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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


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