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# Determinants of Interest Rates | Literature Review

Info: 4513 words (18 pages) Example Literature Review
Published: 6th Dec 2019

Tagged: Banking

## Problem Statement

To study the determinants of interest rate.

## Hypothesis

H1: Inflation in an economy has a positive impact on interest rates.

H2: Exchange rate fluctuation has a positive impact on interest rates.

## Outline of the Study

Section 2 covers the literature review on “DETERMINANTS OF INTEREST RATES”. Chapter 3 shows methodology which includes method of data collection, data collection source sampling technique and sample size. Section 4 cover results, recommendation, discussion and summary. Final chapter which is chapter 5 covers conclusion of complete study and remarks.

## Definitions:

KIBOR: Karachi Inter Bank Offer Rate (KIBOR) is a rate given by expert and specialized institutions on weekly, monthly and 1, 2 and 3 yearly basis to all the commercial banks of Pakistan to charge their customers accordingly. KIBOR is inflation adjusted rate, and banks add extra 2% to 3% in KIBOR to charge their customers to earn profit.

Inflation: refers to an increase in general price level in a country in a particular time period. Or inflation is generally considered as an inordinate rise in general prices in a country.

Exchange Rate: An exchange rate (also known as FOREX rate, FX rate or Foreign Exchange Rate) is defined as the rate at which one currency is exchanged with another currency. Or it is the value of one currency in-term of another currency. For example an inter bank exchange rate of 86 Pakistani Rupee (Rs Rupee) to United State Dollar (US \$) means US\$1 will be exchanged for each Rs 86.

## 3.1 Methods of Data Collection

All data which was used in my research would be collected through secondary sources includes State Bank of Pakistan (SBP) and Security and exchange commission of Pakistan (SECP).

## 3.2 Sampling Technique

Secondary data will be used and total information will be collected from secondary sources.

## 3.3 Sample Size

6- Years data was taken from SBP and SECP on monthly basis from 2005 to 2010.

## 3.4 Instrument of data collection

This research is totally based on secondary data. No any instrument/primary data was used in my research.

## 3.5 Statistical Technique

In my research I used Multiple Linear regression (MLR). Multiple linear regression is a statistical model which examines the relationship between two or more explanatory variables and a response variable by fitting a linear equation to observed data.

y = http://www.stat.yale.edu/Courses/1997-98/101/beta.gif0 + http://www.stat.yale.edu/Courses/1997-98/101/beta.gif1x1 + http://www.stat.yale.edu/Courses/1997-98/101/beta.gif2x2 + … + http://www.stat.yale.edu/Courses/1997-98/101/beta.gifpxp

To examine the data the data Statistical Package for the Social Sciences (SPSS) software is used.

The equation of my model is following:

Y = 2.864 + 0.116X1 – 0.037X2

Where,

Y= Karachi inter bank offer rate (KIBOR)

x1=CPI

x2=Exchange Rate

## RESULTS AND IMPLICATIONS

The data of 6 year monthly average was taken from State Bank of Pakistan and Security and Exchange Commission of Pakistan of KIBOR, Inflation (CPI) and exchange rate. The statistical technique that was study for this study was Multiple Linear Regression (MLR). This study tends to focus on the impact of inflation and exchange rate on KIBOR. And data examination was done with the help of Statistical Package for Social Sciences (SPSS).

## 4.1 Findings and Interpretation of the results

My research is based on 3 variables.

KIBOR= Dependant Variable

CPI= Independent Variable

EXCHANGE RATE= Independent variable

## Model Summary

Model

R

R Square

Std. Error of the Estimate

1

.893a

.797

.791

.97749

Predictors: (Constant), EXRT, CPI

Dependent Variable: KIBOR

The co efficient of determination (R2) is 79.7%. This explains that the variation in KIBOR with respect to CPI and Exchange Rate is up to 79.7%.

## ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

259.338

2

129.669

135.711

.000a

Residual

65.928

69

.955

Total

325.266

71

a. Predictors: (Constant), EXRT, CPI

b. Dependent Variable: KIBOR

The value of F-statistic is 135.711 which is high and the p-value is 0.000 which is less than 0.05 (level of significance) this implies that the test of ANOVA is significant and the model is valid from the given predictors.

## Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Collinearity Statistics

B

Std. Error

Beta

Tolerance

VIF

1

(Constant)

1.573

.766

2.053

.044

CPI

.180

.027

.445

6.740

.000

.675

1.481

EXRT

.109

.013

.561

8.514

.000

.675

1.481

a. Dependent Variable: KIBOR

Here the significance value (the p-value) is less than 0.05 which means that the constant term as well as the coefficient of independent variables is significant for model. The overall research result shows that there is a positive impact of inflation (CPI) and Exchange rate on KIBOR.

## HYPOTHESIS ASSESMENT SUMMARY

NO

Hypothesis

Beta

Accept/Reject

1

Inflation in an economy has a positive impact on interest rates.

.445

Accept

2

Exchange rate fluctuation has a positive impact on interest rates.

.561

Accept

## DISCUSSIONS, IMPLICATIONS, FUTURE RESEARCH AND CONCLUSIONS

In this study data of monthly rates was collected from State Bank of Pakistan (SBP) and Security and Exchange Commission of Pakistan (SECP) for dependant variable KIBOR and independent variables, inflation and exchange rate from 2005 to 2010 and the statistical technique that was used to examine the data was Multiple Linear Regression (MLR). SPSS was used along with Multiple linear Regression to evaluate the impact of the independent variables i.e. inflation and exchange rate on dependent variable KIBOR.

## 5.1 CONCLUSION

This research study concludes that among the two independent variables inflation and exchange rate both exchange rate and inflation (CPI) has a positive relationship with the dependent variable KIBOR. So we can conclude that an increase in inflation (CPI) and exchange rate will result in an increase in KIBOR and a decrease in inflation (CPI) and exchange rate will reduce KIBOR.

## 5.2 IMPLICATIONS AND LIMITATIONS

It is very important for Government and Financial institutes to get some extra information about the variables that can affect interest rate to fluctuate. Investors and financial institutions can analyze and observe the behavior of KIBOR more effectively and efficiently with the help of this study. Whereas limitations are concerned this study has few limitations, out of numerous factors that can determine KIBOR only few of those are taken into account due to the shortage of time availability and some security risks involved.

## 5.3 RECOMMENDATIONS

This study was limited to only two factors that affect KIBOR whereas there can be more than two factors which can affect KIBOR. The data was taken for only 6 years from 2005 to 2010 but research can also be conducted for longer time period.

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Banking can be defined as the business of a bank or someone employed in the banking industry. Used in a non-business sense, banking generally means carrying out activities related to the management of one’s bank accounts or finances.

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