market spillovers were much smaller than
stock market spillovers in magnitude. 更重要的是, the industry-level analysis
showed that the stock market spillovers originated mostly from common shocks in
the manufacturing sector rather than from those in the financial sector. The financial
spillovers from emerging Asia increased in the post-GFC period because emerging
Asian economies were increasingly more connected with the rest of the world in
integrated global production networks. This supports the view that direct financial
market linkages from emerging Asia to advanced countries were, 如果有的话, limited
even after the GFC.
In the 2000s, emerging Asia underwent rapid industrialization in integrated
global production networks and their real fundamental shocks came to have
substantial spillover effects on advanced economies. Our empirical results are
consistent with the view that even though the financial market in emerging Asia
has been less developed, the increased role of Asian economies in integrated global
production networks raised spillovers from emerging Asia in the global financial
市场. 然而, limited direct financial linkages from emerging Asia to advanced
countries are still important policy agenda even after the GFC. This is particularly
true in Asian bond markets. In emerging Asia, we probably need further structural
reforms of financial markets, which may contribute to solving persistent external
imbalances in the global financial markets.
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附录. Shocks after the New York Stock Market Closes
In the main text, the order of the Cholesky decomposition in the global vector
autoregressions (GVARs) was set to be the variable in Japan, the first and second
PCs in Asia, the variable in the United Kingdom, the variable in Europe, 和
variable in the United States (我们). We chose the order because Asian financial
markets are open before European and New York markets open. 然而, 在里面
我们, some important news may be announced after the New York market closes.
One may have concern that our order of the Cholesky decomposition would identify
some shocks in the US as Japanese market shocks. The purpose of this Appendix
is to show that our results are essentially the same even if we control for spillover
effects of shocks after the New York market closes.
In the analysis, we split daily changes of Japan’s stock price index into
“daytime change” and “nighttime change.” The “daytime change” in date t is the
change of Nikkei 225 从 9:15 a.m. 到 3:30 下午. in date t. The “nighttime change”
in date t is the change of Nikkei 225 从 3:30 下午. in date t−1 to 9:15 a.m. 在
date t. In the GVARs, the order of the Cholesky decomposition was set to be the
daytime change in Japan, the first and second PCs in Asia, the variable in the United
王国, the variable in Europe, the variable in the US, and the nighttime change in
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Financial Spillovers in Asian Emerging Economies 117
Table A1.1 Variance Decomposition of the Principal Components in Asian Stock
Returns (%)
(我) Decomposition of the 1st principal component
1st PC
Shock
62.59
55.94
63.64
Pre-GFC period
Pretapering period
Tapering period
Advanced Economies
全部的
日本
英国
德国
我们
Nighttime
36.02
43.26
34.10
18.39
14.80
14.92
6.08
19.70
8.32
2.93
1.61
0.77
8.57
7.03
9.96
0.05
0.12
0.14
(二) Decomposition of the 2nd principal component
2nd PC
Shock
98.36
96.95
98.16
Pre-GFC period
Pretapering period
Tapering period
Advanced Economies
全部的
日本
英国
德国
我们
Nighttime
1.20
2.27
1.33
0.30
0.09
0.56
0.07
1.24
0.16
0.33
0.03
0.01
0.42
0.84
0.51
0.08
0.07
0.08
GFC = global financial crisis, PC = principal component, UK = United Kingdom, US = United States.
来源: 作者的计算.
日本. Given the order of the Cholesky decomposition, it is natural to suppose that
the “daytime change” would reflect shocks in Japan, while the “nighttime change”
would reflect shocks after the New York market closes but before Asian markets
打开.
By using the new order of the Cholesky decomposition, we examine stock
market spillovers between Asian and advanced financial markets. The estimated
equations are the same as those in section III, except that we use “daytime change”
and “nighttime change.” Using the first and the second PCs in Asia, we estimate
the GVARs for the three subsample periods. Tables A1.1 and A1.2 summarize the
results of the variance decompositions. Table A1.1 reports in percentages how much
of the first and second PCs in Asia were explained by shocks in the advanced
经济体, while Table A1.2 reports how much of stock prices in the advanced
economies were explained by the first and second PCs in Asia.
In both of the tables, the contributions of “daytime change” in Tables A1.1
and A1.2 are very similar to those of Japan’s daily stock returns in Tables 2.1 和
2.2. 更重要的是, the first and second PCs in Asia and the stock returns in the
other advanced countries have very similar contributions in Tables A1.1 and A1.2
to those in Tables 2.1 和 2.2. This implies that our results are essentially the same
as those in section III even if we split daily changes of Japan’s stock price index into
“daytime change” and “nighttime change.”
This happened because spillovers due to “nighttime change” are, 如果有的话, 非常
small in our estimated GVARs. 例如, in Table A1.1, the contributions of
the “nighttime change” are less than 0.1% in explaining the first and second PCs
in Asia. This implies that even if some important news were announced after the
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118 Asian Development Review
Table A1.2 Variance Decomposition in Advanced Economies’
Stock Returns (%)
(我) Japan’s stock prices
Pre-GFC period
Pretapering period
Tapering period
(二) UK stock prices
Pre-GFC period
Pretapering period
Tapering period
日本
Shock
97.40
95.66
97.84
英国
Shock
79.92
74.40
41.59
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
2.04
3.76
1.23
0.23
0.48
0.38
0.33
0.09
0.55
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
15.11
10.94
46.21
4.76
13.49
10.81
0.21
1.17
1.39
(三、) Germany’s stock prices
德语
Shock
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
Pre-GFC period
Pretapering period
Tapering period
(四号) US stock prices
Pre-GFC period
Pretapering period
Tapering period
37.24
22.33
35.91
我们
Shock
62.36
40.81
64.96
(v) Nighttime stock prices
55.43
66.38
51.89
7.05
9.79
10.81
0.28
1.50
1.39
Other Advanced
Economies
1st PC 2nd PC
Shock
Shock
35.00
51.40
28.75
2.43
6.30
5.88
0.21
1.49
0.42
Pre-GFC period
Pretapering period
Tapering period
Nighttime Other Advanced
Shock
47.83
49.14
49.08
Economies
46.17
46.05
46.51
1st PC 2nd PC
Shock
Shock
5.91
3.33
4.12
0.09
1.48
0.29
GFC = global financial crisis, PC = principal component, UK = United Kingdom,
US = United States.
来源: 作者的计算.
New York market closed, the news had negligible spillover effects on Asian stock
returns. 因此, even if we control their spillover effects, we still find that stock
market spillovers from emerging Asia became far from negligible in the post-GFC
时期, although financial market spillovers from the advanced economies to Asia
were much larger than those from Asia to the advanced economies.
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