# Interest Rate As A Predictor Of Inflation

Interest rate and rate of inflation are two of most important variables which are being studied in macroeconomic since a long time. Fisher (1930) presented the theory of interest which is considered as a great milestone in Many researchers have did work on interest rate and inflation, like Fisher (1930), Fama (1970, 1975, 1976, 1977), Carlson (1977), Nelson and Schwert (1977), Leiderman (1979), Fama and Gibbons (1982), Kandel, Ofer, and Sarig (1996), etc.

This study focuses the Fama’s (1975) work. Fama (1975) tested short term interest rate as predictor of inflation for the U.S economy for the period 1953-71. Leiderman (1979) did almost the same study for Argentina for the period 1964-76. Economic situations of U.S. and Argentina are different. At that time U.S was considered as relatively low inflation country while Argentina was considered as a country where inflation rate is relatively high.

Fama (1975) concluded that market was efficient in using all information about future inflation rates, which were in time series of past inflation rates, to set one-to six-month nominal rate of interest and equilibrium expected real rates of return on one- to six-month bills are constant. On the basis of these two important conclusions Fama (1975)also concluded that changes in one- to six month nominal rates of interest through time reflects changes in one- to six-month expected rate of inflation which is measured correctly.

Leiderman (1979) also tested the role of interest rate as predictor of inflation with a view that: Fama’s (1975) findings were based on the data of United States, where inflation had been relatively mild, and so had been its variability through time. Leonardo (1979) aimed to test Fama’s (1975) findings in Argentina, which was characterized by coexistence of high volatile inflation and of less than well developed financial markets, for the period 1964-76. Leiderman (1979) not only tested the interest rate but he also added four lagged values of rate of inflation and one lagged value of rate of interest step by step in equations and hence formed 6 equations. Leiderman (1979) concluded that both interest rate and lagged inflation separately provide data to predict future inflation but when both were simultaneously considered as predictors of inflation then only the interest rate emerges as an important predictor of inflation. This result also mach with the Fama’s (1975) results for the U.S.

## 1.2 Problem Statement:

The focal issue of this study is similar to Fama (1975) and Leiderman (1979). They tested interest rate as predictor of inflation for U.S and Argentina respectively. This study was focused to empirically assess interest rate as a predictor of inflation in the Pakistan’s environment, where there is also less than well developed financial markets, rate of inflation is high, economic conditions are very unstable, high degree of Government intervention in financial market. These conditions were very much similar to Argentina. KIBOR for 1 month and rate of inflation (monthly CPI) were being used for this study. To attain above mentioned objectives following hypothesis has been developed.

## 1.3 Hypothesis:

H1. There is significant correlation among rate of inflation and rate of interest.

H2. Short term interest rate is a good predictor of inflation.

## 1.4 Outline of the Study:

The thesis is comprised of five chapters. Chapter two explains the literature review, Chapter three provides information about research method, Chapter four consist of explanation about results and their interpretations and Chapter five presents discussion, conclusions, implications, recommendations and future research.

## CHAPTER 2: LITERATURE REVIEW

The rate of interest and inflation has significant importance in the literature of macroeconomic since a long time. Both are important macroeconomic factors. Many researcher have did work in this area such as Fisher (1930), Fama (1970, 1975, 1976, 1977), Carlson (1977), Nelson and Schwert (1977), Leiderman (1979), Mishkin (1981), Fama and Gibbons (1982), and Kandel, Ofer, and Sarig (1996), etc. Here only literature relevant to the topic of this study has been discussed briefly.

## Theory of Interest (1930):

## This theory was presented by Irving Fisher in 1930. This theory is considered as a great milestone for the work done in the area of rate of interest. Even though there are some critiques on it, but no doubt this opened a way for future research and base for the further studies. Fisher (1930) worked on the relationship of nominal rate of interest and expected rate of inflation. Fisher (1930) wrote that in well functioning capital market, with accurate future forecast, nominal rate of interest will be equal to stable real rate of return plus likely rate of inflation and it can also be the sum of balanced projected real return and market’s judgment of anticipated rate of inflation because forecasts are not perfect. Fisher (1930) also found proofs that price changes normally shape rate of interest predictably in the way theory mentions, but possessions are not significant to prove the theory because of flaw in forecast and it also significantly insulate price movements for some intervals.

## 2.2 Expanded work on Theory of Interest (1930):

Many researchers expanded the work of Fisher (1930). Some raised arguments and explained the issues according to their point of view. Some draw further branches from the base developed by Fisher (1930). Some of them are Fama (1970, 1975, 1976, 1977), Carlson (1977), Nelson and Schwert (1977), Leiderman (1979), Mishkin (1981), Fama and Gibbons (1982), and Kandel, Ofer, and Sarig (1996), etc.

Kandel, Ofer, and Sarig (1996) used newly available data and directly tested the Fisher (1930) hypothesis that the real rate of interest is independent of inflation expectations by developing a system to take out ex-ante real rate of interest from simultaneously observed prices of index and nominal bonds. Kandel, Ofer, and Sarig (1996) reported a negative correlation between ex-ante real interest rates and expected inflation. This contradicts the Fisher’s (1930) hypothesis but it is consistent, under diminishing returns to capital, with the Mundell (1963) and Tobin (1965) disagreement that high inflation expectations cause higher capital accumulation.

Kandel, Ofer, and Sarig (1996) result was also consistent with the Darby (1975) and Feldstein (1976) case that taxation of inflation gains causes the real rate of interest to be negatively correlated with expected inflation and with Stulz (1986) disagreement that uncertainty about monetary policy leads to such a negative correlation.

Kandel, Ofer, and Sarig (1996) also reported that nominal interest rates include an inflation premium. The premium is high when inflation uncertainty is high and is positively related to a proxy for inflation uncertainty. The existence of a risk premium is consistent with theoretical analysis of nominal contracts under uncertain inflation.

## 2.3 Eugene Fama’s Work

Fama (1975) empirically examined part of Fisher’s (1930) hypothesis that interest rates contain market forecasts of future inflation rates. Fama (1975) took one- to six-month data of U.S. Treasury bill rates and subsequently observed rate of inflation.

Fama (1975) concluded that market was efficient in using all information about future inflation rates, which were in time series of past inflation rates, to set one- to six-month nominal rate of interest and equilibrium expected real rates of return on one- to six-month bills were constant. On the basis of these two important conclusions Fama (1975) also concluded that changes in one- to six month nominal rates of interest through time reflects changes in one- to six-month expected rate of inflation which were measured accurately.

For these conclusion Fama (1975) also had a support by findings that real returns on bills have an auto-correlation close to zero and differences in nominal rates through time reflects changes in accurately measured probable standards of potential rates of changes in purchasing power, it was explained by regressions of change in the purchasing power of money on nominal interest rates.

Fama (1976) further did the work in the same area. Fama (1976) tested the relationship of expected real return and two sources of inflation uncertainty in the real returns and premiums on bills. Fama (1976) failed to discover deviation through time in probable real returns as a function of the key source of uncertainty in real returns, but there was an argument that during sample period (1953-71) uncertainty of rate of inflation did not appear to adjust to a great extent and may be because of it, relationship did not found. Fama (1976) found a regular variation through time in uncertainty about potential assessments of probable rates of change in purchasing power and may be because of it Fama (1976) concluded that there is relationship between these sources of inflation uncertainty and anticipated real returns and premiums.

Carlson (1977), Hess and Bicksler (1975), Joines (1977) and Nelson and Schwert (1977) challenged the work of Fama (1975) on standard statistical grounds. Fama (1977) appreciated that they took interest in his work and accepted their challenge and tried to explain the points rose out by them. Fama (1977) explained all his tests and concluded that if values are taken at face value interest rate remains the single best predictor of inflation, no body discovered the other variables which make significant contribution in the prediction of inflation other than that which is wholly explained by interest rate alone. Fama (1977) also stated that the largest part of variation in nominal interest rates reflects variation in expected inflation rates, seems intact. Summing up the whole discussion Fama (1977) stated that although the model is not an exact description of the world, the specific deviations discovered so far are to some extent manifestations of measurement errors in the estimates of inflation rates and interest rates.

## 2.4 Works of Other Researchers:

Carlson (1977) raised argument on the results of Fama (1975). According to Carlson (1977) the first assumption of Fama (1975) does not hold up when an expected real rate series is constructed from survey data on inflation expectations. A very significant regularity in the series is that the short-term (six months to a year) anticipated real rate falls during recessions, when short-term marginal productivity of capital would be expected to fall. The second assumption of Fama (1975) contradicts because considerable information about succeeding inflation was not reflected completely in nominal interest rates and it was also conflicted with the general tendency in the data which increase the statistical false impression that variations in interest rates on Treasury Bills are excellent predictors of variations in inflation.

Carlson (1977) concluded that variations in short-term interest rates are not good predictors of variations in inflation rates and Fama's (1975) regression tests over periods with substantial trends in both inflation and interest rates cannot hold up true because of uncertain macroeconomic conditions.

Nelson and Schwert (1977) challenged the conclusions of Fama’s (1970). Fama (1970) stated in his paper that that the real rate of interest, ignoring taxes, is constant and the market for U.S. Treasury Bills is efficient in the sense of embodying rational expectations. According to Nelson and Schwert (1977) tests carried out by Fama’s (1970) were not powerful enough to accept the both hypothesis. More powerful tests had been applied by using the same data and conclusions were made that expectations of inflation have accounted for most of the variation in short-term interest rates during the postwar period, and that those expectations embody significant information beyond that contained in past inflation rates alone.

Leiderman (1979) also tested Fama’s (1975) hypothesis for Argentina, which is characterized as high inflation, semi-industrialized economy with a less than well developed financial market, for the period 1964-76. Leiderman (1979) derived six equations by also considering lagged values of rate of inflation as a potential predictor of inflation, at the end he concluded that both interest rates alone and lagged inflation alone embody information about the expected value of future inflation. Yet, when both the interest rate and lagged inflation rates are simultaneously considered as potential predictors of inflation, only the interest rate emerges as an important predictor.

Rolando (1989) also tested the joint hypothesis of Treasury bill market efficiency and constant ex ante real rate of interest which was presented by Fama’s (1975). Rolando (1989) tested these hypotheses by using 3-month T-bill rate and CPI as rate of inflation for the period 1968-87. At the end of this study Rolando (1989) stated that the interest rate is not the best predictor of inflation as shown by the fact that forecasts based solely on nominal interest rate are less accurate than alternative forecasts based on information available to market agents at the time when nominal interest rate was set.

## CHAPTER 3: RESEARCH METHOD

## 3.1 Variables:

The main purpose of this study has been to test is there a significant relationship between short term interest rate and rate of inflation exists, then to find out whether the short term interest rate is good predictor of inflation or not. For this purpose following variables has been included in the study:

## 3.1.1 Rate of inflation (CPI) - dependent

The rate of inflation is an important macroeconomic factor and one of key variables most of central banks around the world scrutinize when setting their main policy rate. Containing inflation to a sustainable level is imperative for economic growth; it not only protects the low and fixed income groups on the consumer side but also keeps the cost of doing business manageable on the production side. The policy objective of the government has always been to ensure economic growth while keeping inflation under control. However, given the unprecedented surge in Pakistan’s domestic inflation during Fiscal Year 2008-09, the need for containment and stabilization has been given top priority by policymakers. In Pakistan CPI is used for this purpose.

## 3.1.2 Rate of interest (1 month KIBOR) - independent

KIBOR stands for Karachi Inter Bank Offered Rate, which is the most common base for all financial institution working under the guidelines of State Bank of Pakistan. That’s why it is used for the purpose of analysis. Changes in it are made to increase or decrease money supply in the market. Whole banking system is mainly dependent on its movements and because of which all institutions which directly or indirectly lends or borrows from bank and other financial institutions are also highly concerned with it. It plays a vital roll in Pakistan’s economy.

Following hypothesis has been developed in the study:

H1. There is significant correlation among rate of inflation and rate of interest.

H2. Short term interest rate is a good predictor of inflation.

## 3.2 Sample Size:

To fulfill the desired objectives of the study researcher took Pakistan’s data for the period of July 2005 to November 2009.

## 3.3 Sampling Technique:

Researcher has taken one month lag between rate of interest and rate of inflation to study the above mentioned objectives, that’s why data of interest rate starts from July 2005 and ends at October 2009, while the data of rate of inflation has been entered from August 2005 and end on November 2009.

## 3.4 Method of Data Collection:

The data has been taken from the publications of State Bank of Pakistan and the publication of Finance Ministry. Both are very much reliable and authentic.

## 3.5 Statistical Technique:

The statistical program used for the analysis and presentation of data in this research is the Statistical Package for the Social Sciences (SPSS). First of all test of correlation has been applied and then auto regression technique has been applied in this study.

## CHAPTER 4: RESULTS

## 4.1 Findings and Interpretations of the Results:

## Table 4.1.1: Correlations

Interest Rate

Rate of Inflation

Interest Rate

Pearson Correlation

1

.757**

Sig. (2-tailed)

.000

N

53

53

Rate of Inflation

Pearson Correlation

.757**

1

Sig. (2-tailed)

.000

N

53

53

**. Correlation is significant at the 0.01 level (2-tailed).

Table 1.1 is showing the results of test of correlation. According to these results interest rate is significantly correlated with rate of inflation. Pearson correlation coefficient 0.757 and sig value is 0.000 for interest rate shows that there is strong positive correlation among dependent variable (rate of inflation) and independent variable (interest rate). Hence on the basis of these results first hypothesis of the study is being accepted that there is significant relationship between short term interest rate and rate of inflation.

## Table 4.1.2: Model Fit Summary (Iteration 0)

R

R Square

Std. Error of the Estimate

Durbin-Watson

.757

.573

3.987

.265

The Prais-Winsten estimation method is used.

Table 2 is showing the model fit summary of Iteration 0. In this iteration R.Square value is 0.573 significant at 0.000. It means that independent variable (interest rate) is explaining 57.3% variation in dependent variable (rate of inflation), another thing is noticeable that even though its explaining much part of variation in rate of inflation but still 42.7% variation is unexplained, which means that there must be some other variables which influence rate of inflation and this is the work for future study to find and test some other independent variables in the same area. One very important thing in Table 2 is value of Durbin-Watson which is 0.265 indicating that there is some issue of auto-correlation, which means dependent variable is being very much explained by its own values instead of independent variable. To remove this issue and see the exact impact of interest rate on rate of inflation further iterations applied to test whether or not the variation in rate of inflation is due to variation in rate of interest or due to some other independent variables which are not included in this model.

## Table 4.1.3: Regression Coefficients (Iteration 0)

Standardized Coefficients

T

Sig

Beta

Interest Rate

0.757

8.264

.000

(Constant)

-4.055

.000

The Prais-Winsten estimation method is used.

Table 3 is providing the regression coefficients for the applied model of Iteration 0. Results shown here reflecting that all the variables are statistically significant. Beta for independent variable (interest rate) 0.757 a positive value means that there is a significant positive relationship between interest rate and rate of inflation of Pakistan, but issue of autocorrelation must be addressed first, as Durbin-Watson is 0.265, before accepting interest rate as predictor of inflation.

## Table 4.1.4: Model Fit Summary (Iteration 5)

R

R Square

Std. Error of the Estimate

Durbin-Watson

.119

.014

1.405

1.266

The Prais-Winsten estimation method is used.

Model fit summary of final iteration 5 has been demonstrated in Table 4. It is showing that Durbin-Watson is very much improved and reached the level of 1.266, indicating that issue of auto-correlation has been very much resolved. Now table 4 is showing exact impact of independent variable on dependent variable. Now R.Square is just 0.014, which means that independent variable (interest rate) is explaining only 1.4% variation in dependent variable (rate of inflation) and remaining 98.6% variation in dependent variable is unexplained. There must be some other more influencing independent variable which are not included in this model and lead us to future study in the same area with some other independent variables.

## Table 4.1.5: Regression Coefficients (Iteration 5)

standardized Coefficients

T

Sig

Beta

Interest Rate

.119

.846

.401

(Constant)

1.488

.143

The Prais-Winsten estimation method is used.

Regression coefficient of final Iteration 5 has been shown in Table 5. Results shown here reflecting that all the variables are statistically insignificant. Beta for independent variable (interest rate) 0.119 a positive but very small value means that there is a insignificant positive relationship between interest rate and rate of inflation of Pakistan. This relationship is not significant up to that extent upon which interest rate can be accepted as predictor of rate of inflation, because it’s explaining very small variation in rate of inflation. Anyhow this result is not disappointing as it is leading a direction for future research in this area with some other independent variables which may explain more amount of variation in rate of inflation. Hence on the basis of above discussion of results its clear that second hypothesis of this thesis cannot be accepted.

## 4.2 Hypothesis Assessment Summary:

## Table 4.2.1: Hypothesis Assessment Summary

## Hypothesis

H1: There is significant correlation among rate of inflation and last months rate of interest.

H2. Short term interest rate is a good predictor of inflation.

## Variables

KIBOR for 1month (interest rate) : Independent variable

CPI (rate of inflation) : Dependent variable

## Sample Size

From July 2005 to November 2009

## Tests Applied

Test of Correlation

Auto Regression test

## Result of Tests

## Test of Correlation

Interest Rate

Rate of Inflation

Interest Rate

Pearson Correlation

1

0.757

Sig. (2-tailed)

0.000

## Auto Regression

R square

Durbin Watson

B

t

Sig

Iteration 0

0.573

0.265

2.366

8.264

0.000

Iteration 5

0.014

1.266

0.239

0.846

0.401

Conclusions

H1: Accepted (significant correlation among rate of inflation and last months rate of interest)

H2: Rejected (Short term interest rate is a good predictor of inflation)

## CHAPTER 5: DISCUSSIONS, CONCLUSIONS,

## IMPLICATIONS, RECOMMENDATIONS AND FUTURE

## RESEARCH

## 5.1 Discussions and Conclusions:

In this study focal issue was to test that whether there is significant relationship exists between interest rate and rate of inflation and do the short term interest rate is a good predictor of inflation. For this purpose 1 month KIBOR is taken as independent variable and CPI is taken as dependent variable. The data has been taken for the period of 2005-09.

The result supported only first hypotheses of this study that there is significant relationship between interest rate and rate of inflation. Where as results did not supported 2nd hypotheses of this study. On the basis of these results short term interest rate did not found to be the good predictor of inflation.

This result contradicted with Fama (1975) and Leonardo (1979), but this result is very much similar to the results of Carlson (1977), Hess and Bicksler (1975), Joines (1977) and Nelson and Schwert (1977), Rolando (1989), those who concluded that interest rate is not a good predictor of inflation.

## 5.2 Implications and Recommendations:

Instead of interest rate there must be some other variable which may have significant impact on rate of inflation. Table 1.5 provides the model fit summary of final iteration 5. Which show that R square value of 0.014 with Durbin-Watson value of 1.266 where as t-statistics value of 0.846 significant at 0.401. It means that model has explained only 1.4 per cent variation in rate of inflation and 98.6 per cent variation is still unexplained. This result indicates that interest rate and rate of inflation have a strong positive relation but still this relation cannot be used to predict future rate of inflation.

## 5.3 Future Research:

Results discussed above show that there is 98.6% variation in rate of inflation remain unexplained by the model. It leads that there are some other variables which have more influence on the rate of inflation and if they may be included in the model for the same data they might explain more variation in inflation. This part is way for future research in this area.

## CHAPTER 6: REFRENCES

Carlson, J. (1977). Short-term interest rate as predictors of inflation: Comment. The American Economic Review, 67, 469-475.

Darby, M.R. (1975). The financial and tax effects of monetary policy on interest rates. Economic Inquiry, 13, 266-276.

Fisher, I. (1930). The theory of interest. Retrieved from

http://www.econlib.org/library/YPDBOOKS/Fisher/fshToI.html

Fama, E. (1975). Short-term interest rate as predictor of inflation. The American Economic Review, 65, 269-282.

Fama, E. (1976). Inflation uncertainty and expected returns on treasury bills. Journal of Political Economy, 84, 427-448.

Fama, E, (1977). Interest rates and inflation: The message in the entrails. The American Economic Review, 67, 487-496.

Fama, E. (1970). Efficient capital market: A review of theory and empirical work. The Journal of Finance, 35, 383-417.

Fama, E., & Gibbson, M.R. (1982). Inflation, real returns and capital investment. Journal of Monetary Economics, 9, 297-323.

Feldstein, M. (1976). Inflation, income taxes and the rate of interest: A theoretical analysis. The American Economic Review, 66, 809-820.

Hess, P. J., & Bicksler, J.L. (1975). Capital asset prices versus time series models as predictors of inflation: The expected real rate of interest and market efficiency. The Journal of Financial Economics, 2, 341-60

Joines, D. (1977). Short term interest rate as predictor of inflation: Comment. The American Economic Review, 67, 476-477.

Kandel, S., Ofer, A.R., & Sarig, O. (1996). Real interest rates and inflation: An ex-ante empirical analysis. The Journal of Finance, 51, 205-225.

Leiderman, L. (1979). Interest as predictor of inflation in a high-inflation semi-industrialized economy. The Journal of Finance, 34, 1019-1025.

Mishkin, F.S. (1981). The real interest rate: An empirical investigation. Carnegie-Rochester Conference Series on Public Policy, 15, 151-200.

Mundell, R. (1963). Inflation and real interest. Journal of Political Economy, 71, 280-283.

Nelson, C., & Schwert, G.W. (1977). Short-term interest rates as predictors of inflation: On testing the hypothesis that the real rate of interest is constant. The American Economic Review, 67, 478-486.

Rolando, F.P. (1989). Interest rate as a predictor of inflation revisited. Southern Economic Journal, 55, 1025-1028.

Stulz, R.M. (1986). Interest rates and monetary policy uncertainty. Journal of Monetary Economics, 17, 331-347.

Tobin, J. (1963). Money and economic growth. Econometrica, 33, 671-684.

## Appendices

## DATA FOR SPSS INPUT

Month

Interest rate

(KIBOR)

Rate of Inflation

(CPI)

Jul-05

7.42

## ------

Aug-05

8.05

8.40

Sep-05

7.80

8.50

Oct-05

7.88

8.30

Nov-05

8.38

7.90

Dec-05

8.40

8.50

Jan-06

7.80

8.80

Feb-06

8.19

8.10

Mar-06

8.11

6.90

Apr-06

8.35

6.20

May-06

8.81

7.10

Jun-06

8.54

7.70

Jul-06

8.12

7.60

Aug-06

9.56

8.90

Sep-06

9.18

8.70

Oct-06

8.98

8.10

Nov-06

9.16

8.10

Dec-06

9.07

8.90

Jan-07

9.62

6.60

Feb-07

9.33

7.40

Mar-07

9.19

7.70

Apr-07

9.12

6.90

May-07

8.94

7.40

Jun-07

8.73

7.00

Jul-07

8.89

6.40

Aug-07

9.26

6.50

Sep-07

9.05

8.40

Oct-07

9.14

9.30

Nov-07

9.11

8.70

Dec-07

9.05

8.80

Jan-08

9.48

11.90

Feb-08

9.42

11.30

Mar-08

9.42

14.10

Apr-08

9.43

17.20

May-08

9.44

19.30

Jun-08

12.06

21.50

Jul-08

12.43

24.30

Aug-08

12.03

25.30

Sep-08

12.88

23.90

Oct-08

14.10

25.00

Nov-08

13.74

24.70

Dec-08

13.42

23.30

Jan-09

13.87

20.50

Feb-09

12.28

21.10

Mar-09

10.64

19.10

Apr-09

12.54

17.20

May-09

12.91

14.40

Jun-09

13.11

13.10

Jul-09

12.09

11.20

Aug-09

11.79

10.70

Sep-09

12.17

10.10

Oct-09

12.29

8.90

Nov-09

## -------

8.90

## OUTPUT FOR TEST OF CORRELATION

## Correlations

Interest Rate

Rate of Inflation

Interest Rate

Pearson Correlation

1

.757**

Sig. (2-tailed)

.000

N

53

53

Rate of Inflation

Pearson Correlation

.757**

1

Sig. (2-tailed)

.000

N

53

53

**. Correlation is significant at the 0.01 level (2-tailed).

## OUTPUT FOR AUTO-REGRESSION

## ITERATION 0

## Autocorrelation Coefficient

Rho (AR1)

Std. Error

0

3.987

The Prais-Winsten estimation method is used.

## Model Fit Summary

R

R Square

Std. Error of the Estimate

Durbin-Watson

.757

.573

3.987

.265

The Prais-Winsten estimation method is used.

## ANOVA

Sum of Squares

df

Mean Square

Regression

1085.592

1

1085.592

Residual

810.637

51

15.895

The Prais-Winsten estimation method is used.

## Regression Coefficients

Standardized Coefficients

t

Sig

Beta

Interest Rate

.757

8.264

.000

(Constant)

-4.055

.000

The Prais-Winsten estimation method is used.

## ITEREATION 5

## Autocorrelation Coefficient

Rho (AR1)

Std. Error

.972

.033

The Prais-Winsten estimation method is used.

## Model Fit Summary

R

R Square

Std. Error of the Estimate

Durbin-Watson

.119

.014

1.405

1.266

The Prais-Winsten estimation method is used.

## ANOVA

Sum of Squares

df

Mean Square

Regression

1.415

1

1.415

Residual

98.765

50

1.975

The Prais-Winsten estimation method is used.

## Regression Coefficients

Standardized Coefficients

t

Sig

Beta

Interest Rate

.119

.846

.401

(Constant)

1.488

.143

The Prais-Winsten estimation method is used.

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