This presentation summarizes a thesis that examines the role of stock prices in Pakistan's monetary policy transmission mechanism. The presentation outlines the introduction, research hypothesis, literature review, data and methodology, econometric model, and planned results and discussion sections. The introduction discusses monetary policy, transmission mechanisms, and the relevance of stock prices through Tobin's q theory and wealth effects. The literature review covers studies on monetary policy and macroeconomic variables, stock prices as an asset price channel, and stock markets as a sole transmission channel. Vector autoregression and structural vector autoregression models are proposed to analyze quarterly data from 1991 to 2010 on monetary policy instruments, stock prices, output, inflation and other variables.

2. MS Thesis Presentation
Monetary Policy Transmission Mechanism:
Role of Stock Prices
Muhammad Ilyas Siddiqui
321-SE/MS Eco/S13
Supervised By
Dr. Arshad Ali Bhatti
Assistant Professor, IIIE
International Institute of Islamic Economics
IIU, Islamabad
January 7, 2016

3. Presentation Plan
 Introduction
 Why this study?
 Research Hypothesis
 Literature Review
 Data and Methodology
 Econometric Model
 Results and Discussions

4. Introduction
• Monetary policy is one of the two major policies (other being Fiscal policy),
the Government uses to control the economy.
• Monetary policy refers to any action taken by the Central bank, on behalf of
the Government, to influence either the supply of money or the price of
money, as given by the rate of interest (Moynihan and Titley, 2007)
• Monetary policy transmission mechanism (MTM) explains the channels or
paths through which changes in interest rate are transmitted into real
economy.
MTM channels:
• Interest Rate Channel: It is core of Keynesian theory and works through
changes in real interest rate as cost of capital.
• Exchange Rate Channel: It works in face of flexible exchange rate through
change in relative currencies value.
• Credit Channel: It exits due to credit market imperfections and product of two
sub-channels that is bank lending channel and balance sheet channel.

5. Introduction….
• MTM channels….
• Other Asset Prices Channel: It works through effect of monetary policy on relative asset prices
and real wealth.
• Expectation Channel: This channel works through the psychology of economic agents.
Monetary policy actions may have an effect on the economy through their impact on the
confidence and expectations of economic agents about the future outlook of the economy
(Dabla-Norris and Floerkemeier, 2006).
• Relevance of Stock Prices
• Tobin’s q theory. Tobin (1969) defines q as the market value of firms divided by the replacement
costs of capital at going rates. At a high value of q, it is favorable for firms to issue new stock
rather to purchase new plant and equipment which implies that investment is more likely.
• Keynesian theory. According to Keynesian economist, rise in interest rates make bonds more
attractive for investors hence, they switch over from stock market to bond market. This situation
induces reduction in equity prices. Therefore, lower equity prices causes a lower q which in
turn, leads to lower investment spending resulting in reduced output.
• Wealth effects on consumption when equity prices come down as a result of contractionary
monetary policy, the value of real wealth with people decreases. They feel less rich and
withdraw consumption spending. This affects aggregate demand adversely. Ultimately,
aggregate output fall (Modigliani ,1971).

6. Introduction….
• Relevance of Stock Prices
• Tobin’s q theory. Tobin (1969) defines q as the market value of firms divided by the
replacement costs of capital at going rates. At a high value of q, it is favorable for firms
to issue new stock rather to purchase new plant and equipment which implies that
investment is more likely.
• Keynesian theory. rise in interest rates make bonds more attractive for investors hence,
they switch over from stock market to bond market. This situation induces reduction in
equity prices. Therefore, lower equity prices causes a lower q which in turn, leads to
lower investment spending resulting in reduced output.
• Wealth effects on consumption when equity prices come down as a result of
contractionary monetary policy, the value of real wealth with people decreases. They
feel less rich and withdraw consumption spending. This affects aggregate demand
adversely. Ultimately, aggregate output fall (Modigliani ,1971).
• Monetary Policy and Stock Prices; Nature of Relationship
• Negative- a positive shock in money supply will lead people to expect a contractionary
monetary policy (Habibullah et. al., 1996; Sack, 2001).
• Positive- money supply increases in response of higher money demand that is due the
enhanced economic activity (Sellin, 2001; Alatiki and Fazel, 2008).
• Depended- In case the investors anticipate fully the expansionary monetary policy, the
stock market will not react; however, the stock price will increase if the shock is
unexpected (Olivier Blanchard, 2011).

7. Why this study?
• There is limited empirical literature that focuses on the MTM in Pakistan.
• The empirical literature on stock prices as one of MTM channels is even
much scarce.
• We do not find any empirical study which examines the role of stock
prices as a separate MTM channel in Pakistan.
• To fill the literature gap, we analyze the impacts of monetary policy on
output and inflation through stock prices.

8. Literature Review
• There are three strands in the literature.
• The first strand asses relation between monetary policy and
other macroeconomic variables and discusses their mutual
relationships. It covers a large space (Ando and Modigliani, 1963;
Baumol, 1965; Bosworth, 1975; Ahmed, 1999; Hussain and
Mahmood, 2001; Nishat and Shaheen, 2004).
• The second strand gives analyzes stock prices as one of the
channels of the MTM along with other asset price channels.
Concerning studies are less in number (Mishkin, 1996, 2001;
Agha, 2005; Aqeel, 2011).
• The third strand concentrates on stock market as an only
transmitting channel of monetary policy. Such studies are very
few throughout the economic literature. (Chami, 1999; Sourial,
2002; Ehrmann and Fratzcher, 2004 and Seong, 2013).

9. Literature Review
• The major studies in first category are :
• Thorbecke (1997); Filer (1999); Sack (2001); Shahbaz and Ahmed (2008);
Foresti (2006); Mahmood (2001); Ajit Singh (2008); Saleem et. al. (2013);
 These studies analyze the interrelationships between monetary policy,
stock prices and economic growth.
 Most of the studies use M1, M2, money market rates, Repo rate , six
month treasury bills, USA Federal Fund rate, GDP, KSE-100, exchange
rate, CPI, IPI as indicators.
 Major techniques used are OLS regression, ECM, Granger causality and
vector auto regression.
 Findings do not endorse single result. All types of relationships- positive,
negative, significant, insignificant, unidirectional, bidirectional.

10. Literature Review
• Important studies in the second category are:
• Mishkin (2001); Sack (2002); Agha (2005); Baig (2011);
•
• Important studies in the third category are:
• Chami et. al. (1999); Sourial (2002); Seong (2013); Ehrmann and Fratzscher
(2004)

11. Data and Methodology
• We use quarterly data from 1991:Q1 to 2010: Q2
• 1-Policy (independent) variables: They are the basic instruments through which monetary policy
works.
• Narrow Money (M1)
• Short Run (Interbank) Money Market Rate (MMR)
• 2-Intermediate (target) variables: By using these variables monetary policy hit the target variables.
• Nominal Exchange Rate (EXR)
• Private Sector Credit (PSC)
• Stock Market Index, KSE-100 (SMI)
• 3-Target (dependent) variables: They are the ultimate target of monetary policy and among the
macroeconomic variables through which economy is controlled.
• Real Gross Domestic Product (GDB)
• Consumer Price Index (CPI)
• 4-Exogenous block: These variables represent the shock originating in the external world.
• World (IMF) Commodity Prices (COMP)
• Federal Fund Rate (FFR)

12. Estimation Methodology
• Following the literature, we utilize vector auto regression (VAR) as
estimation technique.
• Since the work of Sims (1980), VAR models are common in estimation of
MTM
• They can summarize the dynamic relationships among variables (Bernanke
and Gertler, 1995)
• They are appropriate both for advanced and emerging countries as they
can generate multivariate forecasts and their data requirements are less
demanding.
• Problems of large-scale econometric models can be avoided with VAR.
•

13. Estimation Methodology
• Second Stage of Estimation
• A structural VAR (SVAR) is estimated for Pakistan at the second stage to
confirm the results of base line VAR model.
• SVAR is important:
• 1- to identify a monetary policy shock based on economic theory.
• 2- give allowance of imposing enough restrictions to identify an
exogenous policy shock, without having to specify complete or large-scale
models of the economy.
• 3- it takes into consideration money aggregates and short run interest
rate jointly and help to identify monetary policy shocks appropriately.
• 4- it is considered suitable for small open economies such as Pakistan.
• 5- it takes no account of the properties of time series data. (Perera, 2013).

14. Econometric Model
Following Perera and Wickramanayake (2013), we use VAR in two stages.
First Stage of Estimation
The unrestricted - baseline VAR model based on assumption that system is recursive and therefore
Cholesky decomposition can be employed for identification. We can specify our baseline model in
following matrix form
yt = k + A(L)yt-1 + Bxt + ut (4.1)
where yt = vector of endogenous variables
k = vector of constants
xt = vector of exogenous variables
ut = vector of serially uncorrelated disturbances ( zero mean and a time invariant covariance
matrix)
A(L) = coefficient matrix (a matrix polynomial in the lag operator)
In the baseline specification, the vector of endogenous variables such as real gross domestic product
(GDPt) and the consumer price index (CPIt).
The measure of monetary aggregate that is narrow money supply (M1t) and the domestic nominal
short-term interest rate given by interbank money market rate (MMRt). We write it as follows:
y,
t = (GDPt CPIt M1t MMRt) (4.2)

15. Econometric Model
The general form of structural VAR model of order p is as follows:
Aoyt = co +∑p
i=1 Aiyt-1 + εt (4.3)
yt = 7*1vector of endogenous variables
yt = (COMPIt, FFDRt, GDPt, CPIt, M1t, MMRt, SMIt)
Ao = 7*7 contemporaneous matrix
Ai = 7*7 autoregressive coefficient matrices
εt = 7*1 vector of structural disturbances assumed to have zero covariance.
multiplying both sides of (4.3) with A-1
o to get the reduced form as:
yt = ao + ∑p
i=1 Bi yt-I + et
Where ao = A-1
o co Bi = A-1
o Ai et = A-1
o εt (εt = Ao et)
We can derive structural disturbances by imposing appropriate restrictions on Ao

16. Components
VD of
GDP
Time Period VD of
CPI
MMR (baseline) 0.210728
1.378362
3.124916
5.113285
Q4
Q8
Q12
Q16
0.168485
2.810061
4.561628
4.239366
M1 (baseline) 5.842879
9.610432
12.77320
15.29505
Q4
Q8
Q12
Q16
0.236158
3.194236
10.83325
20.41191
SMI (stock market channel) 3.750656
5.686760
7.136972
8.245667
Q4
Q8
Q12
Q16
1.564091
0.986778
2.220572
6.091740
MMR (stock market channel) 0.227681
1.291607
3.065665
5.210945
Q4
Q8
Q12
Q16
0.126579
2.506933
4.535215
4.337248
M1 (stock market channel) 3.506075
4.75628
5.915295
6.958337
Q4
Q8
Q12
Q16
0.382503
0.382503
2.323669
4.749184
SMI (all channel endogenous) 2.882958
4.383710
5.801023
7.069753
Q4
Q8
Q12
Q16
1.876468
1.295246
5.727449
13.90800
Table 5.3: Variance decomposition (VD) of GDP and CPI - Baseline Model versus SM channel

17. Components
VD of
GDP
Time Period VD of
CPI
EXR ( exchange rate channel) 0.419714
1.039137
1.361452
1.479931
Q4
Q8
Q12
Q16
4.182306
18.13292
28.89163
33.82420
MMR ( exchange rate channel) 0.608441
1.740702
3.052492
4.430022
Q4
Q8
Q12
Q16
0.613067
0.446562
0.325828
0.428118
M1 ( exchange rate channel) 5.858769
5.858769
13.46811
16.40583
Q4
Q8
Q12
Q16
0.312333
3.159039
11.10071
20.36989
PSC (bank lending channel) 19.18298
19.25027
18.97339
18.46213
Q4
Q8
Q12
Q16
0.281123
0.352633
1.470962
4.030985
MMR (bank lending channel) 0.579082
1.745838
3.642293
6.079923
Q4
Q8
Q12
Q16
0.224509
2.571515
3.857057
3.564473
M1 (bank lending channel) 8.299370
9.652282
11.36304
12.94446
Q4
Q8
Q12
Q16
0.286655
4.649080
11.27792
18.13594
Table 5.4: Variance decomposition (VD) of GDP and CPI - EXR and PSC channels

18. Components VD of GDP Time Period VD of CPI
SMI (SVAR) 0.533167
2.463111
3.506124
4.073808
Q4
Q8
Q12
Q16
0.402664
0.664915
1.828915
5.235307
PSC (SVAR) 20.39558
18.98588
17.80314
16.72251
Q4
Q8
Q12
Q16
0.548890
0.246428
0.217958
0.197210
EXR (SVAR) 0.748846
1.335725
1.592848
1.724218
Q4
Q8
Q12
Q16
3.117706
10.41930
17.89436
21.60731
Table 5.5: Variance decomposition (VD) of GDP and CPI – SVAR models

19. Conclusion
 Both baseline unrestricted VAR and structural VAR confirm the significance
and potency of monetary policy in Pakistan during the research period.
 Our estimation results show that Stock market channel is the least effective.
Also it does not bear any Granger causality toward any variable. This is in
accordance with Sourial, 2002, who declared it as a future channel.
 The overall findings of the study suggest that, the stock market as an
MTM channel is observed as an active channel only when working in
collaboration with other channels; it has significant impact on prices in long
run. This is more likely due to strong correlation between output and SMI
 In response of tight monetary policy, the aggregate price levels responds
significantly in first six quarters and then dissipate and keep on rising for the
rest of (4 quarters) period. Output shows V- shaped response, bottoming
out after third quarter and then keeps on declining for rest of (7 quarters)
period.

20. Conclusion
 Exchange rate channel is the most significant channel in
Pakistan. Both in VAR and SVAR, it has bi-directional
causality with inflation. Also it has uni- directional causal
relationship with interest rate in both VAR and SVAR
 The second most significant candidate is bank lending
channel. It has bi-directional causality with output and
un-directional with inflation
 the findings about stock market channel call for caution
because the share ownership is not still very common in
Pakistan rather firms prefer bank credit on equity
sharing for their financing needs (Agha, 2005).

21. Policy Implications
 Stock market channel needs more attention. As in collaboration with other two channels,
stock market gave much better results which is signal for policy makers to understand the
situation.
 The stock markets of Pakistan have been very sensitive to political upheavals and law and
order situations in Pakistan. Fortunately, both these factors are in process of substantial
improvement in Pakistan due to military operations. Therefore, it has now become easier for
policy maker to exploit fully the stock market channel in Pakistan.
 Exchange rate channel can be focused for further improvement in Pakistan economic
conditions. The liberal exchange rate regime is already in operation and volume of remittances
has increasingly improved. Both these aspects have strengthened the exchange rate channel in
Pakistan.
 Further reforms in baking system are needed to enhance the performance of bank lending
channel. Past history of Pakistan witness that the process of reformation in banking system has
boosted the economy.

22. Data Sources
• Monthly reports and bulletins of State Bank of Pakistan,
especially working paper no. 54, 2013.
• Websites of International Financial Statistics (IFS)
• Publications of Karachi Stock Exchange (KSE)
• Various data sources of International Monetary Fund (IMF)
• Pakistan Economic Survey (Different Issues). Ministry of
Finance, Government of Pakistan.