This document summarizes a research study that analyzed the effect of interest rates on stock prices on the Ghana Stock Exchange from 2009 to 2013. The study found a negative relationship between interest rates and stock prices over this period. Specifically, a 1% increase in interest rates was found to decrease stock prices by approximately 1.48%, and vice versa. This negative relationship can be explained by investors preferring to invest in fixed income assets like treasury bills when interest rates rise. The document provides an overview of previous studies that have examined the relationship between interest rates and stock market returns, finding mixed results, and discusses the rationale for expecting a negative correlation.

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Analysis of the Effect of Interest Rate on Stock Prices
A Case Study of Ghana Stock Exchange
Dr.Emmanuel Teitey,Ph.D
Kings University College- School of Business,Ghana
teitey2000@gmail.com/eminet1972@hotmail.com
Tel.+233-0548704485/0277430485
2018

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Abstract
One importance of the Ghana stock exchange is that it assists investors or shareholders in
boosting impressive financial results. For instance, five-year performance from 2009 to 2013
showed steady growth in profit and returns on investments of Banks listed at the Ghana stock
exchange. Steady growth was possible due to the negative relationship that existed between
interest rates and stock prices within the period (2009-2013). This research used quantitative
methodology and was performed using regression analyses to assess the relationship between
interest rates and stock prices on the Ghana stock exchange. The ordinary least square regression
was estimated with stock price as the dependent variable and interest rate as the independent
variable. The variables were transformed into their natural logarithm forms. The result obtained
was: LNS = 8.6835 – 1.4756LNI + e, which mean a negative relationship exists between interest
rates and stock prices. A unit or percentage increase in interest rates would lead to a decrease in
stock prices by approximately 1.48%, while a unit or percentage decrease in interest rates would
lead to an appreciation in stock prices by 1.48 %. This relationship could be explained by the
influence of when interest rates rise, people prefer to invest in the treasury market and other
fixed income markets, thereby moving funds away from the stock market; and the fall in demand
for stocks will push stock prices downward. The opposite is true for a fall in interest rates.
Key words: stock prices, interest rate, stock market, fluctuation, regression

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Overview
Most studies suggest that macroeconomic environment has an important effect on stock
market returns (Ahma, Ihsan, & Sahia, 2007; Fifield, Power, & Sinclair, 2002; Kuwornu, 2012).
Maintaining macroeconomic stability has been one of the main challenges for developing
countries. The relationship between stock market returns and interest rates has been examined by
researchers as it plays an important role in influencing a country`s economic development
(Fifield, et al., 2002). Interest rates are determined by the monetary policy of a country according
to its economic situation. Changes in interest rates influences the value of a company`s stock and
shares and, thus, the stock returns. Interest rates are one of the important macroeconomic
variables, which are directly related to economic growth. Generally, an interest rate is considered
as the cost of capital, which means the price paid for the use of money for a period of time. From
the point of view of a borrower, the interest rate is the cost of borrowing money or “borrowing
rate” (Bintou, 2011).
The rationale for the relationship between interest rates and stock market returns is that
stock prices and interest rates are said to be negatively correlated (Camra, 2011). Higher interest
rates, resulting from contraction monetary policy, usually negatively affects stock market returns
because higher interest rates reduce the value of equity and makes fixed income securities more
attractive as an alternative to holding stocks. This will reduce the tendency of investors to borrow
and invest in stocks and raise the cost of doing business, hence, affecting the profit margin. On
the contrary, lower interest rates result from an expansionary monetary policy boost stock market
(Fama, 1981).
Anokye and Tweneboah (2008) found “the relationship between stock prices and
interest rates to be negative and statistically significant on the Ghana stock market” (p.13). This
research used single economic variable (borrowing rate), which has not been adequately
researched in Ghana, while Anokye and Tweneboah (2008) applied quadruple economic variable
(inflation, rube oil prices, exchange rate, and interest rate; and each variable was analysed
individually). Also, this research is apposite due to institutional, developmental, and
technological changes over time so any research reflecting current issues is appropriate.
Literature Review
Many research studies investigated how the performance of the stock market is affected by
certain macro-economic variables ( Anokye & Tweneboah, 2008; Aydemir & Demirehan, 2009;
Yartey and Adjasi, 2007). Many were interested in variables that may affect the stock market due
to the importance of stock market itself as it assesses the economic condition of that particular
country. This is particularly important to an emerging stock market, becasue as it affects how the
country implements its strategies in order to accelerate economic growth (Anokye &
Tweneboah,2008; Aydemir & Demirehan,2009; Yartey and Adjasi, 2007).
Interest rates are one of the most important macroeconomic variables that can be used to
explain economic growth and how efficient stock markets are (Harlina, Intan, Nasruddin, & Emi,
2011). Interest rates often are known to be the cost of capital; the price paid for the use of money
for a period (Harlina et al, 2011). The relationship between interest rates and stock return is said to
be a negative relation. Interest rate levels, as well as their volatilities, affect the return distribution
of the financial sector based on empirical evidence (Harlina et al, 2011). Harlina et al. (2011) also
stated that there are other researchers who suggest that there is no relationship between the stock
return and interest rate in the long term. Some studies concluded that the relationship was positive,

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while others disagreed (Anokye & Tweneboah, 2008; Aydemir & Demirehan, 2009; Yartey &
Adjasi, 2007).
According to the Zenith Bank Ghana Ltd. (2015a), the Bank of Ghana in January 2015
issued a government of Ghana calendar for securities for the year 2015 from January 1st
to June
30th,
showing the amount and types of securities the government intended to borrow from the
public. The Government intended to borrow within this period an amount of GH¢25,420.00m. The
Central Bank envisaged to issue at least GH¢880.00 million of Treasury Bills and Notes weekly at
all times to support government liquidity requirements, which includes the redemption/rollover of
maturing securities for the week with a policy rate at 19%, and interbank rate at 23.70%, as of
December, 2014. With inflation rates as of December 2014 the same year standing at 17% and the
government`s insatiable demand for public funds in 2015, (99.81% increase in the amount of
securities to be issued in 2015), one can conclude that interest rates on short term securities (91-
Day Treasury Bills - 2-Year Notes) would soar. The expectation is that interest rates on a 91-Day
Treasury Bill at the end of June would raise, reaching an average of 28%. This translates,
therefore, into higher interest rates to be offered to customers of banks who ask for credit; hence,
low prices of stocks and shares at the Ghana stock exchange (Zenith Bank Ghana, Ltd., 2015a).
Interest rates have a strong relationship with stock volatility as can be seen by how it
changes on the sector and composite return and volatility as in Istanbul Stock Exchange, where
these variables are considered the possible proxy for the rate of daily information arrivals. Index
returns decrease in response to changes in interest rates; the only service sector return reacts
negatively and significantly to the exchange rate changes. Interest and exchange rate significantly
affect indices in ISE. In particular, the market volatility is more sensitive to changes in interest
rates (Harlina et al, 2011).
Furthermore, the negative relationship between stock market and interest rates can be
explained by the Japan stock market. Kurihara and Nezu (2006) found that the insignificant
relationship between stock prices and interest rate is due to the fact that Japan has applied
unprecedented monetary easing to reduce interest. Therefore, interest rates will reduce the impact
on stock price. On the other hand, Ologunde, Elumilade, and Saolu (2006) stated “there is a
positive impact on stock market.”. This theory can be proven by stock market capitalization. When
the interest rate is high, the stock market capitalization will increase. Thus, economic growth and
development is retarded. Government controls the interest rate to help the growth of the stock
market. Anokye and Tweneboah (2008) also agreed that there is a negative relationship between
real long term interest rate and stock market movement in Ghana by employing vector error
correction model. This is because in the late 90`s, there was high Treasury Bill rate and investors
would invest in treasury bills because it is more profitable than stock market. This has decelerated
the performance of the Ghana stock market.
Interest rate, exchange rate, and inflation have some influence on the performance of stock
market. Blanchard (1981) described the relationship of output, stock market and interest rates.
Blanchard states that “higher stock money lowers interest rate which means lower cost of capital
and in turn causes better stock market value” (p. 133). Blanchard observed that a change in the
policy would cause a change in the stock market because of real interest rate and anticipated
profits. The announcement of a policy leads to change in profits and discount rates which in turn
affect the performance of stock market. Blanchard then concluded that the flexible policies affect
the nominal money which leads to change in the stock market (Blanchard, 1981).This is possible
and pertained to current issue because any favorable information at the market, the market respond
positively to it.

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A number of studies were conducted to find the relationship between macroeconomic
variable and stock prices but a few studies focused on sector-wise relationship (Kaul, 1987; Wong,
Khan, & Du, 2005; Zafar, Urooj, & Durrani, 2008). One study of Wong et al. (2005) investigated
the effects of exchange rate, interest rate, and their volatilities on stock prices of the banking
industry of Pakistan. Co-integrated results suggest the existence of significant negative long-term
relationship between exchange rate and short-term interest rate with stock prices (Wong et al.,
2005). However, positive and significant relationships exist between volatilities of exchange rate
and interest rate with stock prices. Causality analysis confirms bidirectional causality between
exchange and stock prices. Whereas unidirectional causality tested between the short-term interest
rate and stock prices, sensitivity analysis confirms that the results are robust. These results suggest
that investors should invest in fixed income securities market when exchange and interest rates are
highly volatile. This situation normally happens with the market speculators who are ready to do
anything when price volatilities occur. The results also support the view that exchange rate and
interest rate can be used as indicators for investment decision making in the fixed income securities
market (Wong et al., 2005).
Interest rates will affect a stable stock market as an important factor in a country`s strategy
to facilitate the flow of investment in the stock market in order to accelerate economic growth.
Zafar et al. (2008) investigated the impacts of interest rate volatility on stock market returns and
they concluded that interest rate has a significant negative relationship with the stock market. An
increase in interest rates generally results in people tending to keep their savings in the banks so
that they get high interest rather than investing in the risky stock market. Besides, higher interest
rates also reduce the profitability of firms and hence a decline in stock prices. As interest rates
decrease, investors switch their money from banks and invest in the stock market. Consequently,
stock market performance increases as a result of a decrease in interest rate and this in turn reduces
the probability of financial distress. Thus, interest rates have a significant negative relationship
with stock market performance (Zafar et al., 2008).
Kaul (1987) stated there is an inverse relationship among stock returns, expected inflation
and positive relationship between stock returns and real activity. Kaul tested the hypothesis of the
negative relationship by selecting data from 1926 to 1940. Kaul (1987) was considering changes in
the monetary policy regime. Most of the time, these periods was normally experienced high
inflation and high interest rate regimes and the behaviour of economic variables could be clearly
seen or identified during this era. Kaul observed that this inverse relationship can be explained by
understanding the equilibrium process in the monetary sector depending on money demand and
supply influence. Empirical tests showed the sensitivity of bank stock returns of the market against
interest rates and exchange rate risks, they covered stocks of 48 US banks for the period 1975 to
1987, and the results proved that exchange rates had a significant negative relation to US banks
stock returns (Kaul, 1987).
Research Problem
The problem that this study explored was interest rate fluctuation in Ghana and its
influence on stock prices of the Ghana stock exchange. This represents a research problem
because interest rates are regulated by the activities of the government and the central bank.
Government serves as a borrower of funds from the general public through issuing of short-term
instruments (Treasury Bills). When Treasury Bills are issued, interest rates rise and vice versa.
This study, therefore, sought to discover the reactions of stock prices at the Ghana stock
exchange when interest rates rise, thus, compelling the government to clean up the excess fund in
the system by purchasing back short-term instruments through the Central Bank. This study was

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appropriate because there are lots of conflicting results from the various researchers (Beenstock
& Chan, 1988; Chen, Roll, & Ross. 1986; Fifield et al., 2002). Some say there is negative
relationship, others say they see a positive relationship, whiles another group observes no
relationship at all (; Beenstock & Chan, 1988; Chen et al., 1986; Fifield et al., 2002 ). Also, it has
been long since these studoes were conducted, hence, a new research is appropriate for the
reflection of current issues.
This study also contributes to the existing academic body of knowledge and derivative
literature as it brings new evidence from the analysis of interest rate and its effect on the stock
prices of the Ghanaian stock market. In 2006, for example, foreign equity accounted for 75.3%
of the equity finance recording in Ghana compared to 29.9% in 2001 according to a Ghana
Investment Promotion Centre`s quarterly report (GIPC, 2007, December).
According to the Zenith Bank Ghana Ltd. (2015a) the Bank of Ghana in January 2015
issued a government of Ghana calendar for securities for the year 2015 from January 1st
to June
30th
showing the amount and types of securities the government intended to borrow from the
public. The Government intended to borrow within this period an amount of GH¢25,420.00m.
The Central Bank envisaged to issue at least GH¢880.00 million of Treasury Bills and Notes
weekly at all times to support government liquidity requirements, which includes the
redemption/rollover of maturing securities for the week with a policy rate at 19%, and interbank
rate at 23.70%, as of December, 2014. With inflation rates as of December 2014 the same year
standing at 17% and the government`s insatiable demand for public funds in 2015, (99.81%
increase in the amount of securities to be issued in 2015), one can conclude that interest rates on
short term securities (91-Day Treasury Bills - 2-Year Notes) would soar. The expectation is that
interest rates on a 91-Day Treasury Bill at the end of June would raise, reaching an average of
28%. This translates, therefore, into higher interest rates to be offered to customers of banks
who ask for credit; hence, low prices of stocks and shares at the Ghana stock exchange (Zenith
Bank Ghana, Ltd., 2015a).
Research Design
The major research questions that guided this analysis study were: (R1) did changes in
interest rate relates to stock prices of the Ghana stock exchange. (R2)Is there a relationship
between this is a quantitative research using a positivistic approach and analytical survey. The
sampling technique was stratified, and purposive sampling approach employed.
Hypotheses were formulated based on the research question:
(R1)Ho: Interest rates did not relate to stock prices.
H1: Interest rates relates to stock prices.
(R2)Ho: There is no relationship between interest and stock prices.
H1: There is a relationship between interest rate and stock prices.
These hypotheses were tested to assess the significance of the regression analysis. The
study failed to accept null hypotheses because the probability value was greater than 1%
and 5% critical value at a significant level that means relationship exist between interest
rate and stock prices.

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Population and Sampling Strategy
The sampling technique was stratified, and purposive sampling approach was employed.
The population size for the research was five years (2009-2013) of interest rate computation of
the Bank of Ghana and the World Bank, as well as five years (2009-2013) of stock prices
computation of the Ghana Stock Exchange Market report and stock literatures. Relationship
between interest rates and stock prices was analysed using the following method:
First, the study used ordinary least square (OLS) regressions by analyzing explanatory
variables with each response variable as the stock prices. Second, the study used unit root test,
which was used to analyze all explanatory variables and their response variables that were
applicable in the study, since these variables are time series in nature. Therefore, the study
performed DF Unit Root Tests to decide whether those time series were stationary or non-
stationary.
Third, autocorrelation is one of the most important assumptions made in regression
analysis. If the successive residuals are correlated there is a condition of autocorrelation for time
series data. Durbin-Watson statistic (d) is applied to check whether there is an autocorrelation
problem for the sample data set. Fourth, this study also performed the test for multicollinearity
to examine whether the explanatory variables are correlated which ensures the validity of
multiple regression models in predicting stock prices (Patterson, 2000). And finally, the study
performed a Causality test to determine whether changes in the short-term and long term interest
rates (average interest rates) cause changes in stock prices (Patterson, 2000).
Research Data
The researcher used secondary data because with quantitative studies secondary data like
time series data gives accurate measurement while with primary data like ,interviews and
questionnaires does not give precise measurement. Reading of documents in the form of
literature review is also a research instrument so there is an instrument.
The research employed secondary sources as the main data collection method. These
secondary data sources were analyzed and literature on interest rate and stock prices were used.
Data was collected from secondary sources, such as the Bank of Ghana, official database of the
World Bank, the Market Report of the Ghana Stock Exchange, and other literature. These data
sources provided pertinent information on stock prices and were used to analyze the interest rate
and stock prices of the Ghana stock exchange (Coleman & Agyire-Tettey,2008; Dadadu,2010;
Egu,,2010; Kuwornu,2012; Owusu-Nantwi, 2011 ).
Data Collection Procedures
This research focused mainly on secondary types of data. All secondary data on interest
rate was collected from the Bank of Ghana and official database of the World Bank while data
on stock prices were also collected from the market report of the Ghana stock exchange and
other stock literature reviews.
The data collection was mainly from the Ghana stock exchange and the Bank of Ghana.
The amount of secondary data at the disposal of this research is quite considerable. This has been
obtained from internal and external sources. The internal sources of data are obtainable from the
Bank of Ghana and the Ghana stock exchange while the external source was the official database
of the World Bank.
Data Aanalysis
The research used quantitative data analysis methods. Trend analysis was applied based
on the period 2009-2013. This period was chosen because interest rate fluctuations within the
last decades cannot be comprehended. The study performed five years performance evaluation

9. 9
analysis based on the data gathered or the time series data. The research relied on four broad
indicators of performance which include: (a) Increase in interest rate, (b) Decrease in interest
rate, (c) Increase in stock prices; (d) Decrease in stock prices since the two variables have an
inverse relationship, and the information was analysed using SPSS and Stata.
Main Findings of the Research
The chapter presented solutions to the research questions and developed the theoretical
foundation through literature search, and methodology of the research used in this study. This
section presents findings and results of the research including hypotheses and detailed statistical
analysis.
Unit Root Tests
The second research question concentrated on the correlation of interest rate and stock
prices were analysed using Dicky-fuller Unit Root test, the hypothesis prove statistically positive
with P-value > 05 level of significant which indicated we accept null hypothesis and we do not
reject it. Thus, the null hypothesis that states interest rates have a unit root, and concludes that
the interest rate variable is stationary at level 1 is rejected. Similarly, stock prices also proved to
be stationary at level 1. A p-value of 0.9394 led to the rejection of null hypothesis that stock
price has a unit root. In the research conducted by Yartey and Adjasi (2007), the stock market
prices in Ghana were reported to be affected by macroeconomic variables of the economy with
respect to their intensity in different markets. An investor, therefore, needs to be aware of the
behaviour of the stock market with the results which are generated after the fluctuation of these
key variables (Yartey & Adjasi, 2007).
Least Squares Regression
The first research question concentrated on the co-efficient correlation or relationship
between the interest rate and stock prices were analysis using ordinary least square regression,
the hypothesis shown negative correlation or relationship that is -1.48% at 5% level of
significant means a unit or percentage increase in interest rate would lead to a fall in stock prices
by approximate while a unit or percentage decrease in interest rate would lead to an appreciation
in stock prices by-1.48%. The results confirm the literature reviewed and research conducted by
Burshop,Chambers and Cheffins (2011). In their research, they included US, UK, and Japan
stock markets operation, the relationship between macroeconomic variables and the fluctuation
of stock prices. The finding of these studies shows that with the minor variation, macroeconomic
variables have significant impact on the stock prices.
Test of Autocorrelation
The second research question concentrated on the interest rate and stock prices
relationship were analysed using the autocorrelation statistical test using the Durbin Watson test.
The hypothesis proves statistical significantly negative with the DW value of 0.83 > 05 %
Significant level which means that we fail to accept null hypothesis and thus reject it and
conclude that there is absence of autocorrelation in the data. The statistical test used is the
Durbin Watson test with the hypothesis: Ho: p = 0. There is no positive or negative
autocorrelation. Ha: p ≠ 0: there is no positive or negative autocorrelation. The findings from this
research have provided evidence for the theoretical literature reviewed. This was possible
because in the research by French, Schwert, and Stambaugh (1987) found that there was a
negative relationship between stock returns and both long-term and short-term interest rate.

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Test of Causality
. The first research questions concentrated on the co-efficient correlation or relationship between
interest rate and stock prices of the Ghana stock exchange were analysed using the causality test.
The hypothesis proves statistically significant with the causality test value of 0.08 > 05 %
significant level which means that we fail to accept null hypothesis and thus reject it and
conclude interest rate is the compelling factor that causes fluctuation in stock prices of the
Ghana stock exchange. These findings support the results of Nishat and Shaheen (2004) who
found a causal relation between interest rates and stock exchange prices.
Conclusions and Recommendations
Several studies were conducted to find the relationship between macroeconomic variables
and stock prices (Anokye & Tweneboah, 2008; Aydemir & Demirehan, 2009; Yartey & Adjasi,
2007) This study investigated the effects of interest rates on stock prices of the Ghana stock
exchange. This research generally fit the aims and objectives of this study. Discussion of the
results, conclusions, and practical recommendations and recommendations for the future are,
however, made to further improve upon the findings of this research.
Discussion of Results
The findings and results of the study found that based on the research questions the hypothesis
established statistical significant with the causality test value of 0.08 > 05 % significant level
which means that we fail to accept null hypothesis and thus reject it and conclude interest
rate is the compelling factor that causes fluctuation in stock prices of the Ghana stock
exchange .The results of Granger causality were reported in the analysis. The result shows the
existence of bidirectional causality among interest rate and stock prices. At 5% level of
significant the null hypothesis can be rejected, that interest rate does not Granger cause stock
prices and concludes that interest rate Granger causes stock prices. However, the null hypothesis
fails to be rejected, that Stock prices do not Granger cause interest rate. Thus, there is a
unidirectional causality moving from interest rates to stock prices. In other words, interest rates
are one compelling factor in the stock price variables. These findings support the results of
Nishat and Shaheen (2004) who found causal relationships between interest rate sand stock
exchange prices.
Conclusions and Practical Recommendations
Therefore, investors in the Ghana stock exchange need to consider interest rates before
taking investment decisions. This is another area of concern, which the Ghana stock exchange
needs to critically observe, because with data like that of 2011, the naïve investor will find it
difficult to study the market activities. Even the existing investors and potential investors could
hardly study a market activity similar to these, and this will even lead to inefficient market
Hypothesis, hence, limited accessibility to information available in the market. This confirms the
research founding’s by Fama (1981) the efficient market hypothesis provided that at any given
period and in a liquid market, securities prices fully reflect all available information..
References
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13. 13
Appendices
Appendix A
Regression Analysis Results
Table A1
Unit Root Tests
Null Hypothesis: LNI has a unit root
Exogenous: None
Lag Length: 5 (Automatic - based on SIC, maxlag=9)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic 0.057113 0.6933
Test critical values: 1% level -2.644302
5% level -1.952473
10% level -1.610211
Null Hypothesis: LNS has a unit root
Exogenous: None
Lag Length: 1 (Automatic - based on SIC, maxlag=9)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic 1.214712 0.9394
Test critical values: 1% level -2.634731
5% level -1.951000
10% level -1.610907

14. 14
Table A2
Least Squares Regression
Dependent Variable: LNS
Method: Least Squares
Date: 05/02/15 Time: 14:46
Sample: 160
Included observations: 60
Variable CoefficientStd. Error t-Statistic Prob.
LNI -1.475644 0.751342 -1.964011 0.0577
C 8.683520 0.787068 11.03274 0.0000
R-squared 0.101891 Mean dependent var 7.140471
Adjusted R-squared 0.075476 S.D. dependent var 0.293469
S.E. of regression 0.282177 Akaike info criterion 0.361387
Sum squared resid 2.707207 Schwarz criterion 0.449360
Log likelihood -4.504963 Hannan-Quinn criter. 0.392092
F-statistic 3.857339 Durbin-Watson stat 0.298697
Prob(F-statistic) 0.057747

15. 15
Table A3
Test of Autocorrelation
Breusch-Godfrey Serial Correlation LM Test:
F-statistic 41.36077 Prob. F(6,28) 0.0000
Obs*R-squared 32.35000 Prob. Chi-Square(6) 0.0000
Test Equation:
Dependent Variable: RESID
Method: Least Squares
Date: 05/02/15 Time: 14:50
Sample: 160
Included observations:60
Presample missing value lagged residuals set to zero.
Variable CoefficientStd. Error t-Statistic Prob.
LNI 1.794463 0.330729 5.425784 0.0000
C -1.842002 0.343338 -5.364976 0.0000
RESID(-1) 0.730477 0.136083 5.367862 0.0000
RESID(-2) 0.379921 0.149698 2.537911 0.0170
RESID(-3) -0.070814 0.164167 -0.431351 0.6695
RESID(-4) -0.220198 0.152394 -1.444923 0.1596
RESID(-5) 0.202434 0.152807 1.324767 0.1960
RESID(-6) 0.235973 0.145515 1.621641 0.1161
R-squared 0.898611 Mean dependent var 6.26E-16
Adjusted R-squared 0.873264 S.D. dependent var 0.278116
S.E. of regression 0.099009 Akaike info criterion -1.594072
Sum squared resid 0.274481 Schwarz criterion -1.242179
Log likelihood 36.69330 Hannan-Quinn criter. -1.471252
F-statistic 35.45209 Durbin-Watson stat 0.831920
Prob(F-statistic) 0.000000

16. 16
Table A 4
Test of Causality
Pairwise Granger Causality Tests
Date: 05/02/15 Time: 14:51
Sample: 160
Lags: 2
Null Hypothesis: Obs F-StatisticProb.
LNI does not Granger Cause LNS 34 2.74740 0.0808
LNS does not Granger Cause LNI 2.31345 0.1169