A Time Series Analysis on Correlation between Inflation Rate, Monetary Policy and Interest rate with Gross Domestic

BWFF3033 FINANCIAL MARKET AND INSTITUTIONS

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INTRODUCTION ................................................................................................................................. 2

LITERATURE REVIEW .................................................................................................................... 3

LITERATURE REVIEW BASED ON INFLATION ........................................................................ 3

LITERATURE REVIEW BASED ON INTEREST RATE ............................................................... 4

LITERATURE REVIEW BASED ON MONETARY POLICY ........................................................ 4

LITERATURE REVIEW BASED ON STOCK AND INVESTMENT ............................................ 5

METHODOLOGY ............................................................................................................................... 6

Data Source ......................................................................................................................................... 6

Estimation Technique ......................................................................................................................... 6

RESULTS AND DISCUSSION ........................................................................................................... 7

RESULTS ........................................................................................................................................... 7

DISCUSSION ..................................................................................................................................... 9

CONCLUSION ......................................................................................................................... 11

REFERENCES ......................................................................................................................... 12

APPENDIX ............................................................................................................................... 14

TABLE OF CONTENTS


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A Time Series Analysis on Correlation between Inflation Rate, Monetary Policy and

Interest rate with Gross Domestic Product

Mohamad Helmi Surep, Norhidayah Mohd Idros, Zarina Mohd.Nor,

Nor Faezah Che Hamzah and Nur Amirah Mohamad

Colloege of Business (COB), School of Economic, Finance and Banking (SEFB)

Universiti Utara Malaysia (UUM) 06010, Changloon Kedah, Malaysia

Abstract: This paper examines the correlation between inflation rate, monetary policy and

interest rate with gross domestic product (GDP) in Malaysian over the period 1980 to 2010.

The paper reports a strong relation between inflation rate based on CPI, monetary policy in

money supply and interest rate for deposit account with gross domestic product (GDP) in

Malaysian.

Keyword: Inflation rate, monetary policy, interest rate, gross domestic product.

INTRODUCTION

INTRODUCTION: A time series model can provide a reasonable benchmark to evaluate the

value added in forecasting of economic theory relative to the pure explanatory power of the

past behaviour of the variable. In this paper we conduct a detailed analysis of the time series

analysis on correlation between inflation rate, monetary policy and interest rate with gross

domestic product (GDP) focusing on the Malaysia, for which 30 years time series analysis

from 1980 to 2010. Our main goal is to investigation whether this 3 variable have correlation

between long-run economic growth and GDP.

The gross domestic product (GDP) or gross domestic income (GDI) is the value of

total production of goods and services in a country over a specified period and it is one of the

measures of national income and output for a given country's economy. GDP can be defined

in three ways, all of which are conceptually identical. First, it is equal to the total

expenditures for all final goods and services produced within the country in a stipulated

period of time (usually a 365-day year). Secondly, it is equal to the sum of the value added at

every stage of production (the intermediate stages) by all the industries within a country, plus

taxes less subsidies on products, in the period. Third, it is equal to the sum of the income

generated by production in the country in the period—that is, compensation of employees,

taxes on production and imports less subsidies, and gross operating surplus (or profits). The

most common approach to measure GDP is using the expenditure method:

GDP = Private Consumption + Gross Investment – Government

Spending + (Export – Import)

According to the graft, it shows the Malaysia GDP per purchasing power parity (PPP)

from year 1980 till 2010. We can see that at year 1980 increase to 1985 and then stable at

year 1986 and 1987. Next, it rises till year 1998 but drop at year 1989. After that, the graft

also shows that the GDP per capita PPP increase slowly until 2009 which is a value is 14000

that the highest value than other years. Lastly, it decline to 13900 at year 2000.


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From this graph we can conclude that the graft has fluctuated among year and the

factor that influences this GDP became fluctuated is inflation based on CPI, interest in

deposit and monetary policy in money supply. In this paper also we had a additional variable

that might be influence the GDP, but our analysis is not focus on this additional variable we

just give a overview how does this stock market will influence GDP by giving a past research

by other researcher in the literature review section. Next, the basic assumptions for this

research are:

Null hypothesis (H0) : Inflation rate, interest rate and money supply do not have a

Significant influence on Gross Domestic Product in Malaysia

Alternative hypothesis (H1): Inflation rate, interest rate and money supply have a

Significant influence on Gross Domestic Product in Malaysia

Lastly, this paper consists of five sections. In section, the literature review that is

consists of four variables that have been chosen. In section three, the methodology that is will

discuss about how we get the data and the estimation technique. In section four, the result of

the analysis and the discussion based on our literature review. Section five is our conclusion

about this research.

LITERATURE REVIEW

LITERATURE REVIEW BASED ON INFLATION

Multivariate Time Series Analysis on Correlation between Inflation Rate and

Employment Rate with Gross Domestic Product

This journal is written by Fadli Fizari Abu Hassan Asari, Zuraida Mohamad, The Sofia Alias,

Norazidah Shamsudin, Nurul Syuhada Baharuddin and Kamaruzaman Jusoff on 2011 at

Faculty of Business Management, Universiti Teknologi MARA, Dungun and at Faculty of

Forestry, Universiti Putra Malaysia. This study examined the correlation between inflation

rate and total employment with gross domestic product. It uses time series data ranging from

1982 to 2006 and the scope is in Malaysia. The researcher applied STATA software to

process the data using log-log model in this study


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A Comparison of Time Series Models for Forecasting GDP Growth and Inflation

This journal is written by Massimiliano Marcellino on April 2007 at IEP-Universita Bocconi,

IGIER and CEPR. In this paper the researcher conduct a detailed analysis of the forecasting

performance of univariate time series models for GDP growth and inflation, the two key

variables for macroeconomic analysis, focusing on the US, for which very long time series

are available. The researcher has use Forecasting method that have linear method, time-

varying methods and non-linear methods. In summary, the gains from a more careful

specification of the benchmark model for GDP growth and inflation appear to be both

statistically and economically significant.

LITERATURE REVIEW BASED ON INTEREST RATE

An Impact Analysis of Real Gross Domestic Product Inflation and Interest Rates on

Stock Prices of Quoted Companies in Nigeria

The journal case study from Department of Accounting, Faculty of Management Sciences

Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria by Daferighe. Emmanuel E

and Aje. Samuel O. This journal was published in online on 2009 by © EuroJournals and this

journal aimed at examining the relationship between real GDP, inflation and interest rates,

and stock prices with a view to determining whether the fluctuations in the behaviour of stock

prices is influenced by those variables and analyse the impacts arising thereby. This research

intends to assess the impact of real GDP, inflation and interest rates on stock prices of quoted

companies in Nigeria and the method that use in this research are based on Stock Market

Value Index (SMVI).

The Impact of Foreign Interest Rates on the Economy: The Role of the Exchange Rate

Regime

The journal case study from Department, International Monetary Fund, Street, N.W.,

Washington on 27 June 2007 by Julian di Giovanniy and Jay C. Shambaugh. This journal

about the effect of interest rates in based on countries on other countries' annual real GDP

growth. This paper explores the connection between interest rates in major industrial

countries and annual real output growth in other countries and examines the potential

channels through which major-country interest rates affect other economies. We confirm the

results by moving beyond standard panel analysis, using a random coefficient model which

allows us to use a variety of controls and test why some countries experience more of an

impact from foreign interest rates.

LITERATURE REVIEW BASED ON MONETARY POLICY

Impact of Monetary Policy on Gross Domestic Product (GDP)

The journal case study from Iqra University, Business Administration Department, Karachi

and College of Management Sciences, Karachi on 27 June 2007. This literature was written

by Irfan Hameed and Ume-Amen it also can be obtained from the website ijcrb.webs.com.

This research article focuses on the impact of monetary policy on GDP and the country was

Pakistan. The study proved that the interest rate has minor relationship with GDP but the

growth in money supply greatly affects the GDP of an economy. This research use three

method is a data sources and nature of data in detail, the model to be applied to find out the

results and the hypothesis to be checked for this study.


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Fiscal and Monetary Policies and Economic Growth

The journal case study from Doctoral School of Finance and Banking, Academy of Economic

Bucharest, Romania and it was written by Moisa Altar on January 2003. This paper analyses

the way in which monetary and fiscal policy influences the performances of economic growth

and the methodology that this author use basis of a dynamic model with discrete variables of

the Sidrauski- Brock type, with infinite-lived households and money in the utility function.

This paper aim is to analyze the influence of several monetary and fiscal decisions on the

optimal trajectories and on the performance-function of the model

The Effects of Money Supply on Economic Growth in Iran

This literature was written by Fahimeh Movahedi Rad about The Effects of Money Supply on

Economic Growth in Iran. It was published in © EuroJournals on 2012 at Department of

Human Sciences, Islamic Azad University Mashhad Branch, and Mashhad, Iran. The journal

can be obtained from the website www.eurojournals.com/ajsr.htm. This literature concern

about symmetric impacts of monetary shocks on economic growth Applying econometric

technique by co-integration analysis and Error correction mechanism in Iran economy during

the period 1960-2010. This literature consists the theoretical and empirical literature of the

asymmetric effects of monetary shocks also Effects too Money Supply on Economic Growth

in Iran .In conclude, this happen at short run economic growth by increasing unexpected

money and must pay a higher cost in the long run to decrease inflation.

Linkage between Monetary Instruments and Economic Growth

This literature was written by Hameed Gul, Dr Khaid Mughal, and Dr Sabit Rahim on May

2012 at Islamabad about the Linkage between Monetary Instruments and Economic Growth.

In the literature it is showed that how the decisions of monetary authorities influence the

macro variables like GDP, money supply, interest rates, exchange rates and inflation. The

foremost objective of monetary policy is to enhance the level of welfare of the masses. The

method of least square OLS was used as strategy to explain the relationship between the

variables under study.

LITERATURE REVIEW BASED ON STOCK AND INVESTMENT

Stock Market and Economic Growth: An Empirical Analysis for Germany

The journal case study from Department of Applied Informatics, University of Macedonia,

Thessaloniki, Macedonia, Greece by Adamopoulus Antonios. It was published in online on

April 15, 2010. The main objective of this paper was to investigate the causal relationship

among economic growth, stock market development and bank lending at the Germany for the

period 1965-2007 using a Vector Error Correction Model (VECM).

Financial Stock Market and Economic Growth in Developing Countries: The Case of

Douala Stock Exchange in Cameroon

Rachelle Wouono Ognaligui was written this literature on May 2010 about Financial Stock

Market and Economic Growth in Developing at Cameroon, China. This paper examines

Sims’ causality test based on Granger definition of causality was used to examine causality

relationships between stock markets and economic growth in Cameroon based on the time

series data from 2006 to 2010. Our paper comes up with the opportunity given to the

Cameroonian government to understand that it is time to find financial policies, to encourage

companies and develop financial stock market culture, and enhance to push companies to

initiate IPO instead of bank loans when money is needed to increase their investment. It used


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Granger equation as a methodology in this literature to calculate whether stock market

development causes economic growth, or vice versa. In addition,

METHODOLOGY

Data Source

Data Source: In order to check the correlation between inflation rates, monetary policy and

interest rate with GDP we required to research inflation rate based on CPI, interest rate on

deposit in financial institution, monetary policy money supply (M2) and GDP at purchase

price. All this data is in term of currency Ringgit Malaysia and this data gather from the

period 1980-2010. The main data source in this regard has been the World Data Bank and the

additional sources was official websites of Bank Negara Malaysia has also been visited in this

regard.

Variables: Description for each variable under study is as under:

Monetary Policy: Monetary policy is the total amount of money available in an economy

at a particular point of time. The importance of an appropriate

monetary aggregate can hardly be over emphasized, particularly for

those countries that attach their monetary policy to monetary

aggregates. In this case we only focus in money supply M2

Interest Rate: Interest rate is the term interest rate usually means any bank lending

rate. However, the rates don’t always move rapidly because they are

driven by different forces. This rate is focus more on deposit in

financial institution. In this research we only look at bank institution.

Inflation: Inflation refers to the persistent rise in general price level. Inflation

affects the distribution of both income and wealth. In this case our is

more to inflation based on consumer price index CPI

Estimation Technique

Estimation Technique: To conduct this time series analysis we have applied EVIEW

software to process the data by using log-log model. The logarithm equation is as below: In

this EVIEW software we conduct two difference way analyses.

LOGGDP = - α + β LOGINFLATION - β LOGINTEREST + β LOGM2

Unit Roof Test: this Unit Roof Test use to integration orders of variables are examined by

Augmented Dickey – Fuller (ADF) unit root tests. Unit root tests are important to test

integration between the variables involved in the research conducted. This analysis involving

GDP, inflation, interest rate and money supply in two difference analyses that is trends and

trend intercept. This result of unit test we show whether the data have integrated between

GDP with inflation, interest rate and money supply.


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Co-Integration Test: This is followed by a multivariate co-integration analysis. The

multivariate co-integration techniques developed by Johansen and Juselious; Engle and

Granger using a maximum likelihood estimation procedure allows researchers to estimate

simultaneously models involving two or more variables to circumvent the problems

associated with the traditional regression methods used in previous studies on this issue.

Therefore, the Johansen method applies the maximum likelihood procedure to determine the

presence of cointegrated vectors in non-stationary time-series.

Vector error correction model: Since the variables included in the VAR model are found to

be co-integrated, the next step is to specify and estimate a Vector Error Correction Model

(VECM) including the error correction term to investigate dynamic behaviour of the model.

Once the equilibrium conditions are imposed, the VEC model describes how the examined

model is adjusting in each period towards its long-run equilibrium state.

RESULTS AND DISCUSSION

RESULTS

4.1 Descriptive Statistics

Table 1: Descriptive statistics on the data

Descriptive statistics: Table 1 shows the descriptive statistics including the minimum and

maximum values, mean, standard deviation and skewness of data. Firstly standard deviation

is widely used measure of the variability or dispersion, being algebraically more tractable

through practically less robust than the expected deviation or average absolute deviation. A

low standard deviation indicates that the data point to be very close to mean, vice verse.

Standard deviation for GDP at purchaser's prices is RM283427.8 and standard deviation for

inflation based on CPI is 2.077012. Next standard deviation for interest based on deposit is

2.606031and lastly standard deviation for money supply M2 is RM310000000000 or

3.10E+11. In addition skewness is a term describing the non-symmetry of a bell shaped

distribution. Skewed right is when too much data is on the left side of the curve, skewed left

is when too much data is on the right side of the curve. Skewness is important to know

because it can create some inaccurate estimates of means and standard deviations of data

expected to be symmetric. To get more analysis on these data we conduct a further analysis

that is unit root tests.

Stats GDP Inflation Interest M2

Min 54285.00 0.000000 2.000000 4.30E+10

Max 765965.0 10.00000 10.00000 1.06E+12

Mean 283427.8 3.225806 5.483871 3.59E+11

Sd 221375.6 2.077012 2.606031 3.10E+11

Sk 0.824469 1.060141 0.368642 0.844453


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4.2 Unit Roof Tests

Table 2: Results of Unit Roots Tests Based on Augmented Dickey-Fuller (ADF) Test

Trend Intercept and Trend

Level First Difference Level First Difference

LogGP -0.275231 -4.013205** -2.373107 -3.920186**

LogINFLATION -2.131528 -2.972549* -3.233263 -4.449267**

LogINTEREST -1.794903 -4.585405** -3.074261 -5.126128**

LogM2 -0.662644 -5.219095** -2.600832 -2.895983**

Notes: *, ** denote significance at 5% and 1% significant levels respectively.

Unit roof tests: In this analysis all variable have been tested at level and first difference.

From Augmented Dickey-Fuller (ADF) test we did trend analysis and trend intercept

analysis, firstly the result for trend analysis show that for t-statistics are statistically not

significant at level meaning that the null hypothesis is not rejected. This indicates that these

series are non-stationary at their level from. Consequently, the process is continued into the

first difference values of data and is show that this data have stationary at first difference.

After al variable finish with this analysis, our analysis continued to ADF trend intercept

analysis. The result from this analysis give us the same result from trend analysis that is

stationary at first difference but not at level. Based on table 2, it is show that all variable are

now stationary at first difference. Thus, all of the respective null hypotheses are rejected. This

analysis still continues with co-integration test.

4.3 Co-integration Test

Co-integration test: Cointegration rank (rank of matrix o) is estimated using Johansen

methodology. Johansen’s approach derives two likelihood estimators for the CI rank: a trace

test and a maximum Eigen value test.

Table 3: Results of Johansen-Juselius Test

Eigenvalue Statistics Trace statistic 5% Critical Value 1% Critical Value

r = 0 0.845452 72.08355** 47.21 54.46

r = 1 0.612749 31.00404* 29.68 35.65

r = 2 0.307547 10.13305 15.41 20.04

r = 3 0.088878 2.047721 3.76 6.65

Note: * indicates a significant level at 5%. The Trace and Max. Eigen value statistics have

been adjusted based on T-kn/T where T=number of effective observations, k=lag length,

n=number of independent variables

The CI rank (R) can be formally tested with the trace and the maximum Eigen value

statistics. The results are presented in Table 3. The trace statistic either rejects the null

hypothesis of no co-integration among the variables or does not reject the null hypothesis that

there is one co-integration relation between the variables. Start by testing H0: r = 0. If it

rejects, repeat for H0: r = 1. When a test is not rejected, stop testing there and that value of r is

the commonly-used estimate of the number of cointegrating relations. In this test, H0: r = 1 is

rejected at the 5% level (31.00 > 29.68). In other words, this trace test result rejects the null

hypothesis that these four variables are cointegrated at one co-integration. Since null

hypothesis is significant at r=1 so that we can conclude that at one co-integration exists


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among the variable. To know whether our variable moves closely to achieve that long run

equilibrium we will conduct further analysis that is Vector Error Correction.

Table 4: Long-run Equilibrium Coefficients for VECM

Variable Coefficient Std. Error t-Statistic Prob.

LNINTEREST -0.031969 0.101699 -0.314346 0.7559

LNINFLATION 0.098254 0.054399 1.806186 0.0829

LNM2 0.853898 0.049306 17.31824 0.0000

C -10.17191 1.430300 -7.111731 0.0000

R-squared 0.975875 Mean dependent var 12.29226

Adjusted R-squared 0.972979 S.D. dependent var 0.844986

S.E. of regression 0.138898 Akaike info criterion -0.982710

Sum squared resid 0.482317 Schwarz criterion -0.794118

Log likelihood 18.24930 F-statistic 337.0831

Durbin-Watson stat 1.323069 Prob(F-statistic) 0.000000

Vector Error Correction Model: The presence of cointegration between variables show that

exists one co-integration among variable, to know whether GDP, inflation, interest and

money supply have long-run relationship in the period 1980 - 2010 the VEC model can be

applied.

LGGDP = - 10.1719 + 0.09825LGINFLATION - 0.03196LGINTEREST + 0.85389LGM2

The cointegrating equation: Which is given at above has been normalized for LGGDP just

to get meaning from the coefficients. As all variable are logarithmic, we may interpret

coefficients in terms of elasticity because we have one co-integration among variable. So we

may say that 1 percent increase in inflation is associated with 0.098 percent increase in

Malaysia’s GDP. The coefficient of money supply M2 rate is also significant, and its value is

0.854 showing that 1 percent increase (decrease) will increase (decrease) GDP by 0.854

percent. On the other hand, the coefficients of interest showing that 1 percent increase in

interest on deposit is associated with 0.0319 percent decrease in GDP. Thus, GDP elasticity

with respect to money supply M2 is more elastic as compared to GDP elasticity with respect

to inflation and interest. This result clearly shows that monetary policy is the main factor that

effect Malaysia’s GDP from 1980 to 2010.

DISCUSSION

DISCUSSION: This paper currently study about the correlation between inflation rate,

monetary policy and interest rate with gross domestic product (GDP) in Malaysian over the

period 1980 to 2010. From the finding it is show that the entire variable has a correlation with

GDP in economic growth respectively. But the relationship between GDP and entire variable

can divide into two, which is in short-run economic growth and long-run economic growth.

INFLATION AND GDP

From our finding we can conclude that inflation only have a short-run economic growth, a

very limited role in GDP and have negative relationship with GDP. According to Fadli Fizari

Abu Hassan Asari et al.(2011) in journal Multivariate time series analysis on correlation

between inflation rate and employment rate with gross domestic product has mention that


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“the effects of inflation on economic growth continues to be an important and complex topic

in economic. Based on statement, if inflation has real economic effects, then governments can

influence economic performance through monetary policy”. Other that he also mentions that

“The structuralisms argue that inflation is necessary for economic growth, whereas the

monetarists argue the opposite” and he stated that “Inflation does not affect real output in the

long run, but that in the short-run inflation negatively affects output”. Besides this journal,

from other journal also give a same result from their research for example a journal that is A

comparison of time series models for forecasting GDP growth and inflation by Massimiliano

Marcellino (2007) has mention that “We can anticipate that we find a very limited role for

nonlinearity for both GDP growth and inflation, while a careful specification of the linear

models is very important” and the conclusion that led them in research say that “Inflation

forecasts produced by the Phillips curve generally have been more accurate than forecasts

based on other macroeconomic variables, including interest rates, money and commodity

prices”

INTEREST AND GDP

From this analysis it shows that interest rate in deposit only has negative relationship with

GDP and it will effect in short-run economic growth only. From other finding by Julian di

Giovanniy and Jay C. Shambaugh (2007) in their journal The Impact of Foreign Interest

Rates on the Economy: The Role of the Exchange Rate Regime show that “The main finding

thus implies that there are real costs to the loss of monetary autonomy that comes with

pegging and provides further support for the hypothesis that interest rates can have

substantial effects on the real economy. Specifically, base-country interest rates that are 1

percentage point higher lead to a 0.20 percentage point decline in annual GDP growth in

pegged countries as opposed to no change in countries with floats” this clearly show that

interest only give negative relationship to GDP as Julian di Giovanniy and Jay C.

Shambaugh (2007) said.

MONETARY POLICY AND GDP

Based on this analysis money supply give a positive relationship to GDP and it is more to

long-run economic growth compare to inflation and interest rate. From the journal that is

impact of monetary policy on gross domestic product (GDP) by Irfan Hameed and Ume-

Amen stated that “Monetary policy rests on the relationship between the rates of interest in an

economy, that is the price at which money can be borrowed, and the total supply of money.

Monetary policy uses a variety of tools to control one or both of these, to influence outcomes

like economic growth, inflation, exchange rates with other currencies and unemployment”

from this statement it show that money supply or monetary policy will affect many part of

economic, not only GDP. In our case money supply has effect the most in GDP so that the

percentage increase in GDP is higher in money supply. Other than that, according Fahimeh

Movahedi Rad in his journal The Effects of Money Supply on Economic Growth in Iran stated

that “although policy makers can increase the economic growth to some extent by supplying

unexpected amount of money, but with reduction of money supply and inflation, they should

spend much more due to the reduction of economic growth. Thus economic policy makers

should always consider monetary disciplines and macroeconomic stability and they should

not sacrifice it for short-term meager economic growth interest.” Based this statement it give

us evidence about our analysis.


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STOCK MARKET AND GDP

At the introduction section we have discuss about our additional variable that will affect

Malaysia’s that is stock market. It this section we will give a brief example and evidence how

does stock market effect GDP or economic growth. Firstly according to Adamopoulus

Antonios in his journal Stock Market and Economic Growth: An Empirical Analysis for

Germany. “Stock market development may influence economic growth is risk diversification.

Obstfeld suggests that international risk sharing through internationally integrated stock

markets improves the allocation of resources and accelerates the process of economic growth.

Evolution of stock market has impact on the operation of banking institutions and hence, on

economic promotion. This means that stock market is becoming more crucial, especially in a

number of emerging markets and their role should not be ignored. Information in stock

markets is contained in equity prices, while loan managers collect that in banks.” So this how

will stock market influence the growth of economic. In addition, journal Financial Stock

Market and Economic Growth in Developing Countries: the Case of Douala Stock Exchange

in Cameroon by Rachelle Wouono Ognaligui stated that

“The financial stock market facilitates higher investments and the allocation of capital, and

indirectly the economic growth. Sometimes investors avoid investing directly to the

companies because they cannot easily withdraw their money whenever they want. But

through the financial stock market, they can buy and sell stocks quickly with more

independence. An efficient stock market contributes to attract more investment by financing

productive projects that lead to economic growth, mobilize domestic savings, allocate capital

proficiency, reduce risk by diversifying, and facilitate exchange of goods and services.

Positive causal correlation between stock market development and economic activity. Many

other researchers argue that there is a positive correlation between financial development and

economic growth”. From both of this report it clearly show how does stock market affect the

GDP.

CONCLUSION

Conclusion: In this paper we have provided an extensive evaluation of the role of

sophisticated time series analysis on correlation between inflation rate, monetary policy and

interest rate with gross domestic product. We know that the factor that influences GDP

became fluctuated is inflation based on CPI, interest in deposit and monetary policy in money

supply. Our conclusion is inflation and interest rate influence the GDP in the short run only.

It means that inflation and interest rate only have a short-run economic growth, a very limited

role in GDP and have negative relationship with GDP. In addition, there is no relationship

between inflation and interest rate with GDP in the long run. However, from this analysis

money supply and our additional variable that is stock market give a positive relationship to

GDP and it is more to long-run economic growth compared to inflation and interest rate.

Besides, money supply or monetary policy will affect many part of economic, not only GDP.

Therefore, the result is called unidirectional since only money supply and stock market can

influence the GDP in the long run. This finding is particularly evident because we use real

time data or considering only the period starting from 1980 until 2010. It is recommended

that future researchers should improve the reliability and validity of the result by replacing

the other independent variables such as level of income, population and others.


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APPENDIX

Data 1: Original Data

Series Name

GDP (current

LCU) M2 (current LCU)

Deposit interest rate (%)

Inflation, consumer prices (annual

%)

1980 54,285 42,988,400,000 6 7 1981 58,669 51,521,800,000 10 10 1982 63,726 59,944,942,857 10 6 1983 71,223 69,845,700,000 8 4 1984 81,009 81,224,200,000 10 4 1985 78,890 89,196,000,000 9 0 1986 72,907 100,776,900,000 7 1 1987 81,085 102,999,600,000 3 0 1988 92,370 111,841,100,000 5 3 1989 105,233 136,257,600,000 6 3 1990 119,081 76,660,900,000 7 3 1991 135,123 89,599,100,000 8 4 1992 150,682 154,031,700,000 7 5 1993 172,193 194,638,300,000 5 4 1994 195,460 217,037,900,000 6 4 1995 222,472 257,245,200,000 7 3 1996 253,733 304,796,200,000 8 3 1997 281,795 353,672,088,820 9 3 1998 283,243 354,483,971,030 4 5 1999 300,764 397,372,516,000 3 3 2000 356,401 437,299,573,000 3 2 2001 352,579 488,183,360,263 3 1 2002 383,213 510,073,620,908 3 2 2003 418,769 554,078,590,009 3 1 2004 474,048 624,375,109,916 3 2 2005 522,445 679,277,474,460 3 3 2006 574,441 771,869,840,064 3 4 2007 642,049 833,021,504,227 3 2 2008 742,470 920,783,860,959 3 5 2009 679,938 992,051,869,993 2 1

2010 765,965 1,064,945,222,88

7 3 2

Data 2: Data In Terms of Logarithm Year LNGDP LNDEPOSIT LNINFLATION LNM2

1980 10.9020032247 1.79175946923 1.94591014906 24.4841961488

1981 10.9796667573 2.30258509299 2.30258509299 24.665270856

1982 11.0623479215 2.30258509299 1.79175946923 24.8166923588

1983 11.1735710789 2.07944154168 1.38629436112 24.9695543603

1984 11.3023155386 2.30258509299 1.38629436112 25.1204790693

1985 11.2758097561 2.19722457734 N/A 25.2141020325

1986 11.1969399353 1.94591014906 0 25.3361749997

1987 11.3032532662 1.09861228867 N/A 25.3579909417

1988 11.4335575296 1.60943791243 1.09861228867 25.4403449509

1989 11.5639322183 1.79175946923 1.09861228867 25.6378130488

1990 11.6875592128 1.94591014906 1.09861228867 25.062657637

1991 11.8139407537 2.07944154168 1.38629436112 25.2186111122

1992 11.9229269349 1.94591014906 1.60943791243 25.7604242623

1993 12.0563712197 1.60943791243 1.38629436112 25.9944088013

1994 12.1831110339 1.79175946923 1.38629436112 26.1033378296

1995 12.31255653 1.94591014906 1.09861228867 26.2732955526

1996 12.444037812 2.07944154168 1.09861228867 26.4429091935

1997 12.5489351352 2.19722457734 1.09861228867 26.591636018

1998 12.5540604654 1.38629436112 1.60943791243 26.5939289662

1999 12.614081183 1.09861228867 1.09861228867 26.7081400051

2000 12.7838117804 1.09861228867 0.69314718056 26.8038843189

2001 12.7730299896 1.09861228867 0 26.9139569105

2002 12.8563462493 1.09861228867 0.69314718056 26.957820907

2003 12.9450747342 1.09861228867 0 27.0405723729

2004 13.0690638614 1.09861228867 0.69314718056 27.1600171624

2005 13.1662749941 1.09861228867 1.09861228867 27.2442955327

2006 13.261152673 1.09861228867 1.38629436112 27.3720817718

2007 13.3724199037 1.09861228867 0.69314718056 27.4483252942

2008 13.5177377448 1.09861228867 1.60943791243 27.548491167

2009 13.4297568965 0.69314718056 0 27.6230412312

2010 13.5488917558 1.09861228867 0.69314718056 27.6939444799

Data 3: co-integration Test

Date: 10/28/12 Time: 13:07 Sample: 1980 2010

Included observations: 22 Test assumption: Linear deterministic trend in the data

Series: LNGDP LNDEPOSIT LNINFLATION LNM2 Lags interval: 1 to 2

Likelihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Value Critical Value No. of CE(s)

0.845452 72.08355 47.21 54.46 None ** 0.612749 31.00404 29.68 35.65 At most 1 * 0.307547 10.13305 15.41 20.04 At most 2 0.088878 2.047721 3.76 6.65 At most 3

*(**) denotes rejection of the hypothesis at 5%(1%) significance level L.R. test indicates 2 cointegrating equation(s) at 5% significance level


15 | P a g e

Data 4: Unit Roof Test – Trend

Interest

Level First Difference ADF Test Statistic -1.794903 1% Critical Value* -3.6752

5% Critical Value -2.9665


*MacKinnon critical values for rejection of hypothesis of a unit root.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(LNDEPOSIT)

Method: Least Squares

Date: 10/11/12 Time: 17:29

Sample(adjusted): 1982 2010

Included observations: 29 after adjusting endpoints


LNDEPOSIT(-1) -0.208054 0.115914 -1.794903 0.0843

D(LNDEPOSIT(-1)) 0.058167 0.185480 0.313603 0.7563

C 0.291976 0.194189 1.503566 0.1447

R-squared 0.113194 Mean dependent var -0.041516


S.E. of regression 0.290045 Akaike info criterion 0.460139

Sum squared resid 2.187285 Schwarz criterion 0.601583

Log likelihood -3.672016 F-statistic 1.659352


ADF Test Statistic -4.585405 1% Critical Value* -3.6852





Dependent Variable: D(LNDEPOSIT,2)


Date: 10/11/12 Time: 17:32




D(LNDEPOSIT(-1)) -1.294712 0.282355 -4.585405 0.0001

D(LNDEPOSIT(-1),2) 0.210105 0.191258 1.098545 0.2824

C -0.054881 0.058971 -0.930643 0.3609

R-squared 0.556526 Mean dependent var 1.98E-17






GDP

Level First Difference






Dependent Variable: D(LNGDP)


Date: 10/10/12 Time: 17:48




LNGDP(-1) -0.004338 0.015761 -0.275231 0.7853

D(LNGDP(-1)) 0.023755 0.196507 0.120886 0.9047

C 0.139565 0.193731 0.720404 0.4777


Adjusted R-squared -0.073217 S.D. dependent var 0.065203










Dependent Variable: D(LNGDP,2)


Date: 10/10/12 Time: 17:52




D(LNGDP(-1)) -1.172826 0.292242 -4.013205 0.0005

D(LNGDP(-1),2) 0.210406 0.231670 0.908215 0.3724

C 0.105173 0.029529 3.561663 0.0015







Inflation






Dependent Variable: D(LNCPIINFLASI)


Date: 10/11/12 Time: 17:46


Included observations: 24

Excluded observations: 5 after adjusting endpoints


LNCPIINFLASI(-1) -0.430333 0.201890 -2.131528 0.0450

D(LNCPIINFLASI(-1)) -0.340092 0.201027 -1.691774 0.1055

C 0.393308 0.247736 1.587610 0.1273











Dependent Variable: D(LNCPIINFLASI,2)


Date: 10/11/12 Time: 17:47





D(LNCPIINFLASI(-1)) -1.311281 0.441130 -2.972549 0.0078

D(LNCPIINFLASI(-

1),2)

-0.177287 0.278820 -0.635850 0.5325

C -0.084481 0.113430 -0.744783 0.4655






16 | P a g e




Money Supply M2






Dependent Variable: D(LNM2)


Date: 10/11/12 Time: 17:12




LNM2(-1) -0.022248 0.033575 -0.662644 0.5134

D(LNM2(-1)) -0.010786 0.193956 -0.055611 0.9561

C 0.688211 0.879425 0.782570 0.4409


Adjusted R-squared -0.058819 S.D. dependent var 0.160912










Dependent Variable: D(LNM2,2)


Date: 10/11/12 Time: 17:14




D(LNM2(-1)) -1.384520 0.265280 -5.219095 0.0000

D(LNM2(-1),2) 0.359414 0.185820 1.934200 0.0645

C 0.144745 0.041373 3.498574 0.0018


Adjusted R-

squared

0.539736 S.D. dependent var 0.233693





Data 5: Unit Roof Test – Trend and intercept

Interest






Dependent Variable: D(LNDEPOSIT)


Date: 10/21/12 Time: 14:29




LNDEPOSIT(-1) -0.634077 0.196111 -3.233263 0.0034

D(LNDEPOSIT(-1)) 0.237344 0.189445 1.252838 0.2219

C 1.420157 0.472038 3.008564 0.0059

@TREND(1980) -0.027534 0.010739 -2.563823 0.0167












Dependent Variable: D(LNDEPOSIT,2)


Date: 10/21/12 Time: 14:26




D(LNDEPOSIT(-1)) -1.287435 0.289359 -4.449267 0.0002

D(LNDEPOSIT(-1),2) 0.205383 0.200845 1.022596 0.3167

C -0.078730 0.134402 -0.585785 0.5635

@TREND(1980) 0.001572 0.007334 0.214279 0.8321







GDP






Dependent Variable: D(LNGDP)


Date: 10/21/12 Time: 14:03




LNGDP(-1) -0.366898 0.154607 -2.373107 0.0256

D(LNGDP(-1)) 0.218741 0.199294 1.097579 0.2828






Dependent Variable: D(LNGDP,2)


Date: 10/21/12 Time: 14:17




D(LNGDP(-1)) -1.174122 0.299507 -3.920186 0.0006

D(LNGDP(-1),2) 0.212273 0.239700 0.885579 0.3846


17 | P a g e

C 4.001250 1.649154 2.426244 0.0228

@TREND(1980) 0.034662 0.014716 2.355490 0.0267







C 0.104012 0.038843 2.677757 0.0132

@TREND(1980) 7.79E-05 0.001644 0.047362 0.9626







Inflation






Dependent Variable: D(LNINFLATION)


Date: 10/21/12 Time: 14:36





LNINFLATION(-1) -0.723571 0.278208 -2.600832 0.0171

D(LNINFLATION(-1)) -0.195051 0.218435 -0.892947 0.3825

C 1.155703 0.566334 2.040674 0.0547

@TREND(1980) -0.024102 0.016204 -1.487445 0.1525












Dependent Variable: D(LNINFLATION,2)


Date: 10/21/12 Time: 14:38





D(LNINFLATION(-1)) -1.328117 0.458607 -2.895983 0.0096

D(LNINFLATION(-

1),2)

-0.166548 0.289935 -0.574433 0.5728

C -0.152930 0.323185 -0.473197 0.6418

@TREND(1980) 0.003591 0.015818 0.227025 0.8230







Money Supply M2






Dependent Variable: D(LNM2)


Date: 10/21/12 Time: 14:16




LNM2(-1) -0.565813 0.184048 -3.074261 0.0050

D(LNM2(-1)) 0.265856 0.193287 1.375448 0.1812

C 13.92651 4.491364 3.100730 0.0047

@TREND(1980) 0.060377 0.020181 2.991748 0.0062












Dependent Variable: D(LNM2,2)


Date: 10/21/12 Time: 14:21




D(LNM2(-1)) -1.388561 0.270879 -5.126128 0.0000

D(LNM2(-1),2) 0.361793 0.189644 1.907753 0.0685

C 0.160821 0.076844 2.092819 0.0471

@TREND(1980) -0.000948 0.003788 -0.250255 0.8045







Documents

A Time Series Analysis on Correlation between Inflation Rate, Monetary Policy and Interest rate with Gross Domestic