JOURNAL OF SERVIC E SCIENCE AND MANAGEMENT
J. Serv. Sci.. & Management. 2008; 1:73-78
Published Online June 2008 in Scientific Research Publishing (www.SRPublishing.org/journal/jssm)
ServiceScienceandManagement June 2008
Empirical Research on Repo Rates Based on Exponenti-
al Smooth Transition Autoregressive Model
Qi-zhi He
School of Statistics, Anhui University of Finance and Economics, Bengbu 233030, P.R.china
ABSTRACT
In the process of China's marketization of interest rates, researching the characteristics of interest rates has very
important theoretical a nd practical significan ce. Based on Chinese interbank repo in terest rates, the characteristics of
daily interest rates and monthly interest rates and their spreads have been researched, and unit root tests are paid to
the level, the first difference and the spread of daily interest rates and monthly interest rates based on the traditional
method and the exponential smooth transition autoregressive method (ESTAR) respectively. The results show: Firstly,
as for different term of repo interest rates, the characteristics are different. Secondly, both lists of daily rates and
monthly rates are integrated of order 1. Thirdly, the spread of daily interest rates and monthly interest rates is not
stationary by use of ADF, but stationary b y use of ESTAR. Finally, the long-run eq uilibrium relationship b etween daily
repo interest rates and monthly repo interest rates is stab le with nonlinear adjustment.
Keywords: Repo interest rates, Unit root, Nonlinear, Augm ented Dickey-Fuller (ADF), Exponential smooth transition
autoregressive (ESTAR)
1. INTRODUCTION
Term structure of interest rates provides a characterization
of interest rates as a function of maturity. It is the
benchmark of assets pricing, financial product design, risk
management and investment such as discussed in
[1,2,3].Because of its numerous uses, estimation of the
term structure has received considerable attention from
researchers and practitioners, such as Xie Chi and Wu
Xiong-wei (2002), Xie Chi (2004,2005,2006), Zheng
Zhen-long and Lin Hai (2003,2004,2005,2006,2007),
ZHOU Rong-xie and QIU Wan-hua(2004),WANG
Xiao-Fang(2006), Fan Long-zhen(2006), He Qi-zhi
(2007)[4,5], etc..But most of the researches are only about
how to estimate the term structure of interest, and few
involved in the relationship between the different
maturities of interest rates.
The expectation theory regarding the term structure of
interest rates is one of the bases of finance and
macroeconomy. According to the expectation theory, the
yield spread between different-term interest rates is
stationary, or different-term interest rates have the
cointegration relationship with cointegrating vector (-1,1)’.
Thus it is helpful to judge the existence of the expectation
theory by checking the cointegration relationship between
different-term interest rates. Many documents have studied
the expectation theory by use of the traditional unit root
tests (DF and ADF)and cointegration tests (EG and AEG),
such as Campbell,J.Y. (1987, 1995) ,SHI Min,WANG
Shou-yang(2005)[6], and Wu Dan, Xie Chi(2005)[7],etc.
These traditional tests assume only linear adjustment.
There are, however, economic situations where a
non-linear adjustment process may exist [8]. For example,
policy intervention may take place only when the economy
deviates from equilibrium by a certain margin. The nature
of the policy action may also differ, depending on the
direction of that deviation. Another example is that
arbitrageurs enter the market only if the price deviation of
an asset from its no-arbitrage equilibrium is sufficiently
large to compensate for transaction costs. As to the
empirical research of the expectation hypothesis of the
term structure, for the sake of simplicity, many researches
have neglected the inherent nonlinear adjustment of the
term structure of interest rate. In fact, sometimes only
series of moderate length are available and the number of
observations is small. The small number of observations
and the market friction including transaction costs in
financial assets markets is likely to lead to nonlinear
speeds of convergence to equilibrium of rates of return,
and often lead to the nonlinear adjustment of term structure
of interest rates.
Recently, some authors have emphasized such nonlinear
features and adjustment of economic variables [9]. Typical
nonlinear time series models which appear useful in
practice concern various forms of regime-switches. Since
the seminal articles ofTer asvirtaa && and Anderson (1992)
and Ter asvirtaa && (1994), smooth transition autoregressive
(STAR) models have become one of most popular classes
of non-linear models in modern applied economics [10].
The STAR models have been employed in modeling the
dynamics of various types of economic time series, for
example industrial production in Ter asvirtaa
&& and
Anderson(1992),unemployment in Skalin andTer asvirtaa &&
(2002), interest rates in van Dijk and Franses (2000),
exchange rates in Taylor, Peel, and Sarno (2001), real

74 Qi-zhi He
ServiceScienceandManagement June 2008
interest and exchange rates in George Kapetanios,
etc.(2003)[11], inter alia. Most recently, Maki, Daiki
(2005, 2006) [12, 13] investigated the term structure of
interest rates in Japan using the nonlinear unit root test:
ESTAR. His results provide strong evidence against the
unit root of the yield spread between long-term and
short-term interest rates, compared with standard unit root
tests assuming only linear adjustment.
The purpose of this paper is to investigate the term
structure of interest rates in china using the unit root test in
the exponential nonlinear smooth transition autoregressive
(ESTAR) framework, as proposed by Kapetanios (2003).
Their ESTAR approach tests for a unit root against a
nonlinear stationary process based on the STAR process.
In that paper they analyzed the implications of the
existence of a particular kind of nonlinear dynamics for
unit root testing procedures, and provided an alternative
framework for a test of the null of a unit root process
against an alternative of a nonlinear exponential smooth
transition autoregressive (ESTAR) process.
The plan of the paper is as follows: section 2 addresses
the expectation theory and the traditional unit root test (DF,
and ADF). Section 3 introduces the nonlinear unit root test
proposed by Kapetanios (2003) and applied by Maki,
Daiki(2005,2006) in Japan. Section 4 presents empirical
applications in china. Section 5 provides a summary of the
paper, and contains some concluding remarks.
2. THE EXPECTATION THEORY REGA-
RDING TERM STRUCTURE AND THE U-
NIT ROOT TEST
2.1. The expectation theory regarding term
structure
The expectation hypothesis expressed by SHI Min,WANG
Shou-yang(2005) is as follows:
1
()( )()
0
1k
nmn
tttim
i
rEr
k
θ
−
+
=
=+
∑ (1)
Where n and m represent respectively the long term and
short term, k equal to [n/m], ()n
t
r is the time t continuously
compounded yield to maturity of the n period, ()m
tim
r
+
is the
time tim+ continuously compounded yield to maturity of
the m period, Et is the expectation operator based on
available information, and ()n
θ
denotes term premium.
Both sides of equation (1) subtract()m
t
r:
1
(, )()( )( )()
0
1
()( )()
01
1()
1
k
nmn mmm
ttt ttimt
i
ki
nmn
ttjm
ij
s
rrEr r
k
Er
k
θθ
−
+
=
−
+
==
=− =−
+= Δ+
∑
∑∑
Known from equation (2), if ()n
t
r，()m
t
rhave a unit root,
()( )nm
tt
rr− will be a stationary process, or ()n
t
r and ()m
t
r
have the cointegration relationship with cointegrating
vector (-1, 1)’. Thus we can test for cointegration using
unit root tests including the traditional unit root tests (DF
and ADF).
2.2. The traditional unit root tests (DF and ADF)
From theoretical and applied point of view, the traditional
unit root tests (DF) can be represented as follows1:
1ttt
yyu δ
−
Δ
=+
(3)
11ttt
y
yu
β
δ
−
Δ
=+ +
(4)
12 1ttt
ytyu
β
βδ
−
Δ
=+ ++
(5)
Where
δ
, 12
,
ββ
is the parameter,
δ
represents the
intercept, {t
y} denote variable list, t denote time or trend
variable, t
u

i.i.d. 2
(0, )
σ
.
A null hypothesis with a unit root implies that0
δ
=
.
The choice of formula (3), (4) or (5) is important since the
distribution of the test statistic under the null hypothesis
differs among these three cases.
When the errors in (3), (4) or (5) are serially correlated,
(3), (4) or (5) result in the following regression with
p-order augmentation (ADF):
1
1
m
ttitit
i
yy yu δα
−−
=
Δ
=+Δ+
∑ (6)
11
1
m
ttitit
i
yy yu βδ α
−−
=
Δ
=++Δ +
∑ (7)
12 1
1
m
ttitit
i
yty yu ββ δα
−−
=
Δ
=+++Δ +
∑ (8)
3. THE NONLINEAR UNIT ROOT TEST
(ESTAR) [11, 12, 13]
The traditional unit root tests only assume linear
adjustment, but the term structure of interest rates often has
the characteristics of inherent nonlinear adjustment
because of market frictions .Thus sometimes, wrong
conclusions will be drawn if using the traditional unit root
tests for term structure. In order to take into account such
nonlinear adjustment, this paper employs the unit root test
in the nonlinear exponential STAR framework developed
by Kapetanios, G., Y. Shin, and A. Snell (2003).
11
(;),1,, .
tt ttdt
yy yytT
β
γθ ε
−− −
=
+Θ +=L (9)
Where t
ε

i.i.d.(0, 2
σ
), and
β
and
γ
are unknown
parameters. The ESTAR model defines different regimes
in terms of small and large absolute deviations of the
transition variable values from the threshold parameter
value. Hence, this model has a ‘sandwich’ structure with
the outer regime that is contrasted with the inner regime
(Boriss Siliverstovs, 2005). The transition function of the
exponential form is as follows:
1 To know whether the DF model should include the intercept, the
intercept and the time trend or neither in the test regression,
, see [14].

Empirical Research on Repo Rates 75
Service Science and Management June 2008
2
(;)1 exp()
td
td
yy θθ
−
−
Θ=−−
(10)
Where it is assumed that0
θ
≥，and 1d≥ is the delay
parameter. The exponential transition function is bounded
between zero and 1;..ie Θ：R →[0, 1] has the
properties:
(0)0; lim()1
xx →±∞
Θ= Θ=
and is symmetrically U-shaped around zero.
Substituting (6) into (5) Kapetanios, G., Y. Shin, and A.
Snell obtain an exponential STAR (ESTAR) model,
2
11
[1 exp()]
tt ttdt
yy yy
β
γθε
−− −
=+ −−+
(11)
Both sides of equation (11) subtract1t
y−:
2
11
[1 exp()]
tt ttdt
yy yy
φ
γθε
−− −
Δ=+− −+ (12)
where 1
φ
β =−
.
The application that motivates the model is that of Sercu
et al. (1995) and of Michaelet al. (1997).These authors
analyse nonlinearities in the PPP relationship. They adopt
a null of a unit root for real exchange rates and have an
alternative hypothesis of stationarity, namely the long run
PPP. Their theory suggests that the larger the deviation
from PPP, the stronger the tendency to move back to
equilibrium. In the context of the model, this would imply
that while 0
ϕ
≥ is possible, we must have0
γ
<
and
0
ϕ
γ +<for the process to be globally stationary. They
claim that the ADF test may lack power against such
stationary alternatives and one of the contributions of this
paper is to provide an alternative test designed to have a
power against such an ESTAR processes.
More formally, geometric ergodicity and the associated
asymptotic stationarity can be established by the drift
condition of Tweedie (1975). A variant of the condition
states that an irreducible aperiodic Markov chain t
y
is
geometrically ergodic if there exists
constants 1
δ
<,B,L <∞ and a small set C such that
1
[/],,
tt
EyyyyLy c δ
−=< +∀∉
1
[/], ,
tt
EyyyByc
−=≤∀∈
The concept of the small set is the equivalent of a
discrete Markov chain state in a continuous context. For
more details see Tweedie (1975), Balke and Fomby (1997)
and Kapetanios(1999).
Following the practice in the literature (e.g. Balke and
Fomby, 1997, in the context of TAR models and Michael
et al., 1997 in the context of ESTAR models),
Kapetanios(2003) and Daiki Maki (2005,2006) impose
0
ϕ
=in (12), implying that t
y
follows a unit root process
in the middle regime. Kapetanios(2003) and Daiki Maki
(2005,2006) consider a null hypothesis that is a special
case of a linear unit root which in terms of the above model
implies that 0
ϕ
=
and 0
θ
=.Under the alternative
hypothesis (0
ϕ
=
but0
θ
>), thent
yfollows a nonlinear
but globally stationary process provided that −2 <
γ
< 0,
which we assume holds. In practice, there is likely to be
little theoretical or prior guidance as to the value of the
delay parameter d. We would suggest that d be chosen to
maximise goodness of fit over d = {1, 2, max
,dL}.In what
follows, to clarify ideas and in keeping with empirical
practice to date (as in for example Michael et al.),
Kapetanios(2003) and Daiki Maki (2005,2006) set d = 1.
Imposing φ = 0 and d = 1 gives their specific ESTAR
model (12) as
2
11
[1 exp()],
ttt t
yyy u γθ
−−
Δ
=−−+
(13)
Hence we test
0
H
:0
θ
=
, (14)
Against the alternative
1
H
:0
θ
>. (15)
Obviously, testing the null hypothesis (14) directly is
not feasible, since γ is not identified under the null. If we
compute a first-order Talyor series approximation to the
ESTAR model under the null we get the auxiliary
regression
1
3,
t
t
yyerror δ
−
Δ= + （16）
This suggests that we could obtain the t-statistic for δ =
0 against δ < 0 as
^^
/..(),
NL
tse
δ
δ = （17）
Where
^
δ
is the OLS estimate of
δ
and ^
..()se
δ
is the
standard error of ^
δ
. Their test is motivated by the fact that
the auxiliary regression is testing the significance of the
score vector from the quasi-likelihood function of the
ESTAR model, evaluated at θ = 0. Unlike the case of
testing linearity against nonlinearity for the stationary
process, the NL
t test does not have an asymptotic standard
normal distribution.
When the errors in (13) and (16) are serially correlated,
(13) and (16) result in the following regression with
p-order augmentation:
2
11
1
[1 exp()],
p
tjtjt tt
j
yyy yu ργ θ
−− −
=
Δ
=Δ+ −−+
∑ (18)
1
3
1
t
p
tjtj
j
yyyerror ρδ
−
−
=
Δ=Δ ++
∑ （19）
We can test the unit root via (18) instead of (13) and (19)
instead of (16).
4. DATA AND EMPIRICAL RESULTS
In this paper, we employ the monthly interest rates of
treasury bonds repurchase trading of national interbank

76 Qi-zhi He
ServiceScienceandManagement June 2008
market as long-term interest rates, expressed as R1M, daily
interest rates as short-term interest rates, expressed as R1.
It is because of the following reason to choose repurchase
interest rate data [15]. First, repurchase interest rate of
interbank market is the main variety of interest rate in
China’s money market. In regards to the trading structure
of money market, the amount of repurchase trade has a
larger proportion in total transaction amount than that of
trade in the Offered Market and Bond Market. Second,
repurchase interest rate of interbank market is not only the
tool of controlling and adjusting economics to every
country’s central bank, but also one of important standards
to decide the loan and deposit rate to commercial banks.
The daily data obtained from www.ChinaMoney.com.cn
consists of 572 periods between 2004:8-2006:1. Fig. 1
provides the change situations of R1, R1M and profit
spread (R1M-R1). According to Fig. 1 and footnote○
1, it
can be confirmed: Empirical tests to R1 and R1M should
include the intercept without the time trend, and empirical
test to profit spread=R1M-R1 should not include the
constant or the time trend. Tab.1 gives the simple statistics
characteristics of them.
4.1. Tests for nonlinear of interest rates
For simplicity, we estimate the nonlinear effect
θ
imposing 1
γ
=− on equation (12), similar to
Kapetanios(2003)、Daiki Maki (2005,2006). From Table 2,
we can know that R1M does not have
θ
at a significant
level, and R1 and the yield spread has a significant
θ
. This
estimation shows that R1M do not have nonlinear
adjustment, but R1 and the yield spread have nonlinear
adjustment.
As for the criteria to determine the appropriate length of
the distributed lag, we use the Akaike info criterion (AIC),
Schwarz criterion (SC) and t-sig. As to the Akaike info
criterion (AIC) and Schwarz criterion (SC), we select the
model with the smallest information criterion. As to t-ing,
we set the maximum lag=12. t-ing selects the lag order k
via top-down testing. To begin with, we estimate the
equation with the maximum lag (here, the maximum lag
kmax=12). We use the lag order if the t-statistic of the
parameter of the maximum lag is significant. If the
t-statistic is not significant, we estimate the equation with
the lag=kmax - 1. That is, when the t-statistic of the
parameter of the lag=kmax -q is significant at a conventional
level, we employ the lag order (Daiki Maki, 2005).
4.2. Unit root tests
ADF and ESTAR denote the unit root tests by Dickey and
Fuller (1979) and Kapetanios et al. (2003), respectively.
As shown in Table 3, all of the tests do not reject the unit
root of interest rates at the level, but reject the unit root of
interest rates at first-order difference. Therefore, the results
show that interest rates is integrated of order 1, namely I (1)
process.
4.3. Cointegration tests
According to the expectation theory, if different term
interest rates are all integrated of order 1 :I(1),the yield
spread between different term interest rates are stationary,
or different term interest rates have the cointegration
relationship with cointegrating vector (-1,1)’. Table 4
shows the results of the unit root tests of the yield spread.
The results of ADF test fail to reject a unit root at a 1%
significance level according to either criterion, even at a
5% according to AIC and t-ing criterions. In contrast, the
test by Kapetanios et al. (2003) provides strong evidence
against the unit root of the yield spread at a 1%
significance level, even when different lag criterions are
employed. This finding asserts that the long-run
equilibrium relationship between different term interest
rates is stable with nonlinear adjustment.
Fig.1 Interest rates of repurchase trading
5. CONCLUSION
The paper has researched the characteristics of Chinese
interbank repo interest rates, and the relation between
Chinese interbank repo interest rates with different
maturities. The traditional unit root test ADF and the unit
root test in the exponential nonlinear smooth transition
autoregressive (ESTAR) framework are introduced and
applied to the reality of Chinese financial market. Main
conclusions are as follows:
First, the monthly interest rates R1M do not have the
characteristic of nonlinear adjustment, but R1 and the yield
spread have the characteristic of nonlinear adjustment.
Second, both lists of monthly interest rates R1M and
daily interest rates R1 are integrated of order 1 :I(1),
whatever tested by ADF test or tested by ESTAR proposed
by Kapetanios et al. (2003).
Third, if we test the spread R1M-R1 by use of ADF, No
matter use AIC, sc information standard or t-sig criterion,
it will not refuse unit root at at a 1% level (AIC informati-

Empirical Research on Repo Rates 77
Service Science and Management June 2008
Tab.1 Sample descriptive statistics
Variables Observatio
ns
Mean Max Min Std. Dev Skewness Kurtosis
R1 605 1.650762 3.6029001.0530000.482511 0.903755 4.232855
R1M 572 2.071604 3.5347001.1904000.589263 0.190826 1.879266
Table 2 Tests for nonlinearityA
R1 R1M sperad
θ
t
θ
θ
t
θ
θ
t
θ
AIC 16.64400(9) 2.676826**8.271662(9) 1.647177517.3570(5) 2.889583**
sc 17.08785(8) 2.759931**7.379115(8) 1.470843660.7691(2) 3.725535**
t-sig 17.08785(8) 2.759931**5.405781(5) 1.026662517.3570(5) 2.889583**
Annotate: A Parentheses show lag length.
*(**) Significant at a 5 %( 1%) level to refuse.
Tab. 3 U nit root t ests for r epo rates B
methods ADF STAR
variables R1 R1M R1 R1M
level:
AIC -2.724232(9) -2.273499(9) -2.706878(9) -1.654935(9)
sc -2.845593(8) -2.147877(8) -2.793031(8) -1.477065(8)
t-sig -2.845593(8) -1.801322(5) -2.793031(8) -1.029404(5)
first difference:
AIC -7.520771**(12) -8.221985**(12) -3.460175**(12) -6.318140**(12)
sc -7.520771**(12) -8.221985**(12) -3.460175**(12) -6.318140**(12)
t-sig -7.176747**(7) -16.14545(12) -3.397295* (9) -6.293071** (8)
Annotate:
B Unit root tests are sensitive to lag length, we determine lag length
using three lag criterions: the Akaike Information Criterion and
Schwarz Criterion and t-sig introduced by Ng and Perron(1995).see[1].
*( **) Significant at 5 %( 1%) level to refuse.
Tab.4 Unit root tests for the yield spread
ADF ESTAR
AIC -1.571899(5) -3.035473** (5)
sc -2.340362* (2) -3.939495** (2)
t-sig -1.571899(5) -3.939495** (2)
Annotate :*( **) Significant at a 5 %( 1%) level to refuse.
on standard and t-sig criterion even at at a 5% level).Thus
we can get the wrong conclusion that the spread R1M-R1
is not a stationary list and the expectation theory can not
come into existence.
Forth, if we test the spread R1M-R1 by use of ESTAR,
after considering non-linear adjustment, No matter use
AIC, sc information standard or t-ing criterion, it will
refuse unit root at a 1% level. Thus the spread R1M-R1
have the cointegration relationship with cointegrating
vector (-1, 1)’, and then we can get the conclusion to
support the expectation theory.
The results provide strong evidence against the unit root
of the yield spread between daily interest rates and
monthly interest rates. The findings show that the long-run
equilibrium relationship between different term interest
rates is stable with nonlinear adjustment. Moreover, the
applied cointegration tests with non-linear adjustment
have multidimensional generalizations, and can be used
to many other variables. For example, the number of

78 Qi-zhi He
ServiceScienceandManagement June 2008
observations of most macroeconomic variables,
measuring the business cycle, is small, because those
variables are sampled only quarterly or annually. Thus,
there are also nonlinear properties in those
macroeconomic variables with a small number of
observations. We can also apply the ESTAR model to
research the relation between the variables.
6. ACKNOWLEDGEMENTS
The achievements of young fund project of humanities and
social science of education ministry（No. 07JC790028）;
The achievements of young fund project of Anhui
Province Office of Education(2007jql082); The
achievements of project of humanities and social science
of Anhui Province Office of Education(2007sk120).
REFERENCES
[1] Martellini，L. and Priaulet，P.， Fixed-income
Securities， John Wiley & Sons,Ltd. ，Chich es ter ，
2001.
[2] ZHU Shi-wu, CHEN Jian-heng, “Empirical Research
of the Term Structure of Interest Rates of Stock
Exchange”, Journal of Financial Research, 2003,
Vol.280（10）, pp.63-73.
[3] HE Qi-zhi, HE Jian-min, “Real Option Pricing
Method for R&D Investment under Changing Risk-free
Rate and Discount Rate”. Journal of Southeast University,
2008, Vol,2.
[4] HE Qi-zhi, “A New Method for Heteroscedasticity of
Term Structure Model Using Exponential Splines”,IEEE.
International Conference on Communications, Services,
Knowledge and Engineering, Shanghai, 2007,
pp.4068-4071.
[5] He Qi-zhi, “Empirical Tests for Term Structure of
Interest Rates Based on Nonlinear Adjustment , ” IEEE.
International Conference on Wireless Communications,
Networking and Mobile Computing, Shanghai, 2007,
pp.4096-4099.
[6] SHI Min, WANG Shou- yang,etc, “Empirical analysis
on term structure of China interbank offered rates”,
Journal Of Management Sciences in China,2005,Vol. 5,
pp.43-49.
[7] Wu Dan, Xie Chi, “Test of the Expectations Theory of
the Term Structure of Treasury Market Among China
Banks”,Chinese Journal Of Management, 2005，Vol.9(5),
pp.536-541.
[8] Ying Liu, “Modeling Mortgage Rate Changes with a
Smooth Transition Error-Correction Model”. Working
paper, 2001.
[9] Dick van Dijk, Philip Hans Frances, and Lucas，
“Testing for Smooth Transition Nonlinearity in the
Presence of Outliers”, working paper.
[10] Siliverstovs, Boriss, “The Bi−parameter Smooth
Transition Autoregressive model”, Economics Bulletin,
2005, Vol.3, No. 22, pp. 1−11
[11] Kapetanios, G., Y. Shin, and A. Snell, “Testing for a
unit root in the nonlinear STAR framework”, Journal of
Econometrics, 2003,Vol. 112, pp.359-379.
[12] Daiki,Maki，“ Non-linear adjustment in the term
structure of interest rates: a cointegration analysis in the
non-linear STAR framework”, Applied Financial
Economics,2006, Vol.11, pp.1301-1307.
[13] Daiki,Maki, “ The term structure of interest rates
with nonlinear adjustment: Evidence from a unit root test
in the nonlinear STAR framework”,Economics
bulletin,2005, Vol.5, pp.1-7.
[14] ZOU Ping,Financial Econometrics, Shanghai
University of Finance & economics Press, Shaihai, 2005,
8.
[15] Wen Bin, “An Empirical Study on the Choice of
Benchmark Interest Rate after Interest Rates
Liberalization in China”, Studies of International Finance,
2004, Vol. 11, pp.54-60.
[16] Duffee, G., “Term premia and interest rate forecasts
in affine models”, Journal of Finance , 2002 , Vol.57,
pp.405-443.
[17] Gerlach S,Smets F, “The term structure of
Eurorates:Some evidence in support of the expectations
hypothesis”,Journal of International Money and Finance,
1997, Vol. 16(2), pp.305-321.
[18] Hamilton J., Kim D. H, “A Reexamination of the
Predictability of Economic Activity Using the Yield
Spread”, Journal of Money,Credit, and Banking,2002,
Vol. 34(2), pp.340-344.
[19] William Poole, “Understanding the Term Structure
of Interest Rates”, Federal reserve bank of st.louis review,
2005, Vol. 9, pp.589-595.
[20] Caner, M., Hansen, B.E., “Threshold autoregression
with a near unit root”. Econometrica, 2001, Vol, 69,
pp.1555-1596.
AUTHOR’ BIOGRAPHY
He Qi zhi (1974—), male, Lecturer, graduate. The paper is an extended version of the paper “Empirical Tests for Term
Structure of Interest Rates Based on Nonlinear Adjustment” accepted by Management Track within WiCOM:
Engineering, Services and Knowledge Management (EMS 2007), and I am very thankful for the excellent suggestions
from the JSSM Editorial Board. Email: