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INFLUENCE OF ANTICIPATED INFLATION ON SHORT
TERM INTEREST RATES
A dissertation submitted in partial fulfillment of the requirement for the
award of M.B.A Degree of Bangalore University.
By
AVINASH S HUKKERI
04XQCM6011
(2004-2006)
Under the guidance of
Dr. T V N Rao
Professor MPBIM
M P Birla Institute of ManagementAssociate Bharatiya Vidya Bhavan
#43, Race Courese road,
Bangalore-01.
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EXECUTIVE SUMMARY
The study influence of anticipated inflation on short term interest rates is done with anintention to understand the impact of inflation in the short run over the interest rates. We
have made use of composite yield of 91-day Government T-bills and urban non manual
employee consumer price index. We have considered the period from April 1995 to
March 2006. This is post liberalization period in India. The data collected tabulated is
arranged and quarterly percentages are calculated.
Data used satisfies both the stationarity Dickey-Fuller unit root test and Johansen
cointegration test, which supports the requirements for using regression analysis. The
dependent variable short term interest rate is regressed with independent variable
anticipated inflation rate. One quarter lag of interest rate and interest rate is considered
for anticipated inflation rate.
The regression and correlation analysis show that short term interest rates do not adjust
for changes for inflation rates which is anticipated. Both interest rates and inflation are
linearly independent at one to one lag. Thus we conclude that short term interest rates do
not adjust for anticipated inflation rates.
However this work has its own limitations due to time constrain and lack of individual
expertise also. The limitations of this work are as under
1. The study do not considers the money supply in the economy which also
influences the inflationary changes. We assume that all other parameters remain
constant
2. The inflation index used is not unique and other indices can also be made use to
consider the inflation rates. The use of other indices may vary the accuracy of the
results interpreted here. Similarly other short term interest rates can also influence
in the same way.
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CHAPTER 1
INTRODUCTION
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INTRODUCTION
Irving Fisher (1930) provided the relationship between the expected inflation and interestrates. Fishers doctrine is that nominal interest rate can be taken as the sum of real rate of
interest and inflation anticipated by the market.
Fishers hypothesis is that the nominal interest rate (rt) can be taken to be the sum of real
rate of interest (pt) and the rate of inflation anticipated by the public (t).
rt = pt + t
This means, the real interest rate equals the nominal rate minus inflation therefore, if rt
rises, so must t , if you assume ptto be constant. If an economic theory or model has this
property, it shows the Fisher effect.
Fisher Effect: The one for one adjustment of the nominal interest rate to the inflation rate.
According to the principle of monetary neutrality, an increase in the rate of money
growth raises the rate of inflation but does not affect any real variable. An important
application of this principle concerns the effect of money on interest rates. Interest rates
are important variables for macroeconomists to understand because they link the
economy of the present and the economy of the future through their effects on saving and
investment.
The relationship between inflation and nominal interest rate and real interest rate put in
simple words is;
Real interest rate= Nominal Interest Rate - Inflation Rate
Nominal Interest Rate= Real interest Rate + Inflation Rate
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Illustration:
If inflation permanently rises from a constant level, let's say 4%per yr, to a constant
level, say 8%per yr, that currency's interest rate would eventually catch up with the
higher inflation, rising by 4 points a year from their initial level. These changes leave the
real return on that currency unchanged. The Fisher Effect is evidence that in the long-run,
purely monetary developments will have no effect on that country's relative prices.
International Fisher Relation
The international Fisher relation predicts that the interest rate differential between two
countries should be equal to the expected inflation differential. Therefore, countries withhigher expected inflation rates will have higher nominal interest rates, and vice versa.
This work concentrates on the relationship that exists between interest rates and the
inflation rates, which are main components of the Fishers effect. The interest rate
constitutes two components nominal interest rate and real interest rate. The same are
explained below.
Interest rate
An interest rate is the price a borrower pays for the use of money he does not own, and
the return a lender receives for deferring his consumption, by lending to the borrower.
Interest rates are normally expressed as a percentage over the period of one year on the
principle amount or capital employed.
The nominal interest rate is the amount, in money terms, of interest payable.For
example, suppose A deposits Rs100 with a bank for 1 year and they receive interest of
Rs10. At the end of the year their balance is Rs110. In this case, the nominal interest rate
is 10% per annum.
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Real interest rate
The real interest rate is the nominal interest rate minus the inflation rate. It is a measure
of cost to the borrower because it takes into account the fact that the value of money
changes due to inflation over the course of the loan period.
Except for loans of a very short duration, the inflation rate will not be known in advance.
People often base their expectation of future inflation on an average of inflation rates in
the past, but this gives rise to errors. The real interest rate after the fact may turn out to be
quite different from the real interest rate that was expected in advance. Conversely, when
inflation was on a downward trend in most countries, lenders fared well, while borrowers
ended up paying much higher real borrowing costs than they had expected.
The complexity increases for bonds issued for a long term, where the average inflation
rate over the term of the loan may be subject to a great deal of uncertainty. In response to
this, many governments have issued real return (also known as inflation indexed bonds),
in which the principle value rises each year with the rate of inflation, with the result that
the interest rate on the bond is a real interest rate.
Interest rates are set by a government institution, usually a central bank, as the main tool
of monetary policy. The institution offers to buy or sell money at the desired rate and,
because of their immense size, they are able to effectively set the nominal interest rate on
a short-term risk-free liquid bond (such as Govt Treasury Bills).
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Inflationary expectations
Most economies generally exhibit inflation, meaning a given amount of money buys
fewer goods in the future than it will now. The borrower needs to compensate the lender
for this.
According to the theory of rational expectations, people form an expectation of what will
happen to inflation in the future. They then ensure that they offer or ask a nominal
interest rate that means they have the appropriate real interest rate on their investment.
Money and inflation: Loans, bonds, and shares have some of the characteristics of money
and are included in the broad money supply. By setting the nominal interest rate on a
short-term risk-free liquid bond (such as Govt Treasury Bills). The Government
institution can affect the markets to alter the total of loans, bonds and shares issued.
Generally speaking, a higher real interest rate reduces the broad money supply.Through
the quantity theory of money, increases in the money supply lead to inflation. This means
that interest rates can affect inflation in the future.
The other factors that influence the interest rates are
1. Deferred consumption
2. Alternative investments
3. Risks of investment
4. Liquidity preference.
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CHAPTER 2
LITERATURE REVIEW
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LITERATURE REVIEW
Thomas J Sargenti in his workAnticipated Inflation and the Nominal Rate of Interest
proposed his work to estimate whether the Fishers equation rt= a +
t+e
t
1can in general
be taken to characterize correctly the relationship between inflation and nominal rate of
interest. In his studies he studied the relationship between the rt
t
(nominal rate of interest)
and (rate of inflation at time t) within the context of simple linear dynamic
macroeconomic model. The model used is a Keynesian in structure and has assigned
important roles to price level adjustments and anticipations of inflation effects frequently
emphasized by monetarists. The factors that determine the appropriateness of above said
equation were the same factors that within the standard IS-LM framework determine the
relative short-term potency of money and fiscal policy in affecting the level of aggregate
output.
Sargents conclusion is that the relationship between inflation and nominal rate of interest
is in principal more complex than is depicted by Fisher. However the correctness of the
equation is true and it can be expected that an increase in anticipated inflation to drive the
nominal interest rate upward by the entire amount of increase it may take a very long
time for the adjustment to occur. Sergeant also considers the money supply as a
determinant of nominal interest rate which is not included in the Fishers equation
1 rt is nominal rate on bonds, t is rate of inflation anticipated by public, et is a stochastic term which
represents numerous factors affecting rt and are not included in a or in t . a is a constant which can be
interpreted as the longrun equilibrium real rate of interest.
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William E Gibsonii
in his study Interest rates and Inflationary Expectations: New
Evidence alleviates the need to test the market determining the interest rates using
directly observed data on price expectations. Gibsons work made use of the data of
Joseph Levingston2
for the period of 1952 to 1970 for measuring the Fishers hypothesis.
In his studies Gibson used the Joseph Levingstone data for constructing expected rates of
price changes, which were related to market interest rates. Gibson used US treasury
securities to measure market interest rates. He considered five different maturity
categories of Us Treasury bills ranging from 3 month bills to 10years and longer term to
maturity bond along with market yields. Estimates for 6 month and 12 month expected
rates of inflation indicated a strong association between interest rates and measures of
expectations. Interest rates have shown quick response to changes in expectations.
The period before 1952 for US Treasury bill market was controlled and rates remained
stable irrespective of inflation changes. After this period the market determined the
interest rates even though the interest rates were not much adjusted for inflation till 1959.
post 1959 was the period which showed the adjustments in interest rates towards the
inflation changes. The results were calculated by regressing the actual prices on their
earlier periods and for the pre and post 1959 sub-periods.
Gibsons studies show that when the rate of inflation increases to high rate, the expected
rate of inflation increases for two reasons they are; firstly, At a constant rate of
adjustment of expected to actual inflation rates, the expected rate rises because the actual
rate rises and second the co-efficient of adjustment of expected to actual rises, rising the
portion of actual rate incorporates with the expected rate.
The results of the study say that, the real rate of interest is not affected by price
expectation over six month period and that interest rates fully adjust to expectations
2 Joseph Levingston a nationally syndicated financial columnist has twice yearly since 1946 surveyed a
group of business Government, labour and academic economists on their expectations of future values of
selected aggregate economic variables. The latter include the consumer price index.
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within six months. And expectations of given term have less influence on yields as the
term to maturity increases beyond the term of the expectation.
Leidermansiii
study succeeded Eugene Famas study on Fishers theory. In his paper
titled Interest Rates as Predictors of Inflation in a High-Inflation Semi-Industrialized
Economy suggests that Famas findings which are based on inflation where inflation has
been mild and so has been at variability through time.
Lidermans study aimed at empherically assessing the role of interest rates as the
predictors of inflation in different settings, one characterized by the co-existance of the
high and volatile inflation and of less than well developed financial markets. Thus he
selected the markets of Argentina for the same and used the data for period of 1964-1976.
he supported the selection of Argentina as it is a semi-industrialised country, less than
well developed financial market which have experienced relatively high degree of
government intervention, which probably impair the operational efficiency of capital
market as well as prediction of interest rates.
Lidermans Fisher type equation was
it = o+ 1 E (t / It-1) (1)
Where itis nominalinterest rate quoted at the end of (t-1) on a bill that matures at the
end of t and t is rate of inflation for period t. E (t / It-1) is the expected value of
inflation rate implied by the information set available at time t-1 i.e. I t-1 .
Under the assumption that nominal interest rate equals the sum of real rate and expected
rate of inflation, where the expected rate of inflation is given by
it- E (t / It-1) = o+(1-1) E (t / It-1) (2)
Independence of real interest rate with respect to movements in anticipated inflation
amounts to 1=1.
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To study the role of interest rates as predictors of inflation equation (1) was rewritten as
E (t / It-1) = o + 1it (3)
Where o = (- o) / 1 and 1=1 / 1.
Since past inflation rates may help assess the expected inflation rates from t-1 to t.
Thus equation (3) can be rewritten as
E (t / It, t-1, t-2 .) = o + 1it (4)
Liderman inserted a prediction error in the above equation (4) as follows
t = t - E (t / It-1)
So the equation (4) can be rewritten as
t = o+ 1it+t (5)
Leat square estimations of equation (5) and the variants of equation were used in order to
test the hypothesis of predominance of interest rates over past inflation as predictors of
t.
Liderman considered the quarterly Argentinean data from 1964 to 1976 (50
observations). He considered the bill brokerage yields which have very large market and
this market is close to being a free financial market.
The dependent variable was t, the inflation rate fromt-1 to t. the co-efficient of
determinant indicate that the nominal interest rate contains nontrivial information aboutthe rate of change in purchasing power from t-1 to t.
Two major conclusions were made by his work.
1. markets use all information about subsequent inflation rates in setting quarterly
inflation rates, and
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2. An increase in expected inflation is not fully transmitted to nominal interest rate
so it implies a reduction in the contemporaneous real interest rate.
Alexander B . Holmes and Myron L. Kwastiv
in their paper Interest Rates and
Inflationary Expectations: Tests for Structural Changes 1952-1976 studied the
relationship between the nominal interest rates and anticipated inflation rates during the
structural changes i.e. during the period 1952-1976 in the US economy.
Holmes and Kwast used Brown-Durbin tests for structural stability, for the data used and
the results indicated were found significant. In their analysis Holmes and Kwast used CPI
data, short term Treasury bill data and expected prices were constructed from Livingston
survey, for the analysis.
Their analysis found that there was radical upward shift in size of the coefficients at the
estimated period and immediately after the period of estimated structural change, which
confirms that market rates adjust more strongly to inflationary expectations in the late
1960s and there after than they had before. And also interest rates are estimated not to
adjust to inflationary expectations before the period of structural change, but to make a
significant positive adjustment after the estimated shift.
Thus the work of Holmes and Kwast support the dating of structural change as
determined by the Brown-Durbin technique and the hypothesis that the interest rates
respond more strongly to inflationary expectations after the structural shift.
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CHAPTER 3
RESEARCH
METHODOLOGY
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STUDY BACKGROUND
Ever since Irving Fisher (1930) provided the relationship between the expected inflation
and interest rates; considerable attention has been paid for it. Many financial
controversies and literatures have surrounded this relationship.
Fishers doctrine holds that nominal interest rate can be taken as the sum of real rate of
interest and inflation anticipated by the market.
Thomas J Sargent in his works has analyzed the Fishers doctrine. Sargent found that the
relationship between the anticipated inflation and nominal rate of interest is in principlemore complex than depicted in Fishers equation. It can be expected that an increase in
anticipated inflation drives the nominal interest rate upward by the entire amount of
increase, but this adjustment is not quick.
In Indian context very less studies have been done in this regard as interest liberalizations
are of recent past. Thenmozhi and Radha (2004)v
have shown that Fishers hypothesis is
true in India the context and have found that there is a long run relationship between
interest rates and expected inflation and interest rates can be modeled considering
expected inflation and other macroeconomic variable to arrive at a more valid model of
forecasting interest rates.
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PURPOSE OF THE STUDY
The effects of expected inflation on market interest rates have been of great concern for
decades. Irving Fishers description of interest rates relationship with expected inflation
is convincing on the theoretical levels.
I.Fishers doctrine holds that the nominal interest rate (rt) can be taken to be the sum of
real rate of interest (pt) and the rate of inflation anticipated by the public (t).
Thus Fishers equation as proposed by him is
rt = pt + t (1)
In his works Fisher and group assume that real rate of return (pt) is unaffected by the
change in anticipated inflation rate (t). thus one can conclude that the term p t (real rate of
return) in equation (1) is a constant and stochastic term et that is uncorrelated with t.
symbolically
pt = a + et (2)
Where et represents numerous factors affecting rt, which are not included in a ort .
From both the equations we can rewrite the equation (1) as follows
rt = a + et + t (3)
The purpose of this paper is to establish whether equation (3) can in general be taken to
characterize correctly the relationship between anticipated inflation changes and nominal
rate of interest.
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SCOPE OF THE STUDY
Level of inflation always has a bearing on the short term interest rates. The interest rate is
a key financial variable that affects decisions of consumers, business firms, financial
institutions, professional investors and policy makers. Timely forecasts of inflation rates
can therefore provide valuable to financial market participants. Forecasts of interest rates
can also help to reduce interest rate risks faced by individuals and firms.
In Indian context the relationship between anticipated inflation changes and returns were
not of much concern till the 1990,s due to administered interest rate mechanism. Since
the economic reforms and the liberalization of capital market the interest rates are marketdetermined.
The earlier findings report that no relationship between interest rates observed at point of
time and rates of subsequently observed inflation exist. However the general finding is
that there are relationships between current rates of interest and past rates of inflation.
If interest rates are not adjusted for changes in inflation then the real rate of return
decreases. Expected price changes have a bearing on the purchasing power, thus on the
level of consumption also. Hence interest rate determination in Indian context also needs
focus.
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STUDY OBJECTIVE
To characterize the relationship between anticipated inflation changes and nominal rates
of interest
STATISTICAL METHOD
Correlation and regression analysis will be made use in order to analyze the relationship
between interest rates and inflation.
Regression and correlation analysis show us how to determine nature and strength of
relationship between two variables. We need to find out the causal relationship between
changes in interest rate to the changes in inflation.
Regression analysis shows the relationship between the variables and correlation shows
the degree of relationship between the variables.
The regression equation is given as follows
Y = a + b (X)
Where, Y is dependent variable, the value which is dependent on changes in X.
X is the independent variable
a is the Y intercept, the value of Y is the value at which regression line crosses
the Y axis.
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b is the slope of the equation, it represents how much each unit of change in
independent variable X changes the dependent variable Y.
b = Y2 Y1 OR n XY ( X) ( Y)
X2-X1 n X2- ( X)
2
Where n is the number of observations
In our study the interest rate will be denoted by Y since it is a dependent on inflation.
The variable X explains the inflation.
To find out the variability of values around the regression line standard error of estimate
is calculated.
Standard error of estimate is given by
Se = Y2
a Y- b XY(n-2)
To find out degree to which one variable is linearly related to another is calculated using
correlation. There are two measures to analyze the same viz coefficient of determination
and coefficient of correlation.
Coefficient of determination is used to measure the extent or strength of association
between the two variables X and Y. it is denoted by r2. it is calculated as follows
r2
= a Y + b XY - n Y2
Y2
n Y2
Coefficient of correlation (r) is also a measure which describes how well one variable is
explained by the other. It is square root of coefficient of determination. The sign of r
indicates that the direction of relationship. If r2
is positive the root will be positive and it
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indicates the direct relationship and if the r2
is negative its root will be negative and
indicates an inverse relationship
Unit Root Test
A test of stationarity (or nonstationarity) that is well known is the UNIT ROOT TEST.
The starting point of unit root test is
Y t=Y (t-1) +Ut
Where,
Ut=white noise term.
Yt= random variable at discrete time interval t.
If =1, then the unit root exist. That is: the time series under consideration is
nonstationary or follows a random walk.
If! = 1, then unit root does not exist. That is: the time series under consideration is
stationary.
Theoretically value can be calculated by regressing Y t with one period lag values.
Augmented Dickey Fuller (ADF) Test:
ADF Test is used for calculating , where = -1.
Hypothesis:
H0= Time series is non stationary.
H1= Time series is stationary.
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Decision Rule:
1) If T* >ADF critical value not reject the null hypothesis i.e., unit root exists.2) If T*
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3. T-Test for the significance of an observed sample correlation coefficient.
T-Test for significance of an observed sample correlation coefficient
This test is conducted to find the significance of observed samples.
Hypothesis:
H0 = sample correlation does not differ significantly. (TcalTtab)
DATA
The study for the study of mentioned objective will be on the basis of secondary data
collected from various websites3. For calculations software are used.
3 The sources of data are mentioned in the bibliography.
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PERIOD OF STUDY
The proposed period for the study is from April 1995 to March 2006 and data from the
Indian economy. The data earlier to the period will not support the studies due to
controlled market.
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CHAPTER 4
RESULTS AND ANALYSIS
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Interpretation of ADF test:
For series X (Inflation rate changes)
The computed ADF test-statistic (-3.158648) at none, is smaller than the critical values
(-2.6182) @1%, (-1.9488) @ 5% level, -1.6199 @ 10% level. Thus the hypothesis is
rejected for unit root; the data for inflation series is stationary. It is clear that data has
passed the Dickey Fuller test and we can continue further tests.
For series Y (Interest rate changes)
The computed ADF test-statistic (-5.943633) at none, is smaller than the critical values
(-2.6182) @1%, (-1.9488) @ 5% level, (-1.6199) @ 10% level. Thus the hypothesis is
rejected for unit root; the data for interest rates is stationary. It is clear that data haspassed the Dickey Fuller test and we can continue further tests.
Interpretation of DW statistics:
The results of Dublin and Watson tests are close to 2 for both the series viz 1.89 for X
series and 2.01 for Y series. The DW statistics indicate that there is no autocorrelation
existing.
Tests Series X (inflation rates) Series Y ( interest rates)
ADF test Stationary Stationary
D-W Statistics No autocorrelation No autocorrelation
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Interpretation of cointegration test:
The cointegration test for series X and series Y at 1 to 1 lag intervals has critical value of
15.41@ 5%, 20.04 @ 1%, which leads to rejection of the hypothesis Ho which says no
cointegration exists, thus the result indicates the cointegration of both the series X and Y.
thus the existence of cointegration further supports the study methodology.
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VariablesEntered/Removed
Model Variables EnteredVariablesRemoved Method
1 INF . Enter
aAll requested variablesentered.
bDependent Variable:INTREST
ModelSummary
Model R R Square
AdjustedRSquare
Std. Error ofthe Estimate
1 0.122 0.015 -0.009 9.8367
aPredictors: (Constant),INF
Coefficients
UnstandardizedCoefficients
StandardizedCoefficients t Sig.
Model BStd.Error Beta
1 (Constant) -2.501 2.344-
1.067 0.292
INF 0.949 1.203 0.122 0.789 0.434
a Dependent Variable:INTREST
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Scatter Diagram
INF
543210-1-2
INTREST
40
30
20
10
0
-10
-20
-30
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Regression results
a = -2.501
b = 0.949
The constant term a = (-2.501) is Yintercept, the negative sign indicates that real rate
of return does not compensate for the inflation rate. The other term b indicates the slope
of the regression equation which is 0.949.
The test results indicate that for the considered series there is no significant relationship
existing.
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Correlation Tested
Correlations
INF INTREST
INF Pearson Correlation 1 0.122
Sig. (2-tailed) . 0.434
N 43 43
INTREST Pearson Correlation 0.122 1
Sig. (2-tailed) 0.434 .
N 43 43
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Correlation
r = 0.0122 and r2
= 0.015
r2
explains the percentage of influence that is explained by the inflation. Thus it says that
1.5% of the change in interest rate is due to the inflation change.
Thus the interest rates and inflation rates are linearly independent at lag 1.
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CHAPTER 5
SUMMARY ANDCONCLUSIONS
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SUMMARY AND CONCLUSION
The study considers the secondary data of the Indian economy from April 1995 to March
2006. The data constitutes of 91 day Government T-Bills composite yields and
Consumer Price Index is used for the purpose of inflation rates. The quarterly changes in
the inflation rates and interest rates are calculated for the ten years.
The inflation rates constitute the independent variable in the regression equation and
interest rates form the dependent variable. One period lag is taken between the interest
rate and inflation so that the lag in the inflation forms the anticipated inflation. The
variables are regressed to find out the relationships that both have and results areinterpreted.
From the statistical analysis it can be interpreted that in Indian context the relationship
between the short term interest rates and the anticipated inflation doesnt show any
significant relationship. The interest rates in short terms have been unable to compensate
for the inflation changes that occur in the short run. From the study we can say also say
that in short term the investors are not compensated for the inflationary changes.
In total interest rates and inflation are linearly independent at lag one. No relationship is
observed between the said variables in short term.
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BIBLIOGRAPHY
The sources of the data are as follows
Websites used
www.rbi.org.in
www.reservebank.org.in
www.eaindustry.nic.in
www.mospi.nic.in
Software used
SPSS
Eviews
Books Referred
Statistical methods Levin and Rubin
Econometrics Damodaran Gujarati
i Thomas J Sargeant anticipated inflation and nominal interest rates quarterly journal of finance pg no
212, 1972
ii Interest Rates And Inflationary Expectations: New Evidences American Economic Review (December
1972, pg no 854-865)
iii Interest Rates as Predictors of Inflation in a High Inflation Semi Industrialized Economy. Leonardo
Leiderman , Journal of finance, vol XXXIV, September 1979.
iv Interest Rates and Inflationary Expectations: Tests for Structural Change 1952-1976, Journal offinance, vol. XXXIV No.3, June1979.v Short Term Interest Rates and Macroeconomic Variables an OSL Model M Thenmozhi and Radha S,
Th ICFAI i it J 2006 5 16