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THE RELATIONSHIP BETWEEN INFLATION RATE AND
NOMINAL INTEREST RATE IN BOLIVARIAN REPUBLIC OF
VENEZUELA: REVISITING FISHER’S HYPOTHESIS
Mustafa Kasim, PhD student
School of Management
University of Brighton, United Kingdom
Bentouir Naima, Assistant Professor
Department of Economics, Management and Commercial Sciences
Ain Temouchent University, Algeria
Abstract
Stability of economics over the world represented by understanding the
relationship among the interest rate and inflation rate. This paper investigates the
relationship between inflation rate and nominal interest rate based on Fisher equation,
using a monthly frequency data in case of Venezuela between 1/1/1990 to 31/12/2016.
The Dickey Fuller (ADF) test and Phillips-Perron (PP) test both have empirically used
to check the unit root. Also, Johansen for Co-integration test is exploited to study the
equilibrium relation for long run between the inflation rate and the nominal interest
rate in the time series data. The result shows that both variables are non-stationary at
Level I (0) in both tests (ADF and PP), after converting the variables to first difference
I (1) with taking the log both of interest rate and inflation rate become stationary. The
Johansen co-integration null hypothesis is failed to be rejected in both tests Trace-
statistics test and Max-Eigen statistics. This means that the long-run equilibrium
relation between the inflation rate and nominal interest rate in Venezuela during 1990
to 2016 is not existed, i.e. the Fisher hypothesis does not hold through the sub-period
in Venezuela.
Keywords: nominal interest rate, inflation rate, Fisher Hypothesis, United
Kingdom, co-integration, relationship, Johensen test, Bolivarian Republic
JEL Codes: E31, E43
Received: August 27, 2018
Revision: November 9, 2018
Accepted: November 14, 2018
Kasim, M. and Naima, B. (2018), “The Relationship
Between Inflation Rate and Nominal Interest Rate in
Bolivarian Republic Of Venezuela: Revisiting Fisher’s
Hypothesis”, Journal of Applied Management and
Investments, Vol. 7 No. 4, pp. 214-224.
Introduction
Studying the causal relationship between inflation rate and short-term interest
rate (nominal rate) recently becomes under consideration, whereas the economists has
resumed looking at this relation after negligence from the early 1930s to the late of
1960s (Wood, 1981), when the economic situation has dramatically changed (Li and
Zheng, 2017), the relationship between these both rates commonly known as the Fisher
equation. The Fisher equation can be defined as one-to-one relationship between the
expected inflation and the nominal interest rate, assuming the real interest rate is
stationary, constant (Fisher, 1930). The co-movement of expected inflation and
nominal interest rate is of crucial interest for central banks and investors. If the Fisher
hypothesis does hold, the real interest rate must be independent of changes in inflation
and monetary shocks at any given time (Ray, 2012).
215
The relationship between the interest rate and the inflation has attracted much
attention in recent years, since 1930s when Irvin Fisher presented his equation to
examine this relationship, which is maintains that the nominal interest rate is the sum
of the constant real rate and the expected decline in the purchasing power of money.
For the several years money has been a central issue in monetary policy making, when
the economic world is changing rapidly and targeting monetary becomes less and less
attractive, effective attraction of investments is one of the most urgent problems of
governance of the world community (Sharapatyuk, 2016), but the instability of money
demand function is the main reason to keep this subject as one of the most debatable
studies, wherein the authorities give a big importance to controlling the nominal
interest rate at the money market, and monitor the behaviour of real rates.
Testing the relationship between the nominal interest rate and the inflation rate is
important for many reasons such as the fundamental role of interest rate on
investments, savings when the interest rate became as the key component of the
financial market, banks face transformation in the evolution of interest rate
liberalization (Wang, 2016), and other operations, which are executed based on this
variable, as well as the big impact on the monetary policies, economic and financial
models such as the capital asset pricing model (CAPM).
The emerging economies are becoming increasingly important in the world
economy, representing more than 50% of the world population (Dash, 2017). The
importance of choosing Venezuela as a case study, comes from it has been full swing
the highest inflation rate in 2017 by 652.67 percent compare with the previous year
according to Statista (2018). So, we think that Venezuela is a good example to study
the relation among the aforementioned variables by looking at the nominal interest rate
and studying whether it can be determined the expected inflation rate. This paper has
organized in six chapters; Introduction, Literature Review, Data and Methodology,
Result and Discussion, Conclusion and lastly References list.
Literature Reviews
Theoretical Framework
Fisher equation is also known as Fisher hypothesis which suggests that there
exist a positive relationship between rates of interest (nominal) and expected inflation.
Fisher equation or hypothesis provides theoretical basis for studying the relationship
between the interest rate and expected inflation. The implication of the Fisher equation
affects the debtors and creditors and also important for the effectiveness of the
monetary policy and efficiency in banking sectors. The Fisher hypothesis supports
strongly the US economy in particular and for the industrial countries in general
(Hassan, 1999).
Equation of Fisher hypothesis can be defined as:
IFRNIRRIR
or
IFRRIRNIR
, (1)
where NIR is the nominal interest rate, RIR is the real interest rate and IFR is the
inflation rate then Fisher.
The Fisher equation states that a one-unit increase in IFR causes a one-unit
increase in the nominal interest rate (Elhindi), this one to one relation between inflation
and nominal interest rate is known as Fisher effect.
216
Critical Literature Reviews
Revisiting the relationship between the interest rate and inflation rate, which is
known as a Fisher effect have become a widely investigated, to confirm whether the
Fisher hypothesis still a valid to represent the relationship between these two variables.
Many researchers have found that the Fisher hypothesis is hold in long term, i.e.
a positive relationship between the interest rate and inflation rate is appeared. Hence
some of them ( Phylaktis and Blake, 1993) studied the relation between the two rates
(interest and inflation) in three countries have a high background inflation rate these
are; Argentina, Brazil and Mexico. This study has concluded that there is a long run
equilibrium relationship among the nominal interest rate and inflation. Another study
was done by Hassan (1999), where it was used a quarterly data from 1957 Q1 to 1991
Q2 by applying co-integration technique for Pakistan. Hassan (1999) concluded that
there exists a long run relationship between the nominal interest rate and inflation.
Million (2004) utilized a monthly data for treasury bills rate and consumer price index
between January of 1951 to December of 1999. The Fisher effect was strongly
appeared in a situation where the stochastic trend in excited in both the inflation and
the nominal interest rate and in such situation, he found strong correlation between the
inflation and nominal interest rate. Also in the same year Granville and Mallick (2004)
have found that a long run relationship between the nominal interest rate and inflation
rate, when they were using Johansen co-integration of annual data for the UK between
1900 to 2000. Later, Macri (2006) has used Johansen technique of co-integration to
analyses a quarterly short-term data from first quarter of 1979 to second quarter of
2005 for Australia. There is a positive long run co-integration relationship between the
nominal interest rate and inflation rate in Australia. Westerlund (2008) studied Fisher
effect for the 20 countries of OECD. The panel quarterly data from 1980 to 2004
collected and using co-integration techniques. The result showed that there is an
exciting of relationship between the interest rate and inflation rate in data. Beyer and
Haug (2009) studied Fisher hypothesis for 15 countries of OECD using co-integration
techniques like ARDL and Johansen co-integration test. Similarly, they found the
Fisher co-integration relationship is exciting through OECD countries in long term.
Lastly, Saeidi and Vailan (2011) have used an annual data ranging from 1991 to 2009
in Iran. They found that the Fisher hypothesis effect is valid in Iran in short, midterm
and long term. Furthermore the study of Teker et al. (2012) investigated on the long-
run relationship between the interest and the inflation rates in Turkey during the period
of 2002 to 2011 using threshold vector error correction (T-VEC) analysis. The results
showed that if the percentage change in the difference between inflation and interest
rates is more than 11%, this status distinguishes the effect of error correction, and in
situations where the difference is above the threshold value, a shock experienced in
interest rates rapidly converges to equilibrium, finally According to the T-VEC
equations; the interest rate and the inflation are positively affected by their past two
and one periods respectively. Ayub et al. (2014) have studied the casual of relationship
between inflation rate and interest rate in Pakistan through the sub-period 1973 to
2010, using both ADF and PP tests of unit root and co-integration technique like
Johanson and Engle Granger, the result of studying showed that existing of relationship
between the inflation rate and interest rate. Baciu (2014) highlighted the significant
statistical connections between the inflation rate and the main macroeconomic
variables in Romania covering the period of 1997-2013 applying the explorative
217
method of principal components Analysis. The main findings presented on the period
of June 1997- July 2005 the inflation rate is strongly correlated with the growth of
monthly net average nominal wage, other findings showed the period after adoption of
the direct targeting regime in August 2005; also it is observed a strong correlation
between the inflation and the reference interest rate.
There are another researchers group have found that Fisher hypothesis has not
always excited, where the relationship between the interest rate and inflation rate in
one country can be different from period to other. Lanne (2001) has used unit root test
and co-integration test for the US monthly data for period January 1953 to December
1990, and the result showed that Fisher effect showed the validity over the period of
1953:1 to 1079:12. Whereas the over the other time laps i.e. from 1979:11 to 1990:12
the data showed no validity of the Fisher hypothesis. Berument and Mehdi (2002) have
investigated the effect of Fisher hypothesis for 26 countries, and they concluded that
some of these countries supported the relation between the inflation and interest rate in
long term. While the other some were not. Sundqvist (2002) studied the empirical
investigation of Fisher effect for six countries in the long term, a using quarterly data
between 1993 to 2000, the result concluded that the US and Japan have support what
Fisher hypothesis has pointed out, while the rest of country were not. Alexander (2006)
studied the relationship between the nominal interest rate and expected inflation rate
for South Africa. Using co-integration technique for the period of 2000 to 2005, the
study concluded that the short run relationship did not verify empirically whereas in
the long run relationship the data verify the Fisher Equation for South Africa. Ergene
(2015) attempted to examine the dynamic relationship between inflation, growth and
interest rate under the informal economy using panel VAR and quarterly data during
the period of 1960 to 2010, this paper contributed by given some results such as, the
interest rate has a negative impact on both growth and the size of informal activities,
while inflation does not have a significant effect on them, other results concluded that
the fluctuations in interest rate are mostly carried out by the changes in inflation. The
causal relation from inflation to interest rate is significantly stronger than the causal
relation from interest rate to inflation.
While Ahmed and Abdelsalam (2017) examined the existence of the augmented
version Fisher hypothesis including the inflation instability in Egypt during the period
of 1997 to 2017, using the different ARCH family models; (ARCH-M), (E-GARCH),
(APGARCH), (EGARCH (1,1,1) -M. the main results of this examination concluded
that predicted inflation has a positive and significant impact in the first regime while it
insignificant in the second regime, other finding showed that there is no relationship
between the expected inflation and interest rate in both regimes, which is explained by
the weakness of money market.
Third group of researches these have found counter result of exciting the relation
between the interest rate and inflation rate in long term Paleologos and Georgantelis
(1999) have applied a Johnsons technique of co-integration analysis for Greece from
the period of first quarter in 1980 to the second quarter in 1996, in order to study the
Fisher hypothesis validity for economy of Greece, they concluded that there is no one
to one movement in nominal interest rate and inflation rate in long run for Greece
economy. Herwartz and Reimers (2006) investigated the co-integration link between
the inflation and nominal interest rate for around monthly time series data of 43 years
of 114 for period of 1960:1 to 2004:6. The result showed that there exists a long run
218
relationship between nominal interest rates and inflation for number of the countries of
the world under consideration. They also added that, although of finding either a high
inflation rate or interest rate, the long run relationship not exists as mentioned by
Fisher. Gul and Acikalin (2008) studied the effect of Fisher hypothesis in Turkey
between 1990 to 2003, using Johansen co-integration method, the result highlighted
that it is possible to determine the long-run relationship, but not the one-to-one relation
between nominal interest rates and inflation, meaning that the full Fisher hypothesis
does not hold. Charles et al. (2018) used modified consumer spending model during
the period of 1981 to 2011 in Nigeria, in order to testing the effects of interest and
inflation rates on consumer spending, the study based on the causal relationship
between the consumer spending, interest and inflation rates using Granger causality
Wald test. They concluded that indirect tax and savings as important determinants of
PCE in Nigeria, the result of the Granger test concluded that future interest and
inflation rates cannot be predicted using PCE.
The Data
To investigate the relationship between the aforementioned variables and in
conformity with the availability of the necessary data and an accepted number of
observations, data has been chosen from the Federal Reserve Bank of St. Louis and
IECONOMICS websites. The data are in monthly frequency for Venezuela from
01/01/1990 to 31/12/2016, including 324 observations.
First variable is a Consumer Price Index is used to indicate an increase in
domestic prices of the commodities relatively more than increase in the prices of the
commodities globally. It indicates the increase in the prices of goods and service over
the time. And the other variable is a nominal interest rate refers to those interest rates
which are considered before taking inflation into consideration or before adjusting the
interest rate for inflation. And when the nominal rates adjusted for the inflation are
called real interest rate (Shah and Waleed, 2010).
Figure 1. Fisher Hypothesis Relationship
Source: Statista (2018)
The Log has been taking for both variables in order to get stationary data at the
219
same order, as the CPI always gets stationary at second order I (2). In addition to that,
the rate of interest that has been used through this paper is a short-term interest rate
(three months Deposit rate). The Fisher hypothesis implies that short-term interest rates
can efficiently predict future inflation trends.
The Hypothesis of Study
H0: There is a long-run relationship between the nominal interest rate and the
inflation;
H1: The long-run relationship between the nominal interest rate and the inflation
does not exist.
Methodology
Unit Root Test
The co-integration test among the study variables requires a previous test for the
existence of a unit root for each variable, using the Augmented Dickey–Fuller (ADF)
(1979) test on the following regression:
The ADF regression tests for the existence of unit root of, namely in all model
variables at time t. The variable expresses the first differences with lags, and is a
variable that adjusts the errors of autocorrelation. The coefficients are to be estimated.
The null and the alternative hypothesis for the existence of a unit root in variable is:
0H0
vs
0H1
.
Co-integration and Johansen test
Granger and Newbold (1974) have highlighted that, in terms of time series, if the
variables are non-stationary in their levels, they can be integrated with integration
order 1, when their first differences are stationary. These variables can be co-integrated
as well, if there are one or more linear combinations among the variables that are
stationary. If these variables are co-integrated, then there is a constant long-run linear
relationship among them. There are two important ways to test for co-integration. The
Engle and Granger methodology (1987) seeks to determine whether the residuals of the
equilibrium relationship are stationary. The Johansen (1988) and Stock-Watson (1988)
methodologies determine the rank of (π) which equals the number of co-integration
vectors.
Enders (2004) explained the Engle-Granger testing procedure; he began with the
type of problem likely to be encountered in applied studies. Suppose that two variables
and are believed to be I (1) and we want to determine whether there exists an
equilibrium relationship between these two variables. Therefore, we need to estimate
the long-run equilibrium relationship in the form:
tt10t ezy
. (2)
In order to determine if the variables are actually co-integrated denote the
residual sequence from this equation
t
e
ˆ
. Thus, the
t
e
ˆ
series are the estimated
values of the deviation from the long-run relationship. If these deviations are found to
be stationary, the
t
y
and
t
z
sequences are co-integrated of order 1. It would be
convenient if we could perform ADF test on these residuals to determine their order of
220
integration in the form:
tt1tt e
ˆ
e
ˆ
ye
ˆ
. (3)
Since the
t
e
ˆ
sequence is a residual from a regression equation, there is no
need to indicate an intercept term; the parameter of interest in is, where
1py
. If the
null hypothesis cannot be rejected
0y
, then it means that the residual series contain a
unit root. Hence, we conclude that
t
y
and
t
z
sequences are not co-integrated.
Instead, the rejection of the null hypothesis implies that the residual sequence is
stationary and we conclude that
t
y
and
t
z
sequences are co-integrated. If the
variables are co-integrated, the residual from the equilibrium regression can be used to
estimate the error correction model (ECM) (Enders, 2004).
Additionally, according to Johansen (1988), the Johansen test can be seen as a
multivariate generalization of the augmented Dickey-Fuller test. The generalization is
the examination of linear combinations of variables for unit roots. The Johansen test
and estimation strategy – maximum likelihood – makes it possible to estimate all co-
integrating vectors when there are more than two variables. If there are three variables
each with unit roots, there are at most two v vectors. For example, let r be the rank of
(π) which equals the number of co-integrating vectors. There are two tests: 1. the
maximum Eigen value test, and 2. the trace test. For both test statistics, the initial
Johansen test is a test of the null hypothesis of no co-integration against the alternative
of co-integration. The maximum Eigen value test examines whether the rank of the
matrix (π) is zero. The null hypothesis is that rank
0)(
and the alternative hypothesis
is that rank
1)(
. If the rank of the matrix is zero, the largest Eigen value (λ) is zero,
there is no co-integration and tests are done. If the largest Eigen value (λ) is nonzero,
the rank of the matrix is at least one and there might be more co-integrating vectors.
The test of the maximum (remaining) Eigen value is a likelihood ratio test. The test
statistic is:
)r1ln(T)1r,r(LR 1000
, (4)
where is
)1r,r(LR 00
the likelihood ratio test statistic for testing whether rank
)(
versus the alternative hypothesis that rank
1r0
.
Moreover, Johansen (1988) explained the trace test. It is a test whether the rank
of the matrix (π) is. The null hypothesis is that rank
0
r
. The alternative hypothesis is
that
n)(rank
, where n is the maximum number of possible co-integrating vectors.
For the succeeding test if this null hypothesis is rejected, the next null hypothesis is
that rank
1r0
, and the alternative hypothesis is that
n)(rank1
. The test
statistic is:
nri i0 10 )1ln(T)n,r(LR
, (4)
221
where
)n,r(LR 0
is the likelihood ratio statistic for testing whether rank
r)(
versus
the alternative hypothesis that rank
n)(
.
Result and Discussions
Econometric analysis begins by checking whether the sample size of secondary
data is integrated in the same order. In other word, is the data stationary at same order?
Unit root testing procedures like Augmented Ducky-Fuller (ADF) and Phillip-Perron
(PP) are applied to check the data.
The Table-1 represents the result of ADF and PP tests for the both nominal
interest and inflation rates at levels include a constant and trend. The output indicates
that the nominal interest rate is non-stationary at both 1% and 5% significance level
using both ADF and PP test. As well as, the inflation rate shows non-stationary data at
level. Table 1. Unit Root Test for Stationarity
Nominal Interest Rate
Test
Test
statistics
1%
5%
Null
Hypothesis
Status
Augmented
Ducky-Fuller
-2.696756
-3.988134
-3.424482
Fail to Reject
H0
Non-
stationary
Phillip-Perron
-2.930947
-3.986725
-3.423799
Fail to Reject
H0
Non-
stationary
Inflation
Augmented
Ducky-Fuller
-0.200123
-3.988036
-3.424435
Fail to Reject
H0
Non-
stationary
Phillip-Perron
0.341923
-3.986725
-3.423799
Fail to Reject
H0
Non-
stationary
After taking the first difference of nominal interest rate and inflation, both
variables become stationary, which is integrated at first difference I (1) by using
Augmented Ducky-Fuller and Phillip-Perron tests that can be verified from the Table
2. Table 2. Unit Root Stationarity after First Difference
Nominal Interest Rate
Test
Test
statistics
1%
5%
Null
Hypothesis
Status
Augmented
Ducky-Fuller
-5.268169
-3.451351
-2.870682
Fail to Reject
H0
Non-
stationary
Phillip-Perron
-14.29658
-3.450474
-2.870302
Fail to Reject
H0
Non-
stationary
Inflation
Augmented
Ducky-Fuller
-3.623091
-3.988036
-3.424435
Fail to Reject
H0
Non-
stationary
Phillip-Perron
-13.19072
-3.986815
-3.423842
Fail to Reject
H0
Non-
stationary
To conclude unit root test, both nominal interest rate and inflation rate are not
stationary at level but once both variables have converted to the first difference I (1),
222
both of them become stationary. Now it is possible to apply the Johansen Test of Co-
integration as its condition is existing, i.e. the variables should be integrated at the
same order.
Johansen Test of Co-integration: The Johansen test of co-integration used two
different approaches for deciding the co-integration relationship between nominal
interest and inflation rate i.e., trace statistic and max-Eigen statistic. The following is
the output of the Johansen co-integration test for time based data for Venezuela.
Table 3. Co-integration Test
Johansen Co-integration Statistics
Test
Statistic
H0:
H1:
Eigen
Value
Computed Value
of Test statistics
Critical Value
5%
Decision
Trace-
statistics
r = 0
r > 0
0.020479
6.770598
15.49471
Fail to
Reject H0
r = 1
r > 1
0.000533
0.170128
3.841466
Max-
Eigen
statistics
r = 0
r > 0
0.020479
6.600471
14.26460
Fail to
Reject H0
r = 1
r > 1
0.000533
0.170128
3.841466
It is clear from Table-3, that the computed value of the test statistic, both
approaches of Johansen co-integration test, is less than the critical value at 5% level of
significance so we cannot reject the null hypothesis. It is concluded that the existing of
a co-integration or equilibrium relationship for long run between nominal interest and
inflation rate in Venezuela for period of 1990-2016 is not appeared, which is that the
fisher hypothesis does not hold in case of Venezuela.
Conclusions
The main objective of the study is to find out the equilibrium relationship for
long run between the aforementioned variables, i.e. the study of the validity of the
Fisher Hypothesis. It is found that both variables nominal interest rate and inflation rate
for Venezuela from 1990 to 2016 show non-Stationary at I (0) and after taking first
difference I (1) of both variables, they become stationary.
The result of Johansen co-integration test, it is obtained that there is no existing
of long run relationship or co-integration among nominal interest rate and inflation rate
at 5% significance level for period of 1990 to 2016 in Venezuela. That meaning the
fisher hypothesis does not hold in Venezuela over the studying period. Building on
that, we accept the alternative hypothesis H1, and reject the null hypothesis, which
shows the existence of the long-run relationship between the two variables. Our result
consonant with investigations by Paleologos and Georgantelis (1999), Herwartz and
Reimers (2006), and Gul and Acikalin (2008), which has proved that the Fisher
hypothesis not valid. For further contributions we recommend to test the impact of
fluctuations of inflation and interest rates on the performance of banks, especially on
their profitability and level of safety (decrease/increase of risk). The other
recommendation is to examine the relationship of these both variables on asset pricing
by applying the Capital Asset Pricing Model (CAMP).
References
Ahmed, D.A. and Abdelsalam, M.A.M. (2017), "Inflation instability impact on interest
223
rate in Egypt: augmented Fisher hypothesis test", Applied Economics and
Finance, Vol. 5 No. 1, pp. 1-13.
Alexander, H. (2006), "The relationship between interest rates and inflation in South
Africa: Revisiting Fisher’s hypothesis", Thesis, Rhodes University, South Africa.
Ayub, G., Rehman, N., Iqbal, M., Zaman, Q. and Atif, M. (2014), "Relationship
between Inflation and Interest Rate: Evidence from Pakistan", Research Journal
of Recent Sciences, Vol. 3 No. 4, pp.51-55.
Baciu, I.C. (2014), "The Relationship Between Inflation And The Main
Macroeconomic Variables In Romania", Network Intelligence Studies, Vol. 2
No. 4, pp. 161-172.
Berument, H. and Mehdi, M. (2002), "The Fisher Hypothesis: a multi-country
analysis", Applied Economics, Vol. 34 No. 13, pp. 1645-1655.
Beyer, A., and Haug, A. (2009), "Structural breaks, cointegration and the Fisher
Effect", Working paper series No: 1013/ February, pp. 1-33, European Central
Bank, Germany.
Charles, O. Manasseh, F.C., Abada, J.E., Ogbuabor, J.U.J., Onwumere, C.E., Urama,
O.E.O. (2018), "The Effects of Interest and Inflation Rates on Consumption
Expenditure: Application of Consumer Spending Model", International Journal
of Economics and Financial, Vol. 8 No. 4, pp 32-38.
Dash, M. (2017), "A Study of Granger Causality in Latin American Stock Markets",
Journal of Applied Management and Investments, Vol. 6 No. 2, pp. 82-88.
Ergene, S. (2015), "Growth, inflation, interest rate and informality: Panel VAR
evidence from OECD Economies'', Economics Bulletin, Vol. 35 No. 1, pp. 750-
763.
Fisher, I. (1930), The Theory of Interest, Macmillan, New York.
Granville, B. and Mallick, S. (2004), "Fisher hypothesis: UK evidence over a century".
Applied Economics Letters, Vol. 11 No. 2, pp. 87-90.
Gul, E. and Acikalin, S. (2008), "An examination of the Fisher hypothesis: The case of
Turkey", Applied Economics, Vol. 40 No. 24, pp. 3227–3231.
Hassan, H. (1999), "Fisher Effect in Pakistan", Pakistan Development Review, Vol. 38
No. 2, pp. 153-166.
Herwartz, H. and Reimers, H.E. (2006), "Modelling the Fisher hypothesis: Worldwide
evidence", Economics working paper, No. 2006-04, Department of Economics,
Christian-Albrechts-Universität Kiel, Kiel.
Lanne, M. (2001), "Near Unit Root and the relationship between inflation and interest
rate: A reexamination of the Fisher Effect", Empirical Economics, Vol. 26 No. 2,
pp. 357-366.
Li, Z. and Zheng, X. (2017), "A Critical Study of Commercial Banks’ Credit Risk
Assessment and Management for SMEs: The Case of Agricultural Bank of
China", Journal of Applied Management and Investments, Vol. 6 No. 2, pp. 106-
117.
Macri, J. (2006), "Fisher Hypothesis: Further Evidence for Australia", Department of
Economics, Macquarie University, Sydney, presented in 3rd Annual international
conference of the applied business and entrepreneurship association, 16-20
November, NSW 2109, Australia, pp. 1-8.
Million, N. (2004), "Central Bank’s intervention and the Fisher hypothesis: a threshold
cointegration investigation", Economic Modelling, Vol. 21 No. 6, pp. 1051-1064.
224
Paleologos, J.M. and Georgantelis, S.E., (1999), "Does the Fisher Effect apply in
Greece? A Cointegration Analysis", Economia Internazionale, Vol. 52, pp. 229-
244.
Phylaktis, K. and Blake, D. (1993), "The Fisher Hypothesis: Evidence From Three
High Inflation Economies", Weltwirtschaftliches Archive, Vol. 129 No. 3, pp.
591-599.
Ray, S. (2012), "Empirical testing of international Fisher effect in United States and
selected Asian economies", Advances in Information Technology and
Management, Vol. 2, pp. 216-228.
Saeidi, P. and Vailan, H. (2011), "Studying the relationship between currency rate,
interest rate and inflation rate based on Fisher international theory and Fisher
international effect in Iran economy", Australian Journal of Basic and Applied
Sciences, Vol. 5 No. 12, pp. 1371-1378.
Shah, I. and Waleed, M. (2010), "The Fisher Equation, Belgium before and after Euro
currency", Thesis, School of Economics and Management, Lund University,
Sweden.
Sharapatyuk, D.A. (2016), "The Concept of Management of Investment Flows in
Modern Globalization Processes and the Market Economy", Journal of Applied
Management and Investments, Vol. 5 No. 4, pp. 264-269.
Sundqvist, E. (2002), "An empirical investigation of the international Fisher effect",
Bachelor’s Thesis, Lulea University of Technology, Lulea, Sweden.
Statista (2018), The 20 countries with the highest inflation rate in 2017, , available at:
https://www.statista.com/statistics/268225/countries-with-the-highest-inflation-
rate/ (accessed July 15, 2018).
Teker, D., Alp, E.A. and Kent, O. (2012), "Long-Run Relation between Interest Rates
and Inflation: Evidence from Turkey", Journal of Applied Finance and Banking,
Vol. 2 No. 6, pp. 41-54.
Wang, Y. (2016), "An Exploratory Study of Interest Rate Liberalization in Commercial
Banks in China", Journal of Applied Management and Investments, Vol. 5 No. 4,
pp. 270-279.
Westerlund, J. (2008), "Panel cointegration tests of the Fisher effect", Journal of
Applied Econometrics, Vol. 23 No. 2, pp. 193-233.
Wood, J. (1981), "Interest rate and Inflation rate", Federal Reserve Bank of Chicago.
Economic Perspectives, Vol. 5 No. 3, pp. 3-12.
