monetary policy and stock market movements in turkey

7/27/2019 Monetary Policy and Stock Market Movements in Turkey

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School of Economics and Finance

Queen Mary University of London

MONETARY POLICY AND STOCK MARKET MOVEMENTS IN TURKEY

Izzet Onur SERAKIBI

Email Address

[email protected]

M.Sc. in Business Finance

August,2013


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I.TABLE OF CONTENTS:

I.TABLE OF CONTENTS:...................................................................................................2

II.ABSTRACT:...................................................................................................................4

1-INTRODUCTION:...........................................................................................................4

2.A BRIEF REVIEW OF THE LITERATURE ON THE MONETARY POLICY AND ASSET PRCERELATIONS:.................................................................................................................... 6

2.1.The Taylor Rule:........................................................................................................72.1.1. Specification of the Taylor Rule:...........................................................................9

2.1.1.1. Estimation Data:................................................................................................9

2.1.1.2. A Brief Information About Turkish Stock Market:...............................................9

2.1.1.2.1. The Credit Outlook of Turkey as an Investment Criteria:..............................10

2.1.1.3.The Standart Taylor Rule:.................................................................................10

2.1.1.4.The Augmented Taylor Rule:............................................................................112.1.1.5. Forward Looking Models and Generalized Method of Moments: .....................11

2.1.2. Estimation of the Taylor Rule:...........................................................................12

2.1.2.1. Graphical Inspection of the Data:....................................................................12

2.1.2.2. Standart Taylor Rule with Ordinary Least-Squares Method :..........................14

2.1.2.3. The Wald Test:.................................................................................................15

2.1.2.4.Visual Impression Regarding the Model:...........................................................162.1.2.5.Chow Breakpoint Test:......................................................................................17

2.1.2.6. Estimating The Augmented Taylor Rule: ........................................................17

2.1.2.6.1.Ordinary Least-Squares Analysis (ATR):........................................................18

2.1.2.6.2. Diagnostic- Normality Test:..........................................................................19

2.1.2.6.3. Diagnostic- Heteroskedasticity Test:............................................................19

2.1.2.6.4. Diagnostic- Breusch-Godfrey Serial Correlation LM Test:.............................192.1.2.6.5. Ordinary Least Squares Method (Newey-West Option):................................20

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2.1.2.6.6. Generalized Method of Moments(GMM) Estimator:......................................22

3.CONCLUSION:............................................................................................................23REFERENCES................................................................................................................. 24

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II.ABSTRACT:

In this dissertation, we investigate the hypothesis that monetary policy responds to

movements in asset prices.In the study the arguments in favor and against the above hypothesis will

be studied, the empirical framework will be discussed and the hypothesis will be tested. In the

investigation, we adopt the Taylor rule as the empirical framework and used its standard and

augmented versions in order to reach a conclusion.In this study, we will especially explore that

whether the stock market movements play a crucial role in shaping monetary policy either directly

or indirectly in Turkey between the years 1997 and 2012.

1-INTRODUCTION:

Turkish economy showed an outstanding performance between the years of 1997 and

2012.During the period, the inflation rate dropped to %6.16 from %85 and parallel to the inflation

rate interest rate dropped almost %60 while GDP rose almost %4 annually in average. Additionally

BIST100, the stock market value of Turkey rose almost 60% in 2012 and reached the 80.000 index

level while it was only at 1.613 index level at 1997.

The objective of this investigation is to test the hypothesis that monetary policy responds to

movements in asset prices. In this study, we will try to prove that there is a significant correlation

between monetary policy and asset pricing.Policy rules of central bank of Turkey and reflections of

those decisions in the stock market between the period of 1997 and 2012 will be the main

investigation subject of this study.

According to Bernanke and Mihov (1998) the process by which the central banks control the

money supply in order to keep the interest rate at certain levels for promoting economic growth and

price stability is called monetary policy.The need to the central banks in providing a stable

economic outlook has increased during the last years. So as a policy maker, central banks should

struggle with inflation as well as they should prevent the markets from the financial crisis.

Bernanke (2000) also claims that inflation is no longer a great issue to concern about since

the worlds leading central banks have been very successful at keeping it under control over the

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past twenty years. Nowadays an apparent increase in financial instability and increased volatility of

asset prices seem to be the next battles facing central banks.

According to Mishkin (2012) mismanagement of financial liberalization and asset-price

booms and busts can trigger financial crises which usually results in failures of major financial

institutions and increased uncertainty in the financial markets.When investor psychology affects

the assets prices such as equity shares and real estate above their fundamental economic values, the

rise of asset prices called as an asset-price bubble. Those bubbles in asset prices are often driven by

credit booms which are usually supported by the policies of the central banks.

Allen and Gale (2000) argue that the recent financial crises which was caused by the

bubble of asset prices is resulted with widespread defaults of some leading financial institutions.

The money borrowed from banks for asset investment is always attractive for investors who plan to

default on the loan rather than making safe but small amounts of profit in their investments. At the

times of financial fragility, the risk appetite of the investors in both the real and financial sectors

investments can lead the asset prices to very high levels and cause crisis due to the insufficient

positive credit expansion.

There have been two major asset bubble crisis in 1929 and 1980 at the last century.Both of

them caused protracted recessions and deflation.According to Bordo and Jeanne (2002)The policy

makers have a perennial interest in the relation of monetary policy and asset price movements since

it is essential to decide whether trying to prevent the results of an asset market collapse before it

turns to a financial crisis or whether it was more effective to react the asset prices after financial

markets completely went down.

Bean (2004) claims that in the aftermath of the recent crisis caused by asset price bubbles inJapan and U.S. the most popular debate between central bankers and academic circles was the role

of the asset prices in the setting of monetary policy. Views of Gilchrist and Leahy (2002) remind

the following period of increased volatility in asset prices in Japan and US.Then most of the

economists had called for central banks to respond to asset price volatility against to large swings in

growth rates.

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2.A BRIEF REVIEW OF THE LITERATURE ON THE MONETARYPOLICY AND ASSET PRCE RELATIONS:

The role of asset price movements in shaping monetary policy can be explained by two

opposite view in the literature. Some economist such as Bernanke and Gertler (2001) and Vickers

(1999) claim that there is no need to believe in asset price volatility as a key determinant for setting

monetary policy but on the other hand, Cecchetti, Genberg and Wadhwani (2002) believe volatility

in asset prices can help central banks when shaping monetary policy by providing more

information.

According to Bernanke and Gertler (2001) the appropriate position of asset prices in the

monetary policy has been witnessed to many debates. The question of whether central banks should

respond to volatility in asset prices or not can be answered by the inflation-targeting approach.

According to this view volatility in asset prices may affect the monetary policy if onlythe expected

inflation rate is affected negatively from those movements. For instance, a bubble in asset prices

can increas the aggregate demand by increasing consumers wealth and affect the inflation

negatively.Furthermore, once the effects of asset prices in the general price level have been

accounted for central banks should not response the changes in the asset prices anymore. This is acrucial point in monetary policy because this kind of attempts to influence asset prices can affect the

investors psychology and lead the markets unpredictable future.

According to Cecchetti et al. (2002), it is possible to improve macroeconomic performance

by reacting to asset price misalignments systematically. Just by setting policy rates with an eye

toward particularly in misalignments and generally in asset prices can help to smooth output and

inflation fluctuations. Distortions in investment and consumption created by asset price bubbles can

cause excessive increases followed by severe falls in both inflation and GDP. To raise interest

rates when asset prices rise above the expected levels and to lower them modestly when asset prices

fall below the reasonable levels will help central banks to offset the impact on inflation and output

gap of these bubbles. The important outcome of this kind of monetary policy is to show the markets

that central banks can take the necessary measurement in this way. The probability of bubbles in

equity prices might be reduced and a contribution to greater macroeconomic stability would also be

provided by this method.

Bernanke and Gertler (2001), claim whether the volatility in asset prices is the result of

bubbles or technological shocks, an aggressive inflation-targeting policy stabilizes output and

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inflation. In their opinion the study of Cecchetti et al. ignores the fact of shocks other than bubble

shocks and the probabilistic nature of the bubble. Their theory lies on the assumption of a bubble

shock which lasts precisely five periods. Also, the knowledge of the central banks about the

reasons and the bursting moment of the bubbles are both highly unlikely conditions. A panic-driven

financial instability that could affect the economy negatively can be reduced and macroeconomic

stability can be sustained by inflation targeting monetary policy. In the end, they conclude for

plausible parameter values the central banks should not respond to asset prices.

On the other hand, Cecchetti et al.(2002) claims that the underlying sources of shocks to the

economy determines the relationship between fluctuations in asset prices on the one hand, andoutput and inflation on the other. So they suggest that monetary authority should not interfere to all

changes in asset prices mechanically and in the same way. Since the private sector might possess

more information about equilibrium valuations of asset prices, it would be possible to react

anything from asset price fluctuations that can help to shape monetary policy.

Cecchetti et al. (2002) also claims that not all asset price changes, but the asset price

instability should be identified and responded in an inflation-targeting strategy. That means stock

market value should be included in the information sets in order to be processed by the central bank

just as well as the output gap. The problem of to differentiate the asset price movements and to

realize whether they are justified by underlying fundamentals or not is the main challenge of the

policymakers.

2.1.The Taylor Rule:

As a major tool of monetary policy central banks should change the interest rate in order toprovide macro economic stability first and then keep the employment in maximum levels.Taylor

rule which was proposed by world renowned monetary economist John B. Taylor and named after

him can help central banks with the question of how much would it be the optimum interest rate.

Taylor principle is a different aspect of taylor rule and stipulates that the nominal interest rate

should be raise more than the increase in the inflation rate.

According to Castro (2008) to set up the interest rate past or current values of inflation and

output gap is a commonly used method by central banks.In its very original form, the main

objectives of the Taylor rule are providing the price stability and keeping the economy moving

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towards maximum employment.In order to keep the general price level stable Taylor rule simply

recommends that when the inflation rate is exceeded the target level central banks should rise the

interest rate above the level of the stabilizing rate and when it is below the target level interest rate

should be decreased to the levels below the target.In order to accomplish the second objective of

the Taylor rule it is suggested that the interest rate should be determined above the stabilizing rate

when real GDP is above the target. If real GDP is below the potential real GDP Taylor,

recommends that the interest rate should be reduced below the stabilizing rate.

According to Taylor (1993) conducive monetary policy requires to put equal weights on the

impact of inflation and GDP since putting more weight on the inflation gap could be a sign of more

aggressive policy to target inflation by the central banks.

Godhart and Hofmann (2000) believe that the question of how asset price volatility should

be considered in principle for objectives of monetary policy is subject to a consensus among leading

economists.An inflation target which can also be defined as achieving price stability is the primary

objective of the central banks while inflation is a price index which consist of current goods and

services but excludes assets prices directly.

Frait and Komarek (2006) point out that asset price developments are usually taken into

account when refining monetary policy, even if central banks formally targets price stability. The

reason for this approach lies on the fact that asset price movements, especially physical assets, can

impact on CPI inflation by tempting the people to invest in those assets.Once people starts buying

those assets the production of the assets rises as well as the demand for the raw materials and this

cycle triggers the CPI inflation.

Figure 1.

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Furher and Tootell (2008) claim that there has been identification or observational

equivalence problem in Feds response to asset prices. As it can be seen from above Figure 1. when

equity price indexes fluctuated significantly fed responded those asset movements by increasing or

decreasing the federal interest rate.The correlation between the interest rate and asset prices that can

be observed in Figure 1. can not answer the question of whether it was a traditional monetary policy

or an independent concern for asset prices.Using ex post data and attempting to identify the effects

of asset prices on monetary policy may have a misleading impact.

2.1.1. Specification of the Taylor Rule:

Many scholars all around the world highly interested and used the Taylor rule in the past

years.Since it can provide an answer to how to set monetary policy by a simple method in this

study, the Taylor rule will be the econometric framework that is going to be used in the analysis.

2.1.1.1. Estimation Data:

As we mentioned above in this study, the Taylor rule will be used as the estimation

framework as well as some of the Turkish economic data ranging from 1997:1Q to 2012:4Q., will

be used as the estimation data.In the study we will apply RGDP, which is the Turkish real GDP,

CPI, which is the consumer price index of Turkey , interest is the interest rate, set by the Central

Bank of Turkey and BIST100 which is the stock market value of Turkey to our model to estimate

the Taylor rule.

The data which we need to carry out our study including GDP, CPI, Interest Rates and

BIST100 index of Turkey were extracted from International Monetary Fund International Financial

Statistics via UK Data Service international macrodata.

2.1.1.2. A Brief Information About Turkish Stock Market:

First time in Turkish history on January 3, 1986 stock trading started at the Caalolu

building of Istanbul Stock Exchange (IMKB) with a number of 80 listed companies.On

October,1992 IMKB was accepted to The World Federation of Exchanges as a full member. The

legal framework of Turkish capital markets, consist of Capital Markets Law (CML) and Turkish

Commercial Code.The more detailed regulations are manifested as Communiqus of Capital

Markets Board and Regulations of Stock Exchange. In order to harmonize the Turkish capital

markets regulation with the EU acquis, the Capital Markets Law No. 6362 was enacted by the

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Turkish law maker.With that amendment in Capital Markets Law Turkish government also aimed to

liberalize the activity of running organized markets and re-brand IMKB as Borsa Istanbul

(BIST).After the recent changes in the Capital Markets Law Borsa Istanbul is now subject to

private law as a joint-stock company.Borsa Istanbul (2013).

By the end of 2012, the number of the traded companies on BIST reached to 404 while it

was 258 at 1997. Under the name of Borsa Istanbul, two major national indices are existed.

SERPAM (2013).Those are BIST30 and BIST100.BIST30 is consisted of 30 large companies by

the value of outstanding shares traded in the stock market. Financial institutions and a couple of

leading holding companies are examples of firm types of the BIST30.BIST100 is the major index ofBorsa Istanbul.It is consisted of BIST30 and the following largest industrial companies by the value

of outstanding shares traded in the stock market. Usually BIST30 companies have higher beta value

than BIST100 companies and BIST30 index also considered as a more reliable indicator about the

general trend of the markets.

2.1.1.2.1. The Credit Outlook of Turkey as an Investment Criteria:

By the august of 2013, the long-term foreign-currency credit rating of Turkey wasconfirmed as BB+ by S&P, BBB- by Fitch and Baa3 by Moodys. Moodys and Fitch already

upgraded Turkeys foreign-currency sovereign credit rating to the investment grade.Another

foreign-currency sovereign credit rating upgrade is expected by S&P which will lift the general

credit outlook of Turkey to the investment grade in foreign-currency.

2.1.1.3.The Standart Taylor Rule:

The Taylor rule which formulates the linear relation between inflation ,GDP and the interest ratewas established by John B. Taylor in 1993.At this point of the study, the very first step of our

econometric analysis consists of estimating the standard Taylor rule (STR) as it is given below as

equation (1).

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According to Taylor (1993), in the above formula represents the log of the interest

rate(the federal funds rate), c represents the constant, represents the actual annual inflation rate,

represents the desired inflation rate, represents the log of GDP and is the potential GDP.

We will assume that in order to keep the analysis simple.

2.1.1.4.The Augmented Taylor Rule:

Among the monetary policy makers two opposite views emerged regarding how to set a well

refined monetary policy. According to the first view monetary authority should not respond to

movements in asset prices and wait for to see the progress in the economic data such as the inflation

rate. On the other hand, stock market movements could help to predict the future fluctuations in the

monetary markets and the augmented Taylor rule which is employed by monetary authorities would

be the best econometric framework for this purpose.

The second step of the econometric analysis will be estimating the augmented Taylor rule.In the 1main literature, asset price volatility suppose to bring more information to the central banks

and by doing so it could affect the decisions of the monetary authority.According to Castro (2008) a

financial conditions index containing data from stock market movements can be included in the

standard Taylor rule to have an augmented version of it. In order to test this possibility, we should

include in equation the variable, which measures the stock market value. If we start our estimation

for the equation by using only one lag of s and reached the conclusion of that s(-1) is statically

significant, we can estimate the model again with using more lags until we meet, a non significant

lagged regressor. The augmented version of Taylor rule is given below as equation (2).

2.1.1.5. Forward Looking Models and Generalized Method of Moments:

As John Maynard Keynes (1923) once said that we might have been too late if we would

have waited until a price movement was actually very close before taking some measurements. This

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words reflect the importance of the forward-looking models in monetary policy. When private

economic actors change their economic behavior in a particular economic subject some variables

such as long-term interest rates may be changed. According to Kamada and Muto (2000) this

mechanism of expectation formation is generally called as rational expectations models while the

models that integrated with such expectations regardless current and past information are called as

forward looking models. Mavroeidis (2004) points out that since they based on micro-foundations

and built on rational expectations, generalized method of moments (GMM) methods have become

popular for estimating forward-looking models.

The third step of the econometric analysis will be estimating our model by GMM. This is ageneral estimation method which is derived from the method of moment. It is developed by Lars

Peter Hansen in 1982. Many other estimators can be considered as special cases of generalized

method of moments. It can allow economic models to be specified without making unwanted

assumptions. It is consistent and asymptotically normal. In order to produce estimates of the

unknown parameters of the model it combines observed data with the information extracted from

orthogonality conditions. Hansen (2007) also points out that it can be used when maximumlikelihood estimation is not applicable and the parameter of interest is finite-dimensional. Its

properties of taking account of both sampling and estimation error and being constructed without

specifying the full data generating process made generalized method of moments a widely used

estimator.2.1.2. Estimation of the Taylor Rule:

The main purpose of this exercise is to test whether the stock market movements play a

crucial role in shaping monetary policy either directly or indirectly.

2.1.2.1. Graphical Inspection of the Data:

The below figure depicts the movements in interest rate between the years of 1997 and

2012.During this period interest rate decreased significantly.It remained stable with slight changes

between 2005 and 2009 and continued to incline afterward. From the second half of the 1997 to

2012 it dropped almost 60%. Figure 2.

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10

20

30

40

50

60

70

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

IR

The below figure depicts the movements in GDP quarterly between the years of 1997 and

2012.During this period, GDP of Turkey increased significantly and reached almost 1.500 Billion

Turkish Lira annually by 2012.During the period, it negatively correlated with the interest rate.

Figure 3.

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

GDP

The below figure depicts the movements in inflation between the years of 1997 and

2012.During this period inflation decreased significantly excluding the year of 2001.In 1997 the

beginning year of the analysis it was 85%. From 2004 inflation dropped to single numbers. In 2012

inflation rate moved on below the interest rate to the number of 6.16%.

Figure 4.

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0

10

20

30

40

50

60

70

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

INFLATION

The below figure depicts the movements in BIST100 between the years of 1997 and 2012.

During this period, BIST100 increased significantly excluding the period of 2008-2009 and

negatively correlated with the interest rate. During the year of 2012, it rose almost 60% and reached

the 80.000 index level while it was only at 1.613 index level at 1997.

Figure 5.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

BIST100

2.1.2.2. Standart Taylor Rule with Ordinary Least-Squares Method :

After we plug in all the variables in to the equation now we can estimate our standard Taylor

rule by employing the Ordinary least-squares estimator. Hutcheson (2011) claims that ordinary

least-squares (OLS) method is a very useful tool if we have a single response variable to model thathas been recorded on at least an interval scale.

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Under the assumptions of no perfect multicollinearity and homoscedastic and serially

uncorrelated errors, the OLS estimator will be consistent when the regressors are exogenous.

Dependent Variable: ITMethod: Least SquaresSample (adjusted): 1998Q1-2012Q3Included observations: 59 after adjustmentsVariable Coefficient Std. Error t-Statistic Prob.C 2.933112 0.060857 48.19687 0.0000INFLATION 0.024756 0.002187 11.32129 0.0000

OUTPUT_GAP -0.000779 0.005033 -0.154783 0.8775R-squared 0.729526 Mean dependent var 3.495158Adjusted R-squared 0.719866 S.D. dependent var 0.556525S.E. of regression 0.294556 Akaike info criterion 0.442814Sum squared resid 4.858740 Schwarz criterion 0.548451Log likelihood -10.06301 Hannan-Quinn criter. 0.484050F-statistic 75.52180 Durbin-Watson stat 0.146077Prob(F-statistic) 0.000000

According to the table above the coefficient associated to the inflation rate is significant

and impacted the interest rate positively while the coefficient associated to output_gap is

insignificant and impacted the interest rate negatively. The model can explain 73% of total

variability of interest rate based on R-squared and 72% of adjusted R-squared. An increase of 1%

in the inflation rate leads to a 0.024% increase in the interest rate while an unitary increase in the

output gap decreases the interest rate by -0.000779%. In the model, the constant is positive and

indicates that when the output_gap and inflation are zero, the stabilizing interest rate would be at

the rate of 2.933112.The probability of F-statistic is zero which is a value that support the

correctness of the model and shows that our regressors are jointly different from

zero.According to this argument the null hypothesis can be rejected.The final conclusion of the

OLS test points out that there might be a serial correlation problem in the model since the DW

statistic is more than 10%.

2.1.2.3. The Wald Test:

Engle (1984) points out that in order to test the aforementioned restriction, we need to set a

Wald test which is based upon Walds elegant analysis upon asymptotic approximation to the T and

F tests in econometrics.

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According to Taylor (1993) output gap and the inflation own an equal weight in shaping

monetary policy.In order to do that both second and third coefficient should be set equal to 50%

The Central Banks that adopts a more severe inflation targeting policy should put more weight on

inflation compared to the output gap.According to that argument when we set the restriction as all

the coefficients are equal to 50%.The variations in the dependent variable can not be explained by

the independent variables.

Wald Test:Equation: Untitled

Test Statistic Value df ProbabilityF-statistic 44354.99 (2, 56) 0.0000Chi-square 88709.98 2 0.0000

According to the table above the p-values associated to the F-test and Chi-square are equal

to 0.00. Since it is less than 10% we can reject the null hypothesis that claims output gap and the

inflation own an equal weight in shaping monetary policy.Therefore, we may conclude that all the

regressors are jointly significant and inflation and output gap weight differently in shaping

monetary policy.

2.1.2.4.Visual Impression Regarding the Model:

The below graph gives us a visual representation of the estimation and shows how it

performs in predicting the variability of the dependent variable.

-.6

-.4

-.2

.0

.2

.4

.6

2.5

3.0

3.5

4.0

4.5

5.0

98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

Residual Actual Fitted

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The above model consistently underestimates the actual interest rate from 1998 to 2009

while it overestimates it from 2009 onwards. Since the residual do not seem to be i.i.d. , we can

conclude the regression model misses something.

2.1.2.5.Chow Breakpoint Test:

On the basis of the visual representation of the estimation, a possibility of omitted variables

problem may rise. At this point of the study, the presence of some shocks that can affect the

stability of the relationship under investigation will be checked by chow breakpoint test.

At the below three test, all probability values are smaller than 10%. That means we can

reject the null hypothesis that there is no break at 2001Q1.Thus, we refer that there is a structural

break in the relationship, which is found in the estimation, at 2001Q1.As it will be explained

very briefly in the following paragraph the issues which caused the structural break at 2001 were

triggered by a political debate and rapidly turned to a financial crisis.

Chow Breakpoint Test: 2001Q1Null Hypothesis: No break at specified breakpointVarying regressors: All equation variables

Equation Sample: 1998Q1- 2012Q3F-statistic 3.337075 Prob. F(3,53) 0.0261Log likelihood ratio 10.20824 Prob. Chi-Square(3) 0.0169Wald Statistic 10.01122 Prob. Chi-Square(3) 0.0185

Ozatay and Sak (2002) describe how 2001-2002 financial crisis started in Turkey as it is

given at the following part.On the 19th of February, , the prime minister declared that there was

political conflict between him and the President soon after he left the National Security Councilmeeting.After this announcement the over-night rate increased to 2058% on the following day

and 4019% on the 21th of February.The banking sector rushed to foreign currency. Since the US

markets were closed at that specific date, the Central Bank could not satisfy the foreign currency

demand of the banking sector.After the announcement about the country was switching to a

freely floating exchange rate system the dollar rate jumped almost 40%.

2.1.2.6.Estimating The Augmented Taylor Rule:

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As we mentioned before on chapter 2.1.1.4. according to Castro (2008) a financial

conditions index containing data from the stock market movements can be included in the standard

Taylor rule to have an augmented version of it by including in equation the variable s which

measures the stock market value.The augmented version of Taylor rule (ATR) is given below as

equation (2).

2.1.2.6.1.Ordinary Least-Squares Analysis (ATR):

In order to explain the variability of dependent variable better we included the stock market

value in the model.At the table given below the coefficient associated to s(-1) which represents the

stock market value is negative and insignificant.It can also be observed from the table that the

goodness of fit of the model increased very slightly after we include the first lag of s.When we

look at the R-squared, we can see it increased from 0.729 to 0.735 while adjusted R-squared

increased from 0.719 to 0.720, which shows that our model can explain a little bit better the

variability of the dependent variable.Including the stock market value did not contribute to the

model to explain the relations between interest rate and stock market value.

Dependent Variable: ITMethod: Least SquaresSample (adjusted): 1998Q2 -2012Q3

Included observations: 58 after adjustmentsVariable Coefficient Std. Error t-Statistic Prob.

C 2.924457 0.062285 46.95252 0.0000INFLATION 0.025980 0.002293 11.32999 0.0000

OUTPUT_GAP -0.000396 0.005046 -0.078574 0.9377S(-1) -0.000506 0.000849 -0.595461 0.5540

R-squared 0.735205 Mean dependent var 3.482925Adjusted R-squared 0.720494 S.D. dependent var 0.553326S.E. of regression 0.292534 Akaike info criterion 0.446001Sum squared resid 4.621117 Schwarz criterion 0.588101Log likelihood -8.934043 Hannan-Quinn criter. 0.501352F-statistic 49.97701 Durbin-Watson stat 0.148557Prob(F-statistic) 0.000000

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2.1.2.6.2. Diagnostic- Normality Test:

In order to check whether them odel is suffering from heteroskedasticity and serial

correlation we should carry out some tests to check our model.

0

1

2

3

4

5

6

-0.4 -0.2 0.0 0.2 0.4

Series: ResidualsSample 1998Q3 2012Q3Observations 57

Mean 3.17e-16Median 0.003373Maximum 0.529819Minimum -0.462369Std. Dev. 0.279457Skewness 0.113068Kurtosis 2.172355

Jarque-Bera 1.748319Probability 0.417213

According to the above table of Jarque Bera test hypothesis of normality in the distribution

of the residuals can not be rejected since the Jarque Bera probability value is insignificant.

2.1.2.6.3. Diagnostic- Heteroskedasticity Test:

In order to determine the heteroscedasticity in the model , we need to analyse both F-statistic

and Chi-square results.

Heteroskedasticity Test: WhiteF-statistic 1.227908 Prob. F(14,42) 0.2923Obs*R-squared 16.55446 Prob. Chi-Square(14) 0.2807Scaled explained SS 8.076087 Prob. Chi-Square(14) 0.8853

At the table given above the probability value of Chi-square and F-statistic are bigger than

10%.Under these circumstances, the null hypothesis of homoskedasticity can not be rejected.

Therefore, the residuals are homoskedastic.

2.1.2.6.4. Diagnostic- Breusch-Godfrey Serial Correlation LM Test:

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On the other hand, the below table shows that probability value of both test statistic is 0.000.

So now we can reject the null hypothesis clearly and reach the conclusion of our model is suffering

from serial correlation problem.

Breusch-Godfrey Serial Correlation LM Test:F-statistic 253.3161 Prob. F(1,51) 0.0000Obs*R-squared 47.44743 Prob. Chi-Square(1) 0.0000

2.1.2.6.5. Ordinary Least Squares Method (Newey-West Option):

Since the model is suffering from serial correlation problem we should re-estimate our

model.In order to do that we will employ the Newey-West standard to the model.

Dependent Variable: ITMethod: Least SquaresSample (adjusted): 1998Q2 2012Q3

Included observations: 58 after adjustmentsHAC standard errors & covariance (Bartlett kernel, Newey-West fixed

bandwidth = 4.0000)Variable Coefficient Std. Error t-Statistic Prob.

C 2.924457 0.119247 24.52436 0.0000INFLATION 0.025980 0.003244 8.008201 0.0000

OUTPUT_GAP -0.000396 0.004555 -0.087032 0.9310S(-1) -0.000506 0.001008 -0.501905 0.6178

R-squared 0.735205 Mean dependent var 3.482925

Adjusted R-squared 0.720494 S.D. dependent var 0.553326S.E. of regression 0.292534 Akaike info criterion 0.446001Sum squared resid 4.621117 Schwarz criterion 0.588101Log likelihood -8.934043 Hannan-Quinn criter. 0.501352F-statistic 49.97701 Durbin-Watson stat 0.148557Prob(F-statistic) 0.000000

In order to correct the estimation, the Newey-West standard errors were employed to the

model.At the table, the results of this correction can be seen. Under the projection of new results,

both stock market value and output_gap are negative and insignificant.

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Based on our previous results there would be another fact that the fluctuations in the stock

market affect the decisions of Central Bank indirectly. According to the below tables it may also be

argued that the asset price volatility may affect both the output gap and the inflation rate.

Dependent Variable: INFLATIONMethod: Least SquaresSample (adjusted): 1998Q2 - 2012Q4Included observations: 59 after adjustmentsHAC standard errors & covariance (Bartlett kernel, Newey-West fixed


C 0.333998 0.495057 0.674665 0.5027

INFLATION(-1) 0.953567 0.039631 24.06104 0.0000OUTPUT_GAP(-1) -0.056344 0.088231 -0.638601 0.5257

S(-1) -0.011326 0.016846 -0.672348 0.5042R-squared 0.966615 Mean dependent var 21.69211Adjusted R-squared 0.964794 S.D. dependent var 18.41917Sum squared resid 656.9231 Schwarz criterion 5.524350Log likelihood -154.8132 Hannan-Quinn criter. 5.438482F-statistic 530.8215 Durbin-Watson stat 1.338431Prob(F-statistic) 0.000000

At the above table inflation is added to the model as a dependent variable.The results show

that the probability value of the stock market index is negative and insignificant. On the other hand

at the below table output_gap is added to the model as a dependent variable and the results show

that the probability value of the stock market index is positive but still insignificant.

Dependent Variable: OUTPUT_GAP

Method: Least SquaresSample (adjusted): 1998Q2 - 2012Q3Included observations: 58 after adjustmentsHAC standard errors & covariance (Bartlett kernel, Newey-West fixed


C -2.272452 1.220084 -1.862538 0.0680INFLATION(-1) 0.126676 0.042023 3.014455 0.0039

OUTPUT_GAP(-1) 0.162174 0.059430 2.728819 0.0086S(-1) 0.021235 0.024834 0.855083 0.3963

R-squared 0.184590 Mean dependent var 1.347184

Adjusted R-squared 0.139289 S.D. dependent var 8.396291S.E. of regression 7.789617 Akaike info criterion 7.009932Sum squared resid 3276.619 Schwarz criterion 7.152032

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Log likelihood -199.2880 Hannan-Quinn criter. 7.065283F-statistic 4.074781 Durbin-Watson stat 1.772091

Prob(F-statistic) 0.011100

According to the two tables given above the policy rule of Turkish Central Bank (interest

rate) was not affected from the stock market volatility indirectly.

2.1.2.6.6. Generalized Method of Moments(GMM) Estimator:

If we want to check whether policy rule of Turkish Central Bank was affected directly or it

responds to stock market movements only in so far it uses those movements as an indicator for

inflation and output gap forecasts. Therefore, it might be more appropriate to estimate the model

using a GMM estimator:

Dependent Variable: IT

Method: Generalized Method of MomentsSample (adjusted): 1998Q4 - 2012Q3Included observations: 56 after adjustmentsLinear estimation with 1 weight updateEstimation weighting matrix: HAC (Bartlett kernel, Newey-West fixedbandwidth = 4.0000)Standard errors & covariance computed using estimation weightingmatrixInstrument specification: INFLATION(-1) INFLATION(-2)OUTPUT_GAP(-1) OUTPUT_GAP(-2) S(-2) S(-3)

Constant added to instrument listVariable Coefficient Std. Error t-Statistic Prob.

C 2.844306 0.116867 24.33799 0.0000INFLATION 0.028807 0.003244 8.878953 0.0000

OUTPUT_GAP -0.003732 0.003913 -0.953739 0.3446S(-1) -0.000697 0.001029 -0.677083 0.5014

R-squared 0.720439 Mean dependent var 3.457147Adjusted R-squared 0.704311 S.D. dependent var 0.545603S.E. of regression 0.296684 Sum squared resid 4.577116Durbin-Watson stat 0.170815 J-statistic 4.848948Instrument rank 7 Prob(J-statistic) 0.183198

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According to the above table the probability associated with the J-statistic strongly supports

the choice of the instruments. The output_gap is not statistically significant as inflation is the only

significant variable in the equation. The coefficient associated with s(-1) is negative and statistically

insignificant. This GMM analysis also shows that there is not any empirical evidence that the

market volatility in BIST100 affects the interest rate directly.

3.CONCLUSION:

This dissertation has investigated whether the stock market movements play a crucial role inshaping monetary policy either directly or indirectly in Turkey.In the investigation, we adopted the

Taylor rule as the empirical framework and used its standard and augmented versions in order to

reach a conclusion. Right from the beginning at every stage of the investigation all the tests results

we obtained show that the stock market movements do not play a crucial role in shaping monetary

policy neither directly nor indirectly in Turkey.

As we mentioned before at previous chapters of our investigation Turkish economy showed anoutstanding performance between the years of 1997 and 2012.During the period, the inflation rate

dropped to %6.16 from %85 and parallel to the inflation rate interest rate dropped almost %60

while GDP rose almost %4 annually in average. Additionally BIST100, the stock market value of

Turkey rose almost 60% in 2012 and reached the 80.000 index level while it was only at 1.613

index level at 1997.

All those macro economic data of Turkey given above and our test results together show that

during our investigation period, Turkish Central Banks policy rule was to achieve and maintain

price stability which is also its primary objective that was given by the law.The Central Bank of

Turkey aimed to achieve and maintain price stability at the first place while it was also

supporting a sustainable growth and increased employment instead of supporting the stock

market. At the end of the investigation, we can claim that there is not any empirical evidence

that supports the hypothesis of the stock market movements play a crucial role in shaping

monetary policy directly or indirectly in Turkey.

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